Prognostic Significance of -Clonal Haematopoiesis of Indeterminate Potential-Mutations with hs-CRP in Patients with STEMI --- from a Prospective Cohort Study Combining Bidirectional Mendelian Randomization

Prognostic Significance of -Clonal Haematopoiesis of Indeterminate Potential-Mutations with hs-CRP in Patients with STEMI --- from a Prospective Cohort Study Combining Bidirectional Mendelian Randomization | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prognostic Significance of -Clonal Haematopoiesis of Indeterminate Potential-Mutations with hs-CRP in Patients with STEMI --- from a Prospective Cohort Study Combining Bidirectional Mendelian Randomization Xiaoxiao Zhao, Runzhen Chen, Jiannan Li, Hong Liu, Nan Li, Linghan Xue, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9229638/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction Clonal haematopoiesis of indeterminate potential (CHIP), driven by age-related somatic mutations in hematopoietic stem cells, has emerged as a novel modulator of cardiovascular risk. Objectives This study investigates the prognostic interplay between TET2-CHIP mutations, systemic inflammation quantified by high-sensitivity C-reactive protein (hs-CRP), and clinical outcomes in ST-segment elevation myocardial infarction (STEMI), leveraging bidirectional Mendelian randomization (MR) to elucidate causal relationships. Patients and methods Deep-targeted sequencing data from 1,403 STEMI patients (March 2017–January 2020) were analyzed to identify 42 CHIP-associated mutations using unique molecular identifiers (UMIs). Associations between CHIP and all-cause mortality were evaluated, alongside correlations with hs-CRP. A bidirectional Mendelian randomization (MR) study was performed using genetic instruments for TET2-CHIP from the UK Biobank (2,041 cases; 173,918 controls) and hs-CRP data from the European Bioinformatics Institute consortium (353,466 cases and 34,594,039 controls) to assess causality. Results Those exhibiting elevated hsCRP levels and TET2-CHIP variants (VAF >2%) were characterized by advanced age, reduced ejection fraction, higher troponin/NT-proBNP levels, increased prevalence of diabetes, and an elevated all-cause mortality rate (all p<0.05). Furthermore, multivariable Cox proportional hazards regression models confirmed the independent association between TET2-CHIP associated somatic mutations and all-cause mortality (adjusted HR, 3.77 [95% CI, 1.61-8.81]; P = 0.002; P for trend < 0.001). Simultaneous assessment of CHIP and degree of inflammatory status as measured by hs-CRP revealed combined effects on mortality, depicted by a superior risk for patients with more than median hs-CRP and concomitant CHIP (p＜0.0001). Bidirectional MR studies indicated that the increased value of hs-CRP improves the propensity for CHIP. Conclusion CHIP and hs-CRP synergistically predict poor prognosis in STEMI patients, with a potential causal relationship between TET2-related CHIP and inflammatory status. These findings highlight the potential of targeting CHIP-associated inflammatory pathways to improve cardiovascular outcomes. Clonal hematopoiesis high-sensitivity C-reactive protein Mendelian Randomization Myocardial infarction Figures Figure 1 Figure 2 Figure 3 Figure 4 What’s new? Clonal hematopoiesis of indeterminate potential (CHIP) has been recognized as a significant risk factor for cardiovascular disease. However, the relationship between CHIP and inflammatory biomarkers, such as high-sensitivity C-reactive protein, remains to be fully elucidated. In this prospective cohort of 1,286 ST‑elevation myocardial infarction (STEMI) patients treated with primary percutaneous coronary intervention, we observed that TET2‑mutated CHIP acts synergistically with elevated high‑sensitivity C‑reactive protein (hs‑CRP) to markedly increase the risk of mortality and other major clinical endpoints. Together, these markers delineate a subset of patients at exceptionally elevated risk, even after adjustment for conventional risk factors. Our findings are further supported by Mendelian randomization analyses, which indicate that chronic inflammatory exposure may serve as a causative driver of somatic clonal expansion, thereby establishing a pathogenic continuum from persistent inflammation to clonal dominance and subsequent cardiovascular vulnerability. These results collectively underscore the potential clinical utility of CHIP screening in acute coronary syndrome populations and furnish a mechanistic rationale for therapeutic strategies