Kevin Sean O'Connell

• Kopal, Jakub; Bakken, N. R.; Parekh, Pravesh; Shadrin, Alexey; Jaholkowski, Piotr Pawel & Ystaas, L. A. R. [Show all 14 contributors for this article] (2026). Early-childhood temperament trajectories map onto transdiagnostic psychiatric risk. Molecular Psychiatry. ISSN 1359-4184. doi: 10.1038/s41380-026-03881-0. Full text in Research Archive
• Ystaas, Lars A.R.; Parekh, Pravesh; Parker, Nadine; Akkouh, Ibrahim Ahmed; Birkenæs, Viktoria & Sønderby, Ida Elken [Show all 12 contributors for this article] (2026). Genetic liability to addiction underlies comorbid bipolar and substance use disorders. Biological Psychiatry. ISSN 0006-3223. doi: 10.1016/j.biopsych.2026.08.008. Full text in Research Archive
• Koch, Elise; Parker, Nadine; Mohammad, Helin; Lenk, Hasan Cagin; Ystaas, Lars Andreas Rømo & Jaholkowski, Piotr Pawel [Show all 13 contributors for this article] (2026). Genetic overlap between treatment-resistant schizophrenia and smoking initiation. International Journal of Neuropsychopharmacology. ISSN 1461-1457. 29(7). doi: 10.1093/ijnp/pyag035. Full text in Research Archive Show summary

  Background Early detection of treatment-resistant schizophrenia (TRS) is of substantial clinical importance. While TRS is heritable, the associated genetic variants have been difficult to identify. Cigarette smoking is associated with non-response to antipsychotics, and smoking behavior and schizophrenia have a shared genetic basis. Thus, TRS may also have a shared genetic basis with smoking behavior. Objective Here, we aim to identify genetic variants associated with TRS by leveraging overlapping genetic variants with smoking initiation to increase statistical power. Methods We analyzed genome-wide data for TRS and smoking initiation with the conditional/conjunctional false discovery rate (cond/conjFDR) to identify shared loci, and LD score regression to determine genetic correlations. To investigate potential causal effects of shared loci, we performed Mendelian randomization analyses. Shared loci were mapped to genes, which were further investigated for enrichment of drug target genes. Results We observed a significant positive genetic correlation between TRS and smoking initiation (rg = 0.47 P = .0002). Leveraging the genetic overlap between TRS and smoking initiation, we identified four novel loci jointly associated with TRS and smoking initiation. The condFDR results improved polygenic prediction of TRS. Mendelian randomization indicates putative evidence for a causal effect of genetic liability to TRS on smoking initiation. The functional genetic analyses suggest that alpha-1-adrenergic receptors may be involved in the pathophysiology of TRS and possibly related to the efficacy of clozapine versus other antipsychotic drugs. Conclusion In conclusion, our results show that shared genetic mechanisms influence both TRS and smoking behavior, which provide new insights into the biological underpinnings of TRS.

• Muntané, Gerard; Shadrin, Alexey; Guardiola-Ripoll, M.; O'Connell, Kevin Sean; Frei, Oleksandr & Nærland, Terje [Show all 8 contributors for this article] (2026). Genetic overlap and shared risk loci between autism spectrum disorder and cardiometabolic traits. Molecular Psychiatry. ISSN 1359-4184. doi: 10.1038/s41380-026-03563-x. Full text in Research Archive Show summary

  Autism spectrum disorder (ASD) is a neurodevelopmental condition affecting 2% of the global population. Beyond core symptoms such as social communication deficits and repetitive behaviors, individuals with ASD are at increased risk of cardiometabolic comorbidities, including obesity, diabetes, and cardiovascular disease. Here, we investigate the shared genetic architecture between ASD and cardiometabolic traits using large genome-wide association studies datasets and advanced statistical approaches: the bivariate causal mixture (MiXeR) model and pleiotropy-informed conditional false discovery rate (pleioFDR). Our results show significant polygenic overlap between ASD and several cardiometabolic phenotypes, despite almost negligible genetic correlation between the traits. Specifically, we observed positive genetic correlations within the shared component for ASD and metabolic traits, such as body mass index (rg=0.03), type 2 diabetes (rg=0.23), and total cholesterol (rg=0.78). In contrast, negative correlations emerged between ASD and cardiovascular traits, including diastolic and systolic blood pressure (rg = -0,22, for both), pulse pressure (rg = -0.25), and coronary artery disease (rg = -0.90). Finally, we identified 100 shared loci between ASD and cardiometabolic traits, mapping to 124 genes and suggesting shared biological mechanisms underlying these phenotypes and pointing to potential therapeutic targets. Shared loci between ASD and metabolic traits predominantly showed concordant effects, whereas those overlapping with cardiovascular traits—particularly blood pressure–related traits—tended to exhibit discordant effects. Together, these findings deepen our understanding of the biological connections between ASD and cardiometabolic comorbidities and may help inform more personalized strategies for managing ASD and its associated long-term health risks.

• Holen, Børge; Rahman, Mohammad Zillur; Shadrin, Alexey; Icick, Romain; O'Connell, Kevin Sean & Rødevand, Linn [Show all 14 contributors for this article] (2026). Shared genetic variants across substance use disorders implicate common neurobiological pathways, a genome‐wide mixed methods study. BMJ General Psychiatry (GPSYCH). ISSN 2096-5923. 39(2). doi: 10.1002/gps3.70017. Full text in Research Archive Show summary

  ABSTRACT Background Substance use disorders (SUDs) are highly heritable, but the extent of shared and distinct genetic architecture across different SUDs is unclear. Aims To compare the genetic architectures of alcohol use disorder (AUD), cannabis use disorder (CUD) and opioid use disorder (OUD) and to identify shared and unique genetic loci. Methods We analysed large‐scale genome‐wide association study (GWAS) summary statistics from individuals of European ancestry recruited in Europe and the USA. The mixture model MiXeR was used to estimate the unique genetic architecture characteristics of each SUD, including its polygenicity, single nucleotide polymorphism (SNP)‐heritability and discoverability, a measure of the distribution of genetic signal across all causal variants. Pairwise conditional/conjunctional false discovery rate (cond/conjFDR) analyses identified shared loci, followed by biological annotation of implicated genes. Results AUD demonstrated the highest polygenicity, followed by CUD and OUD. SNP‐based heritability was 0.10 for AUD and OUD and 0.01 for CUD. Discoverability was highest for OUD, followed by AUD and CUD. Currently, genome‐wide significant SNPs explain 2.0% of AUD, 0.3% of CUD and 0.2% of OUD variance. Cond/conjFDR identified 39 novel loci for AUD, 10 for CUD and 1 for OUD. Of implicated genes, most were expressed in the brain, including several involved in gamma‐aminobutyric acid and dopaminergic neurotransmission, opioid neurophysiology, myelination, DNA recombination, apoptosis and ubiquitin‐dependent protein catabolism. Conclusions SUDs have polygenic architectures with many shared loci and are similar with regards to some characteristics. However, the level of polygenicity differs across SUDs, with AUD being considerably more polygenic than OUD, whereas CUD is intermediate in terms of its polygenicity. The novel loci implicate genes primarily expressed in the brain, involving a variety of biological functions. The findings expand our view of the aetiology of these disorders, while supporting the hypothesis of a shared set of pleiotropic SUD genes.

• Parker, Nadine; Koch, Elise; Shadrin, Alexey; Fuhrer, Julian; Hindley, Guy F. L. & Stinson, Sara Elizabeth [Show all 15 contributors for this article] (2026). Leveraging the genetics of psychiatric disorders to prioritize potential drug targets and compounds. Neuropsychopharmacology. ISSN 0893-133X. doi: 10.1038/s41386-026-02380-8. Full text in Research Archive
• Stinson, Sara E.; Shadrin, Alexey; Rahman, Mohammad Zillur; Rødevand, Linn; Broce, Iris J. & Selbæk, Geir [Show all 17 contributors for this article] (2026). Distinct metabolic signatures of Alzheimer's and Parkinson's disease revealed through genetic overlap. EBioMedicine. 127. doi: 10.1016/j.ebiom.2026.106254. Full text in Research Archive Show summary

  Background: Metabolic dysfunction is a major risk factor for neurodegeneration, yet the genetic architecture linking systemic metabolism to Alzheimer's disease (AD) and Parkinson's disease (PD) remains unclear. Methods: We integrated genome-wide association data for 249 circulating metabolites and proglucagon with summary statistics for AD, PD, and cardiometabolic traits. Genetic correlations, polygenic overlap, causal relationships, and shared genetic loci were quantified using linkage disequilibrium score regression, high-definition likelihood, bivariate mixture modelling, Mendelian randomisation, and conjunctional false discovery rate analyses, followed by functional and tissue-specific enrichment analyses. Findings: AD displayed a metabolic-genetic profile aligned with body mass index, type 2 diabetes, coronary artery disease, and stroke, whereas PD exhibited largely opposing patterns (Spearman's rs = −0.26). Mendelian randomization analyses supported causal effects of lipoprotein subclasses, glutamine, and proglucagon on AD risk, with opposite or null effects in PD. Shared loci between metabolites and AD were enriched for lipid metabolism and cholesterol transport, whereas PD-associated loci were enriched for mitochondrial function, vesicle trafficking, and stress-response signalling. Interpretation: AD and PD are shaped by fundamentally distinct metabolic-genetic architectures. Metabolically targeted interventions, particularly those modulating lipid, amino acid, and proglucagon pathways, may require disease-specific and genetically informed strategies for prevention and treatment of neurodegenerative diseases.

• Wiström, Erik David; Fuhrer, Julian; Shadrin, Alexey; Fominykh, Vera; O'Connell, Kevin Sean & Jaholkowski, Piotr Pawel [Show all 17 contributors for this article] (2026). Dissecting the genetic relationship between severe mental disorders and autoimmune diseases. Brain, Behavior, and Immunity. ISSN 0889-1591. 133. doi: 10.1016/j.bbi.2025.106249. Full text in Research Archive Show summary

  Severe mental disorders have been linked to immune system dysfunction. While a genetic association between mental disorders and autoimmune diseases has been suggested, their genetic relationship remains incompletely understood. Utilizing a complementary set of statistical analyses, we conducted a comprehensive investigation of the genetic architecture between severe mental disorders (major depression (MD), bipolar disorder (BD), and schizophrenia (SCZ)) and seven autoimmune diseases (autoimmune thyroiditis, celiac disease, inflammatory bowel disease (IBD), multiple sclerosis, psoriasis, rheumatoid arthritis, and type 1 diabetes), involving a total of 667,518 cases from 10 genome-wide association studies. While MD was positively genetically correlated with five autoimmune diseases, BD and SCZ were only positively correlated with IBD, suggesting differences in the genetic signal shared with autoimmunity across these mental disorders. A considerable fraction of genetic variants influencing autoimmune diseases (range 17.1–88.4 %) was estimated to overlap with mental disorders; however, this constitutes only a minor part of genetic variants influencing the more polygenic mental disorders. Finally, we identified 172 genetic loci jointly affecting mental disorders and autoimmune diseases, implicating both lipid metabolism and TNF signaling. In conclusion, MD, BD, and SCZ have a small but distinct genetic overlap with autoimmune diseases, which may inform new possible immune targets for treatment in mental illness.

• Ahn, Yeeun; Kim, Jaehyun; Jung, Kyeongmin; Lee, Dong June; Jung, Jin Young & Eom, Yewon [Show all 15 contributors for this article] (2025). Relationship Between Problematic Alcohol Use and Various Psychiatric Disorders: A Genetically Informed Study. American Journal of Psychiatry. ISSN 0002-953X. 182(7), p. 671–682. doi: 10.1176/appi.ajp.20240095. Full text in Research Archive
• O'Connell, Kevin Sean; Adolfsson, Rolf; Andlauer, Till F.M.; Bauer, Michael; Baune, Bernhaud & Biernacka, Joanna M. [Show all 52 contributors for this article] (2025). New Genomics Discoveries Across the Bipolar Disorder Spectrum Implicate Neurobiological and Developmental Pathways. Biological Psychiatry. ISSN 0006-3223. 98(4), p. 302–310. doi: 10.1016/j.biopsych.2025.05.020. Full text in Research Archive Show summary

  Bipolar disorder (BD) is a highly heritable mental disorder that affects millions of people worldwide. Our understanding of the genetic etiology and biological processes that underlie BD have greatly increased in recent years. Extensive progress has been made in identifying common variant signals for BD, and the polygenic score from the latest genome-wide association study (GWAS) may provide some clinical utility if combined with other risk factors for BD. The role of rare variation in BD remains to be determined, although genes annotated to common variant loci are shown to be enriched for rare variation. BD subtypes have been shown to differ in their genetic architecture, and as such, genetic studies across the subtypes of the BD spectrum will identify subtype-specific signals and reveal subtype-specific biological mechanisms. Despite this, subtype-specific GWAS sample sizes have not increased at the same rate as BD cases, and more concerted efforts are required to obtain this information for participants included in future BD GWASs. Moreover, assessment of culture, geography, and other systematic differences that may impact patient assessment will be necessary to ensure accurate inclusion of diverse ancestral groups and global representation in genetic studies of BD moving forward.

• Koromina, Maria; Ravi, Ashvin; Panagiotaropoulou, Georgia; Schilder, Brian M.; Humphrey, Jack & Braun, Alice [Show all 133 contributors for this article] (2025). Fine-mapping genomic loci refines bipolar disorder risk genes. Nature Neuroscience. ISSN 1097-6256. 28(7), p. 1393–1403. doi: 10.1038/s41593-025-01998-z. Full text in Research Archive Show summary

  Bipolar disorder is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 bipolar disorder risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci and prioritized 17 likely causal SNPs for bipolar disorder. We mapped these SNPs to genes and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci and results from rare variant exome sequencing in bipolar disorder. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment, including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, FKBP2, RASGRP1, FURIN, FES, MED24 and THRA among others in bipolar disorder. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of bipolar disorder polygenic risk scores across diverse populations and present a high-throughput fine-mapping pipeline.

• Höffler, Kira Daniela; Katrinli, Seyma; Halvorsen, Matthew W.; Stavrum, Anne-Kristin Støbakk; O'Connell, Kevin Sean & Shadrin, Alexey [Show all 18 contributors for this article] (2025). Optimizing genetic ancestry adjustment in DNA methylation studies: a comparative analysis of approaches. Epigenetics & Chromatin. 18, p. 1–14. doi: 10.1186/s13072-025-00627-0. Full text in Research Archive Show summary

  Background Genetic ancestry is an important factor to account for in DNA methylation studies because genetic variation influences DNA methylation patterns. One approach uses principal components (PCs) calculated from CpG sites that overlap with common SNPs to adjust for ancestry when genotyping data is not available. However, this method does not remove technical and biological variations, such as sex and age, prior to calculating the PCs. The first PC is therefore often associated with factors other than ancestry. Methods We developed and adapted the adapted EpiAnceR+ approach, which includes (1) residualizing the CpG data overlapping with common SNPs for control probe PCs, sex, age, and cell type proportions to remove the effects of technical and biological factors, and (2) integrating the residualized data with genotype calls from the SNP probes (commonly referred to as rs probes) present on the arrays, before calculating PCs and evaluated the clustering ability and relationship to genetic ancestry. Results The PCs generated by EpiAnceR+ led to improved clustering for repeated samples from the same individual and stronger associations with genetic ancestry groups predicted from genotype information compared to the original approach. EpiAnceR+ also outperformed the use of DNA methylation PCs or surrogate variables for ancestry adjustment. Conclusions We show that the EpiAnceR+ approach improves the adjustment for genetic ancestry in DNA methylation studies. EpiAnceR+ can be integrated into existing R pipelines for commercial methylation arrays, such as 450 K, EPIC v1, and EPIC v2. The code is available on GitHub (https://github.com/KiraHoeffler/EpiAnceR).

