Genome-wide association study of CMR image-based aortic stiffness in 45,789 individuals identifies loci linked with cardiovascular diseases

Abstract Background The use of artificial intelligence on large-scale cardiac magnetic resonance (CMR) imaging data has enabled detailed characterisation of cardiac shape and function for use in genome-wide association studies (GWAS), leading to improved understanding of genetic aetiology of cardiovascular diseases (CVDs). Aortic stiffness is associated with increased risk of cardiovascular events in observational studies. Here, we present a novel CMR-based pressure-independent measure of aortic stiffness, identify genetic associations and explore links with CVDs. Purpose Identify genetic contributions to pressure-independent aortic stiffness and links to CVDs using large-scale GWAS analysis on the UK Biobank cohort. Methods A pre-trained neural network was used to segment CMR images of participants in the UK Biobank to quantify ascending aorta diameter, which together with contemporaneous systolic and diastolic blood pressure measurements (SBP, DBP, respectively) were used to calculate a pressure-independent measure of aortic stiffness (β0). The measurement assumes an exponential relationship between pressure and aortic diameter. We then performed a GWAS on β0 in 45,789 participants of European ancestry without CVDs. A multi-trait-based conditional & joint analysis (mtCOJO) was performed to estimate genetic effects independent of SBP, DBP and aortic area. We mapped the independent lead variants associated with aortic stiffness at P < 5x10-8 to nearest gene, and characterised shared genetic association across CVDs using Open Targets Platform database. Results The GWAS identified 17 independent lead variants, including 6 that remained significant in the conditional analysis. Four of these lead variants, not previously reported in GWAS of other aortic traits, were located near CTD-2203A3.1, MCF2L, CFDP1 and CDH13 genes (red annotations in the Figure). MCF2L, CFDP1 and CDH13 have been associated with coronary artery disease, and CFDP1 with myocardial infarction and coronary atherosclerosis in previous studies. Conclusion A GWAS of CMR-derived aortic stiffness identified 4 loci distinct from other aortic traits that also associate with other CVDs, suggesting genetic links between aortic stiffness and CVDs. Further analyses are required to explore biological mechanisms underlying these genetic associations.Aortic Stiffness Manhattan Plot

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Journal
European Heart Journal
Published
2024-10-01
DOI
https://doi.org/10.1093/eurheartj/ehae666.3830
Primary Topic
Genetic Associations and Epidemiology
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article
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article

Genome-wide association study of CMR image-based aortic stiffness in 45,789 individuals identifies loci linked with cardiovascular diseases

Albert Henry, Bryan Williams, Anders Mälarstig, Alun David Hughes et al.
European Heart Journal
Genetic Associations and Epidemiology
article

Genome-wide association study of CMR image-based aortic stiffness in 45,789 individuals identifies loci linked with cardiovascular diseases

Albert Henry, Bryan Williams, Anders Mälarstig, Alun David Hughes, Rhodri Davies, Aroon D. Hingorani, Nikhil Paliwal, Chris Finan, R Thomas Lumbers
article en

Abstract

Abstract Background The use of artificial intelligence on large-scale cardiac magnetic resonance (CMR) imaging data has enabled detailed characterisation of cardiac shape and function for use in genome-wide association studies (GWAS), leading to improved understanding of genetic aetiology of cardiovascular diseases (CVDs). Aortic stiffness is associated with increased risk of cardiovascular events in observational studies. Here, we present a novel CMR-based pressure-independent measure of aortic stiffness, identify genetic associations and explore links with CVDs. Purpose Identify genetic contributions to pressure-independent aortic stiffness and links to CVDs using large-scale GWAS analysis on the UK Biobank cohort. Methods A pre-trained neural network was used to segment CMR images of participants in the UK Biobank to quantify ascending aorta diameter, which together with contemporaneous systolic and diastolic blood pressure measurements (SBP, DBP, respectively) were used to calculate a pressure-independent measure of aortic stiffness (β0). The measurement assumes an exponential relationship between pressure and aortic diameter. We then performed a GWAS on β0 in 45,789 participants of European ancestry without CVDs. A multi-trait-based conditional & joint analysis (mtCOJO) was performed to estimate genetic effects independent of SBP, DBP and aortic area. We mapped the independent lead variants associated with aortic stiffness at P < 5x10-8 to nearest gene, and characterised shared genetic association across CVDs using Open Targets Platform database. Results The GWAS identified 17 independent lead variants, including 6 that remained significant in the conditional analysis. Four of these lead variants, not previously reported in GWAS of other aortic traits, were located near CTD-2203A3.1, MCF2L, CFDP1 and CDH13 genes (red annotations in the Figure). MCF2L, CFDP1 and CDH13 have been associated with coronary artery disease, and CFDP1 with myocardial infarction and coronary atherosclerosis in previous studies. Conclusion A GWAS of CMR-derived aortic stiffness identified 4 loci distinct from other aortic traits that also associate with other CVDs, suggesting genetic links between aortic stiffness and CVDs. Further analyses are required to explore biological mechanisms underlying these genetic associations.Aortic Stiffness Manhattan Plot

European Heart JournalVol. 45(Supplement_1)
Karolinska Institutet (SE), University College London (GB)
Good health and well-being
Openalex Percentile: Top 78%
Genetic Associations and Epidemiology
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