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1. Shared genetic loci between depression and cardiometabolic traits.

Author: Kristin Torgersen, Zillur Rahman, Shahram Bahrami, Guy Frederick Lanyon Hindley, Nadine Parker, Oleksandr Frei, Alexey Shadrin, Kevin S O'Connell, Martin Tesli, Olav B Smeland, John Munkhaugen, Srdjan Djurovic, Toril Dammen, and Ole A Andreassen
Subjects: Genetics, QH426-470
Abstract: Epidemiological and clinical studies have found associations between depression and cardiovascular disease risk factors, and coronary artery disease patients with depression have worse prognosis. The genetic relationship between depression and these cardiovascular phenotypes is not known. We here investigated overlap at the genome-wide level and in individual loci between depression, coronary artery disease and cardiovascular risk factors. We used the bivariate causal mixture model (MiXeR) to quantify genome-wide polygenic overlap and the conditional/conjunctional false discovery rate (pleioFDR) method to identify shared loci, based on genome-wide association study summary statistics on depression (n = 450,619), coronary artery disease (n = 502,713) and nine cardiovascular risk factors (n = 204,402-776,078). Genetic loci were functionally annotated using FUnctional Mapping and Annotation (FUMA). Of 13.9K variants influencing depression, 9.5K (SD 1.0K) were shared with body-mass index. Of 4.4K variants influencing systolic blood pressure, 2K were shared with depression. ConjFDR identified 79 unique loci associated with depression and coronary artery disease or cardiovascular risk factors. Six genomic loci were associated jointly with depression and coronary artery disease, 69 with blood pressure, 49 with lipids, 9 with type 2 diabetes and 8 with c-reactive protein at conjFDR < 0.05. Loci associated with increased risk for depression were also associated with increased risk of coronary artery disease and higher total cholesterol, low-density lipoprotein and c-reactive protein levels, while there was a mixed pattern of effect direction for the other risk factors. Functional analyses of the shared loci implicated metabolism of alpha-linolenic acid pathway for type 2 diabetes. Our results showed polygenic overlap between depression, coronary artery disease and several cardiovascular risk factors and suggest molecular mechanisms underlying the association between depression and increased cardiovascular disease risk.
Published: 2022
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2. The genetic landscape of basal ganglia and implications for common brain disorders

Author: Shahram Bahrami, Kaja Nordengen, Jaroslav Rokicki, Alexey A. Shadrin, Zillur Rahman, Olav B. Smeland, Piotr P. Jaholkowski, Nadine Parker, Pravesh Parekh, Kevin S. O’Connell, Torbjørn Elvsåshagen, Mathias Toft, Srdjan Djurovic, Anders M. Dale, Lars T. Westlye, Tobias Kaufmann, and Ole A. Andreassen
Subjects: Science
Abstract: Abstract The basal ganglia are subcortical brain structures involved in motor control, cognition, and emotion regulation. We conducted univariate and multivariate genome-wide association analyses (GWAS) to explore the genetic architecture of basal ganglia volumes using brain scans obtained from 34,794 Europeans with replication in 4,808 white and generalization in 5,220 non-white Europeans. Our multivariate GWAS identified 72 genetic loci associated with basal ganglia volumes with a replication rate of 55.6% at P
Published: 2024
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3. Genome-wide association analysis of treatment resistant schizophrenia for variant discovery and polygenic assessment

Author: Hasan Çağın Lenk, Elise Koch, Kevin S. O’Connell, Robert Løvsletten Smith, Ibrahim A. Akkouh, Srdjan Djurovic, Ole A. Andreassen, and Espen Molden
Subjects: Medicine, Genetics, QH426-470
Abstract: Abstract Background Treatment resistant schizophrenia (TRS) is broadly defined as inadequate response to adequate treatment and is associated with a substantial increase in disease burden. Clozapine is the only approved treatment for TRS, showing superior clinical effect on overall symptomatology compared to other drugs, and is the prototype of atypical antipsychotics. Risperidone, another atypical antipsychotic with a more distinctive dopamine 2 antagonism, is commonly used in treatment of schizophrenia. Here, we conducted a genome-wide association study on patients treated with clozapine (TRS) vs. risperidone (non-TRS) and investigated whether single variants and/or polygenic risk score for schizophrenia are associated with TRS status. We hypothesized that patients who are treated with clozapine and risperidone might exhibit distinct neurobiological phenotypes that match pharmacological profiles of these drugs and can be explained by genetic differences. The study population (n = 1286) was recruited from a routine therapeutic drug monitoring (TDM) service between 2005 and 2022. History of a detectable serum concentration of clozapine and risperidone (without TDM history of clozapine) defined the TRS (n = 478) and non-TRS (n = 808) group, respectively. Results We identified a suggestive association between TRS and a common variant within the LINC00523 gene with a significance just below the genome-wide threshold (rs79229764 C > T, OR = 4.89; p = 1.8 × 10−7). Polygenic risk score for schizophrenia was significantly associated with TRS (OR = 1.4, p = 2.1 × 10−6). In a large post-mortem brain sample from schizophrenia donors (n = 214; CommonMind Consortium), gene expression analysis indicated that the rs79229764 variant allele might be involved in the regulation of GPR88 and PUDP, which plays a role in striatal neurotransmission and intellectual disability, respectively. Conclusions We report a suggestive genetic association at the rs79229764 locus with TRS and show that genetic liability for schizophrenia is positively associated with TRS. These results suggest a candidate locus for future follow-up studies to elucidate the molecular underpinnings of TRS. Our findings further demonstrate the value of both single variant and polygenic association analyses for TRS prediction.
Published: 2024
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4. Genetic insights into psychotic major depressive disorder: bridging the mood-psychotic disorder spectrumResearch in context

Author: Thuy-Dung Nguyen, Joeri J. Meijsen, Robert Sigström, Ralf Kuja-Halkola, Ying Xiong, Arvid Harder, Kaarina Kowalec, Joëlle A. Pasman, Carolina Scarpa, Elin Hörbeck, Lina Jonsson, Sara Hägg, Niamh Mullins, Kevin S. O’Connell, Christina Dalman, Dorte Helenius, Richard Zetterberg, Henrik Larsson, Paul Lichtenstein, Ole A. Andreassen, Thomas Werge, Alfonso Buil, Mikael Landén, Patrick F. Sullivan, and Yi Lu
Subjects: Psychotic major depressive disorder, Psychotic disorders, Genetic, Epidemiology, Medicine, Medicine (General), R5-920
Abstract: Summary: Background: Psychotic major depressive disorder (MDD), a subtype of MDD characterised by psychotic symptoms that occur exclusively during mood episode, is clinically significant yet underexplored genetically due to its rarity. This study comprehensively examines the genetic basis of psychotic MDD and elucidates its position within the mood-psychotic spectrum. Methods: This population-based cohort study used Swedish and Danish registry data for over 5.1 M individuals born between 1958 and 1993/1996. Specialist-diagnosed psychotic MDD was defined using ICD-10 sub-codes of MDD, F32.2/F32.3. We estimated familial aggregation/coaggregation using generalised estimating equations, heritability and genetic correlations using structural equation modelling. We also analysed ∼30,000 genotyped MDD cases from the UK Biobank and a Swedish cohort to explore which polygenic risk score (PRS) may predispose individuals to psychotic MDD. Findings: With over 10,000 psychotic MDD identified from the two nationwide patient registers, this study highlights the familial aggregation of psychotic MDD, co-aggregation with mood and psychotic disorders, and its stronger genetic correlation with schizophrenia compared to non-psychotic MDD. The familial risks increased with closer biological relatedness, suggesting genetic influence. Pedigree-heritability of psychotic MDD was 30.17% (95% CI 23.53–36.80%). While the genetic correlation between psychotic and non-psychotic MDD was high (0.82, 95% CI 0.73–0.92), the psychotic subgroup showed a higher genetic correlation with schizophrenia than non-psychotic MDD (0.67 vs 0.46, p-value 7.55∗10−4). Within 30,000 genotyped MDD cases, individuals with psychotic MDD had higher mean PRS for schizophrenia and BD but a lower MDD PRS than non-psychotic MDD. PRS for BD type-I was associated with increased odds of psychotic MDD, while BD type-II PRS showed no significant association with psychotic MDD. Interpretation: This study provides evidence for the genetic basis of psychotic MDD, underscoring its unique position bridging the spectrum of mood and psychotic disorders. These findings advance our understanding of the aetiology of psychotic MDD and contribute to the limited body of evidence on this phenotype by utilising large-scale population-based data. Funding: European Research Council; US National Institutes of Mental Health; European Union Horizon 2020 Program; Swedish Research Council; Research Council of Norway; Swedish Foundation for Strategic Research; Hjärnfonden.
Published: 2025
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5. Charting the shared genetic architecture of Alzheimer's disease, cognition, and educational attainment, and associations with brain development

Author: Piotr Jaholkowski, Shahram Bahrami, Vera Fominykh, Guy F.L. Hindley, Markos Tesfaye, Pravesh Parekh, Nadine Parker, Tahir T. Filiz, Kaja Nordengen, Espen Hagen, Elise Koch, Nora R. Bakken, Evgeniia Frei, Viktoria Birkenæs, Zillur Rahman, Oleksandr Frei, Jan Haavik, Srdjan Djurovic, Anders M. Dale, Olav B. Smeland, Kevin S. O’Connell, Alexey A. Shadrin, and Ole A. Andreassen
Subjects: Alzheimer's disease, Cognition, Educational attainment, Genetics/genomics, Neurodevelopment, MiXeR, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: The observation that the risk of developing Alzheimer's disease is reduced in individuals with high premorbid cognitive functioning, higher educational attainment, and occupational status has led to the ‘cognitive reserve’ hypothesis. This hypothesis suggests that individuals with greater cognitive reserve can tolerate a more significant burden of neuropathological changes before the onset of cognitive decline. The underpinnings of cognitive reserve remain poorly understood, although a shared genetic basis between measures of cognitive reserve and Alzheimer's disease has been suggested. Using the largest samples to date and novel statistical tools, we aimed to investigate shared genetic variants between Alzheimer's disease, and measures of cognitive reserve; cognition and educational attainment to identify molecular and neurobiological foundations. We applied the causal mixture model (MiXeR) to estimate the number of trait-influencing variants shared between Alzheimer's disease, cognition, and educational attainment, and condFDR/conjFDR to identify shared loci. To provide biological insights loci were functionally characterized. Subsequently, we constructed a Structural Equation Model (SEM) to determine if the polygenic foundation of cognition has a direct impact on Alzheimer's disease risk, or if its effect is mediated through established risk factors for the disease, using a case-control sample from the UK Biobank. Univariate MiXeR analysis (after excluding chromosome 19) revealed that Alzheimer's disease was substantially less polygenic (450 trait-influencing variants) compared to cognition (11,100 trait-influencing variants), and educational attainment (12,700 trait-influencing variants). Bivariate MiXeR analysis estimated that Alzheimer's disease shared approximately 70 % of trait-influencing variants with cognition, and approximately 40 % with educational attainment, with mixed effect directions. Using condFDR analysis, we identified 18 loci jointly associated with Alzheimer's disease and cognition and 6 loci jointly associated with Alzheimer's disease and educational attainment. Genes mapped to shared loci were associated with neurodevelopment, expressed in early life, and implicated the dendritic tree and phosphatidylinositol phosphate binding mechanisms. Spatiotemporal gene expression analysis of the identified genes showed that mapped genes were highly expressed during the mid-fetal period, further suggesting early neurodevelopmental stages as critical periods for establishing cognitive reserve which affect the risk of Alzheimer's disease in old age. Furthermore, our SEM analysis showed that genetic variants influencing cognition had a direct effect on the risk of developing Alzheimer's disease, providing evidence in support of the neurodevelopmental hypothesis of the disease.
Published: 2024
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6. Genomic insights into the shared and distinct genetic architecture of cognitive function and schizophrenia

Author: Olivia Wootton, Alexey A. Shadrin, Thomas Bjella, Olav B. Smeland, Dennis van der Meer, Oleksandr Frei, Kevin S. O’Connell, Torill Ueland, Ole A. Andreassen, Dan J. Stein, and Shareefa Dalvie
Subjects: Medicine, Science
Abstract: Abstract Cognitive impairment is a major determinant of functional outcomes in schizophrenia, however, understanding of the biological mechanisms underpinning cognitive dysfunction in the disorder remains incomplete. Here, we apply Genomic Structural Equation Modelling to identify latent cognitive factors capturing genetic liabilities to 12 cognitive traits measured in the UK Biobank. We identified three broad factors that underly the genetic correlations between the cognitive tests. We explore the overlap between latent cognitive factors, schizophrenia, and schizophrenia symptom dimensions using a complementary set of statistical approaches, applied to data from the latest schizophrenia genome-wide association study (Ncase = 53,386, Ncontrol = 77,258) and the Thematically Organised Psychosis study (Ncase = 306, Ncontrol = 1060). Global genetic correlations showed a significant moderate negative genetic correlation between each cognitive factor and schizophrenia. Local genetic correlations implicated unique genomic regions underlying the overlap between schizophrenia and each cognitive factor. We found substantial polygenic overlap between each cognitive factor and schizophrenia and biological annotation of the shared loci implicated gene-sets related to neurodevelopment and neuronal function. Lastly, we show that the common genetic determinants of the latent cognitive factors are not predictive of schizophrenia symptoms in the Norwegian Thematically Organized Psychosis cohort. Overall, these findings inform our understanding of cognitive function in schizophrenia by demonstrating important differences in the shared genetic architecture of schizophrenia and cognitive abilities.
Published: 2024
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7. Toxoplasma gondii infection associated with inflammasome activation and neuronal injury

Author: Dimitrios Andreou, Nils Eiel Steen, Lynn Mørch-Johnsen, Kjetil Nordbø Jørgensen, Laura A. Wortinger, Claudia Barth, Attila Szabo, Kevin S. O’Connell, Tove Lekva, Gabriela Hjell, Ingrid Torp Johansen, Monica B. E. G. Ormerod, Unn K. Haukvik, Pål Aukrust, Srdjan Djurovic, Robert H. Yolken, Ole A. Andreassen, Thor Ueland, and Ingrid Agartz
Subjects: Neuron-specific enolase, Interleukin-18, Schizophrenia, Bipolar disorder, Healthy controls, Medicine, Science
Abstract: Abstract Toxoplasma gondii (TOXO) infection typically results in chronic latency due to its ability to form cysts in the brain and other organs. Latent toxoplasmosis could promote innate immune responses and impact brain function. A large body of evidence has linked TOXO infection to severe mental illness (SMI). We hypothesized that TOXO immunoglobulin G (IgG) seropositivity, reflecting previous infection and current latency, is associated with increased circulating neuron-specific enolase (NSE), a marker of brain damage, and interleukin-18 (IL-18), an innate immune marker, mainly in SMI. We included 735 patients with SMI (schizophrenia or bipolar spectrum) (mean age 32 years, 47% women), and 518 healthy controls (HC) (mean age 33 years, 43% women). TOXO IgG, expressed as seropositivity/seronegativity, NSE and IL-18 were measured with immunoassays. We searched for main and interaction effects of TOXO, patient/control status and sex on NSE and IL-18. In the whole sample as well as among patients and HC separately, IL-18 and NSE concentrations were positively correlated (p
Published: 2024
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8. Effect of the NFIB rs28379954 T>C polymorphism on CYP2D6‐catalyzed metabolism of solanidine