• Kopal, Jakub; Shadrin, Alexey A.; Meer, Dennis van der; Smeland, Olav B.; Stinson, Sara E. & Rodevand, Linn [Show all 12 contributors for this article] (2025). Mapping genetic convergence across brain structure, mental health, and cardiometabolic disease. medRxiv. doi: 10.1101/2025.05.22.25328130. Full text in Research Archive Show summary

  Individuals with psychiatric disorders frequently experience comorbid cardiometabolic conditions, complicating treatment and worsening health outcomes. Both psychiatric and cardiometabolic disorders have been individually associated with alterations in brain structure. Yet, it remains unclear whether these associations reflect a shared genetic basis that also contributes to their frequent co-occurrence. Here we analyzed genome-wide association summary statistics for psychiatric disorders, cardiometabolic disease, and brain morphology using complementary genetic approaches to disentangle genetic factors underlying brain alterations and comorbidity. Our results highlighted differences in patterns of genetic overlap across disorders. Schizophrenia showed substantial polygenic overlap with cortical thickness and type 2 diabetes, despite low genetic correlation. In contrast, ADHD was more genetically correlated with cardiometabolic disease but showed limited overlap with cortical morphology. Mediation analysis suggested that cortical surface area may partly mediate the genetic link between ADHD and type 2 diabetes. Pathway enrichment highlighted metabolic stress in ADHD and neurodevelopmental and immune processes in schizophrenia. These findings suggest that psychiatric-cardiometabolic comorbidity arises through both shared and disorder-specific genetic pathways, clarifying the genetic architecture of multimorbidity and informing trait-targeted prevention strategies in psychiatry.

• Rask, Susanna Maria; Solismaa, Anssi; Ahola-Olli, Ari; Molden, Espen; O'Connell, Kevin Sean & Lyytikäinen, Leo Pekka [Show all 9 contributors for this article] (2025). Meta-analyses of clozapine, norclozapine levels and their ratio across three genome wide association studies. Translational Psychiatry. 15(1). doi: 10.1038/s41398-025-03649-0. Full text in Research Archive
• Grotzinger, Andrew D.; Werme, Josefin; Peyrot, Wouter J.; Frei, Oleksandr; Leeuw, Christiaan de & Bicks, Lucy K. [Show all 72 contributors for this article] (2025). Mapping the genetic landscape across 14 psychiatric disorders. Nature. ISSN 0028-0836. 649(8096), p. 406–415. doi: 10.1038/s41586-025-09820-3. Full text in Research Archive Show summary

  Psychiatric disorders display high levels of comorbidity and genetic overlap, challenging current diagnostic boundaries. For disorders for which diagnostic separation has been most debated, such as schizophrenia and bipolar disorder, genomic methods have revealed that the majority of genetic signal is shared. While over a hundred pleiotropic loci have been identified by recent cross-disorder analyses, the full scope of shared and disorder-specific genetic influences remains poorly defined. Here we addressed this gap by triangulating across a suite of cutting-edge statistical and functional genomic analyses applied to 14 childhood- and adult-onset psychiatric disorders (1,056,201 cases). Using genetic association data from common variants, we identified and characterized five underlying genomic factors that explained the majority of the genetic variance of the individual disorders (around 66% on average) and were associated with 238 pleiotropic loci. The two factors defined by (1) Schizophrenia and bipolar disorders (SB factor); and (2) major depression, PTSD and anxiety (Internalizing factor) showed high levels of polygenic overlap and local genetic correlation and very few disorder-specific loci. The genetic signal shared across all 14 disorders was enriched for broad biological processes (for example, transcriptional regulation), while more specific pathways were shared at the level of the individual factors. The shared genetic signal across the SB factor was substantially enriched in genes expressed in excitatory neurons, whereas the Internalizing factor was associated with oligodendrocyte biology. These observations may inform a more neurobiologically valid psychiatric nosology and implicate targets for therapeutic development designed to treat commonly occurring comorbid presentations.

• Jung, Jin Young; Ahn, Yeeun; Park, Jung Wook; Jung, Kyeongmin; Kim, Soyeon & Lim, Soohyun [Show all 17 contributors for this article] (2025). Polygenic overlap between subjective well-being and psychiatric disorders and cross-ancestry validation. Nature Human Behaviour. 9(6), p. 1272–1282. doi: 10.1038/s41562-025-02155-z. Full text in Research Archive
• Shadrin, Alexey; Hindley, Guy; Hagen, Espen; Parker, Nadine; Tesfaye, Markos & Jaholkowski, Piotr Pawel [Show all 16 contributors for this article] (2025). Distinct patterns of genetic overlap among multimorbidities revealed with trivariate MiXeR. Genome Medicine. 17. doi: 10.1186/s13073-025-01528-3. Full text in Research Archive Show summary

  Background: Multimorbidities are a global health challenge. Accumulating evidence indicates that overlapping genetic architectures underlie comorbid complex human traits and disorders. This can be quantified for a pair of phenotypes using various techniques. Still, the pattern of genetic overlap between three distinct complex phenotypes, which is important for understanding multimorbidities, has not been possible to quantify. Methods: Here, we present and validate the novel trivariate MiXeR tool, which disentangles the pattern of genetic overlap between three complex phenotypes using summary statistics from genome-wide association studies. Our simulations show that trivariate MiXeR can reliably reconstruct different patterns of genetic overlap and estimate the proportions of genetic overlap between three phenotypes. Results: We found substantial genetic overlap between gastro-intestinal and brain diseases supporting a genetic basis of the gut-brain axis—the pattern consistent with pairwise analysis. However, the pattern of genetic overlap between three diverse cardiometabolic and renal health indicators and three immune-linked disorders revealed a much larger genomic component shared between all phenotypes than expected from separate pairwise analyses. This suggests the existence of core pathways underlying distinct but related chronic conditions. Conclusions: Overall, trivariate MiXeR offers a novel and efficient tool for investigating patterns of genetic overlap among three complex phenotypes. This contributes to a better understanding of genetic relationships between complex traits and disorders, potentially providing new insights into the mechanisms underlying common multimorbidities. Trivariate MiXeR is freely available at https://github.com/precimed/mix3r .

• Hope, Sigrun; Lin, Aihua; Rødevand, Linn; Hübenette, Saira Jameela; Quintana, Daniel & Sønderby, Ida Elken [Show all 17 contributors for this article] (2025). Shared genetic architecture between autism spectrum disorder, loneliness, and social isolation reveals novel genetic loci. Psychiatric Genetics. ISSN 0955-8829. doi: 10.1097/ypg.0000000000000406. Full text in Research Archive Show summary

  Objective: Deficits in social communication and social interaction are core features of autism spectrum disorder (ASD), and studies suggest that loneliness and social isolation are common. ASD has a strong genetic basis, but the genetic architecture and overlap with social phenotypes are not clear. Methods: We analyzed summary statistics from genome-wide association studies on ASD (46 350), loneliness (452 302), and social isolation (288 950), using linkage disequilibrium score regression, local analysis of covariant annotation (LAVA), bivariate causal mixture model (MiXeR), and the conditional/conjunctional false discovery rate (cond/conjFDR). Results: For ASD and social isolation, we found nonsignificant global genetic correlation ( r g = 0.02, P  = 0.8), but LAVA identified 72 genomic regions with bidirectional correlations, and MiXeR estimated that 8.7 k of 13.1 k variants (81%) were shared, of which 53% had concordant effect directions. For ASD and loneliness, we found a positive genetic correlation ( r g = 0.26, P  = 2e-10), LAVA identified 80 genomic regions with bidirectional genetic correlations, and MiXeR suggested that at least 3.8 k variants were shared. We identified nine specific shared genetic loci between ASD and loneliness and eight between ASD and social isolation (conjFDR < 0.05). Of these, 12 loci were novel for ASD. Genes mapped to these loci are involved in γ-aminobutyric acid (GABA), glutamate, calcium, and stress hormone signaling, cerebral glucose transport, TAU-accumulation, and immune function. Conclusion: We found extensive overlap in genetic architecture between ASD, loneliness, and social isolation, with bidirectional effects. By leveraging data for ASD and social traits, we identified 12 novel ASD related genetic loci implicating several genes, thereby elucidating potential pathways underlying their shared genetic architecture.

• Smeland, Olav B.; Kutrolli, Gleda; Bahrami, Shahram; Fominykh, Vera; Parker, Nadine & Fuhrer, Julian [Show all 21 contributors for this article] (2025). A genome-wide analysis of the shared genetic risk architecture of complex neurological and psychiatric disorders. Nature Neuroscience. ISSN 1097-6256. 28(12), p. 2439–2450. doi: 10.1038/s41593-025-02090-2. Full text in Research Archive Show summary

  Although neurological and psychiatric disorders have historically been considered to reflect distinct pathogenic entities, recent findings suggest shared pathophysiological mechanisms. However, the extent to which these heritable disorders share genetic influences remains unclear. Here we performed a comprehensive analysis of genome-wide association study data, involving nearly 1 million cases across ten neurological diseases and ten psychiatric disorders, to compare their common genetic signal and biological associations. Using complementary statistical tools, we demonstrate that a large set of common genetic variants impacts the risk of multiple neurological and psychiatric disorders, even in the absence of genetic correlations. Furthermore, genome-wide association studies on psychiatric disorders consistently implicate neuronal biology, whereas neurological diseases are associated with diverse neurobiological processes. Together, this study elucidates the genetic relationship between complex neurological and psychiatric disorders, indicating a larger degree of genetic pleiotropy than previously recognized. The findings have implications for disease classification, precision medicine and clinical practice.

• Koch, Elise; Puusepp, Tuuli; Einarsson, Guðmundur; Mitchell, Brittany L.; Harder, Arvid & Lin, Yuhao [Show all 31 contributors for this article] (2025). Genome-wide meta-analyses of non-response to antidepressants provide insights into underlying molecular genetics and suggest potential pharmacotherapies. Molecular Psychiatry. ISSN 1359-4184. doi: 10.1038/s41380-025-03357-7. Full text in Research Archive Show summary

  Antidepressants exhibit a considerable variation in efficacy, and increasing evidence suggests that individual genetics contribute to antidepressant treatment response. Here, we combined data on antidepressant non-response measured using rating scales for depressive symptoms, questionnaires of treatment effect, and data from electronic health records, to increase statistical power to detect genomic loci associated with non-response to antidepressants in a total sample of 135,471 individuals prescribed antidepressants (25,255 non-responders and 110,216 responders). We performed genome-wide association meta-analyses, genetic correlation analyses, leave-one-out polygenic prediction, and bioinformatics analyses for genetically informed drug prioritization. We identified one novel locus (rs1106260) associated with non-response to selective serotonin reuptake inhibitors (SSRIs), and one novel locus (rs60847828) associated with non-response to SSRIs and serotonin-norepinephrine reuptake inhibitors (SNRIs) and showed significant polygenic prediction in independent samples. Genetic correlation analyses show positive associations between non-response to antidepressants and most psychiatric traits, and negative associations with cognitive traits and subjective well-being. In addition, we investigated drugs that target proteins likely involved in mechanisms underlying antidepressant non-response, and shortlisted drugs that warrant further replication and validation of their potential to reduce depressive symptoms in individuals who do not respond to first-line antidepressant medications. These results suggest that meta-analyses of GWAS utilizing real-world measures of treatment outcomes can increase sample sizes to improve the discovery of variants associated with non-response to antidepressants.

• Agrawal, Arpana; Bulik, Cynthia M; Abebe, Dawit Shawel; Andreassen, Ole; Atkinson, Elizabeth G & Choi, Karmel W [Show all 39 contributors for this article] (2025). The Psychiatric Genomics Consortium: discoveries and directions. The Lancet Psychiatry. ISSN 2215-0374. 12(8), p. 600–610. doi: 10.1016/s2215-0366(25)00124-5. Full text in Research Archive Show summary

  Research by the Psychiatric Genomics Consortium (PGC) has advanced the discovery of common and rare genetic variations that contribute to the susceptibility to many psychiatric disorders and neurodevelopmental conditions. This Review reflects on major findings from the past 5 years of research by the PGC in five priority areas: discovery of common variants using genome-wide association studies; rare variation and its interplay with polygenic risk; using genetics to go beyond diagnostic boundaries; ascribing functional attributes to genomic discoveries; and developing and implementing processes for data sharing, outreach to various communities, and training. The insights gained in these domains frame the agenda for the next phase of PGC research. In addition to accelerating integrative findings of common and rare variants within, and across, multiple psychiatric disorders and neurodevelopmental conditions, the next phase will use multiple populations to elucidate genetic causes, integrate results with rapidly accumulating multimodal functional genomics data to gain mechanistic understanding, convert genetic findings to clinically actionable phenotypes, such as treatment response, and address the emerging use of polygenic scores. Together, these next steps will highlight the biological underpinnings of psychiatric disorders and neurodevelopmental conditions, which continue to contribute to global morbidity and mortality.

• Koch, Elise; Shadrin, Alexey; Parker, Nadine; Lock, Siobhan K.; Smith, Robert Løvsletten & Frei, Oleksandr [Show all 11 contributors for this article] (2025). Polygenic overlap with granulocyte counts identifies novel loci for clozapine metabolism and clozapine-induced agranulocytosis. Neuropsychopharmacology. ISSN 0893-133X. 50, p. 947–955. doi: 10.1038/s41386-025-02054-x. Full text in Research Archive Show summary

  While clozapine is the most effective antipsychotic drug, its use is limited due to hematological adverse effects involving the reduction of granulocyte counts with potential life-threatening agranulocytosis. It is not yet possible to predict or prevent the risk of agranulocytosis, and the mechanisms are unknown but likely related to clozapine metabolism. Genome-wide association studies (GWASs) of clozapine metabolism and clozapine-induced agranulocytosis have identified few genetic loci. We used the largest available GWAS summary statistics of clozapine metabolism (clozapine-to-norclozapine ratio) and clozapine-induced agranulocytosis, applying the conditional false discovery rate (condFDR) method to increase power for genetic discovery by conditioning on granulocyte counts variants. To investigate potential causal effects of shared loci, we performed Mendelian Randomization analyses. After conditioning on granulocyte counts, we identified two novel loci associated with clozapine-to-norclozapine ratio. These loci were significantly associated with clozapine metabolism in a validation sample of 392 clozapine-treated individuals. For clozapine-induced agranulocytosis, five loci were identified after conditioning on granulocyte counts. These five loci were significantly associated with reduced granulocyte counts in a small independent sample of clozapine-treated individuals. Genetic liability to slow clozapine metabolism (high clozapine-to-norclozapine ratio) showed evidence of a causal effect on reduced neutrophil counts, and genetic liability to low neutrophil counts exhibited weak evidence of a causal effect on clozapine-induced agranulocytosis. Our findings of shared genetic variants associated with clozapine metabolism and granulocyte counts may form the basis for developing prediction models for clozapine-induced agranulocytosis.

• O'Connell, Kevin Sean; Koromina, Maria; Veen, Tracy van der; Boltz, Toni; David, Friederike S. & Yang, Jessica Mei Kay [Show all 313 contributors for this article] (2025). Genomics yields biological and phenotypic insights into bipolar disorder. Nature. ISSN 0028-0836. 639, p. 968–975. doi: 10.1038/s41586-024-08468-9. Full text in Research Archive Show summary

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

• Wiström, Erik David; O'Connell, Kevin Sean; Koch, Elise; Jaholkowski, Piotr Pawel; Hindley, Guy & Steen, Nils Eiel [Show all 14 contributors for this article] (2025). The genetic overlap between major depressive disorder, white blood cell counts and interleukin 6. Journal of Affective Disorders Reports. 20, p. 1–10. doi: 10.1016/j.jadr.2025.100889. Full text in Research Archive Show summary

  Background: Immune dysregulation may contribute to the pathophysiology of major depressive disorder (MDD). Here we aimed to identify genetic architecture jointly associated with MDD, white blood cell (WBC) count and interleukin 6 (IL-6) levels. Methods: Using genome-wide association studies summary statistics on MDD (330,173 cases and 727,595 controls), WBC counts (nmax = 563,946) and IL-6 (n = 52,654), we performed linkage disequilibrium (LD) score regression, bivariate causal mixture model (MiXeR), conjunctional false discovery rate (conjFDR) and Mendelian randomization (MR) analyses. Additionally, we used an independent MDD dataset (9,582 cases and 84,670 controls) from the Norwegian Mother, Father and Child Cohort Study for polygenic risk score (PRS) analyses. Findings: We found a significant positive genetic correlation (rg = 0.22) between MDD and IL-6. MiXeR estimates indicated substantial differences in the polygenicity of MDD (13.7K variants), WBC subgroups (0.8K-1.8K variants), and IL-6 (0.2K variants), with 10.1 %-31.4 % of the variants influencing WBC subgroups overlapping with MDD. We identified MDD risk loci shared with basophils (8), eosinophils (17), lymphocytes (23), monocytes (14), neutrophils (20), and total WBC counts (20), as well as two loci shared between MDD and IL-6, at conjFDR <0.05. PRS analysis showed a weak, but significantly increased risk for MDD dependent on monocyte count. Limitations: The analyses only included European ancestry samples, and the causal genes associated with the identified genetic loci were not experimentally validated. Conclusions: MDD shares genetic underpinnings with immune system components, which implicates immune-mediated pathways in the pathophysiology of MDD. However, this connection may only be relevant for a minority of patients.

