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Results for “Biologic pathways”

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PubMed2026

Gut microbial diversity at baseline conditions the clinical, microbiome, and metabolic response to paraprobiotic Lactiplantibacillus plantarum LRCC5282 in overweight adults.

The gut microbiota is increasingly recognized as a target for obesity management; however, whether baseline gut microbial diversity conditions responsiveness to microbiota-targeted interventions remains unclear. We aimed to investigate whether baseline gut microbial diversity is associated with responsiveness to a paraprobiotic derived from Lactiplantibacillus plantarum LRCC5282 (LP5282-P) in overweight adults. In a 12-week, randomized, double-blind, placebo-controlled, multicenter trial of 120 overweight adults, LP5282-P produced no significant between-group differences in any clinical outcome across the overall per-protocol population. However, in the low-diversity subgroup, LP5282-P was associated with significant reductions in body weight, body mass index, and circulating leptin levels. These clinical changes were accompanied by compositional shifts in the gut microbiota, including higher relative abundances of Christensenellaceae, Faecalibacterium, and Alistipes. Fecal metabolite profiles showed elevated acetate and butyrate concentrations and altered bile acid composition. Within the low-diversity subgroup, changes in the relative abundances of Akkermansia and Eubacterium were inversely correlated with changes in body weight, body fat mass, and leptin levels. In contrast, the high-diversity subgroup exhibited no consistent response across the outcome domains examined. Overall, baseline gut microbial diversity was associated with differential responsiveness to LP5282-P, supporting its potential use as a stratification variable in future microbiota-targeted intervention trials. Further studies integrating direct measures of microbial activity and host response are warranted to elucidate the biological pathways underlying this diversity-dependent responsiveness. Trial registration: Clinical Research Information Service (CRIS), KCT0008119.

Humans↗

PubMed1990

Positron emission tomography.

While positron emission tomography (PET) represents the most advanced methodology using radiotracers, it is subject to two main constraints. The first is the physical accuracy with which the regional distribution, time course and concentration of the tracer can be determined. This is principally a function of the instrumentation. The second constraint is the biological accuracy, that a chosen tracer molecule defines the specific biological pathway under study. This paper discusses the application of PET, mainly to the brain, and future possible improvements to this powerful technique.

Brain↗

PubMed2026

Large-scale pleiotropic analysis across cancers reveals shared genetic mechanisms and identifies novel functional genes.

Pleiotropic genetic loci have been increasingly reported in cancer, and identifying genetic variants with pleiotropic associations can reveal shared biological pathways influencing multiple cancers. Using summary statistics from genome-wide association studies for 37 cancer types (N = 433 836), we identified extensive genome-wide and local genetic correlations among cancers. Through pairwise pleiotropic analysis, we identified 75 243 significant pleiotropic single nucleotide polymorphisms (SNPs) across 372 cancer pairs, among which 3472 were lead SNPs with potential regulatory functions. Using FUMA and MAGMA, we identified 2527 pleiotropic risk loci and 4272 candidate pleiotropic genes. Notably, genes such as TERT (5p15.33), POU5F1B (8q24.21), and FANCA (16q24.3) exhibited widespread pleiotropy across multiple cancer types. Pathway enrichment analysis highlighted the critical roles of pigment synthesis, metabolism, and apoptosis in skin-related cancers, while cross-cancer enrichment analysis emphasized pathways related to apoptosis, chromatin structure, and intermediate filaments. We also identified 33 novel functional genes harboring previously unreported cancer risk variants. Drug-gene interaction analysis revealed several repositionable FDA-approved drugs. Importantly, drug sensitivity assays demonstrated that bosutinib and cobimetinib exhibited promising therapeutic potential in breast cancer cell lines. Finally, we developed the PleioCancer database (https://gonglab.hzau.edu.cn/PleioCancer/), providing a comprehensive resource for cancer pleiotropy research. These findings have important implications for carcinogenesis cancer, prevention and treatment.

Humans↗

PubMed2026

shinyDeepGxP: a user-friendly R shiny app for predicting surface protein abundance from scRNA-seq expression using deep learning in blood cells.

