Olav Bjerkehagen Smeland

• 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
• Fuhrer, Julian; Shadrin, Alexey; Hughes, Timothy; Parker, Nadine; Hindley, Guy Frederick Lanyon & Frei, Evgeniia [Show all 12 contributors for this article] (2026). Beyond exons: Linking noncoding heritability and polygenicity across complex human traits and disorders. American Journal of Human Genetics. ISSN 0002-9297. p. 1–13. doi: 10.1016/j.ajhg.2026.08.012. Full text in Research Archive
• Tesfaye, Markos; Shadrin, Alexey; Parker, Nadine; Jaholkowski, Piotr Pawel; Parekh, Pravesh & Kutrolli, Gleda [Show all 16 contributors for this article] (2026). Comorbidity Alters the Genetic Relationship Between Anxiety Disorders and Major Depression. Biological Psychiatry. ISSN 0006-3223. 100(6), p. 689–698. doi: 10.1016/j.biopsych.2026.04.026. Full text in Research Archive
• Rødevand, Linn Nilsen; Rahman, Mohammad Zillur; Jaholkowski, Piotr Pawel; Parker, Nadine; Valdimarsdóttir, Unnur Anna & Smeland, Olav Bjerkehagen [Show all 14 contributors for this article] (2026). Evidence for overlapping genetic architecture between lifestyle factors and severe mental disorders with different patterns across diagnoses. EBioMedicine. 128. doi: 10.1016/j.ebiom.2026.106304. Full text in Research Archive
• 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
• Frei, Evgeniia; Frei, Oleksandr; Hagen, Espen; Shadrin, Alexey; Bakken, Nora Refsum & Birkenæs, Viktoria [Show all 9 contributors for this article] (2026). Prediction of adolescent internalizing disorder risk: Evidence from the Norwegian mother, father, and child cohort study. Journal of Affective Disorders. ISSN 0165-0327. 404, p. 1–9. doi: 10.1016/j.jad.2026.121481. Full text in Research Archive Show summary

  Background Internalizing disorders are among the most common psychiatric conditions in adolescence, often associated with long-term adverse outcomes. Early identification of at-risk youth is important for effective intervention, though it remains challenging due to the multifactorial nature of risk. Machine learning (ML) offers opportunities to integrate multiple data sources and improve risk prediction for internalizing disorders. Methods We used data from 13,743 adolescents (mean age 14.45 years; 52.7% female) participating in the Norwegian Mother, Father and Child Cohort Study (MoBa), linked to national health registries. Logistic regression with elastic net regularization was applied to predict the risk of an internalizing disorder (mood, anxiety or stress-related) occurring within one to five years after assessment. Nested models of increasing complexity incorporated sociodemographic, clinical, lifestyle, mental health, psychosocial, and genetic predictors. Model performance was evaluated in a hold-out test set. Simplified models combining three questionnaire scales were also evaluated. Results Test-set performance increased with model complexity, reaching area under the receiver operating characteristic curve (AUC) of 0.731 for the full model. Mental health self-reported symptoms and psychosocial predictors contributed most to the discrimination. Simplified models using three questionnaire scales, alongside age and sex, achieved AUCs up to 0.718 and effectively stratified adolescents into high- and low-risk groups (OR80/20 ranged 6.11–9.35). Conclusion Multimodal ML models integrating registry information, mental health symptoms, psychosocial factors, and genetic data demonstrated moderate predictive performance. Simplified models with three questionnaire items reached comparable performance, highlighting their potential utility in the early identification of adolescents at elevated internalizing disorder risk.

• Karadag, Naz; Fuhrer, Julian; Heuser, Kjell; Andreassen, Ole & Smeland, Olav B. (2026). The genetics of common epilepsies. Genomic Psychiatry. p. 1–8. doi: 10.61373/gp026y.0027. Full text in Research Archive Show summary

  Common epilepsies are heterogeneous neurological disorders with significant heritability. Recent large-scale molecular genetic studies have identified both common and rare genetic variants affecting the risk of common epilepsies, suggesting the involvement of thousands of genetic variants. Most of these are common and individually have minuscule effects on disease risk. To date, more than 20 genomic loci with genome-wide significant common variant associations have been identified for genetic generalized epilepsies, implicating genes related to excitatory and GABAergic neurons, intracellular signal transduction, and synaptic excitability. While only a few common variant associations have reached genome-wide significance for focal epilepsies, exome-wide sequencing studies have robustly implicated protein-truncating ultrarare variants in genes encoding parts of the GATOR1 complex. Emerging data suggest a partly convergent genetic signal across subtypes of epilepsy and across common and rare variants. Furthermore, the genetic associations for common epilepsies overlap with a wide range of clinically related phenotypes, including cognitive ability and comorbid psychiatric and neurological disorders. Presently, genetic risk prediction tools that summarize an individual's common variant risk burden have limited clinical utility, but may eventually improve as statistical power increases. This review describes recent advances in the genetics of common epilepsies and outlines clinical implications and remaining challenges.

• Moberget, Torgeir; Meer, Dennis van der; Bahrami, Shahram; Roelfs, Daniël; Frei, Oleksandr & Kaufmann, Tobias Herbert [Show all 15 contributors for this article] (2026). The genetic architecture of human cerebellar morphology supports a key role for the cerebellum in human evolution and psychopathology. Communications Biology. 9(1). doi: 10.1038/s42003-026-09664-1. Full text in Research Archive Show summary

  The functional domain of the cerebellum has expanded beyond motor control to also include cognitive and affective functions. In line with this notion, cerebellar volume has increased over recent primate evolution, and cerebellar alterations have been linked to heritable mental disorders. To map the genetic architecture of human cerebellar morphology, we here studied a large imaging genetics sample from the UK Biobank (n discovery = 27,302; n replication: 11,264) with state-of-the art neuroimaging and biostatistics tools. Multivariate GWAS on regional cerebellar MRI features yielded 351 significant genetic loci (226 novel, 94% replicated). Lead SNPs showed positive enrichment for relatively recent genetic mutations over the last 20-40k years (i.e., overlapping the Upper Paleolithic, a period characterized by rapid cultural evolution), while gene level analyses revealed enrichment for human-specific evolution over the last ∼6-8 million years. Finally, we observed genetic overlap with major mental disorders, supporting cerebellar involvement in psychopathology.

• 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.

• Colbert, Sarah M. C.; Monson, Eric T.; Andreassen, Ole; Ayinde, Olatunde O.; Barr, Peter B. & Bejan, Cosmin A. [Show all 314 contributors for this article] (2025). Defining suicidality phenotypes for genetic studies: perspectives of the Psychiatric Genomics Consortium Suicide Working Group. Molecular Psychiatry. ISSN 1359-4184. 30(12), p. 6144–6154. doi: 10.1038/s41380-025-03271-y. Full text in Research Archive Show summary

  Suicidality phenotypes, consisting of suicidal ideation (SI), suicide attempt (SA), and suicide death (SD), are all heritable but present unique challenges in genome-wide association studies (GWAS) due to their individual complexity, overlap with each other and with related self-harm phenotypes, and varying associations with psychiatric disorders. GWAS have uncovered several loci associated with suicidality phenotypes by meta-analyzing data from multiple cohorts. However, combining datasets from many research groups, where each group may use different study designs, phenotyping instruments, and definitions of suicidality phenotypes, presents challenges. Heterogeneity resulting from these differences can limit genetic discovery; harmonizing phenotype definitions to ensure consistency will greatly improve results. Here, we describe a standardized phenotyping protocol that draws on the expertise of a subgroup of clinicians, researchers, and experts from the Psychiatric Genomics Consortium Suicide Working Group to propose consensus definitions for SI, SA, and SD for genetic studies.

