Publications by authors named "Sarah E Bergen"

60 Publications

Genetic risk for bipolar disorder and schizophrenia predicts structure and function of the ventromedial prefrontal cortex.

J Psychiatry Neurosci 2021 Jul 22;46(4):E441-E450. Epub 2021 Jul 22.

From the Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden (Abé, Petrovic, Ossler, Thompson, Liberg, Fransson, Ingvar, Landén); the Department of Psychology, Stanford University, Stanford, California, USA (Thompson); the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (Song, Bergen); the Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden (Sellgren); Karolinska University Hospital, Department of Neuroradiology, Stockholm, Sweden (Ingvar); and the Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Sweden (Landén).

Background: Bipolar disorder is highly heritable and polygenic. The polygenic risk for bipolar disorder overlaps with that of schizophrenia, and polygenic scores are normally distributed in the population. Bipolar disorder has been associated with structural brain abnormalities, but it is unknown how these are linked to genetic risk factors for psychotic disorders.

Methods: We tested whether polygenic risk scores for bipolar disorder and schizophrenia predict structural brain alterations in 98 patients with bipolar disorder and 81 healthy controls. We derived brain cortical thickness, surface area and volume from structural MRI scans. In post-hoc analyses, we correlated polygenic risk with functional hub strength, derived from resting-state functional MRI and brain connectomics.

Results: Higher polygenic risk scores for both bipolar disorder and schizophrenia were associated with a thinner ventromedial prefrontal cortex (vmPFC). We found these associations in the combined group, and separately in patients and drug-naive controls. Polygenic risk for bipolar disorder was correlated with the functional hub strength of the vmPFC within the default mode network.

Limitations: Polygenic risk is a cumulative measure of genomic burden. Detailed genetic mechanisms underlying brain alterations and their cognitive consequences still need to be determined.

Conclusion: Our multimodal neuroimaging study linked genomic burden and brain endophenotype by demonstrating an association between polygenic risk scores for bipolar disorder and schizophrenia and the structure and function of the vmPFC. Our findings suggest that genetic factors might confer risk for psychotic disorders by influencing the integrity of the vmPFC, a brain region involved in self-referential processes and emotional regulation. Our study may also provide an imaging-genetics vulnerability marker that can be used to help identify individuals at risk for developing bipolar disorder.
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http://dx.doi.org/10.1503/jpn.200165DOI Listing
July 2021

Environmental Risk Factors for Schizophrenia and Bipolar Disorder and Their Relationship to Genetic Risk: Current Knowledge and Future Directions.

Front Genet 2021 28;12:686666. Epub 2021 Jun 28.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Schizophrenia (SZ) and bipolar disorder (BD) are severe psychiatric disorders which result from complex interplay between genetic and environmental factors. It is well-established that they are highly heritable disorders, and considerable progress has been made identifying their shared and distinct genetic risk factors. However, the 15-40% of risk that is derived from environmental sources is less definitively known. Environmental factors that have been repeatedly investigated and often associated with SZ include: obstetric complications, infections, winter or spring birth, migration, urban living, childhood adversity, and cannabis use. There is evidence that childhood adversity and some types of infections are also associated with BD. Evidence for other risk factors in BD is weaker due to fewer studies and often smaller sample sizes. Relatively few environmental exposures have ever been examined for SZ or BD, and additional ones likely remain to be discovered. A complete picture of how genetic and environmental risk factors confer risk for these disorders requires an understanding of how they interact. Early gene-by-environment interaction studies for both SZ and BD often involved candidate genes and were underpowered. Larger samples with genome-wide data and polygenic risk scores now offer enhanced prospects to reveal genetic interactions with environmental exposures that contribute to risk for these disorders. Overall, although some environmental risk factors have been identified for SZ, few have been for BD, and the extent to which these account for the total risk from environmental sources remains unknown. For both disorders, interactions between genetic and environmental risk factors are also not well understood and merit further investigation. Questions remain regarding the mechanisms by which risk factors exert their effects, and the ways in which environmental factors differ by sex. Concurrent investigations of environmental and genetic risk factors in SZ and BD are needed as we work toward a more comprehensive understanding of the ways in which these disorders arise.
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http://dx.doi.org/10.3389/fgene.2021.686666DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8273311PMC
June 2021

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.

Nat Genet 2021 06 17;53(6):817-829. Epub 2021 May 17.

Department of Neuroscience, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.

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.
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http://dx.doi.org/10.1038/s41588-021-00857-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192451PMC
June 2021

Lack of Support for the Genes by Early Environment Interaction Hypothesis in the Pathogenesis of Schizophrenia.

Schizophr Bull 2021 May 14. Epub 2021 May 14.

Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.

Ursini et al reported recently that the liability of schizophrenia explained by a polygenic risk score (PRS) derived from the variants most associated with schizophrenia was increased 5-fold in individuals who experienced complications during pregnancy or birth. Follow-up gene expression analysis showed that the genes mapping to the most associated genetic variants are highly expressed in placental tissues. If confirmed, these findings will have major implications in our understanding of the joint effect of genes and environment in the pathogenesis of schizophrenia. We examined the interplay between PRS and obstetric complications (OCs) in 5 independent samples (effective N = 2110). OCs were assessed with the full or modified Lewis-Murray scale, or with birth weight < 2.5 kg as a proxy. In a large cohort we tested whether the pathways from placenta-relevant variants in the original report were associated with case-control status. Unlike in the original study, we did not find significant effect of PRS on the presence of OCs in cases, nor a substantial difference in the association of PRS with case-control status in samples stratified by the presence of OCs. Furthermore, none of the PRS by OCs interactions were significant, nor were any of the biological pathways, examined in the Swedish cohort. Our study could not support the hypothesis of a mediating effect of placenta biology in the pathway from genes to schizophrenia. Methodology differences, in particular the different scales measuring OCs, as well as power constraints for interaction analyses in both studies, may explain this discrepancy.
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http://dx.doi.org/10.1093/schbul/sbab052DOI Listing
May 2021

Association of family history of schizophrenia and clinical outcomes in individuals with eating disorders.

