Congenital heart diseases often involve maldevelopment of the evolutionarily recent right heart chamber. To gain insight into right heart structure and function, we fine-tuned deep learning models to recognize the right atrium, right ventricle and pulmonary artery, measuring right heart structures in 40,000 individuals from the UK Biobank with magnetic resonance imaging. Genome-wide association studies identified 130 distinct loci associated with at least one right heart measurement, of which 72 were not associated with left heart structures. Loci were found near genes previously linked with congenital heart disease, including NKX2-5, TBX5/TBX3, WNT9B and GATA4. A genome-wide polygenic predictor of right ventricular ejection fraction was associated with incident dilated cardiomyopathy (hazard ratio, 1.33 per standard deviation; P = 7.1 × 10−13) and remained significant after accounting for a left ventricular polygenic score. Harnessing deep learning to perform large-scale cardiac phenotyping, our results yield insights into the genetic determinants of right heart structure and function.
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UK Biobank data are made available to researchers from research institutions with genuine research inquiries, following IRB and UK Biobank approval. GWAS summary statistics are available at the Broad Institute Cardiovascular Disease Knowledge Portal (http://www.broadcvdi.org). Single nucleus RNA sequencing data are publicly available at the Single Cell Portal (https://singlecell.broadinstitute.org/single_cell accession no. SCP498). The dbGAP study accession numbers used for FHS replication were phs000007.v32.p13 for PA diameter measurement and phs000342.v20.p13 for genotyping. BBJ data are available to bona fide researchers for approved research by application to the Japanese Genotype-phenotype Archive. MGB data are available to MGB investigators. All other data are contained within the article and its Supplementary information, or are available upon reasonable request to the corresponding author.
The code used to perform Poisson surface reconstruction from segmentation output is located at https://github.com/broadinstitute/ml4h and is available under an open-source BSD license. The code used to perform permutation testing to assess enrichment of disease-related genes near GWAS loci is located at https://github.com/carbocation/genomisc and is available under an open-source BSD license. The code used to annotate magnetic resonance images is located at https://github.com/carbocation/traceoverlay and is available under an open-source BSD license.
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We thank all participants of UK Biobank, MGB, BBJ and FHS. We acknowledge the staff of BBJ for their assistance. Cardiac magnetic resonance images in Fig. 1 are reproduced by kind permission of UK Biobank. We acknowledge Servier Medical Art (smart.servier.com) for the right heart illustration in Fig. 1, which is licensed under a Creative Commons Attribution 3.0 Unported License (CC-BY-3.0). We also acknowledge M. O’Reilly, from Pattern at the Broad Institute, for modifying the right heart illustration and for creating the remaining graphical illustrations in Fig. 1. This work was supported by grants from the National Institutes of Health K08HL159346 (J.P.P.), R01HL092577 (P.T.E.), K24HL105780 (P.T.E.), R01HL134893 (J.E.H.), R01HL140224 (J.E.H.), K24HL153669 (J.E.H.), 5T32HL007604-35 (V.N.), T32HL007208 (S. Khurshid), R01HL128914 (E.J.B.), R01HL092577 (E.J.B.), R01HL141434 (E.J.B.), U54HL120163 (E.J.B.) and R01HL139731 (S.A.L.). This work was supported by the Fondation Leducq 14CVD01 (P.T.E.). This work was supported by a John S LaDue Memorial Fellowship (J.P.P.) and the Sarnoff Cardiovascular Research Foundation Scholar Award (J.P.P.). This work was supported by the Tailor-Made Medical Treatment Program of the Ministry of Education, Culture, Sports, Science and Technology (BBJ). This work was supported by the Japan Agency for Medical Research via JP17km0305002 (BBJ), JP17km0305001 (BBJ), JP20km0405209 (BBJ, S. Koyama, K.I., I.K.) and JP20ek0109487 (BBJ, S. Koyama, K.I., I.K.). This work was supported by student scholarships from the Dutch Heart Foundation (S.J.) and the Amsterdams Universiteitsfonds (S.J.). This work was supported by grants from the NIH/NHLBI R01HL148050 (P.N.) and R01HL127564 (P.N.), NIH/NHGRI U01HG011719 (P.N.), and Massachusetts General Hospital Fireman Chair (P.N.). This work was supported by American Heart Association grants 18SFRN34110082 (E.J.B.), 18SFRN34250007 (S.A.L.) and a Strategically Focused Research Networks grant (P.T.E.). This work was supported by the Fredman Fellowship for Aortic Disease (M.E.L.) and the Toomey Fund for Aortic Dissection Research (M.E.L.). This work was funded by a collaboration between the Broad Institute and IBM Research.
J.P.P. has served as a consultant for Maze Therapeutics. P.B. is supported by grants from Bayer AG and IBM applying machine learning in cardiovascular disease. S.A.L. receives sponsored research support from Bristol Myers Squibb/Pfizer, Bayer AG, Boehringer Ingelheim and Fitbit, has consulted for Bristol Myers Squibb/Pfizer and Bayer AG and participates in a research collaboration with IBM. K.N. is employed by IBM Research. J.E.H. is supported by a grant from Bayer AG focused on machine learning and cardiovascular disease and a research grant from Gilead Sciences. J.E.H. has received research supplies from EcoNugenics. A.A.P. is employed as a Venture Partner at GV; he is also supported by a grant from Bayer AG to the Broad Institute focused on machine learning for clinical trial design. P.T.E. received sponsored research support from Bayer AG and IBM Research. P.T.E. has also served on advisory boards or consulted for Bayer AG, Quest Diagnostics, MyoKardia and Novartis. P.N. reports investigator-initated grants from Amgen, Apple, AstraZeneca, Boston Scientific, and Novartis, personal fees from Apple, AstraZeneca, Blackstone Life Sciences, Foresite Labs, Novartis, Roche / Genentech, is a co-founder of TenSixteen Bio, is a shareholder of geneXwell and TenSixteen Bio, and spousal employment at Vertex, all unrelated to the present work. The Broad Institute has filed for a patent on an invention from P.T.E., M.E.L. and J.P.P. related to a genetic risk predictor for aortic disease. All remaining authors report no competing interests.
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Pirruccello, J.P., Di Achille, P., Nauffal, V. et al. Genetic analysis of right heart structure and function in 40,000 people. Nat Genet 54, 792–803 (2022). https://doi.org/10.1038/s41588-022-01090-3