latest research on schizophrenia

Potential schizophrenia treatment, discovered at Vanderbilt and being developed by Neumora Therapeutics, entering Phase 1 clinical trial 

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A potential schizophrenia treatment discovered through the Warren Center for Neuroscience Drug Discovery has been cleared by the U.S. Food and Drug Administration for use in phase 1 clinical trials—the third WCNDD therapeutic to reach that benchmark.  

“Vanderbilt is proud that a discovery by our researchers at the Warren Center is now a significant step closer to helping improve the lives of people with schizophrenia,” Chancellor Daniel Diermeier said. “Our work with Neumora is the very definition of translational research and the work we aim to do every day, which is applying innovation and discovery to help address the world’s most complex challenges.”   

The clinical trial has been initiated by Neumora Therapeutics Inc. , a clinical-stage biopharmaceutical company founded to confront the global brain disease crisis by taking a fundamentally different approach to the way treatments are developed. Vanderbilt and Neumora signed an exclusive, worldwide license and a research collaboration agreement for two novel series of M4 receptor modulator compounds, including NMRA-266, in February 2022.  

Vanderbilt’s agreement with Neumora was centered around the M 4 muscarinic receptor, which NMRA-266 targets through positive allosteric modulation. In preclinical studies conducted by Conn and Lindsley, NMRA-266 was found to be highly selective to the M 4 receptor, the area of the brain that regulates neurotransmission of dopamine. Overactive transmission of dopamine is connected to the positive, negative and cognitive symptoms of schizophrenia.   

“The M 4 PAM story has been a Homer-style Odyssey to get to this point and represents almost 20 years of research funded by National Institutes of Health, the William K. Warren Foundation and pharmaceutical companies,” said Lindsley, also a University Professor of pharmacology, biochemistry and chemistry who holds the William K. Warren, Jr. Chair in Medicine. “This mechanism and NMRA-266 represent a potential game-changer for schizophrenic patients and their families. Moreover, this success is a testament to the virtue of academic drug discovery and Vanderbilt’s commitment to supporting the WCNDD, a clinical-stage biotech enterprise within the university.”  

For the WCNDD to have such regular production of clinical assets when up against diverse neuroscience pipeline is unprecedented among academic drug discovery centers, according to Lindsley.  

“NMRA-266 entering phase 1 trials highlights the complementary relationship between university researchers and industry partners,” said Vice Provost for Research and Innovation Padma Raghavan. “By pairing our faculty’s ingenuity with the private sector’s commercialization know-how, we are able to bring life-changing discoveries to patients in need faster.”  

Schizophrenia spectrum disorders affect 3.7 million U.S. adults, a figure up to three times higher than previously understood, according to a recent study . This fundamentally different mechanism that NMRA-266 acts through is very selective for brain circuits involved in schizophrenia, which means in is unlikely to have the adverse effects of current dopamine antagonists—resulting in an improved standard of care for people with schizophrenia.  

“The initiation of this phase 1 study is an important step in the development of NMRA-266. In pre-clinical studies NMRA-266 demonstrated a favorable pharmacologic profile that includes high potency and selectivity for the M 4  receptor subtype, meriting its advancement into the clinic,” Dr. Robert Lenz, executive vice president and head of research and development at Neumora, said in a  release . “With its pre-clinical profile and clinical validation of the M 4  muscarinic receptor class in treating schizophrenia, we believe that NMRA-266 has strong potential as a treatment for neuropsychiatric disorders.”  

Human clinical trials are a significant advancement in a five-step  drug development process . Drug discovery research begins in the lab and is followed by preclinical research to answer basic questions about safety. Then there is clinical research to ensure that the treatment is safe and effective. The FDA then reviews all submitted data. If approved, the therapeutic will be made available for use by the public and be monitored for safety by the FDA for as long as it is available.  

The Vanderbilt-Neumora collaboration was facilitated by the   Center for Technology Transfer and Commercialization . Vanderbilt researchers who contributed to research around NMRA-266 and the power of academic drug discovery include Darren W. Engers , Aaron Bender ,  Olivier Boutaud ,  Thomas Bridges , Julie Engers ,  Alison Gregro , Carrie Jones ,  Colleen Niswender ,  Jerri Rook and Kayla Temple .  

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A new approach for treating schizophrenia

A potential new treatment for schizophrenia – backed by Wellcome-funded research – may change the lives of millions of people living with the condition globally.

VladSt via Getty Images

Lynsey Bilsland

Head of Mental Health Translation

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Schizophrenia is a severe, long-term mental health condition that affects around 1 in 300 people worldwide. Symptoms include hallucinations, delusions, muddled thoughts, loss of interest in everyday activities and social withdrawal.

While there are different treatment options available, antipsychotic drugs are commonly used to treat the condition, however they don’t work for everyone.

Now, a United States-based biotech organisation called Karuna Therapeutics Inc. has developed a new combination drug called KarXT . It is the first potential new pharmacological approach for treating schizophrenia in over 50 years and may provide an alternative option for people living with the condition.

The science behind the new schizophrenia treatment  

KarXT is a combination therapy meaning it combines two different drugs, xanomeline and trospium chloride, into one treatment.

These drugs target receptors in the brain and body associated with the cholinergic neurotransmitter system – which has a key role in learning and memory, digestion, control of heartbeat, blood pressure, movement and many other functions. There are two types of cholinergic receptors, nicotinic and muscarinic. In KarXT, xanomeline activates muscarinic receptors in the brain, whereas trospium chloride blocks activation of muscarinic receptors in the body.

Xanomeline was originally developed to treat Alzheimer’s disease by US pharmaceutical company, Eli Lilly and Company. While it was shown to improve cognition and some of the behavioural symptoms of Alzheimer’s in trials, including reducing delusions, agitation, and hallucinations, its development was stopped as some people experienced problematic side effects. These side effects were caused by muscarinic receptor activation in the body.

Karuna’s founder, Andrew Miller, anticipated that combining trospium chloride with xanomeline would reduce these side effects and hypothesised this new therapy would reduce psychosis in people living with schizophrenia.

And it worked.

We funded Karuna in 2015 and 2018 to undertake a Phase 1 and then Phase 2 trial of KarXT.

In the Phase 1 trial, KarXT was shown to be safe and well tolerated with a 50% reduction in side effects compared to xanomeline alone in healthy adults. Results from the Phase 2 trial in people with schizophrenia were also positive, and in 2019, Karuna announced that KarXT led to a statistically significant reduction in psychotic symptoms in people living with schizophrenia. Seven years after our initial investment, results from a Phase 3 trial of KarXT in schizophrenia have found the treatment to:

• result in clinically meaningful and statistically significant improvements in symptoms of psychosis, such as delusions and hallucinations, compared to placebo
• improve negative symptoms of schizophrenia, including lack of motivation, social withdrawal, and cognitive impairment, often not impacted by current drugs, and
• not be associated with common problematic side effects of current antipsychotics, such as sleepiness, weight gain and abnormal motor movements.

The difference it will make  

Historically, antipsychotic drug treatments have focused on the neurotransmitter dopamine. They work to block some of the dopamine receptors in the brain, which can lead to problematic side effects. These side effects mean that some people stop taking the medication, causing them to relapse. Moreover, between 20% and 33% of patients don’t respond to dopamine-targeting drugs at all.

The KarXT trial is the first positive Phase 3 trial for an investigational medicine that does not directly rely on dopaminergic or serotonergic pathways in the brain in approximately 70 years. KarXT works in a completely new way and was found to be well tolerated and relieve symptoms of schizophrenia, providing a potential treatment option for people with psychosis – a key priority for our Mental Health team .

Drug development is a lengthy, expensive and risky process. On average, 73.2% of psychiatric drug candidates fail to make it through Phase 2, the stage of clinical development that involves definitive testing of how well the drug works in people with that mental health problem.

Find out how we funded the development of KarXT Show

As a charity, we have to ensure that we’re careful about how we spend our money. Charity law requires us to guarantee that any private benefits arising from our funding are only incidental to the purpose of the project. When we fund research into a new medical product or treatment, we can choose to provide that funding in a way that means a share of the revenue or equity from the commercialisation of the product comes back to Wellcome. Proceeds from that revenue or equity are in turn used to fund more research to solve urgent health challenges. 

If we’re funding a commercial company, we must make sure from the outset that our funding is not subsidising private gain. Decisions to fund projects run by commercial companies are made on the basis that the project will deliver significant public benefit. In these cases, we will often fund their research via loans rather than grants. This sort of funding is known as a programme-related investment. It’s part of our charitable work, not part of our income-generation investment work. 

Because we’re giving this financial support primarily in the interest of advancing health and not as a commercial investment, we’re prepared to take on more financial risk than commercial investors (such as venture capital funders) might. Finding funders and investors prepared to take high financial risks can be tricky in pharmaceutical research, meaning some promising research never gets off the ground. That’s why, for example, we support the AMR Action Fund, which invests in companies developing new antibiotics where success rates have previously been low .

Like any scientific research, there will often be no commercial success and we will not see any return on the money we invested. However, sometimes successful products emerge, and we see a return on our funding. 

Taking into consideration the likelihood of success (and possible returns) from funding Karuna's research, we agreed our funding would be through a convertible loan. 

We loaned approximately US $11.7 million to Karuna over two awards. We converted our loans to equity in the company as it progressed through fundraising rounds. Due to the success of Karuna’s work, the value of that company has increased significantly, and therefore so has the value of Wellcome’s investment. 

Our early high financial-risk investment has the potential impact of a new class of medicine for the 24 million people living with schizophrenia worldwide and the income we received from the shares can be reinvested in new research.

While current therapies for schizophrenia can be effective in managing select positive symptoms, like hallucinations and delusions – they do not address other life-limiting symptom areas. For example, negative symptoms like social withdrawal and cognitive symptoms like memory problems. KarXT has the potential to address all three symptom areas associated with schizophrenia (positive, negative and cognitive).

What’s next for KarXT?  

There are three ongoing trials evaluating the short and long-term effectiveness of KarXT in treating schizophrenia and how safe it is to use over a long period. Following their completion, Karuna aims to file a New Drug Application with the Food and Drug Administration (FDA) for KarXT in schizophrenia in mid-2023.

Karuna is also evaluating KarXT for the treatment of dementia-related psychosis in Alzheimer’s disease and a Phase 3 trial was initiated in August 2022.

It’s really exciting to see what the potential lasting impact of this new breakthrough treatment option will be for schizophrenia, especially for those for whom current drug treatments don’t work. It’s wonderful to be part of Karuna’s success story and to have funded research that may change the lives of millions of people.

We’re funding research to help create transformative change in early intervention for anxiety, depression and psychosis.

There are currently no open funding opportunities for Mental Health. Learn more about the funding we provide .

Lynsey is Head of the Mental Health Translation team at Wellcome, which aims to develop a portfolio of funded projects that enable identification, prediction and intervention early in mental health problems.

Connect with Lynsey :

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December 8, 2021

A potential new approach for the treatment of schizophrenia

by Wendy Bindeman , Vanderbilt University

A new study led by Jeff Conn, Lee E. Limbird Chair in Pharmacology, James Maksymetz, a former graduate student in the Conn laboratory, and other collaborators at the Warren Center for Neuroscience Drug Discovery has identified a protein in the central nervous system, known as mGlu1, as a potential target for novel treatments of schizophrenia.

Schizophrenia, which affects approximately 1 percent of the global population, has been historically difficult to treat. Current clinically approved antipsychotics are effective at reducing "positive symptoms" like hallucinations and delusions in some patients, but they fail to treat "negative symptoms," such as social withdrawal, lack of motivation and cognitive deficits associated with the disease. The new research focused on identifying a new approach that would treat positive and negative symptoms, Maksymetz said.

Schizophrenia is thought to occur when a region of the brain called the prefrontal cortex becomes abnormally active because interneurons, which connect neuron circuits or neuron groups, become dysfunctional and stop regulating neuronal activity. Conn's team sought to modulate the activity of those cells.

After identifying mGlu1—an abbreviation of metabotropic glutamate receptor subtype 1—as a potentially druggable target, they tested it with a compound that enhances its function: a positive allosteric modulator. The PAM was previously developed by Conn in close collaboration with other labs in the WCNDD, including those of Craig Lindsley, University Professor of Chemistry and Pharmacology, and Colleen Niswender, associate professor of pharmacology. Using this compound, they found that enhancing the activity of mGlu1 selectively increased the activity of specific inhibitory interneurons, restoring their ability to inhibit the neuronal circuits they control.

Further, the researchers saw that by working with the PAM, symptoms characteristic of schizophrenia in human patients were reversed. These results suggest that using a PAM to enhance mGlu1 activity is an effective treatment for schizophrenia.

Why it matters

Schizophrenia is an important clinical and societal concern. "Inadequate treatment responses and failures to address 'negative symptoms' and cognitive deficits result in poor patient outcomes," Maksymetz said. "And they incur a huge financial burden on the U.S. and global economies."

Researchers hope that this novel treatment strategy "may eventually provide relief for patients, allow them to reintegrate into and contribute to society, and diminish the burden on our health care systems." The results of this research are particularly exciting because the drug reverses working memory deficits, a hallmark of schizophrenia for which there is currently no treatment.

Today's pharmaceutical schizophrenia treatments were serendipitously discovered half a century ago and were not derived from good understanding of disease biology. Decades of clinical findings have improved researchers' understanding of the biological basis of the disease, opening the door for the development of better-targeted, more efficacious drugs. "We reasoned that if we addressed the underlying disease biology by boosting the function of these interneurons, then we might be able to rescue cognitive deficits associated with prefrontal cortex dysfunction," Maksymetz said.

What's next

The results of this study raise a number of questions about mGlu1 biology. Ongoing studies in the Conn lab are investigating the role and effects of mGlu1 in various regions within the brain.

To translate these findings to the clinic, scientists will need to investigate the efficacy of PAMs when used chronically rather than in the short term, evaluate potential side-effects, and determine whether enhancing mGlu1 reduces other symptoms in schizophrenia, especially "negative symptoms" like a lack of motivation and social withdrawal, which are frequently treatment -resistant.

"We think this study is a good foundation to build upon," Maksymetz said. "Hopefully we will be able to test the hypothesis that mGlu1 PAMs can actually treat patients with schizophrenia someday soon. I truly believe that understanding how neural circuits function and dysfunction will lead to a revolution in treating neuroscience-related diseases, and I'm excited to be a part of it."

The research was published in Cell Reports .

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Blocking Overactive Enzyme Could Treat Schizophrenia Symptoms

Posted: January 19, 2017

New Research Defines Molecular Pathway That May Cause Psychosis in Some Types of Schizophrenia

Posted: January 10, 2017

New Way of Studying DNA as it’s Bundled in Cells Reveals New Schizophrenia Risk Genes

Posted: November 17, 2016

Researchers Catalog Subtle but Widespread Schizophrenia-Associated Differences in Gene Activity

Posted: November 02, 2016

Researchers Pinpoint Neurons That Cause and Maintain Wakefulness

Posted: September 30, 2016

New Technique Recreates Large-Scale Genetic Errors Linked to Neurodevelopmental Disorders

Posted: August 30, 2016

Study Finds Some Autism and Schizophrenia Related Genes May Also Be Involved in Bipolar Disorder

Posted: August 19, 2016

New Tool Calculates Patients’ Personal Psychosis Risk

Posted: July 27, 2016

Women Have More Gene Copy Number Variations Than Men, But This Doesn’t Increase Schizophrenia Risk as Expected

Posted: July 19, 2016

Doubt is Cast on the Contribution of Older Fathers’ Gene Mutations to Increased Mental Illness Risk in Their Children

Posted: July 13, 2016

Infections During Pregnancy Could Cause Developmental Disorders in Children

Posted: June 21, 2016

Prenatal Nicotine Exposure Raised Odds of Schizophrenia in Children

Posted: June 09, 2016

Gut Bacteria's Vital Role in Prefrontal Cortex, Brain's White Matter

Posted: May 24, 2016

Could Anti-Inflammatory Meds Prevent Immune-Linked Brain Disorders?

Posted: May 16, 2016

Blood Markers Indicate High Inflammation Levels in People with Schizophrenia, Bipolar Disorder and Depression

Posted: May 05, 2016

Researchers Reverse Cognitive and Behavioral Deficits in New Mouse Model for Schizophrenia

Posted: May 02, 2016

How Genes May Help Determine Response to Antipsychotic Medications

Posted: May 01, 2016

Testing a Simple Strategy To Prevent Schizophrenia via Dietary Supplements

New Biotypes Classify Psychosis Cases According to Measurable Biological Features

Onset of Psychotic Disorders Differs Among Ultra-High Risk Groups

Posted: April 29, 2016

Children’s Schizophrenia Risk Correlated with Their School Performance vs. Family Members

Posted: April 12, 2016

New Experiments Reveal Brain Circuitry Behind Inability to Experience Pleasure

Posted: April 05, 2016

Immune Activity During Pregnancy Tied to Neuronal Defects, Anxiety, and Cognitive Impairments

Posted: March 21, 2016

A Role for Spontaneous Mutations in the Development of Childhood-Onset Schizophrenia

Posted: March 07, 2016

Abnormalities in a Highly Duplicated Genome Region May Reveal Continuities in Symptoms of Schizophrenia and Autism

Posted: January 28, 2016

A Milestone in the Search for Schizophrenia’s Causes

Posted: January 15, 2016

Overactive Immune Cells Precede Schizophrenia Diagnosis

Posted: January 11, 2016

Animal Study Offers New Clues to the Genetics of Schizophrenia

Posted: December 01, 2015

Connectivity Problems May Indicate Which Individuals are at Greatest Risk for Schizophrenia

Posted: November 20, 2015

Imaging Studies Reveal Affected Brain Regions in Schizophrenia

Posted: November 06, 2015

New Insights into the Genetic Basis of Schizophrenia

Posted: October 22, 2015

Hopeful News on Comprehensive Team Treatment of Early Psychosis

Posted: August 26, 2015

Non-Invasive Stimulation Reworks Brain Waves, Improves Cognition

Posted: July 31, 2015

Genes Linked to Abnormal Brain Waves in Schizophrenia, Psychotic Bipolar Disorder

Posted: July 20, 2015

New Compounds Show Promise in Treating Schizophrenia Symptoms

Posted: July 15, 2015

Can Smoking Tobacco Lead to Schizophrenia?

Posted: July 07, 2015

Schizophrenia-Related Gene Mutation Impairs Fear Processing in Mice

Posted: July 06, 2015

Genetic and Brain Structure Abnormalities Linked in Schizophrenia

Posted: June 26, 2015

Innovative Analysis Finds Unique Brain Structure Patterns in People with Schizophrenia

Posted: June 23, 2015

Brain Connectivity Problems Linked with Psychotic Disorders are Present in Youth with Less Severe Symptoms

Posted: June 16, 2015

Large Study Confirms Major Hypotheses in Schizophrenia Research

Posted: June 09, 2015

Estrogen Drug Improves Cognition in Schizophrenia Patients

Posted: June 01, 2015

Large-Scale Gene Mutation Disrupts Brain Development During Key Period

Posted: May 18, 2015

Gene Associated With Cognitive Deficits a Possible Target For Drug Treatment

Posted: May 11, 2015

Genetic Disorder Points to Cellular Communication Problems in Schizophrenia

Posted: April 24, 2015

Tracing a Circuit Between Two Brain Areas Points To New Schizophrenia Treatment Targets

Posted: April 21, 2015

Three-Month Dosage of Injectable Antipsychotic Prevents Return of Schizophrenia Symptoms

Posted: April 13, 2015

Neurosteroid Treatment Reduces Schizophrenia-Like Symptoms in Mice

Posted: April 10, 2015

Understanding the Link Between White Matter Abnormalities and Schizophrenia Symptoms

Posted: April 06, 2015

Imaging Reveals Specific Brain Circuit Differences in a Subtype of Schizophrenia

Posted: March 23, 2015

Early Cognitive Decline Predicts Later Psychosis in Children With a DNA Deletion Syndrome

Posted: March 20, 2015

Digging Deeper into the Cause of Cognitive Deficits in Schizophrenia

Posted: March 17, 2015

New Clues About How Healthy Circuits Form in Developing Brains

Posted: March 10, 2015

New Clues About a Brain Receptor, a Neurotransmitter, and Schizophrenia

Posted: February 05, 2015

Study Finds Brain-Wave Increase in People With Schizophrenia

Posted: January 30, 2015

Multiple Psychiatric illnesses Share the Same Perturbed Biological Pathways

Posted: January 22, 2015

Genetic Signals Emerging on Schizophrenia Risk

Targeting the d1 dopamine receptor to improve working memory in schizotypal personality disorder.

To Better Understand Mental Disorders, Researchers Reverse Engineer Schizophrenia “in a Dish”

Posted: January 21, 2015

Early-Stage Schizophrenia Associated With Increased Prefrontal Cortex Connectivity That is Reversed Following Treatment

Posted: January 20, 2015

Wiring Anomalies in the Fetal Brain Due To a Faulty Protein May Be a Causal Factor in Schizophrenia

Posted: January 08, 2015

New Pharmaceutical Approach Shows Potential Benefit in More Narrowly Targeting Antipsychotic Medicines

Posted: January 07, 2015

Problems with Attention Traced to Specific Brain Circuit

Posted: December 18, 2014

Researchers Discover New Regions of the Genome That Contribute to the Risk of Schizophrenia

Posted: December 09, 2014

IQ Study Finds Environmental and Genetic Factors in Schizophrenia Risk

Posted: December 03, 2014

Psychotic Symptoms in Young People Foreshadow Later Problems

Posted: November 22, 2014

Developing Risk Profiles for Schizophrenia

Posted: November 05, 2014

The Life of a Spine: Neuron Communication and Schizophrenia

Posted: October 23, 2014

What Causes the Placebo Effect in Clinical Trials of Antipsychotic Medications?

Posted: October 16, 2014

Study Offers New Insight into What Causes Learning Impairment in Schizophrenia

Posted: October 10, 2014

World Mental Health Day: “Living with Schizophrenia”

Posted: September 29, 2014

International Collaborative Effort Develops the Beginnings of a Blood Test for Psychosis

Posted: September 25, 2014

Stem Cell Technology Offers New Insight into Brain Mechanisms Underlying Schizophrenia

Posted: September 18, 2014

Bolstering Reading Skills Could Improve Outcomes in Schizophrenia

Posted: September 16, 2014

Electroconvulsive Therapy, with Clozapine, Shows Promise for Patients with Treatment-Resistant Schizophrenia

Posted: September 10, 2014

Finding Common Roots Across Spectrum of Psychosis May Improve Early Intervention Techniques

Posted: September 08, 2014

Congratulations to Mary-Claire King, Ph.D., Foundation Scientific Council Member, for 2014 Lasker Award!

Posted: September 04, 2014

Psychosocial Training Shows Promise as Supplemental Treatment for Schizophrenia

Posted: September 02, 2014

Resting State Brain Imaging Points to Differences in Early- and Late-Stage Schizophrenia

Posted: August 27, 2014

NARSAD Grantee Discovers Clues to New Pathways for Treatment of Schizophrenia

Posted: August 25, 2014

Can Antioxidants Help Prevent and /or Treat Symptoms of Schizophrenia?

