Genetic Risk Scores for the Determination of Type 2 Diabetes Mellitus (T2DM) in North India

Lisa Mitsuko Shitomi-Jones, Liz Akam, David Hunter, Puneetpal Singh and Sarabjit Mastana ()
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Lisa Mitsuko Shitomi-Jones: School of Sport, Exercise and Health Sciences, Loughborough University, Epinal Way, Leicestershire, Loughborough LE11 3TU, UK
Liz Akam: School of Sport, Exercise and Health Sciences, Loughborough University, Epinal Way, Leicestershire, Loughborough LE11 3TU, UK
David Hunter: School of Sport, Exercise and Health Sciences, Loughborough University, Epinal Way, Leicestershire, Loughborough LE11 3TU, UK
Puneetpal Singh: Department of Human Genetics, Punjabi University, Patiala 147002, India
Sarabjit Mastana: School of Sport, Exercise and Health Sciences, Loughborough University, Epinal Way, Leicestershire, Loughborough LE11 3TU, UK

IJERPH, 2023, vol. 20, issue 4, 1-14

Abstract: Background: Globally, type 2 diabetes mellitus (T2DM) is one of the fastest-growing noncommunicable multifactorial and polygenic diseases, which leads to many health complications and significant morbidity and mortality. South Asians have a high genetic predisposition to T2DM, with India being home to one in six diabetics. This study investigates the association of selected genetic polymorphisms with T2DM risk and develops a polygenic risk score (PRS). Methods: A case–control study recruited fully consented participants from a population of Jat Sikhs in north India. DNA samples were genotyped for a range of polymorphisms and odds ratios were calculated under several genetic association models. Receiver operating characteristic (ROC) curves were produced for combinations of the PRS and clinical parameters. Results: The GSTT1(rs17856199), GSTM1(rs366631), GSTP1(rs1695), KCNQ1(rs2237892), ACE(rs4646994), and TCF7L2(rs12255372; rs7903146; rs7901695) polymorphisms were associated with increased T2DM risk ( p ≤ 0.05). No association was observed with IGF2BP2(rs4402960) or PPARG2(rs1801282). The weighted PRS was found to be significantly higher in patients (mean = 15.4, SD = 3.24) than controls (mean = 11.9, SD = 3.06), and t (454) = −12.2 ( p < 0.001). The ROC curve analysis found the weighted PRS in combination with clinical variables to be the most effective predictor of T2DM (area under the curve = 0.844, 95%CI = 0.0.808–0.879). Conclusions: Several polymorphisms were associated with T2DM risk. PRS based on even a limited number of loci improves the prediction of the disease. This may provide a useful method for determining T2DM susceptibility for clinical and public health applications.

Keywords: India; polygenic risk score; polymorphism; type 2 diabetes (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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