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PubMed2025

Genetic prediction of early adolescent chronotype: effects of sex and pubertal status.

STUDY OBJECTIVES: Adolescence is characterized by later sleep onset and wake times, indicating a shift to an evening chronotype. Genome-wide association studies (GWAS) in adults show chronotype is polygenic and causally linked to depression, schizophrenia, and cognitive function. Yet, the impact of genetics on adolescent chronotype remains largely unexplored, and biological factors influencing the predictive relationship between genetics and chronotype have not been well-defined. This study aims to assess the utility of polygenic scores (PGS) derived from adult GWAS in predicting adolescent chronotype, mental health, and cognition while considering sex- and puberty-dependent effects. METHODS: Generalized linear models were used to assess the relationship between PGS for chronotype and self-reported chronotype, mental health, and cognition in 2411 youths of European ancestry aged 10-13 years. Interaction terms assessed whether the genotype-phenotype relationships varied by sex or pubertal development. Statistical significance was determined using a likelihood ratio test. RESULTS: Significant sex- and puberty-dependent effects were observed. Higher PGS for morningness concordantly predicted earlier self-reported chronotype, but in female youth only. Follow-up analyses showed that sex-specific effects were mediated by the interaction between PGS and pubertal status. Greater genetic predisposition for morningness was negatively associated with somnolence and cognition in males and negatively associated with psychotic-like experiences in females. CONCLUSIONS: The influence of genetic predisposition for early versus late chronotype on adolescent sleep-wake behavior emerges as puberty progresses. These findings suggest puberty is a critical transition when genetic variants associated with chronotype in adults become relevant to pediatric cohorts.

Humans↗

PubMed2026

Integrated Genomics and Transcriptomics Reveal Stable Resistance Loci and Candidate Genes for Powdery Mildew in Wheat.

Powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), poses a substantial threat to global wheat production. Enhancing resistance through molecular breeding necessitates a comprehensive understanding of its genetic and molecular underpinnings. This study leveraged a 2-year phenotypic evaluation of 283 diverse wheat accessions combined with genome-wide association studies (GWAS) to pinpoint stable quantitative trait loci for powdery mildew resistance. We identified 52 robust resistance loci across the wheat genome, including seven novel loci consistently detected across four environments. Comparative transcriptome profiling of resistant and susceptible wheat lines revealed 95 differentially expressed genes, predominantly enriched in defense response, signal transduction, and transcription regulation pathways. By integrating the GWAS and transcriptomic data, we precisely identified three compelling candidate genes (TaPIP5K, TaPKG, and TaORR6) on chromosome 2A, which are implicated in cell wall reinforcement, jasmonic acid signaling, and reactive oxygen species scavenging, respectively. Further validation using expression analysis corroborated their pivotal roles in resistance. Our findings provide a rich repository of validated genetic markers, promising candidate genes, and superior resistant germplasms, offering critical resources to accelerate targeted molecular breeding efforts for durable powdery mildew resistance in wheat.

Blumeria graminis f. sp. tritici↗

PubMed2026

HLA and non-HLA genetic analyses reveal suggestive variants associated with statin-induced liver injury.

BACKGROUND: Statins are widely prescribed for cardiovascular risk reduction and are generally well tolerated. However, they can cause drug-induced liver injury (DILI), and the genetic factors contributing to statin-DILI remain poorly understood. METHODS: HLA association and genome-wide association (GWAS) studies were conducted to identify genetic variants associated with statin-DILI. High-confidence cases (n=71) were identified from the Drug-Induced Liver Injury Network (DILIN) and compared with statin-exposed controls without liver injury (n=551) from the Indiana Biobank. Association testing was performed across ancestries and within ancestry, adjusting for age, sex, and three principal components of genotypes. Top variants were further evaluated in non-statin DILI cases and unexposed controls. In addition, we investigated the frequency of candidate variants among a comprehensive list of pharmacogenetic variants related to statins. RESULTS: HLA-DQA1*03:01 was significantly associated with increased risk of statin-DILI (OR=3.49, 95% CI 2.21-5.51, p-value=1.27×10-7), with enrichment observed across multiple ancestry groups, particularly non-Hispanic Black and Hispanic individuals. From the GWAS, three loci showed suggestive associations (p-value <5×10-06) with statin-DILI, including rs35197737 in RGS1 (OR=5.03, 95% CI 1.11-3.66, p=1.14×10-7), rs75629598 in FRMD4A (OR=4.4, 95% CI=2.33-8.12, p=3.97×10-6), and rs7658630 in the intergenic region on chromosome 4 (OR=4.86, 95% CI 2.66-8.85, p=2.68×10-7). No pharmacogenetic variants revealed statistical significance. CONCLUSION: We identified HLA and non-HLA genetic variants associated with statin DILI. Future studies with larger sample sizes should confirm these observations.