Posted: August 21, 2014

With New Technology, Researchers See How Faulty Human Brain Cells Develop

Posted: August 15, 2014

Foundation-Funded Researcher Identifies Brain “Switchboard” that May Malfunction in Autism, Schizophrenia

Posted: August 08, 2014

Foundation-Supported Research Finds “Helper” Cells in Brain Actually Support Memory Function

Posted: July 25, 2014

“Reprogramming” of Genes Causes Some Symptoms of Mental Illness—May Be Reversible

Posted: July 22, 2014

Advancing Genetics Offer Promise for Developing Risk Profiles, Better Treatments for Schizophrenia

Posted: July 17, 2014

Maternal Infection, Inflammation during Pregnancy Linked to Baby's Risk for Schizophrenia

Posted: July 15, 2014

Stem Cell Technology Offers Rare Inside View of Brain Development and Schizophrenia

Posted: July 07, 2014

New Global Study Quantifies Risk of Mental Illness from Genetic Deletion Syndrome

Posted: July 03, 2014

Dr. Sanjay Gupta of CNN Quotes Foundation President in Articles on Schizophrenia

Posted: July 02, 2014

Gender Differences in the Adolescent Brain that May Link to Mental Illness

Posted: July 01, 2014

New Technique Identifies Genetic Underpinning of Disrupted Brain Connectivity in Schizophrenia

Posted: June 20, 2014

Researchers Complete Picture of How Brain Mechanism Linked to Depression, Schizophrenia Functions

Posted: June 19, 2014

Gene Linked to Bipolar Disorder, Schizophrenia Plays Key Role in Brain Development

Posted: June 17, 2014

NARSAD Grantees Advance Knowledge of Genetics and Early Brain Development in Schizophrenia

Posted: June 05, 2014

Released Today: New Insight into Root Cause of Auditory Hallucinations in Schizophrenia

Posted: June 02, 2014

Foundation-Funded Research Suggests Prenatal Beginnings of Schizophrenia, Could Aid Early Diagnosis

Posted: May 30, 2014

Genetic Sequencing Technology Helps Identify Mutations Linked to Development of Schizophrenia

Posted: May 19, 2014

Transplanting Brain Cells, Researchers Discover Potential Approach to Treat or Prevent Psychosis

Posted: May 08, 2014

Novel Approach Leads to Discovery of Disruption in Brain Connectivity in Schizophrenia

Posted: April 30, 2014

Study on Genetic Variability in Schizophrenia May Improve Prevention and Treatment Strategies

Posted: April 17, 2014

Foundation-Supported Research Advances Technology to Study Developmental Mechanisms of Schizophrenia

Posted: April 10, 2014

Misfiring Brain Signals in Schizophrenia Distort View of Reality

Posted: April 07, 2014

NARSAD Grantee Finds Experimental Compound Reverses Schizophrenia Symptoms in Mice

Posted: March 19, 2014

Brain Mapping Furthers Understanding of Why Imitation is Difficult in Schizophrenia

Posted: March 17, 2014

Scalp EEG Test May Be Able to Predict Future Psychosis

Posted: March 10, 2014

Genetic Analysis Offers New Insight into Memory Impairment in Schizophrenia

Posted: March 07, 2014

NARSAD Grantee Develops 3-D Picture of Protein Important in Schizophrenia

Posted: March 05, 2014

Integrated Approaches to Develop Improved Schizophrenia Therapies

Fine-tuning the circuitry in the brain and intervening early on: exciting next-generation treatment possibilities.

Posted: February 13, 2014

Crossed Wires in the Brain as Potentially Reversible Cause of Schizophrenia

Posted: January 27, 2014

New Understanding of Genetics Behind Schizophrenia From International, Collaborative Research Efforts

Effective brain communication impeded by “new” genetic mutations, progress in identifying sets of genes linked to schizophrenia, solving the schizophrenia puzzle, what makes some genes disrupt brain development, next generation therapies for schizophrenia: from specific genetic mutations to targeting repair pathways.

Posted: January 17, 2014

2013 Baer Prizewinner With a Dream: "To Re-Connect the Soul to the Mind... the Soul to the Brain" - Watch Video

Posted: January 13, 2014

New Technology Assesses Brain Plasticity, May Help with Schizophrenia, Depression

Posted: January 09, 2014

New Research Shows “Jumping Genes” Could Contribute to Schizophrenia

Posted: January 02, 2014

2013 NARSAD Grant Supports Discovery of Genetic Overlap Between Schizophrenia and Cognitive Ability

Posted: December 17, 2013

NARSAD Grant Furthers Exploration of Link between Older Fathers and Mental Illness

Posted: December 16, 2013

NARSAD Young Investigator Grantee Invents New Technology to Study Brain Plasticity

Posted: December 12, 2013

Chicken or Egg? New Research Shows Men and Women’s Brains are Wired Differently

Posted: December 02, 2013

Why do Antibodies Found in the Blood Only Sometimes Link to Neuropsychiatric Illness?

Posted: November 22, 2013

Discovery of First Genetic Protective Factor for Schizophrenia

Posted: October 25, 2013

Esteemed Schizophrenia Researcher, Marc G. Caron, Awarded with 2013 Lieber Prize

Posted: October 24, 2013

Electrical Stimulation Can Improve Cognitive Performance―May Help in Schizophrenia, Bipolar Disorder

Posted: October 23, 2013

Founding Foundation Scientific Council Member Awarded International Mental Health Prize

Posted: October 22, 2013

Researchers Find Way to Increase Neuroplasticity and Treat “Negative” Symptoms of Schizophrenia

State of md supports foundation scientific council member’s early intervention in psychosis program.

Posted: October 21, 2013

Looking for What May Cause Disordered Thinking (“Cognitive Deficits”) in Schizophrenia

Posted: October 08, 2013

Defining Psychotic Disorders―Mood Disorders and Schizophrenia―by Symptom Course and Long-Term Outcome

Posted: October 04, 2013

Pre-Term Birth Associated with Higher Risk of Mental Illness, But Also for Siblings

Posted: September 26, 2013

Long-Term Study of Children Shows Progressive Nature of Thinking Difficulties in Schizophrenia

Posted: August 15, 2013

New Schizophrenia Genes Discovered Through Innovative Genetic Sequencing Approach

Serotonin discovery via x-ray crystallography points toward more precise treatments.

Posted: August 02, 2013

Parent’s Diet May Impact Child’s Mental Health Shows NARSAD Grantee Generational Study

Posted: July 18, 2013

Genetic Sequencing Technology Helps Uncover New Potential Causes of Schizophrenia

Posted: July 16, 2013

Foundation Grantees Link Oxidative Stress with Mental Illness Risk Gene

Posted: July 05, 2013

Brain & Behavior Research Foundation-Funded Study Links Schizophrenia, Inflammation & Bacteria

Posted: July 03, 2013

Is Smoking Self Medication? New NARSAD Grant Research Provides Critical Insights

Posted: July 01, 2013

NARSAD Grant-Funded Discoveries Offer New Treatment Target for Schizophrenia

Posted: June 27, 2013

NARSAD Grantees Discover Potential for Treatment to Reverse Schizophrenia Symptoms

Posted: June 24, 2013

NARSAD Grantee Co-Leads Mammoth Effort to Dissect Mental Illness Risk Gene

Posted: June 20, 2013

NARSAD Grant-Funded Research Helps Identify Mechanisms To Improve Schizophrenia Treatment

Posted: June 14, 2013

Discovery Using Optogenetics May Help Fine-Tune Treatments for Schizophrenia Symptoms

Posted: June 10, 2013

New Computational Method Helps Decode Complex Circuitry of the Brain

Posted: June 07, 2013

Cutting-Edge Stem Cell Technology Offers New Insight Into Development of Schizophrenia

Posted: June 06, 2013

Relapse & Antipsychotic Treatment in Schizophrenia Change Brain

Posted: May 30, 2013

NARSAD Grantees Reverse Schizophrenia Symptoms in Adult Animals

Posted: May 21, 2013

Damaged Protective ‘Net’ May Cause Malfunction in Brain Cells in Schizophrenia

Posted: May 13, 2013

FDA Expedites New Psychosis Treatment Developed by Scientific Council Member

Posted: May 09, 2013

A New Window to Study Mental Illness: Stem Cells Converted to Brain Cells

Posted: May 02, 2013

The Nose May Know: Study Finds New Potential Way to Diagnose Schizophrenia

Posted: April 29, 2013

Foundation-Funded Study Identifies Schizophrenia Early Warning Sign

Posted: April 18, 2013

Intervening in Early Psychosis with Computer-Based Brain Training

How studies with children are helping identify early developmental links to mental illness.

Posted: April 17, 2013

NARSAD Grantee Maps Brain Navigation – Insights May Help Treat Schizophrenia

Posted: April 16, 2013

Understanding Healthy Brain Function Furthers Progress in Identifying Causes of Schizophrenia

Posted: April 03, 2013

New Schizophrenia Genes Discovered Through Innovative Genetic Sequencing

Posted: March 29, 2013

NARSAD Grantees Link Altered Brain Activity to Schizophrenia Cognitive Symptoms

Posted: March 21, 2013

New Technology Enables New Insights Pointing toward Safer Schizophrenia Medications

Posted: March 14, 2013

NARSAD Grant-Funded TMS Now Found Effective in Treating Schizophrenia Symptoms

Posted: March 12, 2013

NARSAD Grantee Discovers Predictor of Psychosis in Bipolar Disorder, Schizophrenia

Posted: March 06, 2013

Single Gene Plays Defining Role in Schizophrenia Symptoms and Outcomes

Posted: March 01, 2013

Recovery Interventions that Promote Productive Lives

Posted: February 25, 2013

NARSAD Grantee Helps Uncover Schizophrenia Warning Sign

Posted: February 19, 2013

NARSAD Grantee ‘2012 Editor’s Choice’ for Work on Recovery from Schizophrenia

Posted: February 12, 2013

Discovery Links Inflammation to Schizophrenia Onset, May Aid Early Intervention/Prevention

Posted: February 07, 2013

Foundation Grantees Develop Brain Atlas to Aid Understanding of Autism, Schizophrenia

Posted: February 01, 2013

Identifying What Keeps Electrical Impulses in the Brain Balanced—Linked to Schizophrenia

Posted: January 25, 2013

NARSAD Grant-Funded Research Identifies New Genetic Link to Development of Schizophrenia

Posted: January 21, 2013

Foundation-Funded Research Helps Identify How Adolescent Stress Can Cause Mental Illness

Posted: January 18, 2013

Schizophrenia Research Forum Features Paper with Discoveries on Genetic Deletion Syndrome

Posted: January 15, 2013

Released Today: Supplement Shows Promise for Preventing Schizophrenia

Posted: January 14, 2013

Learning About Individual Genetics Alleviates Suffering for Patients with Schizophrenia

Posted: December 27, 2012

2012 Highlights: A Sampling of NARSAD Grants at Work

Posted: December 17, 2012

Cognitive Remediation Activates Neuroplasticity and Improves Social Cognition in Schizophrenia

Cells and circuits: neurotransmission with a focus on dopamine.

Posted: November 30, 2012

NARSAD Grantees Lead Study Pointing To Novel Pathways for Treatment of Schizophrenia

Posted: November 29, 2012

2008 Lieber Prizewinner Wins 2013 Grawemeyer Award for Schizophrenia Research

Posted: November 27, 2012

NARSAD Grant-Funded Research Furthers Understanding of What Makes Us Human

Posted: November 26, 2012

Dr. Walters Receives Sidney R. Baer, Jr. Prize for Innovative Schizophrenia Research

Posted: November 02, 2012

NARSAD Grant-Funded Research Identifies Where Empathy Originates in the Brain

Dr. michael owen recognized for outstanding achievement in schizophrenia research.

Posted: November 01, 2012

Prestigious Lieber Prize for Schizophrenia Research Goes to Dr. Michael O’Donovan

Posted: October 15, 2012

NARSAD Grantee Identifies New Pathway to Treat Schizophrenia

Posted: October 11, 2012

NARSAD Grantees Identify New Genetic Mutations that Cause Schizophrenia

Posted: September 24, 2012

A Natural Laboratory: Using an Isolated Population to Study Schizophrenia Genes

Translating epigenetics into novel therapies for autism and schizophrenia, premature birth heightens risk for mental illness, comprehensive identification of key genetic players in schizophrenia.

Posted: August 23, 2012

NY Times: New Study Confirming Risk of Autism and Schizophrenia Increases with Father’s Age

Posted: August 07, 2012

Creating a New Window to Study Synaptic (Dys)Function in Brain and Behavior Disorders

Posted: July 20, 2012

NARSAD Grantee Leads Team That Links Two Risk Factors for Schizophrenia

Posted: July 05, 2012

NARSAD Grant-funded Research Finds Links Between Schizophrenia, Bipolar and Autism

Posted: July 03, 2012

NARSAD Grantee Discusses Innovative Work to Understand and Better Treat Mental Illnesses

Posted: June 28, 2012

FDA to Evaluate Computer-Based Treatment for Cognitive Symptoms in Schizophrenia

Posted: June 19, 2012

NARSAD Grant-Funded Research Identifies Genetic Links in Weight Gain from Antipsychotics

Posted: June 04, 2012

NARSAD Grant-Funded Research Finds Premature Birth Increases Risk for Mental Illness

Posted: May 17, 2012

NARSAD Grantee Leads Breakthrough Research that Identifies the Genetic Code of Schizophrenia

Posted: March 29, 2012

New Discovery On Link Between Early Life Stress and Genetic Susceptibility in Schizophrenia

Posted: March 20, 2012

New Computer Program Improves Behavioral Symptoms and Brain Activity in Schizophrenia

Posted: March 12, 2012

25 Years of Outstanding Schizophrenia Research: The Lieber Prize

Posted: February 29, 2012

NARSAD Grantees Make Breakthrough to Improve Cognition in Schizophrenia

Posted: February 07, 2012

Scientific Council Member Outlines the Progress in – and Need for – Mental Health Research

Posted: January 20, 2012

SC Member Makes Discovery About Teen Susceptibility to Depression and Schizophrenia

Posted: January 19, 2012

A New, Quick Approach to Predict Future Course of Psychosis

Posted: January 06, 2012

Foundation-funded Discovery: Early Childhood Immigration Linked to Psychotic Disorders

Posted: January 05, 2012

NARSAD Grantee Makes New Discovery About Brain Malfunction in Schizophrenia

Posted: December 30, 2011

Basic Research and Novel Therapeutic Treatments Pave the Road to Cures for Mental Illness

Posted: December 05, 2011

Foundation Web-based Schizophrenia Research Forum Honored by ACNP

Posted: November 30, 2011

A Scientist Writes About Autism, Schizophrenia and their Causes

Posted: November 29, 2011

Foundation-funded Investigator Honored for Mental Illness Research Achievements

Posted: November 21, 2011

World-Renowned Investigator’s Personal Connection to Schizophrenia

Posted: November 18, 2011

BBC “Mental Health Revolution” Features Foundation-Funded Psychiatry Research

Posted: November 15, 2011

Coping with Psychosis: Using CBT to Manage Persistent Symptoms

‘father of cbt’ demonstrates its effectiveness treating low-functioning schizophrenia patients, genome-wide studies identify 11 new genetic links to schizophrenia and bipolar disorder.

Posted: November 09, 2011

Breakthrough in Schizophrenia Research by Foundation's 2011 Outstanding Prizewinner

Posted: November 03, 2011

Scientific Council Member Leads Effort that Reprograms Skin Cells to Grow Brain Cells in Lab

Brain & behavior research foundation scientific council member discovers key dopamine receptor structure.

Posted: October 24, 2011

New Understanding of Autism and Schizophrenia in Adolescence?

Posted: October 10, 2011

Outstanding Achievement Prizewinner Makes Discovery, Progressing Research for New Schizophrenia Treatments

Posted: October 06, 2011

NY Times Features Breakthrough in Treatment of Schizophrenia by Foundation-funded Scientist

Posted: October 03, 2011

A “GPS” System for Brain Cells is Created by 2011 NARSAD Distinguished Investigator Grantee

Posted: September 26, 2011

Understanding Why Identical Twins Are Not Carbon Copies in Mental Illness

Posted: September 22, 2011

Foundation Honors Scientists For Outstanding Achievements in Mental Illness Research

Posted: September 15, 2011

The Saturday Evening Post features NARSAD Grantees’ breakthrough insight on link between maternal infection and mental illness

Posted: August 26, 2011

Foundation-Funded Discovery Points Toward Genetic Networks that Predispose to Schizophrenia

Narsad distinguished investigator demonstrates working memory can be restored in elderly primates.

Posted: July 26, 2011

Foundation-funded Study Supports Hypothesis That Davunetide Prevents Cortical Thinning in Brains of Schizophrenia Patients

Posted: May 26, 2011

Brain and Behavior Research Foundation-Funded Study Provides Explanation for Why People with Schizophrenia Have Difficulty with Social Cues

Posted: April 11, 2011

Twenty-year career leading discoveries into the complex circuitry of the brain points toward more effective treatments

Foundation-funded discovery of new schizophrenia gene could lead to new diagnostic and therapy possibilities, leading researcher uses innovative ways to improve treatments.

Posted: March 23, 2011

NARSAD Investigator Makes Major Breakthrough in Understanding Brain Function

Posted: March 01, 2011

Stem Cells Offer New Insight into Helping the Brain Regenerate

Narsad-funded research breakthrough could improve treatment of schizophrenia.

Posted: February 17, 2011

Upcoming Conference: “Advancing Drug Discovery for Schizophrenia”

Posted: February 07, 2011

Hearing from NARSAD Young Investigators (Part 2)

Posted: February 04, 2011

The NARSAD Feed: NARSAD-Funded Discoveries, Economics of (Mental) Health Care Reform, Meditation and Your Brain

Posted: February 01, 2011

NARSAD Supports Innovative Technologies That Improve Treatment of Mental Illness

Narsad scientific council member discovers key dopamine receptor structure.

Posted: January 03, 2011

NARSAD-Funded Research Suggests Brain Scans Could Predict Onset of Schizophrenia

Posted: December 13, 2010

A very grand vision: “We will discover the causes of mental illnesses so that we can someday develop prevention protocol to keep people from developing these illnesses”

Posted: November 01, 2010

Can Studies of Substance Abuse in Schizophrenia Lead to Better Medications?

Leading the way - a brilliant mind in schizophrenia research sees cause for optimism, narsad-funded research identifies new gene candidate for schizophrenia.

Posted: October 01, 2010

NARSAD Researcher Makes Progress Toward His Goal of Prevention of Schizophrenia and Other Mental Illnesses

Posted: September 01, 2010

NARSAD Researcher Makes Discovery in Brain’s Decision-Making Process

Posted: April 10, 2010

Schizophrenia: Is Recovery Possible?

‘retraining the brain’ in patients with schizophrenia.

Posted: April 01, 2010

Mary-Claire King and Judith Rapoport: New Hope From Discovery of Rare Genetic Mutations in Schizophrenia

Aaron beck: reducing schizophrenia’s negative symptoms.

Posted: April 25, 2008

Discovery of Important Genetic Links to Schizophrenia

Posted: November 01, 2003

Identification of Genes Associated with Schizophrenia

Posted: April 01, 1996

Discovery of Novel Gene-Regulating Molecule (Transcription Factor) that Mediates Effects of Stress

Posted: December 01, 1989

Approval of Clozapine to Treat Resistant Schizophrenia

Key figures.

3.5 million adults (1.1%) of the US Adult population live with schizophrenia*

* Source: National Institute of Mental Health

More than 21 million people worldwide are affected by schizophrenia*

* Source: World Health Organization (WHO) 

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New risk genes for #schizophrenia have been discovered by studying DNA in highly compressed bundles. TWEET

Meet a Researcher

Thomas W. Weickert, Ph.D.

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SUNY Upstate Medical University

2016 Independent Investigator Grant

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Huda Akil, Ph.D.

Gardner Quarton Distinguished University Professor of Neuroscience and Psychiatry

Co-Director, Molecular and Behavioral Neuroscience Institute

2007 Goldman-Rakic Prize for Outstanding Achievement in Cognitive Neuroscience

In your work with the Pritzker Neuropsychiatric Research Consortium, have you uncovered any new genes that you think might be related to mental illnesses besides major depression?

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• Frontiers in Psychiatry
• Molecular Psychiatry
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Molecular Mechanisms in Psychiatry 2023: Schizophrenia

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About this Research Topic

Schizophrenia is a debilitating mental disorder that affects millions of people worldwide. Despite the availability of treatments, many individuals with schizophrenia continue to experience significant impairment in their daily lives. Recent research has identified several molecular mechanisms that contribute to the development and progression of schizophrenia, including changes in neurotransmitter levels, alterations in cellular signaling pathways, and abnormalities in brain structure and function. This Research Topic aims to bring together cutting-edge research on the molecular mechanisms of schizophrenia from a variety of disciplines, including genetics, neurobiology, and pharmacology. We invite Original Research articles, Reviews, and Perspectives that cover the following topics: - The genetic basis of schizophrenia: recent advances in identifying genetic risk factors for schizophrenia - The role of neurotransmitters in schizophrenia: the role of dopamine, glutamate, and other neurotransmitters in the pathophysiology of schizophrenia - Cellular signaling pathways in schizophrenia: the role of intracellular signaling pathways, such as the Wnt signaling pathway, in the development and progression of schizophrenia - Brain imaging studies of schizophrenia: recent advances in identifying brain regions involved in schizophrenia - Emerging therapies for schizophrenia: novel therapeutic targets and approaches for the treatment of schizophrenia We particularly encourage submissions that explore new avenues for the development of targeted therapies for schizophrenia, and that highlight the translational potential of research on the molecular mechanisms of the disorder.

Keywords : molecular mechanisms, schizophrenia

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Cortes-Briones, D'Souza Honored With Schizophrenia Research’s Most Downloaded Paper Award

Two Yale scientists have been honored with the journal Schizophrenia Research’s Most Downloaded Paper Award for a 2022 paper titled, “Going Deep Into Schizophrenia With Artificial Intelligence.”

Jose Cortes-Briones, PhD, assistant professor of psychiatry, was the paper’s first author. A contributing author was Deepak D’Souza, MD, Albert E. Kent Professor of Psychiatry.

The award acknowledges the paper as the journal’s most downloaded article published between July 2022 and June 2023.

The purpose of the article was to introduce schizophrenia researchers to the field of deep learning and review its latest applications in schizophrenia research.

The award will be presented at the Schizophrenia International Research Society Annual Congress in Florence, Italy, in April 2024.

• Awards & Honors

Featured in this article

• Jose Cortes-Briones Assistant Professor of Psychiatry
• Deepak Cyril Dsouza, MBBS, MD Albert E Kent Professor of Psychiatry; Chair, Research and Development Committee; Director Schizophrenia Neuropharmacology Research Group at Yale (SNRGY); Director, Neurobiological Studies Unit, VACHS; Director, VA-CMHC Schizophrenia Research Clinic; Director, Yale Center for the Science of Cannabis and Cannabinoids

• Introduction
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• Article Information

ICD-10 indicates International Statistical Classification of Diseases and Related Health Problems, Tenth Revision ; OCR, Ontario Cancer Registry; OHIP, Ontario Health Insurance Plan; RPDB, Registered Persons Database.

FFS indicates fee-for-service; FHG, Family Health Group; FHO, Family Health Organization; FHT, Family Health Team; OR, odds ratio.

eTable 1. Databases Used in Study

eTable 2. Definitions of Primary Care Models

Data Sharing Statement

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O’Neill B , Yusuf A , Lofters A, et al. Breast Cancer Screening Among Females With and Without Schizophrenia. JAMA Netw Open. 2023;6(11):e2345530. doi:10.1001/jamanetworkopen.2023.45530

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Breast Cancer Screening Among Females With and Without Schizophrenia

• 1 MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St Michael’s Hospital, Unity Health Toronto, Ontario, Canada
• 2 Department of Family and Community Medicine, St Michael’s Hospital, Toronto, Ontario, Canada
• 3 Department of Family and Community Medicine, Temerty Faculty of Medicine, University of Toronto, Ontario, Canada
• 4 Women’s College Research Institute, Toronto, Ontario, Canada
• 5 ICES, Toronto, Ontario, Canada
• 6 Department of Family and Community Medicine, North York General Hospital, Toronto, Ontario, Canada
• 7 School of Medicine, Sir James Mackenzie Institute for Early Diagnosis, Population and Behavioural Science Division, University of St Andrews, St Andrews, Scotland
• 8 Institute for Mental Health Policy Research and Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada

Question   How does breast cancer screening completion in Ontario, Canada, differ between females with and without schizophrenia, and how does it compare among those who access care from clinicians who work under different primary care payment models?

Findings   In this case-control study of 127 590 females with schizophrenia (cases) and without (matched controls) schizophrenia, fewer cases had a mammogram within 2 years of their 50th birthday compared with controls. A higher proportion of cases whose clinicians were enrolled in a blended capitation payment model completed mammograms compared with cases whose clinicians were enrolled in fee-for-service or enhanced fee-for-service payment models.

Meaning   Findings of this study suggest that females with schizophrenia tend to undergo less breast cancer screening compared with females without schizophrenia; some of these differences are associated with differences in primary care payment models.

Importance   Breast cancer screening with mammography is recommended in Ontario, Canada, for females 50 years or older. Females with schizophrenia are at higher risk of breast cancer, but in Ontario it is currently unknown whether breast cancer screening completion differs between those with vs without schizophrenia and whether primary care payment models are a factor.

Objective   To compare breast cancer screening completion within 2 years after the 50th birthday among females with and without schizophrenia, and to identify the association between breast cancer screening completion and different primary care payment models.

Design, Setting, and Participants   This case-control study analyzed Ontario-wide administrative data on females with and without schizophrenia who turned 50 years of age between January 1, 2010, and December 31, 2019. Those with schizophrenia (cases) were matched 1:10 to those without schizophrenia (controls) on local health integration network, income quintile, rural residence, birth dates, and weighted Aggregated Diagnosis Group score. Data analysis was performed from November 2021 to February 2023.

