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Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
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Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion
Jeroen R Huyghe1, Anne U Jackson, Marie P Fogarty
1Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.
Nature Genetics
|December 25, 2012
Summary
Researchers identified low-frequency genetic variants influencing insulin secretion and fasting proinsulin levels in Finnish males. This advances understanding of type 2 diabetes genetics.
Area of Science:
- Genetics
- Metabolic Disorders
Background:
- Insulin secretion is vital for glucose homeostasis; its failure characterizes type 2 diabetes.
- Genome-wide association studies (GWAS) have identified some genetic factors, but a significant portion remains unknown.
Purpose of the Study:
- To investigate the role of low-frequency and rare nonsynonymous variants in insulin secretion and processing.
- To identify novel genes associated with fasting proinsulin concentrations and insulinogenic index.
Main Methods:
- Analysis of exome array data from 8,229 nondiabetic Finnish males using the Illumina HumanExome Beadchip.
- Examination of low-frequency (MAF 0.5-5%) and rare (MAF < 0.5%) coding variants.
Main Results:
- Identified low-frequency coding variants linked to fasting proinsulin at known GWAS loci (SGSM2, MADD).
- Discovered three new genes (TBC1D30, KANK1, PAM) with low-frequency variants associated with fasting proinsulin or insulinogenic index.
- Highlighted the influence of distant noncoding SNPs on variant interpretation.
Conclusions:
- Exome array genotyping effectively identifies low-frequency variants contributing to complex traits like insulin secretion.
- This study expands the genetic landscape influencing insulin homeostasis and provides targets for type 2 diabetes research.
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