ArticleGenome medicine2024
Defining type 2 diabetes polygenic risk scores through colocalization and network-based clustering of metabolic trait genetic associations.
Article in Genome medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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21 citing papers in PubMed, 18 citations in OpenAlex.
- Nature vs nurture of glucose homeostasis trajectories in children from the ALSPAC study.Diabetologia · 2026Article
- Life's Essential 8, Polygenic Risk for Type 2 Diabetes, and Dementia: Evidence from the UK Biobank.Nutrients · 2026Article
- Transfer learning enhances clinical utility of polygenic scores with small, phenotypically refined cohorts.Genome research · 2026Article
- Mapping disease loci to biological processes via joint pleiotropic and epigenomic partitioning.Cell genomics · 2026Article
- Bridging the variant-to-function gap in type 2 diabetes: advances and challenges.Diabetologia · 2026Review
- Reactive astrocyte-related pathogenic genes in Parkinson's disease: A multi-omics Mendelian randomization study.Journal of Parkinson's disease · 2026Article
- Multi-layer gut microbiome variation in type 2 diabetes despite preserved higher-order community structure.Frontiers in microbiology · 2026Article
- Purine Metabolism-Related Pathogenic Genes in Trigeminal Neuralgia: A Multiomics Mendelian Randomization Study.Pain research & management · 2026Article
- Quantifying Metabolic Syndrome Severity: Methodological Evolution, Clinical Validation, and Translational Perspectives.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026Review
- Integrative proteomic analysis provides novel therapeutic insights for etiological subtypes of diabetes.Diabetes, obesity & metabolism · 2025Article
- Aetiological clustering of newly diagnosed type 2 diabetes using machine learning: a retrospective cross-sectional study in Dubai, UAE.BMJ open · 2025Article
- Pathogenic genes associated with immune-related genes in graves' disease: a multi-omics Mendelian randomization analysis.Scientific reports · 2025Article
- Polygenic risk score for type 2 diabetes shows context-dependent effects across populations.Nature communications · 2025Article
- Genetic Variants in Metabolic Pathways and Their Role in Cardiometabolic Risk: An Observational Study of >4000 Individuals.Biomedicines · 2025Article
- Mapping disease loci to biological processes via joint pleiotropic and epigenomic partitioning.medRxiv : the preprint server for health sciences · 2025Article
- Sex Hormone-Related Pathogenic Genes in Multiple Sclerosis: A Multi-omics Mendelian Randomization Study.Journal of molecular neuroscience : MN · 2025Article
- Investigating misclassification of type 1 diabetes in a population-based cohort of British Pakistanis and Bangladeshis using polygenic risk scores.Scientific reports · 2025Article
- Actionability of Genetic Variants in Diabetes: Core Aspects and Applied Examples.Diabetes spectrum : a publication of the American Diabetes Association · 2025Article
- Diabetes Management Based on the Phenotype and Stage of the Disease: An Expert Proposal from the AGORA Diabetes Collaborative Group.Journal of clinical medicine · 2024Review
- HumanIslets: An integrated platform for human islet data access and analysis.bioRxiv : the preprint server for biology · 2024Article
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11 authors at 1 institution in 1 country.
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Abstract
backgroundType 2 diabetes (T2D) is a heterogeneous and polygenic disease. Previous studies have leveraged the highly polygenic and pleiotropic nature of T2D variants to partition the heterogeneity of T2D, in order to stratify patient risk and gain mechanistic insight. We expanded on these approaches by performing colocalization across GWAS traits while assessing the causality and directionality of genetic associations.
methodsWe applied colocalization between T2D and 20 related metabolic traits, across 243 loci, to obtain inferences of shared casual variants. Network-based unsupervised hierarchical clustering was performed on variant-trait associations. Partitioned polygenic risk scores (PRSs) were generated for each cluster using T2D summary statistics and validated in 21,742 individuals with T2D from 3 cohorts. Inferences of directionality and causality were obtained by applying Mendelian randomization Steiger's Z-test and further validated in a pediatric cohort without diabetes (aged 9-12 years old, n = 3866).
resultsWe identified 146 T2D loci that colocalized with at least one metabolic trait locus. T2D variants within these loci were grouped into 5 clusters. The clusters corresponded to the following pathways: obesity, lipodystrophic insulin resistance, liver and lipid metabolism, hepatic glucose metabolism, and beta-cell dysfunction. We observed heterogeneity in associations between PRSs and metabolic measures across clusters. For instance, the lipodystrophic insulin resistance (Beta - 0.08 SD, 95% CI [- 0.10-0.07], p = 6.50 × 10
conclusionsWe successfully partitioned T2D genetic variants into phenotypic pathways using a colocalization first approach. Partitioned PRSs were associated to unique metabolic and clinical outcomes indicating successful partitioning of disease heterogeneity. Our work expands on previous approaches by providing stronger inferences of shared causal variants, causality, and directionality of GWAS variant-trait associations.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.