ArticleScientific reports2020
Fine-tuning of Genome-Wide Polygenic Risk Scores and Prediction of Gestational Diabetes in South Asian Women.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 citations in OpenAlex.
- Identification and Potential Clinical Utility of Common Genetic Variants in Gestational Diabetes among Chinese Pregnant Women.Diabetes & metabolism journal · 2025Pooled it
- Association of Genetic Predisposition and Physical Activity With Risk of Gestational Diabetes in Nulliparous Women.JAMA network open · 2022Pooled it
- Prognostic biomarkers of future diabetes in South Asian women diagnosed with gestational diabetes: a prospective cohort study.BMC endocrine disorders · 2026Article
- Gestational Diabetes and Genetics:Genes · 2026Review
- Polygenic risk score as a tool to predict gestational weight gain and gestational diabetes among pregnant women in Taiwan.Journal of human genetics · 2025Article
- Diabetes polygenic risk scores and maternal characteristics in Hoosier Moms Cohort participants.Pregnancy (Hoboken, N.J.) · 2025Article
- Unveiling Gestational Diabetes: An Overview of Pathophysiology and Management.International journal of molecular sciences · 2025Review
- 2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association.Circulation · 2025Review
- Article
- 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association.Circulation · 2024Review
- Gestational diabetes mellitus: genetic factors, epigenetic alterations, and microbial composition.Acta diabetologica · 2024Review
- Genome-wide polygenic risk score for type 2 diabetes in Indian population.Scientific reports · 2023Article
- Article
- Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association.Circulation · 2023Review
- Article
- Microbial risk score for capturing microbial characteristics, integrating multi-omics data, and predicting disease risk.Microbiome · 2022Article
- Microbial Risk Score for Capturing Microbial Characteristics, Integrating Multi-omics Data, and Predicting Disease Risk.bioRxiv : the preprint server for biology · 2022Article
- Integrating polygenic risk scores in the prediction of type 2 diabetes risk and subtypes in British Pakistanis and Bangladeshis: A population-based cohort study.PLoS medicine · 2022Observational
- Genome-wide risk prediction of common diseases across ancestries in one million people.Cell genomics · 2022Article
- Serum metabolomic signatures of gestational diabetes in South Asian and white European women.BMJ open diabetes research & care · 2022Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gestational diabetes Mellitus (GDM) affects 1 in 7 births and is associated with numerous adverse health outcomes for both mother and child. GDM is suspected to share a large common genetic background with type 2 diabetes (T2D). The aim of our study was to characterize different GDM polygenic risk scores (PRSs) and test their association with GDM using data from the South Asian Birth Cohort (START). PRSs were derived for 832 South Asian women from START using the pruning and thresholding (P + T), LDpred, and GraBLD methods. Weights were derived from a multi-ethnic and a white Caucasian study of the DIAGRAM consortium. GDM status was defined using South Asian-specific glucose values in response to an oral glucose tolerance test. Association with GDM was tested using logistic regression. Results were replicated in South Asian women from the UK Biobank (UKB) study. The top ranking P + T, LDpred and GraBLD PRSs were all based on DIAGRAM's multi-ethnic study. The best PRS was highly associated with GDM in START (AUC = 0.62, OR = 1.60 [95% CI = 1.44-1.69]), and in South Asian women from UKB (AUC = 0.65, OR = 1.69 [95% CI = 1.28-2.24]). Our results highlight the importance of combining genome-wide genotypes and summary statistics from large multi-ethnic studies to optimize PRSs in South Asians.
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