Author: Robert Løvsletten Smith, Birgit M. Wollmann, Elisabet Størset, Hasan Çağın Lenk, Kevin S. O'Connell, Marianne Kringen Kristiansen, Magnus Ingelman‐Sundberg, and Espen Molden
Subjects: Therapeutics. Pharmacology, RM1-950, Public aspects of medicine, RA1-1270
Abstract: Abstract Cytochrome P450 2D6 (CYP2D6) is important for metabolism of 20%–25% of all clinically used drugs. Many known genetic variants contribute to the large interindividual variability in CYP2D6 metabolism, but much is still unexplained. We recently described that nuclear factor 1B (NFIB) regulates hepatic CYP2D6 expression with the minor allele of NFIB rs28379954 T>C significantly increasing CYP2D6‐mediated risperidone metabolism. In this study, we investigated the effect of NFIB T>C on metabolism of solanidine, a dietary CYP2D6 substrate. Analyses of solanidine and metabolites (M414, M416, and M444) were performed by ultra‐high performance liquid chromatography‐high‐resolution mass spectrometry in a cohort of 463 CYP2D6‐genotyped patients of which with 58 (12.5%) carried NFIB TC (n = 56) or CC (n = 2). Increased metabolism of solanidine was found in CYP2D6 normal metabolizers (NMs; n = 258, 55.7%) carrying the NFIB C variant (n = 27, 5.8%) with 2.83‐ and 3.38‐fold higher M416‐to‐solanidine (p = 0.039) and M444‐to‐solanidine (p = 0.046) ratios, respectively, whereas this effect was not significant among intermediate metabolizers (n = 166, 35.9%) (p ≥ 0.09). Importantly, no effect of the NFIB polymorphism on solanidine metabolism was seen in TC or CC carriers lacking CYP2D6 activity (poor metabolizers, n = 30, 6.5%, p ≥ 0.74). Furthermore, the NFIB polymorphism significantly explained variability in solanidine metabolism (M414 p = 0.013, M416 p = 0.020, and M416 and M444 p = 0.009) in multiple linear regression models for each metabolic ratio in the entire population, correcting for covariates (including CYP2D6 genotypes). Thus, the study confirms the effect of NFIB in regulating CYP2D6 activity, suggesting an about 200% increase in CYP2D6‐mediated clearance in NMs being NFIB CT or CC carriers, comprising around 6% of Europeans.
Published: 2024
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9. Characterising the shared genetic determinants of bipolar disorder, schizophrenia and risk-taking

Author: Guy Hindley, Shahram Bahrami, Nils Eiel Steen, Kevin S. O’Connell, Oleksandr Frei, Alexey Shadrin, Francesco Bettella, Linn Rødevand, Chun C. Fan, Anders M. Dale, Srdjan Djurovic, Olav B. Smeland, and Ole A. Andreassen
Subjects: Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Abstract Increased risk-taking is a central component of bipolar disorder (BIP) and is implicated in schizophrenia (SCZ). Risky behaviours, including smoking and alcohol use, are overrepresented in both disorders and associated with poor health outcomes. Positive genetic correlations are reported but an improved understanding of the shared genetic architecture between risk phenotypes and psychiatric disorders may provide insights into underlying neurobiological mechanisms. We aimed to characterise the genetic overlap between risk phenotypes and SCZ, and BIP by estimating the total number of shared variants using the bivariate causal mixture model and identifying shared genomic loci using the conjunctional false discovery rate method. Summary statistics from genome wide association studies of SCZ, BIP, risk-taking and risky behaviours were acquired (n = 82,315–466,751). Genomic loci were functionally annotated using FUMA. Of 8.6–8.7 K variants predicted to influence BIP, 6.6 K and 7.4 K were predicted to influence risk-taking and risky behaviours, respectively. Similarly, of 10.2–10.3 K variants influencing SCZ, 9.6 and 8.8 K were predicted to influence risk-taking and risky behaviours, respectively. We identified 192 loci jointly associated with SCZ and risk phenotypes and 206 associated with BIP and risk phenotypes, of which 68 were common to both risk-taking and risky behaviours and 124 were novel to SCZ or BIP. Functional annotation implicated differential expression in multiple cortical and sub-cortical regions. In conclusion, we report extensive polygenic overlap between risk phenotypes and BIP and SCZ, identify specific loci contributing to this shared risk and highlight biologically plausible mechanisms that may underlie risk-taking in severe psychiatric disorders.
Published: 2021
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10. Extensive bidirectional genetic overlap between bipolar disorder and cardiovascular disease phenotypes

Author: Linn Rødevand, Shahram Bahrami, Oleksandr Frei, Yunhan Chu, Alexey Shadrin, Kevin S. O’Connell, Olav B. Smeland, Torbjørn Elvsåshagen, Guy F. L. Hindley, Srdjan Djurovic, Anders M. Dale, Trine V. Lagerberg, Nils Eiel Steen, and Ole A. Andreassen
Subjects: Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Abstract Patients with bipolar disorder (BIP) have a high risk of cardiovascular disease (CVD), despite considerable individual variation. The mechanisms underlying comorbid CVD in BIP remain largely unknown. We investigated polygenic overlap between BIP and CVD phenotypes, including CVD risk factors and coronary artery disease (CAD). We analyzed large genome-wide association studies of BIP (n = 51,710) and CVD phenotypes (n = 159,208–795,640), using bivariate causal mixture model (MiXeR), which estimates the total amount of shared genetic variants, and conjunctional false discovery rate (FDR), which identifies specific overlapping loci. MiXeR revealed polygenic overlap between BIP and body mass index (BMI) (82%), diastolic and systolic blood pressure (20–22%) and CAD (11%) despite insignificant genetic correlations. Using conjunctional FDR
Published: 2021
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11. Population-based body–brain mapping links brain morphology with anthropometrics and body composition

Author: Tiril P. Gurholt, Tobias Kaufmann, Oleksandr Frei, Dag Alnæs, Unn K. Haukvik, Dennis van der Meer, Torgeir Moberget, Kevin S. O’Connell, Olof D. Leinhard, Jennifer Linge, Rozalyn Simon, Olav B. Smeland, Ida E. Sønderby, Adriano Winterton, Nils Eiel Steen, Lars T. Westlye, and Ole A. Andreassen
Subjects: Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Abstract Understanding complex body–brain processes and the interplay between adipose tissue and brain health is important for understanding comorbidity between psychiatric and cardiometabolic disorders. We investigated associations between brain structure and anthropometric and body composition measures using brain magnetic resonance imaging (MRI; n = 24,728) and body MRI (n = 4973) of generally healthy participants in the UK Biobank. We derived regional and global measures of brain morphometry using FreeSurfer and tested their association with (i) anthropometric measures, and (ii) adipose and muscle tissue measured from body MRI. We identified several significant associations with small effect sizes. Anthropometric measures showed negative, nonlinear, associations with cerebellar/cortical gray matter, and brain stem structures, and positive associations with ventricular volumes. Subcortical structures exhibited mixed effect directionality, with strongest positive association for accumbens. Adipose tissue measures, including liver fat and muscle fat infiltration, were negatively associated with cortical/cerebellum structures, while total thigh muscle volume was positively associated with brain stem and accumbens. Regional investigations of cortical area, thickness, and volume indicated widespread and largely negative associations with anthropometric and adipose tissue measures, with an opposite pattern for thigh muscle volume. Self-reported diabetes, hypertension, or hypercholesterolemia were associated with brain structure. The findings provide new insight into physiological body–brain associations suggestive of shared mechanisms between cardiometabolic risk factors and brain health. Whereas the causality needs to be determined, the observed patterns of body–brain relationships provide a foundation for understanding the underlying mechanisms linking psychiatric disorders with obesity and cardiovascular disease, with potential for the development of new prevention strategies.
Published: 2021
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12. Phenotype-specific differences in polygenicity and effect size distribution across functional annotation categories revealed by AI-MiXeR.

Author: Alexey A. Shadrin, Oleksandr Frei, Olav B. Smeland, Francesco Bettella, Kevin S. O'Connell, Osman Gani, Shahram Bahrami, Tea K. E. Uggen, Srdjan Djurovic, Dominic Holland, Ole A. Andreassen, and Anders M. Dale
Published: 2020
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13. Bivariate causal mixture model quantifies polygenic overlap between complex traits beyond genetic correlation

Author: Oleksandr Frei, Dominic Holland, Olav B. Smeland, Alexey A. Shadrin, Chun Chieh Fan, Steffen Maeland, Kevin S. O’Connell, Yunpeng Wang, Srdjan Djurovic, Wesley K. Thompson, Ole A. Andreassen, and Anders M. Dale
Subjects: Science
Abstract: To better understand the phenotypic relationships of complex traits it is also important to understand their genetic overlap. Here, Frei et al. develop MiXeR which uses GWAS summary statistics to evaluate the polygenic overlap between two traits irrespective of their genetic correlation.
Published: 2019
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14. The relationship between cannabis use, schizophrenia, and bipolar disorder: a genetically informed study

Author: Weiqiu Cheng, Nadine Parker, Naz Karadag, Elise Koch, Guy Hindley, Romain Icick, Alexey Shadrin, Kevin S O’Connell, Thomas Bjella, Shahram Bahrami, Zillur Rahman, Markos Tesfaye, Piotr Jaholkowski, Linn Rødevand, Børge Holen, Trine Vik Lagerberg, Nils Eiel Steen, Srdjan Djurovic, Anders M Dale, Oleksandr Frei, Olav B Smeland, and Ole A Andreassen
Subjects: Psychiatry and Mental health, Biological Psychiatry
Published: 2023
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15. Shared genetic architecture between schizophrenia and subcortical brain volumes implicates early neurodevelopmental processes and brain development in childhood

Author: Weiqiu Cheng, Dennis van der Meer, Nadine Parker, Guy Hindley, Kevin S. O’Connell, Yunpeng Wang, Alexey A. Shadrin, Dag Alnæs, Shahram Bahrami, Aihua Lin, Naz Karadag, Børge Holen, Sara Fernandez-Cabello, Chun-Chieh Fan, Anders M. Dale, Srdjan Djurovic, Lars T. Westlye, Oleksandr Frei, Olav B. Smeland, Ole A. Andreassen, RS: MHeNs - R2 - Mental Health, and Psychiatry 2
Subjects: Cellular and Molecular Neuroscience, Psychiatry and Mental health, Phenotype, Thalamus, Genetic Loci, Schizophrenia, Humans, Brain, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Molecular Biology, Genome-Wide Association Study
Abstract: Patients with schizophrenia have consistently shown brain volumetric abnormalities, implicating both etiological and pathological processes. However, the genetic relationship between schizophrenia and brain volumetric abnormalities remains poorly understood. Here, we applied novel statistical genetic approaches (MiXeR and conjunctional false discovery rate analysis) to investigate genetic overlap with mixed effect directions using independent genome-wide association studies of schizophrenia (n = 130,644) and brain volumetric phenotypes, including subcortical brain and intracranial volumes (n = 33,735). We found brain volumetric phenotypes share substantial genetic variants (74–96%) with schizophrenia, and observed 107 distinct shared loci with sign consistency in independent samples. Genes mapped by shared loci revealed (1) significant enrichment in neurodevelopmental biological processes, (2) three co-expression clusters with peak expression at the prenatal stage, and (3) genetically imputed thalamic expression of CRHR1 and ARL17A was associated with the thalamic volume as early as in childhood. Together, our findings provide evidence of shared genetic architecture between schizophrenia and brain volumetric phenotypes and suggest that altered early neurodevelopmental processes and brain development in childhood may be involved in schizophrenia development. acceptedVersion
Published: 2022
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16. Associations Between Symptoms of Premenstrual Disorders and Polygenic Liability for Major Psychiatric Disorders

Author: Piotr Jaholkowski, Alexey A. Shadrin, Andreas Jangmo, Evgeniia Frei, Markos Tesfaye, Guy F. L. Hindley, Marit Haram, Zillur Rahman, Lavinia Athanasiu, Nora Refsum Bakken, Børge Holen, Vera Fominykh, Gleda Kutrolli, Pravesh Parekh, Nadine Parker, Linn Rødevand, Viktoria Birkenæs, Srdjan Djurovic, Oleksandr Frei, Kevin S. O’Connell, Olav B. Smeland, Martin Tesli, and Ole A. Andreassen
Subjects: Psychiatry and Mental health
Abstract: ImportancePremenstrual disorders are heritable, clinically heterogenous, with a range of affective spectrum comorbidities. It is unclear whether genetic predispositions to affective spectrum disorders or other major psychiatric disorders are associated with symptoms of premenstrual disorders.ObjectiveTo assesss whether symptoms of premenstrual disorders are associated with the genetic liability for major psychiatric disorders, as indexed by polygenic risk scores (PRSs).Design, Setting, and ParticipantsWomen from the Norwegian Mother, Father and Child Cohort Study were included in this genetic association study. PRSs were used to determine whether genetic liability for major depression, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, and autism spectrum disorder were associated with the symptoms of premenstrual disorders, using the PRS for height as a somatic comparator. The sample was recruited across Norway between June 1999 and December 2008, and analyses were performed from July 1 to October 14, 2022.Main Outcomes and MeasuresThe symptoms of premenstrual disorders were assessed at recruitment at week 15 of pregnancy with self-reported severity of depression and irritability before menstruation. Logistic regression was applied to test for the association between the presence of premenstrual disorder symptoms and the PRSs for major psychiatric disorders.ResultsThe mean (SD) age of 56 725 women included in the study was 29.0 (4.6) years. Premenstrual disorder symptoms were present in 12 316 of 56 725 participants (21.7%). The symptoms of premenstrual disorders were associated with the PRSs for major depression (β = 0.13; 95% CI, 0.11-0.15; P = 1.21 × 10−36), bipolar disorder (β = 0.07; 95% CI, 0.05-0.09; P = 1.74 × 10−11), attention deficit/hyperactivity disorder (β = 0.07; 95% CI, 0.04-0.09; P = 1.58 × 10−9), schizophrenia (β = 0.11; 95% CI, 0.09-0.13; P = 7.61 × 10−25), and autism spectrum disorder (β = 0.03; 95% CI, 0.01-0.05; P = .02) but not with the PRS for height. The findings were confirmed in a subsample of women without a history of psychiatric diagnosis.ConclusionsThe results of this genetic association study show that genetic liability for both affective spectrum disorder and major psychiatric disorders was associated with symptoms of premenstrual disorders, indicating that premenstrual disorders have overlapping genetic foundations with major psychiatric disorders.
Published: 2023
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17. Genome-wide Association Analysis of Schizophrenia and Vitamin D Levels Shows Shared Genetic Architecture and Identifies Novel Risk Loci

Author: Piotr Jaholkowski, Guy F L Hindley, Alexey A Shadrin, Markos Tesfaye, Shahram Bahrami, Mari Nerhus, Zillur Rahman, Kevin S O’Connell, Børge Holen, Nadine Parker, Weiqiu Cheng, Aihua Lin, Linn Rødevand, Naz Karadag, Oleksandr Frei, Srdjan Djurovic, Anders M Dale, Olav B Smeland, and Ole A Andreassen
Subjects: Psychiatry and Mental health
Abstract: Low vitamin D (vitD) levels have been consistently reported in schizophrenia (SCZ) suggesting a role in the etiopathology. However, little is known about the role of underlying shared genetic mechanisms. We applied a conditional/conjunctional false discovery rate approach (FDR) on large, nonoverlapping genome-wide association studies for SCZ (N cases = 53 386, N controls = 77 258) and vitD serum concentration (N = 417 580) to evaluate shared common genetic variants. The identified genomic loci were characterized using functional analyses and biological repositories. We observed cross-trait SNP enrichment in SCZ conditioned on vitD and vice versa, demonstrating shared genetic architecture. Applying the conjunctional FDR approach, we identified 72 loci jointly associated with SCZ and vitD at conjunctional FDR
Published: 2023
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18. Genome‐wide analyses reveal novel opioid use disorder loci and genetic overlap with schizophrenia, bipolar disorder, and major depression

Author: Børge Holen, Alexey A. Shadrin, Romain Icick, Tahir T. Filiz, Guy Hindley, Linn Rødevand, Kevin S. O'Connell, Espen Hagen, Oleksandr Frei, Shahram Bahrami, Weiqiu Cheng, Nadine Parker, Markos Tesfaye, Piotr Jahołkowski, Naz Karadag, Anders M. Dale, Srdjan Djurovic, Olav B. Smeland, and Ole A. Andreassen
Subjects: Pharmacology, Psychiatry and Mental health, Medicine (miscellaneous)
Published: 2023
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19. Using iPSC Models to Understand the Role of Estrogen in Neuron–Glia Interactions in Schizophrenia and Bipolar Disorder

