Abstract
Metabolome-genome wide association studies (mGWASs) are useful for understanding the genetic regulation of metabolites in complex diseases, including type 2 diabetes (T2D). Numerous genetic variants associated with T2D-related metabolites have been identified in previous mGWASs; however, these analyses seem to have difficulty in detecting the genetic variants with functional effects. An exome array focussed on potentially functional variants is an alternative platform to obtain insight into the genetics of biochemical conversion processes. In the present study, we performed an mGWAS using 27,140 non-synonymous variants included in the Illumina HumanExome BeadChip and nine T2D-related metabolites identified by a targetted metabolomics approach to evaluate 2,338 Korean individuals from the Korea Association REsource (KARE) cohort. A linear regression analysis controlling for age, sex, BMI, and T2D status as covariates was performed to identify novel non-synonymous variants associated with T2D-related metabolites. We found significant associations between glycine and CPS1 (rs1047883) and PC ae C36:0 and CYP4F2 (rs2108622) variants (P<2.05 × 10−7, after the Bonferroni correction for multiple testing). One of the two significantly associated variants, rs1047883 was newly identified whereas rs2108622 had been previously reported to be associated with T2D-related traits. These findings expand our understanding of the genetic determinants of T2D-related metabolites and provide a basis for further functional validation.
Highlights
Metabolome-genome wide association studies are useful for evaluating associations between genetic variants and serum or plasma metabolite levels by integrating genomics and metabolomics data [1]
Individuals were classified into type 2 diabetes (T2D) (n= 512), prediabetes (PD, n= 862), and normal glucose tolerance (NGT, n= 964) groups according to the American Diabetes Association (ADA) diagnostic criteria based on fasting plasma glucose levels (FPG), glycated hemoglobin levels, and 2-h plasma glucose levels (2h-PG) [12]
A total of 2,338 Korean individuals were divided into T2D (n=512), PD (n=862), and NGT (n=964) groups according to the ADA diagnostic criteria, as mentioned in the materials and methods
Summary
Metabolome-genome wide association studies (mGWASs) are useful for evaluating associations between genetic variants and serum or plasma metabolite levels by integrating genomics and metabolomics data [1]. Several previous mGWASs using European cohorts from the Cooperative Health Research in the Region of Augsburg (KORA), Framingham Heart Study (FHS), and Twin UK have identified common variants in dozens of genetic loci associated with metabolite concentrations, including lipids, carbohydrates, amino acids, nucleotides, peptides, and cofactors [3,4,5,6]. MGWASs using existing genotype arrays, like Affymetrix 6.0, are generally focussed on non-coding variants located in intronic or intergenic regions, and have difficulty in capturing potentially functional genetic variants. To overcome this limitation, exome arrays focussed on potentially functional variants in protein-coding regions of genes are an alternative approach [8].
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