research on bipolar disorder

Bipolar disorders

Affiliations.

• 1 Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Department of Pharmacology, University of Toronto, Toronto, ON, Canada; Brain and Cognition Discovery Foundation, Toronto, ON, Canada. Electronic address: [email protected].
• 2 Institute for Mental and Physical Health and Clinical Translation Strategic Research Centre, School of Medicine, Deakin University, Melbourne, VIC, Australia; Mental Health Drug and Alcohol Services, Barwon Health, Geelong, VIC, Australia; Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia; Centre for Youth Mental Health, Florey Institute for Neuroscience and Mental Health, Melbourne, VIC, Australia; Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia.
• 3 Department of Psychiatry, Adult Division, Kingston General Hospital, Kingston, ON, Canada; Department of Psychiatry, Queen's University School of Medicine, Queen's University, Kingston, ON, Canada; Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.
• 4 Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Centre for Youth Bipolar Disorder, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
• 5 Department of Psychiatry, Faculty of Medicine, University of Antioquia, Medellín, Colombia; Mood Disorders Program, Hospital Universitario San Vicente Fundación, Medellín, Colombia.
• 6 Copenhagen Affective Disorders Research Centre, Psychiatric Center Copenhagen, Rigshospitalet, Copenhagen, Denmark; Department of Psychiatry, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
• 7 Discipline of Psychiatry, Northern Clinical School, University of Sydney, Sydney, NSW, Australia; Department of Academic Psychiatry, Northern Sydney Local Health District, Sydney, Australia.
• 8 Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
• 9 Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada; Dauten Family Center for Bipolar Treatment Innovation, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
• 10 Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada.
• 11 Hospital Clinic, Institute of Neuroscience, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Spain.
• 12 Department of Psychiatry, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Psychiatric Research Unit, Psychiatric Centre North Zealand, Hillerød, Denmark.
• 13 Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London and South London and Maudsley National Health Service Foundation Trust, Bethlem Royal Hospital, London, UK.
• 14 Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
• PMID: 33278937
• DOI: 10.1016/S0140-6736(20)31544-0

Bipolar disorders are a complex group of severe and chronic disorders that includes bipolar I disorder, defined by the presence of a syndromal, manic episode, and bipolar II disorder, defined by the presence of a syndromal, hypomanic episode and a major depressive episode. Bipolar disorders substantially reduce psychosocial functioning and are associated with a loss of approximately 10-20 potential years of life. The mortality gap between populations with bipolar disorders and the general population is principally a result of excess deaths from cardiovascular disease and suicide. Bipolar disorder has a high heritability (approximately 70%). Bipolar disorders share genetic risk alleles with other mental and medical disorders. Bipolar I has a closer genetic association with schizophrenia relative to bipolar II, which has a closer genetic association with major depressive disorder. Although the pathogenesis of bipolar disorders is unknown, implicated processes include disturbances in neuronal-glial plasticity, monoaminergic signalling, inflammatory homoeostasis, cellular metabolic pathways, and mitochondrial function. The high prevalence of childhood maltreatment in people with bipolar disorders and the association between childhood maltreatment and a more complex presentation of bipolar disorder (eg, one including suicidality) highlight the role of adverse environmental exposures on the presentation of bipolar disorders. Although mania defines bipolar I disorder, depressive episodes and symptoms dominate the longitudinal course of, and disproportionately account for morbidity and mortality in, bipolar disorders. Lithium is the gold standard mood-stabilising agent for the treatment of people with bipolar disorders, and has antimanic, antidepressant, and anti-suicide effects. Although antipsychotics are effective in treating mania, few antipsychotics have proven to be effective in bipolar depression. Divalproex and carbamazepine are effective in the treatment of acute mania and lamotrigine is effective at treating and preventing bipolar depression. Antidepressants are widely prescribed for bipolar disorders despite a paucity of compelling evidence for their short-term or long-term efficacy. Moreover, antidepressant prescription in bipolar disorder is associated, in many cases, with mood destabilisation, especially during maintenance treatment. Unfortunately, effective pharmacological treatments for bipolar disorders are not universally available, particularly in low-income and middle-income countries. Targeting medical and psychiatric comorbidity, integrating adjunctive psychosocial treatments, and involving caregivers have been shown to improve health outcomes for people with bipolar disorders. The aim of this Seminar, which is intended mainly for primary care physicians, is to provide an overview of diagnostic, pathogenetic, and treatment considerations in bipolar disorders. Towards the foregoing aim, we review and synthesise evidence on the epidemiology, mechanisms, screening, and treatment of bipolar disorders.

Copyright © 2020 Elsevier Ltd. All rights reserved.

Publication types

• Research Support, Non-U.S. Gov't
• Anticonvulsants / therapeutic use
• Antidepressive Agents / therapeutic use
• Antimanic Agents / therapeutic use
• Antipsychotic Agents / therapeutic use
• Bipolar Disorder / classification*
• Bipolar Disorder / drug therapy*
• Bipolar Disorder / genetics
• Bipolar Disorder / psychology
• Carbamazepine / therapeutic use
• Cardiovascular Diseases / complications
• Cardiovascular Diseases / mortality
• Child Abuse / psychology
• Comorbidity
• Depressive Disorder, Major / drug therapy*
• Depressive Disorder, Major / genetics
• Depressive Disorder, Major / psychology
• Environmental Exposure / adverse effects
• Lamotrigine / therapeutic use
• Lithium / therapeutic use
• Mania / drug therapy
• Mania / psychology
• Suicide / psychology
• Suicide Prevention*
• Valproic Acid / therapeutic use
• Young Adult
• Anticonvulsants
• Antidepressive Agents
• Antimanic Agents
• Antipsychotic Agents
• Carbamazepine
• Valproic Acid
• Lamotrigine

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Bipolar Disorder

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Do you have periods of time when you feel unusually “up” (happy and outgoing, or irritable), but other periods when you feel “down” (unusually sad or anxious)? During the “up” periods, do you have increased energy or activity and feel a decreased need for sleep, while during the “down” times you have low energy, hopelessness, and sometimes suicidal thoughts? Do these symptoms of fluctuating mood and energy levels cause you distress or affect your daily functioning? Some people with these symptoms have a lifelong but treatable mental illness called bipolar disorder.

What is bipolar disorder?

Bipolar disorder is a mental illness that can be chronic (persistent or constantly reoccurring) or episodic (occurring occasionally and at irregular intervals). People sometimes refer to bipolar disorder with the older terms “manic-depressive disorder” or “manic depression.”

Everyone experiences normal ups and downs, but with bipolar disorder, the range of mood changes can be extreme. People with the disorder have manic episodes, or unusually elevated moods in which the individual might feel very happy, irritable, or “up,” with a marked increase in activity level. They might also have depressive episodes, in which they feel sad, indifferent, or hopeless, combined with a very low activity level. Some people have hypomanic episodes, which are like manic episodes, but not severe enough to cause marked impairment in social or occupational functioning or require hospitalization.

Most of the time, bipolar disorder symptoms start during late adolescence or early adulthood. Occasionally, children may experience bipolar disorder symptoms. Although symptoms may come and go, bipolar disorder usually requires lifelong treatment and does not go away on its own. Bipolar disorder can be an important factor in suicide, job loss, ability to function, and family discord. However, proper treatment can lead to better functioning and improved quality of life.

What are the symptoms of bipolar disorder?

Symptoms of bipolar disorder can vary. An individual with the disorder may have manic episodes, depressive episodes, or “mixed” episodes. A mixed episode has both manic and depressive symptoms. These mood episodes cause symptoms that last a week or two, or sometimes longer. During an episode, the symptoms last every day for most of the day. Feelings are intense and happen with changes in behavior, energy levels, or activity levels that are noticeable to others. In between episodes, mood usually returns to a healthy baseline. But in many cases, without adequate treatment, episodes occur more frequently as time goes on.

Some people with bipolar disorder may have milder symptoms than others. For example, hypomanic episodes may make an individual feel very good and productive; they may not feel like anything is wrong. However, family and friends may notice the mood swings and changes in activity levels as unusual behavior, and depressive episodes may follow hypomanic episodes.

Types of Bipolar Disorder

People are diagnosed with three basic types of bipolar disorder that involve clear changes in mood, energy, and activity levels. These moods range from manic episodes to depressive episodes.

• Bipolar I disorder is defined by manic episodes that last at least 7 days (most of the day, nearly every day) or when manic symptoms are so severe that hospital care is needed. Usually, separate depressive episodes occur as well, typically lasting at least 2 weeks. Episodes of mood disturbance with mixed features are also possible. The experience of four or more episodes of mania or depression within a year is termed “rapid cycling.”
• Bipolar II disorder is defined by a pattern of depressive and hypomanic episodes, but the episodes are less severe than the manic episodes in bipolar I disorder.
• Cyclothymic disorder (also called cyclothymia) is defined by recurrent hypomanic and depressive symptoms that are not intense enough or do not last long enough to qualify as hypomanic or depressive episodes.

“Other specified and unspecified bipolar and related disorders” is a diagnosis that refers to bipolar disorder symptoms that do not match the three major types of bipolar disorder outlined above.

What causes bipolar disorder?

The exact cause of bipolar disorder is unknown. However, research suggests that a combination of factors may contribute to the illness.

Bipolar disorder often runs in families, and research suggests this is mostly explained by heredity—people with certain genes are more likely to develop bipolar disorder than others. Many genes are involved, and no one gene can cause the disorder.

But genes are not the only factor. Studies of identical twins have shown that one twin can develop bipolar disorder while the other does not. Though people with a parent or sibling with bipolar disorder are more likely to develop it, most people with a family history of bipolar disorder will not develop it.

Brain Structure and Function

Research shows that the brain structure and function of people with bipolar disorder may differ from those of people who do not have bipolar disorder or other mental disorders. Learning about the nature of these brain changes helps researchers better understand bipolar disorder and, in the future, may help predict which types of treatment will work best for a person with bipolar disorder.

How is bipolar disorder diagnosed?

To diagnose bipolar disorder, a health care provider may complete a physical exam, order medical testing to rule out other illnesses, and refer the person for an evaluation by a mental health professional. Bipolar disorder is diagnosed based on the severity, length, and frequency of an individual’s symptoms and experiences over their lifetime.

Some people have bipolar disorder for years before it’s diagnosed for several reasons. People with bipolar II disorder may seek help only for depressive episodes and hypomanic episodes may go unnoticed. Misdiagnosis may happen because some bipolar disorder symptoms are like those of other illnesses. For example, people with bipolar disorder who also have psychotic symptoms can be misdiagnosed with schizophrenia. Some health conditions, such as thyroid disease, can cause symptoms like those of bipolar disorder. The effects of recreational and illicit drugs can sometimes mimic or worsen mood symptoms.

Conditions That Can Co-Occur With Bipolar Disorder

Many people with bipolar disorder also have other mental disorders or conditions such as anxiety disorders, attention-deficit/hyperactivity disorder (ADHD), misuse of drugs or alcohol, or eating disorders. Sometimes people who have severe manic or depressive episodes also have symptoms of psychosis, such as hallucinations or delusions. The psychotic symptoms tend to match the person’s extreme mood. For example, someone having psychotic symptoms during a depressive episode may falsely believe they are financially ruined, while someone having psychotic symptoms during a manic episode may falsely believe they are famous or have special powers.

Looking at symptoms over the course of the illness and the person’s family history can help determine whether a person has bipolar disorder along with another disorder.

How is bipolar disorder treated?

Treatment helps many people, even those with the most severe forms of bipolar disorder. Mental health professionals treat bipolar disorder with medications, psychotherapy, or a combination of treatments.

Medications

Certain medications can help control the symptoms of bipolar disorder. Some people may need to try several different medications before finding the ones that work best. The most common types of medications that doctors prescribe include mood stabilizers and atypical antipsychotics. Mood stabilizers such as lithium or valproate can help prevent mood episodes or reduce their severity. Lithium also can decrease the risk of suicide. While bipolar depression is often treated with antidepressant medication, a mood stabilizer must be taken as well, as an antidepressant alone can trigger a manic episode or rapid cycling in a person with bipolar disorder. Medications that target sleep or anxiety are sometimes added to mood stabilizers as part of a treatment plan.

