St John's Research Institute, Bangalore, Karnataka, India
CSIR Institute of Genomics and Integrative Biology, New Delhi, India.
BMJ Open Diabetes Res Care. 2024 Mar 12;12(2):e003769. doi: 10.1136/bmjdrc-2023-003769.
Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants.
We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test.
Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs).
Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.
遗传变异导致了非胰岛素类抗糖尿病药物（NIAD）的反应差异，进而导致了血糖控制的变化。优化血糖控制对于最大限度地减少 2 型糖尿病相关的长期并发症至关重要。印度独特的遗传结构及其不断增加的 2 型糖尿病负担，需要对与 NIAD 相关的药物遗传学（PGx）变异进行特定人群的调查。印度人口的大规模全基因组数据的最近可用性提供了一个独特的机会，可以生成与 NIAD 相关的 PGx 变异的特定人群图谱。
我们从 1029 个印度全基因组中挖掘了与 44 种 NIAD 相关的 PGx 变异、药物相互作用（DDI）和药物-基因相互作用（DDGI）。使用 Fisher 精确检验估计和比较了人群的等位基因频率。
总体而言，我们发现了 76 个已知的和 52 个预测的常见的、有不良影响的 PGx 变异，这些变异与印度人的 2 型糖尿病治疗反应有关。我们报告了不同种族之间在 NIAD 类别的降低和增加反应相关等位基因的相对累积计数方面存在显著差异。与其他全球人群相比，印度人和南亚人表现出明显的增加的二甲双胍反应相关等位基因减少。对共享 PGx 基因的网络分析预测，在 NIAD 与其他代谢性疾病药物联合使用时，DDI 风险很高。我们还预测，当与质子泵抑制剂（PPIs）联合使用时，CYP3A4/3A5 代谢的 NIAD、沙格列汀、利格列汀和格列吡嗪的 CYP2C19 介导的 DDGI 风险会增加。
印度人和南亚人对糖尿病药物有独特的 PGx 特征，表现为各种 NIAD 类别的不良治疗反应相关等位基因过多。这表明，至少在某些 NIAD 中，人群可能会出现特定的药物反应降低。此外，我们的发现为加速未来在印度人和南亚人中进行糖尿病 PGx 研究以及重新考虑 NIAD 剂量指南提供了一个可行的资源，以确保在该人群中达到最大的疗效和安全性。