Humans↗

PubMed2025

Genome-wide association study of angiotensinogen levels and key single nucleotide polymorphism associations with blood pressure.

OBJECTIVE: The renin angiotensin aldosterone system plays a key role in circulatory homeostasis. We sought to identify genetic determinants of measured plasma angiotensinogen levels and subsequently evaluate the association of these single nucleotide polymorphisms (SNPs) with blood pressure (BP) and hypertension in a multiethnic population. METHODS: Genome-wide association study (GWAS) of plasma angiotensinogen levels, measured using an enzyme-linked immunoassay, was conducted in 4899 Multi-Ethnic Study of Atherosclerosis (MESA) participants (self-identified as White, n = 1865; Hispanic, n  = 1113; Black, n  = 1224; and Chinese, n  = 629). Linear and logistic models examined the association between SNPs with angiotensinogen and hypertension, respectively. Mediation analysis evaluated the effect of angiotensinogen on BP/hypertension through the top SNPs identified by GWAS. RESULTS: In the analysis utilizing all participants, 115 SNPs were associated with angiotensinogen ( P  < 5 × 10 -8 ), including lead SNP rs4762(G>A) in exon 2 ( P  = 1.51E -100 ) and rs5050(T>G) in the promoter region ( P  = 2.26E -69 ) of the AGT gene. Race/ethnic-specific analyses identified rs4762(G>A) as the lead SNP for White and Hispanic participants, whereas Black and Chinese participants had rs5050(T>G) and rs16852311(G>C), respectively. Both rs4762(G>A) and rs5050(T>G) indirectly increased systolic BP, diastolic BP, and the odds of hypertension through its effect of increasing angiotensinogen. CONCLUSIONS: Our findings demonstrate racial/ethnic differences in genetic effects on angiotensinogen levels across multiple SNPs. AGT rs4762(G>A) and rs5050(T>G) impact BP and hypertension through a mediated effect via angiotensinogen, though opposing direct effects may mask the overall association.

Humans↗

PubMed2025

Genetic predisposition to systemic inflammatory proteins is causally associated with inflammatory bowel disease: Insights from multi-omics association study and single-cell RNA-sequencing analysis.

Systemic inflammatory proteins have been reported to be related to inflammatory bowel disease (IBD) in previous observational research. However, their causal links remain obscure. Herein, we performed a Mendelian randomization (MR) analysis to analyze the causality between systemic inflammatory proteins and IBD. Genetic variants related to systemic inflammatory proteins were extracted from a meta-analysis of genome-wide association study (GWAS) data of 8293 European participants. Summary statistics of IBD diverse subtypes were obtained from the international IBD genetic consortium (IIBDGC). We conducted multi-omics method and MR study to detect the causal links through integrating GWAS and protein quantity trait loci (pQTL) data. Inverse variance weighted (IVW) approach was utilized as the dominated analysis method. Moreover, complementary approaches such as MR-Egger intercept test, Cochran Q test and leave-one-out analysis were utilized to validate pleiotropy and heterogeneity. Finally, single-cell RNA-sequencing analysis was performed to detect the expression of significant genes. For IBD, IVW estimates suggested that genetically predicted IL-10 and IL-13 were suggestively associated with an elevated risk of IBD (IL-10: OR: 1.12, 95% CI: 1.00-1.24, P = .04; IL-13: OR: 1.09, 95% CI: 1.01-1.18, P = .023), while CXCL10 was suggestively linked to a lower risk of IBD (CXCL10: OR: 0.90, 95% CI: 0.82-0.99, P = .037). For Crohn disease (CD), the IVW approach provided evidence to sustain that genetically determined IL-13 and CCL3 had a suggestive association with a higher risk of CD (IL-13: OR: 1.13, 95% CI: 1.02-1.26, P = .023; CCL3: OR: 1.22, 95% CI: 1.03-1.45, P = .018). Sensitivity analysis did not explore any heterogeneity and pleiotropy. Our findings supported the causal relationships between 4 specific inflammatory proteins (IL-10, IL-13, CXCL10, and CCL3) and the risk of IBD and CD, thereby providing promising biomarkers of various subtypes stratification and new insights for the prevention and therapeutic target of IBD.

