👤 Rohan Nadkarni

Circulating lipoprotein(a) [Lp(a)] levels are highly heritable and linked to atherosclerotic cardiovascular disease, yet clinical measurement rates remain low (<1%) in the United States. The high heritability of Lp(a) across populations makes genetic prediction an attractive approach for closing this testing gap, but existing polygenic scores transfer poorly across populations. Haplotype-based prediction models, which use standard genome-wide genotype data to capture common-, rare-, and structural-variation at the LPA locus, could bridge this gap, enabling opportunistic identification of individuals with elevated Lp(a) levels across diverse populations within existing large, genotyped cohorts. This study sought to develop and validate a haplotype-based prediction model using genome-wide genotype data to identify individuals with elevated Lp(a) levels across diverse populations. We developed an Among PMBB (n = 1856), MGBB (n = 1401), and BioMe (n = 1686) participants with available genotype and Lp(a) measurements, average age was 60 years, and 51% were female. Overall r A haplotype-based genetic model effectively identified individuals with elevated Lp(a) levels across diverse populations, with potential utility for opportunistic screening among cohorts where genotype data is available, but Lp(a) testing rates are low. Show less

Cardiovascular dysfunction frequently accompanies aging and is often worsened by adverse lifestyle factors and genetic susceptibility. The apolipoprotein E (APOE) gene modulates susceptibility to cardiovascular disease, but how exercise and diet interact with APOE genotype remains insufficiently understood. We investigate the cardioprotective potential of exercise in humanized APOE-targeted replacement mice on control and high-fat diet, using photon-counting computed tomography (PCCT) and deep learning-based image segmentation. This study included 251 male and female mice in mid-to-late life of APOE2, APOE3, and APOE4 genotypes with variation in humanized NOS2 (HN) mediated innate immune response, exercise status (exercised vs. sedentary) and diet (control vs. high-fat). Mice underwent in vivo cine cardiac PCCT imaging following contrast enhancement with liposomal iodine nanoparticles. Stroke volume, ejection fraction, and myocardial mass were derived from automated segmentation of cardiac structures using a 3D U-Net model. We assessed main and interaction effects of genotype, sex, HN status, age, exercise and diet using generalized linear models, while Mann-Whitney U tests assessed effects of exercise within stratified subgroups. Exercise was a significant predictor of improvement in several cardiac functional metrics with a large effect size. The interaction between exercise and diet was a significant predictor of reduced body mass and myocardial mass. Stratified analyses found that exercise improves cardiac functional metrics in APOE4 mice on both diets, and APOE3 mice primarily on control diet, while benefitting HN mice more than non-HN mice. Voluntary exercise can partially rescue cardiac dysfunction induced by high-fat diet in adult APOE-targeted replacement mice, with benefits modulated by genotype, sex, and HN status. APOE4 and HN mice benefitted most from exercise. Contrast-enhanced PCCT combined with deep learning segmentation enables scalable, minimally invasive cardiac phenotyping and reveals interaction effects that are critical for designing precision lifestyle interventions in genetically at-risk populations. Show less

This study evaluates photon-counting CT (PCCT) for the imaging of mouse femurs and investigates how APOE genotype, sex, and humanized nitric oxide synthase (HN) expression influence bone morphology during aging. A custom-built micro-CT system with a photon-counting detector (PCD) was used to acquire dual-energy scans of mouse femur samples. PCCT projections were corrected for tile gain differences, iteratively reconstructed with 20 µm isotropic resolution, and decomposed into calcium and water maps. PCD spatial resolution was benchmarked against an energy-integrating detector (EID) using line profiles through trabecular bone. The contrast-to-noise ratio quantified the effects of iterative reconstruction and material decomposition. Femur features such as mean cortical thickness, mean trabecular spacing (TbSp_mean), and trabecular bone volume fraction (BV/TV) were extracted from calcium maps using BoneJ. The statistical analysis used 57 aged mice representing the APOE22, APOE33, and APOE44 genotypes, including 27 expressing HN. We used generalized linear models (GLMs) to evaluate the main interaction effects of age, sex, genotype, and HN status on femur features and Mann-Whitney U tests for stratified analyses. PCCT outperformed EID-CT in spatial resolution and enabled the effective separation of calcium and water. Female HN mice exhibited reduced BV/TV compared to both male HN and female non-HN mice. While genotype effects were modest, a genotype-by-sex stratified analysis found significant effects of HN status in female APOE22 and APOE44 mice only. Linear regression showed that age significantly decreased cortical thickness and increased TbSp_mean in male mice only. These results demonstrate PCCT's utility for femur analysis and reveal strong effects of sex/HN interaction on trabecular bone health in mice. Show less

Heart failure is a complex trait, influenced by environmental and genetic factors, affecting over 30 million individuals worldwide. Here we report common-variant and rare-variant association studies of all-cause heart failure and examine how different classes of genetic variation impact its heritability. We identify 176 common-variant risk loci at genome-wide significance in 2,358,556 individuals and cluster these signals into five broad modules based on pleiotropic associations with anthropomorphic traits/obesity, blood pressure/renal function, atherosclerosis/lipids, immune activity and arrhythmias. In parallel, we uncover exome-wide significant associations for heart failure and rare predicted loss-of-function variants in TTN, MYBPC3, FLNC and BAG3 using exome sequencing of 376,334 individuals. We find that total burden heritability of rare coding variants is highly concentrated in a small set of Mendelian cardiomyopathy genes, while common-variant heritability is diffusely spread throughout the genome. Finally, we show that common-variant background modifies heart failure risk among carriers of rare pathogenic truncating variants in TTN. Together, these findings discern genetic links between dysregulated metabolism and heart failure and highlight a polygenic component to heart failure not captured by current clinical genetic testing. Show less

To broaden our understanding of bradyarrhythmias and conduction disease, we performed common variant genome-wide association analyses in up to 1.3 million individuals and rare variant burden testing in 460,000 individuals for sinus node dysfunction (SND), distal conduction disease (DCD) and pacemaker (PM) implantation. We identified 13, 31 and 21 common variant loci for SND, DCD and PM, respectively. Four well-known loci (SCN5A/SCN10A, CCDC141, TBX20 and CAMK2D) were shared for SND and DCD, while others were more specific for SND or DCD. SND and DCD showed a moderate genetic correlation (r Show less

Heart failure (HF) is a complex trait, influenced by environmental and genetic factors, which affects over 30 million individuals worldwide. Historically, the genetics of HF have been studied in Mendelian forms of disease, where rare genetic variants have been linked to familial cardiomyopathies. More recently, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with risk of HF. However, the relative importance of genetic variants across the allele-frequency spectrum remains incompletely characterized. Here, we report the results of common- and rare-variant association studies of all-cause heart failure, applying recently developed methods to quantify the heritability of HF attributable to different classes of genetic variation. We combine GWAS data across multiple populations including 207,346 individuals with HF and 2,151,210 without, identifying 176 risk loci at genome-wide significance (P-value < 5×10 Show less