• Kim, Milin; Leonardsen, Esten H.; Rutherford, Saige; Selbæk, Geir; Persson, Karin & Steen, Nils Eiel [Show all 16 contributors for this article] (2025). Mapping Cerebellar Morphology in 15q11.2 CNV Carriers Using Normative Modeling. medRxiv. doi: 10.1101/2025.05.28.25328353. Full text in Research Archive Show summary

  Abstract Copy number variations (CNVs) at the 15q11.2 locus of the human genome have been associated with altered brain structure and increased risk for neurodevelopmental and neuropsychiatric disorders. The cerebellum is increasingly seen as a crucial brain region for neurodevelopmental conditions, yet the effects of 15q11.2 CNVs on cerebellar morphology remain largely unclear. Importantly, 15q11.2 CNVs shows reduced or incomplete penetrance (meaning that not all CNV carriers are affected) and variable expressivity (meaning that symptoms may differ between individuals with the same genetic alteration). Thus, there is a need to not only assess group differences, but also to quantify anatomical variability at the individual level. Here, we address these issues using normative models of brain anatomy trained on large datasets (n > 52k, age range: 3-85) to assess both group and individual-level deviations in cerebellar anatomy in carriers of 15q11.2 deletions (n = 120, mean [SD] age= 64.95 [7.58]) and duplications (n = 149, mean [SD] age=64.31 [7.21]), compared to non-carriers (n = 19,028, mean [SD] age=64.31 [7.58]). Group-level case-control analyses revealed significantly smaller total and regional cerebellar volumes in both deletion and duplication carriers, though with small effect sizes. Individual-level deviation analyses, capturing pronounced alterations in specific individuals, revealed a heterogeneous pattern among carriers. Overall, our findings suggest that CNVs at the 15q11.2 locus exert modest and highly individualized effects on cerebellar morphology.

• 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.

• Frei, Evgeniia; Filiz, Tahir Tekin; Frei, Oleksandr; Loughnan, Robert; Jaholkowski, Piotr Pawel & Parker, Nadine [Show all 12 contributors for this article] (2025). Genome-wide analysis of screen behaviors among adolescents identifies novel loci and overlap with educational attainment and mental disorders. Scientific Reports. 15(1). doi: 10.1038/s41598-025-17450-y. Full text in Research Archive
• Frei, Evgeniia; Frei, Oleksandr; Jaholkowski, Piotr Pawel; Parker, Nadine; Parekh, Pravesh & Shadrin, Alexey [Show all 12 contributors for this article] (2025). The phenotypic and genetic relationship between adolescent mental health and time spent on social media, gaming, and TV. Psychiatry Research. ISSN 0165-1781. 353. doi: 10.1016/j.psychres.2025.116761. 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 .

• 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.

• 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.

• Smeland, Olav Bjerkehagen; Busch, Cecilie; Andreassen, Ole & Manchia, Mirko (2025). Novel Multimodal Precision Medicine Approaches and the Relevance of Developmental Trajectories in Bipolar Disorder. Biological Psychiatry. ISSN 0006-3223. 98, p. 343–353. doi: 10.1016/j.biopsych.2025.03.010. Full text in Research Archive Show summary

  There is a pressing need to establish objective measures to improve diagnosis, prediction, prevention, and treatment of bipolar disorder (BD). Multimodal artificial intelligence (AI) tools could provide these means by incorporating various layers of data orthogonally related to BD, including genomics and other omics, environmental exposures, imaging measures, electronic health records, cognition, sensing devices, and clinical variables. These rapidly evolving AI models hold promise to capture the multidimensional complexity of BD and delineate clinically relevant developmental trajectories that could guide clinical care and therapeutic strategies. In this review, we describe the potential of mapping developmental trajectories that underlie BD, outline how novel multimodal models could improve the prediction of BD and related outcomes, and discuss specific clinical use cases and key ethical and practical challenges regarding the development and potential implementation of these multimodal AI solutions to advance precision medicine approaches in BD.

• Fominykh, Vera; Shadrin, Alexey; Jaholkowski, Piotr Pawel; Fuhrer, Julian; Parker, Nadine & Wiström, Erik David [Show all 11 contributors for this article] (2025). Mapping the genetic landscape of immune-mediated disorders: potential implications for classification and therapeutic strategies. Frontiers in Immunology. 16. doi: 10.3389/fimmu.2025.1543781. Full text in Research Archive Show summary

  Objectives: Based on clinical, biomarker, and genetic data, McGonagle and McDermott suggested that autoimmune and autoinflammatory disorders can be classified as a disease continuum from purely autoimmune to autoinflammatory with mixed diseases in between. However, the genetic architecture of this spectrum has not been systematically described. Here, we investigate the continuum of polygenic immune-mediated disorders using genome-wide association studies (GWAS) and statistical genetics methods. Methods: We mapped the genetic landscape of 15 immune-mediated disorders using GWAS summary statistics and methods including genomic structural equation modeling (genomic SEM), linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and Gaussian causal mixture modeling (MiXeR). We performed enrichment analyses of tissues and biological gene sets using MAGMA. Results: Genomic SEM suggested a continuum structure with four underlying latent factors from autoimmune diseases at one end to autoinflammatory on the opposite end. Across disorders, we observed a balanced mixture of negative and positive local genetic correlations within the major histocompatibility complex, while outside this region, local genetic correlations were predominantly positive. MiXeR analysis showed large genetic overlap in accordance with the continuum landscape. MAGMA analysis implicated genes associated with known monogenic immune diseases for prominent autoimmune and autoinflammatory component. Conclusions: Our findings support a polygenic continuum across immune-mediated disorders, with four genetic clusters. The “polygenic autoimmune” and “polygenic autoinflammatory” clusters reside on margins of this continuum. These findings provide insights and lead us to hypothesize that the identified clusters could inform future therapeutical strategies, with patients in the same clusters potentially responding similarly to specific therapies.

• Adams, Mark J.; Streit, Fabian; Meng, Xiangrui; Awasthi, Swapnil; Adey, Brett N. & Choi, Karmel W. [Show all 51 contributors for this article] (2025). Trans-ancestry genome-wide study of depression identifies 697 associations implicating cell types and pharmacotherapies. Cell. ISSN 0092-8674. 188(3), p. 640–652.e9. doi: 10.1016/j.cell.2024.12.002. Full text in Research Archive Show summary

  In a genome-wide association study (GWAS) meta-analysis of 688,808 individuals with major depression (MD) and 4,364,225 controls from 29 countries across diverse and admixed ancestries, we identify 697 associations at 635 loci, 293 of which are novel. Using fine-mapping and functional tools, we find 308 high-confidence gene associations and enrichment of postsynaptic density and receptor clustering. A neural cell-type enrichment analysis utilizing single-cell data implicates excitatory, inhibitory, and medium spiny neurons and the involvement of amygdala neurons in both mouse and human single-cell analyses. The associations are enriched for antidepressant targets and provide potential repurposing opportunities. Polygenic scores trained using European or multi-ancestry data predicted MD status across all ancestries, explaining up to 5.8% of MD liability variance in Europeans. These findings advance our global understanding of MD and reveal biological targets that may be used to target and develop pharmacotherapies addressing the unmet need for effective treatment.