aimed at attenuating CHIP‑associated inflammation to modify post‑infarction prognosis. Introduction Clonal Hematopoiesis: Bridging Hematologic and Cardiovascular Pathobiology Clonal hematopoiesis (CH), characterized by clonal dominance of hematopoietic stem cells due to acquired somatic mutations, has been recognized as a critical driver of hematologic malignancies, serving both as a marker of clonal evolution and a precursor to overt leukemia [ 1 ]. The advent of next-generation sequencing (NGS) unveiled an unexpected prevalence of myeloid malignancy-associated somatic mutations in asymptomatic individuals [ 2 – 3 ], prompting the formal definition of clonal hematopoiesis of indeterminate potential (CHIP). CHIP is molecularly defined by somatic mutations in leukemia-associated driver genes (e.g., TET2, DNMT3A, ASXL1, JAK2 ) with a variant allele frequency (VAF) ≥ 2%, in the absence of cytopenia or diagnostic features of hematologic neoplasia [ 4 ]. Epidemiological studies reveal an age-dependent penetrance of CHIP, with carriers exhibiting excess mortality not fully explained by cancer progression. Subsequent mechanistic work implicates accelerated cardiovascular mortality as a key contributor, establishing CHIP as a novel risk factor for atherosclerotic disease [ 5 ]. Inflammatory Pathways and Epigenetic Deregulation in cardiovascular disease Mounting evidence positions chronic inflammation and TET2 -driven CHIP as synergistic mediators of cardiovascular pathogenesis [ 6 – 12 ]. Atherosclerosis, a quintessential inflammatory disorder, has spurred the clinical integration of high-sensitivity C-reactive protein (hs-CRP) for risk stratification. As a sensitive biomarker of systemic inflammation, hs-CRP correlates strongly with atherosclerotic burden and adverse outcomes [ 13 ]. The PROVE-IT trial landmark finding—that post-MI hs-CRP reduction predicts survival benefits independent of LDL-cholesterol —underscores inflammation's causal role in CVD progression [ 14 ]. The TET2 gene, first linked to non-malignant clonal hematopoiesis [ 15 ], encodes an α-ketoglutarate- dependent dioxygenase essential for epigenetic regulation of hematopoietic stem/progenitor cell (HSPC) differentiation [ 16 – 18 ]. Preclinical models demonstrate that TET2 loss in myeloid cells exacerbates atherosclerosis via NLRP3 inflammasome-mediated IL-1β hypersecretion [ 19 ]. Notably, bone marrow reconstitution with TET2 -deficient cells in hyperlipidemic mice accelerates plaque formation, while NLRP3 inhibition attenuates this phenotype, providing direct mechanistic evidence [ 20 ]. CHIP in Myocardial Infarction: Unanswered Mechanistic Questions Clinical cohort studies consistently associate CHIP with increased MI incidence and mortality, attributed to a proinflammatory vicious cycle: CHIP-mutant leukocytes exhibit enhanced cytokine/chemokine release (e.g., IL-6, IL-8), while impaired immune regulation perpetuates vascular inflammation [ 21 – 22 ]. However, critical gaps remain: (i) Whether TET2 mutations causally drive inflammation in humans, and (ii) How CHIP interacts with inflammatory burden to modulate post-MI outcomes, remain unexplored. Methods Study design, participants and sample collection This prospective cohort study employed a rigorous methodological framework to investigate the interplay between TET2 - CHIP and systemic inflammation, with a focus on hs-CRP as a key biomarker. The study design is anchored in the China Risk, Genetics, Archiving, and Monograph (CRGAM) initiative—a longitudinal, population-based registry enrolling adults ≥ 18 years diagnosed with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI) at Fuwai Hospital (Beijing), a national tertiary cardiovascular center. Participants were consecutively recruited between March 2017 and January 2020, with standardized protocols ensuring consistency in clinical data acquisition, biospecimen collection, and follow-up procedures (Fig. 1 ). The study adhered to the ethical principles of the Declaration of Helsinki and received approval from the Institutional Review Board of Fuwai Hospital (No. 2017 − 866). Written informed consent was obtained from all participants prior to enrollment. CRGAM was designed with dual aims: (1) to refine cardiovascular risk stratification models by integrating traditional risk factors with genetic and biomarker profiles, and (2) to evaluate the prognostic value of TET2 -CHIP mutations in modulating inflammation-driven mortality post-STEMI. The primary endpoint was all-cause mortality, with follow-up