Author: Denis Reis de Assis, Attila Szabo, Jordi Requena Osete, Francesca Puppo, Kevin S. O’Connell, Ibrahim A. Akkouh, Timothy Hughes, Evgeniia Frei, Ole A. Andreassen, and Srdjan Djurovic
Subjects: schizophrenia, bipolar disorder, estrogen, neuron–glia interactions, iPS cells, brain organoids, Cytology, QH573-671
Abstract: Schizophrenia (SCZ) and bipolar disorder (BIP) are severe mental disorders with a considerable disease burden worldwide due to early age of onset, chronicity, and lack of efficient treatments or prevention strategies. Whilst our current knowledge is that SCZ and BIP are highly heritable and share common pathophysiological mechanisms associated with cellular signaling, neurotransmission, energy metabolism, and neuroinflammation, the development of novel therapies has been hampered by the unavailability of appropriate models to identify novel targetable pathomechanisms. Recent data suggest that neuron–glia interactions are disturbed in SCZ and BIP, and are modulated by estrogen (E2). However, most of the knowledge we have so far on the neuromodulatory effects of E2 came from studies on animal models and human cell lines, and may not accurately reflect many processes occurring exclusively in the human brain. Thus, here we highlight the advantages of using induced pluripotent stem cell (iPSC) models to revisit studies of mechanisms underlying beneficial effects of E2 in human brain cells. A better understanding of these mechanisms opens the opportunity to identify putative targets of novel therapeutic agents for SCZ and BIP. In this review, we first summarize the literature on the molecular mechanisms involved in SCZ and BIP pathology and the beneficial effects of E2 on neuron–glia interactions. Then, we briefly present the most recent developments in the iPSC field, emphasizing the potential of using patient-derived iPSCs as more relevant models to study the effects of E2 on neuron–glia interactions.
Published: 2021
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20. Using Polygenic Hazard Scores to Predict Age at Onset of Alzheimer's Disease in Nordic Populations

Author: Ehsan Motazedi, Weiqiu Cheng, Jesper Q. Thomassen, Oleksandr Frei, Arvid Rongve, Lavinia Athanasiu, Shahram Bahrami, Alexey Shadrin, Ingun Ulstein, Eystein Stordal, Anne Brækhus, Ingvild Saltvedt, Sigrid B. Sando, Kevin S. O’Connell, Guy Hindley, Dennis van der Meer, Sverre Bergh, Børge G. Nordestgaard, Anne Tybjærg-Hansen, Geir Bråthen, Lasse Pihlstrøm, Srdjan Djurovic, Ruth Frikke-Schmidt, Tormod Fladby, Dag Aarsland, Geir Selbæk, Tyler M. Seibert, Anders M. Dale, Chun C. Fan, Ole A. Andreassen, Psychiatry 2, RS: MHeNs - R2 - Mental Health, and Psychiatrie & Neuropsychologie
Subjects: RISK, Multifactorial Inheritance, General Neuroscience, DEMENTIA, Age at onset, Nordic ancestry, PROGRESSION, General Medicine, ASSOCIATION, Alzheimer's disease, VARIANTS, Polymorphism, Single Nucleotide, Article, APOLIPOPROTEIN-E, GENOTYPE, Psychiatry and Mental health, Clinical Psychology, Alzheimer Disease, LINKAGE, Humans, polygenic hazard score, Geriatrics and Gerontology, Age of Onset, HAPLOTYPES, TYPE-4 ALLELE
Abstract: BACKGROUND: Polygenic hazard scores (PHS) estimate age-dependent genetic risk of late-onset Alzheimer's disease (AD), but there is limited information about the performance of PHS on real-world data where the population of interest differs from the model development population and part of the model genotypes are missing or need to be imputed.OBJECTIVE: The aim of this study was to estimate age-dependent risk of late-onset AD using polygenic predictors in Nordic populations.METHODS: We used Desikan PHS model, based on Cox proportional hazards assumption, to obtain age-dependent hazard scores for AD from individual genotypes in the Norwegian DemGene cohort (n = 2,772). We assessed the risk discrimination and calibration of Desikan model and extended it by adding new genotype markers (the Desikan Nordic model). Finally, we evaluated both Desikan and Desikan Nordic models in two independent Danish cohorts: The Copenhagen City Heart Study (CCHS) cohort (n = 7,643) and The Copenhagen General Population Study (CGPS) cohort (n = 10,886).RESULTS: We showed a robust prediction efficiency of Desikan model in stratifying AD risk groups in Nordic populations, even when some of the model SNPs were missing or imputed. We attempted to improve Desikan PHS model by adding new SNPs to it, but we still achieved similar risk discrimination and calibration with the extended model.CONCLUSION: PHS modeling has the potential to guide the timing of treatment initiation based on individual risk profiles and can help enrich clinical trials with people at high risk to AD in Nordic populations.
Published: 2022
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21. Identification of novel genomic risk loci shared between common epilepsies and psychiatric disorders

Author: Naz Karadag, Alexey A Shadrin, Kevin S O’Connell, Guy F L Hindley, Zillur Rahman, Nadine Parker, Shahram Bahrami, Vera Fominykh, Weiqiu Cheng, Børge Holen, Silje Alvestad, Erik Taubøll, Nils Eiel Steen, Srdjan Djurovic, Anders M Dale, Oleksandr Frei, Ole A Andreassen, and Olav B Smeland
Subjects: Neurology (clinical)
Abstract: Psychiatric disorders and common epilepsies are heritable disorders with a high comorbidity and overlapping symptoms. However, the causative mechanisms underlying this relationship are poorly understood. Here we aimed to identify overlapping genetic loci between epilepsy and psychiatric disorders to gain a better understanding of their comorbidity and shared clinical features. We analysed genome-wide association study data for all epilepsies (n = 44 889), genetic generalized epilepsy (n = 33 446), focal epilepsy (n = 39 348), schizophrenia (n = 77 096), bipolar disorder (n = 406 405), depression (n = 500 199), attention deficit hyperactivity disorder (n = 53 293) and autism spectrum disorder (n = 46 350). First, we applied the MiXeR tool to estimate the total number of causal variants influencing the disorders. Next, we used the conjunctional false discovery rate statistical framework to improve power to discover shared genomic loci. Additionally, we assessed the validity of the findings in independent cohorts, and functionally characterized the identified loci. The epilepsy phenotypes were considerably less polygenic (1.0 K to 3.4 K causal variants) than the psychiatric disorders (5.6 K to 13.9 K causal variants), with focal epilepsy being the least polygenic (1.0 K variants), and depression having the highest polygenicity (13.9 K variants). We observed cross-trait genetic enrichment between genetic generalized epilepsy and all psychiatric disorders and between all epilepsies and schizophrenia and depression. Using conjunctional false discovery rate analysis, we identified 40 distinct loci jointly associated with epilepsies and psychiatric disorders at conjunctional false discovery rate The extensive genetic overlap with mixed effect directions between psychiatric disorders and common epilepsies demonstrates a complex genetic relationship between these disorders, in line with their bi-directional relationship, and indicates that overlapping genetic risk may contribute to shared pathophysiological and clinical features between epilepsy and psychiatric disorders.
Published: 2023
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22. Elevated Systemic Levels of Markers Reflecting Intestinal Barrier Dysfunction and Inflammasome Activation Are Correlated in Severe Mental Illness

Author: Søren B Jensen, Mashhood A Sheikh, Ibrahim A Akkouh, Attila Szabo, Kevin S O’Connell, Tove Lekva, John A Engh, Ingrid Agartz, Torbjørn Elvsåshagen, Monica B E G Ormerod, Melissa A Weibell, Erik Johnsen, Rune A Kroken, Ingrid Melle, Ole K Drange, Terje Nærland, Arne E Vaaler, Lars T Westlye, Pål Aukrust, Srdjan Djurovic, Nils Eiel Steen, Ole A Andreassen, and Thor Ueland
Subjects: Psychiatry and Mental health
Abstract: Background and Hypothesis Gut microbiota alterations have been reported in severe mental illness (SMI) but fewer studies have probed for signs of gut barrier disruption and inflammation. We hypothesized that gut leakage of microbial products due to intestinal inflammation could contribute to systemic inflammasome activation in SMI. Study Design We measured plasma levels of the chemokine CCL25 and soluble mucosal vascular addressin cell adhesion molecule-1 (sMAdCAM-1) as markers of T cell homing, adhesion and inflammation in the gut, lipopolysaccharide binding protein (LBP) and intestinal fatty acid binding protein (I-FABP) as markers of bacterial translocation and gut barrier dysfunction, in a large SMI cohort (n = 567) including schizophrenia (SCZ, n = 389) and affective disorder (AFF, n = 178), relative to healthy controls (HC, n = 418). We assessed associations with plasma IL-18 and IL-18BPa and leukocyte mRNA expression of NLRP3 and NLRC4 as markers of inflammasome activation. Study Results Our main findings were: (1) higher levels of sMAdCAM-1 (P = .002), I-FABP (P = 7.6E−11), CCL25 (P = 9.6E−05) and LBP (P = 2.6E−04) in SMI compared to HC in age, sex, BMI, CRP and freezer storage time adjusted analysis; (2) the highest levels of sMAdCAM-1 and CCL25 (both P = 2.6E−04) were observed in SCZ and I-FABP (P = 2.5E−10) and LBP (3) in AFF; and (3), I-FABP correlated with IL-18BPa levels and LBP correlated with NLRC4. Conclusions Our findings support that intestinal barrier inflammation and dysfunction in SMI could contribute to systemic inflammation through inflammasome activation.
Published: 2022

23. Genome‐wide analysis reveals genetic overlap between alcohol use behaviours, schizophrenia and bipolar disorder and identifies novel shared risk loci

Author: Erik D Wiström, Nils Eiel Steen, Weiqiu Cheng, Olav B. Smeland, Srdjan Djurovic, Naz Karadag, Ole A. Andreassen, Anders M. Dale, Oleksandr Frei, Kevin S. O’Connell, Alexey A. Shadrin, Guy Hindley, Shahram Bahrami, and Aihua Lin
Subjects: Genetics, Bipolar Disorder, Alcohol Drinking, Medicine (miscellaneous), Genome-wide association study, Alcohol use disorder, Biology, medicine.disease, Polymorphism, Single Nucleotide, Comorbidity, Genetic architecture, Alcoholism, Psychiatry and Mental health, Genetic Loci, Schizophrenia, mental disorders, medicine, Humans, SNP, Genetic Predisposition to Disease, Bipolar disorder, Genome-Wide Association Study, Genetic association
Abstract: Background and aim Schizophrenia (SCZ) and bipolar disorder (BD) have a high comorbidity of alcohol use disorder (AUD), and both comorbid AUD and excessive alcohol consumption (AC) have been linked to greater illness severity. We aimed to identify genomic loci jointly associated with SCZ, BD, AUD and AC to gain further insights into their shared genetic architecture. Design We analysed summary data (P values and Z scores) from genome-wide association studies (GWAS) using conjunctional false discovery rate (conjFDR) analysis, which increases power to discover shared genomic loci. We functionally characterized the identified loci using publicly available biological resources. Setting AUD and AC data provided by the Million Veteran Program, derived from the United States Department of Veterans Affairs Healthcare System. SCZ and BD data provided by the Psychiatric Genomics Consortium, based on cohorts from countries in Europe, North America and Australia. Participants AUD (34 658 cases, 167 346 controls), AC (n = 200 680), SCZ (31 013 cases and 38 918 controls), BD (20 352 cases and 31 358 controls). All participants were of European ancestry. Measurements Genomic loci shared between alcohol traits, SCZ and BD at conjFDR
Published: 2021
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24. Genome-wide analyses reveal novel opioid use disorder loci and genetic overlap with schizophrenia, bipolar disorder, and major depression

Author: Børge Holen, Alexey A. Shadrin, Romain Icick, Guy Hindley, Linn Rødevand, Kevin S. O’Connell, Oleksandr Frei, Shahram Bahrami, Weiqiu Cheng, Nadine Parker, Markos Tesfaye, Piotr Jahołkowski, Naz Karadag, Anders M. Dale, Srdjan Djurovic, Olav B. Smeland, and Ole A. Andreassen
Abstract: Opioid use disorder (OUD) and mental disorders are often comorbid, with increased morbidity and mortality. The causes underlying this relationship are poorly understood. Although these conditions are highly heritable, their shared genetic vulnerabilities remain unaccounted for. We applied the conditional/conjunctional false discovery rate (cond/conjFDR) approach to analyse summary statistics from independent genome wide association studies of OUD, SCZ, BD and MD. Next, we characterized the identified shared loci using biological annotation resources. OUD data was obtained from the Million Veteran Program (15,756 cases 99,039 controls). SCZ (53,386 cases 77,258 controls), BD (41,917 cases 371,549 controls) and MD (170,756 cases 329,443 controls) data was provided by the Psychiatric Genomics Consortium. We discovered genetic enrichment for OUD conditional on associations with SCZ, BD, MD and vice versa, indicating polygenic overlap with identification of 14 novel OUD loci at condFDRDRD2 on chromosome 11 (BD and MD), at FURIN on chromosome 15 (SCZ, BD and MD), and at the major histocompatibility complex region (SCZ and MD). Our findings provide new insights into the shared genetic architecture between OUD and SCZ, BD, and MD, indicating a complex genetic relationship, suggesting overlapping neurobiological pathways.
Published: 2022
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25. Polygenic overlap with body-mass index improves prediction of treatment-resistant schizophrenia

Author: Kevin S. O'Connell, Elise Koch, Hasan Çağın Lenk, Ibrahim A Akkouh, Guy Hindley, Piotr Jaholkowski, Robert Løvsletten Smith, Børge Holen, Alexey A. Shadrin, Oleksandr Frei, Olav B. Smeland, Nils Eiel Steen, Anders M. Dale, Espen Molden, Srdjan Djurovic, and Ole A. Andreassen
Subjects: Psychiatry and Mental health, Biological Psychiatry
Published: 2023
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26. Genetic variants associated with cardiometabolic abnormalities during treatment with selective serotonin reuptake inhibitors: a genome-wide association study

Author: Ole A. Andreassen, Srdjan Djurovic, Ingrid Dieset, Shahram Bahrami, Olav Spigset, Nils Eiel Steen, Kevin S. O’Connell, Francesco Bettella, Dennis van der Meer, Lavinia Athanasiu, and Katrine K Fjukstad
Subjects: 0301 basic medicine, Pharmacology, business.industry, digestive, oral, and skin physiology, Single-nucleotide polymorphism, Genome-wide association study, Serotonin reuptake, Bioinformatics, medicine.disease, behavioral disciplines and activities, 030226 pharmacology & pharmacy, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Schizophrenia, mental disorders, Genetics, Molecular Medicine, Medicine, lipids (amino acids, peptides, and proteins), Bipolar disorder, business, Adverse effect, Body mass index, Pharmacogenetics
Abstract: Selective serotonin reuptake inhibitors (SSRIs) are prescribed both to patients with schizophrenia and bipolar disorder. Previous studies have shown associations between SSRI treatment and cardiometabolic alterations. The aim of the present study was to investigate genetic variants associated with cardiometabolic adverse effects in patients treated with SSRIs in a naturalistic setting, using a genome-wide cross-sectional approach in a genetically homogeneous sample. We included and genotyped 1981 individuals with schizophrenia or bipolar disorder, of whom 1180 had information available on the outcomes low-density lipoprotein cholesterol (LDL-cholesterol), high-density lipoprotein cholesterol (HDL-cholesterol), triglycerides, and body mass index (BMI) and investigated interactions between SNPs and SSRI use (N = 246) by conducting a genome-wide GxE analysis. We report 13 genome-wide significant interaction effects of SNPs and SSRI serum concentrations on LDL-cholesterol, HDL-cholesterol, and BMI, located in four distinct genomic loci. This study provides new insight into the pharmacogenetics of SSRI but warrants replication in independent populations.
Published: 2021
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27. Efficient meta-analysis of multivariate genome-wide association studies with Meta-MOSTest

Author: Aihua Lin, Alexey Shadrin, Dennis van der Meer, Guy Hindley, Weiqiu Cheng, Ida Elken Sønderby, Shahram Bahrami, Kevin S O’Connell, Zillur Rahman, Nadine Parker, Olav B Smeland, Chun C. Fan, Dominic Holland, Anders M Dale, Ole A Andreassen, and Oleksandr Frei
Abstract: MotivationGenome-wide association studies (GWAS) have been successful in identifying genetic variants associated with a particular phenotype. However, many complex phenotypes are influenced by multiple genetic variants with small effects. Detecting the genetic pleiotropy can provide insights into biological mechanisms influencing complex human phenotypes. The recently developed Multivariate Omnibus Statistical Test (MOSTest) has proven to be efficient and powerful, suited for complex large-scale data. The method substantially increased discovery of genetic variants associated with brain MRI phenotypes in the UK Biobank compared to conventionally use multivariate approach. Here we extend the MOSTest to meta-analysis (Meta-MOSTest), facilitating data analysis of multiple phenotypes across multiple cohorts. We evaluated our updated approach in the UK Biobank using brain MRI phenotypes, by comparing the discovery yield of the single-cohort MOSTest versus Meta-MOSTest through simulating sub-cohorts of different sample sizes from 265 to 26501 subjects.ResultsOur method works efficiently on large-scale cohorts with a large number of MRI phenotypes. We found that lower per-cohort sample sizes resulted in a reduced discovery yield indicating a loss of statistical power. However, with a minimum sample size of 250 subjects across cohorts, Meta-MOSTest was equivalent to MOSTest on discovery yield while maintaining a well-calibrated type I error and equivalent statistical power. We conclude that Meta-MOSTest is a useful tool for multivariate analysis across separate brain imaging genetics cohorts.Availability and implementationAll codes are freely available on GitHub: MOSTest and Meta-MOSTest.
Published: 2022
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28. Genetic architecture of creativity and extensive genetic overlap with psychiatric disorders revealed from genome-wide association analyses of 241,736 individuals

