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<p>This study investigated the predictability of type 2 diabetes (T2D) using genetic risk factors identified through Genome-wide association studies (GWAS) using whole exome sequencing (WES) data from 674 individuals with T2D and 736 controls. Nine single nucleotide polymorphisms (SNPs) were associated with HbA1c, explaining 97.7% of its variability. Ten SNPs were linked to T2D, accounting for 90.5% variability. Multifactor dimensionality reduction (MDR) analysis identified interactions among <i>EFCAB8</i> rs13045180, <i>TCF7L2</i> rs4506565, and <i>SDHAF4</i> rs1048886. The Infinium global screening array (GSA) explained 78.8% of HbA1c variability based on 10 SNPs. Logistic regression analysis revealed four novel (<i>EFCAB8</i>, <i>KLF14</i>, <i>FAM13B</i>, and <i>SLIT2</i>) and seven previously reported associations with T2D. The GSA-derived polygenic risk score (PRS) achieved 86.09% accuracy in predicting T2D. Individuals with PRS &gt; 10 had a 4.54-fold increased risk of coronary artery disease (95% CI 1.75–11.80, <i>p</i> = 0.003). MDR analysis of GSA data highlighted interactions among <i>CDKAL1</i> (rs10946398/rs7756992), <i>TCF7L2</i> rs4506565, and <i>SDHAF4</i> rs1048886, modifying the T2D susceptibility. STRING analysis confirmed interactions among <i>KLF14</i>, <i>TCF7L2</i>, <i>CDKAL1</i>, and <i>SLC30A8</i>. In conclusion, non-coding variants significantly influence T2D susceptibility, with WES and GSA showing comparable efficacy for early T2D prediction.</p>

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Polygenic Risk Scores for Predicting Type 2 Diabetes Using Whole-Exome Sequencing and Global Screening Array

  • 期刊论文

  • 发表日期：

    2025年7月17日

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  • Shaik Mohammad Naushad,
  • Palanichamy Palani Kumar,
  • Yadam Reddy Kanaka Durga Devi,
  • Jagadeesh Babu Sreemanthula,
  • Gopi Palakonda,
  • Tajamul Hussain,
  • Salman Alrokayan,
  • May M. Alrashed,
  • Kotamraju Kaavya,
  • Karra Kiranmayee,
  • Vijay Kumar Kutala

摘要

This study investigated the predictability of type 2 diabetes (T2D) using genetic risk factors identified through Genome-wide association studies (GWAS) using whole exome sequencing (WES) data from 674 individuals with T2D and 736 controls. Nine single nucleotide polymorphisms (SNPs) were associated with HbA1c, explaining 97.7% of its variability. Ten SNPs were linked to T2D, accounting for 90.5% variability. Multifactor dimensionality reduction (MDR) analysis identified interactions among EFCAB8 rs13045180, TCF7L2 rs4506565, and SDHAF4 rs1048886. The Infinium global screening array (GSA) explained 78.8% of HbA1c variability based on 10 SNPs. Logistic regression analysis revealed four novel (EFCAB8, KLF14, FAM13B, and SLIT2) and seven previously reported associations with T2D. The GSA-derived polygenic risk score (PRS) achieved 86.09% accuracy in predicting T2D. Individuals with PRS > 10 had a 4.54-fold increased risk of coronary artery disease (95% CI 1.75–11.80, p = 0.003). MDR analysis of GSA data highlighted interactions among CDKAL1 (rs10946398/rs7756992), TCF7L2 rs4506565, and SDHAF4 rs1048886, modifying the T2D susceptibility. STRING analysis confirmed interactions among KLF14, TCF7L2, CDKAL1, and SLC30A8. In conclusion, non-coding variants significantly influence T2D susceptibility, with WES and GSA showing comparable efficacy for early T2D prediction.