Leukocytes carrying Clonal Hematopoiesis of Indeterminate Potential (CHIP) Mutations invade Human Atherosclerotic Plaques

Background: Leukocyte progenitors derived from clonal hematopoiesis of undetermined potential (CHIP) are associated with increased cardiovascular events. However, the prevalence and functional relevance of CHIP in coronary artery disease (CAD) are unclear, and cells affected by CHIP have not been detected in human atherosclerotic plaques. Methods: CHIP mutations in blood and tissues were identified by targeted deep-DNA-sequencing (DNAseq: coverage >3,000) and whole-genome-sequencing (WGS: coverage >35). CHIP-mutated leukocytes were visualized in human atherosclerotic plaques by mutaFISHTM. Functional relevance of CHIP mutations was studied by RNAseq. Results: DNAseq of whole blood from 540 deceased CAD patients of the Munich cardIovaScular StudIes biObaNk (MISSION) identified 253 (46.9%) CHIP mutation carriers (mean age 78.3 years). DNAseq on myocardium, atherosclerotic coronary and carotid arteries detected identical CHIP mutations in 18 out of 25 mutation carriers in tissue DNA. MutaFISHTM visualized individual macrophages carrying DNMT3A CHIP mutations in human atherosclerotic plaques. Studying monocyte-derived macrophages from Stockholm-Tartu Atherosclerosis Reverse Networks Engineering Task (STARNET; n=941) by WGS revealed CHIP mutations in 14.2% (mean age 67.1 years). RNAseq of these macrophages revealed that expression patterns in CHIP mutation carriers differed substantially from those of non-carriers. Moreover, patterns were different depending on the underlying mutations, e.g. those carrying TET2 mutations predominantly displayed upregulated inflammatory signaling whereas ASXL1 mutations showed stronger effects on metabolic pathways. Conclusions: Deep-DNA-sequencing reveals a high prevalence of CHIP mutations in whole blood of CAD patients. CHIP-affected leukocytes invade plaques in human coronary arteries. RNAseq data obtained from macrophages of CHIP-affected patients suggest that pro-atherosclerotic signaling differs depending on the underlying mutations. Further studies are necessary to understand whether specific pathways affected by CHIP mutations may be targeted for personalized treatment.

[1]  A. Tall,et al.  Inflammasomes and Atherosclerosis: a Mixed Picture. , 2023, Circulation research.

[2]  P. Libby,et al.  Clonal Hematopoiesis of Indeterminate Potential Predicts Adverse Outcomes in Patients With Atherosclerotic Cardiovascular Disease. , 2023, Journal of the American College of Cardiology.

[3]  P. Libby,et al.  Genetic modification of inflammation and clonal hematopoiesis-associated coronary artery disease , 2022, medRxiv.

[4]  E. Schadt,et al.  A mechanistic framework for cardiometabolic and coronary artery diseases , 2022, Nature Cardiovascular Research.

[5]  A. Orekhov,et al.  Anti-Inflammatory Therapy for Atherosclerosis: Focusing on Cytokines , 2021, International journal of molecular sciences.

[6]  Xia Yang,et al.  Mergeomics 2.0: a web server for multi-omics data integration to elucidate disease networks and predict therapeutics , 2021, Nucleic Acids Res..

[7]  P. Libby,et al.  IL-6 inhibition with ziltivekimab in patients at high atherosclerotic risk (RESCUE): a double-blind, randomised, placebo-controlled, phase 2 trial , 2021, The Lancet.

[8]  A. Dopazo,et al.  Clonal Hematopoiesis and Risk of Progression of Heart Failure With Reduced Left Ventricular Ejection Fraction. , 2021, Journal of the American College of Cardiology.

[9]  V. Regitz-Zagrosek,et al.  Colchicine in Patients with Chronic Coronary Disease. , 2021, The New England journal of medicine.

