Genome-wide association analysis reveals insights into the genetic architecture of right ventricular structure and function.
Nay AungJose D VargasChaojie YangKenneth FungMihir M SanghviStefan K PiechnikStefan NeubauerAni ManichaikulJerome I RotterKent D TaylorJoao Augusto Costa LimaDavid A BluemkeSteven M KawutSteffen Erhard PetersenPatricia B MunroePublished in: Nature genetics (2022)
Right ventricular (RV) structure and function influence the morbidity and mortality from coronary artery disease (CAD), dilated cardiomyopathy (DCM), pulmonary hypertension and heart failure. Little is known about the genetic basis of RV measurements. Here we perform genome-wide association analyses of four clinically relevant RV phenotypes (RV end-diastolic volume, RV end-systolic volume, RV stroke volume, RV ejection fraction) from cardiovascular magnetic resonance images, using a state-of-the-art deep learning algorithm in 29,506 UK Biobank participants. We identify 25 unique loci associated with at least one RV phenotype at P < 2.27 ×10 -8 , 17 of which are validated in a combined meta-analysis (n = 41,830). Several candidate genes overlap with Mendelian cardiomyopathy genes and are involved in cardiac muscle contraction and cellular adhesion. The RV polygenic risk scores (PRSs) are associated with DCM and CAD. The findings substantially advance our understanding of the genetic underpinning of RV measurements.
Keyphrases
- mycobacterium tuberculosis
- coronary artery disease
- heart failure
- genome wide association
- deep learning
- ejection fraction
- magnetic resonance
- genome wide
- left ventricular
- systematic review
- pulmonary hypertension
- blood pressure
- machine learning
- percutaneous coronary intervention
- magnetic resonance imaging
- type diabetes
- convolutional neural network
- cardiovascular disease
- escherichia coli
- aortic stenosis
- artificial intelligence
- coronary artery
- brain injury
- transcatheter aortic valve replacement
- transcription factor
- meta analyses
- candida albicans