• Birkenæs, Viktoria; Parekh, Pravesh; Hegemann, Laura Elizabeth; Bakken, Nora Refsum; Frei, Evgeniia & Jaholkowski, Piotr Pawel [Show all 13 contributors for this article] (2025). Youth psychotic experiences: psychometric evaluation and diagnostic associations of the CAPE-16 in adolescents from the Norwegian Mother, Mather and Child Cohort. Journal of Child Psychology and Psychiatry. ISSN 0021-9630. 67(1), p. 27–40. doi: 10.1111/jcpp.70007. Full text in Research Archive Show summary

  Background: Adolescent self-reported psychotic experiences are associated with mental illness and could help guide prevention strategies. Youth report substantially more experiences than adults. However, with large societal changes like the digital revolution and COVID-19 pandemic, existing questionnaires may no longer accurately capture youth experiences. We aimed to determine the ability of the CAPE-16 questionnaire in capturing psychotic experiences across contexts (biological sex and COVID-19 response) and generations, thereby validating important psychometric aspects of the tool in modern adolescents. Methods: We used data from the Norwegian Mother, Father and Child Study (MoBa), a population-based pregnancy cohort. Adolescents responded to the CAPE-16 questionnaire (n = 18,835). For a comparison between age groups, we included adult men from the parent generation who responded to the CAPE-9 (n = 28,793). We investigated the psychometric properties of CAPE-16 through confirmatory factor analyses, measurement invariance testing across biological sex, response before/during the COVID-19 pandemic, and generations (adolescents and fathers), and examined subscale and item-level associations with subsequent registry-based psychiatric diagnoses (average time between CAPE and last registry update: 3.68 ± 1.34 years). Results: Out of 18,835 adolescents, 33.2% reported lifetime psychotic experiences. We confirmed a three-factor structure (paranoia, bizarre thoughts, and hallucinations) and good subscale reliability (ω = .86 and .90). CAPE-16 scores were stable across biological sex and pandemic status. CAPE-9 response patterns were non-invariant across adolescents and adult men, with an item related to digital technology particularly prone to bias. CAPE-16 subscales were associated with subsequent psychiatric diagnoses, especially psychotic disorders. Conclusions: CAPE-16 is a reliable measure of psychotic experiences across sex and a major societal stressor in adolescents. More frequent and distressing experiences increase the risk of subsequent psychiatric diagnoses. Different response patterns between adults and adolescents for items related to digital technology suggest differences in interpretation. Hence, certain items may benefit from revisions.

• Meer, Dennis van der; Hindley, Guy; Shadrin, Alexey; Smeland, Olav Bjerkehagen; Parker, Nadine & Dale, Anders M. [Show all 8 contributors for this article] (2025). Mapping the Genetic Landscape of Psychiatric Disorders With the MiXeR Toolset. Biological Psychiatry. ISSN 0006-3223. 98(6), p. 455–465. doi: 10.1016/j.biopsych.2025.02.886. Full text in Research Archive Show summary

  Psychiatric disorders have complex genetic architectures with substantial genetic overlap across conditions, which may partially explain their high levels of comorbidity. This presents significant challenges to research. Genome-wide association studies (GWASs) have uncovered hundreds of loci associated with single disorders, but the genetic landscape of psychiatric disorders has remained largely obscure. Moving beyond the conventional infinitesimal model, uni-, bi-, and trivariate MiXeR tools, applied to GWAS summary statistics, has enabled us to more comprehensively describe the genetic architecture of complex disorders and traits and their overlap. Furthermore, the GSA-MiXeR tool improves biological interpretation of GWAS findings to better elucidate causal mechanisms. Here, we outline the methodology that underlies the MiXeR tools together with instructions for their optimal use. We review results from studies that have investigated the genetic architecture of psychiatric disorders and their overlap using the MiXeR toolset. These studies have revealed generally high polygenicity and low discoverability among psychiatric disorders, particularly in contrast to somatic disorders. There is also pervasive genetic overlap across psychiatric disorders and behavioral traits, while their overlap with somatic traits is smaller, consistent with differences in polygenicity. Finally, GSA-MiXeR has quantified the contribution of gene sets to the heritability of psychiatric disorders, prioritizing small, biologically coherent gene sets. Together, these findings have implications for our understanding of the complex relationships between psychiatric disorders and related traits. MiXeR tools have provided new insights into the genetic architecture of psychiatric disorders, generating a better understanding of their underlying biological mechanisms and potential for clinical utility.

• Askeland-Gjerde, Daniel E.; Westlye, Lars Tjelta; Andersson, Patrik; Korbmacher, Max; Lange, Ann-Marie Glasø de & Meer, Dennis van der [Show all 10 contributors for this article] (2025). Mediation Analyses Link Cardiometabolic Factors and Liver Fat With White Matter Hyperintensities and Cognitive Performance: A UK Biobank Study. Biological Psychiatry: Global Open Science. 5(4). doi: 10.1016/j.bpsgos.2025.100488. Full text in Research Archive Show summary

  Background Liver fat is associated with cardiometabolic disease, cerebrovascular disease, and dementia. Cerebrovascular disease, most often cerebral small vessel disease, identified by magnetic resonance imaging as white matter hyperintensities (WMHs) often contributes to dementia. However, liver fat’s role in the relationship between cardiometabolic risk, WMHs, and cognitive performance is unclear. Methods In the UK Biobank cohort (N = 32,461, 52.6% female; mean age 64.2 ± 7.7 years; n = 23,354 in the cognitive performance subsample), we used linear regression to investigate associations between cardiometabolic factors measured at baseline and liver fat, WMHs, and cognitive performance measured at follow-up, which was 9.3 ± 2.0 years later on average. We used structural equation modeling to investigate whether liver fat mediated associations between cardiometabolic factors and WMHs and whether WMHs mediated associations between liver fat and cognitive performance. Results Nearly all cardiometabolic factors were significantly associated with liver fat (|r| range = 0.03–0.41, p = 3.4 × 10−8 to 0) and WMHs (|r| = 0.04–0.15, p = 5.8 × 10−13 to 7.0 × 10−159) in regression models. Liver fat was associated with WMHs (r = 0.11, p = 4.3 × 10−82) and cognitive performance (r = −0.03, p = 1.6 × 10−7). Liver fat mediated the associations between cardiometabolic factors and WMHs (|βmediation| = 0.003–0.027, pmediation = 1.9 × 10−8 to 0), and WMHs mediated the associations between liver fat and cognitive performance (βmediation = −0.01, pmediation = 0). Conclusions Our findings indicate that liver fat mediates associations between cardiometabolic factors and WMHs and that WMHs mediate the association between liver fat and cognitive performance. This suggests that liver fat may be important for understanding the effects of cardiometabolic factors on cerebrovascular disease and cognitive function. Experimental studies are warranted to determine relevant targets for preventing vascular-driven cognitive impairment.

• Kim, Milin; Sharma, Nitin; Leonardsen, Esten Høyland; Rutherford, Saige; Selbæk, Geir & Persson, Karin Ester Torun [Show all 19 contributors for this article] (2025). Predicting Mental and Neurological Illnesses Based on Cerebellar Normative Features. Biological Psychiatry: Global Open Science. 5(5), p. 1–11. doi: 10.1016/j.bpsgos.2025.100541. Full text in Research Archive
• 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.

• 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.