• Koch, Elise; Smart, Sophie; Einarsson, Guðmundur; Kämpe, Anders; Jonsson, Lina & Alver, Maris [Show all 30 contributors for this article] (2025). Recommendations for defining treatment outcomes in major psychiatric disorders using real-world data. The Lancet Psychiatry. ISSN 2215-0374. 12, p. 457–468. doi: 10.1016/S2215-0366(25)00061-6. Full text in Research Archive
• Nguyen, Thuy-Dung; Meijsen, Joeri J.; Sigström, Robert; Kuja-Halkola, Ralf; Xiong, Ying & Harder, Arvid [Show all 25 contributors for this article] (2025). Genetic insights into psychotic major depressive disorder: bridging the mood-psychotic disorder spectrum. EBioMedicine. 112. doi: 10.1016/j.ebiom.2025.105576. Full text in Research Archive Show 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.

• Strom, Nora I.; Gerring, Zachary F.; Galimberti, Marco; Yu, Dongmei; Halvorsen, Matthew W. & Abdellaoui, Abdel [Show all 214 contributors for this article] (2025). Genome-wide analyses identify 30 loci associated with obsessive–compulsive disorder. Nature Genetics. ISSN 1061-4036. 57, p. 1389–1401. doi: 10.1038/s41588-025-02189-z. Full text in Research Archive Show summary

  Obsessive–compulsive disorder (OCD) affects ~1% of children and adults and is partly caused by genetic factors. We conducted a genome-wide association study (GWAS) meta-analysis combining 53,660 OCD cases and 2,044,417 controls and identified 30 independent genome-wide significant loci. Gene-based approaches identified 249 potential effector genes for OCD, with 25 of these classified as the most likely causal candidates, including WDR6, DALRD3 and CTNND1 and multiple genes in the major histocompatibility complex (MHC) region. We estimated that ~11,500 genetic variants explained 90% of OCD genetic heritability. OCD genetic risk was associated with excitatory neurons in the hippocampus and the cortex, along with D1 and D2 type dopamine receptor-containing medium spiny neurons. OCD genetic risk was shared with 65 of 112 additional phenotypes, including all the psychiatric disorders we examined. In particular, OCD shared genetic risk with anxiety, depression, anorexia nervosa and Tourette syndrome and was negatively associated with inflammatory bowel diseases, educational attainment and body mass index.

• Icick, Romain; Shadrin, Alexey; Holen, Børge; Karadag, Naz; Parker, Nadine & O'Connell, Kevin Sean [Show all 20 contributors for this article] (2025). Identification of risk variants and cross-disorder pleiotropy through multi-ancestry genome-wide analysis of alcohol use disorder. Nature Mental Health. 3(2), p. 253–265. doi: 10.1038/s44220-024-00353-8. Full text in Research Archive Show summary

  Alcohol use disorder (AUD) is highly heritable and burdensome worldwide. Genome-wide association studies can provide new evidence regarding the etiology of AUD. We report a multi-ancestry genome-wide association study focusing on a narrow AUD phenotype, using novel statistical tools in a total sample of 1,041,450 individuals (102,079 cases; European, 75,583; African, 20,689 (mostly African American); Hispanic American, 3,449; East Asian, 2,254; South Asian, 104; descent). Cross-ancestry functional analyses were performed with European and African samples. Thirty-seven genome-wide significant loci (105 variants) were identified, of which seven were novel for AUD and six for other alcohol phenotypes. Loci were mapped to genes, which show altered expression in brain regions relevant for AUD (striatum, hypothalamus and prefrontal cortex) and encode potential drug targets (GABAergic, dopaminergic and serotonergic neurons). African-specific analysis yielded a unique pattern of immune-related gene sets. Polygenic overlap and positive genetic correlations showed extensive shared genetic architecture between AUD and both mental and general medical phenotypes, suggesting that they are not only complications of alcohol use but also share genetic liability with AUD. Leveraging a cross-ancestry approach allowed identification of novel genetic loci for AUD and underscores the value of multi-ancestry genetic studies. These findings advance our understanding of AUD risk and clinically relevant comorbidities.

• Meer, Dennis van der; Rahman, Mohammad Zillur; Ottas, Aigar; Parekh, Pravesh; Kutrolli, Gleda & Stinson, Sara Elizabeth [Show all 37 contributors for this article] (2025). Pleiotropic and sex-specific genetic mechanisms of circulating metabolic markers. Nature Communications. 16(1). doi: 10.1038/s41467-025-60058-z. Full text in Research Archive Show summary

  Metabolites in plasma form biosignatures of a range of common complex human diseases. Discovering variants with pleiotropic effects across metabolites can reveal underlying biological mechanisms. We therefore performed uni- and multivariate genome-wide association studies (GWAS) on 249 circulating metabolic markers across 328,006 UK Biobank and Estonian Biobank participants. We investigated rare variation through whole exome sequencing gene burden tests, analysed the role of body mass index through Mendelian randomization, and performed genome-wide interaction analyses with sex. We discovered 15,585 loci summed over the univariate GWAS, with high pleiotropy across markers, linked to a wide range of disorders. Findings from common and rare variant gene tests converged on lipid homeostasis pathways. 31 loci interacted with sex, mapped to genes involved in cholesterol processing. The findings offer insights into the genetic architecture of circulating metabolites, revealing pleiotropic loci, highlighting the role of rare variation, and uncovering sex-specific molecular mechanisms of lipid metabolism.

• Jaholkowski, Piotr Pawel; Bahrami, Shahram; Fominykh, Vera; Hindley, Guy; Tesfaye, Markos & Parekh, Pravesh [Show all 23 contributors for this article] (2024). Charting the shared genetic architecture of Alzheimer's disease, cognition, and educational attainment, and associations with brain development. Neurobiology of Disease. ISSN 0969-9961. 203. doi: 10.1016/j.nbd.2024.106750. Full text in Research Archive Show summary

  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.

• Lenk, Hasan Cagin; Smith, Robert Løvsletten; O'Connell, Kevin Sean; Andreassen, Ole A. & Molden, Espen (2024). Rapid Metabolism Underlying Subtherapeutic Serum Levels of Atypical Antipsychotics Preceding Clozapine Treatment: A Retrospective Analysis of Real-World Data. CNS Drugs. ISSN 1172-7047. 38, p. 473–480. doi: 10.1007/s40263-024-01079-y. Full text in Research Archive Show summary

  Introduction Adequate antipsychotic treatment intensity is required before diagnosing resistant schizophrenia and initiating clozapine treatment. We aimed to investigate potential rapid drug metabolism underlying low dose-adjusted serum concentration (CD) of non-clozapine atypical antipsychotics preceding clozapine treatment. Methods Patients using non-clozapine, atypical antipsychotics (aripiprazole, risperidone, olanzapine, or quetiapine) within 1 year before starting clozapine were included in this study from a therapeutic drug monitoring service in Oslo, Norway, between 2005 and 2023. Patients were assigned into low CD (LCD) and normal CD (NCD) subgroups. Using a reference sample with 147,964 antipsychotic measurements, LCD was defined as CDs below the 25th percentile, while patients with NCD exhibited CDs between the 25th and 75th percentile of the respective reference measurements. Metabolic ratios, doses, and frequency of subtherapeutic levels of non-clozapine antipsychotics were compared between LCD and NCD groups. Results Preceding clozapine treatment, 110 out of 272 included patients (40.4%) were identified with LCD. Compared with the NCD group, LCD patients exhibited higher metabolic ratios of olanzapine (1.5-fold; p < 0.001), quetiapine (3.0-fold; p < 0.001), and risperidone (6.0-fold; p < 0.001). Metabolic ratio differences were independent of smoking and CYP2D6 genotype for olanzapine (p = 0.008) and risperidone (p = 0.016), respectively. Despite higher doses of olanzapine (1.25-fold; p = 0.054) and quetiapine (1.6-fold; p = 0.001) in LCD versus NCD patients, faster metabolism among the former was accompanied by higher frequencies of subtherapeutic levels of olanzapine (3.3-fold; p = 0.044) and quetiapine (1.8-fold; p = 0.005). Conclusion LCD and associated rapid metabolism of non-clozapine antipsychotics is frequent before starting clozapine treatment. For olanzapine and quetiapine, this is associated with significantly increased risk of having subtherapeutic concentrations.

• Pentz, Atle Bråthen; O'Connell, Kevin Sean; Jole, Oda van; Timpe, Clara Marie Fides; Slapø, Nora Berz & Melle, Ingrid [Show all 14 contributors for this article] (2024). Mismatch negativity and polygenic risk scores for schizophrenia and bipolar disorder. Schizophrenia Research. ISSN 0920-9964. 264, p. 314–326. doi: 10.1016/j.schres.2024.01.013. Full text in Research Archive Show summary

  Objective: Auditory mismatch negativity (MMN) impairment is a candidate endophenotype in psychotic disorders, yet the genetic underpinnings remain to be clarified. Here, we examined the relationships between auditory MMN and polygenic risk scores (PRS) for individuals with psychotic disorders, including schizophrenia spectrum disorders (SSD) and bipolar disorder (BD) and in healthy controls (HC). Methods: Genotyped and clinically well-characterized individuals with psychotic disorders (n = 102), including SSD (n = 43) and BD (n = 59), and HC (n = 397) underwent a roving MMN paradigm. In addition MMN, we measured the memory traces of the repetition positivity (RP) and the deviant negativity (DN), which is believed to reflect prediction encoding and prediction error signals, respectively. SCZ and BD PRS were computed using summary statistics from the latest genome-wide association studies. The relationships between the MMN, RP, and DN and the PRSs were assessed with linear regressions. Results: We found no significant association between the SCZ or BD PRS and grand average MMN in the psychotic disorders group or in the HCs group (all p > 0.05). SCZ PRS and BD PRS were negatively associated with RP in the psychotic disorders group (β = 0.46, t = 2.86, p = 0.005 and β = 0.29, t = 0.21, p = 0.034, respectively). No significant associations were found between DN and PRS. Conclusion: These findings suggest that genetic variants associated with SCZ and BD may be associated with MMN subcomponents linked to predictive coding among patients with psychotic disorders. Larger studies are needed to confirm these findings and further elucidate the genetic underpinnings of MMN impairment in psychotic disorders.

• Smith, Robert Løvsletten; Wollmann, Birgit Malene Tovik; Størset, Elisabet; Lenk, Hasan Cagin; O'Connell, Kevin Sean & Kringen, Marianne K. [Show all 8 contributors for this article] (2024). Effect of the NFIB rs28379954 T>C polymorphism on CYP2D6-catalyzed metabolism of solanidine. Clinical and Translational Science (CTS). ISSN 1752-8054. 17(2). doi: 10.1111/cts.13743. Full text in Research Archive Show summary

  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.

• Koch, Elise Mirjam; Pardiñas, Antonio F.; O'Connell, Kevin Sean; Selvaggi, Pierluigi; Camacho-Collados, Jose & Babic, Aleksandar [Show all 26 contributors for this article] (2024). How real-world data can facilitate the development of precision medicine treatment in psychiatry. Biological Psychiatry. ISSN 0006-3223. 96, p. 543–551. doi: 10.1016/j.biopsych.2024.01.001. Full text in Research Archive Show summary

  Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements—well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms—to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders.

• Andreou, Dimitrios; Steen, Nils Eiel; Mørch-Johnsen, Lynn Egeland; Jørgensen, Kjetil Nordbø; Wortinger, Laura Anne & Barth, Claudia [Show all 19 contributors for this article] (2024). Toxoplasma gondii infection associated with inflammasome activation and neuronal injury. Scientific Reports. 14(1). doi: 10.1038/s41598-024-55887-9. Full text in Research Archive Show summary

  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 < 0.001). TOXO seropositive participants had significantly higher NSE (3713 vs. 2200 pg/ml, p < 0.001) and IL-18 levels (1068 vs. 674 pg/ml, p < 0.001) than seronegative participants, and evaluation within patients and HC separately showed similar results. Post-hoc analysis on cytomegalovirus and herpes simplex virus 1 IgG status showed no associations with NSE or IL-18 which may suggest TOXO specificity. These results may indicate ongoing inflammasome activation and neuronal injury in people with TOXO infections unrelated to diagnosis.

• Karadag, Naz; Hagen, Espen; Shadrin, Alexey; Meer, Dennis van der; O'Connell, Kevin Sean & Rahman, Mohammad Zillur [Show all 18 contributors for this article] (2024). Dissecting the Shared Genetic Architecture of Common Epilepsies With Cortical Brain Morphology. Neurology: Genetics. 10(3). doi: 10.1212/NXG.0000000000200143. Full text in Research Archive Show summary

  Background and Objectives: Epilepsies are associated with differences in cortical thickness (TH) and surface area (SA). However, the mechanisms underlying these relationships remain elusive. We investigated the extent to which these phenotypes share genetic influences. Methods: We analyzed genome-wide association study data on common epilepsies (n = 69,995) and TH and SA (n = 32,877) using Gaussian mixture modeling MiXeR and conjunctional false discovery rate (conjFDR) analysis to quantify their shared genetic architecture and identify overlapping loci. We biologically interrogated the loci using a variety of resources and validated in independent samples. Results: The epilepsies (2.4 k–2.9 k variants) were more polygenic than both SA (1.8 k variants) and TH (1.3 k variants). Despite absent genome-wide genetic correlations, there was a substantial genetic overlap between SA and genetic generalized epilepsy (GGE) (1.1 k), all epilepsies (1.1 k), and juvenile myoclonic epilepsy (JME) (0.7 k), as well as between TH and GGE (0.8 k), all epilepsies (0.7 k), and JME (0.8 k), estimated with MiXeR. Furthermore, conjFDR analysis identified 15 GGE loci jointly associated with SA and 15 with TH, 3 loci shared between SA and childhood absence epilepsy, and 6 loci overlapping between SA and JME. 23 loci were novel for epilepsies and 11 for cortical morphology. We observed a high degree of sign concordance in the independent samples. Discussion: Our findings show extensive genetic overlap between generalized epilepsies and cortical morphology, indicating a complex genetic relationship with mixed-effect directions. The results suggest that shared genetic influences may contribute to cortical abnormalities in epilepsies.

• Bahrami, Shahram; Nordengen, Kaja; Rokicki, Jaroslav; Shadrin, Alexey; Rahman, Mohammad Zillur & Smeland, Olav Bjerkehagen [Show all 17 contributors for this article] (2024). The genetic landscape of basal ganglia and implications for common brain disorders. Nature Communications. 15(1). doi: 10.1038/s41467-024-52583-0. Full text in Research Archive Show summary

  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 < 0.05 and 87.5% showed the same direction, revealing a distributed genetic architecture across basal ganglia structures. Of these, 50 loci were novel, including exonic regions of APOE, NBR1 and HLAA. We examined the genetic overlap between basal ganglia volumes and several neurological and psychiatric disorders. The strongest genetic overlap was between basal ganglia and Parkinson’s disease, as supported by robust LD-score regression-based genetic correlations. Mendelian randomization indicated genetic liability to larger striatal volume as potentially causal for Parkinson’s disease, in addition to a suggestive causal effect of greater genetic liability to Alzheimer’s disease on smaller accumbens. Functional analyses implicated neurogenesis, neuron differentiation and development in basal ganglia volumes. These results enhance our understanding of the genetic architecture and molecular associations of basal ganglia structure and their role in brain disorders.

