bioRxiv Science⌕ Search

Biology subjects

Nauffal, V.

Publications and source records attributed to Nauffal, V..

2 recordsLinked to original sources

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

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.

genetics↗

Rare Genetic Variation Underlying Human Diseases and Traits: Results from 200,000 Individuals in the UK Biobank

BackgroundMany human diseases are known to have a genetic contribution. While genome-wide studies have identified many disease-associated loci, it remains challenging to elucidate causal genes. In contrast, exome sequencing provides an opportunity to identify new disease genes and large-effect variants of clinical relevance. We therefore sought to determine the contribution of rare genetic variation in a curated set of human diseases and traits using a unique resource of 200,000 individuals with exome sequencing data from the UK Biobank. Methods and ResultsWe included 199,832 participants with a mean age of 68 at follow-up. Exome-wide gene-based tests were performed for 64 diseases and 23 quantitative traits using a mixed-effects model, testing rare loss-of-function and damaging missense variants. We identified 51 known and 23 novel associations with 26 diseases and traits at a false-discovery-rate of 1%. There was a striking risk associated with many Mendelian disease genes including: MYPBC3 with over a 100-fold increased odds of hypertrophic cardiomyopathy, PKD1 with a greater than 25-fold increased odds of chronic kidney disease, and BRCA2, BRCA1, ATM and PALB2 with 3 to 10-fold increased odds of breast cancer. Notable novel findings included an association between GIGYF1 and type 2 diabetes (OR 5.6, P=5.35x10-8), elevated blood glucose, and lower insulin-like-growth-factor-1 levels. Rare variants in CCAR2 were also associated with diabetes risk (OR 13, P=8.5x10-8), while COL9A3 was associated with cataract (OR 3.4, P=6.7x10-8). Notable associations for blood lipids and hypercholesterolemia included NR1H3, RRBP1, GIGYF1, SCGN, APH1A, PDE3B and ANGPTL8. A number of novel genes were associated with height, including DTL, PIEZO1, SCUBE3, PAPPA and ADAMTS6, while BSN was associated with body-mass-index. We further assessed putatively pathogenic variants in known Mendelian cardiovascular disease genes and found that between 1.3 and 2.3% of the population carried likely pathogenic variants in known cardiomyopathy, arrhythmia or hypercholesterolemia genes. ConclusionsLarge-scale population sequencing identifies known and novel genes harboring high-impact variation for human traits and diseases. A number of novel findings, including GIGYF1,represent interesting potential therapeutic targets. Exome sequencing at scale can identify a meaningful proportion of the population that carries a pathogenic variant underlying cardiovascular disease.

genetics↗