Humans↗

PubMed2023

Single-cell transcriptomic atlas of Alzheimer's disease middle temporal gyrus reveals region, cell type and sex specificity of gene expression with novel genetic risk for MERTK in female.

Alzheimer's disease, the most common age-related neurodegenerative disease, is closely associated with both amyloid-ß plaque and neuroinflammation. Two thirds of Alzheimer's disease patients are females and they have a higher disease risk. Moreover, women with Alzheimer's disease have more extensive brain histological changes than men along with more severe cognitive symptoms and neurodegeneration. To identify how sex difference induces structural brain changes, we performed unbiased massively parallel single nucleus RNA sequencing on Alzheimer's disease and control brains focusing on the middle temporal gyrus, a brain region strongly affected by the disease but not previously studied with these methods. We identified a subpopulation of selectively vulnerable layer 2/3 excitatory neurons that that were RORB-negative and CDH9-expressing. This vulnerability differs from that reported for other brain regions, but there was no detectable difference between male and female patterns in middle temporal gyrus samples. Disease-associated, but sex-independent, reactive astrocyte signatures were also present. In clear contrast, the microglia signatures of diseased brains differed between males and females. Combining single cell transcriptomic data with results from genome-wide association studies (GWAS), we identified MERTK genetic variation as a risk factor for Alzheimer's disease selectively in females. Taken together, our single cell dataset revealed a unique cellular-level view of sex-specific transcriptional changes in Alzheimer's disease, illuminating GWAS identification of sex-specific Alzheimer's risk genes. These data serve as a rich resource for interrogation of the molecular and cellular basis of Alzheimer's disease.

Journal Article↗

PubMed2025

Genome-wide association study of copy number variations in Parkinson's disease.

OBJECTIVE: To investigate the impact of copy number variations (CNVs) on Parkinson's disease (PD) pathogenesis using genome-wide data and explore their role in sporadic PD. METHODS: We analyzed CNV data from 11,035 PD patients (including 2,731 early-onset PD (EOPD)) and 8,901 controls from the COURAGE-PD consortium using a sliding window CNV-GWAS and genome-wide burden analysis. The independent dataset from the Global Parkinson Genetics Program (GP2) consisted of 23,089 cases and 18,824 controls were used to validate our initial findings. RESULTS: The exploratory dataset identifies multiple CNV regions associated with PD risk. The nominated CNV loci were not confirmed in an independent dataset, except that only a deletion in the PRKN gene, a well-established EOPD locus, remained genome-wide significant and robustly supported. CNV burden analysis showed a higher prevalence of CNVs in PD-related genes in patients compared to controls (OR=1.56 [1.18-2.09], p=0.0013), with PRKN showing the highest burden (OR=1.47 [1.10-1.98], p=0.026). Patients with CNVs in PRKN had an earlier disease onset. Burden analysis with controls and EOPD patients showed similar results. INTERPRETATION: The largest CNV-based GWAS on PD highlights both the promise and pitfalls of array-based CNV detection in PD and underscores the relevance of whole-genome sequencing approaches in resolving the role of CNV in PD. The array-based findings are prone towards false positive findings that might arise either from platform limitations and/or cohort biases. Future studies require improved genotyping resolution and rigorous cross-cohort validation to reliably assess CNV contributions to PD risk.

Journal Article↗

PubMed2025

Automated Deep Learning-Based Detection of Early Atherosclerotic Plaques in Carotid Ultrasound Imaging.