• 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
• Kim, Milin; Leonardsen, Esten Høyland; Rutherford, Saige; Selbæk, Geir; Persson, Karin Ester Torun & Steen, Nils Eiel [Show all 15 contributors for this article] (2024). Mapping cerebellar anatomical heterogeneity in mental and neurological illnesses. Nature Mental Health. 2(10), p. 1196–1207. doi: 10.1038/s44220-024-00297-z. Full text in Research Archive Show summary

  The cerebellum is linked to motor coordination, cognitive and affective processing, in addition to a wide range of clinical illnesses. To enable robust quantification of individual cerebellar anatomy relative to population norms, we mapped the normative development and aging of the cerebellum across the lifespan using brain scans of >54,000 participants. We estimated normative models at voxel-wise spatial precision, enabling integration with cerebellar atlases. Applying the normative models in independent samples revealed substantial heterogeneity within five clinical illnesses: autism spectrum disorder, mild cognitive impairment, Alzheimer disease, bipolar disorder, and schizophrenia. Notably, individuals with autism spectrum disorder and mild cognitive impairment exhibited increased positive and negative extreme deviations in cerebellar anatomy, while those with schizophrenia and Alzheimer disease showed predominantly negative deviations. Finally, extreme deviations were associated with cognitive scores. Ou

• 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.

• 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.

• Rødevand, Linn Nilsen; Rahman, Zillur; Hindley, Guy Frederick Lanyon; Smeland, Olav Bjerkehagen; Frei, Oleksandr & Filiz, Tahir Tekin [Show all 15 contributors for this article] (2023). Characterizing the Shared Genetic Underpinnings of Schizophrenia and Cardiovascular Disease Risk Factors. American Journal of Psychiatry. ISSN 0002-953X. 180(11), p. 815–826. doi: 10.1176/APPI.AJP.20220660. Full text in Research Archive
• Jaholkowski, Piotr Pawel; Shadrin, Alexey; Jangmo, Anders Andreas Krister; Frei, Evgeniia; Woldeyohannes, Markos Tesfaye & Hindley, Guy Frederick Lanyon [Show all 23 contributors for this article] (2023). Associations Between Symptoms of Premenstrual Disorders and Polygenic Liability for Major Psychiatric Disorders. JAMA psychiatry. ISSN 2168-6238. doi: 10.1001/jamapsychiatry.2023.1137. Full text in Research Archive
• 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.

• Wang, Hao; Makowski, Carolina; Zhang, Yanxiao; Qi, Anna; Kaufmann, Tobias Herbert & Smeland, Olav Bjerkehagen [Show all 10 contributors for this article] (2023). Chromosomal inversion polymorphisms shape human brain morphology. Cell reports. 42(8). doi: 10.1016/j.celrep.2023.112896. Full text in Research Archive Show summary

  The impact of chromosomal inversions on human brain morphology remains underexplored. We studied 35 common inversions classified from genotypes of 33,018 adults with European ancestry. The inversions at 2p22.3, 16p11.2, and 17q21.31 reach genome-wide significance, followed by 8p23.1 and 6p21.33, in their association with cortical and subcortical morphology. The 17q21.31, 8p23.1, and 16p11.2 regions comprise the LRRC37, OR7E, and NPIP duplicated gene families. We find the 17q21.31 MAPT inversion region, known for harboring neurological risk, to be the most salient locus among common variants for shaping and patterning the cortex. Overall, we observe the inverted orientations decreasing brain size, with the exception that the 2p22.3 inversion is associated with increased subcortical volume and the 8p23.1 inversion is associated with increased motor cortex. These significant inversions are in the genomic hotspots of neuropsychiatric loci. Our findings are generalizable to 3,472 children and demonstrate inversions as essential genetic variation to understand human brain phenotypes.

• 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.

• Jaholkowski, Piotr; Shadrin, Alexey A.; Jangmo, Andreas; Frei, Evgeniia; Woldeyohannes, Markos Tesfaye & Hindley, Guy F. L. [Show all 23 contributors for this article] (2023). Associations Between Symptoms of Premenstrual Disorders and Polygenic Liability for Major Psychiatric Disorders. JAMA psychiatry. ISSN 2168-6238. 80(7), p. 738–742. doi: 10.1001/jamapsychiatry.2023.1137. Full text in Research Archive
• 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.

• Meer, Dennis van der; Cheng, Weiqiu; Rokicki, Jaroslav; Fernandez-Cabello, Sara; Shadrin, Alexey & Smeland, Olav Bjerkehagen [Show all 19 contributors for this article] (2023). Clustering Schizophrenia Genes by Their Temporal Expression Patterns Aids Functional Interpretation. Schizophrenia Bulletin. ISSN 0586-7614. 50(2), p. 327–338. doi: 10.1093/schbul/sbad140. Full text in Research Archive Show summary

  Background Schizophrenia is a highly heritable brain disorder with a typical symptom onset in early adulthood. The 2-hit hypothesis posits that schizophrenia results from differential early neurodevelopment, predisposing an individual, followed by a disruption of later brain maturational processes that trigger the onset of symptoms. Study design We applied hierarchical clustering to transcription levels of 345 genes previously linked to schizophrenia, derived from cortical tissue samples from 56 donors across the lifespan. We subsequently calculated clustered-specific polygenic risk scores for 743 individuals with schizophrenia and 743 sex- and age-matched healthy controls. Study results Clustering revealed a set of 183 genes that was significantly upregulated prenatally and downregulated postnatally and 162 genes that showed the opposite pattern. The prenatally upregulated set of genes was functionally annotated to fundamental cell cycle processes, while the postnatally upregulated set was associated with the immune system and neuronal communication. We found an interaction between the 2 scores; higher prenatal polygenic risk showed a stronger association with schizophrenia diagnosis at higher levels of postnatal polygenic risk. Importantly, this finding was replicated in an independent clinical cohort of 3233 individuals. Conclusions We provide genetics-based evidence that schizophrenia is shaped by disruptions of separable biological processes acting at distinct phases of neurodevelopment. The modeling of genetic risk factors that moderate each other’s effect, informed by the timing of their expression, will aid in a better understanding of the development of schizophrenia.

• Akkouh, Ibrahim Ahmed; Ueland, Thor; Szabo, Attila; Hughes, Timothy; Smeland, Olav Bjerkehagen & Andreassen, Ole [Show all 8 contributors for this article] (2023). Longitudinal Transcriptomic Analysis of Human Cortical Spheroids Identifies Axonal Dysregulation in the Prenatal Brain as a Mediator of Genetic Risk for Schizophrenia. Biological Psychiatry. ISSN 0006-3223. 0(7), p. 1–12. doi: 10.1016/j.biopsych.2023.08.017. Full text in Research Archive Show summary

  Background Schizophrenia (SCZ) has a known neurodevelopmental etiology, but limited access to human prenatal brain tissue hampers the investigation of basic disease mechanisms in early brain development. Here, we elucidate the molecular mechanisms contributing to SCZ risk in a disease-relevant model of the prenatal human brain. Methods We generated induced pluripotent stem cell–derived organoids, termed human cortical spheroids (hCSs), from a large, genetically stratified sample of 14 SCZ cases and 14 age- and sex-matched controls. The hCSs were differentiated for 150 days, and comprehensive molecular characterization across 4 time points was carried out. Results The transcriptional and cellular architecture of hCSs closely resembled that of fetal brain tissue at 10 to 24 postconception weeks, showing strongest spatial overlap with frontal regions of the cerebral cortex. A total of 3520 genes were differentially modulated between SCZ and control hCSs across organoid maturation, displaying a significant contribution of genetic loading, an overrepresentation of risk genes for autism spectrum disorder and SCZ, and the strongest enrichment for axonal processes in all hCS stages. The two axon guidance genes SEMA7A and SEMA5A, the first a promoter of synaptic functions and the second a repressor, were downregulated and upregulated, respectively, in SCZ hCSs. This expression pattern was confirmed at the protein level and replicated in a large postmortem sample. Conclusions Applying a disease-relevant model of the developing fetal brain, we identified consistent dysregulation of axonal genes as an early risk factor for SCZ, providing novel insights into the effects of genetic predisposition on the neurodevelopmental origins of the disorder.