data systematically collated through hospital records, national death registries, and direct patient contact (Supplemental Methods 1). Data acquisition Demographic and clinical parameters—encompassing medical history, active therapeutic regimens, anthropometric measurements, and familial cardiovascular disease burden—were prospectively catalogued through validated case report forms administered by trained clinical personnel. Serum hs-CRP levels were derived from institutional electronic medical repositories, with rigorous adherence to temporal alignment between biomarker quantification and study enrollment. To screen for CHIP, we implemented a targeted next-generation sequencing panel interrogating recurrently mutated loci in DNMT3A, TET2 , ASXL1, and JAK2. Expanded technical specifications regarding sequencing workflows (including library preparation, variant calling parameters, and somatic mutation validation criteria) are comprehensively outlined in Supplementary Methods 2. Peripheral blood samples were acquired under written informed consent protocols. Genomic DNA was isolated from leukocyte fractions using magnetic bead-based purification, followed by ultra-deep sequencing (median coverage > 1,000×) of 42 CHIP-associated gene targets (full gene list in Supplementary Table S1 ). Selection of data sources of the two-sample bidirectional MR All genetic instruments for the bidirectional Mendelian randomization (MR) analyses were obtained from publicly accessible repositories with full ethical compliance. The study rigorously adhered to the STROBE-MR reporting guidelines (Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization) to ensure methodological transparency and reproducibility [ 23 ]. Genetic associations for TET2 -mutated CHIP were derived from the UK Biobank (UKB) genome-wide association study (European ancestry: 2,041 cases vs 173,918 controls; GWAS accession: GCST90102620). These instruments were applied to interrogate causal relationships with circulating hs-CRP levels from the European Bioinformatics Institute (EBI) consortium (n = 353,466; build GRCh37: GCST90018950), with reciprocal analysis evaluating hs-CRP→CHIP causal pathways. Statistical analysis Continuous variables were presented as mean ± standard deviation, while categorical data were expressed as counts and percentages. Group comparisons for continuous variables were performed using Student's t-test or Mann-Whitney U test based on distribution normality. Categorical variables were analyzed through Pearson's χ² test or Fisher's exact test, with the latter employed when expected cell counts fell below five. Survival curves were generated using the Kaplan-Meier method, with between-group differences evaluated by log-rank test. Multivariable Cox proportional hazards regression models were constructed to assess independent associations between TET2 -CHIP status (defined as VAF ≥ 2%) and clinical endpoints, including all-cause mortality, cardiac death, recurrent myocardial infarction, revascularization, and ischemic stroke. Model covariates comprised age, sex, smoking status, hypertension, hyperlipidemia, prior myocardial infarction, peripheral artery atherosclerosis, previous PCI/CABG, anthropometric measures (height, weight), and hemodynamic parameters (heart rate, systolic/diastolic blood pressure). Interaction effects between TET2 -CHIP and hs-CRP levels were tested through multiplicative interaction terms in separate Cox models. Results are reported as hazard ratios (HRs) with 95% confidence intervals (CIs), with statistical significance defined as two-tailed P < 0.05. We employed a two-sample bidirectional MR framework to investigate causal relationships between TET2 -CHIP mutations (UK Biobank European subset, n = 173,918) and hs-CRP levels (EBI consortium, n = 153,466). A concise overview of genetic instruments derived from genome-wide association studies related to overall CHIP mutations. This encompasses both small and large CHIP mutations, in addition to specific mutations in DNMT3A and TET2 , which were obtained from the UK Biobank. Genetic instruments for CHIP phenotypes were selected from genome-wide association studies (GWAS) meeting stringent criteria: genome-wide significance (P < 5×10⁻⁸), linkage disequilibrium independence (r² 10 were included to ensure instrument strength. Primary causal estimates were derived through inverse-variance weighted (IVW) meta-analysis under random-effects assumptions. In the primary analysis, we obtained estimates through inverse variance