Exposures   Exposures were schizophrenia and primary care payment models.

Main Outcomes and Measures   Outcomes included breast cancer screening completion among cases and controls within 2 years after their 50th birthday and the association with receipt of care from primary care physicians enrolled in different primary care payment models, which were analyzed using logistic regression and reported as odds ratios (ORs) and 95% CIs.

Results   The study included 11 631 females with schizophrenia who turned 50 years of age during the study period and a matched cohort of 115 959 females without schizophrenia, for a total of 127 590 patients. Overall, 69.3% of cases and 77.1% of controls had a mammogram within 2 years after their 50th birthday. Cases had lower odds of breast cancer screening completion within 2 years after their 50th birthday (OR, 0.67; 95% CI, 0.64-0.70). Cases who received care from a primary care physician in a fee-for-service (OR, 0.57; 95% CI, 0.53-0.60) or enhanced fee-for-service (OR, 0.79; 95% CI, 0.75-0.82) payment model had lower odds of having a mammogram than cases whose physicians were paid under a Family Health Team model.

Conclusions and Relevance   This case-control study found that, in Ontario, Canada, breast cancer screening completion was lower among females with schizophrenia, and differences from those without schizophrenia may partially be explained by differences in primary care payment models. Widening the availability of team-based primary care for females with schizophrenia may play a role in increased breast cancer screening rates.

People with schizophrenia experience markedly earlier mortality than the general population, dying 10 to 25 years sooner than those without the condition. 1 , 2 Multiple studies of premature mortality among this population have identified cancer as an important factor. 3 , 4 Schizophrenia is 1 of the top 5 mental health conditions with the largest implications for the health of people in Ontario, Canada. 5

People with schizophrenia may be at higher risk of developing breast cancer. A study in Finland reported that females with schizophrenia had higher rates of breast cancer, especially those with antipsychotic medication use for at least 5 years. 6 A meta-analysis of 125 760 patients showed that those with schizophrenia had a 31% increased risk of developing breast cancer (standardized incidence ratio, 1.31; 95% CI, 1.14-1.50). 7 The association between schizophrenia and breast cancer may be partially attributable to a shared genetic cause between the 2 diseases. 8

Cancer screening, including for cervical and colorectal cancers, is a factor in reduced mortality. 9 , 10 Although uncertainty exists about the effectiveness of mammography to reduce breast cancer–specific or all-cause mortality, 11 - 13 it is recommended by Cancer Care Ontario and the Canadian Task Force on Preventive Health Care. 14 , 15 In Ontario, the standard of care and guideline recommendation for patients with an average risk of breast cancer is screening with mammography every 2 years from age 50 to 74 years. 16

Many jurisdictions, including Ontario, have health system–level cancer screening programs, which are known to have differential access by socioeconomic status. 17 Some studies have shown lower cancer screening rates among people with severe mental illness, including 2 Ontario studies: 1 reporting lower cervical cancer screening rates among people with psychosis in a Toronto Family Health Team, 18 and another reporting lower cervical cancer screening among people with schizophrenia from provincewide data. 19 An international systematic review found that females with schizophrenia across multiple countries were half as likely to be screened for breast cancer than the general population, but the study did not include subgroup or sensitivity analyses of the characteristics of the study settings, such as different features of how health systems were organized or funded that may be associated with screening completion. 20 Another systematic review found that people with psychosis had a higher risk of breast cancer and were 22% more likely to have had metastasized cancer at the time of diagnosis. 21 Studies from the US 22 - 24 and the UK 25 , 26 and 2 systematic reviews 27 , 28 found lower cancer screening among people with serious mental illness. Studies from Manitoba, Canada, identified lower breast cancer screening with mammography 29 and lower cervical cancer screening with Papanicolaou tests among people with schizophrenia. 30 Although these studies reported differences in cancer screening rates between people with and without schizophrenia, they did not focus on aspects of health system delivery, such as primary care payment models or care organization, that could play a role in increased cancer screening among this population.

There are differences between the health systems in previous studies and the Ontario setting that highlight the importance of investigating screening rates among people with schizophrenia in the Ontario setting. Starting in 2002, Ontario family physicians (who provide most primary care in the province) have had the option to enter a series of new primary care payment models. These models included enhanced fee-for-service (FFS), known as Family Health Groups (FHGs) and comprehensive care models, whereby physicians receive pay-for-performance financial incentives for preventive care, such as completion of cancer screening. Another available model, known as Family Health Organization (FHO), provides compensation mostly through blended capitation rather than FFS payments in addition to pay-for-performance preventive care incentives. 31 In a FHO, specific pay-for-performance financial incentives were instituted starting in 2006 for preventive care, such as cervical, breast, and colon cancer screening. Some FHOs are part of Family Health Teams (FHTs), with additional team members such as nurses, social workers, dietitians, and other allied health professionals. In 2016, 29.1% of Ontario family physicians were in an FFS model, 23.8% were in enhanced FFS models, and 23.7% were in FHO-FHT models. 32 Research comparing cancer screening rates between patients who accessed care from physicians in these capitation-based models and those in the traditional FFS model did not find a difference in rates. 33 Additionally, there were no substantial differences between these models in quality of care for other conditions among the general population, such as those with diabetes, 34 and 1 study 35 suggested that timely access to care might be worse for people whose clinicians were under the capitated models. However, among those with schizophrenia, there is evidence of better guideline-congruent diabetes care favoring capitated models. 36 Therefore, it is important to understand the extent to which these capitation and team-based payment initiatives may be beneficial for cancer screening among high-risk populations, such as those with schizophrenia.

The present study aimed to compare breast cancer screening (mammogram) completion within 2 years after the 50th birthday among females with and without schizophrenia and to identify the association between breast cancer screening completion and different primary care payment models in Ontario, Canada. We investigated differences in breast cancer screening completion among those with schizophrenia who accessed care from a physician practicing in a capitated model vs an FFS model, and differences in rates between capitated models. We hypothesized that a capitated model would have patients with higher breast cancer screening completion, whereas a team-based capitated model would have patients with the highest breast cancer screening completion.

This retrospective matched case-control study obtained data from ICES, which securely houses and provides facility for analyzing health administrative data from Ontario, including data cleaning and linkage. ICES is a prescribed entity under the Section 45 provision in the Ontario Personal Health Information Protection Act, which authorizes health information custodians to transfer personal health information for evaluation of health services for resource allocation planning. In accordance with the Section 45 provision, this study was exempt from research ethics board approval and informed consent requirement. We followed the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) and Reporting of Studies Conducted Using Observational Routinely Collected Data ( RECORD ) reporting guidelines.

Ontario is Canada’s most populous province, with a population of 15 007 816 as of 2022 (approximately 40% of Canada’s population). 37 All necessary physician visits, medical tests, hospital services, and cancer screenings (including mammograms) are fully insured by the Ontario Health Insurance Plan (OHIP) for all Ontario permanent residents, with no payment at the point of care. Primary care physician (PCP) services are paid for by OHIP through several primary care payment models; reform of these models was instituted between 2002 and 2007. 38

As described, the 3 primary care payment models in Ontario are as follows: FFS, in which PCPs receive payment per visit, without pay-for-performance incentives; enhanced FFS (FHG), in which most compensation is from payment per visit, with some pay-for-performance incentives; and capitation (FHO-FHT), in which most compensation is from a per-patient per-year payment, with pay-for-performance incentives for preventive care. 39 The FHT model includes additional per-patient funding for hiring nonphysician staff, such as nurses, dietitians, and social workers.

The study population included all Ontario residents who were documented as female in the Registered Persons Database, who had continuous OHIP coverage throughout the study period (January 1, 2010, to December 31, 2019), and who turned 50 years of age during the study period. The primary analysis compared breast cancer screening completion between females with schizophrenia and those without that condition. To identify schizophrenia status, we used the algorithm developed by Kurdyak et al, 40 including data from outpatient physician visits and hospitalizations to identify documentation at multiple time points and settings of a schizophrenia diagnosis.

We excluded patients who were diagnosed with breast cancer before age 50 years, as identified through relevant OHIP codes in the Ontario Cancer Registry, a structured database in which all cancer diagnoses in Ontario are documented. Additionally, we excluded those who had mastectomy prior to age 50 years and received breast implants. We excluded females with particularly high risk for breast cancer, as identified from breast cancer screening that was organized through the High Risk Ontario Breast Screening Program for females with a known personal or first-degree family history of a gene variant associated with breast cancer, who were previously assessed by a genetics clinic as having a greater than 25% lifetime risk, those with a personal or family history of a cancer suggestive of a hereditary breast cancer syndrome, and those with a personal history of chest radiation before age 30 years. 41

The primary outcome was completion of breast cancer screening within 2 years after the 50th birthday. We identified this status from the Ontario Breast Screening Program, 16 which facilitates breast cancer screening completion for females aged 50 to 74 years with average risk (excluding those with a history of breast cancer, with a high risk of breast cancer, or with breast implants). We also identified completion of breast cancer screening from physician billing codes in the OHIP database indicating that a radiologist had read and reported the results of a screening mammogram; there are different codes for diagnostic mammograms.

Cases (females with schizophrenia) and controls (females without schizophrenia) were matched 1:10 on the following variables: local health integration network (the region in which the person lives in the province, as of January 1, 2010), 42 income quintile (1-5, with 1 indicating the lowest income and 5 indicating the highest income), rural residence (residential address in a community with <10 000 people as of January 1, 2010), birth dates within 180 days of each other, and weighted Aggregated Diagnosis Group (ADG) score. 43

Data about age and rurality were obtained from the Registered Persons Database. Income levels were ascertained by using Canadian Census data and by assigning residential-address forward sortation areas to income quintiles using the Statistics Canada Postal Code Conversion File Plus. 44 , 45 Health status was assessed using ADGs (Johns Hopkins ACG System). 43 These ADGs allocated related diseases and reasons for presentation to health care to individual ADGs according to the following characteristics: duration, severity, diagnostic certainty, cause, and specialty care involvement. Data used to calculate ADGs were generated when patients interacted with any part of the health system, including primary, specialty outpatient, and hospital and community care. These groupings were associated with different levels of future health service use and represented a measure of patient complexity. Health service use was assessed from OHIP physician billing codes related to the type of service, and data were obtained from the Discharge Abstract Database, 46 National Ambulatory Care Reporting System, 47 and the Ontario Mental Health Reporting System. 48

Data on primary care payment models were obtained from the Client Agency Program Enrolment data set. 49 Cases and controls were attributed to a physician if they were formally enrolled (rostered) or, for those receiving care from physicians who were not under capitation models, were assigned to the family physician who billed the largest dollar amount for primary care services for that patient during the study period. 50 We considered the following primary care payment models in this study: team-based capitation (FHT), non–team-based capitation (FHO), enhanced FFS/FHG, physician not in a patient enrollment model (FFS physicians), and no physician (patient did not have any primary care visits during the study period and were not designated as rostered to a PCP in a capitated payment model). More information on the variables extracted from each database is provided in eTables 1 and 2 in Supplement 1 .

The accuracy of matching cases to controls was assessed using weighted SD of differences between groups. Baseline characteristics (such as income quintiles) were reported with descriptive statistics for both cases and controls. The outcome of breast cancer screening completion for cases and controls was analyzed using logistic regression and reported with odds ratios (ORs). Furthermore, using logistic regression and reported with ORs, we conducted an unadjusted analysis to compare breast cancer screening completion among people with schizophrenia across primary care payment models.

Significance testing was performed with 2-sided tests. P  < .05 was used to indicate statistical significance. Data analysis was performed from November 2021 to February 2023 using SAS, version 9.4 (SAS Institute Inc).

This study included 11 631 females with schizophrenia (cases) who turned 50 years of age during the study period and were matched to 115 959 without schizophrenia (controls), for a total of 127 590 participants ( Figure 1 ). Matching was adequate, with SDs close to 0 ( Table 1 ). Overall, 34.8% of cases and 34.9% of controls were in the lowest income quintile, and 8.7% of cases and 8.6% of controls lived in rural communities. The largest proportion of both cases (13.1%) and controls (8.6%) lived in the Toronto Central region, and 1.9% of cases and controls lived in the rural Northwest region of Ontario. Most females with schizophrenia (46.2%) had a weighted ADG score of 10 or higher, suggesting substantial comorbidity and future health service use.

For the primary outcome of breast cancer screening completion, 69.3% of cases and 77.1% of controls had a mammogram within 2 years of their 50th birthday. Those with schizophrenia had lower odds of having a mammogram compared with those with schizophrenia (OR, 0.67; 95% CI, 0.64-0.70; P  < .001) ( Table 2 ).

There were differences in breast cancer screening completion among cases who received care from PCPs in different primary care payment models ( Table 3 ; Figure 2 ). Most cases were enrolled with a physician either in an FHG model (30.8%) or an FHT model (24.8%) ( Table 1 ). Among females with schizophrenia, 5.9% were found to have no physician visits during the study period. These patients also had lower odds of having a mammogram while being enrolled with a physician in an FFS vs an FHT model (OR, 0.57; 95% CI, 0.53-0.60; P  < .001). The odds of having a mammogram while enrolled with a physician in an FHG model were lower compared with an FHT model for females with schizophrenia (OR, 0.79; 95% CI, 0.75-0.82; P  < .001).

Most of the total study population (62.5%) had a mammogram before age 50 years. Furthermore, 55.6% of cases had a mammogram before age 50 years. The proportion of controls who had a mammogram before age 50 years was higher than the proportion of cases (63.2%).

This case-control study of breast cancer screening among females in Ontario, Canada, found lower odds of undergoing mammograms among those with schizophrenia. The overall pattern of lower completion of breast cancer screening among patients with schizophrenia was consistent with findings in other settings.

We explored differences in breast cancer screening completion between patients who accessed care from physicians in different primary care payment models to identify associations between these models and breast cancer screening completion. We found higher odds of mammogram completion among those receiving care under capitated models, in which most of the payments were per patient per year (rather than per visit) and there were pay-for-performance incentives for high proportions of breast cancer screening completion. We were unable to assess the relative implications of these 2 aspects of compensation for breast cancer screening completion, but the fact that patients of physicians in capitation models had higher odds of having mammograms suggests an association with 1 or both aspects of of these models. This association with breast cancer screening was not seen in the general Ontario population in the year after the pay-for-performance initiative was instituted 51 (ie, 63.2% of eligible patients had a mammogram within 30 months of March 31, 2010). In the present study, we found a higher proportion of breast cancer screening completion (77.1% of those without schizophrenia and 69.3% of those with schizophrenia). One possible explanation for this higher mammogram completion may be the use of different definitions or may be the improvement, over time, in breast cancer screening completion within capitation models, specifically patients with higher barriers to screening completion, such as those with schizophrenia. We believe the higher breast cancer screening completion in this study among females with schizophrenia receiving care from PCPs in capitation and team-based capitation models compared with 2010 data may be associated with different allocation of resources (eg, physician or allied health professional time); this resource allocation may be particularly beneficial for patients with complex care needs, such as those with schizophrenia. A recent study in Ontario comparing primary care enrollment of adults with and without serious mental illness found lower enrollment in those models among people with serious mental illness. 52 The finding that a mammogram was higher among those with schizophrenia in capitation models (which require enrollment) suggests that ensuring people with schizophrenia have access to these models is warranted. Total health care costs have been shown to be lower among patients of physicians in capitation models than FFS models, further supporting this point, 53 although a specific comparison between costs for people with schizophrenia between those models has not been reported.

One finding, which to our knowledge has not been reported previously, was the proportion of people in both the case and control cohorts who had mammograms before the age of 50 years. Ontario guidelines recommend the completion of breast cancer screening for people with average risk after age 50 years, noting that before age 50 years mammograms can be ordered for screening purposes on a case-by-case basis and in consultation between patients and clinicians. We found that 55.6% of cases and 63.2% of controls received mammograms before age 50 years. This finding represents a deviation from the Ontario guidelines and is likely associated with patient preference or concern about a family history of breast cancer leading to mammogram ordering at a younger age than at the age when routine screening is recommended. Since mammography has a lower positive predictive value for cancer detection among younger people given their lower prevalence of breast cancer, 54 it is important that clinicians discuss the benefits and risks of this approach with patients.

Limitations of this study include the nature of observational data, which prevented our assessment of causality. We included only patients with valid Ontario health coverage and who were permanent residents of Ontario. Some variables were neighborhood level rather than individual level, such as income quintile, and thus we were unable to account for some potential confounders, such as race and ethnicity. Our definition of completing a screening mammogram was different from that used in other studies. We chose within 2 years after the 50th birthday because that was consistent with Ontario guidelines of starting breast cancer screening with mammography at age 50 years.

This case-control study found that females with schizophrenia had lower breast cancer screening completion in Ontario, Canada, than those without schizophrenia. Among the cases, higher odds of mammography completion were seen in those who accessed care from PCPs who were paid under capitation rather than FFS; mammogram completion was highest among those who received care from PCPs working under team-based capitation models. Given that cancer mortality is one of the most substantial factors of mortality in people with schizophrenia, efforts to increase breast cancer screening rates are essential. Widening the availability of team-based, capitated primary care payment model may be a way to achieve this goal.

Accepted for Publication: October 19, 2023.

Published: November 29, 2023. doi:10.1001/jamanetworkopen.2023.45530

Open Access: This is an open access article distributed under the terms of the CC-BY License . © 2023 O’Neill B et al. JAMA Network Open .

Corresponding Author: Braden O’Neill, MD, DPhil, CCFP, MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St Michael’s Hospital, 209 Victoria St, Toronto ON M5B 1T8, Canada ( [email protected] ).

Author Contributions: Dr O’Neill and Ms Huang had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: O'Neill, Lofters, Kiran, Greiver, Sullivan, Kurdyak.

Acquisition, analysis, or interpretation of data: O'Neill, Yusuf, Huang, Ekeleme.

Drafting of the manuscript: O'Neill, Yusuf, Ekeleme.

Critical review of the manuscript for important intellectual content: O'Neill, Lofters, Huang, Ekeleme, Kiran, Greiver, Sullivan, Kurdyak.

Statistical analysis: Huang, Ekeleme, Kurdyak.

Obtained funding: O'Neill.

Administrative, technical, or material support: Lofters, Ekeleme, Sullivan, Kurdyak.

Supervision: O'Neill, Sullivan, Kurdyak.

Conflict of Interest Disclosures: Dr O'Neill reported receiving salary support as a clinician scientist from the Department of Family and Community Medicine at the University of Toronto and St Michael’s Hospital and being a member of the Ontario Health Centre for Excellence in Mental Health and Addictions Schizophrenia and Psychosis Advisory Table outside the submitted work. Dr Lofters reported receiving personal fees from Ontario Health and grants from Pfizer/ReThink Breast Cancer outside the submitted work. No other disclosures were reported.

Funding/Support: This study was supported by the Medical Psychiatry Alliance and the Li Ka Shing Knowledge Institute, St Michael’s Hospital, Unity Health Toronto.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2 .

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Current Concepts and Treatments of Schizophrenia

Piotr stępnicki.

1 Department of Synthesis and Chemical Technology of Pharmaceutical Substances, Faculty of Pharmacy with Division of Medical Analytics, Medical University of Lublin, 4A Chodzki St., PL-20093 Lublin, Poland; [email protected] (P.S.); [email protected] (M.K.)

Magda Kondej

Agnieszka a. kaczor.

2 School of Pharmacy, University of Eastern Finland, Yliopistonranta 1, P.O. Box 1627, FI-70211 Kuopio, Finland

Schizophrenia is a debilitating mental illness which involves three groups of symptoms, i.e., positive, negative and cognitive, and has major public health implications. According to various sources, it affects up to 1% of the population. The pathomechanism of schizophrenia is not fully understood and current antipsychotics are characterized by severe limitations. Firstly, these treatments are efficient for about half of patients only. Secondly, they ameliorate mainly positive symptoms (e.g., hallucinations and thought disorders which are the core of the disease) but negative (e.g., flat affect and social withdrawal) and cognitive (e.g., learning and attention disorders) symptoms remain untreated. Thirdly, they involve severe neurological and metabolic side effects and may lead to sexual dysfunction or agranulocytosis (clozapine). It is generally agreed that the interactions of antipsychotics with various neurotransmitter receptors are responsible for their effects to treat schizophrenia symptoms. In particular, several G protein-coupled receptors (GPCRs), mainly dopamine, serotonin and adrenaline receptors, are traditional molecular targets for antipsychotics. Comprehensive research on GPCRs resulted in the exploration of novel important signaling mechanisms of GPCRs which are crucial for drug discovery: intentionally non-selective multi-target compounds, allosteric modulators, functionally selective compounds and receptor oligomerization. In this review, we cover current hypotheses of schizophrenia, involving different neurotransmitter systems, discuss available treatments and present novel concepts in schizophrenia and its treatment, involving mainly novel mechanisms of GPCRs signaling.

1. Introduction

Schizophrenia is an important health issue, affecting almost 1% of the population, frequently with significant social and economic implications, as patients often suffer from unemployment and are homeless. Moreover, antipsychotics prescribed to treat schizophrenia are used in bipolar affective disorder, which has a prevalence of 2.3% in the population. Consequently, about 16.5 million patients in the EU need antipsychotics on a daily basis. This generates a significant healthcare costs, as central nervous system (CNS) disorders are among the most costly medical conditions (EUR 386 billion annually in the EU) [ 1 ]. Current treatments of schizophrenia have significant limitations. Firstly, they are efficient for only about half of patients enabling them independent life [ 2 ]. Secondly, they ameliorate mainly positive symptoms (e.g., hallucinations and thought disorders which are the core of the disease) but negative (e.g., flat affect and social withdrawal) and cognitive (e.g., learning and attention disorders) symptoms remain untreated [ 3 ]. Thirdly, they involve severe neurological and metabolic side effects and may lead to sexual dysfunction or agranulocytosis (clozapine) [ 4 ]. The reason for only partial effectiveness of current antipsychotics is the pathomechanism of schizophrenia which is not adequately understood due to its complexity and involvement of many molecular targets.

The current understanding of schizophrenia is constituted by the dopaminergic hypothesis which denotes alterations of dopamine neurotransmission in the mesolimbic system responsible for positive symptoms and mesocortical pathway, causing negative symptoms, complemented by the glutamatergic hypothesis which considers changes in prefrontal neuronal connectivity involving glutamatergic neurotransmission at NMDA receptor [ 5 ]. In particular, increased presynaptic dopamine synthesis is relevant for the pathogenesis of schizophrenia [ 6 ]. The methods of treatment of schizophrenia are classified as the first (mainly dopamine D 2 receptor antagonists), second (multi-target antagonists with greater antagonism at serotonin 5-HT 2A receptor than at dopamine D 2 receptor) and third generation antipsychotics represented, e.g., by aripiprazole, brexpiprazole and cariprazine. Aripiprazole is a partial dopamine D 2 receptor agonist in G α pathway but it can display agonist, partial agonist or antagonist activity at dopamine D 2 receptor upon different signaling readouts [ 7 ]. In particular it is an antagonist or a partial agonist for β-arrestin-2 signaling pathway [ 7 ].

As G protein-coupled receptors (GPCRs) are classical and well-validated targets for antipsychotics, the elaboration of concepts on the nature of GPCR signaling opens novel and unexplored possibilities for more effective and safer antipsychotics. GPCR functioning is conceptualized by the ternary complex model which involves activation of the receptor by an agonist and transmission of the signal to G protein. However, it was reported that many GPCR ligand display high degree of promiscuity which was considered a drawback in GPCR-oriented drug discovery [ 8 ]. In many complex diseases including schizophrenia, the single target drugs turned out a failure, whereas multi-target drugs are much more efficient [ 9 ]. Clozapine has a low nanomolar affinity to several aminergic GPCRs which reflexes the complex pathomechanism of the disease.

Another important breakthrough in the field was discovery that a specific receptor can couple to a few G proteins and can signal independently on G proteins by occurring in an ensemble of conformations which trigger interaction with biased ligands to downstream effectors. This phenomenon is termed the functional selectivity [ 10 , 11 ] and may lead to safer drugs thanks to selective modulation of one pathway over another one. In the field of dopamine D 2 ligands as antipsychotics, it was found that many clinically useful drugs are antagonists of β-arrestin recruitment [ 12 ]. Contrarily, it was also reported that dopamine D 2 receptor ligands which are antagonists of Gα i/o pathway and agonists of β-arrestin pathway may display beneficial antipsychotic properties with diminished extrapyramidal unwanted effects in animal models [ 7 ].

