Clonal hematopoiesis gene variants in South Asian Indians with premature coronary artery disease

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Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Clonal hematopoiesis gene variants in South Asian Indians with premature coronary artery disease View ORCID Profile Vinay J Rao , Jayaprakash Shenthar , View ORCID Profile Pradeep Natarajan , View ORCID Profile Perundurai S Dhandapany doi: https://doi.org/10.1101/2025.07.19.25331819 Vinay J Rao 1 Cardiovascular Development and Disease Mechanisms, Institute for Stem Cell Science and Regenerative Medicine , Bangalore, Karnataka, India 2 The University of Trans-Disciplinary Health Sciences and Technology , Bangalore, Karnataka, India Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Vinay J Rao Jayaprakash Shenthar 3 Department of Cardiology, Sri Jayadeva Institute of Cardiovascular Sciences and Research , Bangalore, Karnataka, India Find this author on Google Scholar Find this author on PubMed Search for this author on this site Pradeep Natarajan 4 Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital , Boston, MA 5 Program in Medical and Population Genetics, Broad Institute of Harvard and MIT , Cambridge, MA 6 Department of Medicine, Harvard Medical School , Boston, MA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Pradeep Natarajan Perundurai S Dhandapany 1 Cardiovascular Development and Disease Mechanisms, Institute for Stem Cell Science and Regenerative Medicine , Bangalore, Karnataka, India Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Perundurai S Dhandapany For correspondence: dhan{at}instem.res.in Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Importance While CHIP gene variants greatly elevate the risk of CAD among various global ancestries, pCAD remains under-researched. In particular, there is a lack of genetic data concerning pCAD in the South Asian Indian population. Objectives To investigate whether CHIP gene variants are associated with SAI-pCAD. If so, are there any differences between SAI-pCAD and other populations. Design The pCAD samples for this case-control study were collected between 2016-2019. Setting Samples were obtained within two hours following a myocardial infarction at the Sri Jayadeva Institute of Cardiovascular Sciences and Research, which is among the largest heart care centers in South Asia, located in Bengaluru, India. Participants Whole-exome sequencing and analysis were conducted on 842 SAI-pCAD individuals and 717 control subjects. The definition of pCAD included relatively young patients, specifically those under 55 years. Main Outcomes and Measures ASXL1 and TET2 were significantly associated with SAI-pCAD. Results All CHIP genes were considered for variant filtering, and among them, only 11 contained pathogenic variants in SAI-pCAD. Of these 11 genes, ASXL1 and TET2 showed significant associations after accounting for other factors like age, sex, type 2 diabetes (T2D), smoking/nicotine use, systemic hypertension, and levels of low-density lipoproteins (LDL) and triglycerides (TG). However, JAK2 , a gene often linked with pCAD in other global populations, was not found in SAI-pCAD. Conclusion and Relevance The SAI-pCAD exhibits both overlapping and unique CHIP gene variants when compared to other global populations, which contributes to the advancement of precision medicine based on ancestry. Question Is there a link between clonal hematopoiesis of indeterminate potential (CHIP) gene variants and premature coronary artery disease (pCAD) among South Asian Indians (SAI)? Findings In this research involving 842 pCAD patients and 1746 control subjects, 19% of the individuals were discovered to carry pathogenic variants in CHIP genes. Of the various CHIP genes, only ASXL1 and TET2 showed an association with SAI-pCAD. Meaning SAI-pCAD is associated with ASXL1 and TET2 , but not other CHIP genes, such as DNMT3A and JAK2 , which are prevalent in other global populations. Introduction Premature CAD is predominantly seen in individuals younger than 55 years old 1 . CHIP impacts the genetic stability of hematopoietic stem cells and involves histone modifiers, DNA methylation and demethylation, cell cycle, DNA repair, splicing, and signaling proteins. Disruptions in these pathways result in the clonal expansion and proliferation of these cells 2 . CHIP gene variants are frequently linked to the onset of CAD in older adults across various global populations 3 – 5 . Primarily, four CHIP