SEARCH · PubMed Health

Results for “GWASs”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed2025

A Comprehensive Review of GWASs of Human Hair Traits.

Hair traits are nonpathogenic features that vary among individuals. Unlike hair follicle (HF) diseases, which are rare in the population, hair traits can be measured in everyone. This facilitates the construction of large cohorts that are well-powered for gene discovery. GWASs identify genetic variants that are widely shared among people globally, providing knowledge with broad population relevance. We compile findings from hair trait GWASs to deepen our understanding of HF biology. In reviewing genetic factors that influence hair traits, we demonstrate overlap with disease genes, underscoring that genetic studies of traits improve our knowledge about health and disease.

Humans↗

PubMed2026

Can Psychiatric Genetics Advance Without Incorporating a Life Course Perspective?

Psychiatric disorders unfold over the life course; however, genomic studies of these conditions overwhelmingly rely on phenotypes collected at a single time point, often in adulthood. Therefore, genome-wide association studies (GWASs) of psychiatric conditions may miss genetic variants with time-varying relevance to etiology, prevention, and treatment, such as those that influence trajectories of symptoms and behaviors, age at onset, course of treatment response, and the co-evolution of comorbidities. With recent advances in longitudinal biobanks and analytic tools, we posit that incorporating a life course perspective in psychiatric genetics will enable critically relevant insights into each of these areas of investigation. We propose that the current inconsistent portability of polygenic scores across age groups can be reconciled through the design of carefully considered longitudinal GWASs in age-diverse samples. Pioneering longitudinal GWASs in psychiatry have revealed novel genomic signals associated with time-dependent phenotypes that are distinct from those influencing lifetime diagnosis, suggesting that the study of longitudinal phenotypes will complement cross-sectional approaches and empower biological and therapeutic discoveries. Advances in post-GWAS functional annotation resources and analytic approaches now enable us to contextualize the genetic contributions to psychiatric disorders as dynamic age- and exposure-dependent processes. Although longitudinal GWASs pose unique challenges with regard to data availability, selection bias, and missing data, integrating temporality into psychiatric genetics at scale is now attainable and promises to reveal novel biology and therapeutic opportunities for psychiatric conditions.

Cohort study↗

PubMed2025

Genome-wide association studies in chronic venous disease: A systematic review.

BACKGROUND: Chronic venous disease (CVD) arises from venous hypertension secondary to impaired venous return, causing significant morbidity and diminished quality of life. Genetic factors are likely important in the pathogenesis and susceptibility of a patient to develop CVD. This systematic review summarizes genome-wide association studies (GWASs) that investigate the link between genetic variants and CVD. METHODS: A systematic review was conducted in accordance with the PRISMA guidelines, with the search dates ranging from January 1, 1994, to July 17, 2025. Abstract and full-text screening were completed by two independent reviewers, with any conflicts referred to a third senior reviewer. GWASs in adults investigating links between genetic variants and CVD were included. Exclusion criteria included patients with venous thromboembolism, arterial or diabetic disease, or animal models. RESULTS: Thirteen studies were included after screening 517 studies from a search of PubMed, EMBASE, and Ovid. Database sources included UK Biobank, FinnGen, PopGen, and country- or hospital-specific databases with a majority Caucasian and European patient cohort. A total of 602,760 patients were identified with varicose veins and 3,664,604 control cases that were studied with GWASs and other statistical methods including a two-sample Mendelian randomization approach, functional mapping, and genetic correlations. A variety of statistically significant genetic polymorphisms were identified that can be attributed to the heritability of varicose veins affecting inflammation and immunity (eg, PPP3R1, EBF1, and GATA2), hypertension (eg, CASZ1), and vascular architecture (eg, CASZ1, PIEZO1, and STIM2). Protective variants (eg, GJD3, MMP10, and 4EBP1) were also identified in Finnish populations. However, replication studies showed that these genetic polymorphisms are not generalizable to specific populations. CONCLUSIONS: This systematic review highlights genes contributing to the development of CVD that have been identified in the literature. An improved understanding of genetic contributions to the pathogenesis of CVD may inform future diagnostics, prognostics, and personalized treatment. Further larger scale studies representative of global populations, including meta-analyses of genome-wide association datasets, are required owing to individual GWASs being statistically insufficient to draw generalizable conclusions.

