Rare copy number variants (CNVs) are a key component of the genetic basis of psychiatric conditions, but have not been well characterized for most. We conducted a genome-wide CNV analysis across six diagnostic categories (N = 574,965): autism (ASD), ADHD, bipolar disorder (BD), major depressive disorder (MDD), PTSD, and schizophrenia (SCZ). We identified 35 genome-wide significant associations at 18 loci, including novel associations in SCZ ( SMYD3, USP7 - HAPSTR1 ) and in the combined cross-disorder analysis ( ASTN2 ). Rare CNVs accounted for 1-3% of heritability across diagnoses. In ASD, associations were uniformly positive, consistent with autism having diverse etiologies and clinical presentations. By contrast, CNVs showed a dose-dependent relationship for other diagnoses, including SCZ and PTSD, with reciprocal deletions and duplications having inversely correlated effects and distinct genotype-phenotype relationships. Our findings suggest that genes have effects that are both dose-dependent and pleiotropic, such that a positive influence on one dimension of psychopathology may be accompanied by positive or negative effects on others.

Delay discounting (DD), a person’s preference for smaller immediate rewards over larger delayed rewards, is a heritable trait that is associated with psychiatric and physical outcomes, yet the biological mechanisms underlying these links are not known. We performed a GWAS of DD using 134,935 23andMe research participants and identified 11 genome-wide significant loci. We did not replicate our previously reported association with rs6528024 (chrXq13.3, GPM6B; P = 5.30 × 10−02). The SNP-heritability of DD was 9.85 ± 0.57%. We observed genetic correlations between DD and 73 behavioral, physical, and neuroimaging traits, many of which persisted even after accounting for educational attainment, intelligence, and executive function. Network analysis revealed that the associations between DD and certain traits were explained by both overlapping and trait-specific biological processes. In a hospital-based cohort (N = 66,917), DD polygenic scores were associated with 212 medical conditions. These results demonstrate that DD has a pleiotropic and polygenic common variant architecture, and is genetically associated with numerous outcomes, making it a promising endophenotype for psychiatric and physical health.

Bipolar disorder is a leading contributor to the global burden of disease1. Despite high heritability (60-80%), the majority of the underlying genetic determinants remain unknown2. We analysed data from participants of European, East Asian, African American and Latino ancestries (n = 158,036 cases with bipolar disorder, 2.8 million controls), combining clinical, community and self-reported samples. We identified 298 genome-wide significant loci in the multi-ancestry meta-analysis, a fourfold increase over previous findings3, and identified an ancestry-specific association in the East Asian cohort. Integrating results from fine-mapping and other variant-to-gene mapping approaches identified 36 credible genes in the aetiology of bipolar disorder. Genes prioritized through fine-mapping were enriched for ultra-rare damaging missense and protein-truncating variations in cases with bipolar disorder4, highlighting convergence of common and rare variant signals. We report differences in the genetic architecture of bipolar disorder depending on the source of patient ascertainment and on bipolar disorder subtype (type I or type II). Several analyses implicate specific cell types in the pathophysiology of bipolar disorder, including GABAergic interneurons and medium spiny neurons. Together, these analyses provide additional insights into the genetic architecture and biological underpinnings of bipolar disorder.

