Enlargement of the aorta is an important risk factor for aortic aneurysm and dissection, a leading cause of morbidity in the developed world. Here we performed automated extraction of ascending aortic diameter from cardiac magnetic resonance images of 36,021 individuals from the UK Biobank, followed by genome-wide association. We identified lead variants across 41 loci, including genes related to cardiovascular development (HAND2, TBX20) and Mendelian forms of thoracic aortic disease (ELN, FBN1). A polygenic score significantly predicted prevalent risk of thoracic aortic aneurysm and the need for surgical intervention for patients with thoracic aneurysm across multiple ancestries within the UK Biobank, FinnGen, the Penn Medicine Biobank and the Million Veterans Program (MVP). Additionally, we highlight the primary causal role of blood pressure in reducing aortic dilation using Mendelian randomization. Overall, our findings provide a roadmap for using genetic determinants of human anatomy to understand cardiovascular development while improving prediction of diseases of the thoracic aorta.
This is a preview of subscription content, access via your institution
Open Access articles citing this article.
Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure
Nature Communications Open Access 14 November 2022
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Rent or buy this article
Prices vary by article type
Prices may be subject to local taxes which are calculated during checkout
All imaging and genetic data of the UK Biobank are available upon request to the UK Biobank organization. Summary statistics of ancestry-specific GWAS as well as multi-ancestry meta-analysis are available for download from the GWAS catalog under accession number GCP000259. Similarly, the PGS constructed in the current paper is available for download from the PGS catalog under accession number PGS0002236.
Stojanovska, J., Cascade, P. N., Chong, S., Quint, L. E. & Sundaram, B. Embryology and imaging review of aortic arch anomalies. J. Thorac. Imaging 27, 73–84 (2012).
Lopez, L. et al. Relationship of echocardiographic Z scores adjusted for body surface area to age, sex, race, and ethnicity: the Pediatric Heart Network Normal Echocardiogram Database. Circ. Cardiovasc. Imaging 10, e006979 (2017).
Lemaire, S. A. & Russell, L. Epidemiology of thoracic aortic dissection. Nat. Rev. Cardiol. 8, 103–113 (2011).
Aday, A. W., Kreykes, S. E. & Fanola, C. L. Vascular genetics: presentations, testing, and prognostics. Curr. Treat. Options Cardiovasc. Med. 20, 103 (2018).
Saeyeldin, A. A. et al. Thoracic aortic aneurysm: unlocking the “silent killer” secrets. Gen. Thorac. Cardiovasc. Surg. 67, 1–11 (2019).
Raunsø, J. et al. Familial clustering of aortic size, aneurysms, and dissections in the community. Circulation 142, 920–928 (2020).
Wheeler, A. P., Yang, Z., Cordes, T. M., Markham, L. W. & Landis, B. J. Characterization of the rate of aortic dilation in young patients with thoracic aortic aneurysm. Pediatr. Cardiol. 42, 148–157 (2021).
Wild, P. S. et al. Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function. J. Clin. Invest. 127, 1798–1812 (2017).
McBride, K. L. et al. Inheritance analysis of congenital left ventricular outflow tract obstruction malformations: segregation, multiplex relative risk, and heritability. Am. J. Med. Genet. A 134A, 180–186 (2005).
Pinard, A., Jones, G. T. & Milewicz, D. M. Genetics of thoracic and abdominal aortic diseases: aneurysms, dissections, and ruptures. Circ. Res. 124, 588–606 (2019).
Renard, M. et al. Clinical validity of genes for heritable thoracic aortic aneurysm and dissection. J. Am. Coll. Cardiol. 72, 605–615 (2018).
Tong, J. K. T. & Rabkin, S. W. The relationship between hypertension and thoracic aortic aneurysm of degenerative or atherosclerotic origin: a systematic review. Austin Hypertens. 1, 1004 (2016).
Xia, M., Luo, W., Jin, H. & Yang, Z. HAND2-mediated epithelial maintenance and integrity in cardiac outflow tract morphogenesis. Development 146, dev177477 (2019).
Strehle, E. M. et al. Genotype–phenotype analysis of 4q deletion syndrome: proposal of a critical region. Am. J. Med. Genet. A 158A, 2139–2151 (2012).
Song, K. et al. Heart repair by reprogramming non-myocytes with cardiac transcription factors. Nature 485, 599–604 (2012).
van der Harst, P. & Verweij, N. Identification of 64 novel genetic loci provides an expanded view on the genetic architecture of coronary artery disease. Circ. Res. 122, 433–443 (2018).
Klarin, D. et al. Genetic architecture of abdominal aortic aneurysm in the Million Veteran Program. Circulation 142, 1633–1646 (2020).
Ward, L. D. & Kellis, M. HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants. Nucleic Acids Res. 40, D930–D934 (2012).
Watanabe, K., Taskesen, E., Van Bochoven, A. & Posthuma, D. Functional mapping and annotation of genetic associations with FUMA. Nat. Commun. 8, 1826 (2017).
