medwireNews: Exome array genotyping, which allows focus on the protein coding regions of the genome, has enabled researchers to identify three new genes containing low-frequency variants that influence insulin levels.
The team also found low-frequency genetic variants in two genes known to be associated with fasting proinsulin concentrations.
"The exome array allowed us to test a large number of individuals - in this case, more than 8,000 people - very efficiently," said study author Karen Mohlke (University of North Carolina, Chapel Hill, USA) in a press statement.
In addition to allowing researchers to focus on coding regions of the genome, exome array analysis is also cheaper than more traditional genetic sequencing. "We expect that this type of analysis will be useful for finding low-frequency variants associated with many complex traits, including obesity or cancer," said Mohlke.
As reported in Nature Genetics, the team searched for low-frequency (minor allele frequency [MAF] 0.5-5.0%) and rare (MAF below 0.5%) coding variants associated with insulin levels in 8229 Finnish men without diabetes.
They found two new low-frequency variants, rs61741902 and rs35233100, in the genes SGSM2 and MADD, respectively, both of which were identified in previous research as being involved in insulin secretion and regulation.
In addition, they identified three new genes -TBC1D30, KANK1, and PAM - containing 12 low-frequency variants associated with fasting proinsulin levels or the insulinogenic index.
As none of the participants in the study were diabetic, Mohlke and colleagues believe the variants they detected could predispose people to developing diabetes. However, they concede that more research is needed to confirm this.
"Studying genetic variants - even rare ones - helps us learn how genes affect health and disease," said Mohlke. "In this study, we've implicated new genes as playing a role in insulin processing and secretion."
The researchers conclude: "Although sequencing will still be required to completely assess variants associated with insulin processing, secretion and glycemic traits, this study provides proof of principle that exome array genotyping is a powerful approach to identify low-frequency functional variants and fine map genome-wide association study-identified loci in complex traits."
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