Clonal hematopoiesis of indeterminate potential (CHIP) and cardiovascular diseases-an updated systematic review

Cardiovascular diseases (CVDs) are the leading cause of mortality in India. Residual risk exists in patients receiving optimal guideline-directed medical therapy. Possession of certain somatic mutations, at a variant allele frequency of ≥ 2% in peripheral blood, driving clonal expansion in the absence of cytopenias and dysplastic hematopoiesis is defined as clonal hematopoiesis of indeterminate potential (CHIP). Recently, it was found that carriers of CHIP had a higher risk to have coronary artery disease (CAD) and early-onset myocardial infarction. Association of CHIP with heart failure and valvular heart diseases is increasingly being considered. The common link that connects CHIP mutations and CVDs is inflammation leading to increased expression of cytokines and chemokines. We intended to do a systematic review about the association of CHIP mutations and CVD along with identifying specific CHIP mutations involved in increasing the risk of having CVDs. We performed an extensive literature search in PubMed and Google Scholar databases. Out of 302 articles, we narrowed it down to 10 studies based on our pre-specified criteria. The methodology adopted for the identification of CHIP mutations in the selected studies included - whole-exome sequencing (n = 3), whole-genome analysis (n = 1), transcriptome profiling analysis (n = 1), whole-genome analysis (n = 1), and single-cell RNA-sequencing (n = 1). We found that the available literature suggested an association between CHIP and CVD. The most commonly described CHIP mutations in patients with CVD are DNMT3A, TET2, ASXL1, TP53, JAK2, and SF3B. We further analyzed the commonly mutated CHIP genes using bioinformatics tools. Protein function and interaction analysis were performed using the g: Profiler and GeneMANIA online tools. The results revealed significant bio grid interactions for molecular functions, biological processes, and biological pathways. Interaction analysis showed significant physical and co-expression interactions.

We conclude that there exists a significant association between CHIP mutations and CVD with DNMT3A, TET2, ASXL1, TP53, JAK2, and SF3B as the commonly implicated genes. The recognition of the link between CHIP and cardiovascular events will expand our understanding of residual risk and will open up new avenues of investigation and therapeutic modalities in the management of patients with CVD.