European Neuropsychopharmacology最新文献

{"title":"A REPEATED MEASURES GWAS IN RELATIVES: DETECTING AGE-VARYING GENETIC EFFECTS ON MATERNAL DEPRESSION IN MOBA","authors":"Christopher Rayner , Tom McAdams , Alexandra Havdahl , Eivind Ystrom , Ziada Ayorech","doi":"10.1016/j.euroneuro.2025.08.483","DOIUrl":"10.1016/j.euroneuro.2025.08.483","url":null,"abstract":"<div><h3>Background</h3><div>Genome-wide association studies (GWAS) of depression typically rely on case-control analyses, using lifetime history (LTH) of a diagnosis as the primary outcome. Longitudinal cohorts provide opportunities to understand how genetic effects on depression vary across time and contexts. We aimed to harness repeated measures in a single sample to minimise phenotypic heterogeneity and improve statistical power to detect genetic effects on depression.</div></div><div><h3>Methods</h3><div>We used data from mothers who participated in the Norwegian Mother, Father and Child study (MoBa). We restructured the Hopkins Symptoms Checklist Depression (SCL-D) scores for 76,044 mothers by age, producing an accelerated longitudinal design with 418,159 depression observations across the lifecourse (age range: 16, 60 years old). We used continuous-time item response theory models to minimise measurement error, and Empirical Bayes Estimates with Simultaneous Correction (SCEBE) to conduct repeated measures GWAS (GWASRM). We estimated genetic effects on depression symptoms at age 30, and the linear change in age (variant by age interaction), which were combined to compute age-specific effects at ages 20 to 50 (GWASt=20..50). For comparison, we performed a GWAS of LTH depression assessed in the same sample (GWASLTH). Summary statistics from GWASRM and GWASLTH were compared using heritability and genetic correlations. We also performed 10-fold-leave-one-out GWASRM and GWASLTH, leaving 10 test datasets for polygenic index (PGI) analyses. The efficacy and robustness of SCEBE was further assessed via comparison with linear mixed effects models applied to a subset of the data. The impact of selective attrition on GWASRM is also currently under investigation.</div></div><div><h3>Results</h3><div>SCEBE is an efficient and robust method for estimating genetic variant main effects and variant-by-age interactions, with perfect overlap with effects estimated using a linear mixed model. Following GWASRM, there was one independently significant (p < 5e-8) locus associated with depression symptoms at age 30 and an additional locus at age 40. The SNP-based heritability (h2SNP) of GWASt ranged from 0.01 to 0.05. Following GWASLTH there was one independently significant locus associated with lifetime history of depression, and the h2SNP estimate was 0.15. The age-specific PGI (PGIt) was associated with higher SCL-D symptoms (β=4.21, 95% CI: 6.27, 2.14; p=6.68e-5). The PGILTH was also associated with SCL-D symptoms (β=3.73, 95% CI: 2.78, 4.68).</div></div><div><h3>Discussion</h3><div>Despite the anticipated gains in statistical power from a repeated measures approach in a homogenous sample, we did not detect substantial improvement in genome-wide signal for depression. These results might be due to etiological heterogeneity associated with depression and unobserved confounding. For example, medication status was not available across these time-points and wa","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"99 ","pages":"Pages 15-16"},"PeriodicalIF":6.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MULTIVARIATE GENOME-WIDE ASSOCIATION STUDY OF PTSD, ALCOHOL USE AND ALCOHOL USE DISORDERS","authors":"","doi":"10.1016/j.euroneuro.2025.08.497","DOIUrl":"10.1016/j.euroneuro.2025.08.497","url":null,"abstract":"","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"99 ","pages":"Page 21"},"PeriodicalIF":6.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GENETIC UNDERPINNINGS OF TREATMENT-RESISTANT DEPRESSION: INSIGHTS FROM THE PSYCHSTRATA CONSORTIUM","authors":"Julia Kraft ,&nbsp;Chiara Fabbri ,&nbsp;Eleni Friligkou ,&nbsp;Brittany Mitchell ,&nbsp;Kristi Krebs ,&nbsp;Joanna Biernacka ,&nbsp;Julia Sealock ,&nbsp;Mikael Landén ,&nbsp;Danyang Li ,&nbsp;deCODE Genetics Team ,&nbsp;FinnGen consortium ,&nbsp;Juan De La Hoz ,&nbsp;FinnGen consortium ,&nbsp;Yingzhe Zhang ,&nbsp;Elise Koch ,&nbsp;Bernhard T. Baune ,&nbsp;Stephan Ripke","doi":"10.1016/j.euroneuro.2025.08.535","DOIUrl":"10.1016/j.euroneuro.2025.08.535","url":null,"abstract":"<div><div>Depressive Symptoms in Major Depressive Disorder (MDD) are primarily treated with antidepressant medication. However, a substantial proportion of patients do not achieve a meaningful symptom improvement, even after multiple medication trials, posing a major clinical and public health challenge. Investigating the genetic underpinnings of treatment-resistant depression (TRD) may potentially reveal biological components that contribute to poor treatment outcomes.