Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution

Abstract

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.

Figure 1.. Summary of meta-analysis study design and workflow.

Abbreviations:EUR- European, AFR- African, SAS- South Asian, EAS- East Asian, and HIS- Hispanic/Latino ancestry.* Novel variants include those that are >1MB from a previously published WHRadjBMIGWAS tag SNP.¥ Independent (INDEP) includes variants that are nearby known WHRadjBMI GWAS tag variants, but were determined independent after conditional analysis.

Figure 2.

Minor allele frequency compared to estimated effect. This scatter plot displays the relationship between minor allele frequency (MAF) and the estimated effect (β) for each significant coding variant in our meta-analyses. All novel WHRadjBMI variants are highlighted in orange, and variants identified only in models that assume recessive inheritance are denoted by diamonds and only in sex-specific analyses by triangles. Eighty percent power was calculated based on the total sample size in the Stage 1+2 meta-analysis and P = 2 × 10⁻⁷. Estimated effects are shown in original units (cm/cm) calculated by using effect sizes in standard deviation (SD) units times SD of WHR in the ARIC study (sexes combined = 0.067, men = 0.052, women = 0.080). WHR; waist-to-hip ratio

Figure 3.

Regional association plots for known loci with novel coding signals identified by conditional analyses. Point color reflects r² calculated from the ARIC dataset. In a) there are two independent variants in RSPO3 and KIAA0408, based on results from the stage 1 All Ancestry women (N = 180,131 for RSPO3 and 139,056 for KIAA0408). In b) we have a variant in RREB1 that is independent of the GWAS variant rs1294421, based on results from the stage 1 All Ancestry sex-combined individuals (N = 319,090).

Figure 4.

Heat maps showing DEPICT gene set enrichment results from the stage 1 All Ancestry sex-combined individuals (N = 344,369). For any given square, the color indicates how strongly the corresponding gene (x-axis) is predicted to belong to the reconstituted gene set (y-axis). This value is based on the gene’s z-score for gene set inclusion in DEPICT’s reconstituted gene sets, where red indicates a higher and blue a lower z-score. To visually reduce redundancy and increase clarity, we chose one representative “meta-gene set” for each group of highly correlated gene sets based on affinity propagation clustering (Online Methods, Supplementary Note). Heatmap intensity and DEPICT P-values (Supplementary Data 8–9) correspond to the most significantly enriched gene set within the meta-gene set. Annotations for the genes indicate (1) the minor allele frequency of the significant ExomeChip (EC) variant (blue; if multiple variants, the lowest-frequency variant was kept), (2) whether the variant’s P-value reached array-wide significance (< 2 × 10⁻⁷) or suggestive significance (< 5 × 10–4) (shades of purple), (3) whether the variant was novel, overlapping “relaxed” GWAS signals from Shungin et al. (GWAS P < 5 × 10⁻⁴), or overlapping “stringent” GWAS signals (GWAS P < 5 × 10⁻⁸) (pink), and (4) whether the gene was included in the gene set enrichment analysis or excluded by filters (shades of brown/orange) (Online Methods, Supplementary Note). Annotations for the gene sets indicate if the meta-gene set was found significant (shades of green; FDR < 0.01, < 0.05, or not significant) in the DEPICT analysis of GWAS results from Shungin et al.