Genome wide association studies on three-dimensional aortic geometric indices measured with magnetic resonance imaging

Abstract Introduction To date, three-dimensional properties of the aorta have not been comprehensively quantified in a population level dataset, nor has there been a genome-wide association study (GWAS) to identify significant single nucleotide polymorphisms (SNPs) associated with geometric properties of the aorta. Methods We segmented the thoracic aorta of 48,045 subjects in the UK Biobank using a U-Net convolutional neural network. We then computed geometric measurements (centerline length, arch height, arch width, arch height-width ratio, curvature, and mean, minimum and maximum diameter) across six subsegments of the aorta. Centerline length was allometrically indexed to body height. Using generalized linear models, we performed GWAS on each geometric phenotype adjusted for the following covariates: (1) age, (2) sex, and (3) ten genetic principal components. SNPs with a minor allele frequency < 0.05 were excluded. We performed LD-based clumping with an r2 threshold of 0.001 to identify significant loci and used LDSC to compute the genetic heritability of each geometric phenotype. Results After performing LD clumping, we identified 457 significant(P<5e-8) SNPs across 36 aortic geometric parameters. GWAS-based heritability analyses showed a mean heritability of 13.8 (9.9) % across all aortic geometric parameters, with all intercepts being close to 1, suggesting minimal genomic inflation. Maximum aorta diameter exhibited the highest observed heritability of 34.5 (3.0) %. Allometric centerline length showed a heritability of 13.6 (1.5) %. Similarly, arch height and width showed heritability of 14.6 (1.5) %, and 13.64 (1.5) % respectively. Aortic curvature showed limited heritability at 8.54 (1.2) %, with arch curvature being further reduced to 7.6 (1.20) %. Conclusion To our knowledge, this was the first study that investigated the genetic architecture of aortic centerline length, aortic curvature, and aortic tortuosity. These results suggest that aortic remodeling associated with aging and pathological conditions has important genetic contributions. SNPs associated with aortic geometry may identify therapeutic targets to prevent aortic remodeling, which should be the focus of future work.significant_snpsheritability