genes— ASXL1, DNMT3A, JAK2 , and TET2 —are associated with CAD 3 . Various mechanistic studies, including those using mouse models of CHIP genes, have demonstrated their involvement in the pathogenesis of CAD 6 . Nonetheless, no genetic research has been conducted on CHIP genes in SAI-pCAD. In this study, we carried out whole-exome sequencing on 842 well-characterized SAI-pCAD patients and 717 SAI-controls. Our findings revealed that only ASXL1 and TET2 are significantly associated with SAI-pCAD. Methods Patient recruitment and selection criteria A group of 842 unrelated patients with premature coronary artery disease (pCAD) was enrolled from the Sri Jayadeva Institute of Cardiovascular Sciences and Research in Bengaluru. All participants provided written consent. The study received ethical clearance from the respective institutional human ethics committee (IHEC) with the reference number: inStem/IEC-10/001. The criteria for identifying pCAD patients was under 55 years. Selection of CAD patients was primarily based on coronary angiography and the initial occurrence of myocardial infarction. Details regarding the evaluation of acute myocardial infarction (AMI) and related covariates are provided in eMethods in Supplement 1. Control criteria For this study, 717 healthy volunteers from the aforementioned hospital were chosen as controls. Initially, we compared our findings with these healthy controls and subsequently with additional healthy controls from India 7 (n=1029), resulting in a total of 1746 participants, with an average age of 50.87 ± 18.42 years for males and 37.87 ± 17.06 years for females. The SAI-pCAD and SAI-controls were from South India with a confirmed South Asian ancestry, as reported previously using ancestral-specific markers 8 . Whole-exome sequencing and analysis We used published protocols to isolate DNA, whole-exome sequencing and analysis of the exome data to obtain variants in CHIP genes 3 , 4 , 9 . Detailed method is available in eMethods in Supplement 1. Global CAD cohorts used for analysis To identify genetic variations between SAI-pCAD and CAD groups from different ancestries, we evaluated the hazard ratios in comparison to those from earlier studies involving American (BioImage, and Mass General Brigham Biobank [MGBB]), British (UK Biobank [UKBB]), and Swedish (Malmö Diet and Cancer [MDC]) populations 3 , 5 . Statistical analysis To determine the link between CHIP genes and SAI-pCAD, Fisher’s exact test was utilized. The Benjamini-Hochberg correction was applied to adjust for multiple testing. Subsequently, logistic regression was conducted in comparison to the respective control group, accounting for various covariates such as age, sex, LDL levels, TG levels, T2D, smoking/nicotine use, and systemic hypertension. A P -value or adjusted P -value <0.05 was deemed statistically significant. Results Baseline characteristics of SAI-pCAD cohort Table 1 presents the patient information. To summarize, out of 842 SAI-pCAD patients, the average age was 40.39 ± 5.54 years for males and 46.83 ± 6.88 years for females. Of these patients, 598 (71.02%) were male, 776 (92.16%) experienced chest pain, 300 (35.63%) had elevated LDL levels, 515 (61.16%) had high TG levels, 714 (84.80%) were diagnosed with dyslipidemia, 233 (27.67%) had systemic hypertension, 242 (28.74%) had T2D, 411 (48.81%) were smokers or used nicotine, 42 (4.98%) had ischemic heart disease, and 674 (80.05%) led a sedentary lifestyle. Furthermore, 443 patients had single-vessel involvement, while 240 had multiple vessels affected. Echocardiography results showed an average left ventricular ejection fraction of 52.30% ± 7.25. View this table: View inline View popup Download powerpoint Table 1: Baseline characteristics of SAI-pCAD Total CHIP gene variants in SAI-pCAD In this study, we identified 161 rare or novel variants only in 11 CHIP genes among 842 SAI-pCAD cases, compared to 142 variants found in 1,746 Indian control exomes (19.12% versus 8.13%, P =3.177*10 −15 ) (eTable 2 in Supplement 1). All the variants detected were either missense or frameshift ( Figure 1A ). Most individuals had a single CHIP variant, with 16 out of 161 (9.93%) showing compound heterozygous variants. Variants in ASXL1 and LUC7L2 genes frequently co-occurred with IDH1 variants, respectively ( Figure 1B ). Among the 11 genes, five ( ASXL1, CBLB, IDH1, LUC7L2 , and TET2 ) were significantly more common in the SAI-pCAD group than in the total Indian controls ( Figure 1C , eFigure 2 in Supplement 