Author: Hyejin Kim, Yeeun Ahn, Joohyun Yoon, Kyeongmin Jung, Soyeon Kim, Injeong Shim, Tae Hwan Park, Hyunwoong Ko, Sang-Hyuk Jung, Jaeyoung Kim, Sanghyeon Park, Dong June Lee, Sunho Choi, Soojin Cha, Beomsu Kim, Min Young Cho, Hyunbin Cho, Dan Say Kim, Hong Kyu Ihm, Woong-Yang Park, Hasan Bakhshi, Kevin S O’Connell, Ole A Andreassen, Jonathan Flint, Kenneth S. Kendler, Woojae Myung, and Hong-Hee Won
Abstract: Creativity is heritable and exhibits familial aggregation with psychiatric disorders, but its genomic basis and genetic relationship with psychiatric disorders remain largely unknown. Here, we conducted a genome-wide association study (GWAS) using an expanded, machine learning-based definition of creativity in individuals of European ancestry from the UK Biobank (n= 241,736) and identified 25 creativity-associated loci. Extensive genetic overlap with psychiatric disorders, including schizophrenia, major depression, bipolar I disorder, attention deficit/hyperactivity disorder, and anorexia nervosa, was demonstrated by the genetic correlation, polygenic risk score, and MiXeR analyses. The condFDR and conjFDR analyses identified additional loci for creativity and psychiatric disorders, as well as shared genetic loci between creativity and psychiatric disorders. This GWAS showed significant correlations with GWASs using traditional definitions of creativity and GWASs adjusted for educational attainment. Our findings contribute to the understanding of the genetic architecture of creativity and reveal its polygenic relationships with psychiatric disorders.
Published: 2022
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29. Genetic loci shared between major depression and intelligence with mixed directions of effect

Author: Oleksandr Frei, Francesco Bettella, Jan Ivar Røssberg, Guy Hindley, Shahram Bahrami, Anders M. Dale, Kevin S. O’Connell, Alexey A. Shadrin, Olav B. Smeland, Torill Ueland, Florian Krull, Srdjan Djurovic, Nils Eiel Steen, Chun Chieh Fan, and Ole A. Andreassen
Subjects: False discovery rate, Multifactorial Inheritance, Social Psychology, Intelligence, Experimental and Cognitive Psychology, Genome-wide association study, Biology, Genetic correlation, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Behavioral Neuroscience, 0302 clinical medicine, medicine, Humans, Cognitive Dysfunction, Genetic Predisposition to Disease, Allele, Behavioural genetics, 030304 developmental biology, Genetic association, Genetics, 0303 health sciences, Depressive Disorder, Major, Genome, medicine.disease, Phenotype, Genetic Loci, Major depressive disorder, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Genome-wide association studies (GWAS) have identified several common genetic variants influencing major depression and general cognitive abilities, but little is known about whether the two share any of their genetic aetiology. Here we investigate shared genomic architectures between major depression (MD) and general intelligence (INT) with the MiXeR statistical tool and their overlapping susceptibility loci with conjunctional false discovery rate (conjFDR), which evaluate the level of overlap in genetic variants and improve the power for gene discovery between two phenotypes. We analysed GWAS data on MD (n = 480,359) and INT (n = 269,867) to characterize polygenic architecture and identify genetic loci shared between these phenotypes. Despite non-significant genetic correlation (rg = −0.0148, P = 0.50), we observed large polygenic overlap and identified 92 loci shared between MD and INT at conjFDR
Published: 2021

30. Genome-wide analysis reveals extensive genetic overlap between schizophrenia, bipolar disorder, and intelligence

Author: Shahram Bahrami, Alexey A. Shadrin, Kyoko Watanabe, Oleksandr Frei, Olav B. Smeland, Anders M. Dale, Torill Ueland, Kevin S. O’Connell, Florian Krull, Srdjan Djurovic, Francesco Bettella, Danielle Posthuma, Jeanne E. Savage, Ole A. Andreassen, Nils Eiel Steen, Amsterdam Neuroscience - Complex Trait Genetics, Complex Trait Genetics, Human genetics, and Amsterdam Reproduction & Development (AR&D)
Subjects: 0301 basic medicine, False discovery rate, Adult, Male, Multifactorial Inheritance, Bipolar Disorder, Intelligence, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Polymorphism (computer science), Databases, Genetic, medicine, Humans, Cognitive Dysfunction, Genetic Predisposition to Disease, Effects of sleep deprivation on cognitive performance, Bipolar disorder, Molecular Biology, Genetics, Cognition, medicine.disease, Psychiatry and Mental health, 030104 developmental biology, Schizophrenia, Genetic Loci, Etiology, Female, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Schizophrenia (SCZ) and bipolar disorder (BD) are severe mental disorders associated with cognitive impairment, which is considered a major determinant of functional outcome. Despite this, the etiology of the cognitive impairment is poorly understood, and no satisfactory cognitive treatments exist. Increasing evidence indicates that genetic risk for SCZ may contribute to cognitive impairment, whereas the genetic relationship between BD and cognitive function remains unclear. Here, we combined large genome-wide association study data on SCZ (n = 82,315), BD (n = 51,710), and general intelligence (n = 269,867) to investigate overlap in common genetic variants using conditional false discovery rate (condFDR) analysis. We observed substantial genetic enrichment in both SCZ and BD conditional on associations with intelligence indicating polygenic overlap. Using condFDR analysis, we leveraged this enrichment to increase statistical power and identified 75 distinct genomic loci associated with both SCZ and intelligence, and 12 loci associated with both BD and intelligence at conjunctional FDR
Published: 2020
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31. Multivariate genetic analysis of personality and cognitive traits reveals abundant pleiotropy and improves prediction

Author: Guy Hindley, Alexey Shadrin, Dennis van der Meer, Nadine Parker, Weiqiu Cheng, Kevin S. O’Connell, Shahram Bahrami, Aihua Lin, Naz Karadag, Børge Holen, Thomas Bjella, Chun C Fan, Torill Ueland, Srdjan Djurovic, Olav B. Smeland, Oleksandr Frei, Anders M. Dale, and Ole A. Andreassen
Abstract: Personality and cognition are heritable mental traits, and their genetic determinants may be distributed across interconnected brain functions. However, previous studies have employed univariate approaches which reduce complex traits to summary measures. We applied the “pleiotropy-informed” multivariate omnibus statistical test (MOSTest) to genome-wide association studies (GWAS) of 35 item and task-level measures of neuroticism and cognition from the UK Biobank (n=336,993). We identified 431 significant genetic loci and found evidence of abundant pleiotropy across personality and cognitive domains. Functional characterisation implicated genes with significant tissue-specific expression in all tested brain tissues and enriched in brain-specific gene-sets. We conditioned independent GWAS of the Big 5 personality traits and cognition on our multivariate findings, which boosted genetic discovery in other personality traits and improved polygenic prediction. These findings advance our understanding of the polygenic architecture of complex mental traits, indicating a prominence of pleiotropic genetic effects across higher-order domains of mental function.Graphical abstract
Published: 2022
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32. 74. DEVELOPMENTAL MANIFESTATIONS OF POLYGENIC RISK FOR BIPOLAR DISORDER FROM INFANCY TO MIDDLE CHILDHOOD

Author: Ragna Askeland, Laurie Hannigan, Elizabeth Corfield, Oleksander Frei, Anita Thapar, George Davey Smith, Ted Reichborn-Kjennerud, Ole A. Andreassen, Helga Ask, Kevin S. O'Connell, and Alexandra Havdahl
Subjects: Pharmacology, Psychiatry and Mental health, Neurology, Pharmacology (medical), Neurology (clinical), Biological Psychiatry
Published: 2022
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33. Shared heritability among psychiatric disorders and traits

Author: Kevin S. O’Connell, Guy Hindley, Olav B. Smeland, Alexey Shadrin, Yunpeng Wang, Oleksandr Frei, and Ole A. Andreassen
Published: 2022
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34. Systemic Cell Adhesion Molecules in Severe Mental Illness: Potential Role of Intercellular CAM-1 in Linking Peripheral and Neuroinflammation

Author: Mashhood A. Sheikh, Kevin S. O’Connell, Tove Lekva, Attila Szabo, Ibrahim A. Akkouh, Jordi Requena Osete, Ingrid Agartz, John A. Engh, Dimitrios Andreou, Birgitte Boye, Erlend Bøen, Torbjørn Elvsåshagen, Sigrun Hope, Maren Caroline Frogner Werner, Inge Joa, Erik Johnsen, Rune A. Kroken, Trine Vik Lagerberg, Ingrid Melle, Ole Kristian Drange, Gunnar Morken, Terje Nærland, Kjetil Sørensen, Arne E. Vaaler, Melissa Authen Weibell, Lars T. Westlye, Pål Aukrust, Srdjan Djurovic, Nils Eiel Steen, Ole A. Andreassen, and Thor Ueland
Subjects: Medisinske Fag: 700 [VDP], Biological Psychiatry
Abstract: Background Cell adhesion molecules (CAMs) orchestrate leukocyte trafficking and could link peripheral and neuroinflammation in patients with severe mental illness (SMI), by promoting inflammatory and immune-mediated responses and mediating signals across blood-brain barrier. We hypothesized that CAMs would be dysregulated in SMI and evaluated plasma levels of different vascular and neural CAMs. Dysregulated CAMs in plasma were further evaluated in vivo in leukocytes and brain tissue and in vitro in induced pluripotent stem cells. Methods We compared plasma soluble levels of different vascular (VCAM-1, ICAM-1, P-SEL) and neural (JAM-A, NCAD) CAMs in circulating leukocytes in a large SMI sample of schizophrenia (SCZ) spectrum disorder (n = 895) and affective disorder (n = 737) and healthy control participants (n = 1070) controlling for age, sex, body mass index, C-reactive protein, and freezer storage time. We also evaluated messenger RNA expression of ICAM1 and related genes encoding ICAM-1 receptors in leukocytes using microarray (n = 842) and in available RNA sequencing data from the CommonMind Consortium (CMC) in postmortem samples from the dorsolateral prefrontal cortex (n = 474). The regulation of soluble ICAM-1 in induced pluripotent stem cell–derived neurons and astrocytes was assessed in patients with SCZ and healthy control participants (n = 8 of each). Results Our major findings were 1) increased soluble ICAM-1 in patients with SMI compared with healthy control participants; 2) increased ITGB2 messenger RNA, encoding the beta chain of the ICAM-1 receptor, in circulating leukocytes from patients with SMI and increased prefrontal cortex messenger RNA expression of ICAM1 in SCZ; and 3) enhanced soluble ICAM-1 release in induced pluripotent stem cell–derived neurons from patients with SCZ. Conclusions Our results support a systemic and cerebral dysregulation of soluble ICAM-1 expression in SMI and especially in patients with SCZ.
Published: 2022

35. List of contributors

Author: Nzaar Al-Chalabi, Ole A. Andreassen, David Baron, Kenneth Blum, Abdalla Bowirrat, Philip Brady, Raymond Brewer, Jean Lud Cadet, Aiden Corvin, Alanna Cote, Vincenzo De Luca, Jürgen Deckert, Caroline K. Diehl, Vita Dolžan, Angelika Erhardt, Ali Bani Fatemi, Marcelo Febo, Alessandra G. Ferrera, Oleksandr Frei, Mark S. Gold, Joseph F. Goldberg, Elizabeth A. Heron, Guy Hindley, Laura M. Huckins, Amarachukwu Igblom, Marin M. Juki, Lea K. Davis, Jessica Kiri Dennis, Camillia Kong, Blanka Kores Plesničar, Manuel Mattheisen, Gregory A. Miller, Asmita Mishrekar, Charles B. Nemeroff, John I. Nurnberger, Cathal Ormond, Kevin S. O’Connell, Claudia Pisanu, Jessica Qian, Nicolas Ramoz, Brigitte Rockstroh, Niamh M. Ryan, James N. Samsom, Alexey Shadrin, Olav B. Smeland, Alessio Squassina, Tea Terzi, Panayotis K. Thanos, Evangelia Eirini Tsermpini, Yin Wang, Yunpeng Wang, Albert H.C. Wong, Cindy M. Yee, Hannah Young, and Young Zhou
Published: 2022
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36. Genetics of bipolar disorder

Author: Kevin S. O’Connell, Olav B. Smeland, and Ole A. Andreassen
Published: 2022
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37. The shared genetic basis of mood instability and psychiatric disorders: A cross-trait genome-wide association analysis

Author: Guy Hindley, Kevin S. O'Connell, Zillur Rahman, Oleksandr Frei, Shahram Bahrami, Alexey Shadrin, Margrethe C. Høegh, Weiqiu Cheng, Naz Karadag, Aihua Lin, Linn Rødevand, Chun C. Fan, Srdjan Djurovic, Trine V. Lagerberg, Anders M. Dale, Olav B. Smeland, and Ole A. Andreassen
Subjects: Cellular and Molecular Neuroscience, Psychiatry and Mental health, Depressive Disorder, Major, Multifactorial Inheritance, Bipolar Disorder, Schizophrenia, Humans, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Genetics (clinical), Genome-Wide Association Study
Abstract: Recent genome-wide association studies of mood instability (MOOD) have found significant positive genetic correlation with major depression (DEP) and weak correlations with other psychiatric disorders. We investigated the polygenic overlap between MOOD and psychiatric disorders beyond genetic correlation to better characterize putative shared genetic determinants. GWAS summary statistics for schizophrenia (SCZ, n = 105,318), bipolar disorder (BIP, n = 413,466), DEP (n = 450,619), attention-deficit hyperactivity disorder (ADHD, n = 53,293), and MOOD (n = 363,705) were analyzed using the bivariate causal mixture model and conjunctional false discovery rate methods. MOOD correlated positively with all psychiatric disorders, but with wide variation in strength (rg = 0.10–0.62). Of 10.4 K genomic variants influencing MOOD, 4 K–9.4 K influenced psychiatric disorders. Furthermore, MOOD was jointly associated with DEP at 163 loci, SCZ at 110, BIP at 60 and ADHD at 25. Fifty-three jointly associated loci were overlapping across two or more disorders, seven of which had discordant effect directions on psychiatric disorders. Genes mapped to loci associated with MOOD and all four disorders were enriched in a single gene-set, “synapse organization.” The extensive polygenic overlap indicates shared molecular underpinnings across MOOD and psychiatric disorders. However, distinct patterns of genetic correlation and effect directions may relate to differences in the core clinical features of each disorder. publishedVersion
Published: 2022

38. Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Author: Niamh Mullins, JooEun Kang, Adrian I. Campos, Jonathan R.I. Coleman, Alexis C. Edwards, Hanga Galfalvy, Daniel F. Levey, Adriana Lori, Andrey Shabalin, Anna Starnawska, Mei-Hsin Su, Hunna J. Watson, Mark Adams, Swapnil Awasthi, Michael Gandal, Jonathan D. Hafferty, Akitoyo Hishimoto, Minsoo Kim, Satoshi Okazaki, Ikuo Otsuka, Stephan Ripke, Erin B. Ware, Andrew W. Bergen, Wade H. Berrettini, Martin Bohus, Harry Brandt, Xiao Chang, Wei J. Chen, Hsi-Chung Chen, Steven Crawford, Scott Crow, Emily DiBlasi, Philibert Duriez, Fernando Fernández-Aranda, Manfred M. Fichter, Steven Gallinger, Stephen J. Glatt, Philip Gorwood, Yiran Guo, Hakon Hakonarson, Katherine A. Halmi, Hai-Gwo Hwu, Sonia Jain, Stéphane Jamain, Susana Jiménez-Murcia, Craig Johnson, Allan S. Kaplan, Walter H. Kaye, Pamela K. Keel, James L. Kennedy, Kelly L. Klump, Dong Li, Shih-Cheng Liao, Klaus Lieb, Lisa Lilenfeld, Chih-Min Liu, Pierre J. Magistretti, Christian R. Marshall, James E. Mitchell, Eric T. Monson, Richard M. Myers, Dalila Pinto, Abigail Powers, Nicolas Ramoz, Stefan Roepke, Vsevolod Rozanov, Stephen W. Scherer, Christian Schmahl, Marcus Sokolowski, Michael Strober, Laura M. Thornton, Janet Treasure, Ming T. Tsuang, Stephanie H. Witt, D. Blake Woodside, Zeynep Yilmaz, Lea Zillich, Rolf Adolfsson, Ingrid Agartz, Tracy M. Air, Martin Alda, Lars Alfredsson, Ole A. Andreassen, Adebayo Anjorin, Vivek Appadurai, María Soler Artigas, Sandra Van der Auwera, M. Helena Azevedo, Nicholas Bass, Claiton H.D. Bau, Bernhard T. Baune, Frank Bellivier, Klaus Berger, Joanna M. Biernacka, Tim B. Bigdeli, Elisabeth B. Binder, Michael Boehnke, Marco P. Boks, Rosa Bosch, David L. Braff, Richard Bryant, Monika Budde, Enda M. Byrne, Wiepke Cahn, Miguel Casas, Enrique Castelao, Jorge A. Cervilla, Boris Chaumette, Sven Cichon, Aiden Corvin, Nicholas Craddock, David Craig, Franziska Degenhardt, Srdjan Djurovic, Howard J. Edenberg, Ayman H. Fanous, Jerome C. Foo, Andreas J. Forstner, Mark Frye, Janice M. Fullerton, Justine M. Gatt, Pablo V. Gejman, Ina Giegling, Hans J. Grabe, Melissa J. Green, Eugenio H. Grevet, Maria Grigoroiu-Serbanescu, Blanca Gutierrez, Jose Guzman-Parra, Steven P. Hamilton, Marian L. Hamshere, Annette Hartmann, Joanna Hauser, Stefanie Heilmann-Heimbach, Per Hoffmann, Marcus Ising, Ian Jones, Lisa A. Jones, Lina Jonsson, René S. Kahn, John R. Kelsoe, Kenneth S. Kendler, Stefan Kloiber, Karestan C. Koenen, Manolis Kogevinas, Bettina Konte, Marie-Odile Krebs, Mikael Landén, Jacob Lawrence, Marion Leboyer, Phil H. Lee, Douglas F. Levinson, Calwing Liao, Jolanta Lissowska, Susanne Lucae, Fermin Mayoral, Susan L. McElroy, Patrick McGrath, Peter McGuffin, Andrew McQuillin, Sarah E. Medland, Divya Mehta, Ingrid Melle, Yuri Milaneschi, Philip B. Mitchell, Esther Molina, Gunnar Morken, Preben Bo Mortensen, Bertram Müller-Myhsok, Caroline Nievergelt, Vishwajit Nimgaonkar, Markus M. Nöthen, Michael C. O’Donovan, Roel A. Ophoff, Michael J. Owen, Carlos Pato, Michele T. Pato, Brenda W.J.H. Penninx, Jonathan Pimm, Giorgio Pistis, James B. Potash, Robert A. Power, Martin Preisig, Digby Quested, Josep Antoni Ramos-Quiroga, Andreas Reif, Marta Ribasés, Vanesa Richarte, Marcella Rietschel, Margarita Rivera, Andrea Roberts, Gloria Roberts, Guy A. Rouleau, Diego L. Rovaris, Dan Rujescu, Cristina Sánchez-Mora, Alan R. Sanders, Peter R. Schofield, Thomas G. Schulze, Laura J. Scott, Alessandro Serretti, Jianxin Shi, Stanley I. Shyn, Lea Sirignano, Pamela Sklar, Olav B. Smeland, Jordan W. Smoller, Edmund J.S. Sonuga-Barke, Gianfranco Spalletta, John S. Strauss, Beata Świątkowska, Maciej Trzaskowski, Gustavo Turecki, Laura Vilar-Ribó, John B. Vincent, Henry Völzke, James T.R. Walters, Cynthia Shannon Weickert, Thomas W. Weickert, Myrna M. Weissman, Leanne M. Williams, Naomi R. Wray, Clement C. Zai, Allison E. Ashley-Koch, Jean C. Beckham, Elizabeth R. Hauser, Michael A. Hauser, Nathan A. Kimbrel, Jennifer H. Lindquist, Benjamin McMahon, David W. Oslin, Xuejun Qin, Esben Agerbo, Anders D. Børglum, Gerome Breen, Annette Erlangsen, Tõnu Esko, Joel Gelernter, David M. Hougaard, Ronald C. Kessler, Henry R. Kranzler, Qingqin S. Li, Nicholas G. Martin, Andrew M. McIntosh, Ole Mors, Merete Nordentoft, Catherine M. Olsen, David Porteous, Robert J. Ursano, Danuta Wasserman, Thomas Werge, David C. Whiteman, Cynthia M. Bulik, Hilary Coon, Ditte Demontis, Anna R. Docherty, Po-Hsiu Kuo, Cathryn M. Lewis, J. John Mann, Miguel E. Rentería, Daniel J. Smith, Eli A. Stahl, Murray B. Stein, Fabian Streit, Virginia Willour, Douglas M. Ruderfer, Manuel Mattheisen, Abdel Abdellaoui, Mark J. Adams, Till F.M. Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T.F. Beekman, Julien Bryois, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Jane Hvarregaard Christensen, Toni-Kim Clarke, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Nick Craddock, Gregory E. Crawford, Gail Davies, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Valentina Escott-Price, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Josef Frank, Héléna A. Gaspar, Michael Gill, Fernando S. Goes, Scott D. Gordon, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Yang Wu, Hualin S. Xi, Jian Yang, Futao Zhang, Volker Arolt, Dorret I. Boomsma, Udo Dannlowski, E.J.C. de Geus, J. Raymond Depaulo, Enrico Domenici, Katharina Domschke, Jakob Grove, Lynsey S. Hall, Christine Søholm Hansen, Thomas F. Hansen, Stefan Herms, Ian B. Hickie, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, David M. Howard, Rick Jansen, Eric Jorgenson, James A. Knowles, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Donald J. MacIntyre, Dean F. MacKinnon, Robert M. Maier, Wolfgang Maier, Jonathan Marchini, Hamdi Mbarek, Christel M. Middeldorp, Evelin Mihailov, Lili Milani, Francis M. Mondimore, Grant W. Montgomery, Sara Mostafavi, Matthias Nauck, Bernard Ng, Michel G. Nivard, Dale R. Nyholt, Paul F. O’Reilly, Hogni Oskarsson, Caroline Hayward, Andrew C. Heath, Glyn Lewis, Pamela A.F. Madden, Patrik K. Magnusson, Andres Metspalu, Sara A. Paciga, Nancy L. Pedersen, Jodie N. Painter, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Roseann E. Peterson, Wouter J. Peyrot, Danielle Posthuma, Jorge A. Quiroz, Per Qvist, John P. Rice, Brien P. Riley, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Engilbert Sigurdsson, Grant C.B. Sinnamon, Johannes H. Smit, Hreinn Stefansson, Stacy Steinberg, Jana Strohmaier, Katherine E. Tansey, Henning Teismann, Alexander Teumer, Wesley Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, Vassily Trubetskoy, André G. Uitterlinden, Daniel Umbricht, Albert M. van Hemert, Alexander Viktorin, Peter M. Visscher, Yunpeng Wang, Bradley T. Webb, Roy H. Perlis, David J. Porteous, Catherine Schaefer, Kari Stefansson, Henning Tiemeier, Rudolf Uher, Patrick F. Sullivan, Kevin S. O’Connell, Brandon Coombes, Zhen Qiao, Thomas D. Als, Sigrid Børte, Alexander W. Charney, Ole Kristian Drange, Michael J. Gandal, Saskia P. Hagenaars, Masashi Ikeda, Nolan Kamitaki, Kristi Krebs, Georgia Panagiotaropoulou, Brian M. Schilder, Laura G. Sloofman, Bendik S. Winsvold, Hong-Hee Won, Liliya Abramova, Kristina Adorjan, Mariam Al Eissa, Diego Albani, Ney Alliey-Rodriguez, Verneri Antilla, Anastasia Antoniou, Ji Hyun Baek, Michael Bauer, Eva C. Beins, Sarah E. Bergen, Armin Birner, Erlend Bøen, Murielle Brum, Ben M. Brumpton, Nathalie Brunkhorst-Kanaan, William Byerley, Murray Cairns, Miquel Casas, Pablo Cervantes, Cristiana Cruceanu, Alfredo Cuellar-Barboza, Julie Cunningham, David Curtis, Piotr M. Czerski, Anders M. Dale, Nina Dalkner, Friederike S. David, Amanda L. Dobbyn, Athanassios Douzenis, Torbjørn Elvsåshagen, I. Nicol Ferrier, Alessia Fiorentino, Tatiana M. Foroud, Liz Forty, Oleksandr Frei, Nelson B. Freimer, Louise Frisén, Katrin Gade, Julie Garnham, Ian R. Gizer, Katherine Gordon-Smith, Tiffany A. Greenwood, José Guzman-Parra, Kyooseob Ha, Magnus Haraldsson, Martin Hautzinger, Urs Heilbronner, Dennis Hellgren, Peter A. Holmans, Laura Huckins, Jessica S. Johnson, Janos L. Kalman, Yoichiro Kamatani, Sarah Kittel-Schneider, Maria Koromina, Thorsten M. Kranz, Michiaki Kubo, Ralph Kupka, Steven A. Kushner, Catharina Lavebratt, Markus Leber, Heon-Jeong Lee, Shawn E. Levy, Catrin Lewis, Martin Lundberg, Sigurdur H. Magnusson, Adam Maihofer, Dolores Malaspina, Eirini Maratou, Lina Martinsson, Nathaniel W. McGregor, James D. McKay, Helena Medeiros, Vincent Millischer, Jennifer L. Moran, Derek W. Morris, Thomas W. Mühleisen, Niamh O’Brien, Claire O’Donovan, Loes M. Olde Loohuis, Lilijana Oruc, Sergi Papiol, Antonio F. Pardiñas, Amy Perry, Andrea Pfennig, Evgenia Porichi, Towfique Raj, Mark H. Rapaport, J. Raymond DePaulo, Eline J. Regeer, Fabio Rivas, Julian Roth, Panos Roussos, Fanny Senner, Sally Sharp, Paul D. Shilling, Claire Slaney, Janet L. Sobell, Maria Soler Artigas, Anne T. Spijker, Dan J. Stein, Chikashi Terao, Claudio Toma, Paul Tooney, Evangelia-Eirini Tsermpini, Marquis P. Vawter, Helmut Vedder, Simon Xi, Wei Xu, Jessica Mei Kay Yang, Allan H. Young, Hannah Young, Peter P. Zandi, Hang Zhou, null HUNT All-In Psychiatry, Gulja Babadjanova, Lena Backlund, Susanne Bengesser, Douglas H.R. Blackwood, Vaughan J. Carr, Stanley Catts, Dimitris Dikeos, Bruno Etain, Panagiotis Ferentinos, Micha Gawlik, Elliot S. Gershon, Frans Henskens, Jan Hillert, Kyung Sue Hong, Christina M. Hultman, Kristian Hveem, Nakao Iwata, Assen V. Jablensky, George Kirov, Christine Lochner, Carmel Loughland, Carol A. Mathews, Francis J. McMahon, Patricia Michie, Bryan Mowry, Benjamin M. Neale, Caroline M. Nievergelt, Ketil J. Oedegaard, Tomas Olsson, Chris Pantelis, George P. Patrinos, Eva Z. Reininghaus, Takeo Saito, Ulrich Schall, Martin Schalling, Rodney J. Scott, Eystein Stordal, Arne E. Vaaler, Eduard Vieta, Irwin D. Waldman, John-Anker Zwart, John I. Nurnberger, Arianna Di Florio, Roger A.H. Adan, Tetsuya Ando, Harald Aschauer, Jessica H. Baker, Vladimir Bencko, Andreas Birgegård, Joseph M. Boden, Ilka Boehm, Claudette Boni, Vesna Boraska Perica, Katharina Buehren, Roland Burghardt, Laura Carlberg, Matteo Cassina, Maurizio Clementi, Roger D. Cone, Philippe Courtet, James J. Crowley, Unna N. Danner, Oliver S.P. Davis, Martina de Zwaan, George Dedoussis, Daniela Degortes, Janiece E. DeSocio, Danielle M. Dick, Christian Dina, Monika Dmitrzak-Weglarz, Elisa Docampo Martinez, Laramie E. Duncan, Karin Egberts, Morten Mattingsdal, Sara McDevitt, Ingrid Meulenbelt, Nadia Micali, James Mitchell, Karen Mitchell, Palmiero Monteleone, Alessio Maria Monteleone, Melissa A. Munn-Chernoff, Benedetta Nacmias, Marie Navratilova, Ioanna Ntalla, Julie K. O’Toole, Leonid Padyukov, Aarno Palotie, Jacques Pantel, Hana Papezova, Richard Parker, John F. Pearson, Stefan Ehrlich, Geòrgia Escaramís, Thomas Espeseth, Xavier Estivill, Anne Farmer, Angela Favaro, Krista Fischer, James A.B. Floyd, Manuel Föcker, Lenka Foretova, Monica Forzan, Christopher S. Franklin, Giovanni Gambaro, Johanna Giuranna, Paola Giusti-Rodríquez, Fragiskos Gonidakis, Scott Gordon, Monica Gratacos Mayora, Sébastien Guillaume, Ken B. Hanscombe, Konstantinos Hatzikotoulas, Johannes Hebebrand, Sietske G. Helder, Anjali K. Henders, Beate Herpertz-Dahlmann, Wolfgang Herzog, Anke Hinney, L. John Horwood, Christopher Hübel, Liselotte V. Petersen, Kirstin L. Purves, Anu Raevuori, Ted Reichborn-Kjennerud, Valdo Ricca, Samuli Ripatti, Franziska Ritschel, Marion Roberts, Filip Rybakowski, Paolo Santonastaso, André Scherag, Ulrike Schmidt, Nicholas J. Schork, Alexandra Schosser, Jochen Seitz, Lenka Slachtova, P. Eline Slagboom, Margarita C.T. Slof-Op ‘t Landt, Agnieszka Slopien, Nicole Soranzo, Sandro Sorbi, Lorraine Southam, Vidar W. Steen, Laura M. Huckins, James I. Hudson, Hartmut Imgart, Hidetoshi Inoko, Vladimir Janout, Jennifer Jordan, Antonio Julià, Gursharan Kalsi, Deborah Kaminská, Jaakko Kaprio, Leila Karhunen, Andreas Karwautz, Martien J.H. Kas, Martin A. Kennedy, Anna Keski-Rahkonen, Kirsty Kiezebrink, Youl-Ri Kim, Katherine M. Kirk, Lars Klareskog, Gun Peggy S. Knudsen, Janne T. Larsen, Stephanie Le Hellard, Virpi M. Leppä, Paul Lichtenstein, Bochao Danae Lin, Astri Lundervold, Jurjen Luykx, Mario Maj, Katrin Mannik, Sara Marsal, Garret D. Stuber, Jin P. Szatkiewicz, Ioanna Tachmazidou, Elena Tenconi, Alfonso Tortorella, Federica Tozzi, Artemis Tsitsika, Marta Tyszkiewicz-Nwafor, Konstantinos Tziouvas, Annemarie A. van Elburg, Eric F. van Furth, Tracey D. Wade, Gudrun Wagner, Esther Walton, H. Erich Wichmann, Elisabeth Widen, Shuyang Yao, Eleftheria Zeggini, Stephanie Zerwas, Stephan Zipfel, Martin Jungkunz, Lydie Dietl, Cornelia E. Schwarze, Norbert Dahmen, Björn H. Schott, Arian Mobascher, Silvia Crivelli, Michelle F. Dennis, Phillip D. Harvey, Bruce W. Carter, Jennifer E. Huffman, Daniel Jacobson, Ravi Madduri, Maren K. Olsen, John Pestian, J. Michael Gaziano, Sumitra Muralidhar, Rachel Ramoni, Jean Beckham, Kyong-Mi Chang, Christopher J. O’Donnell, Philip S. Tsao, James Breeling, Grant Huang, J.P. Casas Romero, Jennifer Moser, Stacey B. Whitbourne, Jessica V. Brewer, Mihaela Aslan, Todd Connor, Dean P. Argyres, Brady Stephens, Mary T. Brophy, Donald E. Humphries, Luis E. Selva, Nhan Do, Shahpoor Shayan, Kelly Cho, Saiju Pyarajan, Elizabeth Hauser, Yan Sun, Hongyu Zhao, Peter Wilson, Rachel McArdle, Louis Dellitalia, Kristin Mattocks, John Harley, Clement J. Zablocki, Jeffrey Whittle, Frank Jacono, Salvador Gutierrez, Gretchen Gibson, Kimberly Hammer, Laurence Kaminsky, Gerardo Villareal, Scott Kinlay, Junzhe Xu, Mark Hamner, Roy Mathew, Sujata Bhushan, Pran Iruvanti, Michael Godschalk, Zuhair Ballas, Douglas Ivins, Stephen Mastorides, Jonathan Moorman, Saib Gappy, Jon Klein, Nora Ratcliffe, Hermes Florez, Olaoluwa Okusaga, Maureen Murdoch, Peruvemba Sriram, Shing Shing Yeh, Neeraj Tandon, Darshana Jhala, Samuel Aguayo, David Cohen, Satish Sharma, Suthat Liangpunsakul, Kris Ann Oursler, Mary Whooley, Sunil Ahuja, Joseph Constans, Paul Meyer, Jennifer Greco, Michael Rauchman, Richard Servatius, Melinda Gaddy, Agnes Wallbom, Timothy Morgan, Todd Stapley, Scott Sherman, George Ross, Philip Tsao, Patrick Strollo, Edward Boyko, Laurence Meyer, Samir Gupta, Mostaqul Huq, Joseph Fayad, Adriana Hung, Jack Lichy, Robin Hurley, Brooks Robey, Robert Striker, Dietl, Lydie, Schwarze, Cornelia E., Dahmen, Norbert, Schott, Björn H., Nöthen, Markus M., Ripke, Stephan, Mobascher, Arian, Rujescu, Dan, Lieb, Klaus, Roepke, Stefan, Schmahl, Christian, Bohus, Martin, Rietschel, Marcella, Crivelli, Silvia, Dennis, Michelle F., Harvey, Phillip D., Carter, Bruce W., Huffman, Jennifer E., Jacobson, Daniel, Madduri, Ravi, Olsen, Maren K., Pestian, John, Gaziano, J. Michael, Muralidhar, Sumitra, Ramoni, Rachel, Beckham, Jean, Chang, Kyong-Mi, O'Donnell, Christopher J., Tsao, Philip S., Breeling, James, Huang, Grant, Romero, J. P. Casas, Moser, Jennifer, Whitbourne, Stacey B., Brewer, Jessica V., Aslan, Mihaela, Connor, Todd, Argyres, Dean P., Stephens, Brady, Brophy, Mary T., Humphries, Donald E., Selva, Luis E., Do, Nhan, Shayan, Shahpoor, Cho, Kelly, Pyarajan, Saiju, Hauser, Elizabeth, Sun, Yan, Zhao, Hongyu, Wilson, Peter, McArdle, Rachel, Dellitalia, Louis, Mattocks, Kristin, Harley, John, Zablocki, Clement J., Whittle, Jeffrey, Jacono, Frank, Gutierrez, Salvador, Gibson, Gretchen, Hammer, Kimberly, Kaminsky, Laurence, Villareal, Gerardo, Kinlay, Scott, Xu, Junzhe, Hamner, Mark, Mathew, Roy, Bhushan, Sujata, Iruvanti, Pran, Godschalk, Michael, Ballas, Zuhair, Ivins, Douglas, Mastorides, Stephen, Moorman, Jonathan, Gappy, Saib, Klein, Jon, Ratcliffe, Nora, Florez, Hermes, Okusaga, Olaoluwa, Murdoch, Maureen, Sriram, Peruvemba, Yeh, Shing Shing, Tandon, Neeraj, Jhala, Darshana, Aguayo, Samuel, Cohen, David, Sharma, Satish, Liangpunsakul, Suthat, Oursler, Kris Ann, Whooley, Mary, Ahuja, Sunil, Constans, Joseph, Meyer, Paul, Greco, Jennifer, Rauchman, Michael, Servatius, Richard, Gaddy, Melinda, Wallbom, Agnes, Morgan, Timothy, Stapley, Todd, Sherman, Scott, Ross, George, Tsao, Philip, Strollo, Patrick, Boyko, Edward, Meyer, Laurence, Gupta, Samir, Huq, Mostaqul, Fayad, Joseph, Hung, Adriana, Lichy, Jack, Hurley, Robin, Robey, Brooks, Striker, Robert, Wray, Naomi R., Mattheisen, Manuel, Trzaskowski, Maciej, Byrne, Enda M., Abdellaoui, Abdel, Adams, Mark J., Agerbo, Esben, Air, Tracy M., Andlauer, Till F. M., Bacanu, Silviu-Alin, Bækvad-Hansen, Marie, Beekman, Aartjan T. F., Bigdeli, Tim B., Binder, Elisabeth B., Bryois, Julien, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Cai, Na, Castelao, Enrique, Christensen, Jane Hvarregaard, Clarke, Toni-Kim, Coleman, Jonathan R. I., Colodro-Conde, Lucía, Couvy-Duchesne, Baptiste, Craddock, Nick, Crawford, Gregory E., Davies, Gail, Degenhardt, Franziska, Derks, Eske M., Direk, Nese, Dolan, Conor V., Dunn, Erin C., Eley, Thalia C., Escott-Price, Valentina, Hassan Kiadeh, Farnush Farhadi, Finucane, Hilary K., Foo, Jerome C., Forstner, Andreas J., Frank, Josef, Gaspar, Héléna A., Gill, Michael, Goes, Fernando S., Gordon, Scott D., Weinsheimer, Shantel Marie, Wellmann, Jürgen, Willemsen, Gonneke, Witt, Stephanie H., Wu, Yang, Xi, Hualin S., Yang, Jian, Zhang, Futao, Arolt, Volker, Baune, Bernhard T., Berger, Klaus, Boomsma, Dorret I., Cichon, Sven, Dannlowski, Udo, de Geus, E. J. C., DePaulo, J. Raymond, Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Grabe, Hans J., Hamilton, Steven P., Grove, Jakob, Hall, Lynsey S., Hansen, Christine Søholm, Hansen, Thomas F., Herms, Stefan, Hickie, Ian B., Hoffmann, Per, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Hougaard, David M., Howard, David M., Ising, Marcus, Jansen, Rick, Jones, Ian, Jones, Lisa A., Jorgenson, Eric, Knowles, James A., Kohane, Isaac S., Kraft, Julia, Kretzschmar, Warren W., Kutalik, Zoltán, Li, Yihan, Lind, Penelope A., MacIntyre, Donald J., MacKinnon, Dean F., Maier, Robert M., Maier, Wolfgang, Marchini, Jonathan, Mbarek, Hamdi, McGrath, Patrick, McGuffin, Peter, Medland, Sarah E., Mehta, Divya, Middeldorp, Christel M., Mihailov, Evelin, Milaneschi, Yuri, Milani, Lili, Mondimore, Francis M., Montgomery, Grant W., Mostafavi, Sara, Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nivard, Michel G., Nyholt, Dale R., O'Reilly, Paul F., Oskarsson, Hogni, Hayward, Caroline, Heath, Andrew C., Kendler, Kenneth S., Kloiber, Stefan, Lewis, Glyn, Li, Qingqin S., Lucae, Susanne, Madden, Pamela A. F., Magnusson, Patrik K., Martin, Nicholas G., McIntosh, Andrew M., Metspalu, Andres, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Nordentoft, Merete, O'Donovan, Michael C., Paciga, Sara A., Pedersen, Nancy L., Owen, Michael J., Painter, Jodie N., Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Peterson, Roseann E., Peyrot, Wouter J., Pistis, Giorgio, Posthuma, Danielle, Quiroz, Jorge A., Qvist, Per, Rice, John P., Riley, Brien P., Rivera, Margarita, Mirza, Saira Saeed, Schoevers, Robert, Schulte, Eva C., Shen, Ling, Shi, Jianxin, Shyn, Stanley I., Sigurdsson, Engilbert, Sinnamon, Grant C. B., Smit, Johannes H., Smith, Daniel J., Stefansson, Hreinn, Steinberg, Stacy, Streit, Fabian, Strohmaier, Jana, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Traylor, Matthew, Treutlein, Jens, Trubetskoy, Vassily, Uitterlinden, André G., Umbricht, Daniel, Van der Auwera, Sandra, van Hemert, Albert M., Viktorin, Alexander, Visscher, Peter M., Wang, Yunpeng, Webb, Bradley T., Penninx, Brenda W. J. 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F., Tsitsika A., Tyszkiewicz-Nwafor M., Tziouvas K., van Elburg A.A., van Furth E.F., Wade T.D., Wagner G., Walton E., Whiteman D.C., Wichmann H.E., Widen E., Yao S., Zeggini E., Zerwas S., Zipfel S., Jungkunz M., Dietl L., Schwarze C.E., Dahmen N., Schott B.H., Mobascher A., Crivelli S., Dennis M.F., Harvey P.D., Carter B.W., Huffman J.E., Jacobson D., Madduri R., Olsen M.K., Pestian J., Gaziano J.M., Muralidhar S., Ramoni R., Beckham J., Chang K.-M., O'Donnell C.J., Tsao P.S., Breeling J., Huang G., Romero J.P.C., Moser J., Whitbourne S.B., Brewer J.V., Aslan M., Connor T., Argyres D.P., Stephens B., Brophy M.T., Humphries D.E., Selva L.E., Do N., Shayan S., Cho K., Pyarajan S., Hauser E., Sun Y., Zhao H., Wilson P., McArdle R., Dellitalia L., Mattocks K., Harley J., Zablocki C.J., Whittle J., Jacono F., Gutierrez S., Gibson G., Hammer K., Kaminsky L., Villareal G., Kinlay S., Xu J., Hamner M., Mathew R., Bhushan S., Iruvanti P., Godschalk M., Ballas Z., Ivins D., Mastorides S., Moorman J., Gappy S., Klein J., Ratcliffe N., Florez H., Okusaga O., Murdoch M., Sriram P., Yeh S.S., Tandon N., Jhala D., Aguayo S., Cohen D., Sharma S., Liangpunsakul S., Oursler K.A., Whooley M., Ahuja S., Constans J., Meyer P., Greco J., Rauchman M., Servatius R., Gaddy M., Wallbom A., Morgan T., Stapley T., Sherman S., Ross G., Tsao P., Strollo P., Boyko E., Meyer L., Gupta S., Huq M., Fayad J., Hung A., Lichy J., Hurley R., Robey B., Striker R., Erlangsen A., Kessler R.C., Porteous D., Ursano R.J., Wasserman D., Coon H., Demontis D., Docherty A.R., Kuo P.-H., Mann J.J., Renteria M.E., Stein M.B., and Willour V.
Subjects: LD SCORE REGRESSION, Genome-wide association study, Suicide, Attempted, 3124 Neurology and psychiatry, 0302 clinical medicine, Risk Factors, Insomnia, Suicide attempt, GWAS, Suïcidi, Depression (differential diagnoses), Cause of death, Psychiatry, 0303 health sciences, Factors de risc en les malalties, Mental Disorders, Genetic Correlation, Genome-wide Association Study, Pleiotropy, Polygenicity, Suicide, Suicide Attempt, DEPRESSION, 3. Good health, Genetic correlation, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Depressive Disorder, Major, Mental illness, Cohort, SEX, medicine.symptom, Human, medicine.medical_specialty, Risk factors in diseases, BF, Locus (genetics), BEHAVIORS, Psykiatri, EVENTS, 03 medical and health sciences, SDG 3 - Good Health and Well-being, medicine, ddc:610, GENOME-WIDE ASSOCIATION, IDEATION, Socioeconomic status, METAANALYSIS, Biological Psychiatry, 030304 developmental biology, business.industry, Risk Factor, Genetic architecture, THOUGHTS, RC0321, business, Malalties mentals, 030217 neurology & neurosurgery
Abstract: Statistical analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org) hosted by SURFsara and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu), which is supported by the Office of Research Infrastructure of the National Institutes of Health (Grant Nos. S10OD018522 and S10OD026880). This work was conducted in part using the resources of the Advanced Computing Center for Research and Education at Vanderbilt University, Nashville, TN. This work was funded by the National Institutes of Health (Grant Nos. R01MH116269 and R01MH121455 [to DMR]), NIGMS of the National Institutes of Health (Grant No. T32GM007347 [to JK]), and the Brain & Behavior Research Foundation (NARSAD Young Investigator Award No. 29551 [to NM])., BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders., Office of Research Infrastructure of the National Institutes of Health S10OD018522 S10OD026880, United States Department of Health & Human Services, National Institutes of Health (NIH) - USA R01MH116269 R01MH121455, NIH National Institute of General Medical Sciences (NIGMS) T32GM007347 NARSAD 29551
Published: 2022
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39. Genome-wide association study identifies new locus associated with OCD