Humans↗

PubMed2025

Identification of novel type 1 and type 2 diabetes genes by co-localization of human islet eQTL and GWAS variants with colocRedRibbon.

Over 1,000 genetic variants have been associated with diabetes by genome-wide association studies (GWASs), but for most, their functional impact is unknown; only 7% alter gene expression in pancreatic islets in expression quantitative trait locus (eQTL) studies. To fill this gap, we developed a co-localization pipeline, colocRedRibbon, that prefilters eQTLs by the direction of effect on gene expression and shortlists overlapping eQTL and GWAS variants prior to co-localization. Applying colocRedRibbon to recent diabetes and glycemic trait GWASs, we identified 292 co-localizing gene regions, including 24 co-localizations for type 1 diabetes and 268 for type 2 diabetes and glycemic traits, representing a 4-fold increase. A low-frequency type 2 diabetes protective variant increases islet MYO5C expression, and a type 1 diabetes protective variant increases FUT2 expression. These novel co-localizations advance the understanding of diabetes genetics and its impact on human islet biology. colocRedRibbon has broad applicability to co-localize GWASs and various QTLs.

Humans↗

PubMed2026

Anthropometric and cardio-metabolic trait variation and genetic associations in sub-Saharan Africa.

The genetics of complex traits in Africa has been historically understudied, which can contribute to healthcare inequalities. Here, we present observations of 27 anthropometric, cardiovascular, and blood biomarker measurements across 2,124 individuals from sub-Saharan Africa for whom we also have dense genotype data. First, we identified trait values that differ significantly across populations and subsistence lifestyles (e.g., hemoglobin levels and height). We then identified traits with high degrees of sexual dimorphism (e.g., weight and grip strength). ADMIXTURE analyses revealed substantial population structure in our dataset, and many of the phenotypes studied here are correlated with genetic ancestry components, particularly skin color and body size traits. A variance partitioning approach further revealed traits in which much of the SNP heritability is due to polymorphisms that also contribute to differences between ancestry components. Following genomic imputation, we performed genome-wide association studies (GWASs) for all 27 traits and identified >100 independent autosomal SNPs with genome-wide significant associations for at least one trait (p < 5 × 10-8). Many of these trait-associated variants are rare outside of Africa (minor-allele frequency [MAF] < 1%). We found that 100 kb windows surrounding the top GWAS hits from our African-ancestry cohort were enriched for trait associations in an identically sized European cohort and vice versa. We performed a more detailed analysis of height prediction from genetic data, finding that genome-wide admixture proportions predict height in Africans better than polygenic predictors based on large-scale European height GWASs.

Female↗

PubMed2025

Admixture-mapping analysis reveals genetic determinants of the human plasma proteome.

Protein profiling and genetic findings can be integrated to define the genetic architecture of the circulating proteome in chronic diseases. Most self-identified African American (AA) individuals have both African and European genetic ancestry. Admixture mapping can detect genomic association regions in which causal variants exist with substantial differences in allele frequency or effect sizes between genetic ancestries. We performed admixture mapping of the circulating proteome in 1,989 participants from the Jackson Heart Study (JHS), investigating the relation of local African ancestry within genomic regions with levels of circulating proteins. We conditioned protein-local ancestry association models on variants previously found to be associated with those proteins in genome-wide association studies (GWASs). We replicated findings in 196 AA participants from the Multi-Ethnic Study of Atherosclerosis (MESA). 62 proteins were associated with local African ancestry. 21 of 62 remained statistically significant after conditioning on protein-associated variants observed in previous GWASs. 48 of 54 available protein-local ancestry associations were replicated in the MESA. Proteins associated with local African ancestry included chemokines, factors associated with vascular biology and inflammation, and other biologically interesting proteins. Admixture associations unexplained by previously reported protein-associated variants in conditional analysis suggest the existence of causal variants missed by standard GWAS techniques.

Aged↗

PubMed2024

Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes.