Talk with your health care provider to understand the risks and benefits of each medication. Report any concerns about side effects to your health care provider right away. Avoid stopping medication without talking to your health care provider first. Read the latest medication warnings, patient medication guides, and information on newly approved medications on the Food and Drug Administration (FDA) website  .

Psychotherapy

Psychotherapy (sometimes called “talk therapy”) is a term for various treatment techniques that aim to help a person identify and change troubling emotions, thoughts, and behaviors. Psychotherapy can offer support, education, skills, and strategies to people with bipolar disorder and their families.

Some types of psychotherapy can be effective treatments for bipolar disorder when used with medications, including interpersonal and social rhythm therapy, which aims to understand and work with an individual’s biological and social rhythms. Cognitive behavioral therapy (CBT) is an important treatment for depression, and CBT adapted for the treatment of insomnia can be especially helpful as a component of the treatment of bipolar depression. Learn more on NIMH’s psychotherapies webpage .

Other Treatments

Some people may find other treatments helpful in managing their bipolar disorder symptoms.

• Electroconvulsive therapy (ECT) is a brain stimulation procedure that can help relieve severe symptoms of bipolar disorder. ECT is usually only considered if an individual’s illness has not improved after other treatments such as medication or psychotherapy, or in cases that require rapid response, such as with suicide risk or catatonia (a state of unresponsiveness).
• Transcranial Magnetic Stimulation (TMS) is a type of brain stimulation that uses magnetic waves, rather than the electrical stimulus of ECT, to relieve depression over a series of treatment sessions. Although not as powerful as ECT, TMS does not require general anesthesia and presents little risk of memory or adverse cognitive effects.
• Light Therapy is the best evidence-based treatment for seasonal affective disorder (SAD), and many people with bipolar disorder experience seasonal worsening of depression in the winter, in some cases to the point of SAD. Light therapy could also be considered for lesser forms of seasonal worsening of bipolar depression.

Complementary Health Approaches

Unlike specific psychotherapy and medication treatments that are scientifically proven to improve bipolar disorder symptoms, complementary health approaches for bipolar disorder, such as natural products, are not based on current knowledge or evidence. For more information, visit the National Center for Complementary and Integrative Health website  .

Coping With Bipolar Disorder

Living with bipolar disorder can be challenging, but there are ways to help yourself, as well as your friends and loved ones.

• Get treatment and stick with it. Treatment is the best way to start feeling better.
• Keep medical and therapy appointments and talk with your health care provider about treatment options.
• Take medication as directed.
• Structure activities. Keep a routine for eating, sleeping, and exercising.
• Try regular, vigorous exercise like jogging, swimming, or bicycling, which can help with depression and anxiety, promote better sleep, and is healthy for your heart and brain.
• Keep a life chart to help recognize your mood swings.
• Ask for help when trying to stick with your treatment.
• Be patient. Improvement takes time. Social support helps.

Remember, bipolar disorder is a lifelong illness, but long-term, ongoing treatment can help manage symptoms and enable you to live a healthy life.

Are there clinical trials studying bipolar disorder?

NIMH supports a wide range of research, including clinical trials that look at new ways to prevent, detect, or treat diseases and conditions—including bipolar disorder. Although individuals may benefit from being part of a clinical trial, participants should be aware that the primary purpose of a clinical trial is to gain new scientific knowledge to help others in the future. Researchers at NIMH and around the country conduct clinical trials with patients and healthy volunteers. Talk to a health care provider about clinical trials, their benefits and risks, and whether one is right for you. For more information, visit the NIMH clinical trials webpage .

Finding Help

Behavioral health treatment services locator.

This online resource, provided by the Substance Abuse and Mental Health Services Administration (SAMHSA), can help you locate mental health treatment facilities and programs. Find a facility in your state by searching SAMHSA’s online Behavioral Health Treatment Services Locator  . For additional resources, visit NIMH's Help for Mental Illnesses webpage .

If you or someone you know is in immediate distress or is thinking about hurting themselves, call or text the 988 Suicide & Crisis Lifeline   at 988 or chat at 988lifeline.org. You can also contact the Crisis Text Line    ( text HELLO to 741741 ). For medical emergencies, call 911.

Talking to a Health Care Provider About Your Mental Health

Communicating well with a health care provider can improve your care and help you both make good choices about your health. Find tips to help prepare for and get the most out of your visit . For additional resources, including questions to ask a provider, visit the Agency for Healthcare Research and Quality website  .

The information in this publication is in the public domain and may be reused or copied without permission. However, you may not reuse or copy images. Please cite the National Institute of Mental Health as the source. Read our copyright policy to learn more about our guidelines for reusing NIMH content.

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Genetic contributions to bipolar disorder: current status and future directions

Kevin s. o'connell.

1 Division of Mental Health and Addiction, NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo University Hospital, 0407Oslo, Norway

Brandon J. Coombes

2 Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA

Bipolar disorder (BD) is a highly heritable mental disorder and is estimated to affect about 50 million people worldwide. Our understanding of the genetic etiology of BD has greatly increased in recent years with advances in technology and methodology as well as the adoption of international consortiums and large population-based biobanks. It is clear that BD is also highly heterogeneous and polygenic and shows substantial genetic overlap with other psychiatric disorders. Genetic studies of BD suggest that the number of associated loci is expected to substantially increase in larger future studies and with it, improved genetic prediction of the disorder. Still, a number of challenges remain to fully characterize the genetic architecture of BD. First among these is the need to incorporate ancestrally-diverse samples to move research away from a Eurocentric bias that has the potential to exacerbate health disparities already seen in BD. Furthermore, incorporation of population biobanks, registry data, and electronic health records will be required to increase the sample size necessary for continued genetic discovery, while increased deep phenotyping is necessary to elucidate subtypes within BD. Lastly, the role of rare variation in BD remains to be determined. Meeting these challenges will enable improved identification of causal variants for the disorder and also allow for equitable future clinical applications of both genetic risk prediction and therapeutic interventions.

Definition of illness

Affective disorders are classified along a spectrum from unipolar depression to bipolar disorder (BD) type II and type I (Carvalho, Firth, & Vieta, 2020 ; Grande, Berk, Birmaher, & Vieta, 2016 ). The presence of recurring manic or hypomanic episodes alternating with euthymia or depressive episodes distinguishes BD from other affective disorders (American Psychiatric Association, 2013 ; World Health Organization et al., 1992 ). BD type I (BDI) is characterized by alternating manic and depressive episodes ( Fig. 1 ). Psychotic symptoms also occur in a majority of these patients which may lead to compromised functioning and hospitalization. The Diagnostic and Statistical Manual of Mental Disorder, Fifth Edition (DSM-5) also allows for individuals impaired by manic episodes without depression to still be diagnosed with BDI (American Psychiatric Association, 2013 ). In comparison, a diagnosis of BD type II (BDII) is based on the occurrence of at least one depressive and one hypomanic episode during the lifetime, but no manic episodes ( Fig. 1 ). A diagnosis of BD not otherwise specified or BD unspecified may be given when a patient has bipolar symptoms that do not fit within these major subtype categories. The DSM-5 also includes specifiers which define the clinical features of episodes and the course of the disorder, namely, anxious distress, mixed features, rapid cycling, melancholic features, atypical features, psychotic features (mood-congruent and mood-incongruent), catatonia, peripartum onset, and seasonal pattern (American Psychiatric Association, 2013 ). In addition, the DSM-5 includes schizoaffective BD as a distinct diagnosis wherein individuals suffer from psychotic symptoms as well as episodes of mania or depression (American Psychiatric Association, 2013 ).

Polarity of symptoms for bipolar disorder subtypes. Bipolar disorder type I is characterized by at least one manic episode. Bipolar disorder type II is characterized by at least one depressive and one hypomanic episode during the lifetime, but no manic episodes. Major depressive disorder does not include episodes of hypomania or mania.

Epidemiology

BD is projected to affect about 50 million people worldwide (GBD 2016 Disease and Injury Incidence and Prevalence Collaborators, 2017 ). The BD subtypes each have an estimated lifetime prevalence of approximately 1% (Merikangas et al., 2007 , 2011 ) although large ranges in lifetime prevalence have been reported (BDI: 0.1–1.7%, BDII: 0.1–3.0%) (Angst, 1998 ; Merikangas et al., 2007 , 2011 ). Most studies report no gender differences in the prevalence of BD; however, women may be at increased risk for BDII, rapid cycling, and mixed episodes (Diflorio & Jones, 2010 ; Nivoli et al., 2011 ). The mean age of onset of BD is at approximately 20 years. An earlier age of onset is associated with poorer prognosis, increased comorbidity, onset beginning with depression, and more severe depressive episodes, as well as longer treatment delays (Joslyn, Hawes, Hunt, & Mitchell, 2016 ). Additionally, initial depressive episodes may lead to a misdiagnosis of major depressive disorder until the onset of manic or hypomanic episodes necessary to confirm BD (Zimmerman, Ruggero, Chelminski, & Young, 2008 ).

BD is often comorbid with other psychiatric (Eser, Kacar, Kilciksiz, Yalçinay-Inan, & Ongur, 2018 ; Frías, Baltasar, & Birmaher, 2016 ; Salloum & Brown, 2017 ) and non-psychiatric disorders (Bortolato, Berk, Maes, McIntyre, & Carvalho, 2016 ; Correll et al., 2017 ; Vancampfort et al., 2016 ). It is estimated that >90% of BD patients have at least one lifetime comorbid disorder, and >70% present with three or more comorbid disorders during their lifetime (Merikangas et al., 2007 ). Such ubiquitous comorbidity within BD suggests the disturbance of multiple systems and pathways, and the presence of comorbidities is associated with increased premature mortality in BD when compared to the general population (Kessing, Vradi, McIntyre, & Andersen, 2015 ; Roshanaei-Moghaddam & Katon, 2009 ).

Classical genetic epidemiology

Family studies.

Genetic factors for BD were first investigated using twin, family, and adoption studies. These studies established that family history of BD is an important clinical predictor of The onset of mood disorders in a patient and that the risk of mood disorder decreases as the genetic distance from the proband increases (Craddock & Sklar, 2013 ; Merikangas & Yu, 2002 ). A large family-based Swedish study showed the risk of BD was as much as 7.9, 3.3, and 1.6 times higher for first-, second-, and third-degree relatives of BD probands, respectively, than those without a proband in their family (Song et al., 2015 ). In the largest family study to date in the Swedish cohort with over 2 million individuals, the transmission of BD was found to be statistically homogenous across family type (intact family, families without fathers, and adoptive families) (Kendler, Ohlsson, Sundquist, & Sundquist, 2020 ). This family-based study also estimated the heritability of BD, which is a measure of the proportion of variation in a given trait attributed to genetic variation, to be 44% (95% CI 36–48%). Estimates of heritability from twin studies, which compare the concordance of disease between monozygotic and dizygotic twins, were between 60% and 90% (Craddock & Sklar, 2013 ; Merikangas & Yu, 2002 ; Smoller & Finn, 2003 ). Furthermore, by comparing estimates from twin studies, the heritability of BD is among the highest of all other psychiatric and behavioral disorders (Bienvenu, Davydow, & Kendler, 2011 ).

It has also been well-established that familial risk of BD correlates with increased familial risk of other psychiatric disorders such as schizophrenia, depression, anxiety, drug abuse, attention-deficit hyperactivity disorder (ADHD), personality disorders, and autism spectrum disorder (ASD) (Craddock & Sklar, 2013 ; Kendler et al., 2020 ; Song et al., 2015 ). Schizophrenia, ASD, and depression have the strongest genetic correlations with BD as identified through family studies.

Cohort and population studies

Sample sizes of studies have rapidly increased as genetic studies of BD have moved from family-based designs to cohort and population-based designs. With these, computationally-efficient methods, such as linkage disequilibrium score regression (LDSC), have been developed to estimate both heritability and genetic correlation captured by the single nucleotide polymorphisms (SNPs) which are common locations in the genome where variation occurs between individuals and are measured on a genotyping array (Bulik-Sullivan et al., 2015a ).

