Genetic Analysis of Right Heart Structure and Function in 40,000 People

Abstract

The heart evolved hundreds of millions of years ago. During mammalian evolution, the cardiovascular system developed with complete separation between pulmonary and systemic circulations incorporated into a single pump with chambers dedicated to each circulation. A lower pressure right heart chamber supplies deoxygenated blood to the lungs, while a high pressure left heart chamber supplies oxygenated blood to the rest of the body. Due to the complexity of morphogenic cardiac looping and septation required to form these two chambers, congenital heart diseases often involve maldevelopment of the evolutionarily recent right heart chamber. Additionally, some diseases predominantly affect structures of the right heart, including arrhythmogenic right ventricular cardiomyopathy (ARVC) and pulmonary hypertension. To gain insight into right heart structure and function, we fine-tuned deep learning models to recognize the right atrium, the right ventricle, and the pulmonary artery, and then used those models to measure right heart structures in over 40,000 individuals from the UK Biobank with magnetic resonance imaging. We found associations between these measurements and clinical disease including pulmonary hypertension and dilated cardiomyopathy. We then conducted genome-wide association studies, identifying 104 distinct loci associated with at least one right heart measurement. Several of these loci were found near genes previously linked with congenital heart disease, such as NKX2-5, TBX3, WNT9B, and GATA4. We also observed interesting commonalities and differences in association patterns at genetic loci linked with both right and left ventricular measurements. Finally, we found that a polygenic predictor of right ventricular end systolic volume was associated with incident dilated cardiomyopathy (HR 1.28 per standard deviation; P = 2.4E-10), and remained a significant predictor of disease even after accounting for a left ventricular polygenic score. Harnessing deep learning to perform large-scale cardiac phenotyping, our results yield insights into the genetic and clinical determinants of right heart structure and function.

Heart-brain connections: phenotypic and genetic insights from 40,000 cardiac and brain magnetic resonance images

“…The majority of brain structural MRI traits are highly heritable (heritability ranges from 0.6 to 0.8) 29 and the heritability of brain functional connectivity is largely between 0.2 and 0.6 30 . A few recent genome-wide association study (GWAS) have been separately conducted on CMR [31][32][33][34][35][36] and brain MRI traits [37][38][39][40][41][42] . Although MRI is widely used in clinical research and genetic mapping, few studies have used multiorgan MRI to examine heart-brain connections and identify the heart's and brain's shared genetic signatures.…”

“…To evaluate the genetic determinates underlying heart-brain connections, we performed GWAS for the 82 CMR traits to uncover the genetic architecture of heart and aorta. In comparison to existing GWAS of CMR traits [31][32][33][34][35][36] , our study used a much broader group of cardiac and aortic traits, which allowed us to identify the shared genetic components with a wide variety of brain-related complex traits and disorders. For example, Pirruccello, et al 35 mainly focused on 9 measures of the right heart, Aung, et al 31 analyzed 6 LV traits, and Thanaj, et al 36 studied 3 traits of diastolic function.…”

“…In comparison to existing GWAS of CMR traits 31–36 , our study used a much broader group of cardiac and aortic traits, which allowed us to identify the shared genetic components with a wide variety of brain-related complex traits and disorders. For example, Pirruccello, et al 35 mainly focused on 9 measures of the right heart, Aung, et al 31 analyzed 6 LV traits, and Thanaj, et al 36 studied 3 traits of diastolic function. Our study design is summarized in Fig.…”

Druggable proteins influencing cardiac structure and function: implications for heart failure therapies and cancer related cardiotoxicity

“…The phenome-wide scan drug target analysis of CMR prioritized plasma proteins were evaluated using a multiplicity corrected alpha of 1.24×10 −5 . Under the null-hypothesis the pvalues of a group of tests follow a uniform distribution between zero and one 41 . Hence, to additionally explore the potential impact of multiple testing, we performed CMR-trait speci c "overall" null-hypothesis tests, comparing the empirical p-value distribution (using Kolmogorov-Smirnov "KS"-tests) against the uniform distribution expected under the null-hypothesis 41 .…”

Deep Learning of Left Atrial Structure and Function Provides Link to Atrial Fibrillation Risk

“…The short axis stack only occasionally included the lower portion of the chamber, while the three long-axis (i.e., two-, three-, and four-chamber) views provided only single-slice cross-sections of the LA at different orientations. To integrate information from the four incomplete MRI views into a consistent 3D representation of the LA anatomy, we followed a procedure similar to Pirruccello et al (2021) 54 . Briefly, we first co-rotated the MRI views into the same reference system using standard DICOM metadata (i.e., from the Image Position (Patient) [0020,0032] and Image Orientation (Patient) [0020,0037] tags).…”