• Szabo, Attila; O'Connell, Kevin Sean; Akkouh, Ibrahim Ahmed; Ueland, Thor; Sønderby, Ida Elken & Hope, Sigrun [Show all 16 contributors for this article] (2024). Elevated levels of peripheral and central nervous system immune markers reflect innate immune dysregulation in autism spectrum disorder. Psychiatry Research. ISSN 0165-1781. 342. doi: 10.1016/j.psychres.2024.116245. Full text in Research Archive Show summary

  Background Evidence suggests dysregulated immune functions in the pathophysiology of Autism spectrum disorder (ASD), although specific immune mechanisms are yet to be identified. Methods We assessed circulating levels of 25 immune/neuroinflammatory markers in a large ASD sample (n = 151) and matched controls (n = 72) using linear models. In addition, we performed global brain transcriptomics analyses of relevant immune-related genes. We also assessed the expression and function of factors and pathway elements of the inflammasome system in peripheral blood mononuclear cells (PBMC) isolated from ASD and controls using in vitro methods. Results We found higher circulating levels of IL-18 and adhesion factors (ICAM-1, MADCAM1) in individuals with ASD relative to controls. Consistent with this, brain levels of ICAM1 mRNA were also higher in ASD compared to controls. Furthermore, we found higher expression/activity of Caspase-1 and the inflammasome sensor NLRP3 in PBMCs in ASD, both at baseline and following inflammatory challenge. This corresponded with higher levels of secreted IL-18, IL-1β, and IL-8, as well as increased expression of adhesion factors following inflammasome activation in ASD PBMC cultures. Inhibition of the NLRP3-inflammasome rescued the observed immune phenotype in ASD in vitro. Conclusion Our results suggest a role for inflammasome dysregulation in ASD pathophysiology.

• Tesfaye, Markos; Jaholkowski, Piotr Pawel; Shadrin, Alexey; Meer, Dennis van der; Hindley, Guy & Holen, Børge [Show all 18 contributors for this article] (2024). Identification of novel genomic loci for anxiety symptoms and extensive genetic overlap with psychiatric disorders. Psychiatry and Clinical Neurosciences. ISSN 1323-1316. 78(12), p. 783–791. doi: 10.1111/pcn.13742. Full text in Research Archive Show summary

  Aims: Anxiety disorders are prevalent and anxiety symptoms (ANX) co-occur with many psychiatric disorders. We aimed to identify genomic loci associated with ANX, characterize its genetic architecture, and genetic overlap with psychiatric disorders. Methods: We included a genome-wide association study of ANX (meta-analysis of UK Biobank and Million Veterans Program, n = 301,732), schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD), and validated the findings in the Norwegian Mother, Father, and Child Cohort (n = 95,841). We employed the bivariate causal mixture model and local analysis of covariant association to characterize the genetic architecture including overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of loci associated with anxiety and shared with psychiatric disorders. Results: Anxiety was polygenic with 12.9k genetic variants and overlapped extensively with psychiatric disorders (4.1k–11.4k variants) with predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 119 novel loci for anxiety by conditioning on the psychiatric disorders, and loci shared between anxiety and MD (n=47), BIP (n=33), SCZ (n=71), ADHD (n=20), and ASD (n=5). Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways including cell adhesion and neurofibrillary tangle compared with genes annotated to the shared loci. Conclusions: Anxiety is highly polygenic phenotype with extensive genetic overlap with psychiatric disorders, and we identified novel loci for anxiety implicating new molecular pathways. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified molecular underpinnings may lead to potential drug targets.

• Frei, Oleksandr; Hindley, Guy; Shadrin, Alexey; Meer, Dennis van der; Akdeniz, Bayram Cevdet & Hagen, Espen [Show all 50 contributors for this article] (2024). Improved functional mapping of complex trait heritability with GSA-MiXeR implicates biologically specific gene sets. Nature Genetics. ISSN 1061-4036. 56(6), p. 1310–1318. doi: 10.1038/s41588-024-01771-1. Full text in Research Archive
• Koch, Elise Mirjam; Kämpe, Anders; Alver, Maris; Sigurðarson, Sindri; Einarsson, Guðmundur & Partanen, Juulia [Show all 21 contributors for this article] (2024). Polygenic liability for antipsychotic dosage and polypharmacy - a real-world registry and biobank study. Neuropsychopharmacology. ISSN 0893-133X. 49, p. 1113–1119. doi: 10.1038/s41386-023-01792-0. Full text in Research Archive
• Karadag, Naz; Hagen, Espen; Shadrin, Alexey; Meer, Dennis van der; O'Connell, Kevin Sean & Rahman, Mohammad Zillur [Show all 19 contributors for this article] (2024). Unraveling the shared genetics of common epilepsies and general cognitive ability. Seizure. ISSN 1059-1311. 122, p. 105–112. doi: 10.1016/j.seizure.2024.09.016. Full text in Research Archive Show summary

  Purpose Cognitive impairment is prevalent among individuals with epilepsy, and increasing evidence indicates that genetic factors can underlie this relationship. However, the extent to which epilepsy subtypes differ in their genetic relationship with cognitive function, and information about the specific genetic variants involved remain largely unknown. Methods We investigated the genetic relationship between epilepsies and general cognitive ability (COG) using complementary statistical tools, including linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR). We analyzed genome-wide association study data on COG (n = 269,867) and common epilepsies (n = 27,559 cases, 42,436 controls), including the broad phenotypes ‘all epilepsy’, focal epilepsies and genetic generalized epilepsies (GGE), as well as specific subtypes. We functionally annotated the identified loci using several biological resources and validated the results in independent samples. Results Using MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than ‘all epilepsy’, GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k – 2.9k variants). The other epilepsy phenotypes were insufficiently powered for MiXeR analysis. We quantified extensive genetic overlap between COG and epilepsy types, but with varying negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and ‘all epilepsy’, and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), ‘all epilepsy’ (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: p = 3.62 × 10–7; ‘all epilepsy’: p = 2.58 × 10–3). Conclusion Our study further dissects the substantial genetic basis shared between epilepsies and COG and identifies novel shared loci. An improved understanding of the genetic relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.

• Kim, Hyejin; Ahn, Yeeun; Yoon, Joohyun; Jung, Kyeongmin; Kim, Soyeon & Shim, Injeong [Show all 27 contributors for this article] (2024). Genome-wide association analyses using machine learning-based phenotyping reveal genetic architecture of occupational creativity and overlap with psychiatric disorders. Psychiatry Research. ISSN 0165-1781. 333. doi: 10.1016/j.psychres.2024.115753. Full text in Research Archive
• Holmgren, Asbjørn; Akkouh, Ibrahim Ahmed; O'Connell, Kevin Sean; Osete, Jordi Requena; Bjørnstad, Pål Marius & Djurovic, Srdjan [Show all 7 contributors for this article] (2024). Bipolar patients display stoichiometric imbalance of gene expression in post-mortem brain samples. Molecular Psychiatry. ISSN 1359-4184. 29. doi: 10.1038/s41380-023-02398-0. Full text in Research Archive Show summary

  Bipolar disorder is a severe neuro-psychiatric condition where genome-wide association and sequencing studies have pointed to dysregulated gene expression as likely to be causal. We observed strong correlation in expression between GWAS-associated genes and hypothesised that healthy function depends on balance in the relative expression levels of the associated genes and that patients display stoichiometric imbalance. We developed a method for quantifying stoichiometric imbalance and used this to predict each sample’s diagnosis probability in four cortical brain RNAseq datasets. The percentage of phenotypic variance on the liability-scale explained by these probabilities ranged from 10.0 to 17.4% (AUC: 69.4–76.4%) which is a multiple of the classification performance achieved using absolute expression levels or GWAS-based polygenic risk scores. Most patients display stoichiometric imbalance in three to ten genes, suggesting that dysregulation of only a small fraction of associated genes can trigger the disorder, with the identity of these genes varying between individuals.

• Lenk, Hasan Cagin; Koch, Elise Mirjam; O'Connell, Kevin Sean; Smith, Robert Løvsletten; Akkouh, Ibrahim Ahmed & Djurovic, Srdjan [Show all 8 contributors for this article] (2024). Genome-wide association analysis of treatment resistant schizophrenia for variant discovery and polygenic assessment. Human Genomics. ISSN 1473-9542. 18(1). doi: 10.1186/s40246-024-00673-x. Full text in Research Archive Show summary

  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.

• Wootton, Olivia; Shadrin, Alexey; Bjella, Thomas; Smeland, Olav Bjerkehagen; Meer, Dennis van der & Frei, Oleksandr [Show all 11 contributors for this article] (2024). Genomic insights into the shared and distinct genetic architecture of cognitive function and schizophrenia. Scientific Reports. 14(1). doi: 10.1038/s41598-024-66085-y. Full text in Research Archive Show summary

  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.

• Steen, Nils Eiel; Rahman, Zillur; Szabo, Attila; Hindley, Guy; Parker, Nadine & Cheng, Weiqiu [Show all 20 contributors for this article] (2023). Shared Genetic Loci Between Schizophrenia and White Blood Cell Counts Suggest Genetically Determined Systemic Immune Abnormalities. Schizophrenia Bulletin. ISSN 0586-7614. 49(5), p. 1345–1354. doi: 10.1093/schbul/sbad082. Full text in Research Archive Show summary

  Background: Immune mechanisms are indicated in schizophrenia (SCZ). Recent genome-wide association studies (GWAS) have identified genetic variants associated with SCZ and immune-related phenotypes. Here, we use cutting edge statistical tools to identify shared genetic variants between SCZ and white blood cell (WBC) counts and further understand the role of the immune system in SCZ. Study Design: GWAS results from SCZ (patients, n = 53 386; controls, n = 77 258) and WBC counts (n = 56 3085) were analyzed. We applied linkage disequilibrium score regression, the conditional false discovery rate method and the bivariate causal mixture model for analyses of genetic associations and overlap, and 2 sample Mendelian randomization to estimate causal effects. Study Results: The polygenicity for SCZ was 7.5 times higher than for WBC count and constituted 32%–59% of WBC count genetic loci. While there was a significant but weak positive genetic correlation between SCZ and lymphocytes (rg = 0.05), the conditional false discovery rate method identified 383 shared genetic loci (53% concordant effect directions), with shared variants encompassing all investigated WBC subtypes: lymphocytes, n = 215 (56% concordant); neutrophils, n = 158 (49% concordant); monocytes, n = 146 (47% concordant); eosinophils, n = 135 (56% concordant); and basophils, n = 64 (53% concordant). A few causal effects were suggested, but consensus was lacking across different Mendelian randomization methods. Functional analyses indicated cellular functioning and regulation of translation as overlapping mechanisms. Conclusions: Our results suggest that genetic factors involved in WBC counts are associated with the risk of SCZ, indicating a role of immune mechanisms in subgroups of SCZ with potential for stratification of patients for immune targeted treatment.

• Hindley, Guy; Drange, Ole Kristian; Lin, Aihua; Kutrolli, Gleda; Shadrin, Alexey & Parker, Nadine [Show all 20 contributors for this article] (2023). Cross-trait genome-wide association analysis of C-reactive protein level and psychiatric disorders. Psychoneuroendocrinology. ISSN 0306-4530. 157. doi: 10.1016/j.psyneuen.2023.106368. Full text in Research Archive Show summary

  C-reactive protein (CRP) tends to be elevated in individuals with psychiatric disorders. Recent findings have suggested a protective effect of the genetic liability to elevated CRP on schizophrenia risk and a causative effect on depression despite weak genetic correlations, while causal relationships with bipolar disorder were inconclusive. We investigated the shared genetic underpinnings of psychiatric disorders and variation in CRP levels. Genome-wide association studies for CRP (n = 575,531), bipolar disorder (n = 413,466), depression (n = 480,359), and schizophrenia (n = 130,644) were used in causal mixture models to compare CRP with psychiatric disorders based on polygenicity, discoverability, and genome-wide genetic overlap. The conjunctional false discovery rate method was used to identify specific shared genetic loci. Shared variants were mapped to putative causal genes, which were tested for overrepresentation among gene ontology gene-sets. CRP was six to ten times less polygenic (n = 1400 vs 8600–14,500 variants) and had a discoverability one to two orders of magnitude higher than psychiatric disorders. Most CRP-associated variants were overlapping with psychiatric disorders. We identified 401 genetic loci jointly associated with CRP and psychiatric disorders with mixed effect directions. Gene-set enrichment analyses identified predominantly CNS-related gene sets for CRP and each of depression and schizophrenia, and basic cellular processes for CRP and bipolar disorder. In conclusion, CRP has a markedly different genetic architecture to psychiatric disorders, but the majority of CRP associated variants are also implicated in psychiatric disorders. Shared genetic loci implicated CNS-related processes to a greater extent than immune processes, which may have implications for how we conceptualise causal relationships between CRP and psychiatric disorders.

• Campbell, Megan L.; Dalvie, Shareefa; Shadrin, Alexey; Meer, Dennis van der; O'Connell, Kevin Sean & Frei, Oleksandr [Show all 9 contributors for this article] (2023). Distributed Genetic Effects of the Corpus Callosum Subregions Suggest Links to Neuropsychiatric Disorders and Related Traits. Acta Neuropsychiatrica. ISSN 0924-2708. doi: 10.1017/neu.2023.32. Full text in Research Archive Show summary

  Background: The corpus callosum (CC) is a brain structure with a high heritability and potential role in psychiatric disorders. However, the genetic architecture of the CC and the genetic link with psychiatric disorders remain largely unclear. We investigated the genetic architectures of the volume of the CC and its subregions and the genetic overlap with psychiatric disorders. Methods: We applied multivariate genome-wide association study (GWAS) to genetic and T1-weighted magnetic resonance imaging (MRI) data of 40,894 individuals from the UK Biobank, aiming to boost genetic discovery and to assess the pleiotropic effects across volumes of the five subregions of the CC (posterior, mid-posterior, central, mid-anterior and anterior) obtained by FreeSurfer 7.1. Multivariate GWAS was run combining all subregions, co-varying for relevant variables. Gene-set enrichment analyses were performed using MAGMA. Linkage disequilibrium score regression (LDSC) was used to determine Single nucleotide polymorphism (SNP)-based heritability of total CC volume and volumes of its subregions as well as their genetic correlations with relevant psychiatric traits. Results: We identified 70 independent loci with distributed effects across the five subregions of the CC (p < 5 × 10−8). Additionally, we identified 33 significant loci in the anterior subregion, 23 in the mid-anterior, 29 in the central, 7 in the mid-posterior and 56 in the posterior subregion. Gene-set analysis revealed 156 significant genes contributing to volume of the CC subregions (p < 2.6 × 10−6). LDSC estimated the heritability of CC to (h2SNP = 0.38, SE = 0.03) and subregions ranging from 0.22 (SE = 0.02) to 0.37 (SE = 0.03). We found significant genetic correlations of total CC volume with bipolar disorder (BD, rg = −0.09, SE = 0.03; p = 5.9 × 10−3) and drinks consumed per week (rg = −0.09, SE = 0.02; p = 4.8 × 10−4), and volume of the mid-anterior subregion with BD (rg = −0.12, SE = 0.02; p = 2.5 × 10−4), major depressive disorder (MDD) (rg = −0.12, SE = 0.04; p = 3.6 × 10−3), drinks consumed per week (rg = −0.13, SE = 0.04; p = 1.8 × 10−3) and cannabis use (rg = −0.09, SE = 0.03; p = 8.4 × 10−3). Conclusions: Our results demonstrate that the CC has a polygenic architecture implicating multiple genes and show that CC subregion volumes are heritable. We found that distinct genetic factors are involved in the development of anterior and posterior subregions, consistent with their divergent functional specialisation. Significant genetic correlation between volumes of the CC and BD, drinks per week, MDD and cannabis consumption subregion volumes with psychiatric traits is noteworthy and deserving of further investigation.

• Hope, Sigrun; Shadrin, Alexey; Lin, Aihua; Bahrami, Shahram; Rødevand, Linn & Frei, Oleksandr [Show all 17 contributors for this article] (2023). Bidirectional genetic overlap between autism spectrum disorder and cognitive traits. Translational Psychiatry. 13(1), p. 1–9. doi: 10.1038/s41398-023-02563-7. Full text in Research Archive Show summary

  Autism spectrum disorder (ASD) is a highly heritable condition with a large variation in cognitive function. Here we investigated the shared genetic architecture between cognitive traits (intelligence (INT) and educational attainment (EDU)), and risk loci jointly associated with ASD and the cognitive traits. We analyzed data from genome-wide association studies (GWAS) of INT (n = 269,867), EDU (n = 766,345) and ASD (cases n = 18,381, controls n = 27,969). We used the bivariate causal mixture model (MiXeR) to estimate the total number of shared genetic variants, local analysis of co-variant annotation (LAVA) to estimate local genetic correlations, conditional false discovery rate (cond/conjFDR) to identify specific overlapping loci. The MiXeR analyses showed that 12.7k genetic variants are associated with ASD, of which 12.0k variants are shared with EDU, and 11.1k are shared with INT with both positive and negative relationships within overlapping variants. The majority (59–68%) of estimated shared loci have concordant effect directions, with a positive, albeit modest, genetic correlation between ASD and EDU (rg = 0.21, p = 2e−13) and INT (rg = 0.22, p = 4e−12). We discovered 43 loci jointly associated with ASD and cognitive traits (conjFDR<0.05), of which 27 were novel for ASD. Functional analysis revealed significant differential expression of candidate genes in the cerebellum and frontal cortex. To conclude, we quantified the genetic architecture shared between ASD and cognitive traits, demonstrated mixed effect directions, and identified the associated genetic loci and molecular pathways. The findings suggest that common genetic risk factors for ASD can underlie both better and worse cognitive functioning across the ASD spectrum, with different underlying biology.

