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Longitudinal characterization of impulsivity phenotypes boosts signal for genomic correlates and heritability.

Genomic correlates of impulsivity have been identified in several genome-wide association studies (GWAS) using cross-sectional designs, but no studies have investigated the molecular genetic correlates of impulsivity phenotypes using longitudinally constructed traits. In 3860 unrelated European participants in the Avon Longitudinal Study of Parents and Children (ALSPAC), we constructed longitudinal phenotypes for delay discounting and impulsive personality traits (as measured by the UPPS-P impulsive behavior scales) via assessment at ages 24, 26, and 28. We conducted GWASs of impulsivity using both cross-sectional and longitudinal phenotypes, estimated heritability and their phenotypic and genetic correlations, and evaluated their association with recently-developed polygenic risk scores (PRSs) for the impulsivity indicators themselves and also related psychiatric conditions. Latent growth curve modeling revealed a stable intercept over time for all impulsivity phenotypes. High genetic correlation of cross-sectional measures over time suggested a stable genetic component for delay discounting (rg = 0.53-0.99) and sensation seeking (rg = 0.99). Heritability estimates of the stable longitudinal phenotypes substantively improved as compared to their cross-sectional counterparts, revealing a significant SNP-heritability for delay discounting (0.22; p = 0.03) and sensation seeking (0.35; p = 0.0007). Consistent with previous reports, GWAS and gene-based analyses revealed associations between specific longitudinal impulsivity indicators and CADM2 and NCAM1 genes. The PRSs for the impulsivity indicators and disorders related to self-regulation were also significantly associated with longitudinal impulsivity traits. Finally, we validated the associations between longitudinal impulsivity phenotypes and their PRSs in an independent 13-wave longitudinal study (n = 1019) and the benefit of longitudinal phenotypes in simulation studies. In this first longitudinal genetic study of impulsivity traits, the results revealed stable genomic correlates of delay discounting and sensation seeking over time and further validated the utility of recently-developed PRSs, both in relation to the observed traits and in connecting them to psychiatric disorders. More generally, these findings support using latent intercepts as novel longitudinal phenotypes to boost signal for heritability and genomic correlates of mechanisms contributing to psychiatric disease liability.

Humans

Polygenic and developmental profiles of autism differ by age at diagnosis.

Although autism has been historically conceptualised as a condition that emerges in early childhood, many autistic people are diagnosed later in life. It is unknown whether earlier and later diagnosed autism have different developmental trajectories and genetic profiles. Using longitudinal data from four independent birth cohorts, we demonstrate that two different socioemotional and behavioural trajectories are associated with age at diagnosis. In independent cohorts of autistic individuals, common genetic variants account for approximately 11% of the variance in age at autism diagnosis, comparable to the contribution of individual sociodemographic and clinical factors, which typically explain less than 15% of this variance. We further demonstrate that the polygenic architecture of autism can be decomposed into two modestly genetically correlated (rg = 0.38, SE = 0.07) autism polygenic factors. One of these factors is associated with earlier autism diagnosis, and lower social and communication abilities in early childhood but is only modestly genetically correlated with ADHD and mental health conditions. Conversely, the second factor is associated with later autism diagnosis, increased socioemotional and behavioural difficulties in adolescence, and has moderate to high positive genetic correlations with Attention-Deficit/Hyperactivity Disorder and mental health conditions. These findings indicate that earlier and later diagnosed autism have different developmental trajectories and genetic profiles. Our findings have important implications for how we conceptualise autism and provide one model to explain some of the diversity within autism.

Journal Article

Polygenic and developmental profiles of autism differ by age at diagnosis.