Using this technique, the largest study of BD estimated an SNP-based heritability ( h 2 SNP ), which is a measure of the proportion of variation in a given trait attributed to the genetic variation captured by a genotyping array, of 18.6% (Mullins et al., 2020 ). Figure 2 compares the latest estimates of the twin-based heritability and h 2 SNP for BD to a range of psychiatric, behavioral, and neurological disorders (Bienvenu et al., 2011 ; Browne, Gair, Scharf, & Grice, 2014 ; Cross-Disorder Group of the Psychiatric Genomics Consortium, 2019 ; Demontis et al., 2019a ; Faraone & Larsson, 2019 ; Gatz et al., 2006 ; Jansen et al., 2019 ; Purves et al., 2020 ; Walters et al., 2018 ; Zilhão et al., 2017 ). BD has the greatest twin-based heritability estimate and, similar to other traits, also has a substantial proportion not captured by common variations.

Estimated heritability of psychiatric, behavioral, and neurological disorders. Mean twin-based and SNP-based (on liability scale) heritability for different psychiatric (BIP, bipolar disorder; SCZ, schizophrenia; ADHD, attention-deficit/hyperactivity disorder; MD, major depression; ANX, generalized anxiety disorder), behavioral (AN, anorexia nervosa; AUD, alcohol use disorder; CUD, cannabis use disorder), or neurological (ASD, autism spectrum disorder; AD, Alzheimer's disorder; OCD, obsessive-compulsive disorder; TS, Tourette's syndrome) disorders. Error bars are shown for SNP-based estimates from LDSC.

New methodologies have also allowed the genetic correlation between different traits to be estimated using the summary statistics from overlapping sets of common SNPs in different samples. A recent cross-disorder analysis of eight different psychiatric and neurological disorders found that BD is most strongly genetically correlated with schizophrenia ( r g  = 0.70) but also shares substantial genetic overlap with major depression ( r g  = 0.36), obsessive-compulsive disorder (OCD; r g  = 0.31), anorexia nervosa ( r g  = 0.21), ADHD ( r g  = 0.14), and ASD ( r g  = 0.14) (Cross-Disorder Group of the Psychiatric Genomics Consortium, 2019 ). Furthermore, the high comorbidity of substance use in BD has been linked to substantial genetic correlation with substance use: cigarette use ( r g  = 0.1), cannabis use ( r g  = 0.27), and alcohol use disorder ( r g  = 0.30) (Jang et al., 2020 ; Kranzler et al., 2019 ).

Molecular genetic epidemiology

Common variants.

Genome-wide association studies (GWASs) have been the most successful strategy for identifying specific genetic variants associated with BD. Unlike linkage studies, a GWAS can be performed on a set of unrelated cases and controls by testing for the association of genetic variants across the genome with a trait. The first GWAS of BD in 2007 included 2000 cases and 3000 controls and only identified one independent association signal at p  < 5 × 10 –7 (Wellcome Trust Case Control Consortium, 2007 ). This association was below the now established p  < 5 × 10 –8 threshold for genome-wide significance and further, this association was not supported in an expanded reference group analysis nor in an independent replication. Since then, dozens of additional GWASs of case–control cohorts, consisting of samples from mostly European ancestries, have been published ( Table 1 ). Until the sample size of the GWASs increased to over 10 K, these GWASs identified very few genome-wide significant loci. The most recent GWAS was based on a meta-analysis of 52 case–control cohorts and five large population-based cohorts and included over 40 K cases and 350 K controls identified 64 independent loci across the genome associated with BD (Mullins et al., 2020 ). Thirty-three of these loci were novel for BD, including the region containing the major histocompatibility complex which is also strongly associated with schizophrenia (Mullins et al., 2020 ; Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014 ). Furthermore, additional novel loci identified in this GWAS are also reported as risk loci for schizophrenia, depression, childhood-onset psychiatric disorders, and problematic alcohol use, highlighting shared underlying genetic architecture between BD and these other psychiatric disorders (Mullins et al., 2020 ). Still though, the SNPs in this large study only explain 15–18% of the variance in the trait (Mullins et al., 2020 ).

Summary of bipolar disorder GWAS

Furthermore, as shown in Fig. 3 , univariate causal mixture modeling suggests that we can expect to see substantial increases in identified genome-wide significant loci and consequently in the proportion of h 2 SNP explained by these variants as GWAS sample sizes increase (Holland et al., 2020 ). This is particularly relevant for BD where GWAS studies have now reached the ‘inflection’ point where the significant associations begin to accumulate with smaller increases in sample size (Mullins et al., 2020 ). As such, international collaborations in large-scale GWAS remain imperative for the continued identification of common variants underlying BD etiology, and the plan of the PGC Bipolar Working Group to further increase GWAS sample sizes is encouraging (Sullivan et al., 2018 ).

Statistical power calculations for current and future GWAS. The variance explained by genome-wide significant variants ( y -axis) is calculated for increasing GWAS sample sizes ( x -axis) using the univariate causal mixture model (Holland et al., 2020 ). The legend describes the estimated GWAS sample sizes (SE) needed to capture 50% of the genetic variance (horizontal dashed line) associated with each trait. Stars indicate the sample sizes of currently available GWAS, and circles indicate the estimated sample sizes needed to capture 50% of the genetic variance for each trait. Traits include attention-deficit/hyperactivity disorder (ADHD) (Demontis et al., 2019b ), autism spectrum disorder (ASD) (Grove et al., 2019 ), bipolar disorder (BD) (Mullins et al., 2020 ), depression (MDD) (Howard et al., 2019 ), and schizophrenia (SCZ) (Pardiñas et al., 2018 ). Height is included as a somatic control (no genetic correlation exists between height and bipolar disorder) (Yengo et al., 2018 ). s.e. , standard error.

Genetic overlap

In addition to genetic correlation (Bulik-Sullivan et al., 2015b ) (described above), the most common approach for assessing genetic overlap at the genome-wide level is polygenic risk score (PRS) analysis (International Schizophrenia Consortium et al., 2009 ). The PRS for a given trait is typically a weighted sum of genetic variants where the variants used and their weights are defined by effects measured by previous GWASs of the trait. The genetic liability for BD has been used to predict a number of other psychiatric disorders as well as creativity, educational attainment (Mistry, Harrison, Smith, Escott-Price, & Zammit, 2018 ), addiction (Reginsson et al., 2018 ), as well as psychopathology (Mistry, Escott-Price, Florio, Smith, & Zammit, 2019a ), cognitive functioning (Mistry, Escott-Price, Florio, Smith, & Zammit, 2019b ), progression of unipolar to bipolar depression, and depression onset (Musliner et al., 2019 , 2020 ).

PRSs for BD and other traits have also been used to explain common comorbidities within BD. Suicide attempts by people with BD have been associated with higher genetic liability for depression (Mullins et al., 2019 ) as well as an interaction between trauma and bipolar genetic liability (Wilcox et al., 2017 ). Previous childhood ADHD diagnosis in those with BD was associated with higher genetic liability for ADHD (Grigoroiu-Serbanescu et al., 2020 ; Wilcox et al., 2017 ).

In addition to PRS analysis, cross-disorder GWAS meta-analyses have also been performed for BD and ADHD (Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2018 ; van Hulzen et al., 2017 ), SCZ (Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2018 ), and MDD (Coleman, Gaspar, Bryois, & Breen, 2020 ), identifying two, 114, and 73 genome-wide significant loci associated with these phenotype pairs, respectively. Moreover, numerous genes mapped to BD risk loci are also linked to schizophrenia, ASD, and OCD (O'Connell, McGregor, Lochner, Emsley, & Warnich, 2018 ) further highlighting common genetic architecture across psychiatric disorders.

The conditional/conjunctional false discovery rate statistical tool has also been used to identify BD risk loci as well as shared risk loci between BD and a number of phenotypes. This method leverages the power of two GWAS to boost discovery by re-adjusting the GWAS test statistics in a primary phenotype and allows for the discovery of loci significantly associated with two phenotypes simultaneously (Andreassen, Thompson, & Dale, 2014 ; Smeland et al., 2020b ). Utilizing this method, shared genetic loci have been identified between BD and ADHD ( n  = 5) (O'Connell et al., 2019 ), schizophrenia ( n  = 14) (Andreassen et al., 2013 ), Alzheimer's disease ( n  = 2) (Drange et al., 2019 ), intelligence ( n  = 12) (Smeland et al., 2020a ), body mass index ( n  = 17) (Bahrami et al., 2020 ), and lifespan ( n  = 8) (Muntané et al., 2021 ). This method is agnostic to the effect directions of genetic variants and so shared loci were identified between BD and Alzheimer's disease, intelligence, body mass index, and lifespan despite observed null and non-significant genetic correlations with these phenotypes.

Most recently (Mullins et al., 2020 ), the genetic relationship between BD and 10 clinically and epidemiologically associated traits (daytime sleepiness, morningness, sleep duration, insomnia, mood instability, educational attainment, problematic alcohol use, drinks per week, smoking initiation, and cigarettes per day) were assessed using the MiXeR tool (Frei et al., 2019 ), to identify trait-specific and shared genetic components, and Mendelian randomization (Zhu et al., 2018 ), to establish ‘causal’ relationships. Extensive genetic overlap was identified between all traits and BD, most notably that >90% of the genetic variants estimated to influence BD were also estimated to influence educational attainment. Moreover, bidirectional relationships were identified between BD and sleep duration, mood instability, educational attainment, and problematic alcohol use, while BD was identified as ‘causal’ for morningness and drinks per week and smoking initiation was ‘causal’ for BD (Mullins et al., 2020 ).

Rare variants

In addition to genetic interactions, the difference in heritability could also be explained by rare variants in the genome which are often unmeasured and thus not included in GWASs. While the cost of whole-exome sequencing (WES) and whole-genome sequencing (WGS) has decreased, these technologies are still substantially more expensive than common genotyping arrays. As a result, WGS/WES studies of BD have been limited to small studies consisting mostly of large pedigrees to potentially enrich the sample with causal rare variants and increase power (Forstner et al., 2020 ; Goes et al., 2016 , 2019 ; Maaser et al., 2018 ; Sul et al., 2020 ; Toma et al., 2018 ). While these studies have found evidence of higher rare deleterious burden in cases (Sul et al., 2020 ), higher disruptive variant burden in early-onset cases (Toma et al., 2018 ), evidence of rare variant segregation in pedigrees (Forstner et al., 2020 ; Goes et al., 2016 ; Maaser et al., 2018 ), and evidence of de novo variation (Goes et al., 2019 ), much larger sample sizes will be required to definitively identify rare variants conferring risk for BD.

Copy number variants

Copy number variants (CNVs) refer to regions of the genome where a duplication (three or more copies are present) or deletion (only one copy remains) has occurred such that more or less than the expected two copies in the diploid human genome are present. Carriers of certain CNVs are known to be at considerably elevated risk for developing neurodevelopmental (e.g. ASDs) and mental disorders (e.g. schizophrenia) (Kirov, Rees, & Walters, 2015 ) as well as somatic conditions (e.g. diabetes and hypertension) (Crawford et al., 2019 ). The frequency of CNVs in BD is less than that observed for neurodevelopmental disorders or schizophrenia (Kirov, 2015 ), and correspondingly their role in the disorder appears less with only one CNV robustly associated with BD to date. A 650 kb duplication at 16p11.2 was first described as a de novo CNV for BD (Kirov, 2015 ; Malhotra et al., 2011 ) and this association was replicated in a larger genome-wide analysis (Green et al., 2016 ). This CNV is also implicated in schizophrenia, autism, and intellectual disability (Kirov, 2015 ). Two additional CNVs, at 1q21.1 and 3q29, are also implicated in BD; however, these associations fail to pass the genome-wide significance threshold (Green et al., 2016 ). Interestingly, these two CNVs are also associated with schizophrenia (Kirov, 2015 ). One further study identified enrichment of genic CNVs in schizoaffective BD, but not between BD cases and controls or other BD subtypes (Charney et al., 2019 ).

These findings highlight that the genetic overlap between BD and schizophrenia extends beyond common variation, but suggests a difference in underlying mechanisms. One possible explanation for the smaller role of CNVs in BD is that patients with BD exhibit less cognitive deficits than patients with schizophrenia who can exhibit substantial cognitive deficits, since the same CNVs which are implicated in schizophrenia are also known to cause cognitive problems (Kirov, 2015 ).