Author: Danielle Posthuma, Bernie Devlin, Edna Grünblatt, Ying Wang, Daniele Cusi, Stephan Ruhrmann, Steven A. Rasmussen, Michael S. Breen, Julia Klawohn, Ana Gabriela Hounie, Aline S. Sampaio, Cristina Barlassina, Marta Ribasés, Jackson G. Thorp, Cynthia M. Bulik, Marco A. Grados, Dan J. Stein, Abby Fyer, Vladimir Coric, Martha J. Falkenstein, Stephanie Le Hellard, Behrang Mahjani, Nathaniel McGregor, Homero Vallada, Miguel Casas, Laurent F. Thomas, Janice Krasnow, Abraham Reichenberg, Donald W. Black, Gwyneth Zai, Norbert Kathmann, Manuel Mattheisen, Nicholas G. Martin, Jason W. Krompinger, Josep Antoni Ramos-Quiroga, Judith Becker Nissen, Helga Ask, Damiaan Denys, Carolina Cappi, Euripedes Constantino Miguel, O. Joseph Bienvenu, Bengt T. Fundin, Lisa Osiecki, Karin J. H. Verweij, Paul Sandor, Jeremy Veenstra-VanderWeele, Maureen Mulhern, Sarah E. Medland, David M. Hougaard, Lauren Erdman, Jan Haavik, James L. Kennedy, Christopher P. Walker, Jurjen J. Luykx, Tim B. Bigdeli, Ian M. Hickie, Nienke Vulink, Maurizio Turiel, Peter Falkai, Enda M. Byrne, Valentina Ciullo, Daniel A. Geller, Liang Kung-Yee, Miriam A. Schiele, Lambertus Klei, Götz Berberich, Thomas Werge, Brion S. Maher, Christie L. Burton, Julia M. Sealock, Sandra Meier, Bernadette Cullen, Stephan Ripke, Dorothy E. Grice, Richard Delorme, Ted Reichborn-Kjennerud, Dongmei Yu, Danielle C. Cath, Lili Milani, Abdel Abdellaoui, Andres Metspalu, María Soler Artigas, Maria Conceição do Rosário, Ole Mors, Brian P. Brennan, Barbara E. Stranger, Ann E. Pulver, Nora I. Strom, Joseph D. Buxbaum, Hans J. Grabe, Jens R. Wendland, Michael H. Bloch, Srdjan Djurovic, Raquel Rabionet, Angel Carracedo, Carlos N. Pato, Erika L. Nurmi, Janet L. Sobell, Kevin S. O’Connell, Michael Wagner, David R. Rosenberg, Jonathan R. I. Coleman, Jeremiah M. Scharf, Kerry J. Ressler, Jaakko Kaprio, Edwin H. Cook, Scott L. Rauch, Federica Piras, Merete Nordentoft, Christian Rück, Fabrizio Piras, John-Anker Zwart, Jason A. Elias, Christopher Pittenger, Lea K. Davis, Margaret A. Richter, Evonne McArthur, Bendik S. Winsvold, Yin Yao, James J. Crowley, David L. Pauls, Rosa Bosch, Xavier Estivil, Matthew Halvorsen, Adrian Camarena, Nancy L. Pedersen, Pino Alonso, Eric A. Storch, Bjarne Hansen, Helena Brentani, James T. McCracken, Jan Maerten Smit, Donald Hucks, Alexandra Havdahl, Gerome Breen, Christina M. Hultman, Benjamin M. Neale, Gregory L. Hanna, Mikael Landén, Christine Lochner, Dirk J.A. Smit, Fabio Macciardi, Carol A. Mathews, Nuria Lanzagorta, Laura G. Sloofman, Cristina Rodriguez-Fontenla, Michael A. Jenike, Michele T. Pato, Marion Leboyer, Humberto Nicolini, Anders D. Børglum, Maria Cristina Cavallini, Wei Guo, Benjamin D. Greenberg, Maiken Elvestad Gabrielsen, Magdalena Janecka, Mark A. Riddle, Paul S. Nestadt, Beatriz Camarena, Valsamma Eapen, Susanne Walitza, Jack Samuels, Fernando S. Goes, Nicole C.R. McLaughlin, S. Evelyn Stewart, Jennifer Reichert, Sven Sandin, Gerd Kvale, Katharina Domschke, Ole A. Andreassen, Elles de Schipper, Paul D. Arnold, Kristi Krebs, Zachary Gerring, Teemu Palviainen, Kathleen D. Askland, Alfredo Ramirez, James A. Knowles, Laura Bellodi, Kristen Hagen, Julia Boberg, Thomas V. Fernandez, Gerald Nestadt, John Piacentini, Jakob Grove, Eske M. Derks, Preben Bo Mortensen, Elinor K. Karlsson, Gianfranco Spalletta, David Mataix-Cols, Katharina Bey, and Jonas Bybjerg-Grauholm
Subjects: Genetics, business.industry, Locus (genetics), Genome-wide association study, Single-nucleotide polymorphism, Heritability, behavioral disciplines and activities, humanities, Genetic architecture, Anorexia nervosa (differential diagnoses), mental disorders, medicine, Anxiety, SNP, medicine.symptom, business
Abstract: Obsessive-compulsive disorder (OCD) is a heritable disorder, but no definitive, replicated OCD susceptibility loci have yet been identified by any genome-wide association study (GWAS). Here, we report results from a GWAS in the largest OCD case-control sample (N = 14,140 OCD cases and N = 562,117 controls) to date. We explored the genetic architecture of OCD, including its genetic relationships to other psychiatric and non-psychiatric phenotypes. In the GWAS analysis, we identified one SNP associated with OCD at a genome-wide significant level. Subsequent gene-based analyses identified additional two genes as potentially implicated in OCD pathogenesis. All SNPs combined explained 16% of the heritability of OCD. We show sub-stantial positive genetic correlations between OCD and a range of psychiatric disorders, including anxiety disorders, anorexia nervosa, and major depression. We thus for the first time provide evidence of a genome-wide locus implicated in OCD and strengthen previous literature suggesting a polygenic nature of this disorder.
Published: 2021
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40. Discovery of shared genomic loci using the conditional false discovery rate approach