Type 2 diabetes (T2D) genome-wide association studies (GWASs) often overlook rare variants as a result of previous imputation panels' limitations and scarce whole-genome sequencing (WGS) data. We used TOPMed imputation and WGS to conduct the largest T2D GWAS meta-analysis involving 51,256 cases of T2D and 370,487 controls, targeting variants with a minor allele frequency as low as 5 × 10-5. We identified 12 new variants, including a rare African/African American-enriched enhancer variant near the LEP gene (rs147287548), associated with fourfold increased T2D risk. We also identified a rare missense variant in HNF4A (p.Arg114Trp), associated with eightfold increased T2D risk, previously reported in maturity-onset diabetes of the young with reduced penetrance, but observed here in a T2D GWAS. We further leveraged these data to analyze 1,634 ClinVar variants in 22 genes related to monogenic diabetes, identifying two additional rare variants in HNF1A and GCK associated with fivefold and eightfold increased T2D risk, respectively, the effects of which were modified by the individual's polygenic risk score. For 21% of the variants with conflicting interpretations or uncertain significance in ClinVar, we provided support of being benign based on their lack of association with T2D. Our work provides a framework for using rare variant GWASs to identify large-effect variants and assess variant pathogenicity in monogenic diabetes genes.

Diabetes Mellitus, Type 2↗

PubMed2026

Optimizing Control Definitions in Opioid Use Disorder Genetic Research Using Electronic Health Records.

Amidst the opioid crisis, understanding the genetic basis of opioid use disorder (OUD) is crucial for identifying biological mechanisms and intervention points. However, genome-wide association studies (GWASs) have been hampered by inadequate sample sizes and often the use of control populations not assessed for prior opioid exposure. Because opioid exposure is a prerequisite for the development of OUD, consideration of exposure history in controls is important. Electronic health record data (EHR) paired with genomic information allow a broader sampling of patients with OUD and exposed controls. We leveraged data across two healthcare systems to evaluate the impact of using controls not screened for opioid exposure ('generic') versus minimally opioid-exposed control ('exposed'). First, at the phenotypic level, we conducted phenome-wide association studies (PheWAS) to compare the medical comorbidity profiles of OUD cases when using generic versus exposed controls. While PheWAS results for OUD-related comorbidities were more pronounced when using the generic group, 83% of the disease associations were overlapping and of similar effect sizes. Second, at the genetic level, we conducted GWAS (cases vs. generic; cases vs. exposed) and assessed differences in genetic correlations and degrees of phenotypic misclassification. Genetic results were concordant across control groups based on heritability (generic: 0.16 ± 0.07 vs. 0.10 ± 0.07), associations with the coding OPRM1 variant rs1799971 (pgeneric = 8.83E-03 vs. pexposed = 1.83E-02) and genetic correlations with prior OUD GWAS (rg-generic = 0.83 ± 0.26 vs. rg-exposed = 0.78 ± 0.27). Although GWASs were limited by sample size (Ngeneric = 6269, Nexposed = 6365), compared to an independent OUD GWAS (N = 425 944), the dilution value for the two GWAS was not different from 1, suggesting no major impact of phenotypic misclassification. This study represents the first effort to enhance OUD genetic research through optimization of control definitions using EHR data. Generic controls ascertained within the US health systems, where exposure to prescription opioids is high, offer a practical alternative for genetic studies of OUD.

Humans↗

PubMed2024

Risk relationship between inflammatory bowel disease and urolithiasis: A two-sample Mendelian randomization study.