Psychol Med 2021 Apr 30:1-8. Epub 2021 Apr 30.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Background: Familial co-aggregation studies of eating disorders (EDs) and schizophrenia reveal shared genetic and environment factors, yet their etiological and clinical relationship remains unclear. We evaluate the influence of schizophrenia family history on clinical outcomes of EDs.

Methods: We conducted a cohort evaluation of the association between family history of schizophrenia and ED clinical features, psychiatric comorbidities, and somatic and mental health burden in individuals born in Sweden 1977-2003 with anorexia nervosa (AN) or other EDs (OED: bulimia nervosa, binge-eating disorder, and ED not otherwise specified).

Results: Of 12 424 individuals with AN and 20 716 individuals with OED, 599 (4.8%) and 1118 (5.4%), respectively, had a family history of schizophrenia (in up to third-degree relatives). Among individuals with AN, schizophrenia in first-degree relatives was significantly associated with increased comorbid attention-deficit/hyperactivity disorder (ADHD) [HR(95% CI) 2.26 (1.27-3.99)], substance abuse disorder (SUD) [HR (95% CI) 1.93 (1.25-2.98)], and anxiety disorders [HR (95% CI) 1.47 (1.08-2.01)], but higher lowest illness-associated body mass index (BMI) [1.14 kg/m2, 95% CI (0.19-2.10)]. Schizophrenia in any relative (up to third-degree) in AN was significantly associated with higher somatic and mental health burden, but lower ED psychopathology scores [-0.29, 95% CI (-0.54 to -0.04)]. Schizophrenia in first-degree relatives in individuals with OED was significantly associated with increased comorbid ADHD, obsessive-compulsive disorder, SUD, anxiety disorders, somatic and mental health burden, and suicide attempts.

Conclusions: We observed different patterns of ED-related outcomes, psychiatric comorbidity, and illness burden in individuals with EDs with and without family histories of schizophrenia and provide new insights into the diverse manifestations of EDs.
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http://dx.doi.org/10.1017/S0033291721001574DOI Listing
April 2021

Cross-sex shifts in two brain imaging phenotypes and their relation to polygenic scores for same-sex sexual behavior: A study of 18,645 individuals from the UK Biobank.

Hum Brain Mapp 2021 May 26;42(7):2292-2304. Epub 2021 Feb 26.

Department of Psychology, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK.

Genetic and hormonal factors have been suggested to influence human sexual orientation. Previous studied proposed brain differences related to sexual orientation and that these follow cross-sex shifted patterns. However, the neurobiological correlates of sexual orientation and how genetic factors relate to brain structural variation remains largely unexplored. Using the largest neuroimaging-genetics dataset available on same-sex sexual behavior (SSB) (n = 18,645), we employed a data-driven multivariate classification algorithm (PLS) on magnetic resonance imaging data from two imaging modalities to extract brain covariance patterns related to sex. Through analyses of latent variables, we tested for SSB-related cross-sex shifts in such patterns. Using genotype data, polygenic scores reflecting the genetic predisposition for SSB were computed and tested for associations with neuroimaging outcomes. Patterns important for classifying between males and females were less pronounced in non-heterosexuals. Predominantly in non-heterosexual females, multivariate brain patterns as represented by latent variables were shifted toward the opposite sex. Complementary univariate analyses revealed region specific SSB-related differences in both males and females. Polygenic scores for SSB were associated with volume of lateral occipital and temporo-occipital cortices. The present large-scale study demonstrates multivariate neuroanatomical correlates of SSB, and tentatively suggests that genetic factors related to SSB may contribute to structural variation in certain brain structures. These findings support a neurobiological basis to the differences in human sexuality.
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http://dx.doi.org/10.1002/hbm.25370DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046142PMC
May 2021

Overview of CAPICE-Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe-an EU Marie Skłodowska-Curie International Training Network.

Eur Child Adolesc Psychiatry 2021 Jan 20. Epub 2021 Jan 20.

Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

The Roadmap for Mental Health and Wellbeing Research in Europe (ROAMER) identified child and adolescent mental illness as a priority area for research. CAPICE (Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe) is a European Union (EU) funded training network aimed at investigating the causes of individual differences in common childhood and adolescent psychopathology, especially depression, anxiety, and attention deficit hyperactivity disorder. CAPICE brings together eight birth and childhood cohorts as well as other cohorts from the EArly Genetics and Life course Epidemiology (EAGLE) consortium, including twin cohorts, with unique longitudinal data on environmental exposures and mental health problems, and genetic data on participants. Here we describe the objectives, summarize the methodological approaches and initial results, and present the dissemination strategy of the CAPICE network. Besides identifying genetic and epigenetic variants associated with these phenotypes, analyses have been performed to shed light on the role of genetic factors and the interplay with the environment in influencing the persistence of symptoms across the lifespan. Data harmonization and building an advanced data catalogue are also part of the work plan. Findings will be disseminated to non-academic parties, in close collaboration with the Global Alliance of Mental Illness Advocacy Networks-Europe (GAMIAN-Europe).
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http://dx.doi.org/10.1007/s00787-020-01713-2DOI Listing
January 2021

Association of Youth Depression With Subsequent Somatic Diseases and Premature Death.