• Bang, Lasse; Bahrami, Shahram; Hindley, Guy; Smeland, Olav Bjerkehagen; Rødevand, Linn & Jaholkowski, Piotr Pawel [Show all 18 contributors for this article] (2023). Genome-wide analysis of anorexia nervosa and major psychiatric disorders and related traits reveals genetic overlap and identifies novel risk loci for anorexia nervosa. Translational Psychiatry. 13. doi: 10.1038/s41398-023-02585-1. Full text in Research Archive Show summary

  Anorexia nervosa (AN) is a heritable eating disorder (50–60%) with an array of commonly comorbid psychiatric disorders and related traits. Although significant genetic correlations between AN and psychiatric disorders and related traits have been reported, their shared genetic architecture is largely understudied. We investigated the shared genetic architecture of AN and schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), mood instability (Mood), neuroticism (NEUR), and intelligence (INT). We applied the conditional false discovery rate (FDR) method to identify novel risk loci for AN, and conjunctional FDR to identify loci shared between AN and related phenotypes, to summarize statistics from relevant genome-wide association studies (GWAS). Individual GWAS samples varied from 72,517 to 420,879 participants. Using conditional FDR we identified 58 novel AN loci. Furthermore, we identified 38 unique loci shared between AN and major psychiatric disorders (SCZ, BIP, and MD) and 45 between AN and psychological traits (Mood, NEUR, and INT). In line with genetic correlations, the majority of shared loci showed concordant effect directions. Functional analyses revealed that the shared loci are involved in 65 unique pathways, several of which overlapped across analyses, including the “signal by MST1” pathway involved in Hippo signaling. In conclusion, we demonstrated genetic overlap between AN and major psychiatric disorders and related traits, and identified novel risk loci for AN by leveraging this overlap. Our results indicate that some shared characteristics between AN and related disorders and traits may have genetic underpinnings.

• Karadag, Naz; Shadrin, Alexey; O'Connell, Kevin Sean; Hindley, Guy Frederick Lanyon; Rahman, Zillur & Parker, Nadine [Show all 18 contributors for this article] (2023). Identification of novel genomic risk loci shared between common epilepsies and psychiatric disorders. Brain. ISSN 0006-8950. 146(8), p. 3392–3403. doi: 10.1093/brain/awad038. Full text in Research Archive Show summary

  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 <0.05, four of which were associated with all epilepsies and 39 with genetic generalized epilepsy. Most epilepsy risk loci were shared with schizophrenia (n = 31). Among the identified loci, 32 were novel for genetic generalized epilepsy, and two were novel for all epilepsies. There was a mixture of concordant and discordant allelic effects in the shared loci. The sign concordance of the identified variants was highly consistent between the discovery and independent datasets for all disorders, supporting the validity of the findings. Gene-set analysis for the shared loci between schizophrenia and genetic generalized epilepsy implicated biological processes related to cell cycle regulation, protein phosphatase activity, and membrane and vesicle function; the gene-set analyses for the other loci were underpowered. 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.

• Jaholkowski, Piotr Pawel; Hindley, Guy; Shadrin, Alexey; Tesfaye, Markos; Bahrami, Shahram & Nerhus, Mari [Show all 19 contributors for this article] (2023). Genome-wide Association Analysis of Schizophrenia and Vitamin D Levels Shows Shared Genetic Architecture and Identifies Novel Risk Loci. Schizophrenia Bulletin. ISSN 0586-7614. 49(6), p. 1654–1664. doi: 10.1093/schbul/sbad063. Full text in Research Archive Show summary

  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 < 0.05. Among the 72 shared loci, 40 loci have not previously been reported for vitD, and 9 were novel for SCZ. Further, 64% had discordant effects on SCZ-risk and vitD levels. A mixture of shared variants with concordant and discordant effects with a predominance of discordant effects was in line with weak negative genetic correlation (rg = −0.085). Our results displayed shared genetic architecture between SCZ and vitD with mixed effect directions, suggesting overlapping biological pathways. Shared genetic variants with complex overlapping mechanisms may contribute to the coexistence of SCZ and vitD deficiency and influence the clinical picture.

• Askeland, Ragna Bugge; Hannigan, Laurie John; O'Connell, Kevin Sean; Corfield, Elizabeth Claire; Frei, Oleksandr & Thapar, Anita [Show all 11 contributors for this article] (2023). Developmental manifestations of polygenic risk for bipolar disorder from infancy to middle childhood. Translational Psychiatry. 13(1). doi: 10.1038/s41398-023-02522-2. Full text in Research Archive Show summary

  Abstract Knowledge on how genetic risk for bipolar disorder manifests in developmental, emotional or behavioral traits during childhood is lacking. This issue is important to address to inform early detection and intervention efforts. We investigated whether polygenic risk for bipolar disorder is associated with developmental outcomes during early to middle childhood in the general population, and if associations differ between boys and girls. Our sample consisted of 28 001 children from the Norwegian Mother, Father and Child Cohort study, a prospective pregnancy cohort with available genotype and developmental data. Mothers reported on a range of developmental outcomes in their children at 6 and 18 months, 3, 5 and 8 years. Polygenic risk scores reflecting common variant liability to bipolar disorder were calculated. Linear regression models were used in a multi-group framework to investigate associations between polygenic risk score and developmental outcomes, using sex as a grouping variable. We found robust evidence for an association between polygenic risk scores for bipolar disorder and conduct difficulties (β = 0.041, CI = 0.020–0.062) and oppositional defiant difficulties (β = 0.032, CI = 0.014–0.051) at 8 years. Associations with most other outcomes were estimated within the region of practical equivalence to zero (equivalence range D  = −0.1 to 0.1), with the exceptions of negative association for activity levels (β = −0.028, CI = −0.047– −0.010) at age 5 and benevolence (β = −0.025, CI = –0.043 to –0.008) at age 8, and positive association for motor difficulties (β = 0.025, CI = 0.008–0.043) at age 3, inattention (β = 0.021, CI = 0.003–0.041) and hyperactivity (β = 0.025, CI = 0.006–0.044) at age 8. Our results suggest that genetic risk for bipolar disorder manifests as disruptive behaviors like oppositional defiant and conduct difficulties in childhood in the general population.

• Holen, Børge; Shadrin, Alexey; Icick, Romain; Filiz, Tahir Tekin; Hindley, Guy Frederick Lanyon & Rødevand, Linn [Show all 19 contributors for this article] (2023). Genome-wide analyses reveal novel opioid use disorder loci and genetic overlap with schizophrenia, bipolar disorder, and major depression. Addiction Biology. ISSN 1355-6215. 28(6). doi: 10.1111/adb.13282. Full text in Research Archive Show summary

  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, schizophrenia (SCZ), bipolar disorder (BD) and major depression (MD) of European ancestry. Next, we characterized the identified shared loci using biological annotation resources. OUD data were obtained from the Million Veteran Program, Yale-Penn and Study of Addiction: Genetics and Environment (SAGE) (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 were 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 condFDR < 0.05 and 7 unique loci shared between OUD and SCZ (n = 2), BD (n = 2) and MD (n = 7) at conjFDR < 0.05 with concordant effect directions, in line with estimated positive genetic correlations. Two loci were novel for OUD, one for BD and one for MD. Three OUD risk loci were shared with more than one psychiatric disorder, at DRD2 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.

• Parker, Nadine; Cheng, Weiqiu; Hindley, Guy; O'Connell, Kevin Sean; Karthikeyan, Sandeep & Holen, Børge [Show all 19 contributors for this article] (2023). Genetic Overlap Between Global Cortical Brain Structure, C-Reactive Protein, and White Blood Cell Counts. Biological Psychiatry. ISSN 0006-3223. 95(1). doi: 10.1016/j.biopsych.2023.06.008. Full text in Research Archive Show summary

  Background For many brain disorders, a subset of patients jointly exhibit alterations in cortical brain structure and elevated levels of circulating immune markers. This may be driven in part by shared genetic architecture. Therefore, we investigated the phenotypic and genetic associations linking global cortical surface area and thickness with blood immune markers (i.e., white blood cell counts and plasma C-reactive protein levels). Methods Linear regression was used to assess phenotypic associations in 30,823 UK Biobank participants. Genome-wide and local genetic correlations were assessed using linkage disequilibrium score regression and local analysis of covariance annotation. The number of shared trait-influencing genetic variants was estimated using MiXeR. Shared genetic architecture was assessed using a conjunctional false discovery rate framework, and mapped genes were included in gene-set enrichment analyses. Results Cortical structure and blood immune markers exhibited predominantly inverse phenotypic associations. There were modest genome-wide genetic correlations, the strongest of which were for C-reactive protein levels (rg_surface_area = −0.13, false discovery rate–corrected p = 4.17 × 10−3; rg_thickness = −0.13, false discovery rate–corrected p = 4.00 × 10−2). Meanwhile, local genetic correlations showed a mosaic of positive and negative associations. White blood cells shared on average 46.24% and 38.64% of trait-influencing genetic variants with surface area and thickness, respectively. Additionally, surface area shared 55 unique loci with the blood immune markers while thickness shared 15. Overall, monocyte count exhibited the largest genetic overlap with cortical brain structure. A series of gene enrichment analyses implicated neuronal-, astrocytic-, and schizophrenia-associated genes. Conclusions The findings indicate shared genetic underpinnings for cortical brain structure and blood immune markers, with implications for neurodevelopment and understanding the etiology of brain-related disorders.

• Hindley, Guy Frederick Lanyon; Shadrin, Alexey; Meer, Dennis van der; Parker, Nadine; Cheng, Weiqiu & O'Connell, Kevin Sean [Show all 23 contributors for this article] (2023). Multivariate genetic analysis of personality and cognitive traits reveals abundant pleiotropy. Nature Human Behaviour. 7, p. 1584–1600. doi: 10.1038/s41562-023-01630-9. Full text in Research Archive
• O'Connell, Kevin Sean; Koch, Elise; Lenk, Hasan Cagin; Akkouh, Ibrahim Ahmed; Hindley, Guy Frederick Lanyon & Jaholkowski, Piotr Pawel [Show all 16 contributors for this article] (2023). Polygenic overlap with body-mass index improves prediction of treatment-resistant schizophrenia. Psychiatry Research. ISSN 0165-1781. 325. doi: 10.1016/j.psychres.2023.115217. Full text in Research Archive Show summary

  Treatment resistant schizophrenia (TRS) is characterized by repeated treatment failure with antipsychotics. A recent genome-wide association study (GWAS) of TRS showed a polygenic architecture, but no significant loci were identified. Clozapine is shown to be the superior drug in terms of clinical effect in TRS; at the same time it has a serious side effect profile, including weight gain. Here, we sought to increase power for genetic discovery and improve polygenic prediction of TRS, by leveraging genetic overlap with Body Mass Index (BMI). We analysed GWAS summary statistics for TRS and BMI applying the conditional false discovery rate (cFDR) framework. We observed cross-trait polygenic enrichment for TRS conditioned on associations with BMI. Leveraging this cross-trait enrichment, we identified 2 novel loci for TRS at cFDR <0.01, suggesting a role of MAP2K1 and ZDBF2. Further, polygenic prediction based on the cFDR analysis explained more variance in TRS when compared to the standard TRS GWAS. These findings highlight putative molecular pathways which may distinguish TRS patients from treatment responsive patients. Moreover, these findings confirm that shared genetic mechanisms influence both TRS and BMI and provide new insights into the biological underpinnings of metabolic dysfunction and antipsychotic treatment.

• Jung, Kyeongmin; Yoon, Joohyun; Ahn, Yeeun; Kim, Soyeon; Shim, Injeong & Ko, Hyunwoong [Show all 23 contributors for this article] (2023). Leveraging genetic overlap between irritability and psychiatric disorders to identify genetic variants of major psychiatric disorders. Experimental and Molecular Medicine. ISSN 1226-3613. doi: 10.1038/s12276-023-01005-0. Full text in Research Archive Show summary

  Abstract Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [ n ] of additional SNPs = 105), BD I ( n  = 54), MDD ( n  = 107), and irritability ( n  = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.

• Holen, Børge; Kutrolli, Gleda; Shadrin, Alexey; Icick, Romain; Hindley, Guy & Rødevand, Linn [Show all 16 contributors for this article] (2023). Genome-wide analyses reveal shared genetic architecture and novel risk loci between opioid use disorder and general cognitive ability. Drug and Alcohol Dependence. ISSN 0376-8716. 256. doi: 10.1016/j.drugalcdep.2023.111058. Full text in Research Archive Show summary

  Background Opioid use disorder (OUD), a serious health burden worldwide, is associated with lower cognitive function. Recent studies have demonstrated a negative genetic correlation between OUD and general cognitive ability (COG), indicating a shared genetic basis. However, the specific genetic variants involved, and the underlying molecular mechanisms remain poorly understood. Here, we aimed to quantify and identify the genetic basis underlying OUD and COG. Methods We quantified the extent of genetic overlap between OUD and COG using a bivariate causal mixture model (MiXeR) and identified specific genetic loci applying conditional/conjunctional FDR. Finally, we investigated biological function and expression of implicated genes using available resources. Results We estimated that ~94% of OUD variants (4.8k out of 5.1k variants) also influence COG. We identified three novel OUD risk loci and one locus shared between OUD and COG. Loci identified implicated biological substrates in the basal ganglia. Conclusion We provide new insights into the complex genetic risk architecture of OUD and its genetic relationship with COG.

• Woldeyohannes, Markos Tesfaye; Jaholkowski, Piotr Pawel; Hindley, Guy; Shadrin, Alexey; Rahman, Zillur & Bahrami, Shahram [Show all 17 contributors for this article] (2023). Shared genetic architecture between irritable bowel syndrome and psychiatric disorders reveals molecular pathways of the gut-brain axis. Genome Medicine. 15(1). doi: 10.1186/s13073-023-01212-4. Full text in Research Archive Show summary

  Background: Irritable bowel syndrome (IBS) often co-occurs with psychiatric and gastrointestinal disorders. A recent genome-wide association study (GWAS) identified several genetic risk variants for IBS. However, most of the heritability remains unidentified, and the genetic overlap with psychiatric and somatic disorders is not quantified beyond genome-wide genetic correlations. Here, we characterize the genetic architecture of IBS, further, investigate its genetic overlap with psychiatric and gastrointestinal phenotypes, and identify novel genomic risk loci. Methods: Using GWAS summary statistics of IBS (53,400 cases and 433,201 controls), and psychiatric and gastrointestinal phenotypes, we performed bivariate casual mixture model analysis to characterize the genetic architecture and genetic overlap between these phenotypes. We leveraged identified genetic overlap to boost the discovery of genomic loci associated with IBS, and to identify specific shared loci associated with both IBS and psychiatric and gastrointestinal phenotypes, using the conditional/conjunctional false discovery rate (condFDR/conjFDR) framework. We used functional mapping and gene annotation (FUMA) for functional analyses. Results: IBS was highly polygenic with 12k trait-influencing variants. We found extensive polygenic overlap between IBS and psychiatric disorders and to a lesser extent with gastrointestinal diseases. We identified 132 independent IBS-associated loci (condFDR < 0.05) by conditioning on psychiatric disorders (n = 127) and gastrointestinal diseases (n = 24). Using conjFDR, 70 unique loci were shared between IBS and psychiatric disorders. Functional analyses of shared loci revealed enrichment for biological pathways of the nervous and immune systems. Genetic correlations and shared loci between psychiatric disorders and IBS subtypes were different. Conclusions: We found extensive polygenic overlap of IBS and psychiatric and gastrointestinal phenotypes beyond what was revealed with genetic correlations. Leveraging the overlap, we discovered genetic loci associated with IBS which implicate a wide range of biological pathways beyond the gut-brain axis. Genetic differences may underlie the clinical subtype of IBS. These results increase our understanding of the pathophysiology of IBS which may form the basis for the development of individualized interventions.