Genetic interactions

Other than increasing the sample size of GWAS, the difference between observed twin-based and h 2 SNP ( Fig. 2 ) may also be explained by unaccounted for moderated genetic effects such as interactions between genes and the environment (G×E) or gene–gene interactions (epistatic effects). The role of G×E in BD remains an under-researched area, however, but some interactions have been identified (Aas et al., 2014 , 2020 ; Hosang, Fisher, Cohen-Woods, McGuffin, & Farmer, 2017 ; Oliveira et al., 2016 ; Winham et al., 2014 ). Although these studies highlight the potential role of G×E in the etiology of BD, the lack of replication studies and small sample sizes suggest that they should be interpreted with caution. As with G×E, studies of epistasis in BD are in their infancy and lack replication (Judy et al., 2013 ). As the ability of GWAS to identify risk variants with small effects increases, further study of how implicated genes interact with environmental or other genetic factors to modulate the risk of BD are required.

Clinical implications

Pharmacogenomics.

Lithium, anti-epileptic drug mood stabilizers (such as valproate/divalproex, lamotrigine, and carbamazepine), antipsychotics, and antidepressants are commonly prescribed treatments for BD. However, response to these medications can widely vary between individuals, and some patients may cycle through different medications before they find an effective treatment with minimal side effects. Pharmacogenomic studies aim to use genetics to predict treatment response. A particular challenge to pharmacogenomics in BD has been the measurement of treatment response which can be limited by the length of follow-up, adherence to medication, and confounding due to the multi-drug treatment strategy common to the illness. Consequently, a systematic rating system with a high inter-rater reliability, the Alda score, was developed to quantify the clinical improvement of BD during treatment while also accounting for potential confounders of treatment response (Nunes, Trappenberg, & Alda, 2020 ). However, obtaining large samples with reliable measures has limited the statistical power to discover clinically-informative genetic variants associated with treatment response. Furthermore, heterogeneity between study designs and the samples included have yielded limited replication of any findings. While not yet replicable, promising pharmacogenomic findings for BD were summarized in a recent review (Gordovez & McMahon, 2020 ). Most of the previous pharmacogenomic studies have been focused on either lithium treatment response or HLA haplotypes predicting serious adverse reactions related to carbamazepine, phenytoin, and lamotrigine. A recent study tested for genetic association with treatment response to anti-epileptic drug mood stabilizers, an alternative to lithium, and identified two SNP-level associations in THSD7A and SLC35F3 as well as two gene-level associations with ABCC1 and DISP1 (Ho et al., 2020 ).

With the exception of genetic predictors of adverse reactions to medication, no large genetic effects on treatment response have been identified. However, current pharmacogenomic testing has already been shown to be useful by providing clinicians support in reaching effective and well-tolerated treatments of BD (Ielmini et al., 2018 ). Additionally, as the sample size of pharmacogenomic studies increases, PRSs derived from these studies could further enable a precision medicine approach to BD treatment. In addition to pharmacogenomic PRSs, PRSs derived from large case–control studies could also improve the genetic prediction of treatment response. For example, increased genetic liability for depression and schizophrenia was associated with worse response to lithium (Amare et al., 2020 ; International Consortium on Lithium Genetics (ConLi+Gen) et al., 2018 ). These PRSs could be explaining some of the clinical heterogeneity in the sample as discussed below and thus improve the identification of certain BD clinical profiles that respond best to lithium.

Finally, there is potential application of repurposing drugs and focusing on different drug targets based on recent genetic findings. For example, calcium channel blockers (CBBs), which have been widely used to treat hypertension and other cardiovascular conditions, were also once considered as a treatment in psychiatry (Harrison, Tunbridge, Dolphin, & Hall, 2020 ). However, because CACNA1C has now been implicated as one of the strongest associations with BD (Gordovez & McMahon, 2020 ), there is renewed interest in CBBs as a treatment for the disorder (Cipriani et al., 2016 ).

Risk prediction

In addition to therapeutic intervention, PRSs may also provide clinical utility to inform disease screening (Torkamani, Wineinger, & Topol, 2018 ). While the PRS derived from the latest GWAS of BD only explains about 4.75% of the phenotypic variance, the latest PRS could still be useful for risk stratification (Mullins et al., 2020 ). Compared to individuals with average genetic risk for BD, individuals in the top decile risk had an odds ratio of 3.62 (95% CI 1.7–7.9) of being a case. An important caveat to note about PRSs, however, is that prediction performance is worse when applied to ancestries not included in the training GWAS (Martin et al., 2019 ). For instance, the current BD PRS, estimated using individuals with European ancestries, explains only around 2% and 1% of the phenotypic variance in individuals with East Asian or admixed African American ancestry, respectively (Mullins et al., 2020 ). Encouragingly though, the trans-ethnic prediction accuracy of the PRS has improved as the sample size has increased. Furthermore, the PRS prediction accuracy will also improve as new non-European ancestries are included in future training GWASs.

Clinical heterogeneity

PRSs can also help dissect the high clinical heterogeneity (i.e. bipolar type, psychosis, rapid cycling) present in the disorder (Coombes et al., n.d.). For example, higher genetic liability for schizophrenia is associated with bipolar type I (Charney et al., 2017 ). This finding could be driven by the increased prevalence of psychosis among those with BDI as multiple studies have shown that higher genetic risk of schizophrenia is associated with psychosis in BD, particularly during mania (Allardyce et al., 2018 ; Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2018 ; Charney et al., 2019 ; Coombes et al., 2020 ; Markota et al., 2018 ). Other studies of bipolar subtypes have shown positive associations between BDII and insomnia PRS, rapid cycling and ADHD PRS, as well as early age-of-onset of BD and PRSs for risk-taking and anhedonia (Coombes et al., n.d.; Lewis et al., 2019 ). While no individual PRS is able to explain a large amount of variation among bipolar subtypes, these findings give insight into the genetic contributions to clinical heterogeneity and could help classify the disorder more accurately as well as identify the risk of suicide, psychosis, and other adverse outcomes in patients with BD.

Future directions

Significant advances in our understanding of the genetic architecture of BD have been made, from initial linkage and family studies to current large consortia-driven genome-wide studies. Moreover, integration of these genetic discoveries with other -omic and imaging data will be key to comprehending the role of genetic variation in the etiology of BD. However, distinct shortcomings and limitations to genetic discovery highlight key areas to be prioritized in future studies.

Diverse phenotype ascertainment

Identification of novel loci for BD, and other polygenic complex phenotypes, requires increasing sample sizes ( Fig. 3 ), which remains a challenging and costly task (Lu, Campeau, & Lee, 2014 ). The majority of samples included in the PGC-BD were clinically ascertained, with the inclusion of external biobank samples only in the most recent discovery GWAS (Mullins et al., 2020 ). Numerous efforts have been made to combine electronic health record and registry data with genetic data to facilitate large population-based studies, such as the Electronic Medical Records and Genomics network ( https://emerge-network.org/ ), the UK Biobank ( https://www.ukbiobank.ac.uk/ ), All of Us ( https://allofus.nih.gov/ ), the Million Veterans Program ( https://www.research.va.gov/mvp/ ), and iPsych ( https://ipsych.dk/en/ ). Furthermore, GWAS summary statistics of self-reported phenotypes for thousands to millions of individuals may be obtained through collaboration with the personal genetics company 23andMe, Inc. ( https://research.23andme.com/research-innovation-collaborations/ ). The data generated by such population studies and 23andMe provide a means by which to drastically increase sample size without the costs associated with clinical ascertainment. This approach was shown to be successful for depression, where PGC cohorts were meta-analyzed with data from the UK Biobank and summary statistics from 23andMe, increasing the number of identified associated risk loci from 44 (Wray et al., 2018 ) to 102 (Howard et al., 2019 ). However, a limitation to this use of ‘minimal phenotyping’ data is that the loci identified, especially when based on self-report data, were non-specific for depression highlighting potential differences in genetic architecture when compared to clinically ascertained depression (Cai et al., 2020 ). In line with this, the h 2 SNP estimates of the biobank samples included in the latest PGC BD GWAS are less than that observed for clinically ascertained samples which may reflect more heterogeneous clinical presentations or less severe illness (Mullins et al., 2020 ).

Data generated from ‘minimal phenotyping’ are likely to include other psychopathological features which may underlie self-reported BD such as personality disorders or mild temperamental traits, thereby increasing heterogeneity in the sample and leading to the possibility of non-specific or false-positive results. However, true self-reported BD may reflect the non-hospitalized, non-psychotic part of the BD spectrum, more typical of BDII, which is under-represented in the current PGC BD sample. Moreover, expanding genetic studies to include the full spectrum of BD in population-based non-clinical samples increases the potential for novel discoveries with important implications for clinical management and further research, and is therefore of high interest to both clinicians and the pharmaceutical industry.

Thus, while adopting the ‘minimal phenotyping’ approach for BD will allow GWAS to reach sample sizes not currently feasible by clinical ascertainment and will likely identify numerous novel risk loci, similar post-hoc analyses as that performed for depression (Cai et al., 2020 ), will be required to determine the specificity of identified loci to BD.

Increased deep phenotyping

The high levels of heterogeneity amongst patients with BD, including disorder type, features of episodes, and the course of the disorder, contribute to the difficulty in identifying underlying genetic risk factors. BDI ( h 2 SNP  = 25%) is shown to be more heritable than BDII ( h 2 SNP  = 11%), and the genetic correlation ( r g  = 0.89) between these types suggests that they are closely related, yet distinct, phenotypes (Stahl et al., 2019 ). In support of this, the most recent PGC GWAS for BD identified novel and distinct loci specifically associated with BDI or BDII, which were not identified when all bipolar cases were analyzed together (Mullins et al., 2020 ). Genetic studies of the features and course of BD have predominantly employed a PRS approach, as outlined above, and GWAS data for these subtypes is lacking due to small sample sizes [data from the PGC indicate that none of these subtypes include more than 10 K samples (Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2018 )]. Thus, larger deeply phenotyped samples are required in order to conduct a thorough investigation of the genetic architecture of these subtypes within BD. Doing so would aid subtype-specific discoveries, and may inform on nosology, diagnostic practices, and drug development for BD.

In addition, the potential inclusion of ‘minimal phenotyping’ data, as described above, further emphasizes the need for increased deep phenotyping. Results generated from deep phenotyped samples will serve as standards against which to compare the specificity of results generated from the inclusion of ‘minimal phenotyping’.

Increased ancestral-diversity

The majority of individuals included in GWASs for any trait have overwhelmingly been of European descent and the lack of diversity is even more pronounced in genetic studies of psychiatric disorders (Martin et al., 2019 ; Peterson et al., 2019 ; Sirugo, Williams, & Tishkoff, 2019 ). In BD, the largest GWAS includes only individuals from European ancestries (Mullins et al., 2020 ). This ‘missing diversity’ can greatly hinder our understanding of the etiology of BD. For example, the inclusion of non-European ancestries could substantially improve fine-mapping of disease-associated loci (Peterson et al., 2019 ). Furthermore, the current Eurocentric approach has the potential to exacerbate health disparities already seen in BD (Akinhanmi et al., 2018 ) by limiting the therapeutic advances gained by pharmacogenomics and improved genetic risk predictions to those of European descent (Duncan et al., 2019 ; Martin et al., 2019 ; Sirugo et al., 2019 ). Future inclusion of diverse samples will come with new ethical, technological, and methodological challenges (Peterson et al., 2019 ). Some of these considerations include choosing ancestry-specific genotyping platforms to improve genomic coverage, increasing sample sizes of diverse reference panels to improve imputation accuracy, and improving statistical methods to control for population stratification and estimate ancestry-specific PRSs. Thus, the PGC Bipolar Working Group has committed to expanding the future GWAS to include non-European ancestries.

Larger sequencing efforts

As mentioned above, sequencing efforts in BD are currently in their infancy (Forstner et al., 2020 ; Goes et al., 2016 ; Maaser et al., 2018 ; Sul et al., 2020 ; Toma et al., 2018 ). Although studies provide evidence that rare variants might contribute to the etiology of BD, weak statistical power due to small sample sizes remains an issue. The Bipolar Sequencing Consortium (BSC) was established to facilitate combining existing exome and WGS studies of BD ( http://metamoodics.org/bsc/consortium/ ), and includes approximately 4500 BD cases and 9000 controls, as well as 1200 affected relatives from 250 families. Moreover, a collaboration between the Dalio Initiative in BD ( https://www.daliophilanthropies.org/initiatives/mental-health-and-wellness/ ), the Stanley Centre ( https://www.broadinstitute.org/stanley ), and iPSYCH ( https://ipsych.dk/en/ ) aims to generate WES data from approximately 7000 BD cases and 10 000 matched controls. However, it is estimated that as many as 25 000 cases might be necessary in order to identify significant rare variant associations with BD (Zuk et al., 2014 ), confirmed by recent analyses in schizophrenia (Singh et al., 2020 ), and so continued expansion of these, or similar, efforts will be crucial to determine the role of rare variation in BD.