Importance:The clinical heterogeneity of bipolar disorder (BD) is a major obstacle to improving diagnosis, predicting patient outcomes, and developing personalized treatments. A genetic approach is needed to deconstruct the disorder and uncover its fundamental biology. Previous genetic studies focusing on broad diagnostic categories have been limited in their ability to parse this complexity. Objective:To test the hypothesis that clinically distinct subphenotypes of BD are associated with different underlying common variant genetic architectures. Design Setting and Participants:This multicenter study included a primary genome-wide association study (GWAS) of up to 23,819 bipolar disorder (BD) cases and 163,839 controls. These results were integrated via multi-trait analysis of GWAS (MTAG) with external summary statistics for BD (59,287 cases; 781,022 controls) and schizophrenia (SCZ; 53,386 cases; 77,258 controls). Sample overlap was statistically accounted for. Main Outcomes and Measures:The primary outcomes were the genetic dimensions underlying BD heterogeneity, differentiated by single nucleotide polymorphism (SNP)-heritability (h 2 SNP ), genetic correlations, genomic loci ( P ≤5×10 -8 ), and functional, cell-type, and gene-expression pathway analyses. Results:We identified four genetically-informed dimensions of BD: Severe Illness, Core Mania, Externalizing/Impulsive Comorbidity, and Internalizing/Affective Comorbidity. The analyses yielded up to 181 subphenotype-associated loci, 53 of which are novel. The Severe Illness Dimension was characterized by a unique neuro-immune signature (a protective association with HLA-DMB , P =2.50×10 -273 ) evident only when leveraging SCZ genetic data. The Internalizing/Affective dimension was associated with neurodevelopmental genes (e.g., DCC ). Notably, the rapid-cycling subphenotype showed a unique signature of strong negative selection, a finding not observed in other subphenotypes. Conclusions and Relevance:The clinical heterogeneity of bipolar disorder appears to be defined by a complex and multi-layered genetic architecture. The presented findings provide an empirical framework that may advance psychiatric nosology beyond its current diagnostic boundaries. These results may also inform future research to identify targets for personalized interventions. The delineation of these genetically-informed dimensions offers specific, biologically-grounded hypotheses for subsequent therapeutic discovery. Establishing such a framework is an essential step toward refining diagnostic criteria and developing more effective, personalized treatments. This work lays the foundation for a transition from a uniform treatment model to the paradigm of precision psychiatry. Key Points:Question: What are the distinct genetic architectures underlying the clinical heterogeneity of bipolar disorder?Findings: In this genetic study of 23,819 bipolar disorder (BD) cases and 163,839 controls, clinical heterogeneity mapped onto four genetically-informed dimensions. A severe illness dimension was defined by a neuro-immune signature ( HLA-DMB ) shared with schizophrenia. An affective comorbidity dimension was distinguished by neurodevelopmental pathways involving axonal guidance ( DCC ). Notably, the rapid-cycling phenotype showed evidence of purifying selection, suggesting influence by rare, highly penetrant alleles. Meaning: These findings provide a data-driven biological framework for bipolar disorder, guiding future research toward patient stratification and targeted therapeutics.

Delay discounting (DD), a person's preference for smaller immediate rewards over larger delayed rewards, is a heritable trait that is associated with psychiatric and physical outcomes, yet the biological mechanisms underlying these links are not known. We performed a GWAS of DD using 134,935 adults and identified 14 genome-wide significant loci. We observed genetic correlations between DD and 73 behavioral, physical and neuroimaging traits, many of which persisted even after accounting for educational attainment, intelligence, and executive function. Network analysis revealed that the associations between DD and certain traits were explained by both overlapping and trait-specific biological processes. In a hospital-based cohort (N = 66,917), DD polygenic scores were associated with 212 medical conditions. These results demonstrate that DD has a pleiotropic and polygenic common variant architecture, and is genetically associated with numerous outcomes, making it a promising endophenotype for psychiatric and physical health.