• Cheng, Weiqiu; Parker, Nadine; Karadag, Naz; Koch, Elise; Hindley, Guy Frederick Lanyon & Icick, Romain [Show all 22 contributors for this article] (2023). The relationship between cannabis use, schizophrenia, and bipolar disorder: a genetically informed study. The Lancet Psychiatry. ISSN 2215-0374. 10(6), p. 441–451. doi: 10.1016/S2215-0366(23)00143-8. Full text in Research Archive Show summary

  Background The relationship between psychotic disorders and cannabis use is heavily debated. Shared underlying genetic risk is one potential explanation. We investigated the genetic association between psychotic disorders (schizophrenia and bipolar disorder) and cannabis phenotypes (lifetime cannabis use and cannabis use disorder). Methods We used genome-wide association summary statistics from individuals with European ancestry from the Psychiatric Genomics Consortium, UK Biobank, and International Cannabis Consortium. We estimated heritability, polygenicity, and discoverability of each phenotype. We performed genome-wide and local genetic correlations. Shared loci were identified and mapped to genes, which were tested for functional enrichment. Shared genetic liabilities to psychotic disorders and cannabis phenotypes were explored using causal analyses and polygenic scores, using the Norwegian Thematically Organized Psychosis cohort. Findings Psychotic disorders were more heritable than cannabis phenotypes and more polygenic than cannabis use disorder. We observed positive genome-wide genetic correlations between psychotic disorders and cannabis phenotypes (range 0·22–0·35) with a mixture of positive and negative local genetic correlations. Three to 27 shared loci were identified for the psychotic disorder and cannabis phenotype pairs. Enrichment of mapped genes implicated neuronal and olfactory cells as well as drug–gene targets for nicotine, alcohol, and duloxetine. Psychotic disorders showed a causal effect on cannabis phenotypes, and lifetime cannabis use had a causal effect on bipolar disorder. Of 2181 European participants from the Norwegian Thematically Organized Psychosis cohort applied in polygenic risk score analyses, 1060 (48·6%) were females and 1121 (51·4%) were males (mean age 33·1 years [SD 11·8]). 400 participants had bipolar disorder, 697 had schizophrenia, and 1044 were healthy controls. Within this sample, polygenic scores for cannabis phenotypes predicted psychotic disorders independently and improved prediction beyond the polygenic score for the psychotic disorders. Interpretation A subgroup of individuals might have a high genetic risk of developing a psychotic disorder and using cannabis. This finding supports public health efforts to reduce cannabis use, particularly in individuals at high risk or patients with psychotic disorders. Identified shared loci and their functional implications could facilitate development of novel treatments.

• Smith, Robert Løvsletten; Wollmann, Birgit Malene Tovik; Kausberg, Marianne; Mæland, Sondre; Tveito, Marit & O'Connell, Kevin Sean [Show all 8 contributors for this article] (2022). Effects of a Novel UGT2B Haplotype and UGT1A4*3 Allele Variants on Glucuronidation of Clozapine In vivo. Current drug metabolism. ISSN 1389-2002. 23(1), p. 66–72. doi: 10.2174/1389200223666220201152953. Full text in Research Archive Show summary

  Background: Glucuronidation is an important metabolic pathway of clozapine (CLZ), but the impact of various uridine 5'diphospho-glucuronosyltransferases (UGT) polymorphisms on the exposure and metabolism of CLZ in vivo is unclear. Objective: The objective of this study was to investigate the impact of UGT2B haplotype and UGT1A4*3 allele variants on the formation of CLZ glucuronide metabolites (5N- and N+-glucuronide) and CLZ exposure in patients’ serum after adjusting for sex, age, and smoking habits. Methods: The study was based on serum samples from CLZ-treated patients (n=79) subjected to routine therapeutic drug monitoring (TDM) at Diakonhjemmet Hospital, Oslo, Norway. From the same patients, the following UGT variants were genotyped using Real-Time PCR: UGT2B:GA haplotype (defined as UGT2B:GA; rs1513559A>G and rs416593T>A) and UGT1A4*3 (rs2011425T>G). Serum concentrations of CLZ 5N- and N+-glucuronide were measured by UPLC high-resolution mass spectrometry. Results: None of the genotypes had significant impact on CLZ exposure (p>0.05). However, compared to UGT2B:AT/AT and UGT1A4*1/*1, the 5N-glucuronide exposure was reduced in UGT2B:GA/GA carriers (-75 %, p=0.03) while the exposure was non-significantly increased in UGT1A4*3 carriers (+100 %, p=0.14), respectively. The N+-glucuronide exposure was unchanged in UGT1A4*3 vs. noncarriers (p=0.28), but significantly reduced in heterozygous (-50 %, p=0.016) and homozygous carriers (-70 %, p=0.021) of UGT2B:GA compared to UGT2B:AT/AT carriers, respectively. Conclusion: The UGT2B:GA and UGT1A4*3 variants had no impact on CLZ exposure but were associated with differences and preferences in CLZ glucuronidation. The latter might be of potential relevance for CLZ tolerability since levels of the N+-glucuronide metabolite may reflect the generation and trapping of reactive metabolites involved in CLZ-induced toxicity

• Jensen, Søren Beck; Sheikh, Mashhood Ahmed; Akkouh, Ibrahim Ahmed; Szabo, Attila; O'Connell, Kevin Sean & Lekva, Tove [Show all 23 contributors for this article] (2022). Elevated Systemic Levels of Markers Reflecting Intestinal Barrier Dysfunction and Inflammasome Activation Are Correlated in Severe Mental Illness. Schizophrenia Bulletin. ISSN 0586-7614. 49(3), p. 635–645. doi: 10.1093/schbul/sbac191. Full text in Research Archive Show summary

  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.

• Sheikh, Mashhood Ahmed; O'Connell, Kevin Sean; Lekva, Tove; Szabo, Attila; Akkouh, Ibrahim Ahmed & Osete, Jordi Requena [Show all 31 contributors for this article] (2022). Systemic cell adhesion molecules in severe mental illness: Potential role of intercellular CAM-1 in linking peripheral and neuroinflammation. Biological Psychiatry. ISSN 0006-3223. 93, p. 187–196. doi: 10.1016/j.biopsych.2022.06.029. Full text in Research Archive Show summary

  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.

• Bahrami, Shahram; Hindley, Guy Frederick Lanyon; Winsvold, Bendik K S; O'Connell, Kevin Sean; Frei, Oleksandr & Shadrin, Alexey [Show all 39 contributors for this article] (2022). Dissecting the shared genetic basis of migraine and mental disorders using novel statistical tools. Brain. ISSN 0006-8950. 145(1), p. 142–153. doi: 10.1093/brain/awab267. Full text in Research Archive Show summary

  Migraine is three times more prevalent in people with bipolar disorder or depression. The relationship between schizophrenia and migraine is less certain although glutamatergic and serotonergic neurotransmission are implicated in both. A shared genetic basis to migraine and mental disorders has been suggested but previous studies have reported weak or non-significant genetic correlations and five shared risk loci. Using the largest samples to date and novel statistical tools, we aimed to determine the extent to which migraine’s polygenic architecture overlaps with bipolar disorder, depression and schizophrenia beyond genetic correlation, and to identify shared genetic loci. Summary statistics from genome-wide association studies were acquired from large-scale consortia for migraine (n cases = 59 674; n controls = 316 078), bipolar disorder (n cases = 20 352; n controls = 31 358), depression (n cases = 170 756; n controls = 328 443) and schizophrenia (n cases = 40 675, n controls = 64 643). We applied the bivariate causal mixture model to estimate the number of disorder-influencing variants shared between migraine and each mental disorder, and the conditional/conjunctional false discovery rate method to identify shared loci. Loci were functionally characterized to provide biological insights. Univariate MiXeR analysis revealed that migraine was substantially less polygenic (2.8 K disorder-influencing variants) compared to mental disorders (8100–12 300 disorder-influencing variants). Bivariate analysis estimated that 800 (SD = 300), 2100 (SD = 100) and 2300 (SD = 300) variants were shared between bipolar disorder, depression and schizophrenia, respectively. There was also extensive overlap with intelligence (1800, SD = 300) and educational attainment (2100, SD = 300) but not height (1000, SD = 100). We next identified 14 loci jointly associated with migraine and depression and 36 loci jointly associated with migraine and schizophrenia, with evidence of consistent genetic effects in independent samples. No loci were associated with migraine and bipolar disorder. Functional annotation mapped 37 and 298 genes to migraine and each of depression and schizophrenia, respectively, including several novel putative migraine genes such as L3MBTL2, CACNB2 and SLC9B1. Gene-set analysis identified several putative gene sets enriched with mapped genes including transmembrane transport in migraine and schizophrenia. Most migraine-influencing variants were predicted to influence depression and schizophrenia, although a minority of mental disorder-influencing variants were shared with migraine due to the difference in polygenicity. Similar overlap with other brain-related phenotypes suggests this represents a pool of ‘pleiotropic’ variants that influence vulnerability to diverse brain-related disorders and traits. We also identified specific loci shared between migraine and each of depression and schizophrenia, implicating shared molecular mechanisms and highlighting candidate migraine genes for experimental validation.

• Motazedi, Ehsan; Cheng, Weiqiu; Thomassen, Jesper Qvist; Frei, Oleksandr; Rongve, Arvid & Athanasiu, Lavinia [Show all 30 contributors for this article] (2022). Using Polygenic Hazard Scores to Predict Age at Onset of Alzheimer's Disease in Nordic Populations. Journal of Alzheimer's Disease. ISSN 1387-2877. 88(4), p. 1533–1544. doi: 10.3233/JAD-220174. Full text in Research Archive Show summary

  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.

• Cheng, Weiqiu; Meer, Dennis van der; Parker, Nadine; Hindley, Guy Frederick Lanyon; O'Connell, Kevin Sean & Wang, Yunpeng [Show all 20 contributors for this article] (2022). Shared genetic architecture between schizophrenia and subcortical brain volumes implicates early neurodevelopmental processes and brain development in childhood. Molecular Psychiatry. ISSN 1359-4184. doi: 10.1038/s41380-022-01751-z. Full text in Research Archive Show summary

  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.

• Hindley, Guy Frederick Lanyon; O'Connell, Kevin Sean; Rahman, Zillur; Frei, Oleksandr; Bahrami, Shahram & Shadrin, Alexey [Show all 17 contributors for this article] (2022). The shared genetic basis of mood instability and psychiatric disorders: A cross-trait genome-wide association analysis. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics. ISSN 1552-4841. 189(6), p. 207–218. doi: 10.1002/ajmg.b.32907. Full text in Research Archive Show summary

  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.

• Hindley, Guy; Frei, Oleksandr; Shadrin, Alexey; Cheng, Weiqiu; O'Connell, Kevin Sean & Icick, Romain [Show all 17 contributors for this article] (2022). Charting the Landscape of Genetic Overlap Between Mental Disorders and Related Traits Beyond Genetic Correlation. American Journal of Psychiatry. ISSN 0002-953X. 179(11), p. 833–843. doi: 10.1176/appi.ajp.21101051. Full text in Research Archive
• Meer, Dennis van der; Shadrin, Alexey; O'Connell, Kevin Sean; Bettella, Francesco; Djurovic, Srdjan & Wolfers, Thomas [Show all 17 contributors for this article] (2022). Boosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphology. Biological Psychiatry. ISSN 0006-3223. 92(4), p. 291–298. doi: 10.1016/j.biopsych.2021.12.007. Full text in Research Archive Show summary

  Background Schizophrenia is a complex polygenic disorder with subtle, distributed abnormalities in brain morphology. There are indications of shared genetic architecture between schizophrenia and brain measures despite low genetic correlations. Through the use of analytical methods that allow for mixed directions of effects, this overlap may be leveraged to improve our understanding of underlying mechanisms of schizophrenia and enrich polygenic risk prediction outcome. Methods We ran a multivariate genome-wide analysis of 175 brain morphology measures using data from 33,735 participants of the UK Biobank and analyzed the results in a conditional false discovery rate together with schizophrenia genome-wide association study summary statistics of the Psychiatric Genomics Consortium (PGC) Wave 3. We subsequently created a pleiotropy-enriched polygenic score based on the loci identified through the conditional false discovery rate approach and used this to predict schizophrenia in a nonoverlapping sample of 743 individuals with schizophrenia and 1074 healthy controls. Results We found that 20% of the loci and 50% of the genes significantly associated with schizophrenia were also associated with brain morphology. The conditional false discovery rate analysis identified 428 loci, including 267 novel loci, significantly associated with brain-linked schizophrenia risk, with functional annotation indicating high relevance for brain tissue. The pleiotropy-enriched polygenic score explained more variance in liability than conventional polygenic scores across several scenarios. Conclusions Our results indicate strong genetic overlap between schizophrenia and brain morphology with mixed directions of effect. The results also illustrate the potential of exploiting polygenetic overlap between brain morphology and mental disorders to boost discovery of brain tissue–specific genetic variants and its use in polygenic risk frameworks.

• Lenk, Hasan Cagin; Smith, Robert Løvsletten; O'Connell, Kevin Sean; Jukić, Marin M.; Kringen, Marianne K. & Andreassen, Ole [Show all 8 contributors for this article] (2022). Impact of NFIB and CYP1A variants on clozapine serum concentration—A retrospective naturalistic cohort study on 526 patients with known smoking habits. Clinical and Translational Science (CTS). ISSN 1752-8054. 16(1), p. 62–72. doi: 10.1111/cts.13422. Full text in Research Archive Show summary

  Clinical response of clozapine is closely associated with serum concentration. Although tobacco smoking is the key environmental factor underlying interindividual variability in clozapine metabolism, recent genome-wide studies suggest that CYP1A and NFIB genetic variants may also be of significant importance, but their quantitative impact is unclear. We investigated the effects of the rs2472297 C>T (CYP1A) and rs28379954 T>C (NFIB) polymorphisms on serum concentrations in smokers and nonsmokers. The study retrospectively included 526 patients with known smoking habits (63.7% smokers) from a therapeutic drug monitoring service in Norway. Clozapine dose-adjusted concentrations (C/D) and patient proportions with subtherapeutic levels (<1070 nmol/L) were compared between CYP1A/NFIB variant allele carriers and homozygous wild-type carriers (noncarriers), in both smokers and nonsmokers. Clozapine C/D was reduced in patients carrying CYP1A-T and NFIB-C variants versus noncarriers, both among smokers (−48%; p < 0.0001) and nonsmokers (−35%; p = 0.028). Patients who smoke carrying CYP1A-T and NFIB-C variants had a 66% reduction in clozapine C/D versus nonsmoking noncarriers (p < 0.0001). The patient proportion with subtherapeutic levels was 2.9-fold higher in patients who smoke carrying NFIB-C and CYP1A-T variants versus nonsmoking noncarriers (p < 0.0001). In conclusion, CYP1A and NFIB variants have significant and additive impact on clozapine dose requirements for reaching target serum concentrations. Patients who smoke carrying the studied CYP1A and NFIB variants, comprising 2.5% of the study population, may need threefold higher doses to prevent risk of clozapine undertreatment. The results suggest that pre-emptive genotyping of NFIB and CYP1A may be utilized to guide clozapine dosing and improve clinical outcomes in patients with treatment-resistant schizophrenia.