JAMA Psychiatry 2021 Mar;78(3):302-310

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden.

Importance: Early-onset depression has been linked to poor health outcomes. However, it is unclear the extent to which this disorder is associated with specific diseases and premature death and whether these associations remain after controlling for psychiatric comorbidity.

Objective: To quantify the association of youth depression with subsequent diagnoses of numerous somatic diseases and mortality.

Design, Setting, And Participants: A population-based cohort study was conducted using Swedish national registers containing data on all individuals born in Sweden between 1982 and 1996. A total of 1 487 964 participants were followed up from age 5 years through 2013 if no censoring occurred. Data analysis was performed from January 15, 2019, to August 10, 2020.

Exposures: Youth depression was defined as having received at least 1 diagnosis of depression from inpatient or outpatient care between ages 5 and 19 years.

Main Outcomes And Measures: This study examined 69 somatic conditions diagnosed after youth depression, as well as all-cause and cause-specific mortalities. Overall and sex-specific hazard ratios (HRs), together with 95% CIs, were estimated using Cox proportional hazards regression with attained age as underlying timescale and time-varying exposure, and adjusted for birth year and sex. All analyses were repeated controlling for psychiatric comorbidities. Absolute risk differences were calculated using standardization with Cox proportional hazards regression.

Results: Of 1 487 964 individuals included in the analysis, 51.2% were male. A total of 37 185 patients (2.5%; 67.4% female) had an inpatient or outpatient contact for depression between ages 5 and 19 years (mean [SD] age at first recorded diagnosis of depression, 16.7 [2.1] years for males and 16.7 [1.8] years for females). Age at the end of follow-up ranged between 17 and 31 years. Individuals with youth depression had higher relative risks for 66 of the 69 somatic diagnoses. Strong associations were observed for certain injuries, especially self-harm in females (HR, 14.4; 95% CI, 13.8-15.1), sleep disorders (HR, 8.1; 95% CI, 7.6-8.7), viral hepatitis (HR, 6.1; 95% CI, 5.4-6.8), all-cause mortality (HR, 5.9; 95% CI, 5.3-6.6), and cause-specific mortalities, especially death by intentional self-harm (HR, 14.6; 95% CI, 12.6-16.9). Most associations were attenuated but persisted after adjusting for psychiatric comorbidity. The absolute risk difference of a specific disease within 12 years from the first diagnosis of depression during youth ranged from -0.2% (95% CI, -1.0% to 0.6%) for arthropathies among males to 23.9% (95% CI, 22.7%-25.0%) for the broader category of injuries among females.

Conclusions And Relevance: In this Swedish population cohort study, patients with depression diagnosed during their youth appeared to have increased risks for many somatic diseases as well as for mortality, even after controlling for other psychiatric disorders. These findings suggest that several medical conditions should be considered when investigating youth depression.
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http://dx.doi.org/10.1001/jamapsychiatry.2020.3786DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7726699PMC
March 2021

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals.

Nat Metab 2020 10 16;2(10):1135-1148. Epub 2020 Oct 16.

SCALLOP consortium.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.
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http://dx.doi.org/10.1038/s42255-020-00287-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611474PMC
October 2020

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals.

Nat Metab 2020 10 16;2(10):1135-1148. Epub 2020 Oct 16.

SCALLOP consortium.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.
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http://dx.doi.org/10.1038/s42255-020-00287-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611474PMC
October 2020

A principal component approach to improve association testing with polygenic risk scores.

Genet Epidemiol 2020 10 21;44(7):676-686. Epub 2020 Jul 21.

Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota.

Polygenic risk scores (PRSs) have become an increasingly popular approach for demonstrating polygenic influences on complex traits and for establishing common polygenic signals between different traits. PRSs are typically constructed using pruning and thresholding (P+T), but the best choice of parameters is uncertain; thus multiple settings are used and the best is chosen. Optimization can lead to inflated Type I error. Permutation procedures can correct this, but they can be computationally intensive. Alternatively, a single parameter setting can be chosen a priori for the PRS, but choosing suboptimal settings results in loss of power. We propose computing PRSs under a range of parameter settings, performing principal component analysis (PCA) on the resulting set of PRSs, and using the first PRS-PC in association tests. The first PC reweights the variants included in the PRS to achieve maximum variation over all PRS settings used. Using simulations and a real data application to study PRS association with bipolar disorder and psychosis in bipolar disorder, we compare the performance of the proposed PRS-PCA approach with a permutation test and an a priori selected p-value threshold. The PRS-PCA approach is simple to implement, outperforms the other strategies in most scenarios, and provides an unbiased estimate of prediction performance.
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http://dx.doi.org/10.1002/gepi.22339DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722089PMC
October 2020

Chronicity and Sex Affect Genetic Risk Prediction in Schizophrenia.

Front Psychiatry 2020 9;11:313. Epub 2020 Jun 9.