MOTIVATION: Understanding accurate immune cell heterogeneity and function in single-cell datasets requires access to protein-level information, which is often unavailable due to experimental limitations. RESULTS: We present shinyDeepGxP, an interactive web application featuring our deep learning model, DeepGxP, for predicting surface protein abundance from single-cell RNA-sequencing (scRNA-seq) data. This platform makes DeepGxP accessible to researchers without programming skills. Users can upload scRNA-seq count matrices and use "Predict Protein" to predict the abundance of 224 biologically relevant surface proteins. shinyDeepGxP provides visualizations to help identify distinct cell populations based on predicted protein profiles. Moreover, users can choose "Explore Model" to reveal key RNA predictors and their associated biological pathways for each protein. Overall, shinyDeepGxP is a user-friendly, freely available web tool that provides protein-level detail for RNA-only single-cell datasets, enabling multimodal discovery without additional experiments. AVAILABILITY AND IMPLEMENTATION: shinyDeepGxP can be launched on https://shiny.crc.pitt.edu/deepgxp/.

Journal Article↗

PubMed2025

Meta-analysis models with group structure for pleiotropy detection at gene and variant level using summary statistics from multiple datasets.

Genome-wide association studies (GWASs) have highlighted the importance of pleiotropy in human diseases, where one gene can impact 2 or more unrelated traits. Examining shared genetic risk factors across multiple diseases can enhance our understanding of these conditions by pinpointing new genes and biological pathways involved. Furthermore, with an increasing wealth of GWAS summary statistics available to the scientific community, leveraging these findings across multiple phenotypes could unveil novel pleiotropic associations. Existing selection methods examine pleiotropic associations one by one at a scale of either the genetic variant or the gene, and thus cannot consider all the genetic information at the same time. To address this limitation, we propose a new approach called MPSG (Meta-analysis model adapted for Pleiotropy Selection with Group structure). This method performs a penalized multivariate meta-analysis method adapted for pleiotropy and takes into account the group structure information nested in the data to select relevant variants and genes (or pathways) from all the genetic information. To do so, we implemented an alternating direction method of multipliers algorithm. We compared the performance of the method with other benchmark meta-analysis approaches such as GCPBayes, PLACO, and ASSET by considering as inputs different kinds of summary statistics. We provide an application of our method to the identification of potential pleiotropic genes between breast and thyroid cancers.

Humans↗

PubMed2026

Using deep learning models as a genetic architecture for the simulation of breeding schemes.

In several simulation studies, long-term selection led to the rapid depletion of genetic variance. These outcomes differ from real-life observations that we aim to replicate, thereby highlighting a fundamental limitation of current classical quantitative genetic simulation models. Deep learning (DL) models have demonstrated promising results in capturing complex interactions essential for maintaining genetic variance; thus, we hypothesize that DL-based genetic simulation models may preserve more genetic variance than classical models, because the biological pathways underlying complex traits exhibit interactions that classical models ignore. The primary objective of this study was to introduce alternative DL-based genetic simulation models and compare them with classical genetic simulation models in terms of their retention of additive genetic variance under truncation selection in a simulated full-sib pig breeding scheme using real haplotypes as founders. After 20 generations of directional truncation selection, the classical models (A, ADAA, and ADAAADDD) retained between 55% and 64% of their initial additive genetic variance. In contrast, while the DL_simple model lost all its additive variance, the DL medium retained 92% to 98% of its additive variance, and the DL_complex model's initial additive variance increased by 296% to 314%. This paper introduces DL-based genetic simulation models and concludes that their ability to retain additive genetic variance depends on the models' architectural complexity. When sufficiently complex, DL-based models exhibit greater retention of additive genetic variance because they intrinsically capture epistatic interactions that are converted into additive variance, as selection progresses, thus, affirming the role of non-additive genetic effects in maintaining long-term genetic variation.

Deep Learning↗

PubMed2025

A genome-wide association study identified 10 novel genomic loci associated with intrinsic capacity.