</div><div>Through the PsychSTRATA consortium, we aim to investigate the biological basis of treatment resistance across major psychiatric disorders, including MDD, bipolar disorder, and schizophrenia. In this study, we focus specifically on the genetic basis of TRD within MDD by performing a genome-wide associations study comparing individuals with and without TRD. In collaboration with many international sites and the antidepressant working group of the PGC, we collated and harmonized data from clinical studies, large-scale biobanks, and population-based cohorts, using electronic healthcare records (EHR), structured clinical interviews, and self-report questionnaires to define TRD.</div><div>Analyses are currently ongoing and leverage data from ∼265,000 individuals with MDD, of whom ∼39,500 were classified as TRD and ∼225,500 as non-TRD. Planned analyses include a GWAS meta-analysis, SNP-based heritability estimation, polygenic risk scoring, and comparisons across definitions to characterize the genetic architecture of TRD and validate genetic findings.</div><div>Our results will lead to an improved understanding of the pharmacogenetic mechanisms underlying TRD and help to identify both disorder-specific and shared genetic contributions with bipolar disorder and schizophrenia. Ultimately, this may inform the development of targeted or novel pharmacological strategies for individuals with treatment resistance.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"99 ","pages":"Page 39"},"PeriodicalIF":6.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"POLYGENIC AGGREGATION OF EQTL EFFECTS REVEALS CELL-TYPE AND TRAIT-SPECIFIC LONG-RANGE REGULATORY PATTERNS","authors":"Toni Boltz,&nbsp;Ajay Nadig,&nbsp;Steve McCarroll,&nbsp;Wei Zhou,&nbsp;Elise Robinson","doi":"10.1016/j.euroneuro.2025.08.527","DOIUrl":"10.1016/j.euroneuro.2025.08.527","url":null,"abstract":"<div><div>Gene regulation varies across genomic regions and cellular contexts, shaped by both linear distance and 3D genome architecture. Recent work on chromosomes 22q and 16p revealed that common polygenic risk for neuropsychiatric disorders - particularly schizophrenia (SCZ), autism, ADHD, and low IQ - is associated with widespread decreases in gene expression across these chromosome arms in neuronal cell types. These findings motivated our development of a scalable method to investigate the extent to which long-range regulatory patterns exist genome-wide, and whether these patterns are specific to neuropsychiatric disease or neuronal cellular contexts.</div><div>To systematically assess how regulatory effects vary with SNP-gene distance, we developed a polygenic risk score (PRS)-inspired framework that aggregates eQTL effect sizes weighted by GWAS effect sizes across different trait and cell-type contexts.</div><div>Our initial analysis successfully replicated the previous 22q findings across four neuronal cell types: glutamatergic and GABAergic neurons, astrocytes, and oligodendrocytes. We observed that SCZ-weighted eQTL effects were consistently negative across distances up to 16 Mb, particularly in glutamatergic neurons and astrocytes, where height-weighted eQTL effects were null. Oligodendrocytes exhibited null effects in both trait contexts. These results confirmed the existence of trait- and cell-type-specific signatures of long-range gene regulation. We subsequently expanded the analysis genomewide, identifying many regions of the genome in which long range eQTL effects could not be identified in any trait context (e.g. chr4: 118Mb - 151Mb), and a small number of regions of the genome in which common variant risk for SCZ, but not somatic traits, was similarly downregulating genes across large genomic territories (e.g. chr1: 1Mb - 33Mb).</div><div>Ongoing work will incorporate additional brain and non-brain cell types, and integrate chromatin contact data to connect spatial genome organization with the observed regulatory patterns. These analyses will provide additional insight into how transcriptome-wide gene dysregulation creates risk for SCZ and other neuropsychiatric disorders, and the assign biological consequence to polygenic influences on psychiatric disease. More broadly, this PRS-style eQTL aggregation framework offers a scalable approach for identifying how genetic risk influences gene regulation across distance, cellular identity, and disease relevance.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"99 ","pages":"Page 34"},"PeriodicalIF":6.