BACKGROUND: Carotid plaque presence is associated with cardiovascular risk, even among asymptomatic individuals. While deep learning has shown promise for carotid plaque phenotyping in patients with advanced atherosclerosis, its application in population-based settings of asymptomatic individuals remains unexplored. METHODS: We developed a YOLOv8-based model for plaque detection using carotid ultrasound images from 19,499 participants of the population-based UK Biobank (UKB) and fine-tuned it for external validation in the BiDirect study (N = 2,105). Cox regression was used to estimate the impact of plaque presence and count on major cardiovascular events. To explore the genetic architecture of carotid atherosclerosis, we conducted a genome-wide association study (GWAS) meta-analysis of the UKB and CHARGE cohorts. Mendelian randomization (MR) assessed the effect of genetic predisposition to vascular risk factors on carotid atherosclerosis. RESULTS: Our model demonstrated high performance with accuracy, sensitivity, and specificity exceeding 85%, enabling identification of carotid plaques in 45% of the UKB population (aged 47-83 years). In the external BiDirect cohort, a fine-tuned model achieved 86% accuracy, 78% sensitivity, and 90% specificity. Plaque presence and count were associated with risk of major adverse cardiovascular events (MACE) over a follow-up of up to seven years, improving risk reclassification beyond the Pooled Cohort Equations. A GWAS meta-analysis of carotid plaques uncovered two novel genomic loci, with downstream analyses implicating targets of investigational drugs in advanced clinical development. Observational and MR analyses showed associations between smoking, LDL cholesterol, hypertension, and odds of carotid atherosclerosis. CONCLUSIONS: Our model offers a scalable solution for early carotid plaque detection, potentially enabling automated screening in asymptomatic individuals and improving plaque phenotyping in population-based cohorts. This approach could advance large-scale atherosclerosis research.

atherosclerosis↗

PubMed2025

Comorbidity alters the genetic relationship between anxiety disorders and major depression.

BACKGROUND: Comorbid anxiety disorders (ANX) and major depression (MD) have worse clinical outcomes than either disorder alone. Analysis of genomic data based on comorbidity status may reveal more precise biological pathways and causal relationships with potential clinical implications. We investigated the genetic relationship between ANX and MD with and without mutual comorbidity. METHODS: We leveraged data from UK Biobank to perform disorder-specific genome-wide association studies (GWAS) of ANX-only (n=189,422) and MD-only (n=194,339) and generate polygenic risk scores (PRS). The Norwegian Mother, Father, and Child Cohort (MoBa, n = 130,992) served to test the associations of PRS with diagnoses. MD and ANX GWAS, including comorbidities (MD-comorbid and ANX-comorbid), were used for comparison. Genetic correlations were compared by comorbidity status, and Mendelian randomization was employed to assess causal relationships. RESULTS: The MD-only PRS showed a stronger association with MD-only compared to ANX-only cases (Z=3.74; Padjusted=0.002); however, MD-comorbid PRS did not show a significant difference (Z=2.71; Padjusted=0.08). The genetic correlation between ANX-only and MD-only was 0.53, lower than between ANX-comorbid and MD-comorbid (0.90). ANX-only showed a causal relationship with MD-only (Padjusted=0.015), but not vice versa, and contrasted the bidirectional causal relationship (Padjusted=2.9e-12, and Padjusted=9.3e-06) when comorbidity was included. Gene sets of MD-comorbid, ANX-comorbid, and MD-only, but not of ANX-only, were enriched for immune regulation pathways such as interleukin production. CONCLUSIONS: ANX and MD show more distinct genetics when comorbid cases are excluded, and ANX may be causal for MD. Disorder-specific genetic studies help uncover more relevant biological mechanisms and guide tailored clinical interventions.

Journal Article↗

PubMed2025

Large-scale admixture mapping in the All of Us Research Program improves the characterization of cross-population phenotypic differences.

Admixed individuals have largely been understudied in medical research due to their complex genetic ancestries. However, the consideration of admixture can help identify ancestry-enriched genetic associations, delineating some of the genetic underpinnings of cross-population phenotypic variation. To this end, we performed local ancestry inference within the All of Us Research Program to identify individuals with recent admixture between African (AFR) and European (EUR) populations (N=48,921). We identified evidence of local AFR ancestry enrichment at the HLA locus, suggestive of putative selection since admixture. Furthermore, we performed the largest admixture mapping (ADM) efforts in AFR-EUR Admixed individuals for 22 traits, identifying 71 associations between inferred local AFR ancestries and a trait. Variants from published GWAS could only account for 18 (25%) of the ADM associations, highlighting novel loci where ancestral haplotypes explained some phenotypic variation. Previous studies likely have not identified these loci due to the low availability of high-powered GWAS in populations genetically similar to AFR. One such loci was 9q21.33, associated with 1.4-fold risk of end-stage kidney disease (ESKD) for carriers of inferred local AFR ancestries at the region. This locus contains the gene SLC28A3, which has previously been linked to kidney function but has never been associated with cross-population ESKD prevalence differences. Together, our results expand upon the existing literature on phenotypic differences between populations, highlighting loci where genetic ancestries play a critical role in the genetic architecture of disease.