BACKGROUND: Intrinsic capacity (IC) is a multidimensional concept within the World Health Organization framework for healthy aging. It refers to the composite of an individual's physical and mental capacities that enable them to maintain well-being, functional ability, and engagement in valued activities throughout life. While substantial evidence supports the biological basis of IC and its subdomains, the extent to which genetic factors influence IC remains largely unexplored, with no studies currently available. METHODS: Using datasets from the UK Biobank (UKB; N = 44 631) and the Canadian Longitudinal Study on Aging (CLSA; N = 13 085), we implemented the restricted maximum likelihood method to estimate SNP-based heritability (h2snp), followed by a Genome-Wide Association Study (GWAS) to identify genetic variants associated with IC, and post-GWAS analyses to pinpoint biological implications. RESULTS: The h2snp for IC was estimated at 25.2% in UKB and 19.5% in CLSA. Our GWAS identified 38 independent SNPs for IC across 10 genomic loci and 4289 candidate SNPs, mapped to 197 genes. Post-GWAS analysis revealed the role of these genes in cellular processes such as cell proliferation, immune function, metabolism, and neurodegeneration, with high expression in muscle, heart, brain, adipose, and nerve tissues. Of the 52 traits tested, 23 showed significant genetic correlations with IC, and a higher genetic loading for IC was associated with higher IC scores. CONCLUSIONS: Overall, this study provides comprehensive evidence on the genetic architecture of IC, identifying novel genetic variants and biological pathways, advancing our current knowledge and laying the foundation for ongoing and future research on healthy aging.

Adult↗

PubMed2026

The causal relationship between multiple cardiovascular diseases and glioblastoma: A Mendelian randomization study.

Observational studies suggest an association between glioblastoma (GBM) and cardiovascular diseases (CVDs), but a causal relationship remains unestablished. This study aimed to investigate the causal link between multiple CVDs and GBM risk. The inverse variance weighted method indicated that all 18 CVDs had significant causal associations with GBM (P < .05). Genetically predicted CVDs were uniformly associated with a lower risk of GBM (odds ratio < 1), identifying them as potential protective factors. Sensitivity analyses confirmed the absence of significant heterogeneity or horizontal pleiotropy, and the MR-Steiger test validated the correct causal direction. This Mendelian randomization (MR) study provides evidence that a range of CVDs are causally associated with a decreased risk of developing GBM. These findings suggest shared biological pathways and offer new insights for understanding GBM etiology. We conducted a 2-sample MR analysis using publicly available genome-wide association study data. GBM was the outcome, and 18 cardiovascular-related traits (including coronary artery disease, myocardial infarction, and venous thromboembolism) were exposures. Instrumental variables were single-nucleotide polymorphisms significantly associated with exposures (P < 5 × 10-8). The primary analysis used the inverse variance weighted method, supplemented with MR-Egger, weighted median, and weighted mode methods. Sensitivity analyses, including Cochran Q test, MR-Egger intercept test, leave-one-out analysis, and MR-Steiger directionality test, were performed to ensure robustness.

Causality↗

PubMed2026

HIV immunological nonresponders show low SKAP1 concentration and DNA hypermethylation in the SKAP1 promotor region.

OBJECTIVE: The aim of this study was to improve understanding of biological pathways underlying inadequate CD4 + T-cell restoration after initiating antiretroviral treatment as these so called Immunological nonresponders are at increased risk for morbidity and mortality while treatment options are lacking. DESIGN: We compared baseline multiomics data from 88 Immunological nonresponders and 1467 immunological responders that participated in the 2000HIV study, separated into a discovery and validation cohort. METHODS: We measured expression levels of 2367 plasma proteins, comparing the immunological responders and nonresponders. As this highlighted low Src kinase-associated phosphoprotein 1 (SKAP1) levels in Immunological nonresponders, we measured intracellular SKAP1 levels in CD4 + T-cells, investigated DNA methylation and assessed single-nucleotide polymorphisms (SNPs). We also explored whether HIV or CMV infection may influence SKAP1 expression. RESULTS: SKAP1 plasma levels were significantly lower in Immunological nonresponders in both cohorts. SKAP1 plasma concentrations reflected intracellular levels in CD4 + T-cells. DNA methylation analysis showed significant hypermethylation at the SKAP1 promotor region. Three SNPs close to the SKAP1 gene were associated with poor Immunological response. Preliminary data suggest that HIV or CMV may influence SKAP1 levels. CONCLUSION: Our data show decreased SKAP1 concentrations in immunological nonresponders, potentially driven by hypermethylation of the SKAP1 promoter. Downregulation of SKAP1, which is known to play a role in T cell proliferation and migration, may therefore contribute to the poor restoration of CD4 + cell count after ART.