Department of Biomedicine, Aarhus University, Aarhus, Denmark.

Schizophrenia (SCZ) is a severe mental disorder with immense personal and societal costs; identifying individuals at risk is therefore of utmost importance. Genomic risk profile scores (GRPS) have been shown to significantly predict cases-control status. Making use of a large-population based sample from Sweden, we replicate a previous finding demonstrating that the GRPS is strongly associated with admission frequency and chronicity of SCZ. Furthermore, we were able to show a substantial gap in prediction accuracy between males and females. In sum, our results indicate that prediction accuracy by GRPS depends on clinical and demographic characteristics.
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http://dx.doi.org/10.3389/fpsyt.2020.00313DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297201PMC
June 2020

Familial co-aggregation of schizophrenia and eating disorders in Sweden and Denmark.

Mol Psychiatry 2020 May 7. Epub 2020 May 7.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Eating disorders and schizophrenia are both moderately to highly heritable and share significant genetic risk despite distinct diagnostic criteria. Large-scale family studies on the co-aggregation of these disorders are lacking. Thus, we aimed to estimate the co-occurrence and familial co-aggregation of these disorders within the entire Swedish and Danish population. The proband cohort consisted of individuals born in Sweden (1977-2003) and Denmark (1984-2006) and still residing in their respective country at age six (N = 2,535,191, N = 1,382,367). Probands were linked to their biological parents, siblings, grandparents, uncles/aunts, and cousins. Diagnoses for anorexia nervosa (AN) and other eating disorders (OED: bulimia nervosa, binge-eating disorder, and eating disorder not otherwise specified) for probands and schizophrenia diagnoses for both probands and relatives were obtained. The likelihood of having schizophrenia in those with AN or OED and their relatives was compared with individuals without eating disorder diagnoses and their relatives. Probands with AN or OED were more likely to have schizophrenia than probands without these disorders. All relatives of probands with AN or OED (except parents and uncles/aunts of probands with AN) were at increased risk of schizophrenia. In general, the magnitude of odds ratios attenuated with decreasing genetic relatedness. These results suggest familial liability contributes to the association between eating disorders and schizophrenia. Clinicians should be mindful of this comorbid and co-aggregation pattern as it may influence case conceptualization and treatment decisions.
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http://dx.doi.org/10.1038/s41380-020-0749-xDOI Listing
May 2020

Genome-wide study of immune biomarkers in cerebrospinal fluid and serum from patients with bipolar disorder and controls.

Transl Psychiatry 2020 02 5;10(1):58. Epub 2020 Feb 5.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Bipolar disorder is a common, chronic psychiatric disorder. Despite high heritability, there is a paucity of identified genetic risk factors. Immune biomarkers are under more direct genetic influence than bipolar disorder. To explore the genetic associations with immune biomarker levels in cerebrospinal fluid (CSF) and blood serum which previously showed differences in bipolar disorder, we performed a study involving 291 individuals (184 bipolar disorder patients and 107 controls). The biomarkers assayed in both CSF and serum were: chitinase-3-like protein-1 (YKL-40), monocyte chemoattractant protein-1 (MCP-1), soluble cluster of differentiation (sCD14), tissue inhibitor of metalloproteinases-1 and 2 (TIMP-1 and TIMP-2). C-reactive protein (CRP) was only quantified in serum, and interleukin 8 (IL-8) measures were only available in CSF. Genome-wide association studies were conducted using PLINK for each of three genotyping waves and incorporated covariates for population substructure, age, sex, and body mass index (BMI). Results were combined by meta-analysis. Genome-wide significant associations were detected for all biomarkers except TIMP-1 and TIMP-2 in CSF. The strongest association in CSF was found for markers within the CNTNAP5 gene with YKL-40 (rs150248456, P = 2.84 × 10). The strongest association in serum was also for YKL-40 but localized to the FANCI gene (rs188263039, P = 5.80 × 10). This study revealed numerous biologically plausible genetic associations with immune biomarkers in CSF and blood serum. Importantly, the genetic variants regulating immune biomarker levels in CSF and blood serum differ. These results extend our knowledge of how biomarkers showing alterations in bipolar disorder are genetically regulated.
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http://dx.doi.org/10.1038/s41398-020-0737-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026056PMC
February 2020

Characterization of Single Gene Copy Number Variants in Schizophrenia.

Biol Psychiatry 2020 04 4;87(8):736-744. Epub 2019 Oct 4.

Division of Genetic Medicine, Departments of Medicine, Psychiatry, and Biomedical Informatics, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee. Electronic address:

Background: Genetic studies of schizophrenia have implicated numerous risk loci including several copy number variants (CNVs) of large effect and hundreds of loci of small effect. In only a few cases has a specific gene been clearly identified. Rare CNVs affecting a single gene offer a potential avenue to discovering schizophrenia risk genes.

Methods: CNVs were generated from exome sequencing of 4913 schizophrenia cases and 6188 control subjects from Sweden. We integrated two CNV calling methods (XHMM and ExomeDepth) to expand our set of single-gene CNVs and leveraged two different approaches for validating these variants (quantitative polymerase chain reaction and NanoString).

