ArticleScientific reports2024
Type 1 diabetes genetic risk score variation across ancestries using whole genome sequencing and array-based approaches.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Development and application of type 1 diabetes polygenic scores across diverse populations.Diabetologia · 2026Review
- Polygenic background contributes to GCK-MODY clinical presentation and glycaemic variability.Diabetologia · 2026Article
- Development and validation of a trans-ancestry polygenic risk score for type 1 diabetes.Diabetologia · 2026Article
- Population Prevalence, Penetrance, and Mortality for Genetically Confirmed MODY.The Journal of clinical endocrinology and metabolism · 2026Article
- Article
- Extending the Eisenbarth Model: Stage 0 as a Provisional Framework for Early Risk Stratification and Prevention in Type 1 Diabetes.Journal of diabetes research · 2026Review
- Development and recalibration of a multivariable type 1 diabetes prediction model for type 1 diabetes across multiple screening studies.BMC medicine · 2025Article
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Authors and funding
7 authors.
Funding
Abstract
A Type 1 Diabetes Genetic Risk Score (T1DGRS) aids diagnosis and prediction of Type 1 Diabetes (T1D). While traditionally derived from imputed array genotypes, Whole Genome Sequencing (WGS) provides a more direct approach and is now increasingly used in clinical and research studies. We investigated the concordance between WGS-based and array-based T1DGRS across genetic ancestries in 149,265 UK Biobank participants using WGS, TOPMed-imputed, and 1000 Genomes-imputed array genotypes. In the overall cohort, WGS-based T1DGRS demonstrated strong correlation with TOPMed-imputed array-based score (r = 0.996, average WGS-based score 0.0028 standard deviations (SD) lower, p < 10
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