Humans↗

PubMed2026

Two Genomes, one Outcome: Stratifying Donor and Recipient Polygenic Risk Score to Improve Kidney Allograft Longevity.

Kidney transplantation outcomes arise from complex interactions among donor organ quality, recipient susceptibility, and immunologic compatibility, yet conventional clinical risk models explain only a modest fraction of outcome variability. Polygenic risk scores (PRS) offer a promising framework to enhance transplant risk assessment by integrating genome-wide genetic information from both donor and recipient into biologically informed models. This narrative review examines the mechanistic basis for PRS application in kidney transplantation and variant clustering approaches that link polygenic signals to specific biological pathways underlying alloimmunity, fibrosis, and metabolic dysfunction. We compare current PRS construction methodologies, highlighting their respective strengths and limitations in transplant cohorts. Transplant PRS are distinguished from single-genome disease models by their capacity to capture dual-genome interactions, simultaneously quantifying inherited donor organ liability and recipient genetic susceptibility within an integrated framework. This dual-genome architecture requires novel risk stratification paradigms in which combined donor-recipient polygenic profiles inform pretransplant decision-making in ways that neither genome alone can achieve. However, current PRS contribute only incremental variance beyond established clinical predictors, and critical limitations persist, including European ancestry bias, small cohort sizes, incomplete replication, and undefined clinical actionability thresholds. We critically evaluate these implementation barriers and outline future directions for integrating dual-genome PRS with clinical, molecular, and environmental data. The longer-term goal is to advance precision kidney transplantation through applications such as donor selection, immunosuppression tailoring, and individualized posttransplant surveillance. Realizing this potential will require validation in adequately powered, ancestry diverse, prospective transplant cohorts.

Journal Article↗

PubMed2023

Beyond antibiotic resistance: the whiB7 transcription factor coordinates an adaptive response to alanine starvation in mycobacteria.

Pathogenic mycobacteria are a significant cause of morbidity and mortality worldwide. These bacteria are highly intrinsically drug resistant, making infections challenging to treat. The conserved whiB7 stress response is a key contributor to mycobacterial intrinsic drug resistance. Although we have a comprehensive structural and biochemical understanding of WhiB7, the complex set of signals that activate whiB7 expression remain less clear. It is believed that whiB7 expression is triggered by translational stalling in an upstream open reading frame (uORF) within the whiB7 5' leader, leading to antitermination and transcription into the downstream whiB7 ORF. To define the signals that activate whiB7, we employed a genome-wide CRISPRi epistasis screen and identified a diverse set of 150 mycobacterial genes whose inhibition results in constitutive whiB7 activation. Many of these genes encode amino acid biosynthetic enzymes, tRNAs, and tRNA synthetases, consistent with the proposed mechanism for whiB7 activation by translational stalling in the uORF. We show that the ability of the whiB7 5' regulatory region to sense amino acid starvation is determined by the coding sequence of the uORF. The uORF shows considerable sequence variation among different mycobacterial species, but it is universally and specifically enriched for alanine. Providing a potential rationalization for this enrichment, we find that while deprivation of many amino acids can activate whiB7 expression, whiB7 specifically coordinates an adaptive response to alanine starvation by engaging in a feedback loop with the alanine biosynthetic enzyme, aspC. Our results provide a holistic understanding of the biological pathways that influence whiB7 activation and reveal an extended role for the whiB7 pathway in mycobacterial physiology, beyond its canonical function in antibiotic resistance. These results have important implications for the design of combination drug treatments to avoid whiB7 activation, as well as help explain the conservation of this stress response across a wide range of pathogenic and environmental mycobacteria.