BACKGROUND: The causal genetic relationship between common parenteral manifestations of inflammatory bowel disease (IBD) and urolithiasis remains unclear because their timing is difficult to determine. This study investigated the causal genetic association between IBD and urolithiasis using Mendelian randomization (MR) based on data from large population-based genome-wide association studies (GWASs). METHODS: A two-sample MR analysis was performed to assess the potential relationship between IBD and urolithiasis. Specific single nucleotide polymorphism data were obtained from GWASs, including IBD (n = 59957) and its main subtypes, Crohn's disease (CD) (n = 40266) and ulcerative colitis (UC) (n = 45975). Summarized data on urolithiasis (n = 218792) were obtained from different GWAS studies. A random-effects model was analyzed using inverse-variance weighting, MR-Egger, and weighted medians. RESULTS: Genetic predisposition to IBD and the risk of urolithiasis were significantly associated [odds ratio (OR), 1.04 (95% confidence interval [CI], 1.00-.08), P = 0.01]. Consistently, the weighted median method yielded similar results [OR, 1.06 (95% CI, 1.00-1.12), P = 0.02]. The MR-Egger method also demonstrated comparable findings [OR, 1.02 (95% CI, 0.96-1.08), P = 0.45]. Both funnel plots and MR-Egger intercepts indicated no directional pleiotropic effects between IBD and urolithiasis. CD was strongly associated with it in its subtype analysis [OR, 1.04 (95% CI, 1.01-1.07), P = 0.01], and UC was also causally associated with urolithiasis, although the association was not significant [OR, 0.99 (95% CI, 0.95-1.03), P = 0.71]. CONCLUSION: A unidirectional positive causal correlation was identified between IBD and urolithiasis, with varying degrees of association observed among the different subtypes of IBD. Recognizing the increased incidence of urolithiasis in patients with IBD is crucial in clinical practice. Early detection and surveillance of IBD, improved patient awareness, adoption of preventive strategies, and promotion of collaborative efforts among healthcare providers regarding treatment methodologies are vital for improving patient outcomes.

Humans↗

PubMed2024

Networks of human milk microbiota are associated with host genomics, childhood asthma, and allergic sensitization.

The human milk microbiota (HMM) is thought to influence the long-term health of offspring. However, its role in asthma and atopy and the impact of host genomics on HMM composition remain unclear. Through the CHILD Cohort Study, we followed 885 pregnant mothers and their offspring from birth to 5 years and determined that HMM was associated with maternal genomics and prevalence of childhood asthma and allergic sensitization (atopy) among human milk-fed infants. Network analysis identified modules of correlated microbes in human milk that were associated with subsequent asthma and atopy in preschool-aged children. Moreover, reduced alpha-diversity and increased Lawsonella abundance in HMM were associated with increased prevalence of childhood atopy. Genome-wide association studies (GWASs) identified maternal genetic loci (e.g., ADAMTS8, NPR1, and COTL1) associated with HMM implicated with asthma and atopy, notably Lawsonella and alpha-diversity. Thus, our study elucidates the role of host genomics on the HMM and its potential impact on childhood asthma and atopy.

Humans↗

PubMed2026

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↗

PubMed2025

Implementing a training resource for large-scale genomic data analysis in the All of Us Researcher Workbench.

A lack of representation in genomic research and limited access to computational training create barriers for many researchers seeking to analyze large-scale genetic datasets. The All of Us Research Program provides an unprecedented opportunity to address these gaps by offering genomic data from a broad range of participants, but its impact depends on equipping researchers with the necessary skills to use it effectively. The All of Us Biomedical Researcher (BR) Scholars Program at Baylor College of Medicine aims to break down these barriers by providing early-career researchers with hands-on training in computational genomics through the All of Us Evenings with Genetics Research Program. The year-long program begins with the faculty summit, an in-person computational boot camp that introduces scholars to foundational skills for using the All of Us dataset via a cloud-based research environment. The genomics tutorials focus on genome-wide association studies (GWASs), utilizing Jupyter Notebooks and the Hail computing framework to provide an accessible and scalable approach to large-scale data analysis. Scholars engage in hands-on exercises covering data preparation, quality control, association testing, and result interpretation. By the end of the summit, participants will have successfully conducted a GWAS, visualized key findings, and gained confidence in computational resource management. This initiative expands access to genomic research by equipping early-career researchers from a variety of backgrounds with the tools and knowledge to analyze All of Us data. By lowering barriers to entry and promoting the study of representative populations, the program fosters innovation in precision medicine and advances equity in genomic research.

Humans↗

PubMed2026

Large-Scale Neuroimaging and Genetic Analyses of the Human Thalamus in Loneliness.