[10]  A. Zeiher,et al.  Clonal haematopoiesis in chronic ischaemic heart failure: prognostic role of clone size for DNMT3A- and TET2-driver gene mutations. , 2020, European heart journal.

[11]  Norio Kobayashi,et al.  FANTOM enters 20th year: expansion of transcriptomic atlases and functional annotation of non-coding RNAs , 2020, Nucleic Acids Res..

[12]  B. V. Van Tassell,et al.  Interleukin-1 and the Inflammasome as Therapeutic Targets in Cardiovascular Disease , 2020, Circulation research.

[13]  Dave L Dixon,et al.  Interleukin‐1 Blockade Inhibits the Acute Inflammatory Response in Patients With ST‐Segment–Elevation Myocardial Infarction , 2020, Journal of the American Heart Association.

[14]  P. Libby,et al.  Clonal haematopoiesis: connecting ageing and inflammation in cardiovascular disease , 2019, Nature Reviews Cardiology.

[15]  C McRae,et al.  Myocardial infarction. , 2019, Australian family physician.

[16]  B. Brüne,et al.  Association of Mutations Contributing to Clonal Hematopoiesis With Prognosis in Chronic Ischemic Heart Failure , 2018, JAMA cardiology.

[17]  P. Libby,et al.  CHIP (Clonal Hematopoiesis of Indeterminate Potential). , 2018, Circulation.

[18]  L. Buckley,et al.  Interleukin-1 blockade in cardiovascular diseases: a clinical update , 2018, European heart journal.

[19]  Pierre Geurts,et al.  dynGENIE3: dynamical GENIE3 for the inference of gene networks from time series expression data , 2018, Scientific Reports.

[20]  Mauricio O. Carneiro,et al.  Scaling accurate genetic variant discovery to tens of thousands of samples , 2017, bioRxiv.

[21]  P. Libby,et al.  Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease , 2017, The New England journal of medicine.

[22]  S. Gabriel,et al.  Clonal Hematopoiesis and Risk of Atherosclerotic Cardiovascular Disease , 2017, The New England journal of medicine.

[23]  Matthew A. Cooper,et al.  Clonal hematopoiesis associated with TET2 deficiency accelerates atherosclerosis development in mice , 2017, Science.

[24]  M. Inouye,et al.  Mergeomics: multidimensional data integration to identify pathogenic perturbations to biological systems , 2016, BMC Genomics.

[25]  T. Druley,et al.  Clonal haematopoiesis harbouring AML-associated mutations is ubiquitous in healthy adults , 2016, Nature Communications.

[26]  Tom Michoel,et al.  Cardiometabolic risk loci share downstream cis- and trans-gene regulation across tissues and diseases , 2016, Science.

[27]  Derek W Wright,et al.  Gateways to the FANTOM5 promoter level mammalian expression atlas , 2015, Genome Biology.

[28]  M. McCarthy,et al.  Age-related clonal hematopoiesis associated with adverse outcomes. , 2014, The New England journal of medicine.

[29]  S. Gabriel,et al.  Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. , 2014, The New England journal of medicine.

[30]  W. Jędrzejczak,et al.  Donor NK cell licensing in control of malignancy in hematopoietic stem cell transplant recipients , 2014, American journal of hematology.

[31]  W. Frishman,et al.  Inflammation and Atherosclerosis: A Review of the Role of Interleukin-6 in the Development of Atherosclerosis and the Potential for Targeted Drug Therapy , 2014, Cardiology in review.

[32]  Mauricio O. Carneiro,et al.  From FastQ Data to High‐Confidence Variant Calls: The Genome Analysis Toolkit Best Practices Pipeline , 2013, Current protocols in bioinformatics.

[33]  M. DePristo,et al.  A framework for variation discovery and genotyping using next-generation DNA sequencing data , 2011, Nature Genetics.

[34]  M. DePristo,et al.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. , 2010, Genome research.

[35]  Ola Söderberg,et al.  In situ detection and genotyping of individual mRNA molecules , 2010, Nature Methods.