• 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.

• Osete, Jordi Requena; Akkouh, Ibrahim Ahmed; Ievglevskyi, Oleksandr; Vandenberghe, Matthieu; Assis, Denis Reis de & Ueland, Thor [Show all 14 contributors for this article] (2023). Characterization of lithium (Li) treated human cortical spheroids (hCS). Molecular Psychiatry. ISSN 1359-4184. 28(7). doi: 10.1038/s41380-023-02300-y. Full text in Research Archive
• 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.

• Parker, Nadine; Cheng, Weiqiu; Hindley, Guy; Parekh, Pravesh; Shadrin, Alexey & Maximov, Ivan [Show all 12 contributors for this article] (2023). Psychiatric disorders and brain white matter exhibit genetic overlap implicating developmental and neural cell biology. Molecular Psychiatry. ISSN 1359-4184. doi: 10.1038/s41380-023-02264-z. Full text in Research Archive
• Andreassen, Ole; Hindley, Guy Frederick Lanyon; Frei, Oleksandr & Smeland, Olav Bjerkehagen (2023). New insights from the last decade of research in psychiatric genetics: discoveries, challenges and clinical implications. World Psychiatry. ISSN 1723-8617. 22(1), p. 4–24. doi: 10.1002/wps.21034. Full text in Research Archive
• Birkenæs, Viktoria; Bakken, Nora Refsum; Frei, Evgeniia; Jaholkowski, Piotr Pawel; Smeland, Olav Bjerkehagen & Woldeyohannes, Markos Tesfaye [Show all 15 contributors for this article] (2023). Psychometric Properties and Diagnostic Associations of the Short-Form Community Assessment of Psychic Experiences in a Population-Based Sample of 29 021 Adult Men. Schizophrenia Bulletin. ISSN 0586-7614. 49(5), p. 1229–1238. doi: 10.1093/schbul/sbad074. Full text in Research Archive Show summary

  Abstract Background and Hypothesis Around 5%–7% of the adult population are estimated to have lifetime psychotic experiences (PEs), which are associated with psychosis risk. PEs assessed with Community Assessment of Psychic Experiences (CAPE) are associated with psychosis but also non-psychotic disorders, which could be partly explained by CAPE indirectly capturing emotional symptoms. We investigated the psychometric properties of a shorter version, CAPE-9, and whether CAPE-9 scores are associated with lifetime psychotic or non-psychotic mental disorders after controlling for current anxiety and depressive symptoms. Design CAPE-9 questionnaire data were obtained from 29 021 men (42.4 ± 5.6 yrs.) from the Norwegian Mother, Father, and Child Cohort Study. We investigated CAPE-9 reliability and factor structure. Logistic regression was used to test effects of current anxiety and depressive symptoms (SCL-12) on associations between CAPE-9 scores and psychiatric diagnoses. Results CAPE-9 fit a previously reported 3-factor structure and showed good reliability. Twenty-six percent reported at least one lifetime PE. CAPE-9 scores were significantly associated with most psychiatric disorders (schizophrenia, depression, bipolar disorder, substance abuse, anxiety, trauma-related disorders, and ADHD). After controlling for concurrent emotional symptoms, only associations with schizophrenia (OR = 1.29; 95% CI = 1.18–1.38) and trauma-related disorders (OR = 1.09; CI = 1.02–1.15) remained significant. Conclusions CAPE-9 showed good psychometric properties in this large population-based adult male sample, and PEs were more clearly associated with psychotic disorders after controlling for current emotional symptoms. These results support the use of the short CAPE-9 as a cost-effective tool for informing public health initiatives and advancing our understanding of the dimensionality of psychosis.

• Osete, Jordi Requena; Akkouh, Ibrahim Ahmed; Ievglevskyi, Oleksandr; Vandenberghe, Matthieu; Assis, Denis Reis de & Ueland, Thor [Show all 14 contributors for this article] (2023). Transcriptional and functional effects of lithium in bipolar disorder iPSC-derived cortical spheroids. Molecular Psychiatry. ISSN 1359-4184. 28, p. 3033–3043. doi: 10.1038/s41380-023-01944-0. Full text in Research Archive Show summary

  Lithium (Li) is recommended for long-term treatment of bipolar disorder (BD). However, its mechanism of action is still poorly understood. Induced pluripotent stem cell (iPSC)-derived brain organoids have emerged as a powerful tool for modeling BD-related disease mechanisms. We studied the effects of 1 mM Li treatment for 1 month in iPSC-derived human cortical spheroids (hCS) from 10 healthy controls (CTRL) and 11 BD patients (6 Li-responders, Li-R, and 5 Li non-treated, Li-N). At day 180 of differentiation, BD hCS showed smaller size, reduced proportion of neurons, decreased neuronal excitability and reduced neural network activity compared to CTRL hCS. Li rescued excitability of BD hCS neurons by exerting an opposite effect in the two diagnostic groups, increasing excitability in BD hCS and decreasing it in CTRL hCS. We identified 132 Li-associated differentially expressed genes (DEGs), which were overrepresented in sodium ion homeostasis and kidney-related pathways. Moreover, Li regulated secretion of pro-inflammatory cytokines and increased mitochondrial reserve capacity in BD hCS. Through long-term Li treatment of a human 3D brain model, this study partly elucidates the functional and transcriptional mechanisms underlying the clinical effects of Li, such as rescue of neuronal excitability and neuroprotection. Our results also underscore the substantial influence of treatment duration in Li studies. Lastly, this study illustrates the potential of patient iPSC-derived 3D brain models for precision medicine in psychiatry.

• Docherty, Anna R.; Mullins, Niamh; Ashley-Koch, Allison E.; Qin, Xuejun; Coleman, Jonathan R.I. & Shabalin, Andrey [Show all 51 contributors for this article] (2023). GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors. American Journal of Psychiatry. ISSN 0002-953X. 180(10), p. 723–738. doi: 10.1176/appi.ajp.21121266. Full text in Research Archive Show summary

  Objective: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. Methods: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. Results: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10–8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10–80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. Conclusions: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.

• 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.

• Reas, Emilie T.; Shadrin, Alexey; Frei, Oleksandr; Motazedi, Ehsan; McEvoy, Linda & Bahrami, Shahram [Show all 22 contributors for this article] (2023). Improved multimodal prediction of progression from MCI to Alzheimer's disease combining genetics with quantitative brain MRI and cognitive measures. Alzheimer's & Dementia. ISSN 1552-5260. 19(11), p. 5151–5158. doi: 10.1002/alz.13112. Full text in Research Archive Show summary

  Introduction There is a pressing need for non-invasive, cost-effective tools for early detection of Alzheimer's disease (AD). Methods Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), Cox proportional models were conducted to develop a multimodal hazard score (MHS) combining age, a polygenic hazard score (PHS), brain atrophy, and memory to predict conversion from mild cognitive impairment (MCI) to dementia. Power calculations estimated required clinical trial sample sizes after hypothetical enrichment using the MHS. Cox regression determined predicted age of onset for AD pathology from the PHS. Results The MHS predicted conversion from MCI to dementia (hazard ratio for 80th versus 20th percentile: 27.03). Models suggest that application of the MHS could reduce clinical trial sample sizes by 67%. The PHS alone predicted age of onset of amyloid and tau. Discussion The MHS may improve early detection of AD for use in memory clinics or for clinical trial enrichment.