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RARE CODING VARIANTS IN 195,257 INDIVIDUALS REVEAL 29 NOVEL BIPOLAR DISORDER GENES AND STRUCTURAL MISSENSE HOTSPOTS IN PROTEIN SPACE","authors":"Calwing Liao,&nbsp;The Bipolar Exome Consortium (BipEx),&nbsp;Benjamin Neale","doi":"10.1016/j.euroneuro.2025.08.543","DOIUrl":"10.1016/j.euroneuro.2025.08.543","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;Background&lt;/h3&gt;&lt;div&gt;Bipolar disorder (BD) is a complex psychiatric disorder characterized by recurrent mood disturbances with significant variations in disease severity and treatment response. Despite its substantial impact on individuals, the genetic factors contributing to BD remain incompletely understood. Here, we present an updated effort from the Bipolar Exome (BipEx) consortium. We increased the effective sample size by 5-fold relative to BipEx 1.0 across diverse populations to investigate the role of protein-truncating variants (PTVs), copy number variants (CNVs), and damaging missense variants in the pathogenesis of BD.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Methods&lt;/h3&gt;&lt;div&gt;Our study cohort comprised 195,257 individuals, including 45,479 cases and 149,778 controls from ancestrally diverse populations. Whole exome sequencing was performed to capture protein-coding regions, followed by robust variant calling and stringent quality control. We analyzed ultra-rare variants with a minor allele count &lt; 5, focusing on PTVs and damaging missense variants. CNVs were identified using GATK-gCNV, focusing on rare exonic deletions and duplications spanning more than three exons. To characterize structural convergence of missense variation, we mapped variant positions to protein 3D structures using AlphaFold and identified significant clustering in spatial neighborhoods across the proteome.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Results/Discussion&lt;/h3&gt;&lt;div&gt;We identified 29 FDR-significant genes, including AKAP11, SHANK1, ATP2B2, KDM5B, and DOP1A, associated with increased burden of PTVs and damaging missense variants. These genes cluster into early and late neurodevelopmental expression patterns and recapitulate clinically relevant pathways, including those associated with clozapine response. Using regional missense constraint metrics, we observed damaging missense variants in BD cases—but not controls—within a highly constrained region of ATP2B2. We also identified significant 3D missense clustering in ATP2A2 and G3BP2, implicating structurally focused hotspots as contributing to BD risk. CNV analysis revealed BPNT2 as the strongest deletion-associated gene (OR: 9.04, P = 2.67 × 10⁻⁹), a known lithium target, and BIRC6 as the most significant duplication hit (OR: 5.04, P = 2.49 × 10⁻¹⁴). We also found evidence for a potential reciprocal CNV locus at 15q11.2, where the duplication increases BD risk while the deletion is depleted in cases.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;Conclusion&lt;/h3&gt;&lt;div&gt;By leveraging data from nearly 200,000 individuals, BipEx 2.0 provides a comprehensive view of rare genetic variation in BD, emphasizing contributions from PTVs, CNVs, and damaging missense variants. The identification of missense-convergent 3D protein hotspots, including in ATP2A2 and G3BP2, highlights the value of integrating structural biology into psychiatric gene discovery. These results illuminate convergent biological mechanisms across variant classes and point to new directions for mechanistic i","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"99 ","pages":"Page 43"},"PeriodicalIF":6.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"REMOVING PLEIOTROPIC SIGNALS REVEAL DISEASE-SPECIFIC GENETIC ARCHITECTURE IN NOISY, SHALLOW BIOBANK PHENOTYPES","authors":"Hyunkyung Kim ,&nbsp;Na Cai ,&nbsp;Andy Dahl","doi":"10.1016/j.euroneuro.2025.08.547","DOIUrl":"10.1016/j.euroneuro.2025.08.547","url":null,"abstract":"<div><div>Pleiotropy is pervasive in complex traits, and understanding it is necessary to characterize shared vs specific genetic effects. Specific effects point to the core biology of a trait, which is especially challenging to characterize in heterogeneous traits such as major depressive disorder (MDD). Exploiting shared effects, on the other hand, can improve statistical power to detect genetic effects and exploit them for polygenic prediction. Large multi-trait genetic datasets, like the UK Biobank, provide opportunities to jointly model these shared and specific effects across thousands of related traits.