A genome-wide association study of the human metabolome in a community-based cohort

Abstract

Because metabolites are hypothesized to play key roles as markers and effectors of cardiometabolic diseases, recent studies have sought to annotate the genetic determinants of circulating metabolite levels. We report a genome-wide association study (GWAS) of 217 plasma metabolites, including >100 not measured in prior GWAS, in 2076 participants of the Framingham Heart Study (FHS). For the majority of analytes, we find that estimated heritability explains >20% of interindividual variation, and that variation attributable to heritable factors is greater than that attributable to clinical factors. Further, we identify 31 genetic loci associated with plasma metabolites, including 23 that have not previously been reported. Importantly, we include GWAS results for all surveyed metabolites and demonstrate how this information highlights a role for AGXT2 in cholesterol ester and triacylglycerol metabolism. Thus, our study outlines the relative contributions of inherited and clinical factors on the plasma metabolome and provides a resource for metabolism research.

Figure 1. see also Figure S1 and Table S1. Genetic architecture of the human plasma metabolome

(A) The percent inter-individual variation for positively charged, polar metabolites explained by clinical (black) and genetic factors: top SNP (green), second top SNP (red), other genetic factors (grey). Clinical factors include age, sex, systolic blood pressure, anti-hypertensive medication use, diabetes mellitus, smoking status, body-mass index, and prevalent cardiovascular disease. (B) Data summarized for non-essential and essential amino acids.

Figure 2. see also Figures S2 and S3. Thirty-one genome-wide significant loci associated with metabolites in FHS

Loci with significant metabolite associations in FHS are depicted within the black circle. Overlap with prior studies (dotted circles) is indicated for 8 loci. Prior studies found an association between common variants at *AGXT2 and urinary levels of β-aminoisobutyric acid, †GCKR and the alanine/glutamine ratio, and ‡SLC16A10 and the tyrosine/isoleucine and alanine/tyrosine ratios.

Figure 3. Metabolite profiling demonstrates distinct patterns of TAG associations for select loci

For the 46 triacylglycerols (TAGs) monitored by our platform, the beta coefficient (left y-axis) and P-value (right y-axis) of association are shown for the top variant at (A) GCKR, (B) FADS1-3, (C) APOA1/C3/A4/A5, and (D) rs6593086.

Figure 4. Phosphatidylcholine associations for the GCKR and FADS1-3 loci

For the 18 phosphatidylcholines (PCs) monitored by our platform, the beta coefficient (left y-axis) and P-value (right y-axis) of association are shown for the top variant at (A) GCKR and (B) FADS1-3.

Figure 5. see also Figures S4 and S5 and Table S4. AGXT2 modulates lipid homeostasis in zebrafish

(A) Zebrafish embryos were injected with 2nL of a 400uM solution of a splice blocking agxt2 morpholino oligonucleotide (MO) or control MO. At 48 hpf, agxt2 MO injection resulted in morphants with both normal phenotype (upper right panel, “AGXT2 I”) and morphants with defective yolk sac extension and pericardial edema (lower left panel, “AGXT2 II”). (B) RT-PCR of agxt2 mRNA for control, AGXT2 I and AGXT2 II morphants at 48 hpf; the 300 nucleotide fragment is the WT agxt2 transcript and the 109 nucleotide fragment is the knocked-down (KD) agxt2 transcript. The relative extent of WT agxt2 expression, normalized to rpl13-α, was estimated from band intensities; data are presented as mean ± SD, *P<0.05 for comparison to control. (C) β-aminoisobutyric acid levels in control, AGXT2 I and AGXT2 II morphants at 48 hpf; data are presented as mean ± SD, *P<0.05 for comparison to control. (D) CE and (E) TAG levels for control, AGXT2 I and AGXT II larvae at 5 dpf; data are presented as mean ± SD, *P<0.05 for comparison to control, #P<0.05 for comparison to AGXT2 I. (F) For TAGs (solid circles) and CEs (hollow circles), plot of each metabolite’s association with rs37370 (AGXT2) in FHS on the x-axis versus the percent difference for each metabolite in AGXT I versus control zebrafish on the y-axis.