• 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.

• 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.

• Streit, Fabian; Witt, Stephanie H.; Awasthi, Swapnil; Foo, Jerome C.; Jungkunz, Martin & Frank, Josef [Show all 30 contributors for this article] (2022). Borderline personality disorder and the big five: molecular genetic analyses indicate shared genetic architecture with neuroticism and openness. Translational Psychiatry. 12:153, p. 1–8. doi: 10.1038/s41398-022-01912-2. Full text in Research Archive Show summary

  Abstract Both environmental (e.g. interpersonal traumatization during childhood and adolescence) and genetic factors may contribute to the development of Borderline Personality Disorder (BPD). Twin studies assessing borderline personality symptoms/features in the general population indicate that genetic factors underlying these symptoms/features are shared in part with the personality traits of the Five Factor Model (FFM) of personality—the “Big Five”. In the present study, the genetic overlap of BPD with the Big Five -Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism- was assessed. Linkage disequilibrium score regression was used to calculate genetic correlations between a genome-wide association study (GWAS) in central European populations on BPD ( N  = 2543) and GWAS on the Big Five ( N  = 76,551–122,886, Neuroticism N  = 390,278). Polygenic scores (PGS) were calculated to test the association of the genetic disposition for the personality traits with BPD case-control status. Significant positive genetic correlations of BPD were found with Neuroticism ( rg  = 0.34, p  = 6.3*10 −5 ) and Openness ( rg  = 0.24, p  = 0.036), but not with the other personality traits (all |  rg  | &lt;0.14, all p  &gt; 0.30). A cluster and item-level analysis showed positive genetic correlations of BPD with the Neuroticism clusters “Depressed Affect” and “Worry”, and with a broad range of Neuroticism items ( N  = 348,219–376,352). PGS analyses confirmed the genetic correlations, and found an independent contribution of the personality traits to BPD risk. The observed associations indicate a partially shared genetic background of BPD and the personality traits Neuroticism and Openness. Larger GWAS of BPD and the “Big Five” are needed to further explore the role of personality traits in the etiology of BPD.

• Mullins, Niamh; Kang, JooEun; Campos, Adrian I.; Coleman, Jonathan R.I.; Edwards, Alexis C. & Galfalvy, Hanga [Show all 52 contributors for this article] (2022). Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors. Biological Psychiatry. ISSN 0006-3223. 91(3), p. 313–327. doi: 10.1016/j.biopsych.2021.05.029. Full text in Research Archive Show summary

  Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

• 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.

• Smeland, Olav Bjerkehagen & Andreassen, Ole (2022). Schizophrenia: genetic insights with clinical potential. Nature Reviews Neurology. ISSN 1759-4758. 18, p. 129–130. doi: 10.1038/s41582-021-00613-6. Full text in Research Archive
• 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.

• 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
• Roelfs, Daniel; Alnæs, Dag; Frei, Oleksandr; Meer, Dennis van der; Smeland, Olav Bjerkehagen & Andreassen, Ole Andreas [Show all 8 contributors for this article] (2021). Phenotypically independent profiles relevant to mental health are genetically correlated. Translational Psychiatry. 11(1). doi: 10.1038/s41398-021-01313-x. Full text in Research Archive Show summary

  Genome-wide association studies (GWAS) and family-based studies have revealed partly overlapping genetic architectures between various psychiatric disorders. Given clinical overlap between disorders, our knowledge of the genetic architectures underlying specific symptom profiles and risk factors is limited. Here, we aimed to derive distinct profiles relevant to mental health in healthy individuals and to study how these genetically relate to each other and to common psychiatric disorders. Using independent component analysis, we decomposed self-report mental health questionnaires from 136,678 healthy individuals of the UK Biobank, excluding data from individuals with a diagnosed neurological or psychiatric disorder, into 13 distinct profiles relevant to mental health, capturing different symptoms as well as social and risk factors underlying reduced mental health. Utilizing genotypes from 117,611 of those individuals with White British ancestry, we performed GWAS for each mental health profile and assessed genetic correlations between these profiles, and between the profiles and common psychiatric disorders and cognitive traits. We found that mental health profiles were genetically correlated with a wide range of psychiatric disorders and cognitive traits, with strongest effects typically observed between a given mental health profile and a disorder for which the profile is common (e.g. depression symptoms and major depressive disorder, or psychosis and schizophrenia). Strikingly, although the profiles were phenotypically uncorrelated, many of them were genetically correlated with each other. This study provides evidence that statistically independent mental health profiles partly share genetic underpinnings and show genetic overlap with psychiatric disorders, suggesting that shared genetics across psychiatric disorders cannot be exclusively attributed to the known overlapping symptomatology between the disorders.

• Dieset, Ingrid; Løvhaug, Lars; Selle, Morten Stefan; Kolseth, Asbjørn; Smeland, Olav Bjerkehagen & Færden, Ann (2021). Lessons learned from a cross-sectional survey among patients and staff in an acute psychiatric unit during an ongoing pandemic outbreak. Psychiatry Research. ISSN 0165-1781. 298, p. 1–3. doi: 10.1016/j.psychres.2021.113779. Full text in Research Archive Show summary

  This current cross sectional survey was carried out amongst patients and staff in an acute psychiatric inpatient unit in the very first weeks of the ongoing pandemic outbreak of COVID-19 in Norway. Most patients found the visiting restrictions difficult, many reported that the pandemic made them feel unsafe, affected their sleep and that they feared transmission from other patients. Among staff, almost half were afraid that they would contract the virus, a majority feared they would bring the virus home and infect their family and one third were concerned that the pandemic compromised the treatment provided for the patients.

• 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.

• Szabo, Attila; Akkouh, Ibrahim A.; Vandenberghe, Matthieu; Osete, Jordi Requena; Hughes, Timothy & Heine, Vivi [Show all 10 contributors for this article] (2021). A human iPSC-astroglia neurodevelopmental model reveals divergent transcriptomic patterns in schizophrenia. Translational Psychiatry. 11(1). doi: 10.1038/s41398-021-01681-4. Full text in Research Archive Show summary

  While neurodevelopmental abnormalities have been associated with schizophrenia (SCZ), the role of astroglia in disease pathophysiology remains poorly understood. In the present study, we used a human induced pluripotent stem cell (iPSC)-derived astrocyte model to investigate the temporal patterns of astroglia differentiation during developmental stages critical for SCZ using RNA sequencing. The model generated astrocyte-specific gene expression patterns during differentiation that corresponded well to astroglia-specific expression signatures of in vivo cortical fetal development. Using this model we identified SCZ-specific expression dynamics, and found that SCZ-associated differentially expressed genes were significantly enriched in the medial prefrontal cortex, striatum, and temporal lobe, targeting VWA5A and ADAMTS19. In addition, SCZ astrocytes displayed alterations in calcium signaling, and significantly decreased glutamate uptake and metalloproteinase activity relative to controls. These results implicate novel transcriptional dynamics in astrocyte differentiation in SCZ together with functional changes that are potentially important biological components of SCZ pathology.