Journal Article↗

PubMed2025

Longitudinal Multi-Organ Transcriptomic Atlas of Salt-Induced Hypertension.

BACKGROUND: Salt-sensitive hypertension is a prevalent and clinically significant subtype of hypertension, where increased dietary salt intake elevates blood pressure and causes injury to multiple organ systems. Despite extensive research, dynamic molecular changes and conserved versus organ-specific transcriptional programs in hypertensive multi-organ damage remain poorly understood. Defining complex molecular pathways both in a temporal sequence and in an organ-specific manner is essential for developing targeted, precision therapies to mitigate hypertensive disease burden. METHODS: We generated a longitudinal multi-organ transcriptomic atlas of salt-sensitive hypertension using RNA sequencing of kidney cortex, kidney medulla, heart, and liver from Dahl salt-sensitive rats across four disease stages. A comprehensive bioinformatic analysis mapped dynamic transcriptional programs, evaluated 50 biological pathways, and defined upstream regulators. Histological and biochemical assays complemented transcriptomic analysis, while integration with human genome-wide association studies (GWAS) and compound-transcriptome analysis provided translational insights and identified candidate therapeutics. RESULTS: Salt-induced hypertension elicited both shared and tissue-specific transcriptional programs that evolved with disease progression. The kidney medulla showed robust early immune activation with metabolic suppression, while the cortex exhibited transient metabolic activation before declining and initiating immune activation. The liver and heart showed time-dependent metabolic and inflammatory remodeling. Cross-organ comparisons revealed a shared early proliferative response that converged on proinflammatory and fibrotic signatures. Upstream regulator analysis identified 79 time- and tissue-specific transcription factors associated with gene expression dynamics. GWAS integration analysis revealed endocrine signaling, ion transport, lipid metabolism, and detoxification as conserved pathways across species, underscoring the translational relevance of the model and study. Predictive compound-transcriptome analyses identified kinase inhibitors targeting phosphoinositide 3-kinase, mechanistic target of rapamycin and cyclin-dependent kinases as top candidates to counteract maladaptive transcriptional programs. CONCLUSIONS: This study defines temporal and tissue-specific transcriptomic remodeling in salt-sensitive hypertension and highlights the need for precision interventions to prevent progressive organ damage.

Journal Article↗

PubMed2025

Enhancer-targeting CRISPR screens at coronary artery disease loci suggest shared mechanisms of disease risk.

To systematically identify causal genetic mechanisms that confer risk for coronary artery disease (CAD) in GWAS loci, we mapped genome-wide variant-to-enhancer-to-gene (V2E2G) links in vascular smooth muscle cells (SMC). Enhancers identified by active chromatin features, and further prioritized by base-resolution deep learning models of chromatin accessibility in 108 CAD loci, were studied with CRISPRi targeting and Direct-Capture Targeted Perturb-seq (DC-TAP-seq) evaluation of 470 genes. Seventy-six V2E2G links were identified for 59 candidate CAD genes representing gene programs including epithelial-mesenchymal transformation, ubiquitination, and protein folding as well as BMP and TGFB signaling. Similar methods employed with an independent focused screen targeting one candidate locus at 9p21.3 identified 10 enhancers regulating expression of multiple genes at this location. Detailed molecular studies revealed that two enhancers mediating transcription factor binding and transcriptional regulation contribute to ancestry-specific and sex-specific risk for CAD and the surrogate biomarker vascular calcification. Together, these studies advance our identification of GWAS CAD V2E2G links across the genome, and specific mechanisms of risk at the complex 9p21.3 locus.

Journal Article↗

PubMed2025

Tractor Workflow Pipeline: A Scalable Nextflow Framework for Local Ancestry-Aware Genome-Wide Association Studies.