• Kappel, Djenifer B.; Legge, Sophie E.; Hubbard, Leon; Willcocks, Isabella R.; O'Connell, Kevin Sean & Smith, Robert Løvsletten [Show all 15 contributors for this article] (2022). Genomic Stratification of Clozapine Prescription Patterns Using Schizophrenia Polygenic Scores. Biological Psychiatry. ISSN 0006-3223. 93(2), p. 149–156. doi: 10.1016/j.biopsych.2022.07.014. Full text in Research Archive Show summary

  Background Treatment-resistant schizophrenia affects approximately 30% of individuals with the disorder. Clozapine is the medication of choice in treatment-resistant schizophrenia, but optimizing administration and dose titration is complex. The identification of factors influencing clozapine prescription and response, including genetics, is of interest in a precision psychiatry framework. Methods We used linear regression models accounting for demographic, pharmacological, and clinical covariates to determine whether a polygenic risk score (PRS) for schizophrenia would be associated with the highest dose recorded during clozapine treatment. Analyses were performed across 2 independent multiancestry samples of individuals from a UK patient monitoring system, CLOZUK2 (n = 3133) and CLOZUK3 (n = 909), and a European sample from a Norwegian therapeutic drug monitoring service (n = 417). In a secondary analysis merging both UK cohorts, logistic regression models were used to estimate the relationship between schizophrenia PRSs and clozapine doses classified as low, standard, or high. Results After controlling for relevant covariates, the schizophrenia PRS was correlated with the highest clozapine dose on record for each individual across all samples: CLOZUK2 (β = 12.22, SE = 3.78, p = .001), CLOZUK3 (β = 12.73, SE = 5.99, p = .034), and the Norwegian cohort (β = 46.45, SE = 18.83, p = .014). In a secondary analysis, the schizophrenia PRS was associated with taking clozapine doses >600 mg/day (odds ratio = 1.279, p = .006). Conclusions The schizophrenia PRS was associated with the highest clozapine dose prescribed for an individual in records from 3 independent samples, suggesting that the genetic liability for schizophrenia might index factors associated with therapeutic decisions in cohorts of patients with treatment-resistant schizophrenia.

• Torgersen, Kristin Stensland; Rahman, Zillur; Bahrami, Shahram; Hindley, Guy Frederick Lanyon; Parker, Nadine & Frei, Oleksandr [Show all 14 contributors for this article] (2022). Shared genetic loci between depression and cardiometabolic traits. PLoS Genetics. ISSN 1553-7390. 18(5). doi: 10.1371/journal.pgen.1010161. Full text in Research Archive Show summary

  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.

• Icick, Romain; Shadrin, Alexey; Holen, Børge; Karadag, Naz; Lin, Aihua & Hindley, Guy [Show all 17 contributors for this article] (2022). Genetic overlap between mood instability and alcohol-related phenotypes suggests shared biological underpinnings. Neuropsychopharmacology. ISSN 0893-133X. 47, p. 1883–1891. doi: 10.1038/s41386-022-01401-6. Full text in Research Archive
• Cheng, Weiqiu; Frei, Oleksandr; Meer, Dennis van der; Wang, Yunpeng; O`Connell, Kevin & Chu, Yunhan [Show all 20 contributors for this article] (2021). Genetic Association Between Schizophrenia and Cortical Brain Surface Area and Thickness. JAMA psychiatry. ISSN 2168-6238. 78(9), p. 1020–1030. doi: 10.1001/jamapsychiatry.2021.1435. Full text in Research Archive Show summary

  Importance Schizophrenia is a complex heritable disorder associated with many genetic variants, each with a small effect. While cortical differences between patients with schizophrenia and healthy controls are consistently reported, the underlying molecular mechanisms remain elusive. Objective To investigate the extent of shared genetic architecture between schizophrenia and brain cortical surface area (SA) and thickness (TH) and to identify shared genomic loci. Design, Setting, and Participants Independent genome-wide association study data on schizophrenia (Psychiatric Genomics Consortium and CLOZUK: n = 105 318) and SA and TH (UK Biobank: n = 33 735) were obtained. The extent of polygenic overlap was investigated using MiXeR. The specific shared genomic loci were identified by conditional/conjunctional false discovery rate analysis and were further examined in 3 independent cohorts. Data were collected from December 2019 to February 2021, and data analysis was performed from May 2020 to February 2021. Main Outcomes and Measures The primary outcomes were estimated fractions of polygenic overlap between schizophrenia, total SA, and average TH and a list of functionally characterized shared genomic loci. Results Based on genome-wide association study data from 139 053 participants, MiXeR estimated schizophrenia to be more polygenic (9703 single-nucleotide variants [SNVs]) than total SA (2101 SNVs) and average TH (1363 SNVs). Most SNVs associated with total SA (1966 of 2101 [93.6%]) and average TH (1322 of 1363 [97.0%]) may be associated with the development of schizophrenia. Subsequent conjunctional false discovery rate analysis identified 44 and 23 schizophrenia risk loci shared with total SA and average TH, respectively. The SNV associations of shared loci between schizophrenia and total SA revealed en masse concordant association between the discovery and independent cohorts. After removing high linkage disequilibrium regions, such as the major histocompatibility complex region, the shared loci were enriched in immunologic signature gene sets. Polygenic overlap and shared loci between schizophrenia and schizophrenia-associated regions of interest for SA (superior frontal and middle temporal gyri) and for TH (superior temporal, inferior temporal, and superior frontal gyri) were also identified. Conclusions and Relevance This study demonstrated shared genetic loci between cortical morphometry and schizophrenia, among which a subset are associated with immunity. These findings provide an insight into the complex genetic architecture and associated with schizophrenia.

• Torgersen, Kristin Stensland; Bahrami, Shahram; Frei, Oleksandr; Shadrin, Alexey; O'Connell, Kevin Sean & Smeland, Olav Bjerkehagen [Show all 10 contributors for this article] (2021). Shared genetic architecture between neuroticism, coronary artery disease and cardiovascular risk factors. Translational Psychiatry. 11(1), p. 1–13. doi: 10.1038/s41398-021-01466-9. Full text in Research Archive Show summary

  Neuroticism is associated with poor health, cardiovascular disease (CVD) risk factors and coronary artery disease (CAD). The conditional/conjunctional false discovery rate method (cond/conjFDR) was applied to genome wide association study (GWAS) summary statistics on neuroticism (n = 432,109), CAD (n = 184,305) and 12 CVD risk factors (n = 188,577–339,224) to investigate genetic overlap between neuroticism and CAD and CVD risk factors. CondFDR analyses identified 729 genomic loci associated with neuroticism after conditioning on CAD and CVD risk factors. The conjFDR analyses revealed 345 loci jointly associated with neuroticism and CAD (n = 30), body mass index (BMI) (n = 96) or another CVD risk factor (n = 1–60). Several loci were jointly associated with neuroticism and multiple CVD risk factors. Seventeen of the shared loci with CAD and 61 of the shared loci with BMI are novel for neuroticism. 21 of 30 (70%) neuroticism risk alleles were associated with higher CAD risk. Functional analyses of the genes mapped to the shared loci implicated cell division, nuclear receptor, elastic fiber formation as well as starch and sucrose metabolism pathways. Our results indicate polygenic overlap between neuroticism and CAD and CVD risk factors, suggesting that genetic factors may partly cause the comorbidity. This gives new insight into the shared molecular genetic basis of these conditions.

• Monereo-Sánchez, Jennifer; Schram, Miranda T.; Frei, Oleksandr; O'Connell, Kevin Sean; Shadrin, Alexey & Smeland, Olav Bjerkehagen [Show all 11 contributors for this article] (2021). Genetic Overlap Between Alzheimer’s Disease and Depression Mapped Onto the Brain. Frontiers in Neuroscience. ISSN 1662-4548. 15, p. 1–9. doi: 10.3389/fnins.2021.653130. Full text in Research Archive Show summary

  Background: Alzheimer’s disease (AD) and depression are debilitating brain disorders that are often comorbid. Shared brain mechanisms have been implicated, yet findings are inconsistent, reflecting the complexity of the underlying pathophysiology. As both disorders are (partly) heritable, characterising their genetic overlap may provide aetiological clues. While previous studies have indicated negligible genetic correlations, this study aims to expose the genetic overlap that may remain hidden due to mixed directions of effects. Methods: We applied Gaussian mixture modelling, through MiXeR, and conjunctional false discovery rate (cFDR) analysis, through pleioFDR, to genome-wide association study (GWAS) summary statistics of AD ( n = 79,145) and depression ( n = 450,619). The effects of identified overlapping loci on AD and depression were tested in 403,029 participants of the UK Biobank (UKB) (mean age 57.21, 52.0% female), and mapped onto brain morphology in 30,699 individuals with brain MRI data. Results: MiXer estimated 98 causal genetic variants overlapping between the 2 disorders, with 0.44 concordant directions of effects. Through pleioFDR, we identified a SNP in the TMEM106B gene, which was significantly associated with AD ( B = −0.002, p = 9.1 × 10 –4 ) and depression ( B = 0.007, p = 3.2 × 10 –9 ) in the UKB. This SNP was also associated with several regions of the corpus callosum volume anterior ( B &amp;gt; 0.024, p &amp;lt; 8.6 × 10 –4 ), third ventricle volume ventricle ( B = −0.025, p = 5.0 × 10 –6 ), and inferior temporal gyrus surface area ( B = 0.017, p = 5.3 × 10 –4 ). Discussion: Our results indicate there is substantial genetic overlap, with mixed directions of effects, between AD and depression. These findings illustrate the value of biostatistical tools that capture such overlap, providing insight into the genetic architectures of these disorders.

• Bahrami, Shahram; Shadrin, Alexey A.; Frei, Oleksandr; O`Connell, Kevin; Bettella, Francesco & Krull, Florian [Show all 15 contributors for this article] (2021). Genetic loci shared between major depression and intelligence with mixed directions of effect. Nature Human Behaviour. p. 1–9. doi: 10.1038/s41562-020-01031-2. Full text in Research Archive
• Wiström, Erik David; O'Connell, Kevin Sean; Karadag, Naz; Bahrami, Shahram; Hindley, Guy Frederick Lanyon & Lin, Aihua [Show all 14 contributors for this article] (2021). Genome-wide analysis reveals genetic overlap between alcohol use behaviours, schizophrenia and bipolar disorder and identifies novel shared risk loci. Addiction. ISSN 0965-2140. 117(3). doi: 10.1111/add.15680. Full text in Research Archive Show summary

  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 <0.05. Findings Conditional Q-Q plots showed single-nucleotide polymorphism (SNP) enrichment for both alcohol traits across different levels of significance with SCZ and BD, and vice versa. Using conjFDR analysis we leveraged this genetic enrichment and identified several loci shared between SCZ and AUD (n = 28) and AC (n = 24), BD and AUD (n = 2) and AC (n = 8) at conjFDR <0.05. Among these loci, 24 are novel for AUD, 15 are novel for AC, three are novel for SCZ and one is novel for BD. There was a mixture of same and opposite effect directions among the shared loci. Conclusions Alcohol use disorder and alcohol consumption share genomic loci with the psychiatric disorders schizophrenia and bipolar disorder with a mixed pattern of effect directions, indicating a complex genetic relationship between the phenotypes.

• Rødevand, Linn; Bahrami, Shahram; Frei, Oleksandr; Chu, Yunhan; Shadrin, Alexey A. & O'Connell, Kevin Sean [Show all 14 contributors for this article] (2021). Extensive bidirectional genetic overlap between bipolar disorder and cardiovascular disease phenotypes. Translational Psychiatry. 11. doi: 10.1038/s41398-021-01527-z. Full text in Research Archive Show summary

  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 < 0.05, we identified 129 shared loci between BIP and CVD phenotypes, mainly BMI (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.

• Szabo, Attila; O'Connell, Kevin Sean; Ueland, Thor; Sheikh, Mashhood Ahmed; Agartz, Ingrid & Andreou, Dimitrios [Show all 31 contributors for this article] (2021). Increased circulating IL-18 levels in severe mental disorders indicate systemic inflammasome activation. Brain, Behavior, and Immunity. ISSN 0889-1591. 99, p. 299–306. doi: 10.1016/j.bbi.2021.10.017. Full text in Research Archive Show summary

  Background Schizophrenia (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. Methods We 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. Results We report higher baseline levels of circulating IL-18 system components (IL-18, IL-18BPA, IL-18R1), and 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 types and the expression of inflammasome system elements in SMI. Conclusions Based on these results, we suggest a role for inflammasome activation/dysregulation in SMI. Our findings further the understanding of possible underlying inflammatory mechanisms and may expose important therapeutic targets in SMI.

• O'Connell, Kevin Sean & Coombes, Brandon J. (2021). Genetic contributions to bipolar disorder: Current status and future directions. Psychological Medicine. ISSN 0033-2917. 51(13), p. 2156–2167. doi: 10.1017/S0033291721001252. Full text in Research Archive Show summary

  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.

• Fjukstad, Katrine Kveli; Athanasiu, Lavinia; Bahrami, Shahram; O`Connell, Kevin; Meer, Dennis van der & Bettella, Francesco [Show all 11 contributors for this article] (2021). Genetic variants associated with cardiometabolic abnormalities during treatment with selective serotonin reuptake inhibitors: a genome-wide association study. The Pharmacogenomics Journal. ISSN 1470-269X. 21, p. 574–585. doi: 10.1038/s41397-021-00234-8. Full text in Research Archive Show summary

  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.

• O'Connell, Kevin Sean; Frei, Oleksandr; Bahrami, Shahram; Smeland, Olav Bjerkehagen; Bettella, Francesco & Cheng, Weiqiu [Show all 16 contributors for this article] (2021). Characterizing the Genetic Overlap Between Psychiatric Disorders and Sleep-Related Phenotypes. Biological Psychiatry. ISSN 0006-3223. 90(9), p. 1–11. doi: 10.1016/j.biopsych.2021.07.007. Full text in Research Archive Show summary

  Background: A range of sleep disturbances are commonly experienced by patients with psychiatric disorders, and genome-wide genetic analyses have shown some significant genetic correlations between these traits. Here, we applied novel statistical genetic methodologies to better characterize the potential shared genetic architecture between sleep-related phenotypes and psychiatric disorders. Methods: Using the MiXeR method, which can estimate polygenic overlap beyond genetic correlation, the shared genetic architecture between major psychiatric disorders (bipolar disorder [N = 51,710], depression [N = 480,359], and schizophrenia [N = 77,096]) and sleep-related phenotypes (chronotype [N = 449,734], insomnia [N = 386,533] and sleep duration [N = 446,118]) were quantified on the basis of genetic summary statistics. Furthermore, the conditional/conjunctional false discovery rate framework was used to identify specific shared loci between these phenotypes, for which positional and functional annotation were conducted with FUMA. Results: Extensive genetic overlap between the sleep-related phenotypes and bipolar disorder (63%–77%), depression (76%–79%), and schizophrenia (64%–79%) was identified, with moderate levels of congruence between most investigated traits (47%–58%). Specific shared loci were identified for all bivariate analyses, and a subset of 70 credible genes were mapped to these shared loci. Conclusions: The current results provide evidence for substantial polygenic overlap between psychiatric disorders and sleep-related phenotypes, beyond genetic correlation (|rg| = 0.02 to 0.42). Moderate congruency within the shared genetic components suggests a complex genetic relationship and potential subgroups with higher or lower genetic concordance. This work provides new insights and understanding of the shared genetic etiology of sleep-related phenotypes and psychiatric disorders and highlights new opportunities and avenues for future investigation.

• Krull, Florian; Akkouh, Ibrahim Ahmed; Hughes, Timothy; Bettella, Francesco; Athanasiu, Lavinia & Smeland, Olav Bjerkehagen [Show all 12 contributors for this article] (2021). Dose-dependent transcriptional effects of lithium and adverse effect burden in a psychiatric cohort. Progress in Neuro-psychopharmacology and Biological Psychiatry. ISSN 0278-5846. 112. doi: 10.1016/j.pnpbp.2021.110408. Full text in Research Archive Show summary

  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.

• Hindley, Guy Frederick Lanyon; Bahrami, Shahram; Steen, Nils Eiel; O'Connell, Kevin Sean; Frei, Oleksandr & Shadrin, Alexey [Show all 13 contributors for this article] (2021). Characterising the shared genetic determinants of bipolar disorder, schizophrenia and risk-taking. Translational Psychiatry. 11:466, p. 1–10. doi: 10.1038/s41398-021-01576-4. Full text in Research Archive Show summary

  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.

• Mullins, Niamh; Forstner, Andreas J.; O'Connell, Kevin Sean; Coombes, Brandon; Coleman, Jonathan R. I. & Qiao, Zhen [Show all 59 contributors for this article] (2021). Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nature Genetics. ISSN 1061-4036. 53, p. 817–829. doi: 10.1038/s41588-021-00857-4. Full text in Research Archive
• Kalman, Janos L.; Loohuis, Loes M. Olde; Vreeker, Annabel; McQuillin, Andrew; Stahl, Eli A. & Ruderfer, Douglas [Show all 50 contributors for this article] (2021). Characterisation of age and polarity at onset in bipolar disorder. British Journal of Psychiatry. ISSN 0007-1250. 219(6), p. 659–669. doi: 10.1192/bjp.2021.102. Full text in Research Archive Show summary

  Background Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools. Aims To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics. Method Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts. Results Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 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. Conclusions AAO and PAO are associated with indicators of bipolar disorder 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.