1). Download figure Open in new tab Figure 1: CHIP variants in SAI-pCAD. A) Stacked bar plot representing the distribution of CHIP variants identified in SAI-pCAD. B) Chord plot depicting co-occurring CHIP variants in SAI-pCAD. C) Forest plot of CHIP genes overrepresented in SAI-pCAD. Summary indicates fixed-effects meta-analysis. OR: odds ratio. D) Forest plot of CHIP genes associated to SAI-pCAD after adjusting to age, sex, low-density lipoprotein (LDL) levels, triglyceride (TG) levels, diabetes, smoking, and hypertension. Summary indicates fixed-effects meta-analysis. HR: hazard ratio. All comparisons are between SAI-pCAD and SAI-controls (n=717 controls). CHIP genes associated with SAI-pCAD After adjusting for variables such as age, sex, LDL and TG levels, smoking/ nicotine consumption, systemic hypertension, and T2D, ASXL1 and TET2 showed a significant association with SAI-pCAD compared to SAI-controls (HR, 104; 95% CI, 19.8-568.3, P = 3.95*10-10 and HR, 21.67; 95% CI, 2.1-283.4, P = 1.38*10-04, respectively) ( Figure 1D ). In ASXL1 , two frameshift variants (p.G645Vfs*58 and p.G646Wfs*12) were found in 39 cases. Meanwhile, TET2 exhibited one novel (p.S1970P) and three rare (p.I1195V, p.S1246L, and p.I1873T) missense variants in 16 cases ( Figure 2A and B ). ASXL1 and TET2 have been identified as risk factors for CAD across various ethnic groups. However, genes like DNMT3A and JAK2 , which are commonly linked to CAD in other global populations, were less frequent in SAI-pCAD compared to SAI-controls (HR, 0.34; 95% CI, 0.067-1.6, P = 1 and HR, 0; 95% CI, undefined, P = 1, respectively) ( Figure 1D ). This indicates that the SAI-pCAD cohort shares both similarities and differences in CHIP-mediated genetic risk factors for CAD when compared to other global populations. ASXL1 and TET2 continue to be significant risk factors for pCAD, even when compared to mixed-age and late-onset CAD cases, those over 60 years old ( Figure 2C ). Download figure Open in new tab Figure 2: ASXL1 and TET2 are genetic risk factors for SAI-pCAD. A) Cartoon representation of ASXL1 protein domains highlighting the variants observed in the patients based on NM_015338. B) Cartoon representation of TET2 protein domains highlighting the variants observed in the patients based on NM_ 001127208. A) and B) Variants in red (reported on gnomAD v4.1), variants in black (not reported on gnomAD v4.1). Numbers within the parentheses indicate the number of patients harboring the variant. C) Forest plot of meta-analysis of ASXL1 and TET2 (total: n = 51132, including MDC, BioImage, UKBB, MGBB samples). Summary indicates restricted maximum likelihood estimation. HR: hazard ratio. Comparisons are between SAI-pCAD and SAI-controls (n=717 controls). Discussion CHIP gene variants are a well-documented risk factor for CAD across various populations, yet the Indian population has been poorly studied. Notably, the incidence of coronary artery disease is relatively higher in India compared to the global average 10 . Although the genetics of CAD has been extensively investigated, studies focusing on pCAD are limited. By utilizing a premature SAI case-control cohort consisting of 842 cases and 717 controls, we developed a new South Indian-specific pCAD whole-exome dataset. The exome analysis identified CHIP variants in just 11 CHIP genes. Overall, CHIP variants were present in 19.12% of the SAI-pCAD cohort, leaving 80.88% with unidentified genetic causes. Among the CHIP genes, only ASXL1 and TET2 showed a significant association with SAI-pCAD. Conversely, DNMT3A and JAK2 variants were less common in SAI-pCAD compared to other global populations. ASXL1 triggers AKT activation through a complex mechanism that involves the removal of its lysine 48 ubiquitination, ultimately leading to the proliferation of myeloid cells and their inflammatory functions 11 , 12 . Conversely, TET2 oxidizes 5-methyl cytosine, initiating DNA demethylation, which eventually results in myeloid differentiation via STAT3 and promotes the progression of atherosclerosis 3 , 13 . JAK2 is linked to both pCAD and elderly CAD in various global populations, yet its pathogenic variants are absent in SAI-pCAD, likely due to ancestral differences. Conversely, DNMT3A variants, which are prevalent in elderly CAD patients, do not show an association with pCAD 3 , 4 , including SAI-pCAD. In contrast, our study clearly suggests that ASXL1 and TET2 as significant contributors for SAI-pCAD pathogenesis. Limitations Our research focused