Watanabe, K., Umićević Mirkov, M., de Leeuw, C. A., van den Heuvel, M. P. & Posthuma, D. Genetic mapping of cell type specificity for complex traits. Nat. Commun. 10, 3222 (2019).
McInnes, G. et al. Global Biobank Engine: enabling genotype–phenotype browsing for biobank summary statistics. Bioinformatics 35, 2495–2497 (2019).
Elefteriades, J. A. et al. Indications and imaging for aortic surgery: size and other matters. J. Thorac. Cardiovasc. Surg. 149, S10–S13 (2015).
Paruchuri, V. et al. Aortic size distribution in the general population: explaining the size paradox in aortic dissection. Cardiology 131, 265–272 (2015).
Davis, A. et al. Diameters of the normal thoracic aorta measured by cardiovascular magnetic resonance imaging; correlation with gender, body surface area and body mass index. J. Cardiovasc. Magn. Reson. 15, E77 (2013).
Pearce, W. H. et al. Aortic diameter as a function of age, gender, and body surface area. Surgery 114, 691–697 (1993).
Curran, M. E. et al. The elastin gene is disrupted by a translocation associated with supravalvular aortic stenosis. Cell 73, 159–168 (1993).
Angelov, S. N., Zhu, J., Hu, J. H. & Dichek, D. A. What’s the skinny on elastin deficiency and supravalvular aortic stenosis? Arterioscler. Thromb. Vasc. Biol. 37, 740–742 (2017).
Merla, G., Brunetti-Pierri, N., Piccolo, P., Micale, L. & Loviglio, M. N. Supravalvular aortic stenosis. Circ. Cardiovasc. Genet. 5, 692–696 (2012).
Earhart, B. A. et al. Phenotype of 7q11.23 duplication: a family clinical series. Am. J. Med. Genet. A 173A, 114–119 (2017).
Morris, C. A. et al. 7q11.23 duplication syndrome: physical characteristics and natural history. Am. J. Med. Genet. A 167A, 2916–2935 (2015).
Kirk, E. P. et al. Mutations in cardiac T-box factor gene TBX20 are associated with diverse cardiac pathologies, including defects of septation and valvulogenesis and cardiomyopathy. Am. J. Hum. Genet. 81, 280–291 (2007).
Atik, T. et al. Novel MASP1 mutations are associated with an expanded phenotype in 3MC1 syndrome. Orphanet J. Rare Dis. 10, 128 (2015).
Sirmaci, A. et al. MASP1 mutations in patients with facial, umbilical, coccygeal, and auditory findings of Carnevale, Malpuech, OSA, and Michels syndromes. Am. J. Hum. Genet. 87, 679–686 (2010).
Holler, K. L. et al. Targeted deletion of Hand2 in cardiac neural crest-derived cells influences cardiac gene expression and outflow tract development. Dev. Biol. 341, 291–304 (2010).
Bradley, D. T. et al. A variant in LDLR is associated with abdominal aortic aneurysm. Circ. Cardiovasc. Genet. 6, 498–504 (2013).
Franceschini, N. et al. GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes. Nat. Commun. 9, 5141 (2018).
Giri, A. et al. Trans-ethnic association study of blood pressure determinants in over 750,000 individuals. Nat. Genet. 51, 51–62 (2019).
Yang, X. L. et al. Three novel loci for infant head circumference identified by a joint association analysis. Front. Genet. 10, 947 (2019).
Dewey, F. E., Rosenthal, D., Murphy, D. J., Froelicher, V. F. & Ashley, E. A. Does size matter? Clinical applications of scaling cardiac size and function for body size. Circulation 117, 2279–2287 (2008).
Guo, J. et al. Global genetic differentiation of complex traits shaped by natural selection in humans. Nat. Commun. 9, 1865 (2018).
Goldfinger, J. Z. et al. Thoracic aortic aneurysm and dissection. J. Am. Coll. Cardiol. 64, 1725–1739 (2014).
Milewicz, D. M., Prakash, S. K. & Ramirez, F. Therapeutics targeting drivers of thoracic aortic aneurysms and acute aortic dissections: insights from predisposing genes and mouse models. Annu. Rev. Med. 68, 51–67 (2017).
Muiño-Mosquera, L. et al. Efficacy of losartan as add-on therapy to prevent aortic growth and ventricular dysfunction in patients with Marfan syndrome: a randomized, double-blind clinical trial. Acta Cardiol. 72, 616–624 (2017).
Taylor, A. P. et al. Statin use and aneurysm risk in patients with bicuspid aortic valve disease. Clin. Cardiol. 39, 41–47 (2016).
Toganel, R., Benedek, T. & Chitu, M. Response to statin use and aneurysm risk in patients with bicuspid aortic valve disease. Clin. Cardiol. 39, 307–308 (2016).
Duncan, L. et al. Analysis of polygenic risk score usage and performance in diverse human populations. Nat. Commun. 10, 3328 (2019).
Khera, A. V. et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat. Genet. 50, 1219–1224 (2018).
Inouye, M. et al. Genomic risk prediction of coronary artery disease in 480,000 adults. J. Am. Coll. Cardiol. 72, 1883–1893 (2018).