Our knowledge of the genetic etiology of BD has rapidly accelerated in recent years with advances in technology and methodology as well as the adoption of international consortiums and large population-based biobanks. It is now clear that BD is highly heritable but also highly heterogeneous and polygenic with substantial genetic overlap with other psychiatric disorders. Encouragingly, genetic studies of BD have reached an ‘inflection point’ ( Fig. 3 ). Thus, the number of associated loci is expected to substantially increase in larger future studies and with it, improved genetic prediction of the disorder. Incorporation of ancestrally-diverse samples in these studies will enable improved identification of causal variants for the disorder and also allow for equitable future clinical applications of both genetic risk prediction and therapeutic interventions.

Acknowledgements

We would like to thank the research participants and members of the Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, and other studies reported in this review, for making this research possible.

Financial support

We acknowledge the support from the Research Council of Norway (229129, 213837, 223273), the South-East Norway Regional Health Authority (2017-112), and the PGC US Norway Collaboration (RCN# 248980).

Conflict of interest

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• Diagnosis and...

Diagnosis and management of bipolar disorders

• Related content
• Peer review
• Fernando S Goes , associate professor of psychiatry and behavioral sciences 1 2
• 1 Precision Medicine Center of Excellence in Mood Disorders, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
• 2 Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
• Correspondence to: F S Goes fgoes1{at}jhmi.edu

Bipolar disorders (BDs) are recurrent and sometimes chronic disorders of mood that affect around 2% of the world’s population and encompass a spectrum between severe elevated and excitable mood states (mania) to the dysphoria, low energy, and despondency of depressive episodes. The illness commonly starts in young adults and is a leading cause of disability and premature mortality. The clinical manifestations of bipolar disorder can be markedly varied between and within individuals across their lifespan. Early diagnosis is challenging and misdiagnoses are frequent, potentially resulting in missed early intervention and increasing the risk of iatrogenic harm. Over 15 approved treatments exist for the various phases of bipolar disorder, but outcomes are often suboptimal owing to insufficient efficacy, side effects, or lack of availability. Lithium, the first approved treatment for bipolar disorder, continues to be the most effective drug overall, although full remission is only seen in a subset of patients. Newer atypical antipsychotics are increasingly being found to be effective in the treatment of bipolar depression; however, their long term tolerability and safety are uncertain. For many with bipolar disorder, combination therapy and adjunctive psychotherapy might be necessary to treat symptoms across different phases of illness. Several classes of medications exist for treating bipolar disorder but predicting which medication is likely to be most effective or tolerable is not yet possible. As pathophysiological insights into the causes of bipolar disorders are revealed, a new era of targeted treatments aimed at causal mechanisms, be they pharmacological or psychosocial, will hopefully be developed. For the time being, however, clinical judgment, shared decision making, and empirical follow-up remain essential elements of clinical care. This review provides an overview of the clinical features, diagnostic subtypes, and major treatment modalities available to treat people with bipolar disorder, highlighting recent advances and ongoing therapeutic challenges.

Introduction

Abnormal states of mood, ranging from excesses of despondency, psychic slowness, diminished motivation, and impaired cognitive functioning on the one hand, and exhilaration, heightened energy, and increased cognitive and motoric activity on the other, have been described since antiquity. 1 However, the syndrome in which both these pathological states occur in a single individual was first described in the medical literature in 1854, 2 although its fullest description was made by the German psychiatrist Emil Kraepelin at the turn of the 19th century. 3 Kraepelin emphasized the periodicity of the illness and proposed an underlying trivariate model of mood, thought (cognition), and volition (activity) to account for the classic forms of mania and depression and the various admixed presentations subsequently know as mixed states. 3 These initial descriptions of manic depressive illness encompassed most recurrent mood syndromes with relapsing remitting course, minimal interepisode morbidity, and a wide spectrum of “colorings of mood” that pass “without a sharp boundary” from the “rudiment of more severe disorders…into the domain of personal predisposition.” 3 Although Kraepelin’s clinical description of bipolar disorder (BD) remains the cornerstone of today’s clinical description, more modern conceptions of bipolar disorder have differentiated manic depressive illness from recurrent depression, 4 partly based on differences in family history and the relative specificity of lithium carbonate and mood stabilizing anticonvulsants as anti-manic and prophylactic agents in bipolar disorder. While the boundaries of bipolar disorder remain a matter of controversy, 5 this review will focus on modern clinical conceptions of bipolar disorder, highlighting what is known about its causes, prognosis, and treatments, while also exploring novel areas of inquiry.

Sources and selection criteria

PubMed and Embase were searched for articles published from January 2000 to February 2023 using the search terms “bipolar disorder”, “bipolar type I”, “bipolar type II”, and “bipolar spectrum”, each with an additional search term related to each major section of the review article (“definition”, “diagnosis”, “nosology”, “prevalence”, “epidemiology”, “comorbid”, “precursor”, “prodrome”, “treatment”, “screening”, “disparity/ies”, “outcome”, “course”, “genetics”, “imaging”, “treatment”, “pharmacotherapy”, “psychotherapy”, “neurostimulation”, “convulsive therapy”, “transmagnetic”, “direct current stimulation”, “suicide/suicidal”, and “precision”). Searches were prioritized for systematic reviews and meta-analyses, followed by randomized controlled trials. For topics where randomized trials were not relevant, searches also included narrative reviews and key observational studies. Case reports and small observations studies or randomized controlled trials of fewer than 50 patients were excluded.

Modern definitions of bipolar disorder

In the 1970s, the International Classification of Diseases and the Diagnostic and Statistical Manual of Mental Disorders reflected the prototypes of mania initially described by Kraepelin, following the “neo-Kraepelinian” model in psychiatric nosology. To meet the primary requirement for a manic episode, an individual must experience elevated or excessively irritable mood for at least a week, accompanied by at least three other typical syndromic features of mania, such as increased activity, increased speed of thoughts, rapid speech, changes in esteem, decreased need for sleep, or excessive engagement in impulsive or pleasurable activities. Psychotic symptoms and admission to hospital can be part of the diagnostic picture but are not essential to the diagnosis. In 1994, Diagnostic and Statistical Manual of Mental Disorders , fourth edition (DSM-IV) carved out bipolar disorder type II (BD-II) as a separate diagnosis comprising milder presentations of mania called hypomania. The diagnostic criteria for BD-II are similar to those for bipolar disorder type I (BD-I), except for a shorter minimal duration of symptoms (four days) and the lack of need for significant role impairment during hypomania, which might be associated with enhanced functioning in some individuals. While the duration criteria for hypomania remain controversial, BD-II has been widely accepted and shown to be as common as (if not more common than) BD-I. 6 The ICD-11 (international classification of diseases, 11th revision) included BD-II as a diagnostic category in 2019, allowing greater flexibility in its requirement of hypomania needing to last several days.

The other significant difference between the two major diagnostic systems has been their consideration of mixed symptoms. Mixed states, initially described by Kraepelin as many potential concurrent combinations of manic and depressive symptoms, were more strictly defined by DSM as a week or more with full syndromic criteria for both manic and depressive episodes. In DSM-5, this highly restrictive criterion was changed to encompass a broader conception of subsyndromal mixed symptoms (consisting of at least three contrapolar symptoms) in either manic, hypomanic, or depressive episodes. In ICD-11, mixed symptoms are still considered to be an episode, with the requirement of several prominent symptoms of the countervailing mood state, a less stringent requirement that more closely aligns with Kraepelin's broader conception of mixed states. 7

Epidemiology

Using DSM-IV criteria, the National Comorbidity Study replication 6 found similar lifetime prevalence rates for BD-I (1.0%) and BD-II (1.1%) among men and women. Subthreshold symptoms of hypomania (bipolar spectrum disorder) were more common, with prevalence rate estimates of 2.4%. 6 Incidence rates, which largely focus on BD-I, have been estimated at approximately 6.1 per 100 000 person years (95% confidence interval 4.7 to 8.1). 8 Estimates of the incidence and lifetime prevalence of bipolar disorder show moderate variations according to the method of diagnosis (performed by lay interviewers in a research context v clinically trained interviews) and the racial, ethnic, and demographic context. 9 Higher income, westernized countries have slightly higher rates of bipolar disorder, 10 which might reflect a combination of westernized centricity in the specific idioms used to understand and elicit symptoms, as well as a greater knowledge, acceptance, and conceptualization of emotional symptoms as psychiatric disorders.

Causes of bipolar disorder

Like other common psychiatric disorders, bipolar disorder is likely caused by a complex interplay of multiple factors, both at the population level and within individuals, 11 which can be best conceptualized at various levels of analysis, including genetics, brain networks, psychological functioning, social support, and other biological and environmental factors. Because knowledge about the causes of bipolar disorder remains in its infancy, for pragmatic purposes, most research has followed a reductionistic model that will ultimately need to be synthesized for a more coherent view of the pathophysiology that underlies the condition.

Insights from genetics

From its earliest descriptions, bipolar disorder has been observed to run in families. Indeed, family history is the strongest individual risk factor for developing the disorder, with first degree relatives having an approximately eightfold higher risk of developing bipolar disorder compared with the baseline population rates of ~1%. 12 While family studies cannot separate the effects of genetics from behavioral or cultural transmission, twin and adoption studies have been used to confirm that the majority of the familial risk is genetic in origin, with heritability estimates of approximately 60-80%. 13 14 There have been fewer studies of BD-II, but its heritability has been found to be smaller (~46%) 15 and closer to that of more common disorders such as major depressive disorder or generalized anxiety. 15 16 Nevertheless, significant heritability does not necessarily imply the presence of genes of large effect, since the genetic risk for bipolar disorder appears likely to be spread across many common variants of small effect sizes. 16 17 Ongoing studies of rare variations have found preliminary evidence for variants of slightly higher effect sizes, with initial evidence of convergence with common variations in genes associated with the synapse and the postsynaptic density. 18 19

While the likelihood that the testing of single variants or genes will be useful for diagnostic purposes is low, analyses known as polygenic risk studies can sum across all the risk loci and have some ability to discriminate cases from controls, albeit at the group level rather than the individual level. 20 These polygenic risk scores can also be used to identify shared genetic risk factors across other medical and psychiatric disorders. Bipolar disorder has strong evidence for common variant based coheritability with schizophrenia (genetic correlation (r g ) 0.69) and major depressive disorder (r g 0.48). BD-I has stronger coheritability with schizophrenia compared with BD-II, which is more strongly genetically correlated with major depressive disorder (r g 0.66). 16 Lower coheritability was observed with attention deficit hyperactivity disorder (r g 0.21), anorexia nervosa (0.20), and autism spectrum disorder (r g 0.21). 16 These correlations provide evidence for shared genetic risk factors between bipolar disorder and other major psychiatric syndromes, a pattern also corroborated by recent nationwide registry based family studies. 12 14 Nevertheless, despite their potential usefulness, polygenic risk scores must currently be interpreted with caution given their lack of populational representation and lingering concerns of residual confounds such as gene-environment correlations. 21

Insights from neuroimaging

Similarly to the early genetic studies, small initial studies had limited replication, leading to the formation of large worldwide consortiums such as ENIGMA (enhancing neuroimaging genetics through meta-analysis) which led to substantially larger sample sizes and improved reproducibility. In its volumetric analyses of subcortical structures from MRI (magnetic resonance imaging) of patients with bipolar disorder, the ENIGMA consortium found modest decreases in the volume of the thalamus (Cohen’s d −0.15), the hippocampus (−0.23), and the amygdala (−0.11), with an increased volume seen only in the lateral ventricles (+0.26). 22 Meta-analyses of cortical regions similarly found small reductions in cortical thickness broadly across the parietal, temporal, and frontal cortices (Cohen’s d −0.11 to −0.29) but no changes in cortical surface area. 23 In more recent meta-analyses of white matter tracts using diffuse tension imaging, widespread but modest decreases in white matter integrity were found throughout the brain in bipolar disorder, most notably in the corpus callosum and bilateral cinguli (Cohen’s d −0.39 to −0.46). 24 While these findings are likely to be highly replicable, they do not, as yet, have clinical application. This is because they reflect differences at a group level rather than an individual level, 25 and because many of these patterns are also seen across other psychiatric disorders 26 and could be either shared risk factors or the effects of confounding factors such as medical comorbidities, medications, co-occurring substance misuse, or the consequences (rather than causes) of living with mental illness. 27 Efforts to collate and meta-analyze large samples utilizing longitudinal designs 28 task based, resting state functional MRI measurents, 29 as well as other measures of molecular imaging (magnetic resonance spectroscopy and positron emission tomography) are ongoing but not as yet synthesized in large scale meta-analyses.