Author: Oleksandr Frei, Srdjan Djurovic, Chun Chieh Fan, Wesley K. Thompson, Olav B. Smeland, Alexey A. Shadrin, Dominic Holland, Kevin S. O’Connell, Shahram Bahrami, Anders M. Dale, and Ole A. Andreassen
Subjects: False discovery rate, Multifactorial Inheritance, Genetic correlation, Genetic overlap, Genome-wide association study, Single-nucleotide polymorphism, Computational biology, Biology, Polymorphism, Single Nucleotide, 03 medical and health sciences, Bayes' theorem, Genetics, Humans, SNP, Genetic Predisposition to Disease, Conditional false discovery rate, Genetics (clinical), 030304 developmental biology, Pleiotropy, 0303 health sciences, 030305 genetics & heredity, Genomics, Polygenic architecture, Human genetics, Phenotype, Genome-Wide Association Study
Abstract: In recent years, genome-wide association study (GWAS) sample sizes have become larger, the statistical power has improved and thousands of trait-associated variants have been uncovered, offering new insights into the genetic etiology of complex human traits and disorders. However, a large fraction of the polygenic architecture underlying most complex phenotypes still remains undetected. We here review the conditional false discovery rate (condFDR) method, a model-free strategy for analysis of GWAS summary data, which has improved yield of existing GWAS and provided novel findings of genetic overlap between a wide range of complex human phenotypes, including psychiatric, cardiovascular, and neurological disorders, as well as psychological and cognitive traits. The condFDR method was inspired by Empirical Bayes approaches and leverages auxiliary genetic information to improve statistical power for discovery of single-nucleotide polymorphisms (SNPs). The cross-trait condFDR strategy analyses separate GWAS data, and leverages overlapping SNP associations, i.e., cross-trait enrichment, to increase discovery of trait-associated SNPs. The extension of the condFDR approach to conjunctional FDR (conjFDR) identifies shared genomic loci between two phenotypes. The conjFDR approach allows for detection of shared genomic associations irrespective of the genetic correlation between the phenotypes, often revealing a mixture of antagonistic and agonistic directional effects among the shared loci. This review provides a methodological comparison between condFDR and other relevant cross-trait analytical tools and demonstrates how condFDR analysis may provide novel insights into the genetic relationship between complex phenotypes. acceptedVersion
Published: 2019
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41. 77. BIPOLAR DISORDER IS CHARACTERISED BY STOICHIOMETRIC IMBALANCE OF GENE EXPRESSION IN THE FRONTAL CORTEX

Author: Asbjorn Holmgren, Kevin S O'Connell, Srdjan Djurovic, and Timothy Hughes
Subjects: Pharmacology, Psychiatry and Mental health, Neurology, Pharmacology (medical), Neurology (clinical), Biological Psychiatry
Published: 2022
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42. Genome-wide association analysis reveals extensive genetic overlap between mood instability and psychiatric disorders but divergent patterns of genetic effects

Author: Margrethe Collier Høegh, Trine Vik Lagerberg, Weiqiu Cheng, Alexey A. Shadrin, Olav B. Smeland, Linn Rødevand, Naz Karadag, Oleksandr Frei, Chun Chieh Fan, Kevin S. O’Connell, Srdjan Djurovic, Guy Hindley, Zillur Rahman, Shahram Bahrami, Aihua Lin, Anders M. Dale, and Ole A. Andreassen
Subjects: False discovery rate, medicine.medical_specialty, Biology, medicine.disease, Genetic correlation, Mood, Schizophrenia, mental disorders, medicine, Bipolar disorder, Psychiatry, Synapse organization, Depression (differential diagnoses), Genetic association
Abstract: Mood instability (MOOD) is a transdiagnostic phenomenon with a prominent neurobiological basis. Recent genome-wide association studies found significant positive genetic correlation between MOOD and major depression (DEP) and weak correlations with other psychiatric disorders. We investigated the polygenic overlap between MOOD and psychiatric disorders beyond genetic correlation to better characterize putative shared genetic determinants. Summary statistics for schizophrenia (SCZ, n=105,318), bipolar disorder (BIP, n=413,466), DEP (n=450,619), attention-deficit hyperactivity disorder (ADHD, n=53,293) and MOOD (n=363,705), were analysed using the bivariate causal mixture model and conjunctional false discovery rate methods to estimate the proportion of shared variants influencing MOOD and each disorder, and identify jointly associated genomic loci. MOOD correlated positively with all psychiatric disorders, but with wide variation in strength (rg=0.10-0.62). Of 10.4K genomic variants influencing MOOD, 4K-9.4K were estimated to influence psychiatric disorders. MOOD was jointly associated with DEP at 163 loci, SCZ at 110, BIP at 60 and ADHD at 25, with consistent genetic effects in independent samples. Fifty-three jointly associated loci were overlapping across two or more disorders (transdiagnostic), seven of which had discordant effect directions on psychiatric disorders. Genes mapped to loci associated with MOOD and all four disorders were enriched in a single gene-set, “synapse organization”. The extensive polygenic overlap indicates shared molecular underpinnings across MOOD and psychiatric disorders. However, distinct patterns of genetic correlation and effect directions of shared loci suggest divergent effects on corresponding neurobiological mechanisms which may relate to differences in the core clinical features of each disorder.
Published: 2021
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43. Increased circulating IL-18 levels in severe mental disorders indicate systemic inflammasome activation

Author: Terje Nærland, Attila Szabo, Kjetil Sørensen, Margrethe Collier Høegh, Ingrid Agartz, Gunnar Morken, Torbjørn Elvsåshagen, Mashhood Ahmed Sheikh, Vidar M. Steen, Pål Aukrust, Ole A. Andreassen, Ole Kristian Drange, Thor Ueland, Rune A. Kroken, John Abel Engh, Ingrid Melle, Srdjan Djurovic, Tove Lekva, Sigrun Hope, Melissa Auten Weibell, Nils Eiel Steen, Birgitte Boye, Dimitrios Andreou, Erlend Bøen, Lars T. Westlye, Kevin S. O’Connell, Kirsten Wedervang-Resell, Trine Vik Lagerberg, Inge Joa, Ulrik Fredrik Malt, and Erik Johnsen
Subjects: Psychosis, business.industry, Inflammasome, medicine.disease, Pathophysiology, NLRC4, Schizophrenia, Immunology, medicine, Interleukin 18, Bipolar disorder, business, Dyslipidemia, medicine.drug
Abstract: BackgroundSchizophrenia (SCZ) and bipolar disorder (BD) are severe mental illnesses (SMI) that are part of a psychosis continuum, and dysregulated innate immune responses have been suggested to be involved in their pathophysiology. However, disease-specific immune mechanisms in SMI are not known yet. Recently, dyslipidemia has been linked to systemic inflammasome activation, and elevated atherogenic lipid ratios have been shown to correlate with circulating levels of inflammatory biomarkers in SMI. It is, however, not yet known if increased systemic cholesterol load leads to inflammasome activation in these patients.MethodsWe tested the hypothesis that patients with SCZ and BD display higher circulating levels compared to healthy individuals of key members of the IL-18 system using a large patient cohort (n=1632; including 737 SCZ and 895 BD), and healthy controls (CTRL; n=1070). In addition, we assessed associations with coronary artery disease risk factors in SMI, focusing on relevant inflammasome-related, neuroendocrine, and lipid markers.ResultsWe report higher baseline levels of circulating IL-18 system components (IL-18, IL-18BPA) as well as increased expression of inflammasome-related genes (NLRP3 and NLRC4) in the blood of patients relative to CTRL. We demonstrate a cholesterol dyslipidemia pattern in psychotic disorders, and report correlations between levels of blood cholesterol species and the expression of inflammasome system elements in SMI.ConclusionsBased on these results, we suggest a link between systemic inflammasome activation/dysregulation and cholesterol load in SMI. Our findings further the understanding of possible underlying inflammatory and metabolic mechanisms and may expose important therapeutic targets in SMI.
Published: 2021
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44. Genetic contributions to bipolar disorder: current status and future directions

Author: Brandon J. Coombes and Kevin S. O’Connell
Subjects: medicine.medical_specialty, Multifactorial Inheritance, Future studies, Bipolar Disorder, Population, Psychological intervention, Mood disorder, Comorbidity, Biology, psychiatric genetics, 03 medical and health sciences, 0302 clinical medicine, medicine, Humans, Bipolar disorder, Psychiatry, education, Applied Psychology, Psychiatric genetics, 030304 developmental biology, 0303 health sciences, education.field_of_study, Invited Review, affective disorder, medicine.disease, Biobank, Genetic architecture, Health equity, Psychiatry and Mental health, Psychotic Disorders, Pharmacogenetics, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Bipolar disorder (BD) is a highly heritable mental disorder and is estimated to affect about 50 million people worldwide. Our understanding of the genetic etiology of BD has greatly increased in recent years with advances in technology and methodology as well as the adoption of international consortiums and large population-based biobanks. It is clear that BD is also highly heterogeneous and polygenic and shows substantial genetic overlap with other psychiatric disorders. Genetic studies of BD suggest that the number of associated loci is expected to substantially increase in larger future studies and with it, improved genetic prediction of the disorder. Still, a number of challenges remain to fully characterize the genetic architecture of BD. First among these is the need to incorporate ancestrally-diverse samples to move research away from a Eurocentric bias that has the potential to exacerbate health disparities already seen in BD. Furthermore, incorporation of population biobanks, registry data, and electronic health records will be required to increase the sample size necessary for continued genetic discovery, while increased deep phenotyping is necessary to elucidate subtypes within BD. Lastly, the role of rare variation in BD remains to be determined. Meeting these challenges will enable improved identification of causal variants for the disorder and also allow for equitable future clinical applications of both genetic risk prediction and therapeutic interventions.
Published: 2021

45. Characterization of Age and Polarity at Onset in Bipolar Disorder

Author: Aiden Corvin, Maria Grigoroiu-Serbanescu, Mark Hyman Rapaport, Frederike T. Fellendorf, Urs Heilbronner, Mariam M. Al Eissa, John J Nurnberger, Claire O'Donovan, Claire Slaney, Mark A. Frye, Niamh L. O'Brien, Roland Hasler, Michael John Owen, Michael Conlon O'Donovan, Farah Klöhn-Saghatolislam, Markus M. Nöthen, Scott R. Clark, Mikael Landén, Lina Jonsson, Peter Falkai, Qingqin S. Li, Alessio Squassina, Simon Schmitt, Gustavo Turecki, Heike Anderson-Schmidt, Jonathan Repple, Sofie R. Aminoff, Eduard Vieta, Katherine Gordon-Smith, Stéphane Jamain, William Byerley, Hélène Richard-Lepouriel, Fermín Mayoral, Francis J. McMahon, Marin Veldic, Ingrid Melle, Andrew McQuillin, Nicholas Bass, Gloria Roberts, Douglas M. Ruderfer, John B. Vincent, Nelson B. Freimer, Kirov George, Wei Xu, Susan L. McElroy, Ceylan Balaban, Marco P. Boks, Franziska Degenhardt, Paul E. Croarkin, Wade H. Berrettini, Piotr M. Czerski, Fernando S. Goes, Peter P. Zandi, Sabrina K. Schaupp, Barbara W. Schweizer, Andrew M. McIntosh, Marcella Rietschel, Helena Pelin, Evelyn J. Bromet, Marion Leboyer, Ole A. Andreassen, Georgia Panagiotaropoulou, Alessia Fiorentino, Sally I. Sharp, Torbjørn Elvsåshagen, Kristina Adorjan, Monika Budde, Lisa Jones, Thomas G. Schulze, Vihra Milanova, Janos Kalman, Tim B. Bigdeli, Esther Jiménez, Abigail Ortiz, Dolores Malaspina, Kevin S. O’Connell, Sergi Papiol, Mario Maj, Tim Hahn, Frederike Stein, Jordan W. Smoller, Tomas Novak, Katrin Gade, J. Raymond DePaulo, Sarah Kittel-Schneider, Julia-Katharina Pfarr, Martin Alda, James A. Knowles, Sven Cichon, David Craig, Eli A. Stahl, William A. Scheftner, Bruno Etain, Annabel Vreeker, Guy A. Rouleau, Stephan Ripke, Clement C. Zai, Frank Bellivier, Giovanni Severino, Palmiero Monteleone, Ian Jones, Bertram Müller-Myhsok, Mark Adams, John Strauss, Philip B. Mitchell, Andreas Reif, Fabian Streit, Roel A. Ophoff, James L. Kennedy, Nils Opel, Raffaella Ardau, Paul Grof, Peter R. Schofield, Susanne Bengesser, Maria Hake, Loes M. Olde Loohuis, Joanna Pawlak, Daniela Reich-Erkelenz, Ingrid Agartz, Maria Del Zompo, Antonio Benabarre, Bernhard T. Baune, Arianna Di Florio, Ashley L. Comes, Michael Gill, Cristiana Cruceanu, Susanne Meinert, William Coryell, Alessio Maria Monteleone, Fanny Senner, Trine Vik Lagerberg, Jose Guzman-Parra, Erik Pålsson, Elliot S. Gershon, Melvin G. McInnis, Pavla Stopkova, Nikolaos Koutsouleris, René S. Kahn, Janice M. Fullerton, Howard J. Edenberg, Tilo Kircher, Nina Dalkner, Udo Dannlowski, Rolf Adolfsson, Alfonso Tortorella, Jean-Michel Aubry, James B. Potash, Catina Chillotti, Eva Z. Reininghaus, Janet L. Sobell, Thorsten M. Kranz, Tina Meller, Ayman H. Fanous, Kai Ringwald, K Oliver Schubert, Andreas J. Forstner, Till F. M. Andlauer, Helena Medeiros, Mirko Manchia, Joanna M. Biernacka, Katharina Brosch, Julie Garnham, Olav B. Smeland, Eva C. Schulte, Carlos N. Pato, Nicholas John Craddock, Srdjan Djurovic, Pablo Cervantes, Michele T. Pato, John R. Kelsoe, Claudia Pisanu, Joanna Twarowska-Hauser, and William Lawson
Subjects: 0303 health sciences, medicine.medical_specialty, business.industry, Genome-wide association study, Disease, Heritability, medicine.disease, Genetic architecture, 03 medical and health sciences, 0302 clinical medicine, Autism spectrum disorder, Schizophrenia, Internal medicine, medicine, Bipolar disorder, business, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract: BackgroundStudying the phenotypic and genetic characteristics of age and polarity at onset (AAO, PAO) in bipolar disorder (BD) can provide new insights into disease pathology and facilitate the development of screening tools.AimsTo examine the genetic architecture of AAO and PAO and their association with BD disease characteristics.MethodsGenome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (N=12977) and PAO (N=6773) were conducted in BD patients of 34 cohorts and a replication sample (N=2237). The association of onset with disease characteristics was investigated in two of these cohorts.ResultsEarlier AAO was associated with an increased risk of psychotic symptoms, suicidality, and fewer episodes. A depressive onset correlated with lifetime suicidality and a manic onset with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in SNV-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased polygenic scores for autism spectrum disorder (β=-0.34 years, SE=0.08), major depression (β=-0.34 years, SE=0.08), schizophrenia (β=-0.39 years, SE=0.08), and educational attainment (β=-0.31 years, SE=0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.ConclusionsAAO and PAO are associated with indicators of BD severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents, and phenotype definitions introduce significant heterogeneity, affecting analyses.RELEVANCE STATEMENTIn the largest study to systematically characterize age at onset (N=12977) and polarity at onset (N=6773) in bipolar disorder, we describe an association between illness onset characteristics and indicators of severity, confirming their clinical relevance. Our study shows that that early illness onset is associated with genetic liability for a broad range of psychiatric disorders. However, we also highlight systematic differences in age at onset across cohorts, continents, and phenotype definitions. This heterogeneity results in reduced heritability and affects genetic analyses, underscoring the need for the development of standardized phenotype definitions.
Published: 2021
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46. Dose-dependent transcriptional effects of lithium and adverse effect burden in a psychiatric cohort

