ArticleJournal of cellular and molecular medicine2024
Genome-wide association and polygenic risk score estimation of type 2 diabetes mellitus in Kinh Vietnamese-A pilot study.
Article in Journal of cellular and molecular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Association of IL16 rs11556218 and IL1B rs16944 polymorphisms with type 2 diabetes in the Kinh Vietnamese population.PloS one · 2026Article
- Association of the ABCG2 Q141K variant with gout in Kinh Vietnamese: a cross-sectional study.Clinical rheumatology · 2025Article
- Association of LRRK2 R1628P variant with Parkinson's disease in Kinh Vietnamese: a cross-sectional study.Neurogenetics · 2025Article
- Association between vitamin BBMJ open · 2025Article
- Genetic Risk Phenotypes for Type 2 Diabetes Differ with Ancestry in US Adults with Diabetes and Overweight/Obesity.Archives of medical research · 2025Article
- Genome-wide association and polygenic risk score estimation of type 2 diabetes mellitus in Kinh Vietnamese-A pilot study.Journal of cellular and molecular medicine · 2024Article
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Authors and funding
14 authors.
Funding
Abstract
A genome-wide association study (GWAS) is a powerful tool in investigating genetic contribution, which is a crucial factor in the development of complex multifactorial diseases, such as type 2 diabetes mellitus. Type 2 diabetes mellitus is a major healthcare burden in the Western Pacific region; however, there is limited availability of genetic-associated data for type 2 diabetes in Southeast Asia, especially among the Kinh Vietnamese population. This lack of information exacerbates global healthcare disparities. In this study, 997 Kinh Vietnamese individuals (503 with type 2 diabetes and 494 controls) were prospectively recruited and their clinical and paraclinical information was recorded. DNA samples were collected and whole genome genotyping was performed. Standard quality control and genetic imputation using the 1000 Genomes database were executed. A polygenic risk score for type 2 diabetes was generated in different models using East Asian, European, and mix ancestry GWAS summary statistics as training datasets. After quality control and genetic imputation, 107 polymorphisms reached suggestive statistical significance for GWAS (≤5 × 10
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