Although autism has historically been conceptualized as a condition that emerges in early childhood1,2, many autistic people are diagnosed later in life3-5. It is unknown whether earlier- and later-diagnosed autism have different developmental trajectories and genetic profiles. Using longitudinal data from four independent birth cohorts, we demonstrate that two different socioemotional and behavioural trajectories are associated with age at diagnosis. In independent cohorts of autistic individuals, common genetic variants account for approximately 11% of the variance in age at autism diagnosis, similar to the contribution of individual sociodemographic and clinical factors, which typically explain less than 15% of this variance. We further demonstrate that the polygenic architecture of autism can be broken down into two modestly genetically correlated (rg = 0.38, s.e. = 0.07) autism polygenic factors. One of these factors is associated with earlier autism diagnosis and lower social and communication abilities in early childhood, but is only moderately genetically correlated with attention deficit-hyperactivity disorder (ADHD) and mental-health conditions. Conversely, the second factor is associated with later autism diagnosis and increased socioemotional and behavioural difficulties in adolescence, and has moderate to high positive genetic correlations with ADHD and mental-health conditions. These findings indicate that earlier- and later-diagnosed autism have different developmental trajectories and genetic profiles. Our findings have important implications for how we conceptualize autism and provide a model to explain some of the diversity found in autism.

Humans

Genome-wide analysis of screen behaviors among adolescents identifies novel loci and overlap with educational attainment and mental disorders.

Technological devices play a central role in adolescents' life. Despite concerns about negative effects of excessive screen time, there is little knowledge of screen behaviors' genetic architecture. Using self-reports from adolescents in the Norwegian Mother, Father, and Child Cohort Study (n = 18,490), we performed genome-wide association analysis for four screen behaviors: time spent (1) watching television; (2) gaming; (3) sitting/lying down with a screen device; and (4) using social media. The resulting summary statistics were analysed using the conditional false discovery rate (condFDR) approach to increase genetic discovery. We also estimated SNP-heritabilities of the screen behaviors and genetic correlations with eight psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, attention-deficit hyperactivity disorder, anorexia nervosa, cannabis use disorder and alcohol use disorder), and educational attainment. Screen behaviors displayed significant SNP-heritabilities (0.048-0.12). We observed significant genetic correlations between screen behaviors and psychiatric disorders (rg range: 0.21-0.42). Educational attainment demonstrated negative genetic correlation with screen behaviors, most strongly with social media use (rg = - 0.69). CondFDR analysis identified three novel loci associated with social media use. Thus, we show that screen behaviors are heritable, polygenic traits that partly share genetic signal with mental disorders and educational attainment.

Humans

The relationship between vitamin D levels and depression: a genetically informed study.

BACKGROUND: Low vitamin D (vitD) levels are consistently associated with an increased risk of depression. However, the biological mechanisms underlying this relationship and potential shared genetic overlap remain elusive. METHODS: We investigated the genetic overlap and causal relationships between depression (N = 589,356) and vitD levels (N = 417,580) using genome-wide association study (GWAS) summary statistics. We performed genome-wide and local genetic correlation analyses, followed by quantification of polygenic overlap variants. Shared genetic loci were identified and mapped to genes, which were further analyzed through gene expression and lifespan brain expression trajectory analyses. Bidirectional causal relationships were examined using multiple Mendelian randomization approaches. RESULTS: We observed significant negative genetic correlations (rg = -0.079) and identified genetic overlap (N = 410 variants). Genes mapped to the 13 shared loci showed opposing expression patterns. Tissue- and cell-specific functional enrichment analyses revealed significant signals related to brain development, with distinct patterns emerging between fetal development and adulthood. Shared genes (TRMT61A, ITIH4, RASGRP1, CTNND1, HERC1, IP6K1, FURIN ESR1, ZMYND and GRM5) exhibited notable expression variation in the brian throughout the lifespan, aligning with functional enrichment findings. CONCLUSIONS: Our findings elucidate the shared biological mechanisms underlying the relationship between vitD and depression, suggesting that vitD play an important role in the development of depression through altered early neurodevelopmental processes.

Humans

Assessing the genetic potential of a milk mid-infrared prediction of heat stress response in dairy cows using a temperature-humidity index-independent approach.