Aguirre, M., Rivas, M. A. & Priest, J. Phenome-wide burden of copy-number variation in the UK Biobank. Am. J. Hum. Genet. 105, 373–383 (2019).
Collins, R. What makes UK Biobank special? Lancet 379, 1173–1174 (2012).
Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015).
Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 562, 203–209 (2018).
Petersen, S. E. et al. UK Biobank’s cardiovascular magnetic resonance protocol. J. Cardiovasc. Magn. Reson. 18, 8 (2016).
Fang, H. et al. Harmonizing genetic ancestry and self-identified race/ethnicity in genome-wide association studies. Am. J. Hum. Genet. 105, 763–772 (2019).
Verma, S. S. et al. Imputation and quality control steps for combining multiple genome-wide datasets. Front. Genet. 5, 370 (2014).
Das, S. et al. Next-generation genotype imputation service and methods. Nat. Genet. 48, 1284–1287 (2016).
Biasiolli, L. et al. Automated localization and quality control of the aorta in cine CMR can significantly accelerate processing of the UK Biobank population data. PLoS ONE 14, e0212272 (2019).
Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).
Shi, H., Kichaev, G. & Pasaniuc, B. Contrasting the genetic architecture of 30 complex traits from summary association data. Am. J. Hum. Genet. 99, 139–153 (2016).
Warren, H. R. et al. Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk. Nat. Genet. 49, 403–415 (2017).
de Leeuw, C. A., Mooij, J. M., Heskes, T. & Posthuma, D. MAGMA: generalized gene-set analysis of GWAS data. PLoS Comput. Biol. 11, e1004219 (2015).
Barbeira, A. N. et al. Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics. Nat. Commun. 9, 1825 (2018).
Wu, P. et al. Mappings ICD-10 and ICD-10-CM codes to phecodes: workflow development and initial evaluation. JMIR Med. Inform. 7, e14325 (2018).
Willer, C. J. et al. Discovery and refinement of loci associated with lipid levels. Nat. Genet. 45, 1274–1285 (2013).
Burgess, S., Butterworth, A. & Thompson, S. G. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet. Epidemiol. 37, 658–665 (2013).
Burgess, S., Scott, R. A., Timpson, N. J., Smith, G. D. & Thompson, S. G. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. Eur. J. Epidemiol. 30, 543–552 (2015).
Verbanck, M., Chen, C. Y., Neale, B. & Do, R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat. Genet. 50, 693–698 (2018).
Funding came from the Department of Veterans Affairs Office of Research and Development, MVP grant 1I01BX00264 and the NIH (R00HL130523) to J.R.P.; and a Stanford MCHRI Seed Grant to C.T. The FinnGen project is funded by two grants from Business Finland (HUS 4685/31/2016 and UH 4386/31/2016) and 11 industry partners (AbbVie, AstraZeneca, Biogen, Celgene, Celgene International II Sàrl, Genentech, Merck Sharp & Dohme, Pfizer, GlaxoSmithKline, Sanofi, Maze Therapeutics, Janssen Biotech). We acknowledge the following biobanks for collecting the FinnGen project samples: Auria Biobank (https://www.auria.fi/biopankki/), THL Biobank (https://www.thl.fi/biobank), Helsinki Biobank (https://www.helsinginbiopankki.fi/), the Biobank Borealis of Northern Finland (https://www.ppshp.fi/Tutkimus-ja-opetus/Biopankki/Pages/Biobank-Borealis-briefly-in-English.aspx), Finnish Clinical Biobank Tampere (https://www.tays.fi/en-US/Research_and_development/Finnish_Clinical_Biobank_Tampere), the Biobank of Eastern Finland (https://ita-suomenbiopankki.fi/en/), Central Finland Biobank (https://www.ksshp.fi/fi-FI/Potilaalle/Biopankki), the Finnish Red Cross Blood Service Biobank (https://www.veripalvelu.fi/verenluovutus/biopankkitoiminta) and Terveystalo Biobank (https://www.terveystalo.com/fi/Yritystietoa/Terveystalo-Biopankki/Biopankki/). All Finnish biobanks are members of BBMRI.fi infrastructure (https://www.bbmri.fi). We thank D. Zanetti, M. Aguirre and M. Yu for technical assistance with aspects of the analysis and R. Kajanne for assistance with administrative aspects of the FinnGen resource.
At the time of resubmission, J.R.P. is an employee of Tenaya Therapeutics, which does not have active clinical or preclinical development programs related to the data presented here. The remaining authors declare no competing interests.
Peer review information
Nature Genetics thanks Matthew Bown and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Tcheandjieu, C., Xiao, K., Tejeda, H. et al. High heritability of ascending aortic diameter and trans-ancestry prediction of thoracic aortic disease. Nat Genet 54, 772–782 (2022). https://doi.org/10.1038/s41588-022-01070-7
This article is cited by
Nature Reviews Cardiology (2023)
Nature Cardiovascular Research (2022)
Nature Reviews Cardiology (2022)
Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure
Nature Communications (2022)