</div><div>However, the standard approach to understand pleiotropy–genetic correlation–is overly simplistic as it only captures genome-wide aggregate similarity. While more recent approaches have extended genetic correlation to locus-level measures or factor models spanning many traits, it remains challenging to separate trait-specific effects from those that are broadly shared across related phenotypes. For example, genetic effects on alcohol use, and neuroticism will affect MDD, yet they are not specific to MDD nor likely to shed light on its core etiology. Here, we develop a Bayesian matrix factorization approach to address these limitations by partitioning high-dimensional pleiotropic relationships into effects that are shared vs specific to a focal trait of interest.</div><div>First, we applied our approach to simulated data to demonstrate it can reliably separate genetic effects that are specific to a trait vs that are mediated through secondary traits. Our approach outperforms other factorization-based approaches, such as conditioning on phenome-wide PCs. We then applied our approach to identify MDD-specific genetic effects in UK Biobank by accounting for shared genetic effects across 216 MDD-relevant traits. Specifically, we excluded the best-available measure, LifetimeMDD, and evaluated our ability to recapitulate this measure from two lower-quality measures, a GP-based measure and ICD10-based depression. We first show that our approach yields more specific phenotypes, which are more correlated to LifetimeMDD (R2s increase from 0.551 and 0.272 to 0.634 for the GP and ICD10 measures, respectively). Next, we showed that our approach yields better polygenic scores to predict LifetimeMDD (R2s increase from 0.081 and 0.035 to 0.097 for the GP and ICD10 measures, respectively; both p_bootstrap &lt; .01).</div><div>Overall, our approach can be applied to any large-scale, noisy biobank phenotypes to improve their disorder-specificity. This is an important step toward bridging the gap between carefully-phenotyped datasets and shallowly-phenotyped datasets, which is essential for deriving powerful and specific genetic associations in complex traits.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"99 ","pages":"Page 45"},"PeriodicalIF":6.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"POPULATION MEDICAL GENOMICS IN LATIN AMERICA","authors":"Andres Moreno-Estrada","doi":"10.1016/j.euroneuro.2025.08.453","DOIUrl":"10.1016/j.euroneuro.2025.08.453","url":null,"abstract":"<div><div>Global health efforts require genetic profiling and deep phenotyping from diverse populations to better understand individuals’ variation associated with disease and tackle population-specific health problems. The Mexican Biobank Project is generating the most comprehensive nationwide genomic resource from a Latin American admixed population to reveal the evolutionary processes shaping the current diversity of the Mexican population and the genetic basis of chronic and infectious diseases.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"99 ","pages":"Page 1"},"PeriodicalIF":6.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SINGLE-CELL MULTIOMIC APPROACHES FOR UNDERSTANDING HUMAN BRAIN VARIABILITY IN HEALTH AND DISEASE","authors":"Margarita Behrens","doi":"10.1016/j.euroneuro.2025.08.509","DOIUrl":"10.1016/j.euroneuro.2025.08.509","url":null,"abstract":"<div><div>Diversity and individual variability are essential to human cognitive function. Identifying the conserved and variable transcriptomic and epigenomic signatures of the brain’s cellular components is critical for understanding the neurobiological basis of individual variation and how this changes with age and in mental disorders. We will discuss results from a multiomic single-cell epigenome and transcriptome analyses performed on brain samples with sex and age diversity, and show they provide new insight into the diversity of brain-cell molecular identity across individuals. As well, we will discuss age-related changes in the epigenome of specific cell-types in relation to neurological disorders.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"99 ","pages":"Page 26"},"PeriodicalIF":6.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DEVELOPMENTAL ORIGINS OF PSYCHIATRIC RISK: DISSECTING GENE REGULATION THROUGH SINGLE-CELL MULTIOMIC ANALYSIS","authors":"Panos Roussos","doi":"10.1016/j.euroneuro.2025.08.510","DOIUrl":"10.1016/j.euroneuro.2025.08.510","url":null,"abstract":"<div><div>Psychiatric disorders such as schizophrenia, bipolar disorder, major depression, and autism spectrum disorder frequently originate from disruptions in neurodevelopmental processes, many of which unfold long before clinical symptoms emerge. However, dissecting the molecular and regulatory mechanisms that underlie these early developmental perturbations has remained a major challenge, particularly due to limited access to human brain tissue across the lifespan and the complexity of brain cellular diversity.