Back to table of contents Previous article Priority Data LetterNo AccessSensitivity of Schizophrenia Endophenotype Biomarkers to Anticholinergic Medication BurdenYash B. Joshi, M.D., Ph.D., Juan L. Molina, M.D., David L. Braff, M.D., Michael F. Green, Ph.D., Ruben C. Gur, Ph.D., Raquel E. Gur, M.D., Ph.D., Keith H. Nuechterlein, Ph.D., William S. Stone, Ph.D., Tiffany A. Greenwood, Ph.D., Laura C. Lazzeroni, Ph.D., Allen D. Radant, M.D., Jeremy M. Silverman, Ph.D., Joyce Sprock, B.A., Catherine A. Sugar, Ph.D., Debby W. Tsuang, M.D., Ph.D., Ming T. Tsuang, M.D., Ph.D., Bruce I. Turetsky, M.D., Neal R. Swerdlow, M.D., Ph.D., Gregory A. Light, Ph.D.Yash B. Joshi, M.D., Ph.D., Juan L. Molina, M.D., David L. Braff, M.D., Michael F. Green, Ph.D., Ruben C. Gur, Ph.D., Raquel E. Gur, M.D., Ph.D., Keith H. Nuechterlein, Ph.D., William S. Stone, Ph.D., Tiffany A. Greenwood, Ph.D., Laura C. Lazzeroni, Ph.D., Allen D. Radant, M.D., Jeremy M. Silverman, Ph.D., Joyce Sprock, B.A., Catherine A. Sugar, Ph.D., Debby W. Tsuang, M.D., Ph.D., Ming T. Tsuang, M.D., Ph.D., Bruce I. Turetsky, M.D., Neal R. Swerdlow, M.D., Ph.D., Gregory A. Light, Ph.D.Published Online:11 Apr 2023https://doi.org/10.1176/appi.ajp.20220649AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail View article Access content To read the fulltext, please use one of the options below to sign in or purchase access. Personal login Institutional Login Sign in via OpenAthens Register for access Purchase Save for later Item saved, go to cart PPV Articles - American Journal of Psychiatry $35.00 Add to cart PPV Articles - American Journal of Psychiatry Checkout Please login/register if you wish to pair your device and check access availability. Not a subscriber? Subscribe Now / Learn More PsychiatryOnline subscription options offer access to the DSM-5 library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development. Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.). FiguresReferencesCited byDetailsCited byPoints that Need Attention in Early Auditory Information Processing Research in Schizophrenia: Response to Lin and HsiehYash Joshi, M.D., Ph.D., Neal Swerdlow, M.D., Ph.D., Gregory Light, Ph.D.1 November 2023 | American Journal of Psychiatry, Vol. 180, No. 11Points that Need Attention in Early Auditory Information Processing Research in SchizophreniaYi-Ting Lin, M.D. Ming H. Hsieh, M.D., Ph.D.1 November 2023 | American Journal of Psychiatry, Vol. 180, No. 11The Power of PotentialsSteven Siegel, M.D., Ph.D., Lindsey Crown, Ph.D., Robert Featherstone, Ph.D.1 July 2023 | American Journal of Psychiatry, Vol. 180, No. 7From Postmortem Molecular Studies to Social Determinants of Health Relevant to Racial and Ethnic DisparitiesNed H. Kalin, M.D.1 July 2023 | American Journal of Psychiatry, Vol. 180, No. 7 Volume 180Issue 7 July 01, 2023Pages 519-523 Metrics KeywordsSchizophrenia Spectrum and Other Psychotic DisordersCognition/Learning/MemoryPharmacotherapyPDF download History Received 27 July 2022 Revised 2 November 2022 Accepted 12 December 2022 Published online 11 April 2023 Published in print 1 July 2023

Identifying heritable factors that moderate the genetic risk for schizophrenia (SCZ) could help clarify why some individuals remain unaffected despite having relatively high genetic liability. Previously, we developed a framework to mine genome-wide association (GWAS) data for common genetic variants that protect high-risk unaffected individuals from SCZ, leading to derivation of the first-ever "polygenic resilience score" for SCZ (resilient controls n = 3786; polygenic risk score-matched SCZ cases n = 18,619). Here, we performed a replication study to verify the moderating effect of our polygenic resilience score on SCZ risk (OR = 1.09, p = 4.03 × 10-5 ) using newly released GWAS data from 23 independent case-control studies collated by the Psychiatric Genomics Consortium (PGC) (resilient controls n = 2821; polygenic risk score-matched SCZ cases n = 5150). Additionally, we sought to optimize our polygenic resilience-scoring formula to improve subsequent modeling of resilience to SCZ and other complex disorders. We found significant replication of the polygenic resilience score, and found that strict pruning of SNPs based on linkage disequilibrium to known risk SNPs and their linked loci optimizes the performance of the polygenic resilience score.

