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

Cardiovascular diseases Clonal hematopoiesis of indeterminate potential (CHIP) Mutations Myocardial infarction

Journal

Journal, genetic engineering & biotechnology
ISSN: 2090-5920
Titre abrégé: J Genet Eng Biotechnol
Pays: Netherlands
ID NLM: 101317150

Informations de publication

Date de publication:
19 Jul 2021
Historique:
received: 10 03 2021
accepted: 30 06 2021
entrez: 19 7 2021
pubmed: 20 7 2021
medline: 20 7 2021
Statut: epublish

Résumé

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.

Sections du résumé

BACKGROUND BACKGROUND
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.
SHORT CONCLUSION CONCLUSIONS
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.

Identifiants

pubmed: 34279740
doi: 10.1186/s43141-021-00205-3
pii: 10.1186/s43141-021-00205-3
pmc: PMC8287286
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

105

Informations de copyright

© 2021. The Author(s).

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Auteurs

Nagendra Boopathy Senguttuvan (NB)

Department of Cardiology, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu, 600116, India. drsnboopathy@gmail.com.

Vinodhini Subramanian (V)

Department of Human Genetics, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu, 600116, India.

Vettriselvi Venkatesan (V)

Department of Human Genetics, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu, 600116, India. vettriselviv@sriramachandra.edu.in.

T R Muralidharan (TR)

Department of Cardiology, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu, 600116, India.

Kavitha Sankaranarayanan (K)

Ion Channel Biology Laboratory, AU-KBC Research Centre, MIT Campus of Anna University, Chennai, Tamil Nadu, 600044, India.

Classifications MeSH