The routine exclusion of admixed individuals from traditional Genome-Wide Association Studies (GWAS) due to concerns about spurious associations has hindered genetic analyses involving multiple ancestries. Tractor GWAS addresses this issue by incorporating local ancestry into its analysis, empowering identification of ancestry-enriched hits and generating ancestry-specific summary statistics. However, Tractor requires accurate genomic phasing and local ancestry inference as prerequisite steps, which requires additional bioinformatics expertise and decision points regarding reference panel setup. To streamline, harmonize, and automate this process, we present a scalable Nextflow workflow that integrates all necessary steps, minimizing the need for manual intervention while remaining modular and customizable. The workflow supports multiple commonly used tools and offers flexibility in how Tractor is implemented. To demonstrate its utility, we applied this pipeline to analyze 32 blood biomarkers in 6,245 two-way AFR-EUR admixed individuals from the UK Biobank. This pipeline ran efficiently at scale, replicated known associations, and identified novel ancestry-specific loci. These novel associations were largely driven by variants present on African ancestral tracts but absent from European tracts, underscoring the value of local ancestry-aware methods in uncovering previously missed genetic signals. By enabling the efficient analysis of admixed individuals, our workflow facilitates Tractor use, paving the way for more broader genetic discovery.

Journal Article↗

PubMed2025

A simple approach for multiple observations improves power to detect genetic effects and genomic prediction accuracy.

Many datasets, including widely used biobanks, have more than one observation of numerous phenotypes for at least a portion of their sample. The majority of GWAS utilize only a single observation per individual, even when more than one observation may be available, and apply a standard model in which the additive allelic effect being estimated is assumed to be constant across the age or time range in the sample. Here, we test a set of simple approaches to utilize multiple observations per individual, under this same assumption. We find that utilizing the mean or median of the available observations rather than a single observation improves power to detect associated loci and enriched gene sets and yields higher out-of-sample polygenic score prediction accuracy. Despite growing biobanks, many deeply phenotyped samples are relatively small but have multiple observations. While explicitly modeling age- or time-dependent genetic effects can estimate time- or age-specific genetic effects, most GWAS apply a standard, additive-only model; a simple approach of using the mean or median can improve power by reducing "noise" in the phenotype, utilize standard, optimized software, and be particularly impactful for smaller samples, including samples of diverse genetic ancestry currently existing in widely used biobanks.

Journal Article↗

PubMed2025

CSF proteogenomics implicates novel proteins and humoral immunity in Alzheimer's disease risk.

We profiled 2,961 cerebrospinal fluid (CSF) proteins in 1,005 participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI), including 1,066 proteins not measured in prior studies, using mass spectrometry (MS). We mapped protein quantitative trait loci (pQTLs) in CSF, compared them with brain and plasma pQTLs, and integrated them with Alzheimer's disease (AD) genome-wide association study (GWAS) data. We identified 1,417 index cis pQTLs for 654 unique genes and 130 index trans pQTLs for 94 unique genes. Cross-tissue and cross-proteomic-platform comparisons show broad consistency between MS-based CSF pQTLs and MS-based brain pQTLs as well as affinity-based CSF and plasma pQTLs. Lastly, through integrating CSF pQTLs with the largest AD GWAS, we identified 24 candidate AD causal proteins in CSF, including 10 novel and 14 previously identified in either brain, CSF, or plasma using similar approaches. These CSF AD candidate causal proteins are involved in immune response - notably humoral immunity (3 of 24) - that expands the role of the immune system in AD beyond innate immunity, as well as lysosomal function and neurovascular growth and remodeling. Together, our findings provide novel insights into AD biology and new targets for biomarker and therapeutic development.

Journal Article↗

PubMed2026

Cross-species variant-to-function analyses implicate MEIS1 in conferring sleep abnormalities and impaired cerebellar development.