Schizophrenia is a severe and debilitating psychotic disorder that is highly heritable and relatively common in the population. The clinical heterogeneity associated with schizophrenia is substantial, with patients exhibiting a broad range of deficits and symptom severity. Large-scale genomic studies employing a case-control design have begun to provide some biological insight. However, this strategy combines individuals with clinically diverse symptoms and ignores the genetic risk that is carried by many clinically unaffected individuals. Consequently, the majority of the genetic architecture underlying schizophrenia remains unexplained, and the pathways by which the implicated variants contribute to the clinically observable signs and symptoms are still largely unknown. Parsing the complex, clinical phenotype of schizophrenia into biologically relevant components may have utility in research aimed at understanding the genetic basis of liability. Cognitive dysfunction is a hallmark symptom of schizophrenia that is associated with impaired quality of life and poor functional outcome. Here, we examine the value of quantitative measures of cognitive dysfunction to objectively target the underlying neurobiological pathways and identify genetic variants and gene networks contributing to schizophrenia risk. For a complex disorder, quantitative measures are also more efficient than diagnosis, allowing for the identification of associated genetic variants with fewer subjects. Such a strategy supplements traditional analyses of schizophrenia diagnosis, providing the necessary biological insight to help translate genetic findings into actionable treatment targets. Understanding the genetic basis of cognitive dysfunction in schizophrenia may thus facilitate the development of novel pharmacological and procognitive interventions to improve real-world functioning.

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

Creativity has long been associated with the bipolar spectrum, particularly among unaffected first-degree rela-tives and those with milder expressions of bipolar traits, suggesting that some aspects of the bipolar spectrum may confer advantages for creativity. Here we took a multifaceted approach to better define the shared vulnerability between creativity and bipolar disorder. We recruited 135 individuals with bipolar disorder, 102 creative controls, and 103 non-creative controls for a total of 340 participants. All participants completed a comprehensive assessment battery that included several self-report temperament and personality questionnaires, a computerized test of cognitive function across multiple domains, and an evaluation of creative performance and achievement. Significant group differences were observed for the hypothesized shared vulnerability traits of hypomanic personality, cyclothymic temperament, impulsivity, and positive schizotypy. While both the creative and bipolar groups demonstrated superior creative ability, the creative group alone revealed enhanced cognitive performance. Accounting for intercorrelations between traits, a combination of openness, hypomanic person-ality, divergent thinking, and reasoning ability emerged as the strongest predictors of creativity, collectively explaining 34% of the variance in creative achievement and correctly classifying 85% of individuals with high achievement irrespective of diagnosis. These results confirm and extend earlier observations of a shared vulnerability between creativity and bipolar disorder and suggest that mild to moderate expressions of bipolar spectrum traits are associated with enhanced cognitive functioning and creative expression. Further investigation of these traits is needed to clarify the nature of this shared vulnerability and suggest individualized treatment strategies to improve clinical outcomes in bipolar disorder.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies. Genome-wide association analyses of 41,917 bipolar disorder cases and 371,549 controls of European ancestry provide new insights into the etiology of this disorder and identify novel therapeutic leads and potential opportunities for drug repurposing.

OBJECTIVE:Many psychotropic medications used to treat schizophrenia have significant anticholinergic properties, which are linked to cognitive impairment and dementia risk in healthy subjects. Clarifying the impact of cognitive impairment attributable to anticholinergic medication burden may help optimize cognitive outcomes in schizophrenia. The aim of this study was to comprehensively characterize how this burden affects functioning across multiple cognitive domains in schizophrenia outpatients.METHODS:Cross-sectional data were analyzed using inferential statistics and exploratory structural equation modeling to determine the relationship between anticholinergic medication burden and cognition. Patients with a diagnosis of schizophrenia or schizoaffective disorder (N=1,120) were recruited from the community at five U.S. universities as part of the Consortium on the Genetics of Schizophrenia-2. For each participant, prescribed medications were rated and summed according to a modified Anticholinergic Cognitive Burden (ACB) scale. Cognitive functioning was assessed by performance on domains of the Penn Computerized Neurocognitive Battery (PCNB).RESULTS:ACB score was significantly associated with cognitive performance, with higher ACB groups scoring worse than lower ACB groups on all domains tested on the PCNB. Similar effects were seen on other cognitive tests. Effects remained significant after controlling for demographic characteristics and potential proxies of illness severity, including clinical symptoms and chlorpromazine-equivalent antipsychotic dosage.CONCLUSIONS:Anticholinergic medication burden in schizophrenia is substantial, common, conferred by multiple medication classes, and associated with cognitive impairments across all cognitive domains. Anticholinergic medication burden from all medication classes-including psychotropics used in usual care-should be considered in treatment decisions and accounted for in studies of cognitive functioning in schizophrenia.

