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. 2023 Mar 21;147(12):942-955.
doi: 10.1161/CIRCULATIONAHA.122.061451. Epub 2023 Feb 20.

Multiancestry Genome-Wide Association Study of Aortic Stenosis Identifies Multiple Novel Loci in the Million Veteran Program

Aeron M Small #  1   2 , Gina M Peloso #  3   4 , Jason Linefsky  5   6 , Jayashri Aragam  7 , Ashley Galloway  3 , Vidisha Tanukonda  5 , Lu-Chen Wang  8   9 , Zhi Yu  8   9   10 , Margaret Sunitha Selvaraj  8   10 , Eric H Farber-Eger  11 , Michael T Baker  12 , Shefali Setia-Verma  13 , Simon S K Lee  14 , Michael Preuss  14 , Marylyn D Ritchie  13 , Scott M Damrauer  15   16 , Daniel J Rader  13 , Quinn S Wells  12   17   18 , Ruth Loos  14   19   20 , Steven A Lubitz  8 , George Thanassoulis  21 , Kelly Cho  3 , Peter W F Wilson  5   6   22 ; VA Million Veteran Program; Pradeep Natarajan #  8   23   24   9 , Christopher J O'Donnell #  1   7
Affiliations

Multiancestry Genome-Wide Association Study of Aortic Stenosis Identifies Multiple Novel Loci in the Million Veteran Program

Aeron M Small et al. Circulation. .

Abstract

Background: Calcific aortic stenosis (CAS) is the most common valvular heart disease in older adults and has no effective preventive therapies. Genome-wide association studies (GWAS) can identify genes influencing disease and may help prioritize therapeutic targets for CAS.

Methods: We performed a GWAS and gene association study of 14 451 patients with CAS and 398 544 controls in the Million Veteran Program. Replication was performed in the Million Veteran Program, Penn Medicine Biobank, Mass General Brigham Biobank, BioVU, and BioMe, totaling 12 889 cases and 348 094 controls. Causal genes were prioritized from genome-wide significant variants using polygenic priority score gene localization, expression quantitative trait locus colocalization, and nearest gene methods. CAS genetic architecture was compared with that of atherosclerotic cardiovascular disease. Causal inference for cardiometabolic biomarkers in CAS was performed using Mendelian randomization and genome-wide significant loci were characterized further through phenome-wide association study.

Results: We identified 23 genome-wide significant lead variants in our GWAS representing 17 unique genomic regions. Of the 23 lead variants, 14 were significant in replication, representing 11 unique genomic regions. Five replicated genomic regions were previously known risk loci for CAS (PALMD, TEX41, IL6, LPA, FADS) and 6 were novel (CEP85L, FTO, SLMAP, CELSR2, MECOM, CDAN1). Two novel lead variants were associated in non-White individuals (P<0.05): rs12740374 (CELSR2) in Black and Hispanic individuals and rs1522387 (SLMAP) in Black individuals. Of the 14 replicated lead variants, only 2 (rs10455872 [LPA], rs12740374 [CELSR2]) were also significant in atherosclerotic cardiovascular disease GWAS. In Mendelian randomization, lipoprotein(a) and low-density lipoprotein cholesterol were both associated with CAS, but the association between low-density lipoprotein cholesterol and CAS was attenuated when adjusting for lipoprotein(a). Phenome-wide association study highlighted varying degrees of pleiotropy, including between CAS and obesity at the FTO locus. However, the FTO locus remained associated with CAS after adjusting for body mass index and maintained a significant independent effect on CAS in mediation analysis.

Conclusions: We performed a multiancestry GWAS in CAS and identified 6 novel genomic regions in the disease. Secondary analyses highlighted the roles of lipid metabolism, inflammation, cellular senescence, and adiposity in the pathobiology of CAS and clarified the shared and differential genetic architectures of CAS with atherosclerotic cardiovascular diseases.

Keywords: aortic valve stenosis; genome-wide association study; genomics; lipoprotein(a).

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Conflict of interest statement

Conflict of Interest Disclosures

SMD receives research support from RenalytixAI and personal consulting fees from Calico Labs, outside the scope of the current research. PN reports personal consulting fees from Amgen, Apple, AstraZeneca, Blackstone Life Sciences, Foresite Labs, Genentech, Novartis, and TenSixteen Bio, investigator-initiated grants from Apple, AstraZeneca, and Boston Scientific, is a co-founder of TenSixteen Bio, equity in TenSixteen Bio, geneXwell, and Vertex, and spousal employment at Vertex, all unrelated to the present work. CJO is an employee of Novartis Institutes for Biomedical Research. LCW receives research support from IBM to the Broad Institute.

Figures

Figure 1:
Figure 1:. Hudson Plot of Multi-Ancestry GWAS findings (top) and MAGMA Gene Association Analysis (bottom)
Hudson plot with multi-ancestry GWAS Manhattan plot (top) with genome-wide significant variants (p-value < 5×10−08) labeled in red and a gene analysis of multi-ancestry GWAS data (bottom) using Multi-Marker Analysis of Genomic Annotation (MAGMA) with gene wide significant results (19,021 protein coding genes, p-value < 2.6 × 10−6) labeled in red.
Figure 2:
Figure 2:. Heatmap of Select Phenome-Wide Association Results in White Individuals from the UK Biobank and Replication Million Veteran Program Cohorts
Heatmap of phenome-wide association results for both binary clinical traits and quantitative biomarkers. Binary clinical trait Phenome-Wide Association Study (PheWAS) was performed using the Denny PheWAS method and represents inverse-variance weighted meta-analysis of results from the Million Veteran Program and UK Biobank. Quantitative traits were rank-normal transformed prior to association analysis in the UK Biobank. The heatmap is scaled using Z-scores for all analyses and organized using hierarchical clustering via the Ward method.
Figure 3:
Figure 3:. Mendelian Randomization of Cardiometabolic Biomarkers in the UK Biobank and Risk of Aortic Stenosis
Forest plot of Mendelian randomization experiments for select exposures using genetic instruments built in the UK Biobank against an outcome of aortic stenosis applied in the Million Veteran Program.
See this image and copyright information in PMC

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