Environmental risk factors

Because of the difficulty in measuring and studying the relevant and often common environmental risk factors for a complex illness like bipolar disorder, there has been less research on how environmental risk factors could cause or modify bipolar disorder. Evidence for intrauterine risk factors is mixed and less compelling than such evidence in disorders like schizophrenia. 30 Preliminary evidence suggests that prominent seasonal changes in solar radiation, potentially through its effects on circadian rhythm, can be associated with an earlier onset of bipolar disorder 31 and a higher likelihood of experiencing a depressive episode at onset. 31 However, the major focus of environmental studies in bipolar disorder has been on traumatic and stressful life events in early childhood 32 and in adulthood. 33 The effects of such adverse events are complex, but on a broad level have been associated with earlier onset of bipolar disorder, a worse illness course, greater prevalence of psychotic symptoms, 34 substance misuse and psychiatric comorbidities, and a higher risk of suicide attempts. 32 35 Perhaps uniquely in bipolar disorder, evidence also indicates that positive life events associated with goal attainment can also increase the risk of developing elevated states. 36

Comorbidity

Bipolar disorder rarely manifests in isolation, with comorbidity rates indicating elevated lifetime risk of several co-occurring symptoms and comorbid disorders, particularly anxiety, attentional disorders, substance misuse disorders, and personality disorders. 37 38 The causes of such comorbidity can be varied and complex: they could reflect a mixed presentation artifactually separated by current diagnostic criteria; they might also reflect independent illnesses; or they might represent the downstream effects of one disorder increasing the risk of developing another disorder. 39 Anxiety disorders tend to occur before the frank onset of manic or hypomanic symptoms, suggesting that they could in part reflect prodromal symptoms that manifest early in the lifespan. 37 Similarly, subthreshold and syndromic symptoms of attention deficit/hyperactivity disorder are also observed across the lifespan of people with bipolar disorder, but particularly in early onset bipolar disorder. 40 On the other hand, alcohol and substance misuse disorders occur more evenly before and after the onset of bipolar disorder, consistent with a more bidirectional causal association. 41

The association between bipolar disorder and comorbid personality disorders is similarly complex. Milder manifestations of persistent mood instability (cyclothymia) or low mood (dysthymia) have previously been considered to be temperamental variants of bipolar disorder, 42 but are now classified as related but separate disorders. In people with persistent emotional dysregulation, making the diagnosis of bipolar disorder can be particularly challenging, 43 since the boundaries between longstanding mood instability and phasic changes in mood state can be difficult to distinguish. While symptom overlap can lead to artificially inflated prevalence rates of personality disorders in bipolar disorder, 44 the elevated rates of most personality disorders in bipolar disorder, particularly those related to emotional instability, are likely reflective of an important clinical phenomenon that is understudied, particularly with regard to treatment implications. 45 In general, people with comorbidities tend to have greater symptom burden and functional impairment and have lower response rates to treatment. 46 47 Data on approaches to treat specific comorbid disorders in bipolar disorder are limited, 48 49 and clinicians are often left to rely on their clinical judgment. The most parsimonious approach is to treat primary illness as fully as possible before considering additional treatment options for remaining comorbid symptoms. For certain comorbidities, such as anxiety symptoms and disorders of attention, first line pharmacological treatment—namely, antidepressants and stimulants, should be used with caution, since they might increase the long term risks of mood switching or overall mood instability. 50 51

Like other major mental illnesses, bipolar disorder is also associated with an increased prevalence of common medical disorders such as obesity, hyperlipidemia, coronary artery disease, chronic obstructive pulmonary disease, and thyroid dysfunction. 52 These have been attributed to increase risk factors such as physical inactivity, poor nutrition, smoking, and increased use of addictive substances, 53 but some could also be consequences of specific treatments, such as the atypical antipsychotics and mood stabilizers. 54 Along with poor access to care, this medical burden likely accounts for much of the increased standardized mortality (approximately 2.6 times higher) in people with bipolar disorder, 55 highlighting the need to utilize treatments with better long term side effect profiles, and the need for better integration with medical care.

Precursors and prodromes: who develops bipolar disorder?

While more widespread screening and better accessibility to mental health providers should in principle shorten the time to diagnosis and treatment, early manifestation of symptoms in those who ultimately go on to be diagnosed with bipolar disorder is generally non-specific. 56 In particular, high risk offspring studies of adolescents with a parent with bipolar disorder have found symptoms of anxiety and attentional/disruptive disorders to be frequent in early adolescence, followed by higher rates of depression and sleep disturbance in later teenage years. 56 57 Subthreshold symptoms of mania, such as prolonged increases in energy, elated mood, racing thoughts, and mood lability are also more commonly found in children with prodromal symptoms (meta-analytic prevalence estimates ranging from 30-50%). 58 59 Still, when considered individually, none of these symptoms or disorders are sensitive or specific enough to accurately identify individuals who will transition to bipolar disorder. Ongoing approaches to consider these clinical factors together to improve accuracy have a promising but modest ability to identify people who will develop bipolar disorder, 60 emphasizing the need for further studies before implementation.

Screening for bipolar disorder

Manic episodes can vary from easily identifiable prototypical presentations to milder or less typical symptoms that can be challenging to diagnose. Ideally, a full diagnostic evaluation with access to close informants is performed on patients presenting to clinical care; however, evaluations can be hurried in routine clinical care, and the ability to recall previous episodes might be limited. In this context, the use of screening scales can be a helpful addition to clinical care, although screening scales must be regarded as an impetus for a confirmatory clinical interview rather than a diagnostic instrument by themselves. The two most widely used and openly available screening scales are the mood disorders questionnaire (based on the DSM-IV criteria for hypomania) 61 and the hypomania check list (HCL-32), 62 that represent a broader overview of symptoms proposed to be part of a broader bipolar spectrum.

Racial/ethnic disparities

Although community surveys using structured or semi-structured diagnostic instruments, have provided little evidence for variation across ethnic groups, 63 64 observational studies based on clinical diagnoses in healthcare settings have found a disproportionately higher rate of diagnosis of schizophrenia relative to bipolar disorder in black people. 65 Consistent with similar disparities seen across medicine, these differences in clinical diagnoses are likely influenced by a complex mix of varying clinical presentations, differing rates of comorbid conditions, poorer access to care, greater social and economic burden, as well as the potential effect of subtle biases of healthcare professionals. 65 While further research is necessary to identify driving factors responsible for diagnostic disparities, clinicians should be wary of making a rudimentary diagnosis in patients from marginalized backgrounds, ensuring comprehensive data gathering and a careful diagnostic formulation that incorporates shared decision making between patient and provider.

Bipolar disorder is a recurrent illness, but its longitudinal course is heterogeneous and difficult to predict. 46 66 The few available long term studies of BD-I and BD-II have found a consistent average rate of recurrence of 0.40 mood episodes per year in historical studies 67 and 0.44 mood episodes per year in more recent studies. 68 The median time to relapse is estimated to be 1.44 years, with higher relapse rates seen in BD-I (0.81 years) than in BD-II (1.63 years) and no differences observed with respect to age or sex. 1 2 In addition to focusing on episodes, an important development in research and clinical care of bipolar disorder has been the recognition of the burden of subsyndromal symptoms. Although milder in severity, these symptoms can be long lasting, functionally impairing, and can themselves be a risk factor for episode relapse. 69 Recent cohort studies have also found that a substantial proportion of patients with bipolar disorder (20-30%) continue to have poor outcomes even after receiving guideline based care. 46 70 Risk factors that contribute to this poor outcome include transdiagnostic indicators of adversity such as substance misuse, low educational attainment, socioeconomic hardship, and comorbid disorders. As expected, those with more severe past illness activity, including those with rapid cycling, were also more likely to remain symptomatically and psychosocially impaired. 46 71 72

The primary focus of treating bipolar disorder has been to manage the manic, mixed, or depressive episodes that present to clinical care and to subsequently prevent recurrence of future episodes. Owing to the relapse remitting nature of the illness, randomized controlled trials are essential to determine treatment efficacy, as the observation of clinical improvement could just represent the ebbs and flows of the natural history of the illness. In the United States, the FDA (Food and Drug Administration) requires at least two large scale placebo controlled trials (phase 3) to show significant evidence of efficacy before approving a treatment. Phase 3 studies of bipolar disorder are generally separated into short term studies of mania (3-4 weeks), short term studies for bipolar depression (4-6 weeks), and longer term maintenance studies to evaluate prophylactic activity against future mood episodes (usually lasting one year). Although the most rigorous evaluation of phase 3 studies would be to require two broadly representative and independent randomized controlled trials, the FDA permits consideration of so called enriched design trials that follow participants after an initial response and tolerability has been shown to an investigational drug. Because of this initial selection, such trials can be biased against comparator agents, and could be less generalizable to patients seen in clinical practice.

A summary of the agents approved by the FDA for treatment of bipolar disorder is in table 1 , which references the key clinical trials demonstrating efficacy. Figure 1 and supplementary table 1 are a comparison of treatments for mania, depression, and maintenance. Effect sizes reflect the odds ratios or relative risks of obtaining response (defined as ≥50% improvement from baseline) in cases versus controls and were extracted from meta-analyses of randomized controlled trials for bipolar depression 86 and maintenance, 94 as well as a network meta-analysis of randomized controlled trials in bipolar mania. 73 Effect sizes are likely to be comparable for each phase of treatment, but not across the different phases, since methodological differences exist between the three meta-analytic studies.

FDA approved medications for bipolar disorder

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Summary of treatment response rates (defined as ≥50% improvement from baseline) of modern clinical trials for acute mania, acute bipolar depression, and long term recurrence. Meta-analytic estimates were extracted from recent meta-analyses or network meta-analyses of acute mania, 73 acute bipolar depression, 86 and bipolar maintenance studies 94

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Acute treatment of mania

As mania is characterized by impaired judgment, individuals can be at risk for engaging in high risk, potentially dangerous behaviors that can have substantial personal, occupational, and financial consequences. Therefore, treatment of mania is often considered a psychiatric emergency and is, when possible, best performed in the safety of an inpatient unit. While the primary treatment for mania is pharmacological, diminished insight can impede patients' willingness to accept treatment, emphasizing the significance of a balanced therapeutic approach that incorporates shared decision making frameworks as much as possible to promote treatment adherence.

The three main classes of anti-manic treatments are lithium, mood stabilizing anticonvulsants (divalproate and carbamazepine), and antipsychotic medications. Almost all antipsychotics are effective in treating mania, with the more potent dopamine D2 receptor antagonists such as risperidone and haloperidol demonstrating slightly higher efficacy ( fig 1 ). 73 In the United States, the FDA has approved the use of all second generation antipsychotics for treating mania except for lurasidone and brexpriprazole. Compared with mood stabilizing medications, second generation antipsychotics have a faster onset of action, making them a first line treatment for more severe manic symptoms that require rapid treatment. 99 The choice of which specific second generation antipsychotic to use depends on a balance of efficacy, tolerability concerns, and cost considerations (see table 1 ). Notably, the FDA has placed a black box warning on all antipsychotics for increasing the risk of cerebral vascular accidents in the elderly. 100 While this was primarily focused on the use of antipsychotics in dementia, this likely class effect should be taken into account when considering the use of antipsychotics in the elderly.