Allosteric modulation of GPCRs has lately been a hot topic in GPCR-oriented drug discovery [ 13 , 14 ] as allosteric mode of action brings important advantages over orthosteric drugs: better receptor or even pathway selectivity and fewer side effects and ceiling effect reducing the risk of overdosage [ 15 ]. This approach has not yet been exploited for antipsychotics, however a positive allosteric modulator (PAM) of dopamine D 2 receptor, a peptidomimetic PAOPA, was proven efficient in attenuating symptoms of schizophrenia in animal models [ 16 ]. Few small molecule negative allosteric modulators (NAMs) of dopamine D 2 receptor are known (SB269,652 [ 17 ]; homocysteine and analogs [ 18 ]) and their usefulness in schizophrenia needs to be further evaluated.

Finally, targeting heterodimers of dopamine D 2 receptor which are distinct pharmacological entities, in particular adenosine A 2A –D 2 and serotonin 5HT 2A –D 2 heterodimers with bivalent ligands, dimer-specific monovalent ligands, compounds causing ligand-induced dimerization and peptides, peptidomimetics or small molecules disrupting dimer interface may lead to better pharmaceutics with higher selectivity and tissue specificity [ 19 , 20 ]. Among compounds targeting these dimers only bivalent ligands (not drug-like due to high molecular weight) are relatively easy to design. Compounds from other groups are not known either for D 2 dimers (dimer-specific monovalent ligands and ligands inducing dimerization) or in the whole GPCR family (small molecules disrupting dimer interface). It was only reported that peptides, corresponding to the dopamine D 2 receptor transmembrane regions TMVI and TMVII, effectively dissociated the dimer [ 21 ].

In this review, we cover current hypotheses of schizophrenia, involving different neurotransmitter systems, discuss available treatments and present novel concepts in schizophrenia and its treatment, involving mainly novel mechanisms of GPCRs signaling.

2. Schizophrenia as a Complex Disease

2.1. dopaminergic hypothesis.

The dopaminergic hypothesis of schizophrenia is the fundament of the investigation and treatment of schizophrenia [ 22 ]. The first version of this hypothesis stressed the role of the excess of dopamine but it was developed into an idea linking prefrontal hypodopaminergia and striatal hyperdopaminergia and then to the current aberrant salience hypothesis [ 22 ].

The dopaminergic hypothesis of schizophrenia was proposed for the first time in the 1960s when chlorpromazine was introduced as the first antipsychotic and proved to treat positive symptoms of the disease [ 23 ]. Subsequently, the discovery that amphetamine produces psychosis was another proof for a role of excessive dopamine in schizophrenia. It was thus proposed that the increased dopamine neurotransmission might be a reason of this disease. The advancement of novel antipsychotics was in accordance with the dopaminergic hypothesis of schizophrenia as it was observed that positive symptoms of the disease can be attenuated with dopamine receptor antagonists. However, some findings contradicted this hypothesis, e.g., clozapine, which is a very effective antipsychotic in patients with resistant schizophrenia, has rather low affinity to dopamine D 2 receptors. Moreover, some patients with schizophrenia also have normal level of dopamine metabolites in cerebrospinal fluid or serum. These contradictions and novel findings from PET studies led Davis et al. [ 24 ] to propose that schizophrenia involves diminished frontal and increased striatal dopaminergic neurotransmission. Moreover, they linked the positive symptoms of the disease with the striatal dopamine D 2 receptor overactivation resulting from hyperactive mesolimbic dopamine projections while negative and cognitive symptoms result from the prefrontal cortex dopamine D 1 receptor hypostimulation due to diminished mesocortical dopamine projections [ 22 , 24 ]. Further reformulation of this hypothesis has been reported [ 25 ].

Nowadays, aberrant salience hypothesis of psychosis most commonly links the dopaminergic system with the symptoms of schizophrenia. It is based on the incentive salience hypothesis [ 26 ] which suggests that the mesolimbic dopaminergic neurotransmission is crucial in the attribution of salience which governs attention and affects decision making and functioning [ 22 ]. The aberrant salience hypothesis assumes that the attribution of salience is disturbed by excessive dopamine firing in psychotic episode, while, in healthy individuals, dopamine is responsible for mediating contextually appropriate saliences [ 27 ]. This revised version of dopaminergic hypothesis of schizophrenia may explain some clinical and pharmacological features of the disease, i.e., why the schizophrenia patients do not develop all symptoms of psychosis at once or why antipsychotics exert their therapeutic effects after weeks [ 22 ]. Moreover, it can also shed new light on the side effect of diminished motivation in patients with antipsychotics medication and on the recurrence of psychosis after drug withdrawal.

As mentioned above, the dopamine D 2 receptor is a drug target for all drugs against schizophrenia currently present on the market. First- and second-generation antipsychotics are dopamine D 2 receptor antagonists while third-generation drugs are partial agonists or biased ligands of this receptor. Many drugs applied to treat schizophrenia are antagonists of D 2 -like (D 2 , D 3 and D 4 ) dopamine receptor subtypes [ 28 ]. As dopamine receptor play a key role in coordination of movement, memory and cognition, emotion and affect, and the regulation of prolactin secretion, blockade D 2 -like receptors may result in side effects linked with the long-lasting antipsychotics medication. This involves parkinsonian-like extrapyramidal symptoms typically resulting from the application of the first-generation antipsychotics and metabolic side effects (weight gain, hyperglycemia, increased risk of diabetes mellitus, dyslipidemia and gynecomastia) linked with the second-generation antipsychotics [ 28 ]. In this regard, there are some reports which indicate that D 3 versus D 2 dopamine receptor selective ligands may be an interesting alternative to treat schizophrenia [ 28 ]. It has also been found that the antagonism of dopamine D 3 receptor may be partially responsible for blonanserin-caused cortical dopamine and acetylcholine efflux and cognitive improvement [ 29 ]. Importantly, selective dopamine D 3 receptor antagonists are not efficient in antipsychotic animal models based on D 2 receptor antagonism [ 30 ]. On the other hand, selective D 3 receptor antagonists influence dopaminergic neurons electrical activity in the ventral tegmental area in the way characteristic for the second-generation antipsychotics, neutralize NMDA glutamate receptor blockade effects, and increase cortical dopamine and acetylcholine in microdialysis [ 30 ]. Contrary to dopamine D 2 receptor antagonists, D 3 antagonists beneficially affect several cognitive and social features in animal models, e.g., cognitive flexibility and executive function, that are deteriorated in patients with schizophrenia [ 30 ].

It was also demonstrated that prolonged dopamine D 2 receptor blockade leads to downregulation of D 1 receptors in the prefrontal cortex and, consequently, results in significant deterioration of working memory [ 31 ]. Thus, agonism at D 1 receptors in the prefrontal cortex can have a key role in working memory and thus D 1 receptor might be a target of choice for treating cognitive deficits in schizophrenia [ 32 ].

It should be stressed that, despite a key role of dopamine in the pathomechanism and clinical practice of schizophrenia, dopamine allows understanding the pathophysiology of the disease but not the reason per se [ 22 ]. In this context, dopamine functions as the common final pathway for a number of contributing environmental and/or genetic factors [ 22 ]. Thus, other neurotransmitters, in particular glutamate, are important for the pathomechanism of schizophrenia.

2.2. Glutamatergic Hypothesis

Glutamate belongs to the main excitatory neurotransmitters and is the most common neurotransmitter in the mammalian brain [ 33 ]. Glutamatergic pathways linking to the cortex, the limbic system, and the thalamus regions are important in schizophrenia [ 34 , 35 ]. Disturbances in the glutamatergic neurotransmission may influence synaptic plasticity and cortical microcircuitry, especially NMDA receptor functioning [ 36 ]. NMDA receptors belong to ligand-gated ion channels, and are important for excitatory neurotransmission, excitotoxicity and plasticity [ 37 , 38 ]. NMDA-receptor antagonists, e.g., phencyclidine and ketamine, can mimic psychosis with similar symptoms as in schizophrenia [ 39 ]. Moreover, in therapeutic trials substances which increase NMDA receptor signaling were reported to attenuate some symptoms in patients with schizophrenia [ 40 ]. Next, in postmortem studies, some disturbances in glutamatergic receptor density and subunit composition in the prefrontal cortex, thalamus, and temporal lobe were found [ 38 , 39 , 40 ] and these are brain regions with distorted stimulation while cognitive actions are performed by schizophrenia patients [ 41 , 42 , 43 , 44 ]. NMDA-receptor hypofunction state can lead to morphological and structural brain changes which can result in the development of psychosis [ 45 , 46 ]. It was hypothesized that levels of glutamate lower with age in healthy people, but it was not determined how they are affected by the chronic illness [ 47 ].

Antipsychotics may influence glutamate transmission by affecting the release of glutamate, by interaction with glutamatergic receptors, or by changing the density or subunit composition of glutamatergic receptors [ 35 ]. It was demonstrated that antipsychotics interacting with dopamine D 2 receptor enhance the phosphorylation of the NR1 subunit of the NMDA receptor, thus reinforce its activation and consequent gene expression [ 48 ]. In this context, dopamine–glutamate interactions occur intraneuronally and intrasynaptically. There are also reports that action of some second-generation antipsychotics on NMDA receptors might be different from the effect of the first generation antipsychotics on this receptor [ 49 ]. Antipsychotics also influence glutamate transmission by acting on serotonin receptors [ 50 ].

Disturbances in glutamate signaling may be an attractive drug target for schizophrenia due to its key role in the pathomechanism of this disease in terms of cognitive impairment and negative symptoms [ 34 , 35 ]. Findings for hypoactivity of NMDA receptors in schizophrenia stimulated the clinical trials with substances activating this receptor [ 35 ]. Classical agonists at the NMDA are not useful here as excessive stimulation of NMDA receptors results in excitotoxicity and neuron damage. The glycine modulatory binding pocket on the NMDA receptor can be considered a more promising target. Similarly, positive allosteric modulators of another family of ionotropic glutamatergic receptors, i.e., α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors [ 51 , 52 ] as well as positive allosteric modulators of metabotropic glutamatergic receptors [ 53 ], might be considered promising new treatments of schizophrenia in accordance with the glutamatergic hypothesis of this disease.

2.3. Serotoninergic Hypothesis of Schizophrenia

The serotonin hypothesis of schizophrenia is derived from the reports about the mechanism of action of the hallucinogenic drug lysergic acid diethylamide (LSD) and its linkage to serotonin [ 54 ]. Consideration of the psychotic effects of LSD and the antipsychotic effects of, e.g., risperidone and clozapine, which are dopamine-serotonin receptor ligands, stimulated the research on connections between these neurotransmitters as a drug target in schizophrenia [ 55 ].

It was suggested that the overload of serotonin from the dorsal raphe nucleus (DRN) resulting from stress can disturb the activity of cortical neurons in schizophrenia [ 56 ]. Moreover, long-lasting extensive stress-derived serotonergic overload in the cerebral cortex in schizophrenia, in particular in the anterior cingulate cortex (ACC) and dorsolateral frontal lobe (DLFL), may be a key reason of this disorder [ 57 ].

Serotonin antagonists improve the extrapyramidal side effects of antipsychotics. Despite the lack of absolute proofs aberrance of serotonin signaling in the pathomechanism of schizophrenia, serotonin receptors, particularly 5-HT 3 and 5-HT 6 , still represent promising drug targets for the discovery of novel multi-receptors antipsychotic agents which can alleviate cognitive and negative symptoms of the disease [ 58 , 59 ].

Serotonin-receptor-based signaling was proposed to have an important role in the action of the atypical antipsychotics [ 60 ]. It was suggested by Meltzer et al. [ 61 ] that significant 5-HT 2A receptor antagonism accompanied by diminished dopamine D 2 receptor antagonism are the key pharmacological attributes which characterize clozapine and other second-generation antipsychotics and differentiate them from first-generation drugs. Several serotonin receptors, including 5-HT 2A / 2C , 5-HT 1A , 5-HT 6 and 5-HT 7 receptors, can be partially responsible for the “atypicality” [ 62 ]. Many studies demonstrated that partial and full 5-HT 1A receptor agonists can diminish antipsychotic-induced catalepsy. Consequently, certain second-generation drugs which display a balance between dopamine D 2 antagonism or partial agonism and 5-HT 1A receptor agonism/partial agonism result in low extrapyramidal side effects, which was demonstrated as low cataleptogenic activity in animal models [ 63 ]. Polymorphism of 5-HT 2C receptor gene is associated with olanzapine-induced weight gain [ 64 ]. Moreover, in meta-analyses, three genetic variants within serotonin genes were found linked to clozapine-associated weight gain: rs6313 and rs6314 within HTR2A gene and rs1062613 within HT3A gene [ 65 ]. Moreover, amisulpride, which has a high affinity for serotonin 5-HT 7 receptors, reversed ketamine-induced social withdrawal in rat models [ 66 ]. Next, the antagonism of 5-HT 7 receptors may be partially responsible for antidepressant and procognitive activity of amisulpride [ 67 ].

2.4. Other Aminergic GPCRs in Schizophrenia

Besides dopamine and serotonin receptors, other aminergic receptors are also linked to schizophrenia, i.e., histamine, muscarinic and adrenergic receptors. Histamine H 3 receptor antagonists can be useful in treating cognitive deficits of schizophrenia [ 68 ].

Muscarinic receptors have a key role in modulating synaptic plasticity in the prefrontal cortex and stimulation of these receptors results in long-term depression at the hippocampo-prefrontal cortex synapse [ 69 ]. Cholinergic neurotransmission is impaired in patients with schizophrenia and in animal models of schizophrenia [ 69 ]. Importantly, muscarinic receptor antagonists deteriorate cognitive and negative symptoms in schizophrenia patients and xanomeline, a muscarinic receptor agonist, ameliorates all symptoms in schizophrenia patients and corresponding animal models [ 69 ].

There are also reports that α adrenergic receptors activity can be crucial for aberrant regulation of cognition, arousal, and valence systems associated with schizophrenia [ 70 ].

2.5. GABAergic Hypothesis of Schizophrenia

Gamma-aminobutyric acid (GABA) is the main inhibitory neurotransmitter in the CNS [ 71 ]. GABAergic interneurons are crucial for suppression of the CNS, key for the synchronization and oscillations of activity of neurons which are vital for perception, learning memory, and cognition [ 72 ]. GABA signaling disturbances cause imbalance between excitation and inhibition in the cerebral cortex which is one of the key factors in the pathomechanism of schizophrenia [ 73 , 74 ]. A role of GABA in schizophrenia was first noticed by Eugene Roberts in 1972 [ 75 ]. It was first suggested that GABA can be applied for the treatment of schizophrenia as it inhibits dopaminergic signaling, however recent evidence demonstrated that, in some models, GABA can have adverse effect on the dopamine activity [ 75 ].

Post-mortem studies supported the hypothesis about a changed GABA transmission in schizophrenia [ 72 ]. Importantly, the reduction of glutamic acid decarboxylase-67, GABA synthetic enzyme was observed in brain parts linked with critical cognitive functions (the dorsolateral prefrontal cortex, anterior cingulate cortex (ACC), motor cortex, visual cortex, and hippocampus) [ 72 ].

The decrease in transmission through the TrkB neurotrophin receptor results in a diminished GABA synthesis in parvalbumin-containing subpopulation of GABA neurons in the dorsolateral prefrontal cortex of schizophrenia patients. Despite both pro- and presynaptic compensative responses, the resulting change in the perisomatic inhibition of pyramidal neurons leads to a reduced capacity for the gamma-frequency synchronized neuronal functioning, which is necessary for the working memory functioning [ 76 ].

Changes in the GABA neurotransmission were found in basic and clinical research on schizophrenia and in animal models. The chandelier subtype of parvalbumin-positive GABA neurons can be particularly altered by, and characteristic for schizophrenia [ 77 ]. GABA interneurons are key to brain rhythm-generating networks, and synchrony of neural oscillations is crucial for the perception, memory and consciousness [ 78 ]. GABA signaling disturbances can result in changes in neural synchrony [ 78 ], abnormal gamma oscillations [ 79 ], and working memory deficits.

In clinical studies, the administration of GABA agonists was demonstrated to attenuate schizophrenia symptoms [ 80 ]. Nevertheless, it is not known how GABA interplays with other neurotransmitter systems which needs further investigation.

2.6. Nicotinic Receptors in Schizophrenia

Many people suffering from schizophrenia smoke. This can be attributed to the disease itself or its treatment [ 81 ]. There are numerous reports about disturbed brain cholinergic transmission in patients with schizophrenia [ 82 ]. Patients communicate that smoking helps them to relieve negative symptoms [ 83 , 84 ] which can be linked to their deficiencies regarding nicotinic receptors.

The high rate of smokers among patients with schizophrenia stimulated the research on the role of nicotinic receptors in this disorder [ 85 ]. Studying of α7 receptors with specific venomous toxins showed that α7 receptors are located in brain regions involved in cognition (e.g., the cortex and hippocampus) [ 85 ]. Deterioration of cognitive abilities such as working memory and cognitive flexibility, as well as attention, anticipate psychotic symptoms and are a prognosticator of functional outcome [ 85 ].

Preclinical and clinical research demonstrated that the diminished suppression of P50 auditory evoked potentials in schizophrenia patients can be linked with a lowered density of α7 nicotinic receptors in the CNS [ 86 ]. Schizophrenia patients display weak inhibition of P50-evoked responses to repeated auditory stimuli, which can result from damaged sensory gating. The influence of smoking, however, on the reversing of lowered auditory sensory gating in schizophrenia may be weakened as a result of the desensitization of the nicotine receptors. This was connected with the chromosome 15q14 locus of the α7 nicotinic receptor gene [ 87 ]. Consequently, nicotinic receptors can be an attractive drug target for the treatment of schizophrenia.

The results of trials with α7 nicotinic receptor agonists or positive allosteric modulators are promising [ 88 ] but require further investigation.

2.7. The Endocannabinoid System in Schizophrenia

The endocannabinoid system is changed in schizophrenia (i.e., elevated density of cannabinoid CB1 receptor binding in corticolimbic regions and increased levels of andamide in cerebrospinal fluid). This results in “cannabinoid hypothesis” of schizophrenia [ 89 ]. Moreover, certain genetic changes of the CNR1 gene may protect against schizophrenia or can promote a better pharmacological response to atypical antipsychotics [ 89 ].

2.8. Role of Inflammation and Oxidative Stress in the Pathomechanism of Schizophrenia

The role of inflammation and oxidative stress in schizophrenia is a focus of many studies [ 34 ]. It was reported that severe infections and immune disorders during the life-time are an additional risk factor for the development of schizophrenia [ 90 , 91 ]. Although prenatal infections alone do not seem to be a definitive risk factor, the neurodevelopmental exposure to infection can facilitate the occurrence of psychosis in offspring. This can be supported by the observation that during influenza epidemics women are more likely to give birth to children who develop schizophrenia [ 92 ]. In this regard, there are inflammatory models of psychotic disorders, e.g., the anti-NMDAR encephalitis syndrome [ 93 ]. In this disease, schizophrenia-liked symptoms are combined with elevated level of NMDA receptor autoantibodies. Immunotherapy is a treatment option for this syndrome. This is also indirect proof of involvement of glutamatergic system in the pathomechanism of schizophrenia.

Another treatable immune model of schizophrenia is gluten sensitivity with the occurrence of anti-tissue transglutaminase or anti-gliadin antibodies [ 94 ]. Indeed, there can be a possible relationship between diet rich in grain products with high gluten content and the occurrence or exacerbation of schizophrenia symptoms [ 95 ].

As a consequence of inflammation role in schizophrenia, antibiotics and anti-inflammatory agents have been tested to treat this disease but with a rather limited success [ 96 ]. However, a trial of 1000 mg per day of aspirin as add on treatment demonstrated improvements in the Positive and Negative Syndrome Scale (PANSS) total and positive symptoms [ 97 ].

The importance of oxidative stress in schizophrenia was suggested in the 1930s but it was for a long time underestimated. Recent studies indicate that the oxidative stress preferentially affects interneurons which can be subjected to antioxidant therapies [ 98 , 99 ]. Next, lipid-rich white matter is also sensitive to oxidative stress which can underlie myelin-associated deficiencies in schizophrenia [ 100 ].

3. Classical Approaches to Treat Schizophrenia

Due to poor understanding of the causes of schizophrenia, the treatment, engaging antipsychotic drugs, focuses mainly on reducing the symptoms of the disease. Although psychotic illnesses include a number of various disorders, the term antipsychotic drugs—also known as neuroleptics, major tranquillizers or anti-schizophrenic drugs—conventionally refers to drugs used to treat schizophrenia. The same drugs are also used to treat brain damage, mania, toxic delirium, agitated depression and other acute behavioral disturbances. In terms of pharmacology, most are antagonists of dopamine receptor, although many of them also have an affinity for other targets, especially serotonin receptors, which may have an impact on their clinical efficacy. Currently available drugs have many drawbacks when it comes to their efficacy and side effects. Even though gradual improvements with newer drugs have been achieved, radical new approaches require a deeper understanding of the pathomechanism and causes of the disorder that are still insufficiently understood [ 101 ].

The purpose of treatment is to reduce the suffering of the patient and to improve functioning in cognitive and social area. Life-long treatment with antipsychotic drugs is required in case of many patients. Neuroleptics relieve positive symptoms of schizophrenia such as thought disorder, delusions and hallucinations, and prevent relapse. Their effectiveness is lesser on negative symptoms, which include social withdrawal and apathy. In many patients, negative symptoms have a tendency to persist between periods of treated positive symptoms, but early begun treatment of schizophrenia may prevent the development of negative symptoms over time. Patients suffering from acute schizophrenia usually respond better to treatment than those with the symptoms of chronic disease. To prevent relapses, long-term treatment is usually necessary after the first episode of the disease. Doses that are effective in acute schizophrenia should ordinarily be continued as prophylaxis [ 102 ].

The clinical effectiveness of antipsychotics in enabling patients suffering from schizophrenia to lead relatively normal lives has been presented in many controlled trials. The patient population of psychiatric hospitals, which was comprised of mainly chronic schizophrenics, declined exponentially in the 1950s and 1960s. It took place due to the introduction of neuroleptics, as well as the changing professional and public attitudes in terms of hospitalization of mentally ill patients. However, antipsychotic drugs suffer severe limitations which include:

• - (1) Some patients lack response to drug treatment. Clozapine is recommended in patients resistant to other neuroleptics. The 30% of patients that do not respond are classified as “treatment resistant” and represent a major problem regarding treatment. It is still unknown what underlies the difference between responsive and unresponsive patients, although there are some presumptions that polymorphisms within the dopamine and serotonin receptors family may be involved.
• - (2) They are effective in relieving the positive symptoms (delusions, hallucinations, thought disorders, etc.) but most of them lack effectiveness in controlling the negative symptoms (social isolation, emotional flattening) and cognitive dysfunctions.
• - (3) They may result in a wide range of side effects including extrapyramidal, sedative and endocrine effects that can limit patient compliance.
• - (4) They may decline survival through pro-arrhythmic effects.

Antipsychotic drugs of second generation were believed to overcome these limitations to some degree. However, according to meta-analysis performed by Leucht and co-workers [ 103 ], only some of the examined second-generation neuroleptics, displayed better overall efficacy. Sudden cessation of administration of antipsychotic drugs may result in a rapid onset of psychotic episode, that are different from the underlying illness [ 101 ].

The antagonism of dopamine D 2 receptors located in the mesolimbic pathway is believed to reduce the positive symptoms of schizophrenia. Unluckily, systemically administered neuroleptics do not distinguish between D 2 receptors in different brain areas and thus D 2 receptors present in other regions of the central nervous system will be blocked as well. As a result of this effect, antipsychotics lead to unwanted motor effects (blocking D 2 receptors in the nigrostriatal pathway), enhanced secretion of prolactin (blocking D 2 receptors in the tuberoinfundibular pathway), reduced pleasure (blocking D 2 receptors in the reward system component in the mesolimbic pathway) and presumably they even exacerbate the negative symptoms of the disease (blocking D 2 receptors located in the prefrontal cortex, although they occur in low abundance–D 1 receptors are expressed at higher density). While all neuroleptics, excluding third generation, act by blocking D 2 receptors and therefore, theoretically, should induce all of these side effects, some exhibit additional pharmacological activity (e.g., antagonism at muscarinic and 5-HT 2A receptor) that, to various degree, reduce unwanted effects. Blockade of 5-HT 2A receptor may also contribute to alleviating the negative and cognitive symptoms of schizophrenia [ 101 ].

The concept that serotonin dysfunction can be involved in the development of schizophrenia has come in and out of favor several times. As already mentioned, originally, it was based on the fact that LSD, which is a 5-HT 2A receptors partial agonist, produces hallucinations. However, nowadays, it is thought that serotonin is not directly associated with the pathogenesis of schizophrenia. Nonetheless, affecting serotonin receptors, combined with antagonism at D 2 receptor, has resulted in development of new drugs with improved pharmacological and therapeutic profiles. These are serotonin 5-HT 2A and 5-HT 1A receptors that play an important role in the treatment of schizophrenia.