Author: Olav B. Smeland, Ibrahim Akkouh, Nils Eiel Steen, Lavinia Athanasiu, Timothy P. Hughes, Ole A. Andreassen, Vidar M. Steen, Srdjan Djurovic, Kevin S. O’Connell, Hans-Richard Brattbakk, Florian Krull, and Francesco Bettella
Subjects: Oncology, medicine.medical_specialty, Bipolar Disorder, Lithium (medication), Nausea, Gene Expression, CAMK1D, Lithium, Cohort Studies, Interviews as Topic, Internal medicine, medicine, Humans, Bipolar disorder, Adverse effect, Biological Psychiatry, Whole blood, Pharmacology, Microarray analysis techniques, business.industry, GTPase-Activating Proteins, medicine.disease, Calcium-Calmodulin-Dependent Protein Kinase Type 1, Case-Control Studies, Cohort, medicine.symptom, business, medicine.drug, Antipsychotic Agents
Abstract: Lithium is the first-line treatment for bipolar disorder (BD), but there is a large variation in response rate and adverse effects. Although the molecular effects of lithium have been studied extensively, the specific mechanisms of action remain unclear. In particular, the molecular changes underlying lithium adverse effects are little known. Multiple linear regression analyses of lithium serum concentrations and global gene expression levels in whole blood were carried out using a large case-control sample (n = 1450). Self-reported adverse effects of lithium were assessed with the “Udvalg for Kliniske Undersøgelser” (UKU) adverse effect rating scale, and regression analysis was used to identify significant associations between lithium-related genes and six of the most common adverse effects. Serum concentrations of lithium were significantly associated with the expression levels of 52 genes (FDR < 0.01), largely replicating previous results. We found 32 up-regulated genes and 20 down-regulated genes in lithium users compared to non-users. The down-regulated gene set was enriched for several processes related to the translational machinery. Two adverse effects were significantly associated (p < 0.01) with three or more lithium-associated genes: tremor (FAM13A-AS1, FAR2, ITGAX, RWDD1, and STARD10) and xerostomia (ANKRD13A, FAR2, RPS8, and RWDD1). The adverse effect association with the largest effect was between CAMK1D expression and nausea/vomiting. These results suggest putative transcriptional mechanisms that may predict lithium adverse effects, and could thus have a large potential for informing clinical practice. publishedVersion
Published: 2021

47. TU61. INVESTIGATING THE SHARED GENETIC DETERMINANTS OF MIGRAINE AND MENTAL DISORDERS BEYOND GENETIC CORRELATION

Author: Anders M. Dale, Ketil Joachim Ødegaard, Hautakangas H, Oleksandr Frei, Kevin S. O’Connell, Guy Hindley, Shahram Bahrami, Ole A. Andreassen, Matti J Pirenen, Francesco Bettella, Alexey A. Shadrin, Linn Rødevand, Olav B. Smeland, Srdjan Djurovic, and Bendik S. Winsvold
Subjects: Pharmacology, Psychiatry and Mental health, Neurology, Migraine, business.industry, Medicine, Pharmacology (medical), Neurology (clinical), business, medicine.disease, Genetic correlation, Biological Psychiatry, Clinical psychology
Published: 2021
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48. Genome-wide association study identifies 48 common genetic variants associated with handedness

Author: Inês Barroso, Gail Davies, H.-Erich Wichmann, Bjarke Feenstra, Peter Vollenweider, Nicholas J. Timpson, Alan F. Wright, Frank Geller, Gérard Waeber, John M. Starr, Benjamin M. Neale, George Davey Smith, Tõnu Esko, Ruth J. F. Loos, Andrew A. Hicks, Pedro Marques-Vidal, Dorret I. Boomsma, Harry Campbell, Zoltán Kutalik, David M. Evans, Scott D. Gordon, Eva Albrecht, Peter P. Pramstaller, Leena Peltonen, Jing Hua Zhao, Lavinia Paternoster, Thomas Hansen, Massimo Mangino, Fazil Aliev, Beate St Pourcain, Panos Deloukas, Heather A. Boyd, Guillaume Paré, Marco P. Boks, Monique M.B. Breteler, Jouke-Jan Hottenga, Xin Li, Kari Stefansson, Ian J. Deary, Jari Lahti, Inga Prokopenko, Nicholas Eriksson, Lili Milani, Nicholas J. Wareham, Jordan W. Smoller, Norman Klopp, Lynn Cherkas, Reedik Mägi, Margaret J. Wright, Peter Kraft, Jacques S. Beckmann, Brenda W.J.H. Penninx, Gabriel Cuellar-Partida, André G. Uitterlinden, Fernando Rivadeneira, Wendy L. McArdle, Johan G. Eriksson, Jiali Han, Jennifer E. Huffman, Andres Metspalu, J.M. Vink, Frank J. A. van Rooij, Christian Gieger, M. Arfan Ikram, Cecilia M. Lindgren, Aarno Palotie, Daniel I. Chasman, Joyce Y. Tung, Liang-Dar Hwang, David A. Hinds, Elisabeth Widen, Caroline Hayward, Michelle Luciano, Johannes H. Smit, Gonneke Willemsen, Dale R. Nyholt, Carolina Medina-Gomez, Nicole M. Warrington, Teemu Palviainen, Stacy Steinberg, Kay-Tee Khaw, Kevin S. O’Connell, Bettina Konte, Gudmar Thorleifsson, Eco J. C. de Geus, John P. Kemp, Mads Melbye, Mark I. McCarthy, Sarah E. Medland, Jaakko Kaprio, Cameron D. Palmer, Joel N. Hirschhorn, Ina Giegling, Scott Melville, Thomas Werge, Nicole Soranzo, Sigurdur H. Magnusson, Maris Teder-Laving, Hreinn Stefansson, Kauko Heikkilä, Cornelia M. van Duijn, David L. Duffy, Samuli Ripatti, Igor Rudan, Annette M. Hartmann, Ole A. Andreassen, Mari Nelis, Ozren Polasek, Vincent Mooser, Mousheng Xu, Eero Vuoksimaa, Katri Räikkönen, Nicholas G. Martin, Dan Rujescu, Tim D. Spector, Dawn M. Waterworth, Danielle M. Dick, Roel A. Ophoff, Epidemiology, Internal Medicine, Psychiatry, Biological Psychology, APH - Mental Health, APH - Methodology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Epidemiology and Data Science, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Pediatric surgery, and APH - Digital Health
Subjects: Male, Netherlands Twin Register (NTR), Linkage disequilibrium, Genome-wide association study, LANGUAGE DOMINANCE, Functional Laterality, Linkage Disequilibrium, Behavioral Neuroscience, 0302 clinical medicine, ddc:150, Gene Frequency, SCHIZOPHRENIA, Genetics, 0303 health sciences, Middle Aged, genetics [Genetic Variation], genetics [Functional Laterality], Schizophrenia, ASYMMETRY, genetics [Polymorphism, Single Nucleotide], Female, Adult, Social Psychology, LATERALIZATION, Experimental and Cognitive Psychology, genetics [Genetic Loci], Biology, Quantitative trait locus, Genetic correlation, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, LINKAGE ANALYSIS, METAANALYSIS, MICROTUBULE, AUTISM, ORIGINS, SCREEN, Quantitative Trait, Heritable, Sex Factors, Genetic linkage, medicine, Humans, Bipolar disorder, 030304 developmental biology, Genetic association study, Aged, Genetic Variation, medicine.disease, Genetic Loci, Autism, genetics [Gene Frequency], Developmental Psychopathology, 030217 neurology & neurosurgery, Neuroscience, Genome-Wide Association Study
Abstract: Handedness, a consistent asymmetry in skill or use of the hands, has been studied extensively because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and 32 studies from the International Handedness Consortium, we conducted the world’s largest genome-wide association study of handedness (1,534,836 right-handed, 194,198 (11.0%) left-handed and 37,637 (2.1%) ambidextrous individuals). We found 41 genetic loci associated with left-handedness and seven associated with ambidexterity at genome-wide levels of significance (P < 5×10−8). Tissue enrichment analysis implicated the central nervous system and brain tissues including the hippocampus and cerebrum in the etiology of left-handedness. Pathways including regulation of microtubules, neurogenesis, axonogenesis and hippocampus morphology were also highlighted. We found suggestive positive genetic correlations between being left-handed and some neuropsychiatric traits including schizophrenia and bipolar disorder. SNP heritability analyses indicated that additive genetic effects of genotyped variants explained 5.9% (95% CI = 5.8% – 6.0%) of the underlying liability of being left-handed, while the narrow sense heritability was estimated at 12% (95% CI = 7.2% – 17.7%). Further, we show that genetic correlation between left-handedness and ambidexterity is low (rg = 0.26; 95% CI = 0.08 – 0.43) implying that these traits are largely influenced by different genetic mechanisms. In conclusion, our findings suggest that handedness, like many other complex traits is highly polygenic, and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders that has been observed in multiple observational studies.
Published: 2021
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49. Extensive bidirectional genetic overlap between bipolar disorder and cardiovascular disease phenotypes

Author: Shahram Bahrami, Olav B. Smeland, Kevin S. O’Connell, Torbjørn Elvsåshagen, Oleksandr Frei, Anders M. Dale, Alexey A. Shadrin, Linn Rødevand, Guy Hindley, Trine Vik Lagerberg, Srdjan Djurovic, Yunhan Chu, Nils Eiel Steen, and Ole A. Andreassen
Subjects: 0301 basic medicine, Bipolar Disorder, genetic structures, Genome-wide association study, Neurosciences. Biological psychiatry. Neuropsychiatry, Disease, macromolecular substances, Biology, Predictive markers, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Polymorphism (computer science), medicine, Genetic predisposition, Humans, Genetic Predisposition to Disease, cardiovascular diseases, Bipolar disorder, Biological Psychiatry, Genetic association, 2. Zero hunger, Genetics, medicine.disease, Personalized medicine, Comorbidity, 3. Good health, Psychiatry and Mental health, Phenotype, 030104 developmental biology, Cardiovascular Diseases, Genetic Loci, Psychiatric disorders, Body mass index, 030217 neurology & neurosurgery, Genome-Wide Association Study, RC321-571
Abstract: Patients with bipolar disorder (BIP) have a high risk of cardiovascular disease (CVD), despite considerable individual variation. The mechanisms underlying comorbid CVD in BIP remain largely unknown. We investigated polygenic overlap between BIP and CVD phenotypes, including CVD risk factors and coronary artery disease (CAD). We analyzed large genome-wide association studies of BIP (n = 51,710) and CVD phenotypes (n = 159,208–795,640), using bivariate causal mixture model (MiXeR), which estimates the total amount of shared genetic variants, and conjunctional false discovery rate (FDR), which identifies specific overlapping loci. MiXeR revealed polygenic overlap between BIP and body mass index (BMI) (82%), diastolic and systolic blood pressure (20–22%) and CAD (11%) despite insignificant genetic correlations. Using conjunctional FDR n = 69), systolic (n = 53), and diastolic (n = 53) blood pressure, of which 22 are novel BIP loci. There was a pattern of mixed effect directions of the shared loci between BIP and CVD phenotypes. Functional analyses indicated that the shared loci are linked to brain-expressed genes and involved in neurodevelopment, lipid metabolism, chromatin assembly/disassembly and intracellular processes. Altogether, the study revealed extensive polygenic overlap between BIP and comorbid CVD, implicating shared molecular genetic mechanisms. The mixed effect directions of the shared loci suggest variation in genetic susceptibility to CVD across BIP subgroups, which may underlie the heterogeneity of CVD comorbidity in BIP patients. The findings suggest more focus on targeted lifestyle interventions and personalized pharmacological treatment to reduce CVD comorbidity in BIP.
Published: 2021

50. Using iPSC Models to Understand the Role of Estrogen in Neuron–Glia Interactions in Schizophrenia and Bipolar Disorder

Author: Ibrahim Akkouh, Denis Reis de Assis, Srdjan Djurovic, Attila Szabo, Francesca Puppo, Ole A. Andreassen, Jordi Requena Osete, Kevin S. O’Connell, Timothy P. Hughes, and Evgeniia Frei
Subjects: 0301 basic medicine, Cell signaling, neuron–glia interactions, Induced Pluripotent Stem Cells, Review, Cell Communication, Biology, Models, Biological, drug target, 03 medical and health sciences, 0302 clinical medicine, pathophysiological mechanisms, medicine, estrogen, Animals, Humans, Bipolar disorder, Induced pluripotent stem cell, lcsh:QH301-705.5, Neuroinflammation, bipolar disorder, Neurons, brain organoids, Estrogens, General Medicine, Human brain, medicine.disease, 3. Good health, schizophrenia, iPS cells, 030104 developmental biology, medicine.anatomical_structure, lcsh:Biology (General), Schizophrenia, in vitro model, Neuron, Age of onset, Neuroscience, Neuroglia, 030217 neurology & neurosurgery
Abstract: Schizophrenia (SCZ) and bipolar disorder (BIP) are severe mental disorders with a considerable disease burden worldwide due to early age of onset, chronicity, and lack of efficient treatments or prevention strategies. Whilst our current knowledge is that SCZ and BIP are highly heritable and share common pathophysiological mechanisms associated with cellular signaling, neurotransmission, energy metabolism, and neuroinflammation, the development of novel therapies has been hampered by the unavailability of appropriate models to identify novel targetable pathomechanisms. Recent data suggest that neuron–glia interactions are disturbed in SCZ and BIP, and are modulated by estrogen (E2). However, most of the knowledge we have so far on the neuromodulatory effects of E2 came from studies on animal models and human cell lines, and may not accurately reflect many processes occurring exclusively in the human brain. Thus, here we highlight the advantages of using induced pluripotent stem cell (iPSC) models to revisit studies of mechanisms underlying beneficial effects of E2 in human brain cells. A better understanding of these mechanisms opens the opportunity to identify putative targets of novel therapeutic agents for SCZ and BIP. In this review, we first summarize the literature on the molecular mechanisms involved in SCZ and BIP pathology and the beneficial effects of E2 on neuron–glia interactions. Then, we briefly present the most recent developments in the iPSC field, emphasizing the potential of using patient-derived iPSCs as more relevant models to study the effects of E2 on neuron–glia interactions. publishedVersion
Published: 2021

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