Traditional mood stabilizers, such as lithium, divalproate, and carbamazepine are also effective in the treatment of active mania ( fig 1 ). Since lithium also has a robust prophylactic effect (see section on prevention of mood episodes below) it is often recommended as first line treatment and can be considered as monotherapy when rapid symptom reduction is not clinically indicated. On the other hand, other anticonvulsants such as lamotrigine, gabapentin, topiramate, and oxcarbazepine have not been found to be effective for the treatment of mania or mixed episodes. 101 Although the empirical evidence for polypharmacy is limited, 102 combination treatment in acute mania, usually consisting of a mood stabilizer and a second generation antipsychotic, is commonly used in clinical practice despite the higher burden of side effects. Following resolution of an acute mania, consideration should be given to transitioning to monotherapy with an agent with proven prophylactic activity.

Pharmacological approaches to bipolar depression

Depressed episodes are usually more common than mania or hypomania, 103 104 and often represent the primary reason for individuals with bipolar disorder to seek treatment. Nevertheless, because early antidepressant randomized controlled trials did not distinguish between unipolar and bipolar depressive episodes, it has only been in the past two decades that large scale randomized controlled trials have been conducted specifically for bipolar depression. As such trials are almost exclusively funded by pharmaceutical companies, they have focused on the second generation antipsychotics and newer anticonvulsants still under patent. These trials have shown moderate but robust effects for most recent second generation antipsychotics, five of which have received FDA approval for treating bipolar depression ( table 1 ). No head-to-head trials have been conducted among these agents, so the choice of medication depends on expected side effects and cost considerations. For example, quetiapine has robust antidepressant efficacy data but is associated with sedation, weight gain, and adverse cardiovascular outcomes. 105 Other recently approved medications such as lurasidone, cariprazine, and lumateperone have better side effect profiles but show more modest antidepressant activity. 106

Among the mood stabilizing anticonvulsants, lamotrigine has limited evidence for acute antidepressant activity, 107 possibly owing to the need for an 8 week titration to reach the full dose of 200 mg. However, as discussed below, lamotrigine can still be considered for mild to moderate acute symptoms owing to its generally tolerable side effect profile and proven effectiveness in preventing the recurrence of depressive episodes. Divalproate and carbamazepine have some evidence of being effective antidepressants in small studies, but as there has been no large scale confirmatory study, they should be considered second or third line options. 86 Lithium has been studied for the treatment of bipolar depression as a comparator to quetiapine and was not found to have a significant acute antidepressant effect. 88

Antidepressants

Owing to the limited options of FDA approved medications for bipolar depression and concerns of metabolic side effects from long term second generation antipsychotic use, clinicians often resort to the use of traditional antidepressants for the treatment of bipolar depression 108 despite the lack of FDA approval for such agents. Indeed, recent randomized clinical trials of antidepressants in bipolar depression have not shown an effect for paroxetine, 89 109 bupropion, 109 or agomelatine. 110 Beyond the question of efficacy, another concern regarding antidepressants in bipolar disorder is their potential to worsen the course of illness by either promoting mixed or manic symptoms or inducing more subtle degrees of mood instability and cycle acceleration. 111 However, the risk of switching to full mania while being treated with mood stabilizers appears to be modest, with a meta-analysis of randomized clinical trials and clinical cohort studies showing the rates of mood switching over an average follow-up of five months to be approximately 15.3% in people with bipolar disorder treated on antidepressants compared with 13.8% in those without antidepressant treatment. 111 The risk of switching appears to be higher in the first 1-2 years of treatment in people with BD-I, and in those treated with a tricyclic antidepressant 112 or the dual reuptake inhibitor venlafaxine. 113 Overall, while the available data have methodological limitations, most guidelines do not recommend the use of antidepressants in bipolar disorder, or recommend them only after agents with more robust evidence have been tried. That they remain so widely used despite the equivocal evidence base reflects the unmet need for treatment of depression, concerns about the long term side effects of second generation antipsychotics, and the challenges of changing longstanding prescribing patterns.

Pharmacological approaches to prevention of recurrent episodes

Following treatment of the acute depressive or manic syndrome, the major focus of treatment is to prevent future episodes and minimize interepisodic subsyndromal symptoms. Most often, the medication that has been helpful in controlling the acute episode can be continued for prevention, particularly if clinical trial evidence exists for a maintenance effect. To show efficacy for prevention, studies must be sufficiently long to allow the accumulation of future episodes to occur and be potentially prevented by a therapeutic intervention. However, few long term treatment studies exist and most have utilized enriched designs that likely favor the drug seeking regulatory approval. As shown in figure 1 , meta-analyses 94 show prophylactic effect for most (olanzapine, risperidone, quetiapine, aripiprazole, asenapine) but not all (lurasidone, paliperidone) recently approved second generation antipsychotics. The effect sizes are generally comparable with monotherapy (odds ratio 0.42, 95% confidence interval 0.34 to 0.5) or as adjunctive therapy (odds ratio 0.37, 95% confidence interval 0.25 to 0.55). 94 Recent studies of lithium, which have generally used it as a (non-enriched) comparator drug, show a comparable protective effect (odds ratio 0.46, 95% confidence interval 0.28 to 0.75). 94 Among the mood stabilizing anticonvulsant drugs, a prophylactic effect has also been found for both divalproate and lamotrigine ( fig 1 and supplementary table 1), although only the latter has been granted regulatory approval for maintenance treatment. While there are subtle differences in effect sizes in drugs approved for maintenance ( fig 1 and table 1 ), the overlapping confidence intervals and methodological differences between studies prevent a strict comparison of the effect measures.

Guidelines often recommend lithium as a first line agent given its consistent evidence of prophylaxis, even when tested as the disadvantaged comparator drug in enriched drug designs. Like other medications, lithium has a unique set of side effects and ultimately the decision about which drug to use among those which are efficacious should be a decision carefully weighed and shared between patient and provider. The decision might be re-evaluated after substantial experience with the medication or at different stages in the long term treatment of bipolar disorder (see table 1 ).

Psychotherapeutic approaches

The frequent presence of residual symptoms, often associated with psychosocial and occupational dysfunction, has led to renewed interest in psychotherapeutic and psychosocial approaches to bipolar disorder. Given the impairment of judgment seen in mania, psychotherapy has more of a supportive and educational role in the treatment of mania, whereas it can be more of a primary focus in the treatment of depressive states. On a broad level, psychotherapeutic approaches effective for acute depression, such as cognitive behavioral therapy, interpersonal therapy, behavioral activation, and mindfulness based strategies, can also be recommended for acute depressive states in individuals with bipolar disorder. 114 Evidence for more targeted psychotherapy trials for bipolar disorder is more limited, but meta-analyses have found evidence for decreased recurrence (odds ratio 0.56; 95% confidence interval 0.43 to 0.74) 115 and improvement of subthreshold interepisodic depressive and manic symptoms with cognitive behavioral therapy, family based therapy, interpersonal and social rhythm therapy, and psychoeducation. 115 Recent investigations have also focused on targeted forms of psychotherapy to improve cognition 116 117 118 as well as psychosocial and occupational functioning. 119 120 Although these studies show evidence of a moderate effect, they remain preliminary, methodologically diverse, and require replication on a larger scale. 121

The implementation of evidence based psychotherapy as a treatment faces several challenges, including clinical training, fidelity monitoring, and adequate reimbursement. Novel approaches, leveraging the greater tractability of digital tools 122 and allied healthcare workers, 123 are promising means of lessening the implementation gap; however, these approaches require validation and evidence of clinical utility similar to traditional methods.

Neurostimulation approaches

For individuals with bipolar disorder who cannot tolerate or do not respond well to standard pharmacotherapy or psychotherapeutic approaches, neurostimulation techniques such as repetitive transcranial magnetic stimulation or electric convulsive therapy should be considered as second or third line treatments. Electric convulsive therapy has shown response rates of approximately 60-80% in severe acute depressions 124 125 and 50-60% in cases with treatment resistant depression. 126 These response rates compare favorably with those of pharmacological treatment, which are likely to be closer to ~50% and ~30% in subjects with moderate to severe depression and treatment resistant depression, respectively. 127 Although the safety of electric convulsive therapy is well established, relatively few medical centers have it available, and its acceptability is limited by cognitive side effects, which are usually short term, but which can be more significant with longer courses and with bilateral electrode placement. 128 While there have been fewer studies of electric convulsive therapy for bipolar depression compared with major depressive disorder, it appears to be similarly effective and might show earlier response. 129 Anecdotal evidence also suggests electric convulsive therapy that is useful in refractory mania. 130

Compared with electric convulsive therapy, repetitive transcranial magnetic stimulation has no cognitive side effects and is generally well tolerated. Repetitive transcranial magnetic stimulation acts by generating a magnetic field to depolarize local neural tissue and induce excitatory or inhibitory effects depending on the frequency of stimulation. The most studied FDA approved form of repetitive transcranial magnetic stimulation applies high frequency (10 Hz) excitatory pulses to the left prefrontal cortex for 30-40 minutes a day for six weeks. 131 Like electric convulsive therapy, repetitive transcranial magnetic stimulation has been primarily studied in treatment resistant depression and has been found to have moderate effect, with about one third of patients having a significant treatment response compared with those treated with pharmacotherapy. 131 Recent innovations in transcranial magnetic stimulation have included the use of a novel, larger coil to stimulate a larger degree of the prefrontal cortex (deep transcranial magnetic stimulation), 132 and a shortened (three minutes), higher frequency intermittent means of stimulation known as theta burst stimulation that appears to be comparable to conventional (10 Hz) repetitive transcranial magnetic stimulation. 133 A preliminary trial has recently assessed a new accelerated protocol of theta burst stimulation marked by 10 sessions a day for five days. It found that theta burst stimulation had a greater effect on people with treatment resistant depression compared with treatment as usual, although larger studies are needed to confirm these findings. 134

Conventional repetitive transcranial magnetic stimulation (10 Hz) studies in bipolar disorder have been limited by small sample sizes but have generally shown similar effects compared with major depressive disorder. 135 However, a proof of concept study of single session theta burst stimulation did not show efficacy in bipolar depression, 136 reiterating the need for specific trials for bipolar depression. Given the lack of such trials in bipolar disorder, repetitive transcranial magnetic stimulation should be considered a potentially promising but as yet unproven treatment for bipolar depression.

The other major form of neurostimulation studied in both unipolar and bipolar depression is transcranial direct current stimulation, an easily implemented method of delivering a low amplitude electrical current to the prefrontal area of the brain that could lead to local changes in neuronal excitability. 137 Like repetitive transcranial magnetic stimulation, transcranial direct current stimulation is well tolerated and has been mostly studied in unipolar depression, but has not yet generated sufficient evidence to be approved by a regulatory agency. 138 Small studies have been performed in bipolar depression, but the results have been mixed and require further research before use in clinical settings. 137 138 139 Finally, the evidence for more invasive neurostimulation studies such as vagal nerve stimulation and deep brain stimulation remains extremely limited and is currently insufficient for clinical use. 140 141

Treatment resistance in bipolar disorder

As in major depressive disorder, the use of term treatment resistance in bipolar disorder is controversial since differentiating whether persistent symptoms are caused by low treatment adherence, poor tolerability, the presence of comorbid disorders, or are the result of true treatment resistance, is an essential but often challenging clinical task. Treatment resistance should only be considered after two or three trials of evidence based monotherapy, adjunctive therapy, or both. 142 In difficult-to-treat mania, two or more medications from different mechanistic classes are typically used, with electric convulsive therapy 143 and clozapine 144 being considered if more conventional anti-manic treatments fail. In bipolar depression, it is common to combine antidepressants with anti-manic agents, despite limited evidence for efficacy. 145 Adjunctive therapies such as bright light therapy, 146 the dopamine D2/3 receptor agonist pramipexole, 147 and ketamine 148 149 have shown promising results in small open label trials that require further study.

Treatment considerations to reduce suicide in bipolar disorder

The risk of completed suicide is high across the subtypes of bipolar disorder, with estimated rates of 10-15% across the lifespan. 150 151 152 Lifetime rates of suicide attempts are much higher, with almost half of all individuals with bipolar disorder reporting at least one attempt. 153 Across a population and, often within individuals, the causes of suicide attempts and completed suicides are likely to be multifactorial, 154 affected by various risk factors, such as symptomatic illness, environmental stressors, comorbidities (particularly substance misuse), trait impulsivity, interpersonal conflict, loneliness, or socioeconomic distress. 155 156 Risk is highest in depressive and dysphoric/mixed episodes 157 158 and is particularly high in the transitional period following an acute admission to hospital. 159 Among the available treatments, lithium has potential antisuicidal properties. 160 However, since suicide is a rare event, with very few to zero suicides within a typical clinical trial, moderate evidence for this effect emerges only in the setting of meta-analyses of clinical trials. 160 Several observational studies have shown lower mortality in patients on lithium treatment, 161 but such associations might not be causal, since lithium is potentially fatal in overdose and is often avoided by clinicians in patients at high risk of suicide.

