Genomic insights in ascending aortic size and distensibility
Benjamins, Jan Walter; Yeung, Ming Wai; van de Vegte, Yordi J; Said, M Abdullah; van der Linden, Thijs; Ties, Daan; Juarez-Orozco, Luis E; Verweij, Niek; van der Harst, Pim
(2022) EBioMedicine, volume 75, pp. 1 - 18
(Article)
Abstract
BACKGROUND: Alterations in the anatomic and biomechanical properties of the ascending aorta (AAo) can give rise to various vascular pathologies. The aim of the current study is to gain additional insights in the biology of the AAo size and function. METHODS: We developed an AI based analysis pipeline for the
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segmentation of the AAo, and the extraction of AAO parameters. We then performed genome-wide association studies of AAo maximum area, AAo minimum area and AAo distensibility in up to 37,910 individuals from the UK Biobank. Variants that were significantly associated with AAo phenotypes were used as instrumental variables in Mendelian randomization analyses to investigate potential causal relationships with coronary artery disease, myocardial infarction, stroke and aneurysms. FINDINGS: Genome-wide association studies revealed a total of 107 SNPs in 78 loci. We annotated 101 candidate genes involved in various biological processes, including connective tissue development (THSD4 and COL6A3). Mendelian randomization analyses showed a causal association with aneurysm development, but not with other vascular diseases. INTERPRETATION: We identified 78 loci that provide insights into mechanisms underlying AAo size and function in the general population and provide genetic evidence for their role in aortic aneurysm development.
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Keywords: Artificial intelligence, Ascending aorta distensibility, Ascending aorta size, Cardiovascular disease, Genome-wide association study, Mendelian randomization study, General Biochemistry,Genetics and Molecular Biology, Journal Article
ISSN: 2352-3964
Publisher: Elsevier BV
Note: Funding Information: The work of J.W. Benjamins and M.W. Yeung was supported by the Research Project CVON-AI (2018B017), financed by the PPP Allowance made available by Top Sector Life Sciences & Health to the Dutch Heart Foundation to stimulate public-private partnerships. The work of N.Verweij was supported by NWO VENI grant 016.186.125. Funding Information: This research has been conducted using the UK Biobank Resource under application number 12010. We thank Ruben N. Eppinga, MD, PhD, Tom Hendriks, MD, PhD. Yldau van der Ende, MD, PhD, Yanick Hagemeijer, MSc and Hilde Groot, MD, PhD (University of Groningen, University Medical Center Groningen, and Department of Cardiology), for their contributions to the extraction and processing of data in the UK Biobank. None of the mentioned contributors received compensation, except for their employment at the University Medical Center Groningen. We thank the Center for Information Technology of the University of Groningen for their support and for providing access to the Peregrine high-performance computing cluster. In addition, we thank the “Medische en Informatie Technologie Systeembeheer” of the University Medical Center of Groningen for their support and maintenance of our own computing cluster. Publisher Copyright: © 2021 The Author(s)
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