Results: We found a significant excess of all rare CNVs (deletions: p = .0004, duplications: p = .0006) and single-gene CNVs (deletions: p = .04, duplications: p = .03) in schizophrenia cases compared with control subjects. An expanded set of CNVs generated from integrating multiple approaches showed a significant burden of deletions in 11 of 21 gene sets previously implicated in schizophrenia and across all genes in those sets (p = .008), although no tests survived correction. We performed an extensive validation of all deletions in the significant set of voltage-gated calcium channels among CNVs called from both exome sequencing and genotyping arrays. In total, 4 exonic, single-gene deletions were validated in schizophrenia cases and none in control subjects (p = .039), of which all were identified by exome sequencing.

Conclusions: These results point to the potential contribution of single-gene CNVs to schizophrenia, indicate that the utility of exome sequencing for CNV calling has yet to be maximized, and note that single-gene CNVs should be included in gene-focused studies using other classes of variation.
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http://dx.doi.org/10.1016/j.biopsych.2019.09.023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7103483PMC
April 2020

Longitudinal Cortical Thickness Changes in Bipolar Disorder and the Relationship to Genetic Risk, Mania, and Lithium Use.

Biol Psychiatry 2020 02 29;87(3):271-281. Epub 2019 Aug 29.

Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the Gothenburg University, Gothenburg, Sweden; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet and Stockholm County, Stockholm, Sweden.

Background: Bipolar disorder (BD) is a highly heritable psychiatric disorder characterized by episodes of manic and depressed mood states and associated with cortical brain abnormalities. Although the course of BD is often progressive, longitudinal brain imaging studies are scarce. It remains unknown whether brain abnormalities are static traits of BD or result from pathological changes over time. Moreover, the genetic effect on implicated brain regions remains unknown.

Methods: Patients with BD and healthy control (HC) subjects underwent structural magnetic resonance imaging at baseline (123 patients, 83 HC subjects) and after 6 years (90 patients, 61 HC subjects). Cortical thickness maps were generated using FreeSurfer. Using linear mixed effects models, we compared longitudinal changes in cortical thickness between patients with BD and HC subjects across the whole brain. We related our findings to genetic risk for BD and tested for effects of demographic and clinical variables.

Results: Patients showed abnormal cortical thinning of temporal cortices and thickness increases in visual/somatosensory brain areas. Thickness increases were related to genetic risk and lithium use. Patients who experienced hypomanic or manic episodes between time points showed abnormal thinning in inferior frontal cortices. Cortical changes did not differ between diagnostic BD subtypes I and II.

Conclusions: In the largest longitudinal BD study to date, we detected abnormal cortical changes with high anatomical resolution. We delineated regional effects of clinical symptoms, genetic factors, and medication that may explain progressive brain changes in BD. Our study yields important insights into disease mechanisms and suggests that neuroprogression plays a role in BD.
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http://dx.doi.org/10.1016/j.biopsych.2019.08.015DOI Listing
February 2020

Genes, biomarkers, and clinical features associated with the course of bipolar disorder.

Eur Neuropsychopharmacol 2019 10 1;29(10):1152-1160. Epub 2019 Aug 1.

Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at Gothenburg University, Gothenburg, Sweden; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

There is considerable variability in the severity of bipolar disorder, e.g., in terms of the frequency of inpatient episodes. The long-term progression also differs, where some patients are sensitised with progressively shorter healthy intervals. Little is known about the proportion of patients being sensitised, their clinical characteristics, and biological underpinnings. We analysed long-term progression of bipolar disorder in relation to clinical characteristics (N = 3074), serum biomarkers (N = 745), and genetic variants (N = 1401) in a cohort of Swedish bipolar disorder patients. We took advantage of the National Patient Register, providing reliable data on 35,973 psychiatric inpatient care episodes in Sweden since 1973. First, one third of the cohort cluster together with a maximum of one inpatient episode per year, while the remaining two thirds had >1 episode per year. These groups did not differ with respect to clinical features or biomarkers. Second, among patients with at least five inpatient episodes (defined as severely ill), we find one group with progressively shorter cycle-lengths (one fifth of the total cohort, N = 550). Compared with those with a stable or recuperant trajectory, these patients featured lower functioning, more antidepressant treatment, as well as reduced levels of inflammatory markers in serum. Third, sensitisation was associated with a common genetic variant near the calcium channel gene CACNA2D3 at genome-wide significance. These results suggest the potential for translational research aimed at preventive actions.
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http://dx.doi.org/10.1016/j.euroneuro.2019.07.132DOI Listing
October 2019

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Nat Genet 2019 05 1;51(5):793-803. Epub 2019 May 1.

Department of Psychiatry, Weill Cornell Medical College, New York, NY, USA.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.
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http://dx.doi.org/10.1038/s41588-019-0397-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6956732PMC
May 2019

Contribution of Rare Copy Number Variants to Bipolar Disorder Risk Is Limited to Schizoaffective Cases.

Biol Psychiatry 2019 07 20;86(2):110-119. Epub 2018 Dec 20.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Background: Genetic risk for bipolar disorder (BD) is conferred through many common alleles, while a role for rare copy number variants (CNVs) is less clear. Subtypes of BD including schizoaffective disorder bipolar type (SAB), bipolar I disorder (BD I), and bipolar II disorder (BD II) differ according to the prominence and timing of psychosis, mania, and depression. The genetic factors contributing to the combination of symptoms among these subtypes are poorly understood.

Methods: Rare large CNVs were analyzed in 6353 BD cases (3833 BD I [2676 with psychosis, 850 without psychosis, and 307 with unknown psychosis history], 1436 BD II, 579 SAB, and 505 BD not otherwise specified) and 8656 controls. CNV burden and a polygenic risk score (PRS) for schizophrenia were used to evaluate the relative contributions of rare and common variants to risk of BD, BD subtypes, and psychosis.