• 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.

• Shadrin, Alexey A.; Kaufmann, Tobias; Meer, Dennis van der; Palmer, Clare E.; Makowski, Carolina & Loughnan, Robert [Show all 22 contributors for this article] (2021). Vertex-wise multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology. NeuroImage. ISSN 1053-8119. 244, p. 1–8. doi: 10.1016/j.neuroimage.2021.118603. Full text in Research Archive Show summary

  Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we extended the Multivariate Omnibus Statistical Test (MOSTest) and applied it to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology robustly replicated in 8,060 children of mixed ethnicity from the Adolescent Brain Cognitive Development (ABCD) Study®. This reflects more than 8-fold increase in genetic discovery at no cost to generalizability compared to the commonly used univariate GWAS methods applied to region of interest (ROI) data. Functional follow up including gene-based analyses implicated 10% of all protein-coding genes and pointed towards pathways involved in neurogenesis and cell differentiation. Power analysis indicated that applying the MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. The large boost in power obtained with the vertex-wise MOSTest together with pronounced replication rates and highlighted biologically meaningful pathways underscores the advantage of multivariate approaches in the context of highly distributed polygenic architecture of the human brain.

• Rødevand, Linn; Bahrami, Shahram; Frei, Oleksandr; Lin, Aihua; Gani, Osman & Shadrin, Alexey A. [Show all 18 contributors for this article] (2021). Polygenic overlap and shared genetic loci between loneliness, severe mental disorders, and cardiovascular disease risk factors suggest shared molecular mechanisms. Translational Psychiatry. 11(1). doi: 10.1038/s41398-020-01142-4. Full text in Research Archive Show summary

  Clinical and epidemiological evidence suggest that loneliness is associated with severe mental disorders (SMDs) and increases the risk of cardiovascular disease (CVD). However, the mechanisms underlying the relationship between loneliness, SMDs, and CVD risk factors remain unknown. Here we explored overlapping genetic architecture and genetic loci shared between SMDs, loneliness, and CVD risk factors. We analyzed large independent genome-wide association study data on schizophrenia (SCZ), bipolar disorder (BD), major depression (MD), loneliness and CVD risk factors using bivariate causal mixture mode (MiXeR), which estimates the total amount of shared variants, and conditional false discovery rate to evaluate overlap in specific loci. We observed substantial genetic overlap between SMDs, loneliness and CVD risk factors, beyond genetic correlation. We identified 149 loci jointly associated with loneliness and SMDs (MD n = 67, SCZ n = 54, and BD n = 28), and 55 distinct loci jointly associated with loneliness and CVD risk factors. A total of 153 novel loneliness loci were found. Most of the shared loci possessed concordant effect directions, suggesting that genetic risk for loneliness may increase the risk of both SMDs and CVD. Functional analyses of the shared loci implicated biological processes related to the brain, metabolic processes, chromatin and immune system. Altogether, the study revealed polygenic overlap between loneliness, SMDs and CVD risk factors, providing new insights into their shared genetic architecture and common genetic mechanisms.

• Gurholt, Tiril Pedersen; Kaufmann, Tobias; Frei, Oleksandr; Alnæs, Dag; Haukvik, Unn Kristin H. & Meer, Dennis van der [Show all 17 contributors for this article] (2021). Population-based body–brain mapping links brain morphology with anthropometrics and body composition. Translational Psychiatry. doi: 10.1038/s41398-021-01414-7. Full text in Research Archive Show summary

  Abstract Understanding complex body–brain processes and the interplay between adipose tissue and brain health is important for understanding comorbidity between psychiatric and cardiometabolic disorders. We investigated associations between brain structure and anthropometric and body composition measures using brain magnetic resonance imaging (MRI; n  = 24,728) and body MRI ( n  = 4973) of generally healthy participants in the UK Biobank. We derived regional and global measures of brain morphometry using FreeSurfer and tested their association with (i) anthropometric measures, and (ii) adipose and muscle tissue measured from body MRI. We identified several significant associations with small effect sizes. Anthropometric measures showed negative, nonlinear, associations with cerebellar/cortical gray matter, and brain stem structures, and positive associations with ventricular volumes. Subcortical structures exhibited mixed effect directionality, with strongest positive association for accumbens. Adipose tissue measures, including liver fat and muscle fat infiltration, were negatively associated with cortical/cerebellum structures, while total thigh muscle volume was positively associated with brain stem and accumbens. Regional investigations of cortical area, thickness, and volume indicated widespread and largely negative associations with anthropometric and adipose tissue measures, with an opposite pattern for thigh muscle volume. Self-reported diabetes, hypertension, or hypercholesterolemia were associated with brain structure. The findings provide new insight into physiological body–brain associations suggestive of shared mechanisms between cardiometabolic risk factors and brain health. Whereas the causality needs to be determined, the observed patterns of body–brain relationships provide a foundation for understanding the underlying mechanisms linking psychiatric disorders with obesity and cardiovascular disease, with potential for the development of new prevention strategies.

• Osete, Jordi Requena; Akkouh, Ibrahim; Assis, Denis Reis de; Szabo, Attila; Frei, Evgeniia & Hughes, Timothy [Show all 10 contributors for this article] (2021). Lithium increases mitochondrial respiration in iPSC-derived neural precursor cells from lithium responders. Molecular Psychiatry. ISSN 1359-4184. doi: 10.1038/s41380-021-01164-4. Full text in Research Archive Show summary

  Lithium (Li), valproate (VPA) and lamotrigine (LTG) are commonly used to treat bipolar disorder (BD). While their clinical efficacy is well established, the mechanisms of action at the molecular level are still incompletely understood. Here we investigated the molecular effects of Li, LTG and VPA treatment in induced pluripotent stem cell (iPSC)-derived neural precursor cells (NPCs) generated from 3 healthy controls (CTRL), 3 affective disorder Li responsive patients (Li-R) and 3 Li non-treated patients (Li-N) after 6 h and 1 week of exposure. Differential expression (DE) analysis after 6 h of treatment revealed a transcriptional signature that was associated with all three drugs and most significantly enriched for ribosome and oxidative phosphorylation (OXPHOS) pathways. In addition to the shared DE genes, we found that Li exposure was associated with 554 genes uniquely regulated in Li-R NPCs and enriched for spliceosome, OXPHOS and thermogenesis pathways. In-depth analysis of the treatment-associated transcripts uncovered a significant decrease in intron retention rate, suggesting that the beneficial influence of these drugs might partly be related to splicing. We examined the mitochondrial respiratory function of the NPCs by exploring the drugs’ effects on oxygen consumption rate (OCR) and glycolytic rate (ECAR). Li improved OCR levels only in Li-R NPCs by enhancing maximal respiration and reserve capacity, while VPA enhanced maximal respiration and reserve capacity in Li-N NPCs. Overall, our findings further support the involvement of mitochondrial functions in the molecular mechanisms of mood stabilizers and suggest novel mechanisms related to the spliceosome, which warrant further investigation.