Abstract Background Schizophrenia and bipolar disorder are debilitating neuropsychiatric illnesses collectively affecting 2% of the world’s population, and which cause tremendous human suffering that impacts patients, their families and their communities. Recognizing the major impact of these disorders on the psychosocial function of more than 200,000 US Veterans, the Department of Veterans Affairs (VA) recently genotyping of nearly 9,000 veterans with schizophrenia or bipolar I disorder in Cooperative Studies Program (CSP) #572: “Genetics of Functional Disability in Schizophrenia and Bipolar Illness”, all of whom were extensively assessed for neurocognitive function and disability, and genotyped using a custom Affymetrix Axiom Biobank array. Methods Primary genome-wide association studies (GWAS) of schizophrenia and bipolar disorder were performed across and within ancestry goups, with attempted replication in matched subjects from the PGC and Genomic Psychiatry Cohort (GPC). We combined results for CSP#572 with available summary statistics from the PGC, Indonesia Schizophrenia Consortium and Genetic REsearch on schizophreniA neTwork-China and Netherland (GREAT-CN) study, and multi-ethnic GPC cohorts, achieving among the largest and most diverse studies of these disorders to date. Results Polygenic risk scores based on published PGC summary statistics for schizophrenia or bipolar disorder were significantly associated with case status among EA (P<10–30) and AA (P<0.0005) participants in CSP#572. Our primary analyses of schizophrenia yielded a single genome-wide significant association with variants in CHD7 at 8q12.2 for European-American (EA) participants, which remained significant in a joint analysis of EA and African-American (AA) subjects (P=4.62e-08). While no genome-wide significant associations were detected by our within-ancestry analyses of bipolar disorder, a cross-ancestry meta-analysis of CSP#572 participants yielded a significant finding at 10q25 with variants in SORCS3 (P=2.62e-08). Among loci attaining P<0.0001 in our within-ancestry analyses, 4 and 8 subsequently achieved genome-wide significance, respectively, when jointly analyzed with matched subjects from the PGC and GPC. Combining our results with published summary statistics, we performed a cross-ancestry GWAS meta-analysis of 69,280 schizophrenia cases and 138,379 controls, identifying 200 genome-wide significant loci of which 76 are newly reported here. Cross-ancestry analysis of 28,326 bipolar cases and 90,570 controls identified 24 genome-wide significant loci, including novel associations with common variants in PAX5, DOCK2, MACROD2, BRE, KCNG1, and LINC01378. Discussion We newly describe genome-wide analyses in a diverse cohort of US Veterans with schizophrenia or bipolar disorder, benchmarking the predictive value of polygenic risk scores based on published GWAS findings. Leveraging available summary statistics from studies of global populations, we add to burgeoning lists of genomic loci implicated in the etiologies of these disorders.

Bipolar disorder is a lifelong mood disorder characterized by extreme mood swings between mania and depression. Despite fitness costs associated with increased mortality and significant impairment, bipolar disorder has persisted in the population with a high heritability and a stable prevalence. Creativity and other positive traits have repeatedly been associated with the bipolar spectrum, particularly among unaffected first-degree relatives and those with milder expressions of bipolar traits. This suggests a model in which large doses of risk variants cause illness, but mild to moderate doses confer advantages, which serve to maintain bipolar disorder in the population. Bipolar disorder may thus be better conceptualized as a dimensional trait existing at the extreme of normal population variation in positive temperament, personality, and cognitive traits, aspects of which may reflect a shared vulnerability with creativity. Investigations of this shared vulnerability may provide insight into the genetic mechanisms underlying illness and suggest novel treatments.

Recently emerging evidence indicates accelerated age-related changes in the structure and function of the brain in schizophrenia, raising a question about its potential consequences on cognitive function. Using a large sample of schizophrenia patients and controls and a battery of tasks across multiple cognitive domains, we examined whether patients show accelerated age-related decline in cognition and whether an age-related effect differ between females and males. We utilized data of 1,415 schizophrenia patients and 1,062 healthy community collected by the second phase of the Consortium on the Genetics of Schizophrenia (COGS-2). A battery of cognitive tasks included the Letter-Number Span Task, two forms of the Continuous Performance Test, the California Verbal Learning Test, Second Edition, the Penn Emotion Identification Test and the Penn Facial Memory Test. The effect of age and gender on cognitive performance was examined with a general linear model. We observed age-related changes on most cognitive measures, which was similar between males and females. Compared to controls, patients showed greater deterioration in performance on attention/vigilance and greater slowness of processing social information with increasing age. However, controls showed greater age-related changes in working memory and verbal memory compared to patients. Age-related changes (η2p of 0.001 to .008) were much smaller than between-group differences (η2p of 0.005 to .037). This study found that patients showed continued decline of cognition on some domains but stable impairment or even less decline on other domains with increasing age. These findings indicate that age-related changes in cognition in schizophrenia are subtle and not uniform across multiple cognitive domains.