Preprint↗

PubMed2025

Genome-wide association study of adolescent-onset depression.

Adolescent depression is a heritable psychiatric condition with rising global prevalence and severe long-term outcomes, yet its biological underpinnings remain poorly understood. We conducted the first genome-wide association study of adolescent-onset depression, comprising 102,428 cases (diagnosis or clinical symptom thresholds) and 286,911 controls, including diverse ancestries. Cross-ancestry meta-analysis identified 52 independent variants across 17 loci; European-only analysis found 61 variants at 29 loci, with a SNP-based heritability of 9.8%. Comparative analyses revealed two genes unique to adolescent-onset versus lifetime depression, enriched in neuronal subtypes, and two genes as potential drug repurposing targets. Polygenic scores were associated with adolescent-onset depression across ancestries, persistent depression trajectories, more severe outcomes, as well as reduced cortical volume, surface area and white matter integrity. Genetic correlation and Mendelian randomisation analyses support shared genetic liability and causal links with early puberty and modifiable health and behavioural risk factors. These findings uncover novel genetic loci and refine biological pathways underlying adolescent-onset depression, revealing age-specific mechanisms and early intervention opportunities.

Journal Article↗

PubMed2026

A pangenome framework uncovers the role of deletions in repeated evolution of cave-derived traits.

Structural variants (SVs) are increasingly recognized as key contributors to adaptive evolution, yet they remain underexplored compared with single-nucleotide variation. To understand how large-scale genomic changes shape repeated evolution, we leveraged multiple levels of sequence data across the powerful evolutionary model system of the Mexican tetra fish (Astyanax mexicanus). We constructed one of the first pangenome graphs from a naturally evolving vertebrate, enabling comprehensive discovery of SVs among 120 fish from 11 populations. We discover substantial amounts of structural variation and explore the roles of genomic biases and selection in shaping the distribution of these variants. More than 2400 high-confidence cave-specific deletions are enriched in biological pathways involved in vision, metabolism, and behavior and cluster nonrandomly in quantitative trait loci linked to cavefish traits. Additionally, 67 genes harbor unique deletions between independent cavefish lineages. These reused genes show evidence of population-specific selection (99% contain selective sweeps compared with 8%-15% in genes lacking SVs), indicating that deletions likely rose in frequency through repeated positive selection rather than drift. Together, these results reveal that recurrent deletion events have repeatedly contributed to the evolution of cave-adapted phenotypes and highlight deletions as underexplored contributors of adaptive evolution in extreme environments.

Animals↗

PubMed2026

A Comprehensive Analysis of Differential Protein Expression in the Plasma of Rheumatoid Arthritis Patients Utilizing Data-Independent Acquisition (DIA) Proteomics Technology.

BACKGROUND: Rheumatoid Arthritis (RA) is a Prevalent Autoimmune Disorder Affecting Millions of People Worldwide. A Thorough Understanding of Its Clinical and Pathological Features Is Essential to Improve Patient Outcomes. METHODS: This Study Combined Data-Independent Acquisition Proteomics and Enzyme-Linked Immunosorbent Assay (ELISA) to Identify and Validate Potential Plasma Protein Biomarkers for the Early Diagnosis of RA. RESULTS: Differential Proteomic Analysis Identified Differentially Expressed Proteins Between Patients With RA and Healthy Controls and Characterized Their Functions. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes Enrichment Analyses Were Performed to Explore Protein Functions and Associated Biological Pathways. The STRING Database and the Metascape Platform Were Used to Conduct an in-Depth Analysis of the Protein-Protein Interaction Network, Highlighting the Functional Attributes and Interconnections of Upregulated Proteins and Identifying Key Protein Complexes Involved in RA. ELISA Analysis of Plasma Samples Revealed Significantly Elevated SERPINA3 Levels in Patients With RA, Which Were Positively Correlated With Disease Activity Indicators-Including Erythrocyte Sedimentation Rate, C-Reactive Protein, and Disease Activity Score 28-But Were Not Correlated With Rheumatoid Factor or Its Subtypes. CONCLUSIONS: This Study Provides New Insights and Identifies Potential Biomarkers for the Early Diagnosis of RA.