5-HT 2A receptors belong to G i /G o -coupled receptors and, being activated, produce neuronal inhibition. In the nigrostriatal pathway, 5-HT 2A receptors control the dopamine release in this way. Drugs that are antagonists to 5-HT 2A (e.g., olanzapine, risperidone) enhance the release of dopamine in the striatum by decreasing the inhibitory effect of serotonin. It will manifest in reducing extrapyramidal side effects. Moreover, in the mesolimbic pathway, combined effects of antagonism at D 2 and 5-HT 2A receptors are suggested to counteract the enhanced dopamine function that cause positive symptoms of schizophrenia. Furthermore, block of 5-HT 2A receptor appears to improve the negative symptoms on account of enhancing the release of both dopamine and glutamate in the mesocortical circuit. 5-HT 1A receptors, which are somatodendritic autoreceptors, inhibit serotonin release. Neuroleptics that are 5-HT 1A receptors agonists or partial agonists (e.g., quetiapine) may act by reducing the release of serotonin and thus increasing dopamine release in prefrontal cortex and the striatum.

Some phenothiazine antipsychotics (e.g., periyazine) have been proven to cause fewer extrapyramidal effects than others, which is thought to be correlated with their antagonist properties to muscarinic receptors. Some second-generation drugs (e.g., olanzapine) also exhibit muscarinic antagonist properties. Dopaminergic nerve terminals in the striatum are suggested to innervate cholinergic interneurons which express inhibitory D 2 receptors [ 104 ]. Normally, there is an equilibrium between activation of dopamine D 2 and muscarinic receptor. Antipsychotic drug that block D 2 receptors in the striatum will lead to increased release of acetylcholine on to muscarinic receptors, producing extrapyramidal side effects, which are neutralized if the antagonist of D 2 receptor also display antagonist activity at muscarinic receptors. Maintaining the balance between dopamine and acetylcholine was also the rationale behind the use of benztropine, the muscarinic antagonist, to reduce extrapyramidal side effects of neuroleptics. However, antagonist activity at muscarinic receptors may result in side effects such as blurred vision, dry mouth and constipation [ 101 ].

The term “atypical” is widely used, although it has not been clearly defined. In result, it refers to the diminished tendency of later drugs to cause motor side effects, but it is also used in describing compounds that have different pharmacological profile from first-generation antipsychotics. In practice, it frequently serves—not very usefully—to distinguish the large group of similar first-generation dopamine antagonists from the group of later compounds, which is characterized by higher degree of diversity. Distinction between first- and second-generation antipsychotic drugs rests on such criteria as: receptor profile, occurrence of extrapyramidal side effects (less in second-generation group), efficacy (especially of clozapine) in resistant to treatment group of patients, and efficacy against negative symptoms [ 101 ].

It is also worth mentioning that nowadays new system of nomenclature for psychotropic medications that is neuroscience-based nomenclature (and its further update neuroscience-based nomenclature-2) is recommended [ 105 ]. This system supplies a pharmacological driven nomenclature which focuses on pharmacology and mode of action, reflecting available knowledge and understanding about the targeted neurotransmitter, molecule, system being modified, and mode/mechanism of action. It also includes four additional dimensions: (1) approved indications; (2) efficacy and side effects; (3) “practical note” which summarizes the clinical knowledge that has been prioritized by “filtering” though the taskforce’s “opinion sieve”; and (4) neurobiology.

3.1. First-Generation Antipsychotics

The first-generation antipsychotic drugs act mainly by blocking dopamine D 2 receptors in the brain. They do not exhibit a selectivity for any of the dopamine pathways in the central nervous system and therefore can lead to a range of side-effects, in particular extrapyramidal symptoms and elevated prolactin. In this and the following sections, the most common adverse effect of antipsychotics are mentioned.

The history of antipsychotic drugs dates to December 1950, when chlorpromazine, the first neuroleptic that belongs to the family of phenothiazines, was synthesized in France by the chemist Paul Charpentier as a result of research on new antihistaminic drugs. Further behavioral experiments confirmed antipsychotic properties of chlorpromazine. The release of chlorpromazine to the market took place in 1953 with the trade name Largactil , which derives from “arge” and “acti”, indicating the broad activity of the drug [ 106 ].

According to chemical structure the first-generation antipsychotics may be divided into several groups, as showed in Table 1 [ 107 ].

Classification of first-generation antipsychotic drugs: examples and their chemical structures.

The prototypical and the largest group of antipsychotic drugs in terms of chemical structure is the group of phenothiazines. It may be divided into three subclasses, which comprise in total more than forty drugs. All of them share three-ring phenothiazine structure but differ with side chains joined to the nitrogen atom (position 10 of phenothiazine) and substituents in position 2, which affects the activity of the drug. The three subgroups of phenothiazines have been distinguished considering the side chain in position 10. They are aliphatic, piperidine, and piperazine phenothiazines. The potency of drugs depends on their side chain and therefore aliphatic and piperidine phenothiazines may be characterized as agents of low to medium potency, whereas the potency of piperazine phenothiazines is described as medium to high [ 108 ].

Aliphatic group of phenothiazine derivatives is generally characterized by explicit sedative effects and moderate extrapyramidal and antimuscarinic side effects. Piperidine phenothiazines have moderate sedative effects, but cause fewer extrapyramidal side effects than other groups. Drugs with side chain containing piperazine exhibit fewer sedative and antimuscarinic effects, but more pronounced extrapyramidal side effects than in case of aliphatic and piperidine phenothiazines [ 102 ].

Another group of typical antipsychotic drugs are butyrophenones (e.g., benperidol, droperidol, and haloperidol) whose pharmacological properties are similar to those of piperazine phenothiazines, although their antidopaminergic effect is probably higher than in the case of phenothiazines, with lower antihistaminic, antiadrenergic and anticholinergic effect. Thioxanthenes exhibit moderate sedative, extrapyramidal and antimuscarinic effects, whereas diphenylbutylpiperidines are characterized by reduced sedative, antimuscarinic and extrapyramidal effects [ 108 ].

The relative potency of typical antipsychotics can be expressed by comparison with chlorpromazine and according to that first-generation neuroleptics can be arranged from low to high potency. The measure of “chlorpromazine equivalence” defines the amount of the drug in mg which allows to achieve the same effect as administration of 100 mg of chlorpromazine. The examples of high potent antipsychotic drugs are haloperidol and fluphenazine, both with chlorpromazine equivalent dose of 2 mg. Thioridazine is an antipsychotic of low potency, according to this classification, and is comparable with chlorpromazine—it must be administered in the dose of 100 mg to achieve similar potency as 100 mg of chlorpromazine [ 101 , 108 ].

Due to affecting wide range of receptors and lack of selectivity to dopamine receptors located in the mesolimbic pathway, antipsychotic drugs result in numerous side effects. The most frequent and severe are extrapyramidal effects, such as dyskinesia, dystonias, akathisia, unwanted movements, muscle breakdown, tremors and rigidity, which occur as a result of blocking dopamine D 2 receptors in the nigrostriatal pathway. High doses of typical antipsychotics may induce negative and cognitive symptoms by antagonism to dopamine receptors in the mesocortical pathway, whereas blocking those receptors in the tuberoinfundibular pathway increases the release of prolactin in the pituitary gland and leads to hyperprolactinemia. Another side effects on the CNS are sedation (resulting from antihistaminic activity), drowsiness, vertigo, disturbed sleep, agitation, nightmares, dementia, loss of memory, and depression. Blockade of α 1 adrenergic receptors may cause hypotension. Side effects on cardiovascular system comprise also tachycardia, palpitation, arrhythmia or chest pain. Antipsychotic drugs affect also liver. They increase the concentration of alkaline aminotransferase in the serum and may cause side effects such as jaundice, reversible liver cell hyperplasia, necrosis and increased level of bilirubin. Some effects from the side of the urinary and reproductive system have also been reported: impotence, increased or decreased libido, priapism, polyuria, delayed and premature ejaculation, galactorrhea and anorgasmia. Side effects related to the gastrointestinal system, such as weight gain, nausea, dry mouth, heartburn, anorexia, epigastric distress, dyspepsia, constipation, increased level of pancreatic enzymes, and abdominal cramps, are also common. Other adverse reactions that may result from the treatment with antipsychotic drugs involve: hot flashes, nasal congestion, numbness, blurred vision, dry throat, neutropenia, leukopenia, agranulocytosis, chills, glaucoma, hyperlipidemia, and depression of the respiratory system [ 101 , 108 ].

3.2. Second-Generation Antipsychotics

The new era in treating schizophrenia has begun when, after almost forty years from the introduction of chlorpromazine, the first antipsychotic, FDA approved the clinical use of clozapine in the cases of treatment-resistant schizophrenia. Clozapine has been synthesized in the laboratories of Sandoz and, after clinical trials were performed, released to the market in such countries as Switzerland, Austria, West Germany and Finland. However, studies on clozapine performed at the same time in the USA resulted in reports of agranulocytosis leading to death in some patients treated with the drug. Thus, clozapine disappeared from the market for a long time, but the interest of the scientists in working on the drug did not diminish. Further studies proved the high efficacy of clozapine in the treatment-resistant forms of schizophrenia, which resulted in the FDA approval for the drug in this disease entity [ 109 ].

Clozapine was the first drug with a stronger ability to reduce negative symptoms and that causes fewer extrapyramidal symptoms than known to date antipsychotics. The discovery of clozapine contributed to the introduction of new drugs with more beneficial pharmacological profile than first generation antipsychotics. Generally, second=generation drugs, in comparison with classical antipsychotics, exhibit higher ability to block serotonin 5-HT 2A receptors than dopamine D 2 receptors. Additionally, antagonism to D 2 receptors is weaker in the case of second-generation antipsychotics comparing to those of first generation, which manifests in lower occurrence of extrapyramidal side effects. There are also hypotheses that suggest that atypical antipsychotics bind to dopamine receptors with high dissociation rates or that they are more likely to block dopamine receptors in cortical and limbic regions than in nigrostriatal pathway, which also contributes to lower risk of extrapyramidal effects [ 110 ].

Besides schizophrenia, atypical antipsychotics are used in other diseases, such as bipolar disorder, anxiety disorder, obsessive-compulsive disorder, agitation associated with dementia and autism spectrum disorder [ 111 ]. This makes searching for novel antipsychotics even more important as there is a significant group of patients who need antipsychotics on a daily basis. Second-generation antipsychotics currently approved for clinical use include: clozapine, olanzapine, quetiapine, risperidone, paliperidone, ziprasidone, and molindone ( Figure 1 ).

The chemical structures of representatives of second-generation antipsychotic drugs.

Clozapine, as an atypical antipsychotic, is dopamine and serotonin receptor antagonist. It binds to dopamine D 1–5 receptors, with ten times higher affinity to D 4 receptors than to D 2 . Both D 4 and 5-HT 2A antagonist properties contributes to decrease of negative symptoms and lower occurrence of extrapyramidal side effects. The effect of clozapine on 5-HT 2A receptor signaling differs from classic GPCR antagonists, as it also induces 5-HT 2A receptor internalization and activates Akt signaling via a 5-HT 2A receptor-mediated event [ 112 ]. Thus, clozapine may also be considered a functionally selective agonist. At this serotonin receptor, clozapine is also serotonin 5-HT 1A receptor partial agonist, which is thought to have beneficial effect in terms of reducing negative and cognitive symptoms. Muscarinic receptors are also affected by clozapine: it blocks M 1 , M 2 , M 3 and M 5 receptors, while stimulates M 4 receptor (which results in an excessive salivation as a side effect). Clozapine’s metabolite norclozapine is an allosteric modulator of muscarinic M1 and M4 receptors [ 50 ]. The use of clozapine is associated also with sedation, as a result of antagonism to histamine receptors, and side effects from autonomous system, including hypotension and reflex tachycardia, which in turn result from blockade of α 1 adrenergic receptors. Clozapine is currently used mainly in forms of schizophrenia that are resistant to treatment with other drugs, which means that no satisfactory response has been achieved with at least two other drugs. The main limitation of clozapine is its tendency to cause agranulocytosis, which may lead to death. FDA suggests patients to control the number of white blood cells every week during first six months of treatment (it is the period of the highest risk of agranulocytosis). Afterwards, the number of leukocytes should be controlled every two weeks [ 108 ].

Olanzapine is a chemical analog of clozapine with similar pharmacological properties. However, contrary to clozapine, olanzapine causes fewer autonomic side effects and its use is not associated with a risk of agranulocytosis. Affinity of olanzapine to serotonin 5-HT 2 receptors is approximately two times higher than to dopamine D 2 receptors. It also blocks D 3 and D 4 receptors. Antagonism to histamine, muscarinic and α 1 -adrenoreceptors is weaker than in the case of clozapine. Clinical trials showed that efficacy of olanzapine in reducing positive symptoms is comparable with haloperidol, but is much more effective against negative symptoms and causes fewer side effects than haloperidol. The most frequent side effects of olanzapine are sedation and weight gain.

Quetiapine belongs to antipsychotics, which, besides schizophrenia, are used in treating bipolar disorders and major depressive disorders. Its off-label application includes insomnia, Tourette syndrome or anxiety disorders. Quetiapine acts as a dopamine D 1 , dopamine D 2 and serotonin 5-HT 2 receptors antagonist. Quetiapine is also a 5HT 1a receptor partial agonist. Antagonism to α 1 adrenergic and histamine H 1 receptor manifests in occurrence of side effects such as sedation and orthostatic hypotension.

Risperidone is the first novel atypical antipsychotic. It was introduced to the market at the beginning of the 1990s, twenty years after introduction of clozapine [ 113 ]. It is a benzisoxazole derivative ( Figure 1 ). Its pharmacological profile is reminiscent of properties of olanzapine, except that risperidone is thought to cause sedation less frequent and orthostatic hypotension more often than olanzapine. Therapeutic effect of risperidone results from antagonism to both D 2 and 5-HT 2A receptors with 5-HT 2A antagonism significantly stronger than the D 2 antagonism. Moreover, this drug also causes α 1 adrenergic and histamine receptor blockade. Its anticholinergic effects are negligible. In some patients, risperidone may elevate the level of prolactin and cause arrhythmia. The following other adverse effects may occur during treatment with risperidone: insomnia, restlessness, anxiety, headaches, agitation, EPS, headache, rhinitis, sedation, somnia, fatigue, ocular disturbances, orthostatic dizziness, palpitations, weight gain, diminished sexual desire, erectile and ejaculatory dysfunction, orthostatic dysregulation, reflex tachycardia, gastrointestinal complaints, nausea, rash, galactorrhea and amenorrhea [ 113 , 114 ]. Risperidone is efficient not only in treating positive symptoms but also negative and cognitive disturbances as well as has some anti-depressant properties which makes it one of the most commonly prescribed antipsychotics [ 113 ]. The active metabolite of risperidone is paliperidone, which acts on the same range of receptors. It is used in treating schizophrenia, as well as mania and, in lower doses, in bipolar disorder. Paliperidone comes in formulations of extended release, what allows to administer the drug once per day [ 108 ].

Ziprasidone, another second-generation antipsychotic, acts as antagonist of dopamine D 2 and serotonin 5-HT 2A receptors, partial agonist of 5-HT 1A receptor, and partial antagonist of 5-HT 2C and 5-HT 1D receptors. Besides schizophrenia it is used in acute mania or bipolar disorders [ 115 ].

Molindone acts mainly by affecting dopamine transmission in the brain. It is an atypical antipsychotic with unusual profile of pharmacological properties. It rarely causes sedation and autonomic side effects but is thought to lead to extrapyramidal side effects more frequent than other new antipsychotics, although still less frequently than classical neuroleptics. The use of molindone, contrary to other second-generation antipsychotics, rarely results in weight gain. In patients that do not tolerate or respond to other drugs, the treatment with molindone is sometimes effective [ 108 ].

Other second-generation antipsychotics include: lurasidone, iloperidone, asenapine, sertindole and amisulpiride. They are briefly presented below.

Lurasidone is a benzisothiazole derivative with high antagonist activity at serotonin 5-HT 2A and 5-HT 7 receptors and weaker antagonism at dopamine D 2 receptor [ 116 ]. It is also a partial agonist of serotonin 5-HT 1A receptor and has relatively high affinity adrebergic α 2A and weaker affinity to muscarinic receptors [ 116 ]. In general, lurasidone is effective and well-tolerated for treatment of schizophrenia and for acute bipolar depression. It has low probability of side effects such as weight-gain, and metabolic or cardiac abnormalities, but higher risk of akathisia in comparison to other atypicals [ 116 ].

Iloperidone is a benzoxazole derivative with high affinity to serotonin 5-HT 2A and dopamine D 2 receptors [ 117 ]. Iloperidone has also high affinity to α 1 adrenergic receptors and lower affinity to dopamine D 1 receptors, serotonin 5-HT 1A receptors and histamine H 1 receptors and negligible affinity to muscarinic receptors [ 117 ]. This drug has beneficial EPS and akathisia properties which makes it attractive choice for patients whose compliance is limited by these effects [ 117 ].

Asenapine is a dibenzoxepinopyrrole derivative and has a high affinity for the serotonin 5-HT 2A receptor and to a lesser extent to dopamine D 2 receptor [ 118 ] It is an antagonist of 5-HT 2C , H 1 and α2-receptors. It shares a rather complex binding profile with clozapine, olanzapine and quetiapine. The main side effects of asenapine are weight gain and metabolic disorders [ 119 ].

Sertindole is an indole derivative with a high affinity for dopamine D 2 , serotonin 5-HT 2A and 5-HT 2C , and α 1 adrenergic receptors [ 120 ]. It has also some affinity for histamine H 1 and muscarinic receptors. This drug has low probability to cause sedation and EPS and displays an acceptable metabolic profile. However, cardiac safety should be monitored during treatment with sertindole.

Amisulpiride belongs to benzamides and is a specific antagonist for dopamine D 2 and D3 receptors [ 121 ]. It has negligible affinity to serotonin receptors and receptors typically involved in side effects of atypical antipsychotics. EPS is the most common side effect of amisulpiride.

In the past decade, first-generation antipsychotics have been essentially replaced by newer, atypical antipsychotics mainly due to better toleration of second-generation antipsychotics and their more favorable profile of side effects, especially lower risk of extrapyramidal side effects. However, the second-generation antipsychotics have severe metabolic adverse effects, in particular obesity and diabetes. Weight gain and metabolic disfunctions are common in schizophrenia patients. It is attributed to the blockade of adrenergic, cholinergic, and histaminergic postsynaptic receptors by psychotropic agents [ 122 ]. Indeed, antagonism of histamine H 1 receptors is described as a key reason of second-generation antipsychotics-induced obesity [ 123 ]. Moreover, sedation, a common side effect of clozapine treatment, can be connected with clozapine binding to histamine receptors in the CNS [ 124 ]. Type 2 diabetes mellitus is their most often reported output [ 125 ]. Metabolic side effects are mainly associated with clozapine and olanzapine while data are mixed for risperidone and quetiapine [ 125 ]. For other second-generation antipsychotics, there are only few studies which examined their metabolic effects so it is difficult to draw conclusions [ 125 ].

3.3. Third-Generation Antipsychotics

The newest group of antipsychotic drugs, described as the third generation, consists of aripiprazole, brexpiprazole and cariprazine ( Figure 2 ). That group has been individualized on the grounds of their mechanism of action on dopamine receptors. Unlike other neuroleptics, third-generation drugs are not dopamine D 2 receptor antagonists but D 2 partial agonists. The D 2 receptor partial agonist properties of aripiprazole concern inhibition of cAMP accumulation through the dopamine D 2 receptor (i.e., G α signaling) [ 126 , 127 ] and in the presence of high extracellular concentrations of dopamine (e.g., in mesolimbic areas), compete with dopamine and result in partial antagonism leading to clinical benefits. Contrarily, when extracellular dopamine concentration is on a low level (e.g., in dopamine circuits that are involved in working memory), aripiprazole can bind to additional receptors and activate them partially. Hence, aripiprazole is termed as “dopamine stabilizer” [ 128 , 129 , 130 ]. It has also been demonstrated that aripiprazole is an antagonist in GTPγS binding assays with dopamine D 2 receptor [ 127 , 131 ]. Aripiprazole also failed to activate outward potassium currents following activation of dopamine D 2 receptor, which can indicate that it was inactive or an antagonist for Gβγ signaling through this receptor [ 127 ]. Next, aripiprazole, as another clinically efficient antipsychotic, is an antagonist of β-arrestin pathway [ 132 ]. Moreover, aripiprazole was also reported as agonist or antagonist of other GPCRs [ 133 ]. When it comes to serotonin transmission, aripiprazole exhibits partial agonistic properties to 5-HT 1A and 5-HT 2A (much weaker in the second case), which manifests in functional antagonism at this receptor. Contrary to antipsychotic drugs classified as second generation, aripiprazole displays higher affinity for dopamine D 2 receptor than for serotonin 5-HT 2A receptor. Clinical use of aripiprazole includes, besides schizophrenia, bipolar disorder, major depression, obsessive-compulsive disorder, and autism. Effectiveness of treating schizophrenia with aripiprazole is comparable with haloperidol or quetiapine and slightly higher than in the case of chlorpromazine or ziprasidone. Moreover, aripiprazole is characterized by better tolerability comparing to other antipsychotics [ 134 ]. Side effects that may result from treatment with aripiprazole include mainly akathisia [ 135 ] but also weight gain, agitation, insomnia, anxiety, headache, constipation or nausea [ 129 ]. However, aripiprazole results in considerably lower weight gain and lower increase in glucose and cholesterol levels in comparison to clozapine, risperidone, and olanzapine [ 136 ]. Next, aripiprazole led to weaker EPS, less use of antiparkinsonian drugs, and less akathisia, in relation to typical antipsychotic drugs and risperidone [ 136 ].

Antipsychotic drugs categorized as the third generation and their structures.

Brexpiprazole, approved by FDA in 2015, acts as partial agonist to dopamine D 2 , D 3 and serotonin 5-HT 1A receptors, and exhibits also antagonist properties to 5-HT 2A , 5-HT 2B and 5-HT 7 receptors. Its pharmacological profile is very similar to that of aripiprazole. Brexpirazole and aripiprazle are considerably different in potencies at many receptors. Their antipsychotic efficacy is comparable but brexpiprazole causes less akathisia, EPS and activation [ 137 ]. Moreover, brexpiprazole has precognitive properties [ 138 ] in contrast to aripiprazole [ 139 ]. Brexpiprazole, alone or in combination with escitalopram, facilitates prefrontal glutamatergic transmission via a dopamine D 1 receptor-dependent mechanism [ 140 ]. The drug is used in the treatment of schizophrenia and as an adjunct in major depressive disorder (e.g., in combination with fluoxentine [ 141 , 142 ]). The side effects that may result from using brexpiprazol include akathisia, weight gain, infections of upper respiratory tract, somnolence, headache and nasopharyngitis [ 143 ].

Approval of cariprazine, as well as brexpiprazole, took place in 2015. Similar to other antipsychotics from third generation, cariprazine is dopamine D 2 , D 3 and serotonin 5-HT 1A receptors partial agonist. However, its affinity for dopamine D 3 receptor is approximately ten times higher than for D 2 receptors. Cariprazine can be considered a biased agonist at dopamine receptors, with antagonist or partial agonist activity depending on the signaling pathways linked to D 2 /D 3 receptors [ 144 ]. Mean half-life for cariprazine is 2–5 days over a dose range of 1.5–12.5 mg [ 145 ]. Cariprazine has two clinically significant metabolites, desmethyl-cariprazine and didesmethyl-cariprazine, the latter having a longer half-life than cariprazine [ 145 ]. The clinical use of cariprazine includes schizophrenia and manic or mixed episodes associated with bipolar disorder. In particular, cariprazine can be used for the treatment of schizophrenia patients with dominant negative symptoms, a typically difficult to treat group of patients [ 146 ]. The treatment with cariprazine may lead to occurrence of side effects, such as sedation, akathisia, weight gain, nausea, constipation, anxiety, and dizziness [ 147 ]. Metabolic side effects of cariprazine are however negligible [ 148 ]. In summary, a potential for treatment negative symptoms, anti-abuse potential, and a long half-life make cariprazine a promising drug against schizophrenia [ 149 ].