BACKGROUND: Although loneliness is prevalent and significantly impacts society globally, its neural and genetic bases remain poorly understood. The thalamus, which receives sensory information from the environment, may have a more significant role in social interactions than previously recognized. Here, we integrate neuroimaging and genetic approaches to characterize structural differences within the thalamus associated with loneliness. METHODS: We obtained thalamic nuclei volumes on brain scans from 45,834 individuals (age range: 45-82 years) in the UK Biobank and grouped them into 6 anatomical groups. We investigated effects of loneliness and social isolation using self-reported data. Then, we performed a genome-wide association study (GWAS) analysis on the genetic overlap between thalamic volumes and loneliness. RESULTS: The volumes of the whole thalamus and its medial, lateral, and posterior nuclei are significantly reduced in individuals with loneliness compared with those who do not feel lonely. Loneliness with frequent social contact is associated with smaller volumes, whereas social isolation without loneliness shows no such reduction in thalamus volumes. Leveraging data from GWASs on thalamic volumes (n = 30,114) and loneliness (n = 370,342) in the UK Biobank, we identified shared loci between thalamus structure and loneliness. CONCLUSIONS: Our findings support the emerging view that the thalamus plays important roles in social interactions and in the experience of loneliness.

Genetic architecture↗

PubMed2025

Mendelian randomization reveals causal relationships between cytokines and male reproductive diseases.

This study aims to explore the causal links between cytokines and four male reproductive disorders, namely abnormal spermatozoa (AS), male infertility, erectile dysfunction (ED), and hyperplasia of prostate (HP), employing a two-sample Mendelian randomization (MR) approach. Genetic associations with male reproductive diseases were derived from the IEU OpenGWAS project, with cytokine data from two GWASs focused on the human proteome and cytokines. Estimations were derived using inverse variance weighting, MR-Egger regression, weighted median, weighted model, and simple mode. Furthermore, the robustness of the findings was evaluated through Cochran's Q-test, MR-Egger regression, and leave-one-out sensitivity analysis. Fifteen unique cytokines were identified as having causal relationships with the risk of four male reproductive disorders. Specifically, for AS, interleukin-22 (IL-22), IL-12, and macrophage migration inhibitory factor were negatively correlated with AS, while tumor necrosis factor β levels were positively correlated with AS. In the context of male infertility, IL-2 receptor antagonist levels, IL-34, and granulocyte-colony stimulating factor levels were positively linked to male infertility, whereas IL-21 showed a negative relationship. Regarding ED, IL-19, IL-1β, and eotaxin levels were negatively associated with ED risk, while macrophage inflammatory protein 1β (MIP-1β) levels and interferon gamma-induced protein 10 levels were positively associated. As for HP, stromal-cell-derived factor 1α levels and MIP-1α levels revealed negative associations with HP. In conclusion, this MR analysis revealed that several cytokines were causally associated with male reproductive diseases and could be valuable in offering new insights for further mechanistic and clinical investigations of cytokines-associated male reproductive diseases.

Male↗

PubMed2026

Mapping the immune-genetic architecture of Epstein-Barr virus-related phenotypes and multiple sclerosis through a single-cell genetic framework for target prioritization and pharmacologic hypothesis generation.

BACKGROUND: Multiple sclerosis (MS) is a severe neuroinflammatory disease causing substantial long-term disability. Strong epidemiologic evidence links Epstein-Barr virus (EBV) exposure with MS risk, but genetic evidence for immune target prioritization in EBV-related phenotypes remains limited. METHODS: We integrated single-cell cis-eQTL data from 14 immune cell types with GWASs of an EBV-related clinical phenotype and MS using a single-cell Mendelian randomization framework with colocalization analyses. Candidate eGenes were evaluated in independent cohorts. For multi-SNP instruments, we performed heterogeneity, pleiotropy, MR-Egger, weighted median, mode-based, and MR-PRESSO sensitivity analyses. We also conducted phenome-wide association analyses and queried DrugBank to annotate candidate compounds targeting prioritized genes. RESULTS: We prioritized 43 immune-cell-specific candidate eGenes with convergent genetic support, including 6 for the EBV-related phenotype and 37 for MS. SERPINB1 in NK cells was associated with increased risk of the EBV-related phenotype, whereas HLA-G was associated with decreased risk. For MS, APOM and MSH5 showed protective associations, while AHI1 showed cell-type-dependent, bidirectional associations across immune lineages. Colocalization and independent cohort evaluation supported these findings. Among FDR-significant multi-SNP associations, MR-Egger intercept tests did not indicate directional pleiotropy, although a small subset showed heterogeneity or MR-PRESSO signals. Phenome-wide analyses identified no significant adverse phenotypic associations among evaluable genes at the prespecified threshold. DrugBank annotation nominated sodium nitroprusside, fasudil, artenimol, and choline as hypothesis-generating compounds for experimental follow-up. CONCLUSIONS: This study provides a single-cell genetic framework for prioritizing immune-cell-specific candidate targets for EBV-related phenotypes and MS, and nominates genetically supported targets and pharmacologic hypotheses for experimental investigation.