Selection for heat tolerance remains challenging due to the difficulty of accessing reliable phenotypes at large scale. An alternative could be established using mid-infrared spectra, which are collected routinely through milk recording, and have already shown their value as proxies for a variety of phenotypes that are costly or difficult to measure. Recently, a first prediction of heat stress response in dairy cows based solely on milk mid-infrared spectra was developed. This prediction was obtained using models calibrated on surface body temperature and milk composition variations. Its potential as a detection tool was explored, but no genetic analyses has been performed. On this basis, the objectives of this study were to estimate the heritability of the predicted heat stress response, assess its genetic correlations with traits from the Walloon official genetic evaluation, and identify genomic regions associated with heat tolerance through a GWAS, all without using temperature-humidity index (THI) information. The estimated heritability (0.10) was low but sufficient to enable genetic selection and consistent with expectations for a heat stress-related trait. Also as expected, an antagonistic relationship between heat tolerance and milk production was observed, but its extent was notably reduced compared with traditional approaches. In addition, genetic correlations with other traits were neutral (fat yield) or favorable (protein yield, SCS, fertility, longevity). Concerning the GWAS, genomic regions and candidate genes previously associated with the response to heat stress were highlighted, as well as others related to energy balance maintenance. Overall, these results support the relevance of the prediction for the heat stress response as a new phenotype for heat tolerance selection that does not require any THI information. They also reinforce the importance of energy balance for dairy cows to cope with heat stress.

Journal Article

Genomic response to sex-separated gene pools.

Males and females experience differences in the strength and direction of selection but discerning the type of genes that are targets of sex differences in selection is complicated by their shared genome. We used experimental evolution in Drosophila melanogaster to partially separate the gene pools of males and females for 130 generations. In six replicate populations, we forced one pool of genetically variable Chromosome 2s to experience patrilinear inheritance (segregating like a Y-chromosome) and male-limited selection. The alternative pool segregated like an X-chromosome and experienced female-biased selection. This allowed alleles which are differentially selected for between the sexes to diverge between these pools, enabling us to gain insight into the type of genes subject to such selection. We find that genes which diverge between these pools have an elevated intersexual genetic correlation(rMF) for expression on average, consistent with the idea that high genetic correlations may hinder sex-specific adaptation under normal inheritance. Diverged genes were also enriched for moderately male-biased genes whereas female-biased genes were underrepresented. At the SNP level, we find an overrepresentation of diverged SNPs involved in splicing or occurring in the 5'UTR and an underrepresentation of missense or synonymous SNPs, suggesting sex differences in selection for isoform usage.

intersexual genetic correlation

Genetic evidence links hypertension to accelerated brain aging.

Hypertension affects one-third of adults and is a major comorbidity of neurocognitive disorders. The causal relationship, shared genetic architecture, and upstream mechanisms linking hypertension to brain aging remain unclear. Hypertension GWAS datasets from MVP and FinnGen R12 were meta-analyzed as the exposure, and a European-ancestry brain age gap (BAG) GWAS derived from the UK Biobank and LIFE-Adult cohorts was used as the outcome. MR and GSMR assessed causality. LDSC, HDL, and S-LDSC estimated genetic correlation. Four TWAS methods (MAGMA, FUSION, JTI-PrediXcan, FOCUS) mapped associations to genes, followed by SMR for causal validation and PoPS for prioritization. GSMAP with spatial transcriptomics characterized regional and cell-type enrichment. Hypertension and brain aging were genetically correlated, and MR and GSMR analyses suggested a causal effect of hypertension on increased brain age gap. TWAS identified 15 shared Hypertension-BAG genes, 10 supported by SMR. PoPS prioritized TRIM47 as the core gene. Shared signals were enriched in meninges, fiber tracts, cortical layer 1, and CA1 stratum lacunosum/radiatum, with cell-type enrichment in meninges, smooth muscle cells, oligodendrocytes, and astrocyte subtypes. Hypertension is genetically correlated with, and shows evidence of a causal effect on, accelerated brain aging. TRIM47 is a core gene bridging hypertension and BAG. GSMAP-based spatial enrichment provides a hypothesis-generating framework for understanding vascular, meningeal, and myelin-related pathways linking hypertension to increased brain age gap.

Humans

Post-traumatic stress disorder and REM-sleep behavior disorder: exploring genetic associations and causal links.