Introduction of newer antipsychotic drugs to the clinical practice has contributed chiefly to lowering extrapyramidal side effects. Patients are less likely to suffer from akathisia, dystonias, parkinsonian symptoms or tardive dyskinesia than in the case of treatment with first generation antipsychotics. However, advantage of atypical over typical drugs when it comes to effectiveness is still discussed. Some patients respond better to newer antipsychotics and in others older drugs are more effective. This issue requires further research, which is problematic, considering schizophrenia as a chronic disease and the fact that the percentage of hospitalization of schizophrenic patients is low. It should be stressed, however, that novel compounds acting on dopaminergic system are still under investigation for the treatment of schizophrenia. Compounds such as BL 1020, ITI-007, and JNJ-37822681 have been thoroughly studied, and compounds such as L-THP, Lu AF35700, S33138, and SB-773812 are under vigorous investigation [ 150 ].

4. Targeting Novel GPCR Signaling Mechanisms in Schizophrenia

4.1. gpcrs and their novel signaling mechanisms as drug targets.

According to the classical ternary complex model, the signaling through GPCRs can be illustrated as the coaction of three main players: a receptor, an agonist and a G protein. However, more and more experimental and computational studies support the view that GPCR functioning can be much more complex than depicted by the ternary complex model.

The discovery that a specific receptor can couple to more than one G protein type and, besides that, that GPCRs could trigger G protein-independent pathways, stimulated a more nuanced characterization of GPCR ligands. Indeed, there are ligands termed biased agonists that are capable of preferentially activating one receptor-associated pathway over another [ 151 ]. This has been connected with the existence of multiple receptor states, with different propensities to couple to G proteins or other signaling partners, and which can be differentially affected by functionally selected ligands. This complex receptor modulation, which has been termed functional selectivity [ 10 , 11 ], has opened a new avenue for the interrogation of specific GPCR-activated pathways and their impact on health and disease, as well as for the subsequent detection of pathway-selective drugs with a refined mechanism of action [ 152 ]. Characterization of the significance of particular pathways associated with a given receptor can provide insight into the optimal functional selectivity profile for the treatment of a particular disease. In particular, targeting β-arrestin signaling pathways can be promising in the case of antipsychotics (see below), however it should be avoided in the case of many other drugs, e.g., antinociceptive compounds targeting the µ opioid receptor [ 153 ].

At present, another hot topic in GPCR-oriented drug discovery is the design of allosteric modulators instead of orthosteric ligands [ 154 ]. Allosteric ligands possess the ability to modulate GPCR function by binding to receptor regions away from the orthosteric binding site. Allosteric modulators usually bind to receptor areas with a low degree of conservation between GPCR subtypes [ 155 ]. This binding specificity could also be the basis for the design of more selective drugs. Additionally, the fact that allosteric modulators can function together with ligands interacting at the orthosteric binding site makes drugs exploiting this phenomenon especially useful when treatment can be achieved by enhancing or decreasing an endogenous signal. Such an approach may make it possible to solve the problem of drug dependence, overdose risk and other adverse effects linked with classical orthosteric drugs. The allosteric mode of action brings several advantages, e.g., a ceiling effect preventing overdosing, high receptor selectivity, and even activation pathway selectivity which may in consequence lead to safer and more efficient drugs [ 15 ].

In addition, the growing body of experimental (cross-linking experiments, BRET and FRET studies) and computational (coarse-grained molecular dynamics simulations) reports suggesting negative and positive cooperativity between receptors, has paved the way to the concept that GPCRs can oligomerize [ 19 , 20 ]. Both homo- and heterodimerization was reported for numerous GPCRs and the resulting protein complexes were in some cases linked to particular functional outcomes. Thus, GPCR dimers, oligomers and receptor mosaics are now considered promising drug targets, which, due to their restricted tissue distribution, can result in tissue-specific drugs. Despite a growing number of functional interactions between dimers, drug discovery targeting GPCR complexes remains a challenge. Thus, a better description of the structural aspects of GPCR oligomerization and of its effect on signaling, accompanied by the developing of original treatment strategies, seems essential for further exploration of this mechanism of GPCR signaling [ 156 ].

4.2. Targeting GPCR Signaling Complexity in Schizophrenia

The GPCR signaling mechanisms described above have been considered as potential drug targets for novel antipsychotics. The most commonly exploited approach is intentional ligand promiscuity for multi-target drugs typical for second- and, to a lesser extent, first-generation antipsychotics which requires separation of the drug targets from the off-targets [ 157 ]. The treatment of complex diseases, such as Alzheimer’s disease, Parkinson’s disease, cancer or schizophrenia, which involve multiple receptors and enzymes in their pathomechanisms, require looking for potential drugs which satisfy the criteria of many pharmacophores, oppositely to acting on a single molecular target. It should be emphasized in schizophrenia and other complex psychiatric disorders, selective single-target drugs have a very limited efficacy. Clozapine with a nanomolar affinity to several aminergic GPCRs is efficient against drug-resistant schizophrenia and reflects the molecular pathomechanism of this disease, involving cross-talk of many neurotransmitter systems (in particular, dopaminergic, serotonergic, adrenergic and glutamatergic). The new paradigm in medicinal chemistry is to look for substances that act on several molecular targets simultaneously. To accomplish that, it is essential to find structural features which combine important classes of drug targets, leading to molecules with desired selectivity profiles. Although recently implement antipsychotics (e.g., cariprazine and brexpiprazole) are the third-generation drugs, efforts are still made to design new multi-target ligands which can be developed into second generation antipsychotics [ 29 , 158 ].

The next approach that is currently under extensive investigation is biased signaling and functional selectivity. D 2 receptors couple to Gα i/o subunits, which leads to a number of signaling events through the release/rearrangement of G proteins, involving inhibition/sensitization of adenylyl cyclase, G βγ potentiation of AC2, and ERK activation as well as β-arrestin pathway [ 159 , 160 ]. Latest reports allow concluding that selective modulation of signaling pathways downstream of the D 2 receptor can lead to development of more efficient and safer antipsychotics [ 161 ]. In particular, blockade of β-arrestin pathway can be considered a common feature of antipsychotics that exhibit either antagonist or partial agonist activity through Gα i/o -cAMP pathways [ 161 ]. This supposes that β-arrestin-biased D 2 antagonists can display unique antipsychotic profiles [ 161 ]. Contrary to that, a study with analogs of aripiprazole concluded that D 2 ligands with Gα i/o antagonist and β-arrestin agonist activity can display antipsychotic properties with diminished extrapyramidal side effects in animal model [ 7 ]. Several series of biased D 2 agonists have been reported [ 7 , 162 , 163 ] as underlying ligand and receptor structural features necessary for biased signaling. Moreover, as has already been mentioned, serotonin 5-HT 2A receptor functional selectivity can be important for the activity of antipsychotics as it was reported for clozapine [ 112 , 164 ].

Allosteric modulation of D 2 receptor as a mechanism for novel antipsychotics has been not sufficiently studied. Only a peptidomimetic PAOPA ( Figure 3 ), a positive allosteric modulator of D 2 receptor, has been proven to be successful in animal models of schizophrenia. Few negative allosteric modulators are known, e.g. SB269,652, homocysteine and analogs, see Figure 3 and their antipsychotic potential needs to be evaluated. A clear finding of antagonist allosteric actions on D 2 receptor has been demonstrated for homocysteine and analogs, which supports the possibility that homocysteine analogs can be developed into an efficient antipsychotic drug, since they reduce in vitro dopamine binding. Allosteric compound SB269,652 seems to act on D 2 receptor dimer [ 165 ], similarly as bivalent D 2 receptor ligands based on agonist or antagonist structures [ 166 , 167 ], which are however not drug-like due to their high molecular weight and are pharmacological tools rather than potential drugs. At present, no dimer-specific monovalent ligands are known for D2 receptor homodimers or heterodimers of this receptor and no ligands inducing or disrupting dimerization are known.

Allosteric modulators of dopamine D 2 receptor with possible application for the treatment of schizophrenia.

In addition to allosteric modulators of dopamine D 2 receptor, positive allosteric modulators of metabotropic glutamate receptors are nowadays studied as possible treatment for schizophrenia [ 168 ]. In particular, PAMs of mGluR1, mGluR2, mGluR3 and mGluR5 are promising. Furthermore, PAMs of muscarinic receptors, e.g., M 1 and M 4 receptor could be also useful [ 168 ].

Targeting D 2 -receptor-containing dimers is a new and yet unexploited strategy for the treatment of schizophrenia. Among heterodimers formed by the D 2 receptor, adenosine A 2A –D 2 and serotonin 5-HT 2A –D 2 heterodimers in particular are implicated in the pathomechanism of schizophrenia [ 169 ]. A possible biochemical alteration in schizophrenia might not only be D 2 receptor sensitization with elevated D 2 receptor signaling, but also decreased A 2A receptor activity or interruption of A 2A –D 2 receptor interactions because of the existence of abnormal A 2A –D 2 receptor heteromers or by their disappearance [ 170 ]. Observations supporting the presence of A 2A –D 2 heteromers with antagonistic A 2A –D 2 interactions in the ventral striatopallidal GABA pathway suggested the use of A 2A receptor agonists as a strategy for the treatment of schizophrenia [ 171 ]. The antipsychotic potential of A 2A receptor agonists is underlined through behavioral analysis in animal models of schizophrenia in which they demonstrated an atypical antipsychotic profile [ 171 ]. Other classes of potential antipsychotics acting through the A 2A –D 2 receptor heteromer may be the heteromer selective D 2 receptor orthosteric or allosteric antagonists or compounds promoting ligand-induced dimerization. The possible involvement of the D 2 –5-HT 2A heterodimer in schizophrenia was proposed by studies on the hallucinogenic 5-HT 2A agonists showing that they probably induce a conformational state of the 5HT 2A protomer different from the one produced by serotonin, leading to facilitating allosteric interactions with the D 2 partner [ 171 ]. This increase in the D 2 receptor signaling in the D 2 –5-HT 2A heterodimer in the nucleus accumbens could be the basis for their psychotic actions [ 171 ]. This fact can also supply a better description of the molecular mechanism of the therapeutic effects of the second-generation antipsychotics, such as risperidone and clozapine, which block the 5-HT 2A receptor with higher potency than the D 2 receptor. It can be postulated that, in some cases of schizophrenia, this pathological facilitating interaction between 5-HT 2A and D 2 receptors has developed in the 5-HT 2A –D 2 heterodimer leading to increased D 2 protomer recognition and signaling [ 171 ]. Interestingly, 5-HT 2A or D 2 receptor antagonists acting selectively on this heterodimer or compounds disrupting the heterodimer interface might be a novel strategy to treat schizophrenia. Regarding other dimers with possible involvement in the pathomechanism of schizophrenia, mGluR2–5-HT 2A heteromer should be mentioned [ 172 ] This complex displays unique signaling when interacting with hallucinogenic drugs and activation of mGluR2 cancels hallucinogenic signaling and related behavioral responses. In postmortem studies of human brains from untreated schizophrenic subjects, the 5-HT 2A receptor is up-regulated and the mGluR2 is down-regulated which can predispose to psychosis.

5. Other Non-Classical Approaches for the Treatment of Schizophrenia

The limitations of current antipsychotics are supplemented by reports about involvement of neurtotransmitter systems other than the dopaminergic system, especially glutamate neurotransmission that contributes to the pathomechanism of schizophrenia. Thus, new drug targets resulting in drugs with novel mechanisms of action have been proposed. In particular, glutamate and nicotinic targets seems promising [ 173 , 174 ]. Selective ligands for metabotropic glutamate receptor, phosphodiesterase, glycine transporter subtype 1 and the alpha7 nicotinic acetylcholine receptor are considered worth further investigation [ 173 , 174 ].

Regarding metabotropic glutamate receptors, potentiation of mGluR2/3 and mGluR5 receptors can be beneficial in schizophrenia [ 175 ]. Although classical orthosteric agonists are still an option, subtype-selective allosteric ligands, including positive allosteric modulators of mGluR2 and mGluR5 can offer numerous advantages brought by allosteric mode of action.

Phosphodiesterase (PDE) inhibitors improve neurotransmission by affecting intracellular second messenger signaling [ 176 ]. In particular, inhibitors of PDE2, PDE4, PDE5 and PDE10 seem promising for treating cognitive symptoms of schizophrenia.

Glycine transporter 1 inhibitors applied in combination with antipsychotics are effective for relieving negative symptoms of the disease. α7 nicotinic receptor agonists and positive allosteric modulators and minocycline may treat negative and cognitive symptoms. Complementary oxytocin may help to ameliorate psychotic symptoms and social cognitive deficits. Complementary erythropoietin might benefit cognitive function [ 174 ].

6. Conclusions and Future Prospects

Although current concept and treatment of schizophrenia are still based on the dopaminergic hypothesis of the disease, novel approaches involving new signaling mechanisms on classical drug targets or completely new targets emerge. Schizophrenia is a complex multi-factor disease and according to the current knowledge it does not seem very probable that all symptoms of the disease can be treated with a single-target drug. Indeed, clozapine, which is used to treat resistant schizophrenia has a nanomolar affinity to a dozen of aminergic GPCRs. Searching for multi-target drugs beyond aminergic GPCRs may be a promising strategy to design better antipsychotics. Moreover, novel signaling mechanisms of GPCRs can lead to safer drugs with fewer side effects, e.g., allosteric modulators or biased ligands or even with tissue specificity (dimer-selective ligands). Current efforts in drug design against schizophrenia focus on searching for compounds to treat negative symptoms and to improve cognitive deficits as well as searching for compounds that are better tolerated by patients who often need life-lasting treatment.

In summary, after over a century of schizophrenia treatment, significant progress has been achieved, starting from lobotomy operations, through discovery of chlorpromazine to current second- and third-generation antipsychotics. Novel approaches, following new findings in the disease mechanisms, will finally result in new generations of drugs.

Author Contributions

P.S. wrote Section 3 ; M.K. wrote Section 2 ; and A.A.K. wrote Section 1 , Section 4 , Section 5 and Section 6 .

The work was performed under OPUS grant from National Science Center (NCN, Poland), grant number 2017/27/B/NZ7/01767.

Conflicts of Interest

The authors declare no conflict of interest.

Common household chemicals pose new threat to brain health, study finds

Research shows chemicals in countless household items harm specialized cells in the brain.

A team of researchers from the Case Western Reserve University School of Medicine has provided fresh insight into the dangers some common household chemicals pose to brain health. They suggest that chemicals found in a wide range of items, from furniture to hair products, may be linked to neurological conditions like multiple sclerosis and autism spectrum disorders.

Neurological problems impact millions of people, but only a fraction of cases can be attributed to genetics alone, indicating that unknown environmental factors are important contributors.

The new study published today in the journal Nature Neuroscience , discovered that some common home chemicals specifically affect the brain's oligodendrocytes, a specialized cell type that generates the protective insulation around nerve cells.

"Loss of oligodendrocytes underlies multiple sclerosis and other neurological diseases," said the study's principal investigator, Paul Tesar, the Dr. Donald and Ruth Weber Goodman Professor of Innovative Therapeutics and director of the Institute for Glial Sciences at the School of Medicine. "We now show that specific chemicals in consumer products can directly harm oligodendrocytes, representing a previously unrecognized risk factor for neurological disease."

On the premise that not enough thorough research has been done on the impact of chemicals on brain health, the researchers analyzed over 1,800 chemicals that may be exposed to humans. They identified chemicals that selectively damaged oligodendrocytes belong to two classes: organophosphate flame retardants and quaternary ammonium compounds. Since quaternary ammonium compounds are present in many personal-care products and disinfectants, which are being used more frequently since the COVID-19 pandemic began, humans are regularly exposed to these chemicals. And many electronics and furniture include organophosphate flame retardants.

The researchers used cellular and organoid systems in the laboratory to show that quaternary ammonium compounds cause oligodendrocytes to die, while organophosphate flame retardants prevented the maturation of oligodendrocytes.

They demonstrated how the same chemicals damage oligodendrocytes in the developing brains of mice. The researchers also linked exposure to one of the chemicals to poor neurological outcomes in children nationally.

"We found that oligodendrocytes -- but not other brain cells -- are surprisingly vulnerable to quaternary ammonium compounds and organophosphate flame retardants," said Erin Cohn, lead author and graduate student in the School of Medicine's Medical Scientist Training Program. "Understanding human exposure to these chemicals may help explain a missing link in how some neurological diseases arise."

The association between human exposure to these chemicals and effects on brain health requires further investigation, the experts warned. Future research must track the chemical levels in the brains of adults and children to determine the amount and length of exposure needed to cause or worsen disease.

"Our findings suggest that more comprehensive scrutiny of the impacts of these common household chemicals on brain health is necessary," Tesar said. "We hope our work will contribute to informed decisions regarding regulatory measures or behavioral interventions to minimize chemical exposure and protect human health."

Additional contributing researchers from Case Western Reserve School of Medicine and from the U.S. Environmental Protection Agency included Benjamin Clayton, Mayur Madhavan, Kristin Lee, Sara Yacoub, Yuriy Fedorov, Marissa Scavuzzo, Katie Paul Friedman and Timothy Shafer.

The research was supported by grants from the National Institutes of Health, National Multiple Sclerosis Society, Howard Hughes Medical Institute and New York Stem Cell Foundation, and philanthropic support by sTF5 Care and the Long, Walter, Peterson, Goodman and Geller families.

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• Erin F. Cohn, Benjamin L. L. Clayton, Mayur Madhavan, Kristin A. Lee, Sara Yacoub, Yuriy Fedorov, Marissa A. Scavuzzo, Katie Paul Friedman, Timothy J. Shafer, Paul J. Tesar. Pervasive environmental chemicals impair oligodendrocyte development . Nature Neuroscience , 2024; DOI: 10.1038/s41593-024-01599-2

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• Published: 27 March 2024

The effects of genetic and modifiable risk factors on brain regions vulnerable to ageing and disease

• Jordi Manuello   ORCID: orcid.org/0000-0002-9928-0924 1 , 2 ,
• Joosung Min   ORCID: orcid.org/0000-0002-5541-5014 3 ,
• Paul McCarthy 1 ,
• Fidel Alfaro-Almagro 1 ,
• Soojin Lee 1 , 4 ,
• Stephen Smith 1 ,
• Lloyd T. Elliott 3   na1 ,
• Anderson M. Winkler 5 , 6   na1 &
• Gwenaëlle Douaud   ORCID: orcid.org/0000-0003-1981-391X 1  

Nature Communications volume  15 , Article number:  2576 ( 2024 ) Cite this article

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We have previously identified a network of higher-order brain regions particularly vulnerable to the ageing process, schizophrenia and Alzheimer’s disease. However, it remains unknown what the genetic influences on this fragile brain network are, and whether it can be altered by the most common modifiable risk factors for dementia. Here, in ~40,000 UK Biobank participants, we first show significant genome-wide associations between this brain network and seven genetic clusters implicated in cardiovascular deaths, schizophrenia, Alzheimer’s and Parkinson’s disease, and with the two antigens of the XG blood group located in the pseudoautosomal region of the sex chromosomes. We further reveal that the most deleterious modifiable risk factors for this vulnerable brain network are diabetes, nitrogen dioxide – a proxy for traffic-related air pollution – and alcohol intake frequency. The extent of these associations was uncovered by examining these modifiable risk factors in a single model to assess the unique contribution of each on the vulnerable brain network, above and beyond the dominating effects of age and sex. These results provide a comprehensive picture of the role played by genetic and modifiable risk factors on these fragile parts of the brain.

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Introduction

The development of preventative strategies based on modifying risk factors might prove to be a successful approach in ensuring healthy ageing. Factors particularly scrutinised in dementia and unhealthy ageing have included cerebrovascular factors such as high blood pressure, diabetes and obesity, but also lifestyle ones such as alcohol consumption, and protective factors such as exercise 1 . Assessing these modifiable risk factors together makes it possible to identify the unique contribution of each of these factors on the brain or on cognitive decline. A Lancet commission, updated in 2020 to include, e.g., pollution for its possible role in the incidence of dementia 2 , examined the relative impact of 12 modifiable risk factors for dementia, and showed that these 12 factors may account for 40% of the cases worldwide 3 . Conversely, genetic factors are non-modifiable in nature, but can inform us about the mechanisms underlying the phenotypes of interest. These mechanisms sometimes can be shared across these phenotypes. For instance, genetic overlap has been found for Alzheimer’s and Parkinson’s diseases at a locus in the MAPT region 4 . Likewise, one of the most pleiotropic variants, in the SLC39A8 / ZIP8 gene, shows genome-wide associations with both schizophrenia and fluid intelligence, amongst many other phenotypes 5 , 6 .

One way to objectively and robustly assess susceptibility for unhealthy ageing is to look non-invasively at brain imaging markers 7 . Using a data-driven approach on a lifespan cohort, we previously identified an ensemble of higher-order, ‘transmodal’ brain regions that degenerates earlier and faster than the rest of the brain 8 . The very same areas also develop relatively late during adolescence, thus supporting the ‘last in, first out’ (LIFO) hypothesis, which posits that the process of age-related brain decline mirrors developmental maturation. Importantly, this network of brain regions further demonstrated heightened vulnerability to schizophrenia and Alzheimer’s disease, two disorders that impact on brain structure during adolescence and ageing respectively. Accordingly, this LIFO network was strongly associated with cognitive traits whose impairment is specifically related to these two disorders, namely fluid intelligence and long-term memory 8 .

Here, our main objective was to assess both the genetic and modifiable risk factors’ contributions to the vulnerability of these most fragile parts of the brain. We conducted a genome-wide association study on a prospective cohort of nearly 40,000 participants of the UK Biobank study who had received brain imaging, and in total evaluated the association between the LIFO brain network and 161 modifiable risk factors, classified according to 15 broad categories: blood pressure, cholesterol, diabetes, weight, alcohol consumption, smoking, depressive mood, inflammation, pollution, hearing, sleep, socialisation, diet, physical activity and education.

The vulnerable LIFO brain network in UK Biobank

Similar to our previously observed results 8 , the loadings of the LIFO brain network, i.e., the normalised grey matter volume in the network after regressing out the effects of all the other brain maps (see Methods), demonstrated a strong quadratic association with age in the UK Biobank cohort of 39,676 participants ( R 2  = 0.30, P  < 2.23 × 10 −308 , Fig.  1 ). These higher-order regions thus show an accelerated decrease of grey matter volume compared with the rest of the brain. Furthermore, these areas define a network mainly involved in behavioural tasks related to execution, working memory, and attention (Fig.  1 , Supplementary Information ).

Top left, spatial map of the LIFO network (in red-yellow, thresholded at Z  > 4 for visualisation) used to extract the loadings from every scanned participant from UK Biobank ( n  = 39,676). Top right, these LIFO loadings (in arbitrary units) show a strong quadratic association with age in the UK Biobank cohort, i.e. grey matter volume decreases quadratically with older age in these specific regions ( R 2  = 0.30, P  < 2.23 × 10 −308 ; inset: residual scatterplot). Bottom, the vulnerable network appears to encompass areas mainly involved in execution, working memory, and attention (using the BrainMap taxonomy 60 , and with the LIFO brain network thresholded at both Z  = 4 and Z  = 10, see  Supplementary Information ).

Genetic influences over the vulnerable LIFO brain network

Using a minor allele frequency filter of 1% and a –log 10 (P) threshold of 7.5, we found, in the 39,676 participants, genome-wide associations between the LIFO brain network and seven genetic clusters whose top variants were all replicated (Table  1 /Supplementary Data  1 , Fig.  2 ).

Top row, Manhattan plot showing the 7 significant genetic clusters associated with the LIFO brain network (–log 10 ( P ) > 7.5). Second and third rows, regional association plots of the top variants for each of the 5 autosomal genetic clusters: rs6540873 on chromosome (Chr) 1 ( KCNK2 ), rs13107325 on Chr4 ( SLC39A8 ), rs2677109 on Chr6 ( RUNX2 ) (as a proxy in high LD R 2  = 0.86 with indel 6:45442860_TA_T), rs12146713 on Chr12 ( NUAK1 ), and rs2532395 on Chr17 ( MAPT , KANSL1 )(highest variant after tri-allelic rs2693333; see Supplementary Data  4 for a complete list of significant variants in this 5th MAPT genetic cluster). Bottom row, regional association plots of the top variants for the two genetic clusters in the pseudo-autosomal region PAR1 of the X chromosome: rs312238 ( XG , CD99 ) and rs2857316 ( XG )(UK Biobank has no genotyped variants on the 3’ side). Based on Human Genome build hg19. P -values are derived from a two-sided linear association test.