• O'Connell, Kevin S.; Sønderby, Ida Elken; Frei, Oleksandr; Meer, Dennis van der; Athanasiu, Lavinia & Smeland, Olav Bjerkehagen [Show all 13 contributors for this article] (2021). Association between complement component 4A expression, cognitive performance and brain imaging measures in UK Biobank. Psychological Medicine. ISSN 0033-2917. p. 1–11. doi: 10.1017/S0033291721000179. Full text in Research Archive Show summary

  Background Altered expression of the complement component C4A gene is a known risk factor for schizophrenia. Further, predicted brain C4A expression has also been associated with memory function highlighting that altered C4A expression in the brain may be relevant for cognitive and behavioral traits. Methods We obtained genetic information and performance measures on seven cognitive tasks for up to 329 773 individuals from the UK Biobank, as well as brain imaging data for a subset of 33 003 participants. Direct genotypes for variants (n = 3213) within the major histocompatibility complex region were used to impute C4 structural variation, from which predicted expression of the C4A and C4B genes in human brain tissue were predicted. We investigated if predicted brain C4A or C4B expression were associated with cognitive performance and brain imaging measures using linear regression analyses. Results We identified significant negative associations between predicted C4A expression and performance on select cognitive tests, and significant associations with MRI-based cortical thickness and surface area in select regions. Finally, we observed significant inconsistent partial mediation of the effects of predicted C4A expression on cognitive performance, by specific brain structure measures. Conclusions These results demonstrate that the C4 risk locus is associated with the central endophenotypes of cognitive performance and brain morphology, even when considered independently of other genetic risk factors and in individuals without mental or neurological disorders.

• 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.

• Blokland, Gabriella A. M.; Grove, Jakob; Chen, Chia-Yen; Cotsapas, Chris; Tobet, Stuart & Handa, Robert [Show all 50 contributors for this article] (2021). Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders. Biological Psychiatry. ISSN 0006-3223. 91, p. 102–117. doi: 10.1016/j.biopsych.2021.02.972. Full text in Research Archive Show summary

  Background Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. Methods We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. Results Across disorders, genome-wide significant single nucleotide polymorphism–by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10−8), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10−6) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10−7; rs73033497, p = 8.8 × 10−7; rs7914279, p = 6.4 × 10−7), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10−7) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10−7), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10−7) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). Conclusions In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.

• 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.

• Holland, Dominic; Frei, Oleksandr; Desikan, Rahul S.; Fan, Chun Chieh; Shadrin, Alexey & Smeland, Olav Bjerkehagen [Show all 8 contributors for this article] (2021). The genetic architecture of human complex phenotypes is modulated by linkage disequilibrium and heterozygosity. Genetics. ISSN 0016-6731. 217(3), p. 1–21. doi: 10.1093/genetics/iyaa046. Full text in Research Archive
• 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.

• Andlauer, Till F.M.; Guzman-Parra, José; Streit, Fabian; Strohmaier, Jana; González, Maria José & Flores, Susana Gil [Show all 50 contributors for this article] (2021). Bipolar multiplex families have an increased burden of common risk variants for psychiatric disorders. Molecular Psychiatry. ISSN 1359-4184. 26, p. 1286–1298. doi: 10.1038/s41380-019-0558-2. Full text in Research Archive Show summary

  Multiplex families with a high prevalence of a psychiatric disorder are often examined to identify rare genetic variants with large effect sizes. In the present study, we analysed whether the risk for bipolar disorder (BD) in BD multiplex families is influenced by common genetic variants. Furthermore, we investigated whether this risk is conferred mainly by BD-specific risk variants or by variants also associated with the susceptibility to schizophrenia or major depression. In total, 395 individuals from 33 Andalusian BD multiplex families (166 BD, 78 major depressive disorder, 151 unaffected) as well as 438 subjects from an independent, BD case/control cohort (161 unrelated BD, 277 unrelated controls) were analysed. Polygenic risk scores (PRS) for BD, schizophrenia (SCZ), and major depression were calculated and compared between the cohorts. Both the familial BD cases and unaffected family members had higher PRS for all three psychiatric disorders than the independent controls, with BD and SCZ being significant after correction for multiple testing, suggesting a high baseline risk for several psychiatric disorders in the families. Moreover, familial BD cases showed significantly higher BD PRS than unaffected family members and unrelated BD cases. A plausible hypothesis is that, in multiplex families with a general increase in risk for psychiatric disease, BD development is attributable to a high burden of common variants that confer a specific risk for BD. The present analyses demonstrated that common genetic risk variants for psychiatric disorders are likely to contribute to the high incidence of affective psychiatric disorders in the multiplex families. However, the PRS explained only part of the observed phenotypic variance, and rare variants might have also contributed to disease development.

• Elvsåshagen, Torbjørn; Shadrin, Alexey; Frei, Oleksandr; Meer, Dennis van der; Bahrami, Shahram & Kumar, Vinod J. [Show all 10 contributors for this article] (2021). The genetic architecture of the human thalamus and its overlap with ten common brain disorders. Nature Communications. 12(1). doi: 10.1038/s41467-021-23175-z. Full text in Research Archive Show summary

  Abstract The thalamus is a vital communication hub in the center of the brain and consists of distinct nuclei critical for consciousness and higher-order cortical functions. Structural and functional thalamic alterations are involved in the pathogenesis of common brain disorders, yet the genetic architecture of the thalamus remains largely unknown. Here, using brain scans and genotype data from 30,114 individuals, we identify 55 lead single nucleotide polymorphisms (SNPs) within 42 genetic loci and 391 genes associated with volumes of the thalamus and its nuclei. In an independent validation sample ( n  = 5173) 53 out of the 55 lead SNPs of the discovery sample show the same effect direction (sign test, P  = 8.6e-14). We map the genetic relationship between thalamic nuclei and 180 cerebral cortical areas and find overlapping genetic architectures consistent with thalamocortical connectivity. Pleiotropy analyses between thalamic volumes and ten psychiatric and neurological disorders reveal shared variants for all disorders. Together, these analyses identify genetic loci linked to thalamic nuclei and substantiate the emerging view of the thalamus having central roles in cortical functioning and common brain disorders.

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• Malt, Ulrik Fredrik; Halvorsen, Joar Øveraas; Smeland, Olav Bjerkehagen & Høglend, Per Andreas (2026). Kunnskapsbasert psykiatri. doi: https:/www.gyldendal.no/faglitteratur/medisin/laereboeker/laerebok-i-psykiatri/p-10038591. Full text in Research Archive
• Hindley, Guy; Drange, Ole Kristian; Lin, Aihua; Kutrolli, Gleda; Shadrin, Alexey & Parker, Nadine [Show all 20 contributors for this article] (2024). Corrigendum to “Cross-trait genome-wide association analysis of C-reactive protein level and psychiatric disorders” [Psychoneuroendocrinology 157 (2023) 106368] (Psychoneuroendocrinology (2023) 157, (S0306453023003463), (10.1016/j.psyneuen.2023.106368)). Psychoneuroendocrinology. ISSN 0306-4530. doi: 10.1016/j.psyneuen.2024.106980. Full text in Research Archive
• Birkenæs, Viktoria; Shadrin, Alexey; Frei, Evgeniia; Parekh, Pravesh; Jaholkowski, Piotr Pawel & Smeland, Olav Bjerkehagen [Show all 9 contributors for this article] (2023). Genome-Wide Analysis of Self-Reported Psychotic Experiences in the Norwegian Mother, Father, and Child study. Full text in Research Archive
• Assche, Evelien Van; Schulte, Eva C.; Andreassen, Ole; Smeland, Olav Bjerkehagen & Luykx, Jurjen J. (2022). Editorial: Cross-disorder Genetics in Neuropsychiatry. Frontiers in Neuroscience. ISSN 1662-4548. 16. doi: 10.3389/fnins.2022.826300. Full text in Research Archive

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