OBJECTIVE: To explore potential genetic and/or causal associations between Post-Traumatic Stress Disorder and neurodegeneration-related isolated/idiopathic rapid-eye-movement sleep behavior disorder. METHODS: We conducted polygenic risk score, genetic correlation, and Mendelian randomization analyses using the latest genome-wide association studies summary statistics and individual genotyping data. Next, a blinded observer examined dopamine transporter imaging binding status-a marker of neurodegeneration-in patients with isolated/idiopathic rapid-eye movement sleep behavior disorder, with (N = 6) and without Post-Traumatic Stress Disorder (N = 32). RESULTS: Polygenic risk scores for Post-Traumatic Stress Disorder were associated with isolated/idiopathic rapid-eye-movement sleep behavior disorder, with each standard deviation increase linked to 14.7% higher odds (odds ratio = 1.15, 95% confidence interval: 1.04 to 1.26, p = 0.005). However, genetic correlation was weak, and Mendelian randomization did not support a potential causal relationship. The proportion of individuals with abnormal dopamine transporter imaging binding status was significantly higher in the Post-Traumatic Stress Disorder group compared to those without the disorder (p=0.01, X2 = 6.62). INTERPRETATION: Polygenic risk scores analysis identified an association between Post-Traumatic Stress Disorder and neurodegeneration-related isolated/idiopathic rapid-eye-movement sleep behavior disorder, consistent with the result from the small exploratory substudy. The lack of strong genetic correlation or causation may reflect limited sample size. Further research with larger and more diverse cohorts is crucial to clarify the genetic, biological and physiological mechanisms underlying this association.

Journal Article

Revealing the Shared Genetic Architecture of Metabolic Dysfunction-Associated Steatotic Liver Disease-Related Traits Through Genomic Structural Equation Modeling.

Although individual traits related to metabolic dysfunction-associated steatotic liver disease (MASLD) have been investigated through large-scale genome-wide association studies (GWASs), the shared genetic susceptibility across these traits remains unclear. We therefore conducted a multivariate GWAS of key MASLD-related traits to elucidate their common genetic architecture. We applied genomic structural equation modeling to model a latent genetic factor (MASLD-F) underlying genetically correlated MASLD-related traits, leveraging their GWAS-derived genetic correlations. We then performed functional annotations, including fine-mapping, transcriptome-wide association study, and cell- and tissue-type-specific enrichment analyses, and conducted Mendelian randomization analyses to identify modifiable risk factors. Our multivariate MASLD-F GWAS identified 50 independent variants across 48 genomic loci. Transcriptomic imputation identified several MASLD-F-associated genes, including ARNTL, NPC1, BTBD10, VDAC2, TSKU, SFMBT1, and ABHD17C. We observed significant enrichment of MASLD-F-related genetic signals predominantly in brain tissues, pancreatic islets, and the adrenal gland. Additionally, six modifiable risk factors and four modifiable protective factors for MASLD-F were identified. These findings reveal a complex shared genetic architecture underlying MASLD components, thereby expanding our understanding of disease pathogenesis and providing novel insights for precision medicine and public health interventions.

Humans

Genetic architecture of endometriosis: risk factors, comorbidities and clinical implications.

