| Title: | Fine-tuning of Genome-Wide Polygenic Risk Scores and Prediction of Gestational Diabetes in South Asian Women |
| Journal: | Scientific Reports |
| Published: | 2 Jun 2020 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/32488059/ |
| DOI: | https://doi.org/10.1038/s41598-020-65360-y |
| URL: | https://www.nature.com/articles/s41598-020-65360-y.pdf |
Publication 9119
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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.</p>
6 Authors
- Amel Lamri
- Shihong Mao
- Dipika Desai
- Milan Gupta
- Guillaume Paré
- Sonia S. Anand
Enabling scientific discoveries that improve human health