Progress in genetics of type 2 diabetes and diabetic complications.
Nobuhiro ShojimaToshimasa YamauchiPublished in: Journal of diabetes investigation (2023)
Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life-style intervention more accurately for individuals. Genome-wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large-scale genome-wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi-polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi-omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.
Keyphrases
- type diabetes
- glycemic control
- genome wide association
- cardiovascular disease
- clinical trial
- insulin resistance
- genome wide
- risk factors
- healthcare
- mass spectrometry
- amino acid
- oxidative stress
- gene expression
- metabolic syndrome
- single cell
- dna methylation
- copy number
- deep learning
- phase ii
- double blind
- phase iii
- case control