solely on patients from South India, and the findings might vary when applied to North Indians, who have a different ancestral background 14 . Conclusion Our study is the first to outline ASXL1 and TET2 and their related risk in premature coronary artery disease in a South Asian Indian cohort with a substantial sample size. Early identification of CHIP gene variants will help in disease management of CAD. Article Information Corresponding author Correspondence to: Prof. Dhandapany S Perundurai, Cardiovascular Biology and Disease Theme, Institute for Stem Cell Science and Regenerative Medicine, Bangalore, Karnataka – 560065, India; dhan{at}instem.res.in Author Contributions The study was conceptualized, designed and supervised by PSD. The clinical samples and reagents were provided by JS and PN. The data was analyzed by VJR. The manuscript was drafted by VJR and DSP. The manuscript was reviewed by all. Conflict of Interest Disclosures P.N. reports research grants from Allelica, Amgen, Apple, Boston Scientific, Genentech / Roche, and Novartis, personal fees from Allelica, Apple, AstraZeneca, Bain Capital, Blackstone Life Sciences, Bristol Myers Squibb, Creative Education Concepts, CRISPR Therapeutics, Eli Lilly & Co, Esperion Therapeutics, Foresite Capital, Foresite Labs, Genentech / Roche, GV, HeartFlow, Magnet Biomedicine, Merck, Novartis, Novo Nordisk, TenSixteen Bio, and Tourmaline Bio, equity in Bolt, Candela, Mercury, MyOme, Parameter Health, Preciseli, and TenSixteen Bio, and spousal employment at Vertex Pharmaceuticals, all unrelated to the present work. Funding/Support PSD is supported by the Department of Biotechnology (DBT) (BT/PR45262/MED/12/955/2022), Anusandhan National Research Foundation (ANRF) (CRG/2023/004193), Indian Council for Medical Research (ICMR) IRIS Id– 2023-19831, Indo-French Centre for the Promotion of Advanced Research (IFCPAR/CEFIPRA) CSRP Project Number: 7003-1. PSD is a recipient of American Heart Association (AHA) International Professor award. VJR is supported by ICMR-SRF (3/1/1 (8)/CVD/2020-NCD-1). Role of the Funder/Sponsor The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Data Availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Acknowledgements We acknowledge Dr. Sekar Kathiresan, Dr. Amit Khera, and the patients for making this study possible. 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Share Clonal hematopoiesis gene variants in South Asian Indians with premature coronary artery disease Vinay J Rao , Jayaprakash Shenthar , Pradeep Natarajan , Perundurai S Dhandapany medRxiv 2025.07.19.25331819; doi: https://doi.org/10.1101/2025.07.19.25331819 Share This Article: Copy Citation Tools Clonal hematopoiesis gene variants in South Asian Indians with premature coronary artery disease Vinay J Rao , Jayaprakash Shenthar , Pradeep Natarajan , Perundurai S Dhandapany medRxiv 2025.07.19.25331819; doi: https://doi.org/10.1101/2025.07.19.25331819 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Genetic and Genomic Medicine Subject Areas All Articles Addiction Medicine (567) Allergy and Immunology (863) Anesthesia (297) Cardiovascular Medicine (4411) Dentistry and Oral Medicine (443) Dermatology (380) Emergency Medicine (606) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1505) Epidemiology (15205) Forensic Medicine (30) Gastroenterology (1119) Genetic and Genomic Medicine (6575) Geriatric Medicine (666) Health Economics (994) Health Informatics (4511) Health Policy (1365) Health Systems and Quality Improvement (1608) Hematology (537) HIV/AIDS (1263) Infectious Diseases (except HIV/AIDS) (15903) Intensive Care and Critical Care Medicine (1103) Medical Education (620) Medical Ethics (144) Nephrology (666) Neurology (6573) Nursing (345) Nutrition (998) Obstetrics and Gynecology (1139) Occupational and Environmental Health (954) Oncology (3319) Ophthalmology (968) Orthopedics (369) Otolaryngology (420) Pain Medicine (435) Palliative Medicine (129) Pathology (662) Pediatrics (1689) Pharmacology and Therapeutics (691) Primary Care Research (710) Psychiatry and Clinical Psychology (5423) Public and Global Health (9205) Radiology and Imaging (2191) Rehabilitation Medicine and Physical Therapy (1367) Respiratory Medicine (1191) Rheumatology (593) Sexual and Reproductive Health (709) Sports Medicine (529) Surgery (709) Toxicology (99) Transplantation (288) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9febc6557fd852ad',t:'MTc3OTI4NDY1Mg=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();