BACKGROUND: In 1999, Dr Susan Treloar and colleagues conducted a landmark twin study in Australia and reported their estimate of 51% for the heritability of endometriosis. This important result led several groups to begin mapping genetic factors contributing to increased endometriosis risk. Despite early challenges, advances in genome-wide association studies (GWAS) have identified multiple genetic risk factors and some target genes implicated in follow-up studies on genetic regulation of transcription. Access to large publicly available genetic datasets and analysis with endometriosis GWAS results is also providing new opportunities to answer important questions about comorbid conditions associated with endometriosis and their implications for clinical practice. OBJECTIVE AND RATIONALE: The objective of the review is to summarize the last 25 years of genetic studies in endometriosis, outline contributions to our understanding of the disease, and suggest future directions to accelerate biological insights from genetic studies to improve clinical outcomes. SEARCH METHODS: A comprehensive review of scientific literature on the genetics of endometriosis was conducted through searches in PubMed and Google Scholar up to June 2026. Search terms included "endometriosis AND (genetics OR GWAS OR genetic risk factors)", For studies addressing the functional characterization of genetic risk loci, additional searches employed the terms "endometriosis AND (genotype-phenotype associations OR colocalization OR eQTL OR mQTL OR multi omics methods)". To identify studies examining shared genetic risk between endometriosis and comorbid conditions, the search strategy included "endometriosis AND (genetic correlation OR colocalization OR Mendelian randomisation)". Publications reporting discoveries related to genetic risk factors for endometriosis and studies interpreting their biological and clinical significance were critically evaluated, and 144 publications were discussed in the review. OUTCOMES: Discovery of genetic risk factors started slowly and has accelerated in recent years with developments in technology and international collaborations to combine data and increase statistical power. GWAS have mapped 80 genetic risk factors that implicate gene regulation of hormonal targets, development of the reproductive tract, regulation of cell proliferation, and regulation of epithelial cell differentiation. In common with most other complex diseases, effects of individual common genetic risk factors are small. However, several examples demonstrate that small effect sizes are not a good predictor for the impact of drugs developed against genetically validated targets. Genetic risk factors implicate five genes regulating gonadotrophin release and oestrogen action, the major target pathway of current drugs for treatment of endometriosis demonstrating proof-of-principal for biologically meaningful results. Genetic correlation and Mendelian Randomization studies highlight important causal relationships between endometriosis and comorbid conditions including a possible role for testosterone during development and shared genetic risk factors for gynaecological, gastrointestinal, pain, psychiatric, and inflammatory conditions. Understanding causal relationships between endometriosis and related conditions will aid clinical management and more personalized treatments. WIDER IMPLICATIONS: Genetic studies provide novel insights into endometriosis pathogenesis and associations with related comorbid conditions. Genetic factors modifying gene regulation and disease risk likely act in specific cell types, and access to datasets from genetically informed cell-based models, single-cell and spatial omics data are needed to accelerate progress. Future studies should address critical questions of heterogeneity and disease subtypes, expand the search for genetic risk factors to non-European populations, evaluate the role of rare and structural variants, and better integrate data from functional, genomics, genetics, and clinical studies to reduce diagnostic delay, develop novel treatment strategies, and translate discoveries into personalized management strategies for affected individuals. REGISTRATION NUMBER: N/A.

comorbid conditions

GWAS meta-analysis provides new insights into uveal melanoma risk.

OBJECTIVE: The aim of this research is to identify germline genetic variants that predispose to uveal melanoma (UM) using data from nine studies involving 5839 individuals with UM (3853 novel) and 349,863 healthy controls. METHODS: Five novel UM genome-wide association studies (GWAS) were performed and included for meta-analysis with four previously published UM GWAS. A fixed-effects inverse-variance weighted (IVW) meta-analysis was performed by combining data from these nine UM case-control cohorts. A follow-up transcriptome-wide association study (TWAS) was conducted to identify candidate target genes at UM risk loci. Genetic correlations with melanoma-related phenotypes were measured to elucidate UM's genetic architecture. RESULTS: We identify nine linkage disequilibrium (LD)-independent loci (three novel) with an IVW P value of less than 5 × 10-8. TWAS analysis indicates five potential target genes, including MOB3B, RBAK, and MTSS1, which have established links to multiple cancer types. We note a significant genetic correlation (rg = 0.31, P = 0.01) between UM and cutaneous melanoma (CM), and a non-significant but consistent correlation with naevus count (rg = 0.25, P = 0.08). CONCLUSIONS: This meta-analysis offers new insights into the genetic architecture of UM, highlights potential therapeutic targets, and explores the genetic relationship with CM and skin pigmentation.

Humans

The genetic architecture of fibromyalgia across 2.5 million individuals.

