Systematic Functional Characterization of Candidate Causal Genes for Type 2 Diabetes Risk Variants.
Soren K ThomsenAlessandro CeroniMartijn van de BuntCarla BurrowsAmy BarrettRaphael ScharfmannDaniel EbnerMark I McCarthyAnna L GloynPublished in: Diabetes (2016)
Most genetic association signals for type 2 diabetes risk are located in noncoding regions of the genome, hindering translation into molecular mechanisms. Physiological studies have shown a majority of disease-associated variants to exert their effects through pancreatic islet dysfunction. Systematically characterizing the role of regional transcripts in β-cell function could identify the underlying disease-causing genes, but large-scale studies in human cellular models have previously been impractical. We developed a robust and scalable strategy based on arrayed gene silencing in the human β-cell line EndoC-βH1. In a screen of 300 positional candidates selected from 75 type 2 diabetes regions, each gene was assayed for effects on multiple disease-relevant phenotypes, including insulin secretion and cellular proliferation. We identified a total of 45 genes involved in β-cell function, pointing to possible causal mechanisms at 37 disease-associated loci. The results showed a strong enrichment for genes implicated in monogenic diabetes. Selected effects were validated in a follow-up study, including several genes (ARL15, ZMIZ1, and THADA) with previously unknown or poorly described roles in β-cell biology. We have demonstrated the feasibility of systematic functional screening in a human β-cell model and successfully prioritized plausible disease-causing genes at more than half of the regions investigated.
Keyphrases
- type diabetes
- genome wide
- endothelial cells
- copy number
- genome wide identification
- glycemic control
- cardiovascular disease
- dna methylation
- stem cells
- gene expression
- bone marrow
- cell therapy
- signaling pathway
- genome wide analysis
- metabolic syndrome
- pluripotent stem cells
- high throughput
- mesenchymal stem cells
- weight loss
- transcription factor
- high speed
- genome wide association study
- breast cancer risk