Genome-wide screen for metabolic syndrome susceptibility Loci reveals strong lipid gene contribution but no evidence for common genetic basis for clustering of metabolic syndrome traits

Abstract

Background: Genome-wide association (GWA) studies have identified several susceptibility loci for metabolic syndrome (MetS) component traits, but have had variable success in identifying susceptibility loci to the syndrome as an entity. We conducted a GWA study on MetS and its component traits in 4 Finnish cohorts consisting of 2637 MetS cases and 7927 controls, both free of diabetes, and followed the top loci in an independent sample with transcriptome and nuclear magnetic resonance-based metabonomics data. Furthermore, we tested for loci associated with multiple MetS component traits using factor analysis, and built a genetic risk score for MetS.

Methods and results: A previously known lipid locus, APOA1/C3/A4/A5 gene cluster region (SNP rs964184), was associated with MetS in all 4 study samples (P=7.23×10(-9) in meta-analysis). The association was further supported by serum metabolite analysis, where rs964184 was associated with various very low density lipoprotein, triglyceride, and high-density lipoprotein metabolites (P=0.024-1.88×10(-5)). Twenty-two previously identified susceptibility loci for individual MetS component traits were replicated in our GWA and factor analysis. Most of these were associated with lipid phenotypes, and none with 2 or more uncorrelated MetS components. A genetic risk score, calculated as the number of risk alleles in loci associated with individual MetS traits, was strongly associated with MetS status.

Conclusions: Our findings suggest that genes from lipid metabolism pathways have the key role in the genetic background of MetS. We found little evidence for pleiotropy linking dyslipidemia and obesity to the other MetS component traits, such as hypertension and glucose intolerance.

Figure 1

Forest plot of the MetS case-control association result for SNP rs964184. The plot shows odds ratios (OR) and 95% confidence intervals (CI) separately for the four study samples and for their meta-analysis (in the Summary row). A separate analysis of the ‘older’ and ‘younger’ study samples resulted in very similar odds ratios and overlapping 95% confidence intervals: HBCS+H2000 1.40 (1.22-1.60) and YFS+NFBC 1.27 (1.11-1.44). A meta-analysis of the three older cohorts, excluding the youngest and largest cohort NFBC, resulted in an odds ratio of 1.35 (1.20-1.52). The OR is on the x-axis of the plot and the lines represent the confidence intervals. H2000, Health 2000; HBCS, Helsinki Birth Cohort Study; YFS, Cardiovascular Risk in Young Finns Study; NFBC1966, Northern Finland Birth Cohort 1966.

Figure 2

SNP associations across MetS phenotypes. The plot shows SNP-phenotype associations for the twenty-two top hit SNPs from the MetS component GWA analysis (Figure S6 and Table S3), four top hit SNPs from the TG/HDL/waist circumference –factor analysis, and five SNPs with a suggestive association in the TG/HDL/waist circumference/HOMA-IR –factor analysis (overlapping SNPs excluded). The colours correspond to beta effect size values for the minor allele of the SNP (values above 0.2 have been recoded to 0.2 and values below −0.2 to −0.2 and positive values refer to a risk effect and negative values to a protective effect). P_sig-values for the tests are shown as: * P < 0.01, ** P < 1×10⁻⁴, *** P < 1×10⁻⁶, **** P < 5×10⁻⁸. HDL, high-density lipoprotein; MetS, metabolic syndrome case-control status; TG, triglycerides; F1, TG/HDL/waist circumference -factor; F2, TG/HDL/waist circumference/HOMA-IR -factor; GLU, glucose; DBP, diastolic blood pressure; F3, SBP/DBP blood pressure factor; SBP, systolic blood pressure; INS, insulin; HOMA_IR, Homeostatic Model Assessment Insulin Resistance.