Results: CNV burden did not differ between BD and controls when treated as a single diagnostic entity. However, burden in SAB was increased relative to controls (p = .001), BD I (p = .0003), and BD II (p = .0007). Burden and schizophrenia PRSs were increased in SAB compared with BD I with psychosis (CNV p = .0007, PRS p = .004), and BD I without psychosis (CNV p = .0004, PRS p = 3.9 × 10). Within BD I, psychosis was associated with increased schizophrenia PRSs (p = .005) but not CNV burden.

Conclusions: CNV burden in BD is limited to SAB. Rare and common genetic variants may contribute differently to risk for psychosis and perhaps other classes of psychiatric symptoms.
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http://dx.doi.org/10.1016/j.biopsych.2018.12.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586545PMC
July 2019

Joint Contributions of Rare Copy Number Variants and Common SNPs to Risk for Schizophrenia.

Am J Psychiatry 2019 01 5;176(1):29-35. Epub 2018 Nov 5.

From the Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm; the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Mass.; the Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston; the MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, United Kingdom; the Department of Psychiatry, Harvard Medical School, and Massachusetts General Hospital, Boston; the Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetics Research, Massachusetts General Hospital, Boston; the Departments of Genetics and Psychiatry, University of North Carolina, Chapel Hill; the Departments of Psychiatry and Cellular and Molecular Medicine, University of California, San Diego; and the Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond.

Objective: Both rare copy number variants (CNVs) and common single-nucleotide polymorphisms (SNPs) contribute to liability to schizophrenia, but their etiological relationship has not been fully elucidated. The authors evaluated an additive model whereby risk of schizophrenia requires less contribution from common SNPs in the presence of a rare CNV, and tested for interactions.

Method: Genetic data from 21,094 case subjects with schizophrenia and 20,227 control subjects from the Psychiatric Genomics Consortium were examined. Three classes of rare CNVs were assessed: CNVs previously associated with schizophrenia, CNVs with large deletions ≥500 kb, and total CNV burden. The mean polygenic risk scores (PRSs) between study subjects with and without rare CNVs were compared, and joint effects of PRS and CNVs on schizophrenia liability were modeled by using logistic regression.

Results: Schizophrenia case subjects carrying risk CNVs had a lower polygenic risk than case subjects without risk CNVs but a higher risk than control subjects. For case subjects carrying known risk CNVs, the PRS was diminished in proportion to the effect size of the CNV. The strongly associated 22q11.2 deletion required little added PRS to produce schizophrenia. Large deletions and increased CNV burden were also associated with lower polygenic risk in schizophrenia case subjects but not in control subjects or after removal of known risk CNV carriers.

Conclusions: The authors found evidence for interactive effects of PRS and previously associated CNVs for risk for schizophrenia, and the results for large deletions and total CNV burden support an additive model. These findings offer insights into the genetic architecture of schizophrenia by illuminating how different established genetic risk factors act and interact to influence liability to schizophrenia.
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http://dx.doi.org/10.1176/appi.ajp.2018.17040467DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6408268PMC
January 2019

Elevated expression of a minor isoform of ANK3 is a risk factor for bipolar disorder.

Transl Psychiatry 2018 10 8;8(1):210. Epub 2018 Oct 8.

Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.

Ankyrin-3 (ANK3) is one of the few genes that have been consistently identified as associated with bipolar disorder by multiple genome-wide association studies. However, the exact molecular basis of the association remains unknown. A rare loss-of-function splice-site SNP (rs41283526*G) in a minor isoform of ANK3 (incorporating exon ENSE00001786716) was recently identified as protective of bipolar disorder and schizophrenia. This suggests that an elevated expression of this isoform may be involved in the etiology of the disorders. In this study, we used novel approaches and data sets to test this hypothesis. First, we strengthen the statistical evidence supporting the allelic association by replicating the protective effect of the minor allele of rs41283526 in three additional large independent samples (meta-analysis p-values: 6.8E-05 for bipolar disorder and 8.2E-04 for schizophrenia). Second, we confirm the hypothesis that both bipolar and schizophrenia patients have a significantly higher expression of this isoform than controls (p-values: 3.3E-05 for schizophrenia and 9.8E-04 for bipolar type I). Third, we determine the transcription start site for this minor isoform by Pacific Biosciences sequencing of full-length cDNA and show that it is primarily expressed in the corpus callosum. Finally, we combine genotype and expression data from a large Norwegian sample of psychiatric patients and controls, and show that the risk alleles in ANK3 identified by bipolar disorder GWAS are located near the transcription start site of this isoform and are significantly associated with its elevated expression. Together, these results point to the likely molecular mechanism underlying ANK3´s association with bipolar disorder.
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http://dx.doi.org/10.1038/s41398-018-0175-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6175894PMC
October 2018

Analysis of shared heritability in common disorders of the brain.

Science 2018 06;360(6395)

Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.
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http://dx.doi.org/10.1126/science.aap8757DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6097237PMC
June 2018

Genetic variation in 117 myelination-related genes in schizophrenia: Replication of association to lipid biosynthesis genes.

Sci Rep 2018 05 2;8(1):6915. Epub 2018 May 2.

