Genomic Sequencing Opens A New Era of T2D Research

Type 2 diabetes mellitus (T2D) is a common disease that is mainly caused by insulin resistance and or insulin hypersecretion. Genetic studies using linkage analysis and candidate gene approaches have identified an initial set of T2D-associated loci. Over the past decade, with increasing sample sizes, genome-wide association studies (GWAS) have identified 144 genetic variants in 129 motifs associated with T2D.

Genomic and transcriptomic sequencing and whole-gene association study analysis can not only identify multiple genetic variants associated with T2D, but also detect the effect of T2DM drugs on gene-specific expression, etc., which can contribute to pharmacogenomic studies, drug and personalized therapeutic regimen development.

Genome-wide study reveals genetic markers for type II diabetes in European ancestry

Researchers conducted a Meta-analysis of genome-wide association studies (GWAS) with approximately 16 million genetic variants in 62,892 T2D cases and 596,424 European controls. They identified 139 common and 4 rare variants associated with T2D, of which 42 (39 common and 3 rare variants) were not identified in previous studies. Integration of gene expression data from blood with the GWAS results clarified 33 functional genes of T2D, 3 of which could be targeted by approved drugs.

In addition, the authors combined the GWAS meta-analysis results with gene expression and DNA methylation data to identify genes that may be associated with T2D function and to infer possible mechanisms by which genetic variants affect T2D risk through gene regulation of DNA methylation.

Prioritizing genes and regulatory elements at TP53INP1 locus for T2DPrioritizing genes and regulatory elements at TP53INP1 locus for T2D (Xue A et al. 2018)

Genome-wide analysis study reveals genetic markers of type 2 diabetes in East Asians

More than 240 genetic loci associated with type 2 diabetes (T2D) have been identified in the analysis of individuals of European ancestry. By analyzing genome-wide association data from 23 cohort studies from multiple countries and regions, including China, Korea, Japan, Singapore, and the Philippines, researchers in this study identified genes GDAP1, PTF1A, SIX3, and ALDH2, as well as genes affecting muscle and adipose differentiation, as being associated with diabetes risk. These findings expand the number of genetic variants associated with diabetes and highlight the importance of studying different pedigrees.

Regional association plots at three T2D-associated loci with the strongest association P values and more than five distinct association signals in East Asian individualsRegional association plots at three T2D-associated loci with the strongest association P values and more than five distinct association signals in East Asian individuals (Spracklen C N et al. 2020)

NGS analyzes genetic variation and transcriptomic effects of metformin in individuals with T2DM

Metformin is a relatively effective and inexpensive antidiabetic drug. While most people can tolerate metformin, about 30% still exhibit mild gastrointestinal side effects and about 5% exhibit severe intolerance, the study reports. Using targeted exome sequencing and RNA-seq to analyze the genetic and transcriptomic profiles of T2DM individuals receiving metformin monotherapy, the investigators found that the SLC22A4 gene is associated with improved response to metformin medication and is involved in metformin transport in the intestine and oral absorption. The identification of SLC22A4 gene variants is expected to predict drug response.

Differentially expressed genes in the study populationDifferentially expressed genes in the study population (Vohra M et al. 2022)


The application of multi-omics such as genome sequencing and transcriptomics studies complex diseases such as T2D and the impact of gene association analysis and gene expression after drug administration, which is an important part of pharmacogenomics. Pharmacogenomics offers fascinating prospects for improving patient care by optimizing drug selection and dosing, reducing the risk of adverse events, and further implementing principles of personalized medicine.


  1. Xue A, Wu Y, Zhu Z, et al. Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes. Nature communications, 2018, 9(1): 1-14.
  2. Spracklen C N, Horikoshi M, Kim Y J, et al. Identification of type 2 diabetes loci in 433,540 East Asian individuals. Nature, 2020, 582(7811): 240-245.
  3. Vohra M, Sharma A R, Mallya S, et al. Implications of genetic variations, differential gene expression, and allele-specific expression on metformin response in drug-naïve type 2 diabetes. Journal of Endocrinological Investigation, 2022: 1-14.
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