Genome‐Wide Association Study of Pericardial Fat Area in 28 161 UK Biobank Participants

BACKGROUND Pericardial adipose tissue (PAT) is the visceral adipose tissue compartment surrounding the heart. Experimental and observational research has suggested that greater PAT deposition might mediate cardiovascular disease, independent of general or subcutaneous adiposity. We characterize the genetic architecture of adiposity‐adjusted PAT and identify causal associations between PAT and adverse cardiac magnetic resonance imaging measures of cardiac structure and function in 28 161 UK Biobank participants. METHODS AND RESULTS The PAT phenotype was extracted from cardiac magnetic resonance images using an automated image analysis tool previously developed and validated in this cohort. A genome‐wide association study was performed with PAT area set as the phenotype, adjusting for age, sex, and other measures of obesity. Functional mapping and Bayesian colocalization were used to understand the biologic role of identified variants. Mendelian randomization analysis was used to examine potential causal links between genetically determined PAT and cardiac magnetic resonance–derived measures of left ventricular structure and function. We discovered 12 genome‐wide significant variants, with 2 independent sentinel variants (rs6428792, P=4.20×10−9 and rs11992444, P=1.30×10−12) at 2 distinct genomic loci, that were mapped to 3 potentially causal genes: T‐box transcription factor 15 (TBX15), tryptophanyl tRNA synthetase 2, mitochondrial (WARS2) and early B‐cell factor‐2 (EBF2) through functional annotation. Bayesian colocalization additionally suggested a role of RP4‐712E4.1. Genetically predicted differences in adiposity‐adjusted PAT were causally associated with adverse left ventricular remodeling. CONCLUSIONS This study provides insights into the genetic architecture determining differential PAT deposition, identifies causal links with left structural and functional parameters, and provides novel data about the pathophysiological importance of adiposity distribution.


Supplemental Material
Supplemental Table Legends: Please see the separate Excel file for the supplemental tables.Table S1 -Candidate SNPs, defined as all genome-wide significant SNPs associated with adjusted PAT (p<5x10 -8 ) and additional highly correlated SNPs identified via 1000G Phase 3 data.
Table S2 -Genomic risk loci of interest, respective lead SNPs and independent significant SNPs in the locus.
Table S3 -Lead SNPs identified from genome-wide SNPs at r 2 <0.1.Genomic locus: the index of genomic risk loci specified in Supp Tab 3. #Ind.Sig.SNPs: Independent significant SNPs which are in LD with the corresponding lead SNPs at r 2 <0.1 Table S4 -Phenotypic associations for lead SNPs and additional closely correlated SNPs (r 2 >0.8) available in GWASCatalog Table S5 -Variant annotation for all candidate SNPs using ANNOVAR.
Table S9 -Results for colocalisation analysis.Table shows results for all genes within 1Mb of a significant GWAS hit, tested with expression quatitative trait loci from GTEx8.PPH4 > 0.8 suggests colocalisation of GWAS risk and gene expression.Abbreviations: nsnpsnumber of snps tested at a locus; PP.H0-4.abfposteriorprobability of hypothesis 0-4 respectively; sum_PPH3_PPH4 -sum of posterior hypotheses 3 and 4; ratio_PPH4_PPH3ratio of posterior hypothesis 4 to posterior hypothesis 3.
Table S10 -Differential gene expression analysis (DEG) comparing expression of candidate genes in each tissue type, versus all other tissue types.
Table S11-Phenome-wide associations for EBF2, TBX15 and WARS2 gene among currently available studies on GWASAtlas.
Table S12 -List of prior associations for loss-of-function in potential causal genes with phenotypes in mouse studies, sources using International Mouse Phenotyping Consortium (IMPC) data.
Table S13 -Genetic correlations between PAT and adiposity traits (trunk fat mass ad percentage, whole body fat mass), cardiovascular risk factors (hypertension, diabetes, obesity), and cardiovascular outcomes (coronary heart disease, coronary event, heart failure, stroke, atrial fibrillation and flutter, and cardiac death).

Table S15
-Genome-wide significant variants without adjustment for fat measures.The table displays beta coefficients with standard errors, and p-value estimates.Allele 1 is the effect allele.

Figure S1 -
Figure S1-Genome-wide significant variants for pericardial fat area after adjusting for sex, age, age 2 , age*sex, 10 genetic principal components (PCs), assessment centre, genotype array, and 2 PCs reflecting BMI, WHR, whole body fat mass, trunk fat mass, body fat percentage.The dashed line represents the genome-wide significance threshold, p<5x10 -8 .

Figure
Figure S2 -Q-Q plot of for association of genetic variants with pericardial fat area after adjusting for sex, age, age 2 , age*sex, 10 genetic principal components (PCs), assessment centre, genotype array, and 2 PCs reflecting BMI, WHR, whole body fat mass, trunk fat mass, body fat percentage.The dashed line represents the null hypothesis.

Figure S3 -
Figure S3 -Manhattan plot of the MAGMA gene-based test.The red line represents genome wide significance.With the inclusion of 19,086 protein coding genes, this was defined at P = 0.05/19086 = 2.62x10 -6

Figure S6 .
Figure S6.Results of sensitivity analysis showing prior and posterior probability distributions as a function of the p12 prior for: A -RP4-712E4.1 in subcutaneous adipose tissue; B -RP4-712E4.1 in tibial artery; and C -CDCA2 in the left ventricle.

Figure S7 .
Figure S7.Results from colocalisation analysis of CDCA2 in the left ventricle.A and C show regional association plots for regional association plots for GWAS and eQTL respectively, with chromosome position as mapped in GRCh38.Comparison of betas (B), and p-values (D) from eQTLs and GWAS are shown, with overlay of Pearson's correlation).Results are driven by a single SNP and are therefore less likely to be a true colocalisation.

Figure S8 -
Figure S8 -Average normalised expression of all mapped genes in 54 tissue types extracted from GTEx v8.Red indicates higher gene expression, normalised per gene.

Figure S9 -
Figure S9 -Phenome-wide associations for TBX15 and WARS2 gene among currently available studies on GWASAtlas.Coloring corresponds to phenotype cluster, summarized in labels on the right.Only associations with a minimum p-value of 0.05 are displayed.

Figure S10 -
Figure S10 -Phenome-wide associations for EBF2 gene among currently available studies on GWASAtlas.Coloring corresponds to phenotype cluster, summarized in labels on the right.Only associations with a minimum p-value of 0.05 are displayed.