Humans↗

PubMed1992

Normal and heat-induced patterns of expression of heme oxygenase-1 (HSP32) in rat brain: hyperthermia causes rapid induction of mRNA and protein.

Most cells possess a variety of mechanisms, such as high levels of glutathione, that guard against cytotoxic free radicals, which are suspected in the etiology of various neurological deficits. Neurons, however, are deficient in this antioxidant source. The list of other potent antioxidants includes the bile pigments biliverdin and bilirubin. Heme oxygenase (HO) isozymes, HO-1 (HSP32) and HO-2, catalyze the rate-limiting step in the only biological pathway by which bile pigments are produced. In this study, heat shock is identified as the only stimulus reported to date that can alter expression in brain HO-1 of protein and mRNA in vivo. Using a HO-1 cDNA probe, we examined the level of HO-1 mRNA in normal rat brain and in brain 1 and 6 h following heat shock. Exposure of male rats to 42 degrees C for 20 min caused a 20-fold increase in brain HO-1 1.8-kb mRNA within 1 h after treatment. Quantification of brain HO-1 protein by HO-1 radioimmunoassay revealed a fourfold increase at 6 h posttreatment. In normal brain, HO-1 protein was sparsely expressed in few select neuronal and nonneuronal cell populations in forebrain, diencephalon, cerebellum, and brainstem regions. Six hours following heat shock, an intense increase in HO-1 protein in glia throughout the brain, ependyma lining the ventricles of the brain, paraventricular nucleus, Purkinje cell layer of the cerebellum, and cochlear nucleus of brainstem was observed. We suggest that increases in HO-1 transcript and protein reflect a means to elevate levels of antioxidants in cells with compromised defense mechanisms caused by stress.

Animals↗

PubMed2026

Exogenous lactate ameliorates Aβ-induced energy deficit and neurotoxicity with increased mitochondrial TCA cycle carbon flux in SH-SY5Y cells.

A growing body of evidence has demonstrated the existence of metabolic dysfunction in neurodegenerative diseases, including Alzheimer's disease (AD), suggesting that deprivation of energy substrates impairs cellular dynamics. As glucose utilization declines in patients with AD, the need for alternative energy sources becomes crucial to sustain neuronal activities and prevent cell death induced by neurotoxic proteins, such as amyloid beta (Aβ) aggregates. In this context, lactate has been investigated as a potential alternative brain energy substrate in several studies, yet its impact on neuronal cells under Aβ-induced toxicity remains unclear. We confirmed significant suppression of energy production-related biological pathways by analyzing brain transcriptomic data of patients with AD. In subsequent in vitro studies, exogenous lactate treatment ameliorated neuron-like cell death caused by Aβ aggregates. Using a 13C stable isotope tracer, we verified cellular lactate uptake and its incorporation into tricarboxylic acid (TCA) cycle in neurons under the neurotoxic condition. 13C metabolic flux analysis further supported these findings by revealing that lactate treatment restored Aβ-suppressed mitochondrial TCA cycle fluxes. These metabolic improvements were accompanied by increased expression of mitochondrial proteins. These findings support lactate shuttling as a mechanism for supplying lactate-derived carbon to mitochondrial energy metabolism, which may improve neuronal resilience under Aβ-induced metabolic stress.NEW & NOTEWORTHY This study shows that lactate treatment attenuates Aβ-induced cell death in neuron-like cells and supports mitochondrial carbon metabolism. Glycolytic hypometabolism was observed in human AD brain transcriptome and Aβ-treated neuron-like cells. We confirmed that lactate replenished mitochondrial energetics, making neurons more resilient to neurotoxicity. Using 13C tracing and metabolic flux analysis, we found that lactate-derived carbon was incorporated into the TCA cycle and that lactate treatment was associated with restoration of Aβ-suppressed mitochondrial fluxes.