NORMENT - KG Jebsen Centre for Psychosis Research, Department of Clinical Science, University of Bergen, Bergen, Norway.

Schizophrenia is a serious psychotic disorder with high heritability. Several common genetic variants, rare copy number variants and ultra-rare gene-disrupting mutations have been linked to disease susceptibility, but there is still a large gap between the estimated and explained heritability. Since several studies have indicated brain myelination abnormalities in schizophrenia, we aimed to examine whether variants in myelination-related genes could be associated with risk for schizophrenia. We established a set of 117 myelination genes by database searches and manual curation. We used a combination of GWAS (SCZ_N = 35,476; CTRL_N = 46,839), exome chip (SCZ_N = 269; CTRL_N = 336) and exome sequencing data (SCZ_N = 2,527; CTRL_N = 2,536) from schizophrenia cases and healthy controls to examine common and rare variants. We found that a subset of lipid-related genes was nominally associated with schizophrenia (p = 0.037), but this signal did not survive multiple testing correction (FWER = 0.16) and was mainly driven by the SREBF1 and SREBF2 genes that have already been linked to schizophrenia. Further analysis demonstrated that the lowest nominal p-values were p = 0.0018 for a single common variant (rs8539) and p = 0.012 for burden of rare variants (LRP1 gene), but none of them survived multiple testing correction. Our findings suggest that variation in myelination-related genes is not a major risk factor for schizophrenia.
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http://dx.doi.org/10.1038/s41598-018-25280-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5931982PMC
May 2018

Specificity in Etiology of Subtypes of Bipolar Disorder: Evidence From a Swedish Population-Based Family Study.

Biol Psychiatry 2018 12 20;84(11):810-816. Epub 2017 Nov 20.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Background: Uncertainty remains whether bipolar I disorder (BDI) and bipolar II disorder (BDII) differ etiologically. We used a population-based family sample to examine the etiological boundaries between BDI and BDII by assessing their familial aggregation/coaggregation and by assessing the coaggregation between them and schizophrenia, depression, attention-deficit/hyperactivity disorder, eating disorders, autism spectrum disorder, substance use disorders, anxiety disorders, and personality disorders.

Methods: By linking Swedish national registers, we established a population-based cohort (N = 15,685,511) and identified relatives with different biological relationships. Odds ratios (ORs) were used to measure the relative risk of BDI and BDII in relatives of individuals diagnosed with BDI (n = 4309) and BDII (n = 4178). The heritability for BDI and BDII and the genetic correlation across psychiatric disorders were estimated by variance decomposition analysis.

Results: Compared with the general population, the OR of BDI was 17.0 (95% confidence interval [CI] 13.1-22.0) in first-degree relatives of BDI patients, higher than that of BDII patients (OR 9.8, 95% CI 7.7-12.5). The ORs of BDII were 13.6 (95% CI 10.2-18.2) in first-degree relatives of BDII patients and 9.8 (95% CI 7.7-12.4) in relatives of BDI patients. The heritabilities for BDI and BDII were estimated at 57% (95% CI 32%-79%) and 46% (95% CI 21%-67%), respectively, with a genetic correlation estimated as 0.78 (95% CI 0.36-1.00). The familial coaggregation of other psychiatric disorders, in particular schizophrenia, showed different patterns for BDI and BDII.

Conclusions: Our results suggest a distinction between BDI and BDII in etiology, partly due to genetic differences.
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http://dx.doi.org/10.1016/j.biopsych.2017.11.014DOI Listing
December 2018

National-scale precision medicine for psychiatric disorders in Sweden.

Am J Med Genet B Neuropsychiatr Genet 2018 10 7;177(7):630-634. Epub 2017 Jul 7.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Since psychiatric disorders have genetic architectures dominated by common variants of small effects, successful elucidation in psychiatric genetics necessitates large sample sizes. Collaboration and unconventional ascertainment methods are required to fulfill this need. Electronic health records have been increasingly seen as holding great potential for research, although they often pose substantial technical, legal and ethical challenges. Universal health care and national-scale registers with comprehensive medical, developmental, demographic, and geographic information make the Nordic countries ideal for psychiatric genetic epidemiology. The Genomic Aggregation Project in Sweden is gathering genetic data from subjects with and without complex genetic diseases in a single location for standardized processing and use in a wide variety of scientific investigations. Thirty groups with >160 K genotyped samples have joined GAPS. Although GAPS is general across medicine, many psychiatric disorders are represented within GAPS, and initial studies will focus on major depressive disorder. Through in-depth genetic investigations, the genes and pathways that will be identified can be leveraged for predictive and drug-development purposes. Sweden offers exceptional possibilities for psychiatric genetics, and GAPS aims to harness the wealth of available information for research to improve human health.
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http://dx.doi.org/10.1002/ajmg.b.32562DOI Listing
October 2018

National-scale precision medicine for psychiatric disorders in Sweden.

Am J Med Genet B Neuropsychiatr Genet 2018 10 7;177(7):630-634. Epub 2017 Jul 7.

Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.