</div><div>To address this, we applied state-of-the-art single-nucleus multi-omic technologies—simultaneously profiling gene expression and chromatin accessibility—to construct high-resolution atlases spanning key stages of human brain development and adulthood. Our datasets encompass over one million nuclei from multiple brain regions, including the dorsolateral prefrontal cortex (DLPFC), a region central to cognition and psychiatric vulnerability, and the olfactory epithelium (OE), a regenerative sensory tissue with neurogenic potential. These integrative datasets enable unprecedented insights into dynamic transcriptional programs and epigenetic regulation during neurodevelopment and aging.</div><div>Through trajectory inference and enhancer-gene regulatory network reconstruction, we identified stage-specific transcription factors and cell-type-specific cis-regulatory modules that guide neuronal and glial lineage commitment. We discovered striking convergence in gene regulatory dynamics between olfactory sensory neuron development and early-stage cortical excitatory neurons, suggesting that the OE may serve as a surrogate system to model human neurodevelopment. Furthermore, integrating our regulatory maps with genome-wide association study (GWAS) loci for major psychiatric disorders allowed us to prioritize putative causal genes and regulatory elements operating at specific developmental windows.</div><div>Collectively, our findings highlight the power of multiomic single-cell analysis in unraveling the developmental origins of psychiatric disease. By linking genetic risk to temporally defined regulatory programs and accessible cell types, this work lays a foundation for future efforts to pinpoint disease mechanisms and therapeutic targets. Moreover, our demonstration that accessible neurogenic tissues can recapitulate key features of brain development opens new avenues for modeling psychiatric risk in vivo.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"99 ","pages":"Page 26"},"PeriodicalIF":6.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"THE ROLE OF SEX IN POLYGENIC RISK FOR SEX-BIASED BRAIN DISORDERS","authors":"Arielle Crestol ,&nbsp;Dennis van der Meer ,&nbsp;Nadine Parker ,&nbsp;Ann-Marie de Lange ,&nbsp;Espen Hagen ,&nbsp;Hannah Oppenheimer ,&nbsp;Stener Nerland ,&nbsp;Edith Breton ,&nbsp;Christian K Tamnes ,&nbsp;Ole A. Andreassen ,&nbsp;Ingrid Agartz ,&nbsp;Claudia Barth","doi":"10.1016/j.euroneuro.2025.08.552","DOIUrl":"10.1016/j.euroneuro.2025.08.552","url":null,"abstract":"<div><div>Sex differences in genetic vulnerability have been implicated in psychiatric and neurodegenerative disorders, yet their specific impact on brain health and clinical risk remains poorly understood. Leveraging data from up to 220,836 women and 187,651 men from the UK Biobank (aged 39–81), we assessed how sex and polygenic risk scores (PRSs) for major depressive disorder (PRSMDD), Alzheimer’s disease (PRSAD), schizophrenia (PRSSCZ), and Parkinson’s disease (PRSPD) relate to case-control status and brain age gap (BAG), a neuroimaging marker of brain health. We tested for sex differences in PRSs and performed regression analyses examining associations between sex, PRSs, and either case-control status or BAG. We then compared models with sex-pooled and sex-specific PRSs to explore whether sex-specific PRSs can improve predictive accuracy. While PRSSCZ was higher in women compared to men, no other sex differences were found between PRSs. Our most striking finding was a significant PRSAD-by-sex interaction, in which PRSAD conferred greater risk for AD diagnosis in women compared to men. Consistently, the women-only PRSAD model outperformed the sex-pooled model, while no differences were observed between sex-pooled and men-only models. By contrast, sex-pooled PRS models outperformed sex-specific PRS models for MDD, SCZ, and PD. No sex-by-PRS interactions were significantly associated with BAG. However, men presented with higher BAG values than women, indicative of an older brain age. Further, higher PRSMDD, higher PRSAD, and lower PRSPD were each associated with higher BAG, irrespective of sex. Finally, BAG model performance did not differ between sex-pooled and sex-specific PRS models. Our findings highlight that sex moderates AD genetic risk for diagnostic status in middle-to-late-life adults, and as such, tailoring PRSs by sex may improve risk assessment for AD. While sex-specific PRSs offered limited value for the other disorders, our findings suggest that the value of sex-specific PRSs will likely grow with increased statistical power.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"99 ","pages":"Page 48"},"PeriodicalIF":6.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145204382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}