Humans↗

PubMed2025

Influence of Ancestral and Geographic Factors on Intracerebral Hemorrhage Risks Among Africans and Americans.

BACKGROUND: We investigated whether risk factors for intracerebral hemorrhage (ICH) among indigenous Africans (IA) would vary in prevalence and effect compared with self-reported African, Hispanic, and White Americans by comparing data from 2 independent population-based case-control studies conducted in West Africa and the United States. METHODS: We compared ICH risk factors common to the SIREN (Stroke Investigative Research and Educational Network: 1100 case-control pairs) and the ERICH (Ethnic/Racial Variation of Intracerebral Hemorrhage: 999 case-control pairs African American participants, 998 case-control pairs, Hispanic Americans, 1000 case-control pairs, White Americans) studies. Ethnicity/Race was self-reported. The effect measure of interest is the odds ratio (OR). To test for differences in the effects of the risk factors between the SIREN IA study population and each of the ERICH study populations, a test for heterogeneity was computed using the R program, metagen (version 4.9-6). RESULTS: ICH occurred at a younger age among IA (54.3±13.4 years), African Americans (58.0±12.7), and Hispanic Americans (58.9±14.3), compared with White Americans (69.1±13.9). The largest distinction was for hypertension, where IA exhibited a much larger risk of ICH than the American study population (OR, 67.02 [95% CI, 33.30-134.85]), African American (OR, 3.71 [95% CI, 2.53-5.44]); Hispanic (OR, 3.55 [95% CI, 2.54-4.92]), and White population (OR, 2.69 [95% CI, 1.95-3.69]). Current alcohol use exhibited increased risk in IA (OR, 2.24 [95% CI, 1.36-3.67]), but not in African Americans (OR, 0.63 [95% CI, 0.46-0.86]), Hispanic (OR, 0.87 [95% CI, 0.65-1.17]), and White Americans (OR, 0.51 [95% CI, 0.38-0.69]). CONCLUSIONS: Identical or comparable risk factors do not consistently result in the same disease risk across different cultures and regions. Therefore, to improve our understanding of the genetic determinants and biological pathways driving ICH risk, it is crucial to study multiple populations, including IA, while accounting for the influence of environmental and social factors.

Adult↗

PubMed2026

Genetically Predicted Muscle Mass and Function in Relation to Deep Vein Thrombosis: A Two-step Mendelian Randomization Study Highlighting the Mediating Role of BMI.

BackgroundSarcopenia is observationally linked to venous thromboembolism, but the causal architecture and underlying biological pathways remain largely unclear. This study investigated the causal effects of sarcopenia-related traits on lower extremity deep vein thrombosis (DVT) and quantified potential mediating mechanisms.MethodsWe performed two-sample bidirectional Mendelian randomization (MR) and two-step mediation MR using large-scale GWAS data from UK Biobank, EMBL-EBI, and FinnGen. Exposures included appendicular lean mass (ALM), leg fat-free mass (LFM), hand grip strength, and walking pace. Eighteen candidate mediators were screened for indirect pathways.ResultsGenetically predicted higher ALM was significantly associated with increased DVT risk (FinnGen: OR = 1.288, 95% CI: 1.215-1.365, P < 0.001). Similar positive associations were observed for LFM (OR = 1.920-1.954, P < 0.001). By contrast, muscle functional traits - grip strength and walking pace - demonstrated no consistent causal effects. Reverse MR confirmed a unidirectional relationship. Body mass index (BMI) emerged as a pivotal mediator, accounting for 7.58% - 10.50% of the ALM-DVT effect and 52.74% - 62.73% of the LFM-DVT effect. Notably, the independent effect of ALM was largely attenuated after adjusting for metabolic confounders in multivariable MR.ConclusionGenetic predisposition to high muscle mass, rather than functional strength, increases DVT risk. This relationship appears to be significantly driven by metabolic adiposity, suggesting that the "muscle-vascular-coagulation" interaction is partly explained by body-size-related metabolic burden. Risk stratification should integrate muscle mass evaluation with comprehensive metabolic health assessments.

Humans↗