| Title: | Genome-wide polygenic risk score for type 2 diabetes in Indian population |
| Journal: | Scientific Reports |
| Published: | 18 Jul 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37463971/ |
| DOI: | https://doi.org/10.1038/s41598-023-38768-5 |
| URL: | https://www.nature.com/articles/s41598-023-38768-5.pdf |
Publication 11636
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Abstract
Genome-wide polygenic risk scores (PRS) for lifestyle disorders, like Type 2 Diabetes (T2D), are useful in identifying at-risk individuals early on in life, and to guide them towards healthier lifestyles. The current study was aimed at developing PRS for the Indian population using imputed genotype data from UK Biobank and testing the developed PRS on data from GenomegaDB of Indians living in India. 959 T2D cases and 2,818 controls were selected from Indian participants of UK Biobank to develop the PRS. Summary statistics available for South Asians, from the DIAMANTE consortium, were used to weigh genetic variants. LDpred2 algorithm was used to adjust the effect of linkage disequilibrium among the variants. The association of PRS with T2D, after adjusting for age, sex and top ten genetic principal components, was found to be very significant (AUC = 0.7953, OR = 2.9856 [95% CI: 2.7044-3.2961]). When participants were divided into four PRS quartile groups, the odds of developing T2D increased sequentially with the higher PRS groups. The highest PRS group (top 25%) showed 5.79 fold increased risk compared to the rest of the participants (75%). The PRS derived using the same set of variants was found to be significantly associated with T2D in the test dataset of 445 Indians (AUC = 0.7781, OR = 1.6656 [95%CI = 0.6127-4.5278]). Our study demonstrates a framework to derive Indian-specific PRS for T2D. The accuracy of the derived PRS shows it's potential to be used as a prognostic metric to stratify individuals, and to recommend personalized preventive strategies.</p>
3 Authors
- Sandhya Kiran Pemmasani
- Shravya Atmakuri
- Anuradha Acharya
1 Application
| Application ID | Title |
|---|---|
| 81481 | Integration of genetic, biochemical and life style data to generate composite health scores for individuals of Indian ancestry |
Enabling scientific discoveries that improve human health