Since psychiatric disorders have genetic architectures dominated by common variants of small effects, successful elucidation in psychiatric genetics necessitates large sample sizes. Collaboration and unconventional ascertainment methods are required to fulfill this need. Electronic health records have been increasingly seen as holding great potential for research, although they often pose substantial technical, legal and ethical challenges. Universal health care and national-scale registers with comprehensive medical, developmental, demographic, and geographic information make the Nordic countries ideal for psychiatric genetic epidemiology. The Genomic Aggregation Project in Sweden is gathering genetic data from subjects with and without complex genetic diseases in a single location for standardized processing and use in a wide variety of scientific investigations. Thirty groups with >160 K genotyped samples have joined GAPS. Although GAPS is general across medicine, many psychiatric disorders are represented within GAPS, and initial studies will focus on major depressive disorder. Through in-depth genetic investigations, the genes and pathways that will be identified can be leveraged for predictive and drug-development purposes. Sweden offers exceptional possibilities for psychiatric genetics, and GAPS aims to harness the wealth of available information for research to improve human health.
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http://dx.doi.org/10.1002/ajmg.b.32562DOI Listing
October 2018

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects.

Nat Genet 2017 01 21;49(1):27-35. Epub 2016 Nov 21.

Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 × 10), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 × 10). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 × 10) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 × 10). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.
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http://dx.doi.org/10.1038/ng.3725DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5737772PMC
January 2017

Novel gene-brain structure relationships in psychotic disorder revealed using parallel independent component analyses.

Schizophr Res 2017 04 24;182:74-83. Epub 2016 Oct 24.

Psychiatry, Harvard Medical School, Beth Israel Deaconess Medical Ctr, Boston, MA, USA.

Background: Schizophrenia, schizoaffective disorder, and psychotic bipolar disorder overlap with regard to symptoms, structural and functional brain abnormalities, and genetic risk factors. Neurobiological pathways connecting genes to clinical phenotypes across the spectrum from schizophrenia to psychotic bipolar disorder remain largely unknown.

Methods: We examined the relationship between structural brain changes and risk alleles across the psychosis spectrum in the multi-site Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) cohort. Regional MRI brain volumes were examined in 389 subjects with a psychotic disorder (139 schizophrenia, 90 schizoaffective disorder, and 160 psychotic bipolar disorder) and 123 healthy controls. 451,701 single-nucleotide polymorphisms were screened and processed using parallel independent component analysis (para-ICA) to assess associations between genes and structural brain abnormalities in probands.

Results: 482 subjects were included after quality control (364 individuals with psychotic disorder and 118 healthy controls). Para-ICA identified four genetic components including several risk genes already known to contribute to schizophrenia and bipolar disorder and revealed three structural components that showed overlapping relationships with the disease risk genes across the three psychotic disorders. Functional ontologies representing these gene clusters included physiological pathways involved in brain development, synaptic transmission, and ion channel activity.

Conclusions: Heritable brain structural findings such as reduced cortical thickness and surface area in probands across the psychosis spectrum were associated with somewhat distinct genes related to putative disease pathways implicated in psychotic disorders. This suggests that brain structural alterations might represent discrete psychosis intermediate phenotypes along common neurobiological pathways underlying disease expression across the psychosis spectrum.
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http://dx.doi.org/10.1016/j.schres.2016.10.026DOI Listing
April 2017

Identification of a Bipolar Disorder Vulnerable Gene CHDH at 3p21.1.

Mol Neurobiol 2017 09 25;54(7):5166-5176. Epub 2016 Aug 25.

Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Kunming, Yunnan, People's Republic of China.

Genome-wide analysis (GWA) is an effective strategy to discover extreme effects surpassing genome-wide significant levels in studying complex disorders; however, when sample size is limited, the true effects may fail to achieve genome-wide significance. In such case, there may be authentic results among the pools of nominal candidates, and an alternative approach is to consider nominal candidates but are replicable across different samples. Here, we found that mRNA expression of the choline dehydrogenase gene (CHDH) was uniformly upregulated in the brains of bipolar disorder (BPD) patients compared with healthy controls across different studies. Follow-up genetic analyses of CHDH variants in multiple independent clinical datasets (including 11,564 cases and 17,686 controls) identified a risk SNP rs9836592 showing consistent associations with BPD (P  = 5.72 × 10), and the risk allele indicated an increased CHDH expression in multiple neuronal tissues (lowest P = 6.70 × 10). These converging results may identify a nominal but true BPD susceptibility gene CHDH. Further exploratory analysis revealed suggestive associations of rs9836592 with childhood intelligence (P = 0.044) and educational attainment (P = 0.0039), a "proxy phenotype" of general cognitive abilities. Intriguingly, the CHDH gene is located at chromosome 3p21.1, a risk region implicated in previous BPD genome-wide association studies (GWAS), but CHDH is lying outside of the core GWAS linkage disequilibrium (LD) region, and our studied SNP rs9836592 is ∼1.2 Mb 3' downstream of the previous GWAS loci (e.g., rs2251219) with no LD between them; thus, the association observed here is unlikely a reflection of previous GWAS signals. In summary, our results imply that CHDH may play a previously unknown role in the etiology of BPD and also highlight the informative value of integrating gene expression and genetic code in advancing our understanding of its biological basis.
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http://dx.doi.org/10.1007/s12035-016-0041-xDOI Listing
September 2017

Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder.

Hum Mol Genet 2016 08 21;25(15):3383-3394. Epub 2016 Jun 21.

Institute of Human Genetics, University of Bonn, Germany.

Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behaviour. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ∼2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, P =  5.87 × 10   ; odds ratio (OR) = 1.12) and markers within ERBB2 (rs2517959, P =  4.53 × 10   ; OR = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.
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http://dx.doi.org/10.1093/hmg/ddw181DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5179929PMC
August 2016
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