Humans↗

PubMed2026

Trio-based GWAS reveals loci associated with different forms of isolated cleft lip.

Orofacial clefts (OFCs) are the most common craniofacial birth defect and comprise a diverse group of traits with complex and heterogeneous etiologies. Genetic studies of OFCs typically approach this diversity by stratifying cases into broad diagnostic classes, including cleft lip (CL), cleft palate (CP), and cleft lip with palate (CLP). Although this strategy has yielded important insights into OFC risk, it ignores the phenotypic heterogeneity within each subtype. CL exhibits marked phenotypic variability, involving differences in alveolar involvement, laterality, and sidedness that may reflect distinct etiologies. Given this phenotypic diversity within CL, we assembled a multi-ancestry cohort of 837 nonsyndromic CL case-parent trios with whole-genome sequencing and detailed phenotyping. We performed genome-wide association scans (GWAS) via transmission disequilibrium tests for CL overall and for 14 CL subtypes defined by involvement of the alveolus (with and without), laterality (uni- and bilateral), and sidedness (left and right). We identified four genome-wide significant loci. Two loci, IRF6 and 8q24.21, were both detected in the overall CL GWAS. PLCB1/PLCB4 and MAFB were detected in GWASs of alveolar cleft involvement and CL left sidedness, respectively. These subtype-specific associations were followed by case-only comparisons that reflect the presence or absence of alveolus cleft or left-sided bias of CL to confirm the specificity of the association signal to the particular subtype. Our results provide evidence of within-class CL subtype-specific genetic links for loci previously discussed in the context of primary OFC classes and demonstrate the value of granular OFC subtype characterization to capture trait-specific associations.

Alveolus Cleft↗

PubMed2024

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↗

PubMed2025

Genetic and epigenetic analysis of plasma glial fibrillary acidic protein (GFAP) levels in PTSD.

Glial fibrillary acidic protein (GFAP) is an astrocytic marker that can be assessed in blood using single molecule array technology. Recent studies suggest that individuals with posttraumatic stress disorder (PTSD) have suppressed circulating levels of this CNS biomarker. This study examined the hypothesis that PTSD and plasma GFAP levels share common genetic and epigenetic pathways. Using data from 1096 veterans and civilians, we computed a PTSD polygenic risk score (PRS) derived from a prior PTSD genomewide association study (GWAS) and found that PTSD severity and the PRS were each associated with reduced levels of GFAP. To clarify the basis of the PRS association, we performed a GWAS of GFAP which identified 20 genomewide-significant loci including genes implicated in independent GWASs of PTSD and neurodegenerative disease (e.g., PRKN, NFIA). Comparison of the PTSD and GFAP GWAS results showed that PTSD-associated genes were significantly enriched in the GFAP results with notable overlap involving NPSR1 and the protocadherin alpha (PCDHA) gene cluster. Similarly, we performed an epigenomewide association study (EWAS) of GFAP, which identified 4 genomewide-significant associations (including loci in MCT4 and SREBF1) and then compared those results to the findings of a PTSD EWAS. Results again showed significantly greater overlap than would be expected by chance and included loci implicated in prior studies of depression, dementia, and inflammation. This study clarifies the genetic and epigenetic basis of the association between PTSD and plasma GFAP levels and should encourage future research into the role of GFAP in the pathophysiology of PTSD.

Humans↗