The first autosomal genetic cluster, on chromosome 1, included two variants (lead variant: rs6540873, β  = 0.06, P  = 1.71 × 10 −8 , and rs1452628, with posterior probabilities of inclusion in the causal variant set of 0.56 and 0.45, respectively) close to, and eQTL of, KCNK2 ( TREK1 ). This gene regulates immune-cell trafficking into the central nervous system, controls inflammation, and plays a major role in the neuroprotection against ischemia. Of relevance, these two loci are in particular related in UK Biobank participants with the amount of alcohol consumed, insulin levels, inflammation with interleukin-8 levels, as well as, crucially, with late-onset Alzheimer’s disease (Table  1 /Supplementary Data  1 ).

The second autosomal genetic cluster on chromosome 4 was made of 7 loci, with the lead variant rs13107325 in an exon of SLC39A8/ZIP8 ( β  = 0.14, P  = 2.82 × 10 −13 , posterior probability: 0.99). This locus is one of the most pleiotropic SNPs identified in GWAS, and is, amongst many other associations, related in UK Biobank with cholesterol, blood pressure, weight, inflammation with C-reactive proteins levels, diabetes with insuline-like growth factor 1 levels, alcohol intake, sleep duration, and cognitive performance/impairment, including prospective memory (Table 1 /Supplementary Data  1 ).

The third locus was an indel in chromosome 6 in an intron, and eQTL, of RUNX2 (rs35187443, β  = 0.06, P  = 9.03 × 10 −9 ), which plays a key role in differentiating osteoblasts, and has been very recently shown to limit neurogenesis and oligodendrogenesis in a cellular model of Alzheimer’s disease 9 .

The fourth locus was a SNP in chromosome 12, in an intron of NUAK1 (rs12146713, β  = −0.10, P  = 1.26 × 10 −9 ), and remarkably its top association in UK Biobank was with the contrast between schizophrenia and major depressive disorder 10 , and it was also associated with insulin-like growth factor 1 levels (Table 1 /Supplementary Data  1 ).

The final genetic autosomal genetic cluster was made of 3,906 variants in the MAPT region. Its lead non-triallelic variant, rs2532395 ( β  = −0.09, P  = 3.56 × 10 −15 ) was more specifically <10 kb from KANSL1 and an eQTL of KANSL1 , MAPT and other genes in brain tissues (Table 1 /Supplementary Data  1 , Supplementary Data 4 ). This locus was also associated in UK Biobank with tiredness and alcohol intake. MAPT is in 17q21.31, a chromosomal band involved with a common chromosome 17 inversion 11 . Adding chromosome 17 inversion status as a confounder reduced the significance of the association ( β  = −0.15, P  = 8.45 × 10 −3 ). Since the genotype for rs2532395 was also strongly correlated with chromosome 17 inversion in our dataset (Pearson correlation r  = 0.98, P  < 2 × 10 −16 ), this would suggest that the association between MAPT and the LIFO network is not independent from chromosome 17 inversion. As this extended genetic region is known for its pathological association with many neurodegenerative disorders including Alzheimer’s disease, we investigated whether the LIFO brain regions mediated the effect of the MAPT genetic cluster (using the lead bi-allelic variant rs2532395) on Alzheimer’s disease (see Methods). Despite small average causal mediated effect (ACME) sizes, we found a significant effect for both the dominant model (ACME β  = 1.16 × 10 −4 ; 95% CI = [5.19 × 10 −5 , 1.99 × 10 −4 ]; P  = 4 × 10 −5 ) and the recessive model (ACME β  = 1.55 × 10 −4 ; 95% CI = [3.96 × 10 −5 , 3.74 × 10 −4 ]; P  = 4 × 10 −5 ; full output of the mediation package on the dominant and recessive models in  Supplementary Information ).

The two last genetic clusters of 8 and 9 variants respectively were found on the X chromosome, notably in a pseudo-autosomal region (PAR1), which is interestingly hit at a higher rate than the rest of the genome ( P  = 1.56 × 10 −5 , see  Supplementary Information ). The top variants for these clusters were related to two homologous genes coding for the two antigens of the XG blood group: rs312238 ( β  = −0.05, P  = 1.77 × 10 −10 ) ~ 10 kb from, and an eQTL of, CD99/MIC2 , and rs2857316 ( β  = −0.08, P  = 2.27 × 10 −29 ) in an intron and eQTL of XG  (Table 1 /Supplementary Data  1 ). Since chromosome X has hardly been explored, we carried out our own association analyses between these two top variants and non-imaging variables in UK Biobank. Intriguingly, the first of these two PAR1 loci, rs312238, was found to be significantly associated in the genotyped participants who had not been scanned (out-of-sample analysis in n  = 374,230 UK Biobank participants) with nitrogen dioxide air pollution, our ‘best’ MRF for pollution (see below), and many other environmental, socioeconomic, and early life factors (such as urban or rural setting, distance from the coast, place of birth, number of siblings, breastfed as a baby, maternal smoking around birth), as well as health outcomes (Supplementary Data  2 ). In particular, amongst the more easily interpretable findings of the most associated variables with rs312238, the T allele of this locus was associated with two increased measures of deprivation and/or disability (worse socioeconomic status), the ‘Townsend deprivation index’ and the ‘Health score’, but also with ‘Nitrogen dioxide air pollution’, ‘Maternal smoking around birth’, as well as ‘Number of full brothers’ and ‘Number of full sisters’, thus showing consistent signs of association between this variant and these phenotypes.

We found that the heritability of the LIFO network was significant, with h 2  = 0.15 (se = 0.01). The genetic co-heritability between the LIFO network and Alzheimer’s disease or schizophrenia was not statistically significant (coefficient of co-heritability = −0.12, se = 0.10; P  = 0.23; coefficient of co-heritability = −0.16, se = 0.04, P  = 0.07, respectively).

Modifiable risk factors’ associations with the vulnerable LIFO brain network

Including the modifiable risk factors (MRFs) in a single general linear model allows us to assess the unique contribution of each factor on the LIFO brain network. Not all UK Biobank participants have data available for all of the MRF variables however. An analysis limited to those with complete data for all MRFs would be biased, and based on a relatively small, low-powered sample. We addressed this issue via a two-stage analysis in which: (i) we first identified which variable within each of the 15 MRF categories best represented associations of that category with the LIFO brain network loadings (based on two criteria: significance and <5% missing values), (ii) we investigated the unique contribution of that MRF category, over and above all other categories and the dominating effects of age and sex, to the LIFO loadings.

From the first stage of our analysis, 12 of the 15 categories of MRFs had at least one ‘best’ MRF, i.e., with a significant effect on the LIFO brain network and enough non-missing values across all scanned participants to be investigated further (Table  2 /Supplementary Data  3 ). The contribution of the MRFs on the vulnerable brain network differed vastly depending on whether confounding effects of age, sex and head size were taken into account. The effect size and significance of some MRFs diminished because of some clear collinearity with the confounders. For instance, for the category of blood pressure, the most significant MRF was first “systolic blood pressure, automatic (second) reading” ( r  = −0.20, P  < 2.23 × 10 −308 ), but after regressing out the confounders, the ‘best’ MRF for this category was “medication for blood pressure” ( r  = −0.05, P  = 7.55 × 10 −22 ). Conversely, regressing out the effects of age served to unmask the significant deleterious effects of pollution on the vulnerable brain regions, such as nitrogen dioxide air pollution or particulate matter air pollution (Table  2 /Supplementary Data  3 ).

When considered together in a single model in the second stage of the analysis, 3 best MRFs had an effect on the LIFO brain network that remained significant beyond the dominating effects of age and sex, and of the 9 other best MRFs: diabetes (“diabetes diagnosed by doctor”, r  = −0.05, P  = 1.13 × 10 −24 ), pollution (“nitrogen dioxide air pollution in 2005”, r  = −0.05, P  = 5.39 × 10 −20 ) and alcohol (“alcohol intake frequency”, r  = −0.04, P  = 3.81 × 10 −17 ) (Table  3 ). No MRFs showed any bias in their sub-sampling distribution, i.e., any significant difference between the original sample and the reduced sample of 35,527 participants who had values for all 18 variables considered (the 12 best MRFs and 6 confounders: age, sex, age 2 , age × sex, age 2  × sex, head size; Supplementary Information ). In total, the 12 best MRFs explained 1.5% of the effect on the vulnerable brain network ( F 12;35509  = 43.5).

While 6 out of the 7 genetic clusters associated with the LIFO network were correlated with many variables related to each of the 15 MRF categories, including diabetes, alcohol consumption and traffic pollution (Supplementary Data  1 ), we also found some genetic overlap between the very specific best MRF of “alcohol intake frequency” and the LIFO network in the pleiotropic rs13107325 variant (cluster 2), as well as rs17690703, part of the large genetic cluster 5 in MAPT (Supplementary Data  4 ). No genetic overlap was found for the precise “nitrogen dioxide air pollution in 2005” or “diabetes diagnosed by doctor”, nor for approximate variables.

This study reveals, in a cohort of nearly 40,000 UK Biobank participants, the genetic and modifiable risk factors’ associations with brain regions in a ‘last in, first out’ (LIFO) network that show earlier and accelerated ageing and are particularly vulnerable to disease processes such as that of Alzheimer’s disease 8 . Seven genetic clusters, two of which in the pseudo-autosomal region of the sex chromosomes coding for two antigens of the XG blood system, were found significantly associated and replicated genome-wide. In addition, after accounting for age and sex effects, diabetes, traffic-related pollution and alcohol were the most deleterious modifiable risk factors (MRFs) on these particularly vulnerable brain regions.

Three lead variants for our significant genetic clusters have been previously associated with ageing-related brain imaging measures in recent studies: one, in cluster 1, an eQTL of KCNK2 ( TREK1 ) 12 , 13 , whose increase in expression mediates neuroprotection during ischemia 14 , the ubiquitous rs13107325 (cluster 2), and one, in cluster 4, in an intron of NUAK1 ( ARK5 ) 15 , 16 , 17 , which has been associated with tau pathology 18 (Table  1 /Supplementary Data  1 ). On the other hand, of the seven genetic clusters, three were entirely novel (clusters 3, 6 and 7), and not found in other brain imaging studies, including our most recent work that expanded on our previous GWAS of all of the brain IDPs available in UK Biobank 19 by including more participants—in fact, the same number of participants as analysed in this present work—and, crucially, by also including the X chromosome 20 (Table  1 /Supplementary Data  1 ). This suggests that, beyond the genetic hits that were meaningfully associated with the LIFO brain network and an array of relevant risk factors, lifestyle variables and brain disorders, and found in a few other imaging GWAS, some of the genetic underpinnings of the LIFO network are intrinsically specific to it and to no other pre-existing imaging phenotype.

All five autosomal genetic clusters identified through the GWAS of the LIFO phenotype had relevant associations with risk factors for dementia (Results; Supplementary Data  1 ), including precisely two of the best MRFs (for clusters 2 and 5), and three of them directly related in UK Biobank to the two diseases showing a pattern of brain abnormalities following the LIFO network: schizophrenia (clusters 2 and 4) and Alzheimer’s disease (cluster 1) (Supplementary Data  1 ). In particular, cluster 2 has its lead variant rs13107325 in an exon of one of the most pleiotropic genes ZIP8 , which codes for a zinc and metal transporter. Considering the vulnerability of the LIFO brain network to adolescent-onset schizophrenia and its significant association with fluid intelligence that we previously demonstrated 8 , it is notable that this variant has been associated genome-wide with schizophrenia 6 , as well as intelligence, educational attainment and mathematics ability 5 , 21 . In line with the LIFO brain network being both prone to accelerated ageing and susceptible to Alzheimer’s disease, this genetic locus has also been associated genome-wide with well-known risk factors for dementia. These comprise alcohol—including the exact same variable of “alcohol intake frequency” as identified as one of the best MRFs—cholesterol, weight, sleep—including “sleep duration”—and blood pressure 22 , 23 , 24 , 25 , 26 , all of which significantly contribute to modulating the LIFO brain network when considered separately (Table  2 /Supplementary Data  3 ). Of relevance, this genetic locus is also associated to an increased risk of cardiovascular death 27 . Cluster 5, a large genetic cluster in the MAPT region (Microtubule-Associated Protein Tau), comprised in total 3906 significant variants (Supplementary Data  4 ). This genetic region plays a role in various neurodegenerative disorders related to mutations of the protein tau, such as frontotemporal dementia 28 and progressive supranuclear palsy 29 , but also, of particular pertinence to the LIFO brain network, Alzheimer’s and Parkinson’s disease, with a genetic overlap between these two diseases in a locus included in our significant cluster 5 (rs393152, β  = −0.09, P  = 6.35 × 10 −14 ) 4 . Despite the relatively low number of people with diagnosed Alzheimer’s disease in the genetic discovery cohort, we were able to establish—albeit with small effect sizes—a significant mediation role for the LIFO brain regions between the lead bi-allelic variant for cluster 5 and this Alzheimer’s diagnosis, suggesting once more the importance played by these vulnerable brain areas in unhealthy ageing.

Finally, of the seven clusters, two were located in the pseudo-autosomal region (PAR1) of the sex chromosomes corresponding to the genes XG and CD99 , coding for the two antigens of the XG blood group. This blood group system has been largely neglected, its main contribution related to the mapping of the X chromosome itself, and its clinical role remains elusive 30 . In order to investigate further the possible role of these two variants of the XG blood group, we examined out-of-sample their associations with thousands of non-imaging phenotypes. This analysis revealed that the first of these two loci was significantly and consistently associated with early life factors, environmental factors and health outcomes, including particulate matter and nitrogen dioxide air pollution, the second most deleterious MRF to the LIFO brain network (Supplementary Data  2 ). Whether these associations are due to stratification or genotyping artefacts, or to the fact that this specific variant, which is inherited from a parent, has a parental impact that modulates the effect of early life environment of the UK Biobank participants, the so-called “nature of nurture”, will need further investigation 31 .

Intriguingly, an analysis revealed that the genes involved in the loci associated with the LIFO network (Table  1 /Supplementary Data  1 ) are enriched for the gene ontology terms of leucocyte extravasation, namely “positive regulation of neutrophil extravasation” ( P  = 4.75 × 10 −6 ) and “T cell extravasation” ( P  = 4.75 × 10 −6 ). This result held when removing the genes included in the MAPT extended region (with P  = 2.54 × 10 −6 and P  = 2.54 × 10 −6 , respectively). Leucocyte extravasation facilitates the immune and inflammatory response, and there has been renewed focus on the fact that a breakdown of the blood-brain barrier together with leukocyte extravasation might contribute to both Alzheimer’s disease and schizophrenia 32 , 33 . In line with the enrichment findings, 4 out of the 7 genetic clusters associated with the LIFO network are correlated in UK Biobank blood assays with percentage or count of immune cells (neutrophil, lymphocyte, platelet, monocyte, etc.; Supplementary Data  1 ).

Regarding MRFs’ effects on the LIFO brain network, diabetes and alcohol consumption have been consistently shown to be associated with both cerebral and cognitive decline 34 , 35 . On the other hand, pollution—and notably that of nitrogen oxides—has emerged more recently as a potential MRF for dementia 2 , 36 . In particular, the increase of dementia risk due to nitrogen oxide pollution, a proxy for traffic-related air pollution, seems to be enhanced by cardiovascular disease 37 . In this study, we found that nitrogen dioxide pollution has one of the most deleterious effects onto the fragile LIFO brain regions. This effect could only be unmasked by regressing out the effects of age and sex, as traffic-related air pollution is modestly inversely-correlated with age (Supplementary Data  5 ). It is also worth noting that including age and sex as confounding variables in the first stage of our analysis reduced considerably the contribution of what had appeared at first—before regression—as the most harmful risk factors: blood pressure, cholesterol and weight (Table  2 /Supplementary Data  3 ). Furthermore, the benefit of examining these MRFs in a single model in the second stage of our analysis is that we can assess the unique contribution of each of these factors on the LIFO brain network; in doing so, blood pressure, cholesterol and weight were no longer significant (Table  3 ).

One defining characteristic of the LIFO brain network is how much age explains its variance. Indeed, in the dataset covering most of the lifespan that was initially used to identify the LIFO and spatially define it 8 , age explained 50%. In the UK Biobank imaging project, where imaged participants are over 45 years old, age explained 30% (Fig.  1 ). It is thus perhaps unsurprising that, while the explained variance by each of the MRFs varies widely (Table  2 /Supplementary Data  3 ), it reduces notably once the effect of age and other confounders has been regressed out (without confounders included in the model: maximum 8.4%; with confounders: maximum 0.5%). Combined, the 12 best MRFs explained a significant 1.5% of the effect on the vulnerable brain network after regressing out age, head size and sex effects. Regarding the genetic hits, we found a significant heritability with h 2  = 0.15, in keeping with our results for structural brain phenotypes (except for subcortical and global brain volumes, which demonstrate higher heritability 19 ).

The uniqueness of this study relies on the fact that we combined the strengths of two different cohorts: the first, which revealed the LIFO grey matter network, is lifespan, demonstrating the mirroring of developmental and ageing processes in the LIFO brain areas, something that could never be achieved with UK Biobank because of its limited age range. Of note, for this initial work with the lifespan cohort 8 , we not only included grey matter partial volume images, as done in this current study, but also Freesurfer information of cortical thickness and surface area. The LIFO network showed no contribution from Freesurfer cortical thickness or area. This might hint at processes that only partial volume maps are able to detect due to the LIFO network’s specific localisation, including in the cerebellum and subcortical structures, which are not included in the area and thickness surface methods from Freesurfer.

Limitations of our study pertain to the nature of the data itself and the way each variable is encoded in the UK Biobank (binary, ordinal, categorical, continuous), the number of missing values, what is offered as variables for each modifiable risk factor category (e.g. we chose not to create any compound variables, such as the ratio of cholesterol levels or systolic and diastolic blood pressures), and the curation of each of these variables. Some of the factors might be proxies for another category, but including the ‘best’ ones in a single model alleviate these issues to some extent. Another limitation is the assumption in our models that each risk factor has a linear, additive effect on the vulnerable LIFO brain network. It is also important to note that cross-sectional and longitudinal patterns of brain ageing can differ, as has been shown for instance for adult span trajectories of episodic and semantic memory, especially in younger adults 38 . A recent study has also demonstrated a specific ‘brain age’ imaging measure to be more related to early life influences on brain structure than within-person rates of change in the ageing brain 39 . Further work will be needed to establish how the LIFO network data changes in terms of within-person trends, for instance by investigating the growing UK Biobank longitudinal imaging database. While we took care of assessing the replicability of our genetic results by randomly assigning a third of our dataset for such purposes (all our significant genetic hits were replicated), this was performed within the UK Biobank cohort that exhibits well-documented biases, being well-educated, less deprived, and healthier than the general population, especially for its imaging arm 40 . Independent replications will be needed to confirm the existence of the LIFO-associated genetic loci.

In conclusion, our study reveals the modifiable and non-modifiable factors associated with some of the most fragile parts of the brain particularly vulnerable to ageing and disease process. It shows that, above and beyond the effect of age and sex, the most deleterious modifiable risk factors to this brain network of higher-order regions are diabetes, pollution and alcohol intake. Genetic factors are related to immune and inflammatory response, tau pathology, metal transport and vascular dysfunction, as well as to the XG blood group system from the pseudo-autosomal region of the sex chromosomes, and meaningfully associated with relevant modifiable risk factors for dementia. The unprecedented genome-wide discovery of the two variants on the sex chromosomes in this relatively unexplored blood group opens the way for further investigation into its possible role in underlying unhealthy ageing.

Supplementary Information is available for this paper.

For the present work the imaging cohort of UK Biobank was used and we included 39,676 subjects who had been scanned and for whom the brain scans had been preprocessed at the time of the final set of analyses (M/F 47–53%; 44–82 years, mean age 64 ± 7 years; as of October 2020) 41 , 42 . Structural T1-weighted scans for each participant were processed using the FSL-VBM automated tool to extract their grey matter map 43 , 44 . The ‘last in, first out’ (LIFO) network of mainly higher-order brain regions was initially identified by performing a linked independent component analysis on the grey matter images of another, lifespan observational cohort of 484 subjects 8 , 45 , 46 . This map of interest, along with the other 69 generated by the analysis, was first realigned to the UK Biobank ‘standard’ space defined by the grey matter average across the first 15,000 participants, then regressed into the UK Biobank participants’ grey matter data, to extract weighted average values of grey matter normalised volume inside each of the z-maps, using the z-score as weighting factor. This made it possible to assess the unique contribution of this specific LIFO map, above and beyond all the rest of the brain represented in the other 69 maps. At the end of this process, we obtained a single imaging measure for each of the 39,676 participants, i.e. a ‘loading’ corresponding to their amount of grey matter normalised volume in the LIFO brain network.

Human participants: UK Biobank has approval from the North West Multi-Centre Research Ethics Committee (MREC) to obtain and disseminate data and samples from the participants ( http://www.ukbiobank.ac.uk/ethics/ ), and these ethical regulations cover the work in this study. Written informed consent was obtained from all of the participants.

Modifiable risk factors selection

The following 15 categories of modifiable risk factors (MRFs) for dementia were investigated based on previous literature: blood pressure, diabetes, cholesterol, weight, alcohol, smoking, depression, hearing, inflammation, pollution, sleep, exercise, diet/supplementation, socialisation, and education. These included well-documented cerebrovascular risk factors, and in particular included all of the 12 modifiable risk factors considered in the updated Lancet commission on dementia, with the sole exception of traumatic brain injury 3 . For each category, several MRF variables from UK Biobank were very minimally pre-processed ( Supplementary Information ). In total, 161 MRF variables were obtained. To optimise the interpretability of the results, and to be able to relate them to previous findings, we did not carry out any data reduction, which would have prevented us from identifying exactly which variable—and subsequently, which genetic component for this specific variable—contribute to the effect. For these same reasons, we did not create any compound variable.

Statistical analyses

Genome-wide association study.

We followed the same protocol we had developed for the first genome-wide association study (GWAS) with imaging carried out on UK Biobank 19 . Briefly, we examined imputed UK Biobank genotype data 47 , and restricted the analysis to samples that were unrelated (thereby setting aside only ~450 participants), without aneuploidy and with recent UK ancestry. To account for population stratification, 40 genetic principal components were used in the genetic association tests as is recommended for UK Biobank genetic studies 19 , 20 , 47 . We excluded genetic variants with minor allele frequency <0.01 or INFO score <0.03 or Hardy-Weinberg equilibrium –log 10 ( P ) > 7. We then randomly split the samples into a discovery set with 2/3 of the samples ( n  = 22,128) and a replication set with 1/3 of the samples ( n  = 11,083). We also examined the X chromosome with the same filters, additionally excluding participants with sex chromosome aneuploidy: 12 in non-pseudoautosomal region (PAR) and 9 in PAR for the discovery set, 3 in non-PAR and 6 in PAR for the replication set. Variants were considered significant at –log 10 ( P ) > 7.5, and replicated at P  < 0.05.

Modifiable risk factor study

In the first stage, the general linear model was used to investigate, separately, the association between each of these 161 MRFs and the LIFO network loadings in all the scanned UK Biobank participants ( n  = 39,676). We ran each model twice: once as is, and once adding 6 confounders: age, age 2 , sex, age × sex, age 2 × sex, and head size, to estimate the contribution of these MRFs on the LIFO network above and beyond the dominating effects of age and sex. Sex was based on the population characteristics entry of UK Biobank. This is a mixture of the sex the NHS had recorded for the participant at recruitment, and updated self-reported sex. For the GWAS, both sex and genetic sex were used (the sample was excluded in case of a mismatch). In total, 32 variables tailored to structural imaging had been considered as possible confounders, and we retained those with the strongest association ( R 2  ≥ 0.01; see  Supplementary Information ). Socioeconomic status via the Townsend deprivation index was also considered as a possible confounding variable but explained little variance ( R 2  < 0.001) and thus was not included as a confounder.

MRFs were not considered further if they were not significant—not surviving Bonferroni-correction, i.e., P  > 1.55 × 10 −4 —and if more than 5% of the subjects had their MRF values missing. For each category, a single ‘best’ MRF was then selected as the variable with the highest R 2 among those remaining, after regressing out the confounding effects of age and sex.

In the second stage, all these best MRFs were then included in a single general linear model, together with the same 6 confounders used in the first stage, to assess the unique contribution of each factor on the LIFO brain network loadings. A prerequisite to carry out this single general linear model analysis was to only include participants who would have values for all best MRFs and confounders. This explains the additional criterion of only including MRFs that had no more than 5% of values missing, to ensure that the final sample of participants who had values for all these best and confounding factors would not be biased compared with the original sample—something we formally tested (see  Supplementary Information )—especially as data are not missing at random in UK Biobank, and exhibit some genetic structure 48 . The sample was therefore reduced to a total of 35,527 participants for this second stage analysis (M/F 17,290–18,237; 45–82 years, mean 64 ± 7 years). The effect of these best MRFs taken altogether was considered significant with a very conservative Bonferroni correction for multiple comparisons across all combinations of every possible MRF from each of the initial 15 MRF categories ( P  < 4.62 × 10 −17 , see  Supplementary Information for more details). In addition, both full and partial correlations were computed for the same set of best MRFs and confounders, in order to assess possible relationships between variables.