Genome-wide association studies (GWAS) have identified numerous loci for insomnia, yet functional validation of effector genes remains limited because most risk variants lie in noncoding regions, and the true causal gene is not known. Here, we use prior human cell-based variant-to-gene mapping to nominate six insomnia effector genes and test them in zebrafish, a tractable diurnal vertebrate model well suited for sleep phenotyping. Our CRISPR-based behavioral screening identifies the MEIS1 ortholog, meis1b, as a regulator of sleep maintenance, with crispants displaying impaired nighttime-specific sleep maintenance and increased sleep latency. Comparative chromatin analyses reveal conserved regulatory architecture spanning the human insomnia-associated locus and selectively implicate meis1b, whereas the duplicated ohnolog meis1a was dispensable. Developmental profiling further shows that meis1b is expressed in cerebellar granule progenitors, paralleling human MEIS1 expression, and that its disruption impairs cerebellar development. Together, these findings establish zebrafish as an efficient vertebrate platform for functional interrogation of GWAS candidates and support an evolutionarily conserved cerebellar role for MEIS1 in sleep maintenance.

Animals↗

PubMed2026

Integrative Analysis Uncover the Effects and Multi-Omics Features of Thigh Muscle Fat Infiltration.

The health impacts and underlying biological pathways of thigh muscle fat infiltration (TMFI) remain incompletely understood. In this study, we analyzed TMFI measured by magnetic resonance imaging in 55,120 UK Biobank participants and found that higher TMFI was significantly associated with all-cause mortality as well as with all major system-specific diseases examined (p values ranged from 2.50 × 10-88 to 9.97 × 10-04). TMFI also mediated the effects of lifestyle factors on health-related outcomes, with mediation proportions ranging from 6.7% to 71.7%. A genome-wide association study (GWAS) identified 79 lead single nucleotide polymorphisms (SNPs) linked to TMFI, and the polygenic risk score for TMFI was significantly associated with mortality and all incident diseases across examined organ systems in an independent subset of UK Biobank participants of European ancestry who were not included in the TMFI GWAS (n = 362,286, all p < 0.05). Gene-drug interactions identified multiple drugs that could potentially modulate TMFI. Analysis of single-cell transcriptomic data indicated that myogenic cells were strongly linked to TMFI (p = 7.08 × 10-08). Summary-data-based Mendelian randomization and Transcriptome-Wide Association Study analyses revealed numerous genes whose expression in specific tissues was associated with TMFI. Proteomic and metabolomic profiling uncovered a broad array of circulating biomarkers associated with TMFI, many of which mediated the effects of modifiable factors and genetic risk on TMFI. Overall, our results highlight the biological relevance of TMFI to human health and provide insights into the multi-omics mechanisms underlying TMFI, identifying potential targets for interventions.

Humans↗

PubMed2026

Integrative Multi-Omics Analysis Identifies Thrombosis-Associated Molecular Features Linked to Germline Susceptibility and Immune Cell Communication in Gastric Cancer.

Emerging evidence indicates that coagulation-related molecular programs are associated with thrombosis, tumor progression, and molecular dysregulation in gastric cancer (GC). However, thrombosis-associated molecular features in GC and their potential links to inherited susceptibility remain insufficiently understood. Integrated analyses of transcriptomic data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were performed to identify thrombosis-associated genes and establish a machine learning-based prognostic signature. Genome-wide association study (GWAS), expression quantitative trait loci (eQTL), transcriptome-wide association study (TWAS), and Mendelian randomization (MR) analyses were conducted to investigate susceptibility-associated transcriptional programs in GC. Functional assays were used to evaluate candidate genes associated with malignant phenotypes. Single-cell RNA sequencing (scRNA-seq) and cell-cell communication analyses were further performed to characterize cell-type-specific expression patterns and potential intercellular interactions. A total of 22 differentially expressed thrombosis-associated genes were identified, and a prognostic signature comprising 14 genes was established. The signature stratified patients into high- and low-risk groups and showed prognostic performance in both the training and validation cohorts. Integrative GWAS, eQTL, and TWAS analyses identified susceptibility-associated transcriptional programs that were positively correlated with the thrombosis-associated risk score. Silencing ACTN2 and CRYAB significantly reduced GC cell migration and invasion. scRNA-seq analysis revealed relatively high CRYAB expression in neutrophils, and CellChat analysis suggested potential neutrophil-B cell interactions involving COLLAGEN-related signaling. This integrative multi-omics study identified a thrombosis-associated molecular signature linked to prognosis and germline susceptibility-associated transcriptional programs in GC. ACTN2 and CRYAB may represent candidate genes associated with GC cell migration and invasion, while single-cell analysis suggested potential immune-related communication features.

Humans↗