Background: Latency of the acoustic startle reflex is the time from presentation of the startling stimulus until the response, and provides an index of neural processing speed. Schizophrenia subjects exhibit slowed latency compared to healthy controls. One prior publication reported significant heritability of latency. The current study was undertaken to replicate and extend this solitary finding in a larger cohort. Methods: Schizophrenia probands, their relatives, and control subjects from the Consortium on the Genetics of Schizophrenia (COGS-1) were tested in a paradigm to ascertain magnitude, latency, and prepulse inhibition of startle. Trial types in the paradigm were: pulse-alone, and trials with 30, 60, or 120 ms between the prepulse and pulse. Comparisons of subject groups were conducted with ANCOVAs to assess startle latency and magnitude. Heritability of startle magnitude and latency was analyzed with a variance component method implemented in SOLAR v.4.3.1. Results: 980 subjects had analyzable startle results: 199 schizophrenia probands, 456 of their relatives, and 325 controls. A mixed-design ANCOVA on startle latency in the four trial types was significant for subject group (F (2,973) = 4.45, p = 0.012) such that probands were slowest, relatives were intermediate and controls were fastest. Magnitude to pulse-alone trials differed significantly between groups by ANCOVA (F(2,974) = 3.92, p = 0.020) such that controls were lowest, probands highest, and relatives intermediate. Heritability was significant (p < 0.0001), with heritability of 34-41% for latency and 45-59% for magnitude. Conclusion: Both startle latency and magnitude are significantly heritable in the COGS-1 cohort. Startle latency is a strong candidate for being an endophenotype in schizophrenia. Published by Elsevier B.V.y

Bipolar disorder (BD) is a heritable mental illness with complex etiology. We performed a genome-wide association study (GWAS) of 41,917 BD cases and 371,549 controls, which identified 64 associated genomic loci. BD risk alleles were enriched in genes in synaptic and calcium signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers and antiepileptics. Integrating eQTL data implicated 15 genes robustly linked to BD via gene expression, including druggable genes such as HTR6, MCHR1, DCLK3 and FURIN. This GWAS provides the best-powered BD polygenic scores to date, when applied in both European and diverse ancestry samples. Together, these results advance our understanding of the biological etiology of BD, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

Natural systems, including the brain, often seem chaotic, since they are typically driven by complex nonlinear dynamical processes. Disruption in the fluid coordination of multiple brain regions contributes to impairments in information processing and the constellation of symptoms observed in neuropsychiatric disorders. Schizophrenia (SZ), one of the most debilitating mental illnesses, is thought to arise, in part, from such a network dysfunction, leading to impaired auditory information processing as well as cognitive and psychosocial deficits. Current approaches to neurophysiologic biomarker analyses predominantly rely on linear methods and may, therefore, fail to capture the wealth of information contained in whole EEG signals, including nonlinear dynamics. In this study, delay differential analysis (DDA), a nonlinear method based on embedding theory from theoretical physics, was applied to EEG recordings from 877 SZ patients and 753 nonpsychiatric comparison subjects (NCSs) who underwent mismatch negativity (MMN) testing via their participation in the Consortium on the Genetics of Schizophrenia (COGS-2) study. DDA revealed significant nonlinear dynamical architecture related to auditory information processing in both groups. Importantly, significant DDA changes preceded those observed with traditional linear methods. Marked abnormalities in both linear and nonlinear features were detected in SZ patients. These results illustrate the benefits of nonlinear analysis of brain signals and underscore the need for future studies to investigate the relationship between DDA features and pathophysiology of information processing.