Fibromyalgia is a common and debilitating chronic pain syndrome of poorly understood etiology. Here, we conduct a multi-ancestry genome-wide association study meta-analysis across 2,563,755 individuals (54,629 cases and 2,509,126 controls) from 11 cohorts, identifying the first 26 risk loci for fibromyalgia. The strongest association was with a coding variant in HTT, the causal gene for Huntington's disease. Gene prioritization implicated the HTT regulator GPR52, as well as diverse genes with neural roles, including CAMKV, DCC, DRD2/NCAM1, MDGA2, and CELF4. Fibromyalgia heritability was exclusively enriched within brain tissues and neural cell types. Fibromyalgia showed strong, positive genetic correlation with a wide range of chronic pain, psychiatric, and somatic disorders, including genetic correlations above 0.7 with low back pain, post-traumatic stress disorder and irritable bowel syndrome. Despite large sex differences in fibromyalgia prevalence, the genetic architecture of fibromyalgia was nearly identical between males and females. This work provides the first robust genetic evidence defining fibromyalgia as a central nervous system disorder, thereby establishing a biological framework for its complex pathophysiology and extensive clinical comorbidities.

Journal Article

Common genetic variants are associated with increased likelihood of latent co-occurring neurodevelopmental and mental health factors among autistic individuals.

Autistic individuals show elevated rates of co-occurring neurodevelopmental and mental health conditions, yet the genetic architecture of those comorbidities remains unclear. Using phenotypic (N = 74,204) and genetic (N = 17,582) data from the SPARK study, we investigated the factor structure, heritability, genetic correlation with autism (pleiotropy) and corresponding conditions in the general population (additivity). First, confirmatory factor analysis identified three correlated factors mirroring general population patterns: behavioural (ADHD, disruptive behaviour disorders), cothymic (depression, anxiety), and thought disorder (schizophrenia, bipolar). Second, all three factors had significant SNP heritabilities whilst rare variants were not associated with the tested factors in our sample. Third, polygenic scores and genetic correlations revealed positive shared genetics between the three factors and corresponding conditions in the general population but not with autism, supporting the additivity hypothesis. Fourth, within-family analyses (N = 5236 trios) demonstrated direct but not indirect genetic effects for the behavioural and cothymic factors. In sum, we find evidence for additive effects of other genetic factors in contributing to some latent co-occurring neurodevelopmental and mental health conditions in autism.

Journal Article

Conventional and Shared Genetic Association Analysis Between Diabetes Mellitus and Sensorineural Hearing Loss.

PURPOSE: This study aims to investigate the epidemiological and genetic associations between diabetes mellitus (DM) and sensorineural hearing loss (SNHL) across different subtypes. METHODS: We analyzed 502,490 participants from the UK Biobank using multivariate logistic regression to examine the association between DM and SNHL, considering gender, age, and HbA1c levels. Genetic correlations and causality were examined by linkage disequilibrium score regression and bidirectional Mendelian randomization. Cross-trait meta-analyses identified shared loci between DM and SNHL, followed by gene annotation, functional analysis, and drug candidate exploration for the shared traits. RESULTS: Observational analysis revealed significant associations between DM and SNHL, consistent in subgroups based on age, sex, and certain HbA1c levels. A positive genetic correlation was found between type 2 diabetes mellitus (T2D) and SNHL (Rg = 0.0982, p = 0.0095) between T2D and SNHL, and four loci were identified, with ARHGEF28 and TCF7L2 prioritized as credible pleiotropic genes. Enrichment was indicated in glucose metabolism and organogenesis, with shared heritability in metabolic tissues and outer hair cells. Metformin was identified as potential drug candidates for the T2D-SNHL comorbidity. CONCLUSION: These findings progress our understanding of the epidemiological association, shared genetic basis, and potential therapeutic targets between T2D and SNHL, which might contribute to the management of their comorbidity.

Humans

Shared genetic architecture and cellular convergence between female reproductive disorders and pulmonary function: a genome-wide cross-trait analysis.