Post hoc genetic analyses

Chromosome 17 inversion.

We investigated chromosome 17 inversion status of the participants in the discovery cohort by considering their genotype on 32 variants that tag chromosome 17 inversion according to Steinberg et al. 11 . Of these 32 variants, 24 were present in our genetic data. We labelled the participants homozygous inverted, heterozygous, or homozygous direct (not inverted) when all 24 of these alleles indicated the same zygosity. This yielded an unambiguous inversion status for 21,969 participants (99% of the discovery cohort). To examine if the association between the non-triallelic lead variant of the MAPT genetic cluster (rs2532395, Table  1 /Supplementary Data  1 ) and the LIFO network was independent from this common inversion, we determined inversion/direct status of the discovery cohort and: 1. repeated the association test between rs2532395 and the LIFO phenotype, with chromosome 17 inversion status added as a confounder; and 2. correlated the genotype for rs2532395 with chromosome 17 inversion.

Causality within each genetic cluster

We used CAVIAR (Causal Variants Identification in Associated Regions 49 ) to assess causality of variants that passed the genome-wide significance threshold in each of the genetic clusters we report. CAVIAR uses a Bayesian model and the local linkage disequilibrium structure to assign posterior probabilities of causality to each variant in a region, given summary statistics for an association. We did not perform CAVIAR analysis on the genetic cluster on chromosome 17, as its non-triallelic lead variant (rs2532395) was strongly correlated with chromosome 17 inversion, and the LD matrix was large and low rank. We excluded the X chromosome loci from this analysis due to the difficulty in assessing LD in this chromosome.

Enrichment analysis

Based on the genes listed in the ‘Genes’ column of Table  1 /Supplementary Data  1 , we performed an enrichment analysis for the genes associated with the LIFO brain network using PANTHER 50 . PANTHER determines whether a gene function is overrepresented in a set of genes, according to the gene ontology consortium 51 , 52 .

Mediation analysis between MAPT top variant and Alzheimer’s disease, via the LIFO brain network

As the gene MAPT is associated with Alzheimer’s disease, and as we found a significant association between MAPT and the LIFO brain network, we examined to what extent the effect of MAPT is mediated by the LIFO brain regions. We conducted a mediation analysis using the counterfactual framework in which the average indirect effect of the treatment on the outcome through the mediator is nonparametrically identified (version 4.5.0 of the R package ‘mediation' 53 ). This is a general approach that encompasses the classical linear structural equation modelling framework for causal mediation, allowing both linear and non-linear relationships. In this analysis, the genotype for the lead bi-allelic variant of the MAPT association was used as the treatment, the LIFO loadings as the mediator, and Alzheimer’s disease diagnosis as the outcome.

From the ~43 K UK Biobank participants who had been scanned, we searched for those who had been diagnosed with Alzheimer’s disease specifically, regardless of whether this diagnosis occurred before, or after their brain scans. Based on hospital inpatient records (ICD10: F000, F001, F002, F009, G300, G301, G308, and G309 and ICD9: 3310) and primary care (GP) data (Eu00., Eu000, Eu001, Eu002, Eu00z, F110., F1100, F1101, Fyu30, X002x, X002y, X002z, X0030, X0031, X0032, X0033, XaIKB, XaIKC, and XE17j), we identified 65 such cases— UK Biobank being healthier than the general population, and those scanned showing an even stronger healthy bias—of which 34 were included in the discovery set after QC.

We considered two conditions for the effect of the treatment on the outcome. First, a dominant condition in which the minor allele is assumed to be dominant and for which at least one copy of the minor allele is considered treated. Second, a recessive condition in which the minor allele is assumed to be recessive. We considered that either condition was nominally significant if the confidence interval of the average causal mediated effect did not intersect zero, and had an associated P  < 0.05 ÷ 2 (correcting for the two conditions). We assessed confidence intervals and P -values using 50,000 bootstrapped samples.

Associations between the LIFO brain network’s genetic hits and the MRFs

First, we reported in Table  1 / Supplementary Data  1 the significant associations between the LIFO genetic hits and UK Biobank variables related to the 15 categories listed for the MRFs. For this, we used the Open Targets Genetics website, which reports the GWAS carried out in UK Biobank ( https://genetics .opentargets.org/ ). Second, we assessed whether there was any genetic overlap between the known genetic components of the 3 best MRFs and the LIFO phenotype. Again, we used the Open Targets Genetics website outputs for these 3 very specific UK Biobank variables, and compared the significant hits for these 3 best MRFs within ±250 kbp of, or in high LD (>0.8) with, our own LIFO variants. If reported hits were limited, we also searched online for GWAS done on similar variables. Finally, we also included the list of significant hits for diabetes 54 , which focused on a potential genetic overlap between diabetes and Alzheimer’s disease.

Post hoc association for the sex chromosomes variants

The allele counts of each participant for two specific significant variants of the sex chromosomes not—or hardly—available in open databases such as https://genetics.opentargets.org/ 55 were further associated out-of-sample with all non-imaging phenotypes of UK Biobank ( n  = 16,924). This analysis was carried out in the entire genotyped, quality-controlled sample where participants who had been scanned were removed (final sample: 374,230 participants), taking into account the population structure (40 genetic principal components), as well as the confounding effects of age, sex, age x sex, age 2 and age 2 x sex. Results were corrected for multiple comparisons across all non-imaging phenotypes and the two variants.

Heritability

We examined the heritability of the LIFO phenotype, and the coheritability between the LIFO network and Alzheimer’s disease or schizophrenia using LDSC 56 . This method uses regression on summary statistics to determine narrow sense heritability h 2 of a trait, or the shared genetic architecture between two traits. LDSC corrects for bias LD structure using LD calculated from a reference panel (we used LD from the Thousand Genomes Project Phase 1 57 ). We obtained summary statistics for a meta-analysis of Alzheimer’s disease involving 71,880 cases and 383,378 controls 58 . The number of genetic variants in the intersection between the summary statistics was 1,122,435. For schizophrenia, the summary statistics were obtained from a meta-analysis involving 53,386 cases and 77,258 controls 59 . A total of 1,171,319 genetic variants were in the intersection with the summary statistics for LIFO. For both Alzheimer’s and schizophrenia, the X chromosome was not included in the heritability calculation, as it was excluded from the meta-analysis that we sourced the summary statistics from.

Reproducibility

No data was excluded for the MRF analyses. For the genetic analyses, these were restricted to samples that were unrelated, without aneuploidy and with recent UK ancestry (see above).

No statistical method was used to predetermine sample size. The experiments were not randomised. The Investigators were not blinded to allocation during experiments and outcome assessment.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

All the FLICA decomposition maps − including the LIFO grey matter network − in UK Biobank standard space, the UK Biobank grey matter template, scripts, and the LIFO loadings for all of the participants are freely available on a dedicated webpage: open.win.ox.ac.uk/pages/douaud/ukb-lifo-flica/ .

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Acknowledgements

We are grateful to Profs Christian K. Tamnes, Lars T. Westlye, Kristine B. Walhovd and Anders M. Fjell, and Dr Andreas Engvig for providing the lifespan cohort which was used to initially derive the original ‘last in, first out’ brain network map, and to Prof Augustine Kong for helpful discussion on the associations between the PAR hit and early life and environmental factors. G.D. was supported by a UK MRC Career Development Fellowship (MR/K006673/1) and a Wellcome Collaborative Award (215573/Z/19/Z). S.S. was supported by Wellcome (203139/Z/16/Z; 215573/Z/19/Z). L.E. was funded by NSERC grants (RGPIN/05484-2019; DGECR/00118-2019) and a Michael Smith Health Research BC Scholar Award. A.M.W. received support through the NIH Intramural Research Program (ZIA-MH002781; ZIA-MH002782). This research was funded in whole, or in part, by the Wellcome Trust (215573/Z/19/Z; 203139/Z/16/Z; 203139/A/16/Z). For the purpose of Open Access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. This research was also supported by the NIHR Oxford Health Biomedical Research Centre (NIHR203316). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. The Wellcome Centre for Integrative Neuroimaging is supported by core funding from the Wellcome Trust (203139/Z/16/Z and 203139/A/16/Z).

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These authors contributed equally: Lloyd T. Elliott, Anderson M. Winkler.

Authors and Affiliations

FMRIB Centre, Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK

Jordi Manuello, Paul McCarthy, Fidel Alfaro-Almagro, Soojin Lee, Stephen Smith & Gwenaëlle Douaud

FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy

Jordi Manuello

Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, Canada

Joosung Min & Lloyd T. Elliott

Pacific Parkinson’s Research Centre, The University of British Columbia, Vancouver, BC, Canada

National Institutes of Mental Health, National Institutes of Health, Bethesda, MD, USA

Anderson M. Winkler

Department of Human Genetics, University of Texas Rio Grande Valley, Brownsville, TX, USA

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G.D. conceived and supervised the work, and carried out some of the genetic and modifiable risk factors analyses. J.Ma. carried out most of the genetic and modifiable risk factors analyses. J.Mi., S.L., A.M.W., and L.T.E. carried out additional genetics analyses. G.D., P. McC., F.A.-A., S.S., and L.T.E. created/extracted the imaging and genetics data, and organised the non-imaging data and confound variables. L.T.E. co-supervised the genetic analyses. A.M.W. co-supervised the modifiable risk factor analyses. G.D. interpreted the results and wrote the paper. J.Ma., S.S., L.T.E., and A.M.W. revised the paper.

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Correspondence to Gwenaëlle Douaud .

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Manuello, J., Min, J., McCarthy, P. et al. The effects of genetic and modifiable risk factors on brain regions vulnerable to ageing and disease. Nat Commun 15 , 2576 (2024). https://doi.org/10.1038/s41467-024-46344-2

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DOI : https://doi.org/10.1038/s41467-024-46344-2

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• The framework continues to evolve and update as new information becomes available.

President George H. W. Bush proclaimed  the 1990s “ The Decade of the Brain  ,” urging the National Institutes of Health, the National Institute of Mental Health (NIMH), and others to raise awareness about the benefits of brain research.

“Over the years, our understanding of the brain—how it works, what goes wrong when it is injured or diseased—has increased dramatically. However, we still have much more to learn,” read the president’s proclamation. “The need for continued study of the brain is compelling: millions of Americans are affected each year by disorders of the brain…Today, these individuals and their families are justifiably hopeful, for a new era of discovery is dawning in brain research.”

Still, despite the explosion of new techniques and tools for studying the brain, such as functional magnetic resonance imaging (fMRI), many mental health researchers were growing frustrated that their field was not progressing as quickly as they had hoped.

For decades, researchers have studied mental disorders using diagnoses based on the Diagnostic and Statistical Manual of Mental Disorders (DSM)—a handbook that lists the symptoms of mental disorders and the criteria for diagnosing a person with a disorder. But, among many researchers, suspicion was growing that the system used to diagnose mental disorders may not be the best way to study them.

“There are many benefits to using the DSM in medical settings—it provides reliability and ease of diagnosis. It also provides a clear-cut diagnosis for patients, which can be necessary to request insurance-based coverage of healthcare or job- or school-based accommodations,” said Bruce Cuthbert, Ph.D., who headed the workgroup that developed NIMH’s Research Domain Criteria Initiative. “However, when used in research, this approach is not always ideal.”

Researchers would often test people with a specific diagnosed DSM disorder against those with a different disorder or with no disorder and see how the groups differed. However, different mental disorders can have similar symptoms, and people can be diagnosed with several different disorders simultaneously. In addition, a diagnosis using the DSM is all or none—patients either qualify for the disorder based on their number of symptoms, or they don’t. This black-and-white approach means there may be people who experience symptoms of a mental disorder but just miss the cutoff for diagnosis.

Dr. Cuthbert, who is now the senior member of the RDoC Unit which orchestrates RDoC work, stated that “Diagnostic systems are based on clinical signs and symptoms, but signs and symptoms can’t really tell us much about what is going on in the brain or the underlying causes of a disorder. With modern neuroscience, we were seeing that information on genetic, pathophysiological, and psychological causes of mental disorders did not line up well with the current diagnostic disorder categories, suggesting that there were central processes that relate to mental disorders that were not being reflected in DMS-based research.”

Road to evolution

Concerned about the limits of using the DSM for research, Dr. Cuthbert, a professor of clinical psychology at the University of Minnesota at the time, approached Dr. Thomas Insel (then NIMH director) during a conference in the autumn of 2008. Dr. Cuthbert recalled saying, “I think it’s really important that we start looking at dimensions of functions related to mental disorders such as fear, working memory, and reward systems because we know that these dimensions cut across various disorders. I think NIMH really needs to think about mental disorders in this new way.”

Dr. Cuthbert didn’t know it then, but he was suggesting something similar to ideas that NIMH was considering. Just months earlier, Dr. Insel had spearheaded the inclusion of a goal in NIMH’s 2008 Strategic Plan for Research to “develop, for research purposes, new ways of classifying mental disorders based on dimensions of observable behavior and neurobiological measures.”

Unaware of the new strategic goal, Dr. Cuthbert was surprised when Dr. Insel's senior advisor, Marlene Guzman, called a few weeks later to ask if he’d be interested in taking a sabbatical to help lead this new effort. Dr. Cuthbert soon transitioned into a full-time NIMH employee, joining the Institute at an exciting time to lead the development of what became known as the Research Domain Criteria (RDoC) Framework. The effort began in 2009 with the creation of an internal working group of interdisciplinary NIMH staff who identified core functional areas that could be used as examples of what research using this new conceptual framework looked like.

The workgroup members conceived a bold change in how investigators studied mental disorders.

“We wanted researchers to transition from looking at mental disorders as all or none diagnoses based on groups of symptoms. Instead, we wanted to encourage researchers to understand how basic core functions of the brain—like fear processing and reward processing—work at a biological and behavioral level and how these core functions contribute to mental disorders,” said Dr. Cuthbert.

This approach would incorporate biological and behavioral measures of mental disorders and examine processes that cut across and apply to all mental disorders. From Dr. Cuthbert’s standpoint, this could help remedy some of the frustrations mental health researchers were experiencing.

Around the same time the workgroup was sharing its plans and organizing the first steps, Sarah Morris, Ph.D., was a researcher focusing on schizophrenia at the University of Maryland School of Medicine in Baltimore. When she first read these papers, she wondered what this new approach would mean for her research, her grants, and her lab.

She also remembered feeling that this new approach reflected what she was seeing in her data.

“When I grouped my participants by those with and without schizophrenia, there was a lot of overlap, and there was a lot of variability across the board, and so it felt like RDoC provided the pathway forward to dissect that and sort it out,” said Dr. Morris.

Later that year, Dr. Morris joined NIMH and the RDoC workgroup, saying, “I was bumping up against a wall every day in my own work and in the data in front of me. And the idea that someone would give the field permission to try something new—that was super exciting.”

The five original RDoC domains of functioning were introduced to the broader scientific community in a series of articles published in 2010  .

To establish the new framework, the RDoC workgroup (including Drs. Cuthbert and Morris) began a series of workshops in 2011 to collect feedback from experts in various areas from the larger scientific community. Five workshops were held over the next two years, each with a different broad domain of functioning based upon prior basic behavioral neuroscience. The five domains were called:

• Negative valence (which included processes related to things like fear, threat, and loss)
• Positive valence (which included processes related to working for rewards and appreciating rewards)
• Cognitive processes
• Social processes
• Arousal and regulation processes (including arousal systems for the body and sleep).

At each workshop, experts defined several specific functions, termed constructs, that fell within the domain of interest. For instance, constructs in the cognitive processes domain included attention, memory, cognitive control, and others.

The result of these feedback sessions was a framework that described mental disorders as the interaction between different functional processes—processes that could occur on a continuum from normal to abnormal. Researchers could measure these functional processes in a variety of complementary ways—for example, by looking at genes associated with these processes, the brain circuits that implement these processes, tests or observations of behaviors that represent these functional processes, and what patients report about their concerns. Also included in the framework was an understanding that functional processes associated with mental disorders are impacted and altered by the environment and a person’s developmental stage.

Preserving momentum

Over time, the Framework continued evolving and adapting to the changing science. In 2018, a sixth functional area called sensorimotor processes was added to the Framework, and in 2019, a workshop was held to better incorporate developmental and environmental processes into the framework.;

Since its creation, the use of RDoC principles in mental health research has spread across the U.S. and the rest of the world. For example, the Psychiatric Ratings using Intermediate Stratified Markers project (PRISM)   , which receives funding from the European Union’s Innovative Medicines Initiative, is seeking to link biological markers of social withdrawal with clinical diagnoses using RDoC-style principles. Similarly, the Roadmap for Mental Health Research in Europe (ROAMER)   project by the European Commission sought to integrate mental health research across Europe using principles similar to those in the RDoC Framework.;

Dr. Morris, who has acceded to the Head of the RDoC Unit, commented: “The fact that investigators and science funders outside the United States are also pursuing similar approaches gives me confidence that we’ve been on the right pathway. I just think that this has got to be how nature works and that we are in better alignment with the basic fundamental processes that are of interest to understanding mental disorders.”

The RDoC framework will continue to adapt and change with emerging science to remain relevant as a resource for researchers now and in the future. For instance, NIMH continues to work toward the development and optimization of tools to assess RDoC constructs and supports data-driven efforts to measure function within and across domains.

“For the millions of people impacted by mental disorders, research means hope. The RDoC framework helps us study mental disorders in a different way and has already driven considerable change in the field over the past decade,” said Joshua A. Gordon, M.D., Ph.D., director of NIMH. “We hope this and other innovative approaches will continue to accelerate research progress, paving the way for prevention, recovery, and cure.”

Publications

Cuthbert, B. N., & Insel, T. R. (2013). Toward the future of psychiatric diagnosis: The seven pillars of RDoC. BMC Medicine , 11 , 126. https://doi.org/10.1186/1741-7015-11-126  

Cuthbert B. N. (2014). Translating intermediate phenotypes to psychopathology: The NIMH Research Domain Criteria. Psychophysiology , 51 (12), 1205–1206. https://doi.org/10.1111/psyp.12342  

Cuthbert, B., & Insel, T. (2010). The data of diagnosis: New approaches to psychiatric classification. Psychiatry , 73 (4), 311–314. https://doi.org/10.1521/psyc.2010.73.4.311  

Cuthbert, B. N., & Kozak, M. J. (2013). Constructing constructs for psychopathology: The NIMH research domain criteria. Journal of Abnormal Psychology , 122 (3), 928–937. https://doi.org/10.1037/a0034028  

Garvey, M. A., & Cuthbert, B. N. (2017). Developing a motor systems domain for the NIMH RDoC program.  Schizophrenia Bulletin , 43 (5), 935–936. https://doi.org/10.1093/schbul/sbx095  

Insel, T. (2013). Transforming diagnosis . http://www.nimh.nih.gov/about/director/2013/transforming-diagnosis.shtml

Kozak, M. J., & Cuthbert, B. N. (2016). The NIMH Research Domain Criteria initiative: Background, issues, and pragmatics. Psychophysiology , 53 (3), 286–297. https://doi.org/10.1111/psyp.12518  

Morris, S. E., & Cuthbert, B. N. (2012). Research Domain Criteria: Cognitive systems, neural circuits, and dimensions of behavior. Dialogues in Clinical Neuroscience , 14 (1), 29–37. https://doi.org/10.31887/DCNS.2012.14.1/smorris  

Sanislow, C. A., Pine, D. S., Quinn, K. J., Kozak, M. J., Garvey, M. A., Heinssen, R. K., Wang, P. S., & Cuthbert, B. N. (2010). Developing constructs for psychopathology research: Research domain criteria. Journal of Abnormal Psychology , 119 (4), 631–639. https://doi.org/10.1037/a0020909  

• Presidential Proclamation 6158 (The Decade of the Brain) 
• Research Domain Criteria Initiative website
• Psychiatric Ratings using Intermediate Stratified Markers (PRISM)  
• Roadmap for Mental Health Research in Europe (ROAMER)  

The Cannabis-Schizophrenia Link Grows Stronger

Another cautionary tale about the significant risks of marijuana use..

Posted March 14, 2024 | Reviewed by Gary Drevitch

A 34-year-old male with cannabis use disorder (CUD) recently came into the addiction treatment center where I am the chief medical officer.

He reported having a full-blown psychotic incident before arriving and showed signs of schizophrenia during his time with us. Schizophrenia is a serious brain disorder that causes a person to think, feel, and behave abnormally, and can make daily functioning nearly impossible.

Three things to note about this situation with our resident: First, it’s rare for schizophrenia to show up in males in their 30s. The typical onset is late teens to early 20s for males, and late 20s to early 30s for females. Second, weed/marijuana/cannabis is indeed highly addictive for certain individuals, as it was for our resident.

Third, the episode points to the larger reality that cannabis is significantly more potent than it’s ever been. The result: We’re now in a whole new world regarding the psychological effects it can have on people.

Add the fact that cannabis is far more widely available than ever—as of January 1, 2024, it’s been legalized for recreational use in 24 states plus Washington, DC—and you see the scale of the growing challenge.

Not Your Parents' Marijuana

I warn people about the dangers of marijuana all the time, and in fact, I’ve posted about it on this site several times. The problem is that these kinds of warnings often get lost amid the avalanche of media and marketing messages that marijuana is safe, that it “cures” nearly everything, and that it won’t get you addicted.

Well, it can get you addicted. And if it does, it can wreak havoc on your life. Even if it doesn’t become an addiction, marijuana may trigger changes in the brain like it did with my patient. That can lead to serious problems like chronic psychosis and schizophrenia.

Marijuana is especially dangerous when used by people under age 25 whose brains are still developing. CUD can literally rewire the brains of young people, with disastrous long-term results.

Three facts about marijuana:

• In the 1990s, the average THC concentration of marijuana in the U.S. was about 4 percent. (THC, or Tetrahydrocannabinol, is the psychoactive part of the cannabis plant.) By 2018, average THC concentration had nearly quadrupled to more than 15 percent.
• Research has shown that people who start using marijuana before age 18 are four to seven times more likely to develop CUD.
• Marijuana has the potential to “switch on” certain genes that can lead to schizophrenia in young people. Males are at a higher risk for this than females, but it happens in both genders.

In a massive epidemiology study of 6.9 million Danes published in Psychological Medicine in May 2023, researchers found a clear link between cannabis use and schizophrenia onset. A key finding: Over the 50 years covered by the study, 30 percent of all schizophrenia diagnoses among the study cohort could have been prevented if men aged 21 to 30 had not developed CUD. (In other words, CUD often led to schizophrenia in those men.)

The researchers also found a clear correlation between the rising cannabis potency over time and the increasing rate of schizophrenia diagnoses. One snapshot: The potency of cannabis in Denmark rose from 13 percent THC on average in 2006 to 30 percent in 2016.

As the study authors put it, the increase in schizophrenia cases rose “completely in parallel” with the increasing potency of cannabis.

Words of Advice

Please consider the following, and share it with friends and loved ones:

• Avoid marijuana until you’re an adult. Better still, hold off until age 25 or older, based on the damage it can do to the developing brain.
• Avoid marijuana if you have a family history of schizophrenia or other mental illness.
• Avoid marijuana if you currently have schizophrenia or any other mental illness.
• Urge a loved one or friend who has schizophrenia to avoid marijuana.

We in the medical community must keep educating the public about the dangers of this drug. It is not harmless, and it can be addictive—especially in the potent form it often takes today. We need to keep getting the cautionary word out to counterbalance the overly positive hype that exists around marijuana. We need to share this information with family members, friends, and our patients who are using marijuana.

And lastly, we need to help those who are addicted to obtain treatment in a compassionate and nonjudgmental way. They are not criminals or bad people. Rather, in using marijuana, they are playing with fire regarding their mental health. Their risk of getting badly burned may be higher than they realize.

Hjorthøj C, Compton W, Starzer M, et al. Association between cannabis use disorder and schizophrenia stronger in young males than in females. Psychological Medicine . 2023.

National Institute on Drug Abuse. (2020). Is Marijuana Addictive? https://nida.nih.gov/publications/research-reports/marijuana/marijuana-…

Lantie Jorandby, M.D. , is a board-certified psychiatrist with certification in Addiction Psychiatry and Addiction Medicine. She’s the Chief Medical Officer of Lakeview Health Addiction Treatment & Recovery in Jacksonville, Florida.

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