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Integrating polygenic risk scores in the prediction of type 2 diabetes risk and subtypes in British Pakistanis and Bangladeshis: A population-based cohort study.

Sam HodgsonQin Qin HuangNeneh Sallahnull nullChris J GriffithsWilliam G NewmanRichard C TrembathJohn WrightR Thomas LumbersKaroline B KuchenbaeckerDavid A van HeelRohini MathurHilary C MartinSarah Finer
Published in: PLoS medicine (2022)
Our analysis of the transferability of T2D loci between EUR and BPB indicates the need for larger, multiancestry studies to better characterise the genetic contribution to disease and its varied aetiology. We show that a T2D PRS optimised for this high-risk BPB population has potential clinical application in BPB, improving the identification of T2D risk (especially in the young) on top of an established clinical risk algorithm and aiding identification of subgroups at diagnosis, which may help future efforts to stratify care and treatment of the disease.
Keyphrases
  • type diabetes
  • machine learning
  • cardiovascular disease
  • quality improvement
  • metabolic syndrome
  • dna methylation
  • insulin resistance
  • climate change
  • copy number
  • neural network