Distinct Somatic Mutational Landscapes in Paired Blood and Arterial Tissues in Coronary Artery Disease
Lau, Z. C.; Md. Zanzibul, T.; Sim, K. S.; Lin, X. Y.; Wu, H.; Naaz, A.; Muniasamy, U.; Khor, C. C.; Koh, W.-P.; Sorokin, V. A.; Dorajoo, R.
Show abstract
BackgroundClonal hematopoiesis of indeterminate potential (CHIP) is associated with ageing and atherosclerotic coronary artery disease (CAD), but evidence has largely come from peripheral blood. Whether somatic mutational profiles differ between arterial tissue and blood, and whether hematopoietic clones are represented in arterial tissue, remain poorly understood. MethodsWe performed deep whole-exome sequencing on 302 blood granulocytes and 263 arterial tissues from patients undergoing coronary artery bypass graft surgery, including 221 matched blood-tissue pairs, with mean sequencing depths of 130.5X and 120.8X, respectively. Somatic variants were identified using Mutect2. Associations with age and CAD complexity, assessed using SYNTAX score, were evaluated using multivariable regression. Primary analyses focused on variants with variant allele fractions of 10-25%. ResultsCHIP was detected in 24/302 (7.9%) blood granulocytes, predominantly involving DNMT3A, TET2, and ASXL1. In contrast, somatic mutations in CHIP-associated genes in arterial tissues showed a distinct profile dominated by CALR, SETDB1, and PDSS2. Somatic mutation carrier status increased with age in blood ({beta} = 0.07, p = 0.02) and arterial tissues ({beta} = 0.06, p = 0.04). Blood CHIP was associated with lower SYNTAX score ({beta} = -1.05, p = 2.66 x 10-3), partly driven by DNMT3A carriers ({beta} = -1.06, p = 0.04), whereas arterial CALR mutations were associated with higher SYNTAX score ({beta} = 1.14, p = 0.03). Among 221 matched pairs, only four identical variants, involving CHEK2, DNMT3A, GNB1, and SRSF1, were detected in both compartments. Genome-wide analyses showed compartment specificity, with bile acid metabolism enriched among arterial tissue-specific mutations (PAdj = 0.038). ConclusionBlood and arterial tissues in CAD harbour distinct somatic mutational landscapes with limited cross-compartment sharing. These findings suggest that cardiovascular somatic mutations may reflect both hematopoietic and arterial tissue-associated processes and motivate cell-resolved and spatial studies to define their origins and roles in cardiovascular ageing.
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- The association between clonal hematopoiesis driver mutations, immune cell function and the vasculometabolic complications of obesity 91%
- Cardiomyocyte-specific plakophilin-2 loss is sufficient to induce aging and senescence of nonmyocytes. Relevance to arrhythmogenic cardiomyopathy. 91%
- GATA2 Mediates Macrophage Proliferation During Atherosclerosis 90%
Similar papers in this journal
- Genetic association analyses highlight IL6, ALPL, and NAV1 as three new susceptibility genes underlying calcific aortic valve stenosis 91%
- Machine Learning to Understand Genetic and Clinical Factors Associated with the Pulse Waveform Dicrotic Notch 90%
- Phenome-wide Mendelian randomization identifying circulating proteins for cardiovascular traits in populations of African ancestry 90%
Similar papers in this journal
- Genetically Increased Telomere Length and Aging-related Physical and Cognitive Traits in the UK Biobank 92%
- Allele-specific transcript abundance: A pilot study in healthy centenarians 92%
- Biological age in UK Biobank: biomarker composition and prediction of mortality, coronary heart disease and hospital admissions 91%
Similar papers in this journal
- Activating P2Y1 receptors improves function in arteries with repressed autophagy 92%
- Shared proteomic landscape between arteriosclerosis and cardiovascular endpoints: a Mendelian randomization and observational study integrating AlphaFold3 for structural prediction 90%
- A pivotal role for Nrf2 in endothelial detachment- implications for endothelial erosion of stenotic plaques 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.