Abdominal aortic aneurysm (AAA) is a common disease with significant heritability. In this study, we performed a genome-wide association meta-analysis from 14 discovery cohorts and uncovered 144 independent associations, including 97 previously unreported loci. A polygenic risk score derived from meta-analysis was able to explain AAA beyond clinical risk factors. Genes at AAA risk loci indicate involvement of lipid metabolism, vascular development and remodeling, extracellular matrix dysregulation and inflammation as key mechanisms in the pathogenesis of AAA. We further integrated functional data to elucidate expression of genes associated with AAA. These genes also indicate crossover between the development of AAA and other monogenic aortopathies, particularly via TGF-beta signaling pathways. Motivated by the strong evidence for the role of lipid levels in AAA by PheWAS, we identified therapeutic opportunities using Mendelian Randomization and, in pre-clinical studies, we demonstrated that PCSK9 inhibition in mice prevented the development of AAA.
A variety of disorders are known to be related with aortic geometry, among them abdominal aortic aneurysm (AAA). This work aims to present the main determinants of abdominal aortic diameter in a new cohort of families at high risk of AAA. The Triple-A Genomic Analysis (TAGA) study comprises 407 individuals related in 12 families. Each family was collected through a proband with AAA. We calculated heritability and genetic correlations between abdominal aortic diameter and clinical parameters. A genome-wide linkage scan was performed based on 4.6 million variants. A predictive model was calculated with conditional forest. Heritability of the abdominal aortic diameter was 34%. Old age, male sex, higher height, weight, creatinine levels in serum, and better lung capacity were the best predictors of aortic diameter. Linkage analyses suggested the implication of Epidermal Growth Factor Receptor (EGFR) and Betacellulin (BTC) genes with aortic diameter. This is the first study to evaluate genetic components of variation of the aortic diameter in a population of AAA high-risk individuals. These results reveal EGFR, a gene that had been previously implicated in AAA, as a determinant of aortic diameter variation in healthy genetically enriched individuals, and might indicate that a common genetic background could determine the diameter of the aorta and future risk of AAA.
Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI's Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10% higher in African populations. Three (SERPINA1, ZFP36L2, and TLR10) signals contain predicted deleterious missense variants. Two loci, SOCS3 and HPN, each harbor two conditionally distinct, non-coding variants. The gene region encoding the protein chain subunits (FGG;FGB;FGA), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common (MAF=0.180) in African reference panels but extremely rare (MAF=0.008) in Europeans. Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation.
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