The largest known exome sequence analysis of patients with type 2 diabetes and controls, published online in Nature this week, identifies new rare variants associated with the disease. Exome sequencing is used to identify the protein-coding regions in the genome that might have a role in disease development. These findings may help to improve the way that type 2 diabetes is characterized and treated.
The exome is the portion of the genome that encodes functional proteins. Variants that have strong effects on protein function or diseases can offer insights into the role of particular genes in disease risk. It is predicted that these variants are likely to be rare, and are difficult to detect using genome-wide association studies. Exome sequencing has been expected to improve detection, but relatively few significant rare-variant associations for complex diseases, such as type 2 diabetes, have been identified, which may be in part due to limited sample sizes.
Jason Flannick and colleagues report an exome sequence analysis of 20,791 patients with type 2 diabetes and 24,440 controls across 5 ancestry groups. This is the largest published analysis of exome-sequenced cases of type 2 diabetes (the previous largest sample size was less than 10,000 cases), specifically, and of any disease, more generally. Their analysis identifies new rare-variant gene-level associations, and indicates that around 75,000-185,000 cases may be needed to detect significant rare-variant associations with large effect sizes in established type 2 diabetes gene targets. These results demonstrate the value of exome sequencing, alongside genome-wide association studies, for improving our understanding of complex diseases.
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