SynthesisDiabetologia2023
The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes.
Synthesis in Diabetologia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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12 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes.Nature genetics · 2024Pooled it
- The impact of low-frequency genetic variants on serum protein levels.bioRxiv : the preprint server for biology · 2026Article
- Advances in haplotype phasing and genotype imputation.Nature reviews. Genetics · 2026Review
- Diabetes mellitus polygenic risk scores: heterogeneity and clinical translation.Nature reviews. Endocrinology · 2025Review
- Predictive capabilities of polygenic scores in an East-Asian population-based cohort: the Singapore Chinese health study.Communications biology · 2025Article
- Review
- Large-scale admixture mapping in themedRxiv : the preprint server for health sciences · 2025Article
- Type 1 diabetes genetic risk score variation across ancestries using whole genome sequencing and array-based approaches.Scientific reports · 2024Article
- The PRIMED Consortium: Reducing disparities in polygenic risk assessment.American journal of human genetics · 2024Article
- Integrated clinical risk prediction of type 2 diabetes with a multifactorial polygenic risk score.medRxiv : the preprint server for health sciences · 2024Article
- MagicalRsq-X: A cross-cohort transferable genotype imputation quality metric.American journal of human genetics · 2024Article
- Evaluating the Efficacy of Type 2 Diabetes Polygenic Risk Scores in an Independent European Population.International journal of molecular sciences · 2024Article
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Authors and funding
64 authors at 20 institutions in 6 countries.
Funding
Abstract
aims/hypothesisThe Latino population has been systematically underrepresented in large-scale genetic analyses, and previous studies have relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) released the largest multi-ancestry genotype reference panel representing a unique opportunity to analyse rare genetic variations in the Latino population. We hypothesise that a more comprehensive analysis of low/rare variation using the TOPMed panel would improve our knowledge of the genetics of type 2 diabetes in the Latino population.
methodsWe evaluated the TOPMed imputation performance using genotyping array and whole-exome sequence data in six Latino cohorts. To evaluate the ability of TOPMed imputation to increase the number of identified loci, we performed a Latino type 2 diabetes genome-wide association study (GWAS) meta-analysis in 8150 individuals with type 2 diabetes and 10,735 control individuals and replicated the results in six additional cohorts including whole-genome sequence data from the All of Us cohort.
resultsCompared with imputation with 1000G, the TOPMed panel improved the identification of rare and low-frequency variants. We identified 26 genome-wide significant signals including a novel variant (minor allele frequency 1.7%; OR 1.37, p=3.4 × 10 CONCLUSIONS/
interpretationOur results demonstrate the utility of TOPMed imputation for identifying low-frequency variants in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores. DATA AVAILABILITY: Full summary statistics are available through the Common Metabolic Diseases Knowledge Portal ( https://t2d.hugeamp.org/downloads.html ) and through the GWAS catalog ( https://www.ebi.ac.uk/gwas/ , accession ID: GCST90255648). Polygenic score (PS) weights for each ancestry are available via the PGS catalog ( https://www.pgscatalog.org , publication ID: PGP000445, scores IDs: PGS003443, PGS003444 and PGS003445).
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