• Bahrami, Shahram; Steen, Nils Eiel; Shadrin, Alexey A.; O`Connell, Kevin; Frei, Oleksandr & Bettella, Francesco [Show all 13 contributors for this article] (2020). Shared genetic loci between body mass index and major psychiatric disorders: A genome-wide association study. JAMA psychiatry. ISSN 2168-6238. 77(5), p. 503–512. doi: 10.1001/jamapsychiatry.2019.4188. Full text in Research Archive Show summary

  IMPORTANCE People with major psychiatric disorders (MPDs) have a 10- to 20-year shorter life span than the rest of the population, and this difference is mainly due to comorbid cardiovascular diseases. Genome-wide association studies have identified common variants involved in schizophrenia (SCZ), bipolar disorder (BIP), and major depression (MD) and body mass index (BMI), a key cardiometabolic risk factor. However, genetic variants jointly influencing MPD and BMI remain largely unknown. OBJECTIVE To assess the extent of the overlap between the genetic architectures of MPDs and BMI and identify genetic loci shared between them. DESIGN, SETTING, AND PARTICIPANTS Using a conditional false discovery rate statistical framework, independent genome-wide association study data on individuals with SCZ (n = 82 315), BIP (n = 51 710), MD (n = 480 359), and BMI (n = 795 640) were analyzed. The UK Biobank cohort (n = 29 740) was excluded from the MD data set to avoid sample overlap. Data were collected from August 2017 to May 2018, and analysis began July 2018. MAIN OUTCOMES AND MEASURES The primary outcomes were a list of genetic loci shared between BMI and MPDs and their functional pathways. RESULTS Genome-wide association study data from 1 380 284 participants were analyzed, and the genetic correlation between BMI and MPDs varied (SCZ: r for genetic = −0.11, P = 2.1 × 10−10; BIP: r for genetic = −0.06, P = .0103; MD: r for genetic = 0.12, P = 6.7 × 10−10). Overall, 63, 17, and 32 loci shared between BMI and SCZ, BIP, and MD, respectively, were analyzed at conjunctional false discovery rate less than 0.01. Of the shared loci, 34% (73 of 213) in SCZ, 52% (36 of 69) in BIP, and 57% (56 of 99) in MD had risk alleles associated with higher BMI (conjunctional false discovery rate <0.05), while the rest had opposite directions of associations. Functional analyses indicated that the overlapping loci are involved in several pathways including neurodevelopment, neurotransmitter signaling, and intracellular processes, and the loci with concordant and opposite association directions pointed mostly to different pathways. CONCLUSIONS AND RELEVANCE In this genome-wide association study, extensive polygenic overlap between BMI and SCZ, BIP, and MD were found, and 111 shared genetic loci were identified, implicating novel functional mechanisms. There was mixture of association directions in SCZ and BMI, albeit with a preponderance of discordant ones

• Smeland, Olav Bjerkehagen; Shadrin, Alexey A.; Bahrami, Shahram; Broce, Iris J.; Tesli, Martin Steen & Frei, Oleksandr [Show all 22 contributors for this article] (2020). Genome-wide Association Analysis of Parkinson’s Disease and Schizophrenia Reveals Shared Genetic Architecture and Identifies Novel Risk Loci. Biological Psychiatry. ISSN 0006-3223. 89(3), p. 227–235. doi: 10.1016/j.biopsych.2020.01.026. Full text in Research Archive Show summary

  BACKGROUND:Parkinson’s disease (PD) and schizophrenia (SCZ) are heritable brain disorders that involvedysregulation of the dopaminergic system. Epidemiological studies have reported potential comorbidity between thedisorders, and movement disturbances are common in patients with SCZ before treatment with antipsychotic drugs.Despite this, little is known about shared genetic etiology between the disorders.METHODS:We analyzed recent large genome-wide association studies on patients with SCZ (N= 77,096) and PD(N= 417,508) using a conditional/conjunctional false discovery rate (FDR) approach to evaluate overlap incommon genetic variants and improve statistical power for genetic discovery. Using a variety of biologicalresources, we functionally characterized the identified genomic loci.RESULTS:We observed genetic enrichment in PD conditional onassociations with SCZ and vice versa, indicatingpolygenic overlap. We then leveraged this cross-trait enrichment using conditional FDR analysis and identified 9 novel PDrisk loci and 1 novel SCZ locus at conditional FDR,.01. Furthermore, we identified 9 genomic loci jointly associated withPD and SCZ at conjunctional FDR,.05. There was an even distribution of antagonistic and agonistic effect directionsamong the shared loci, in line with the insignificant genetic correlation between the disorders. Of 67 genes mapped to theshared loci, 65 are expressed in the human brain and show cell type–specific expression profiles.CONCLUSIONS:Altogether, the study increases understanding of the genetic architectures underlying SCZ and PD,indicating that common molecular genetic mechanisms may contribute to overlapping pathophysiological and clinicalfeatures between the disorders.

• Cuellar-Partida, Gabriel; Tung, Joyce Y; Eriksson, Nicholas; Albrecht, Eva; Aliev, Fazil & Andreassen, Ole Andreas [Show all 51 contributors for this article] (2020). Genome-wide association study identifies 48 common genetic variants associated with handedness. Nature Human Behaviour. doi: 10.1038/s41562-020-00956-y. Full text in Research Archive
• Elvsåshagen, Torbjørn; Bahrami, Shahram; Meer, Dennis van der; Agartz, Ingrid; Alnæs, Dag & Barch, Deanna M. [Show all 76 contributors for this article] (2020). The genetic architecture of human brainstem structures and their involvement in common brain disorders. Nature Communications. 11. doi: 10.1038/s41467-020-17376-1. Full text in Research Archive Show summary

  Brainstem regions support vital bodily functions, yet their genetic architectures and involvement in common brain disorders remain understudied. Here, using imaging-genetics data from a discovery sample of 27,034 individuals, we identify 45 brainstem-associated genetic loci, including the first linked to midbrain, pons, and medulla oblongata volumes, and map them to 305 genes. In a replication sample of 7432 participants most of the loci show the same effect direction and are significant at a nominal threshold. We detect genetic overlap between brainstem volumes and eight psychiatric and neurological disorders. In additional clinical data from 5062 individuals with common brain disorders and 11,257 healthy controls, we observe differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinson’s disease, supporting the relevance of brainstem regions and their genetic architectures in common brain disorders.

• Shadrin, Alexey A.; Mucha, Sören; Ellinghaus, David; Makarious, Mary B; Blauwendraat, Cornelis & Sreelatha, Ashwin [Show all 36 contributors for this article] (2020). Shared Genetics of Multiple System Atrophy and Inflammatory Bowel Disease. Movement Disorders. ISSN 0885-3185. doi: 10.1002/mds.28338. Full text in Research Archive Show summary

  Background Multiple system atrophy (MSA) is a rare neurodegenerative disease characterized by intracellular accumulations of α‐synuclein and nerve cell loss in striatonigral and olivopontocerebellar structures. Epidemiological and clinical studies have reported potential involvement of autoimmune mechanisms in MSA pathogenesis. However, genetic etiology of this interaction remains unknown. We aimed to investigate genetic overlap between MSA and 7 autoimmune diseases and to identify shared genetic loci. Methods Genome‐wide association study summary statistics of MSA and 7 autoimmune diseases were combined in cross‐trait conjunctional false discovery rate analysis to explore overlapping genetic background. Expression of selected candidate genes was compared in transgenic MSA mice and wild‐type mice. Genetic variability of candidate genes was further investigated using independent whole‐exome genotyping data from large cohorts of MSA and autoimmune disease patients and healthy controls. Results We observed substantial polygenic overlap between MSA and inflammatory bowel disease and identified 3 shared genetic loci with leading variants upstream of the DENND1B and RSP04 genes, and in intron of the C7 gene. Further, the C7 gene showed significantly dysregulated expression in the degenerating midbrain of transgenic MSA mice compared with wild‐type mice and had elevated burden of protein‐coding variants in independent MSA and inflammatory bowel disease cohorts. Conclusion Our study provides evidence of shared genetic etiology between MSA and inflammatory bowel disease with an important role of the C7 gene in both phenotypes, with the implication of immune and gut dysfunction in MSA pathophysiology. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

• Shadrin, Alexey A.; Frei, Oleksandr; Smeland, Olav Bjerkehagen; Bettella, Francesco; O`Connell, Kevin & Gani, Osman [Show all 12 contributors for this article] (2020). Phenotype-specific differences in polygenicity and effect size distribution across functional annotation categories revealed by AI-MiXeR. Bioinformatics. ISSN 1367-4803. doi: 10.1093/bioinformatics/btaa568. Full text in Research Archive Show summary

  Abstract Motivation Determining the relative contributions of functional genetic categories is fundamental to understanding the genetic etiology of complex human traits and diseases. Here, we present Annotation Informed-MiXeR, a likelihood-based method for estimating the number of variants influencing a phenotype and their effect sizes across different functional annotation categories of the genome using summary statistics from genome-wide association studies. Results Extensive simulations demonstrate that the model is valid for a broad range of genetic architectures. The model suggests that complex human phenotypes substantially differ in the number of causal variants, their localization in the genome and their effect sizes. Specifically, the exons of protein-coding genes harbor more than 90% of variants influencing type 2 diabetes and inflammatory bowel disease, making them good candidates for whole-exome studies. In contrast, &amp;lt;10% of the causal variants for schizophrenia, bipolar disorder and attention-deficit/hyperactivity disorder are located in protein-coding exons, indicating a more substantial role of regulatory mechanisms in the pathogenesis of these disorders. Availability and implementation The software is available at: https://github.com/precimed/mixer. Supplementary information Supplementary data are available at Bioinformatics online.

• Smith, Robert Løvsletten; O`Connell, Kevin; Athanasiu, Lavinia; Djurovic, Srdjan; Kringen, Marianne K. & Andreassen, Ole Andreas [Show all 7 contributors for this article] (2020). Identification of a novel polymorphism associated with reduced clozapine concentration in schizophrenia patients—a genome-wide association study adjusting for smoking habits. Translational Psychiatry. 10(1), p. 1–10. doi: 10.1038/s41398-020-00888-1. Full text in Research Archive Show summary

  Clozapine (CLZ) is the superior antipsychotic drug for treatment of schizophrenia, but exhibits an extensive interpatient pharmacokinetic variability. Here, we conducted a genome-wide association study (GWAS) of CLZ serum concentration adjusting for known smoking habits, which is a major nongenetic factor reducing CLZ levels. The study included 484 patients with 10,283 steady-state serum concentrations of CLZ and N-desmethylclozapine, prescribed dosing, co-medications and known smoking habits (n = 422; 9284 serum samples) from a therapeutic drug monitoring (TDM) service. The GWAS analyses were performed with and without smoking habits as covariate, where possible hits were assessed in relation to the target CLZ concentration range applied in the TDM service (300–2500 nmol/L). The smoking-independent analysis of N-desmethylclozapine serum concentration and the CLZ-to-N-desmethylclozapine ratio replicated the previously identified locus on chromosome 4. After adjusting for smoking habits in patients confirmed as ‘smokers’ (61%) or ‘nonsmokers’ (39%), a novel variant (rs28379954; minor T>C allele frequency 4.1%; 7.6% CT carriers in the population) within the gene encoding the nuclear factor 1 B-type (NFIB) was significantly associated with reduced CLZ serum concentration (p = 1.68 × 10−8, beta = −0.376; explained variance 7.63%). There was no significant association between rs28379954 and N-desmethylclozapine concentration in the GWAS analysis (p = 5.63 × 10−5). The fraction of CLZ TDM samples below 300 nmol/L was significantly higher in carriers vs. noncarriers of the rs28379954 minor C allele [12.0% (95% CI: 9.4–14.7) vs. 6.2% (95% CI: 5.7–6.8), p < 0.001]. We identified a novel variant in the NFIB gene associated with reduced CLZ levels and increased risk of subtherapeutic serum concentrations. This warrants testing of clinical relevance of screening for this gene variant, and also experimental studies to investigate the biological mechanisms of NFIB involvement in CLZ pharmacokinetics.

• O`Connell, Kevin; Shadrin, Alexey A.; Smeland, Olav Bjerkehagen; Bahrami, Shahram; Frei, Oleksandr & Bettella, Francesco [Show all 24 contributors for this article] (2019). Identification of genetic loci shared between ADHD, intelligence and educational attainment. Biological Psychiatry. ISSN 0006-3223. 87(12), p. 1052–1062. doi: 10.1016/j.biopsych.2019.11.015. Full text in Research Archive Show summary

  Background Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that is consistently associated with lower levels of educational attainment. A recent large genome-wide association study identified common gene variants associated with ADHD, but most of the genetic architecture remains unknown. Methods We analyzed independent genome-wide association study summary statistics for ADHD (19,099 cases and 34,194 controls), educational attainment ( N = 842,499), and general intelligence ( N = 269,867) using a conditional/conjunctional false discovery rate (FDR) statistical framework that increases power of discovery by conditioning the FDR on overlapping associations. The genetic variants identified were characterized in terms of function, expression, and biological processes. Results We identified 58 linkage disequilibrium–independent ADHD-associated loci (conditional FDR < 0.01), of which 30 were shared between ADHD and educational attainment or general intelligence (conjunctional FDR < 0.01) and 46 were novel risk loci for ADHD. Conclusions These results expand on previous genetic and epidemiological studies and support the hypothesis of a shared genetic basis between these phenotypes. Although the clinical utility of the identified loci remains to be determined, they can be used as resources to guide future studies aiming to disentangle the complex etiologies of ADHD, educational attainment, and general intelligence.

• O`Connell, Kevin; Shadrin, Alexey A.; Bahrami, Shahram; Smeland, Olav Bjerkehagen; Bettella, Francesco & Frei, Oleksandr [Show all 20 contributors for this article] (2019). Identification of genetic overlap and novel risk loci for attention-deficit/hyperactivity disorder and bipolar disorder. Molecular Psychiatry. ISSN 1359-4184. p. 1–11. doi: 10.1038/s41380-019-0613-z. Full text in Research Archive Show summary

  Differential diagnosis between childhood onset attention-deficit/hyperactivity disorder (ADHD) and bipolar disorder (BD) remains a challenge, mainly due to overlapping symptoms and high rates of comorbidity. Despite this, genetic correlation reported for these disorders is low and non-significant. Here we aimed to better characterize the genetic architecture of these disorders utilizing recent large genome-wide association studies (GWAS). We analyzed independent GWAS summary statistics for ADHD (19,099 cases and 34,194 controls) and BD (20,352 cases and 31,358 controls) applying the conditional/conjunctional false discovery rate (condFDR/conjFDR) statistical framework that increases the power to detect novel phenotype-specific and shared loci by leveraging the combined power of two GWAS. We observed cross-trait polygenic enrichment for ADHD conditioned on associations with BD, and vice versa. Leveraging this enrichment, we identified 19 novel ADHD risk loci and 40 novel BD risk loci at condFDR <0.05. Further, we identified five loci jointly associated with ADHD and BD (conjFDR < 0.05). Interestingly, these five loci show concordant directions of effect for ADHD and BD. These results highlight a shared underlying genetic risk for ADHD and BD which may help to explain the high comorbidity rates and difficulties in differentiating between ADHD and BD in the clinic. Improving our understanding of the underlying genetic architecture of these disorders may aid in the development of novel stratification tools to help reduce these diagnostic difficulties.

• Smeland, Olav Bjerkehagen; Frei, Oleksandr; Shadrin, Alexey A.; O`Connell, Kevin; Fan, Chun Chieh & Bahrami, Shahram [Show all 11 contributors for this article] (2019). Discovery of shared genomic loci using the conditional false discovery rate approach. Human Genetics. ISSN 0340-6717. p. 1–10. doi: 10.1007/s00439-019-02060-2. Full text in Research Archive Show summary

  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.

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• Askeland, Ragna Bugge; Hannigan, Laurie John; O'Connell, Kevin Sean; Corfield, Elizabeth Claire; Frei, Oleksandr & Thapar, Anita [Show all 11 contributors for this article] (2022). Developmental manifestations of polygenic risk for bipolar disorder from infancy to middle childhood. Full text in Research Archive

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