Female reproductive disorders (FRDs), including polycystic ovary syndrome, endometriosis, uterine leiomyomata, and infertility, have been epidemiologically associated with impaired pulmonary function. However, it remains unclear whether this cross-organ link reflects shared genetic etiology and, if so, which cellular mechanisms mediate it. We performed a systematic genome-wide cross-trait analysis of three FRDs and lung function traits (FEV₁, FVC, FEV₁/FVC) using GWAS summary statistics from individuals of European ancestry, integrating genetic correlation, bidirectional causal inference, pleiotropy mapping, and single-cell enrichment analyses. We identified significant negative genetic correlations between FRDs and lung volume traits, most prominently for FVC (rg range: - 0.077 to - 0.178). Bidirectional causal analyses indicated that FRDs have a detrimental effect on lung volume, with higher FRD genetic liability associated with reduced lung volume. Cross-trait meta-analysis identified 17 pleiotropic variants across 11 loci, with the 19q13.2 (LTBP4) and 12q13.13 (HOXC6/HOXC9) loci showing strong evidence of shared causal variants. Critically, single-cell analyses revealed that shared genetic risk converged on mesenchymal lineages across organs, specifically alveolar adventitial fibroblasts in the lung and stromal/smooth muscle cells in the endometrium. Transcriptome-wide analyses further nominated the estrogen-responsive gene RERG as a convergent gene linking these conditions with lung function. Our study revealed a shared genetic architecture between female reproductive disorders and lung function traits, providing a basis for further mechanistic investigations and potential clinical evaluation. Furthermore, our findings suggest that shared fibroproliferative and hormone-responsive pathways may offer insights into the biological mechanisms underlying these conditions.

Female

Genetic structure correlates with ethnolinguistic diversity in eastern and southern Africa.

African populations are the most diverse in the world yet are sorely underrepresented in medical genetics research. Here, we examine the structure of African populations using genetic and comprehensive multi-generational ethnolinguistic data from the Neuropsychiatric Genetics of African Populations-Psychosis study (NeuroGAP-Psychosis) consisting of 900 individuals from Ethiopia, Kenya, South Africa, and Uganda. We find that self-reported language classifications meaningfully tag underlying genetic variation that would be missed with consideration of geography alone, highlighting the importance of culture in shaping genetic diversity. Leveraging our uniquely rich multi-generational ethnolinguistic metadata, we track language transmission through the pedigree, observing the disappearance of several languages in our cohort as well as notable shifts in frequency over three generations. We find suggestive evidence for the rate of language transmission in matrilineal groups having been higher than that for patrilineal ones. We highlight both the diversity of variation within Africa as well as how within-Africa variation can be informative for broader variant interpretation; many variants that are rare elsewhere are common in parts of Africa. The work presented here improves the understanding of the spectrum of genetic variation in African populations and highlights the enormous and complex genetic and ethnolinguistic diversity across Africa.

Africa, Southern

Integrative Genomic and Functional Investigation of the Multi-Layered Genetic Architecture Between Anorexia Nervosa and Bone Loss.

OBJECTIVE: Bone loss is a severe and often irreversible complication of anorexia nervosa (AN), yet the genetic mechanisms underlying this comorbidity remain underexplored. This study focuses on constructing a comprehensive genetic architecture between AN and estimated calcaneal bone mineral density (eBMD). METHOD: We applied an integrative framework incorporating genetic correlation, pleiotropic association, and causal inference across single-variant, multi-variant, and gene expression levels. Functional validation was conducted in vitro to investigate the biological role of the key candidate gene. RESULTS: Local genetic correlation analysis identified significant signals at 8p21.2 and 10q26.3, despite the lack of significant global correlation. Mendelian randomization analysis pointed to a suggestive negative causal effect of genetically predisposed AN on eBMD. Extensive pleiotropic signals were detected, particularly at 3p21.31 and 10q26.3, loci enriched with genes associated with both traits. Notably, we identified a novel pleiotropic signal near NCAM1 at 11q23.2, which was supported by multi-layered genetic evidence and confirmed through in vitro functional experiments. NCAM1, a well-established neural-associated gene, promoted osteoclastic differentiation and bone resorption when overexpressed in osteoclast precursor cells, indicating that NCAM1 possesses distinct functional roles in both neural and skeletal tissues. DISCUSSION: This study constructs a comprehensive genetic architecture underlying AN and eBMD and highlights NCAM1 as a key pleiotropic gene.

anorexia nervosa