Prioritization of genes associated with type 2 diabetes mellitus for functional studies.
Wei Xuan TanXueling SimChin Meng KhooAdrian Kee Keong TeoPublished in: Nature reviews. Endocrinology (2023)
Existing therapies for type 2 diabetes mellitus (T2DM) show limited efficacy or have adverse effects. Numerous genetic variants associated with T2DM have been identified, but progress in translating these findings into potential drug targets has been limited. Here, we describe the tools and platforms available to identify effector genes from T2DM-associated coding and non-coding variants and prioritize them for functional studies. We discuss QSER1 and SLC12A8 as examples of genes that have been identified as possible T2DM candidate genes using these tools and platforms. We suggest further approaches, including the use of sequencing data with increased sample size and ethnic diversity, single-cell omics data for analyses, glycaemic trait associations to predict gene function and, potentially, human induced pluripotent stem cell 'village' cultures, to strengthen current gene functionalization workflows. Effective prioritization of T2DM-associated genes for experimental validation could expedite our understanding of the genetic mechanisms responsible for T2DM to facilitate the use of precision medicine in its treatment.
Keyphrases
- genome wide
- glycemic control
- single cell
- genome wide identification
- copy number
- type diabetes
- stem cells
- dna methylation
- endothelial cells
- big data
- electronic health record
- cardiovascular disease
- high glucose
- oxidative stress
- gene expression
- skeletal muscle
- high throughput
- weight loss
- bone marrow
- immune response
- artificial intelligence
- smoking cessation
- data analysis