The challenge of studying scarce events has led most studies to focus on the reduction of the more common phenomena of suicidal ideation and behavior as a proxy for actual suicides. A recent such multisite study of the Veterans Affairs medical system included a mixture of unipolar and bipolar disorder and was stopped prematurely for futility, indicating no overall effect of moderate dose lithium. 162 Appropriate limitations of this study have been noted, 163 164 including difficulties in recruitment, few patients with bipolar disorder (rather than major depressive disorder), low levels of compliance with lithium therapy, high rates of comorbidity, and a follow-up of only one year. Nevertheless, while the body of evidence suggests that lithium has a modest antisuicidal effect, its degree of protection and utility in complex patients with comorbidities and multiple risk factors remain matters for further study. Treatment of specific suicidal risk in patients with bipolar disorder must therefore also incorporate broader interventions based on the individual’s specific risk factors. 165 Such an approach would include societal interventions like means restriction 166 and a number of empirically tested suicide focused psychotherapy treatments. 167 168 Unfortunately, the availability of appropriate training, expertise, and care models for such treatments remains limited, even in higher income countries. 169

More scalable solutions, such as the deployment of shortened interventions via digital means could help to overcome this implementation gap; however, the effectiveness of such approaches cannot be assumed and requires empirical testing. For example, a recent large scale randomized controlled trial of an abbreviated online dialectical behavioral therapy skills training program was paradoxically associated with slightly increased risk of self-harm. 170

Treatment consideration in BD-II and bipolar spectrum conditions

Because people with BD-II primarily experience depressive symptoms and appear less likely to switch mood states compared with individuals with BD-I, 50 171 there has been a greater acceptance of the use of antidepressants in BD-II depression, including as monotherapy. 172 However, caution should be exercised when considering the use of antidepressants without a mood stabilizer in patients with BD-II who might also experience high rates of mood instability and rapid cycling. Such individuals can instead respond better to newer second generation antipsychotic agents such as quetiapine 173 and lumateperone, 93 which are supported by post hoc analyses of these more recent clinical trials with more BD-II patients. In addition, despite the absence of randomized controlled trials, open label studies have suggested that lithium and other mood stabilizers can have similar efficacy in BD-II, especially in the case of lamotrigine. 174

Psychotherapeutic approaches such as psychoeducation, cognitive behavioral therapy, and interpersonal and social rhythm therapy have been found to be helpful 115 and can be considered as the primary form of treatment for BD-II in some patients, although in most clinical scenarios BD-II is likely to occur in conjunction with psychopharmacology. While it can be tempting to consider BD-II a milder variant of BD-I, high rates of comorbid disorders, rapid cycling, and adverse consequences such as suicide attempts 175 176 highlight the need for clinical caution and the provision of multimodal treatment, focusing on mood improvement, emotional regulation, and better psychosocial functioning.

Precision medicine: can it be applied to improve the care of bipolar disorder?

The recent focus on precision medicine approaches to psychiatric disorders seeks to identify clinically relevant heterogeneity and identify characteristics at the level of the individual or subgroup that can be leveraged to identify and target more efficacious treatments. 1 177 178

The utility of such an approach was originally shown in oncology, where a subset of tumors had gene expression or DNA mutation signatures that could predict response to treatments specifically designed to target the aberrant molecular pathway. 179 While much of the emphasis of precision medicine has been on the eventual identification of biomarkers utilizing high throughput approaches (genetics and other “omics” based measurements), the concept of precision medicine is arguably much broader, encompassing improvements in measurement, potentially through the deployment of digital tools, as well as better conceptualization of contextual, cultural, and socioeconomic mechanisms associated with psychopathology. 180 181 Ultimately, the goal of precision psychiatry is to identify and target driving mechanisms, be they molecular, physiological, or psychosocial in nature. As such, precision psychiatry seeks what researchers and clinicians have often sought: to identify clinically relevant heterogeneity to improve prediction of outcomes and increase the likelihood of therapeutic success. The novelty being not so much the goals of the overarching approach, but the increasing availability of large samples, novel digital tools, analytical advances, and an increasing armamentarium of biological measurements that can be deployed at scale. 177

Although not unique to bipolar disorder, several clinical decision points along the life course of bipolar disorder would benefit from a precision medicine approach. For example, making an early diagnosis is often not possible based on clinical symptoms alone, since such symptoms are usually non-specific. A precision medicine approach could also be particularly relevant in helping to identify subsets of patients for whom the use of antidepressants could be beneficial or harmful. Admittedly, precision medicine approaches to bipolar disorder are still in their infancy, and larger, clinically relevant, longitudinal, and reliable phenotypes are needed to provide the infrastructure for precision medicine approaches. Such data remain challenging to obtain at scale, leading to renewed efforts to utilize the extant clinical infrastructure and electronic medical records to help emulate traditional longitudinal analyses. Electronic medical records can help provide such data, but challenges such as missingness, limited quality control, and potential biases in care 182 need to be resolved with carefully considered analytical designs. 183

Emerging treatments

Two novel atypical antipsychotics, amilsupride and bifeprunox, are currently being tested in phase 3 trials ( NCT05169710 and NCT00134459 ) and could gain approval for bipolar depression in the near future if these pivotal trials show a significant antidepressant effect. These drugs could offer advantages such as greater antidepressant effects, fewer side effects, and better long term tolerability, but these assumptions must be tested empirically. Other near term possibilities include novel rapid antidepressant treatments, such as (es)ketamine that putatively targets the glutamatergic system, and has been recently approved for treatment resistant depression, but which have not yet been tested in phase 3 studies in bipolar depression. Small studies have shown comparable effects of intravenous ketamine, 149 184 in bipolar depression with no short term evidence of increased mood switching or mood instability. Larger phase 2 studies ( NCT05004896 ) are being conducted which will need to be followed by larger phase 3 studies. Other therapies targeting the glutamatergic system have generally failed phase 3 trials in treatment resistant depression, making them unlikely to be tested in bipolar depression. One exception could be the combination of dextromethorphan and its pharmacokinetic (CYP2D6) inhibitor bupropion, which was recently approved for treatment resistant depression but has yet to be tested in bipolar depression. Similarly, the novel GABAergic compound zuranolone is currently being evaluated by the FDA for the treatment of major depressive disorder and could also be subsequently studied in bipolar depression.

Unfortunately, given the general efficacy for most patients of available treatments, few scientific and financial incentives exist to perform large scale studies of novel treatment in mania. Encouraging results have been seen in small studies of mania with the selective estrogen receptor modulator 185 tamoxifen and its active metabolite endoxifen, both of which are hypothesized to inhibit protein kinase C, a potential mechanistic target of lithium treatment. These studies remain small, however, and anti-estrogenic side effects have potentially dulled interest in performing larger studies.

Finally, several compounds targeting alternative pathophysiological mechanisms implicated in bipolar disorder have been trialed in phase 2 academic studies. The most studied has been N -acetylcysteine, a putative mitochondrial modulator, which initially showed promising results only to be followed by null findings in larger more recent studies. 186 Similarly, although small initial studies of anti-inflammatory agents provided impetus for further study, subsequent phase 2 studies of the non-steroidal agent celecoxib, 187 the anti-inflammatory antibiotic minocycline, 187 and the antibody infliximab (a tumor necrosis factor antagonist) 188 have not shown efficacy for bipolar depression. Secondary analyses have suggested that specific anti-inflammatory agents might be effective only for a subset of patients, such as those with elevated markers of inflammation or a history of childhood adversity 189 ; however, such hypotheses must be confirmed in adequately powered independent studies.

Several international guidelines for the treatment of bipolar disorder have been published in the past decade, 102 190 191 192 providing a list of recommended treatments with efficacy in at least one large randomized controlled trial. Since effect sizes tend to be moderate and broadly comparable across classes, all guidelines allow for significant choice among first line agents, acknowledging that clinical characteristics, such as history of response or tolerability, severity of symptoms, presence of mixed features, or rapid cycling can sometimes over-ride guideline recommendations. For acute mania requiring rapid treatment, all guidelines prioritize the use of second generation antipsychotics such as aripiprazole, quetiapine, risperidone, asenapine, and cariprazine. 102 192 193 Combination treatment is considered based on symptom severity, tolerability, and patient choice, with most guidelines recommending lithium or divalproate along with a second generation antipsychotic for mania with psychosis, severe agitation, or prominent mixed symptoms. While effective, haloperidol is usually considered a second choice option owing to its propensity to cause extrapyramidal symptoms. 102 192 193 Uniformly, all guidelines agree on the need to taper antidepressants in manic or mixed episodes.

For maintenance treatment, guidelines are generally consistent in recommending lithium if tolerated and without relative contraindications, such as baseline renal disease. 194 The second most recommended maintenance treatment is quetiapine, followed by aripiprazole for patients with prominent manic episodes and lamotrigine for patients with predominant depressive episodes. 194 Most guidelines recommend considering prophylactic properties when initially choosing treatment for acute manic episodes, although others suggests that acute maintenance treatments can be cross tapered with maintenance medications after several months of full reponse. 193

For bipolar depression, recent guidelines recommend specific second generation antipsychotics such as quetiapine, lurasidone, and cariprazine 102 192 193 For more moderate symptoms, consideration is given to first using lamotrigine and lithium. Guidelines remain cautious about the use of antidepressants (selective serotonin reuptake inhibitors, venlafaxine, or bupropion) in patients with BP-I, restricting them to second or third line treatments and always in the context of an anti-manic agent. However, for patients with BP-II and no rapid cycling, several guidelines allow for the use of carefully monitored antidepressant monotherapy.

Bipolar disorder is a highly recognizable syndrome with many effective treatment options, including the longstanding gold standard therapy lithium. However, a significant proportion of patients do not respond well to current treatments, leading to negative consequences, poor quality of life, and potentially shortened lifespan. Several novel treatments are being developed but limited knowledge of the biology of bipolar disorder remains a major challenge for novel drug discovery. Hope remains that the insights of genetics, neuroimaging, and other investigative modalities could soon be able to inform the development of rational treatments aimed to mitigate the underlying pathophysiology associated with bipolar disorder. At the same time, however, efforts are needed to bridge the implementation gap and provide truly innovative and integrative care for patients with bipolar disorder. 195 Owing to the complexity of bipolar disorder, few patients can be said to be receiving optimized care across the various domains of mental health that are affected in those with bipolar disorder. Fortunately, the need for improvement is now well documented, 196 and concerted efforts at the scale necessary to be truly innovative and integrative are now on the horizon.

Questions for future research

Among adolescents and young adults who manifest common mental disorders such as anxiety or depressive or attentional disorders, who will be at high risk for developing bipolar disorder?

Can we predict the outcomes for patients following a first manic or hypomanic episode? This will help to inform who will require lifelong treatment and who can be tapered off medications after sustained recovery.

Are there reliable clinical features and biomarkers that can sufficiently predict response to specific medications or classes of medication?

What are the long term consequences of lifelong treatments with the major classes of medications used in bipolar disorder? Can we predict and prevent medical morbidity caused by medications?

Can we understand in a mechanistic manner the pathophysiological processes that lead to abnormal mood states in bipolar disorder?

Series explanation: State of the Art Reviews are commissioned on the basis of their relevance to academics and specialists in the US and internationally. For this reason they are written predominantly by US authors

Contributors: FSG performed the planning, conduct, and reporting of the work described in the article. FSG accepts full responsibility for the work and/or the conduct of the study, had access to the data, and controlled the decision to publish.

Competing interests: I have read and understood the BMJ policy on declaration of interests and declare no conflicts of interest.

Patient involvement: FSG discussed of the manuscript, its main points, and potential missing points with three patients in his practice who have lived with longstanding bipolar disorder. These additional viewpoints were incorporated during the drafting of the manuscript.

Provenance and peer review: Commissioned; externally peer reviewed.

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Bipolar disorder is a mood disorder that includes at least one manic episode – characterized by elevated or agitated mood and often reduced need for sleep – accompanied by episodes of major depression.

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