weighting meta-analysis utilizing multiplicative random effects derived from SNP-specific Wald estimates, under the assumption of balanced pleiotropy. Given the challenge associated with verifying the ‘exclusion-restriction’ assumption, we conducted sensitivity analyses employing various assumptions, including MR Egger and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) [ 25 ]. The weighted median of SNP-specific estimates yields valid estimations when at least 50% of the information is sourced from valid SNPs [ 26 ]. Sensitivity analyses included: MR-Egger regression to detect directional pleiotropy (significant intercept P < 0.05 indicating bias). Weighted median estimator requiring ≥ 50% valid instruments. To examine and remove horizontal pleiotropic outliers while assuming that 50% of instruments were valid with balanced pleiotropy satisfying the InSIDE assumption, MR-PRESSO was employed for outlier correction (global test P < 0.05). Leave-one-out sensitivity analyses were also performed to scrutinize the stability concerning individual nucleotide polymorphisms. Heterogeneity was quantified using Cochran's Q statistic, with P < 0.05 suggesting significant variation. All analyses were conducted in R 4.4.1 using dedicated packages (TwoSampleMR, MRPRESSO, PheWAS), adhering to STROBE-MR guidelines. Results Patient characteristics and detection of the CHIP somatic mutations The CRGAM trial prospectively enrolled 1,286 STEMI patients undergoing primary PCI, with subsequent targeted next-generation sequencing performed to detect CHIP mutations. The cohort had a mean age of 60.7 ± 12.4 years (80.6% male), with detailed baseline characteristics presented in Table 1. Over a median follow-up of 3.25 years, we observed 72 all-cause deaths (5.6%), 66 recurrent myocardial infarctions (5.1%), and 66 ischemic strokes (5.1%), with cardiovascular mortality accounting for 72 events (5.6%). Stratification by hs-CRP median (5.65 mg/L) and TET2 -CHIP variant allele frequency (VAF ≥2%) revealed distinct phenotypic clusters: High hs-CRP/ TET2 -CHIP+ group (n=22) demonstrated advanced age (70.3 ± 14.2 vs 59.6 ± 11.8 years; P<0.001), reduced left ventricular ejection fraction (52.4% ± 8.8 vs 54.4% ± 7.5; P=0.003). Elevated cardiac biomarkers: peak troponin T (31.7 vs 20.2 mmol/L; P<0.001), NT-proBNP (1,658 vs 630 mmol/L; P<0.001). Higher diabetes prevalence (50.0% vs 31.1%; P=0.049). Excess all-cause mortality (36.4% vs 6.5%; A detailed characteristic description of Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) and presence of TET2 -CHIP is provided (Supplementary Tables S2-S4), suggesting potential interaction between lipoprotein metabolism and clonal hematopoiesis. Prevalence of -CHIP somatic mutations and hs-CRP The co-distribution of TET2 -CHIP mutations (variant allele frequency ≥2%) and hs-CRP levels was analyzed across diabetes status, sex, and age strata in Figure 2. Non-survivors demonstrated pronounced hs-CRP elevation, with 49.6% in the highest tertile versus 31.5% among survivors (P<0.001; Figure 2A). A hierarchical risk gradient emerged across hs-CRP tertiles, capturing 80.8% of mortality cases in the upper two tertiles compared to 65.1% in survivors. Strikingly, the coexistence of TET2 -CHIP mutations and hs-CRP levels above the median identified a high-risk phenotype (6.4% of non-survivors vs. 1.2% survivors; Pmedian patients exhibited 11.3% mortality versus 2.8% in non-diabetics (Δ=8.5%, P=0.002; Figure 2B). Age stratification revealed a biological gradient, with mortality rates escalating from 0% in CHIP+/ hs-CRP>median patients aged <60 years to 23.5% in those ≥75 years (Figure 2C). Notably, individuals harboring TET2 -CHIP somatic mutations along with higher level of hs-CRP exhibit a significantly elevated incidence of all caused mortality (P < 0.001) and cardiac death within the entire enrolled cohort (p=0.015, refer to Figure 2D). Combined effect of -clonal hematopoiesis of indeterminate potential and degree of inflammation biomarkers Previous investigation utilizing the CRGAM cohort, we established significant associations between the type 2 DM with TET2 -CHIP mutations [27]. Importantly, our findings revealed that both TET2 -CHIP status and hs-CRP levels independently and synergistically contribute to all-cause mortality risk in CRGAM patients. To elucidate the combined impact of hs-CRP levels and TET2 -CHIP status on long-term clinical outcomes, we implemented a comprehensive stratification approach. The cohort was systematically divided into four distinct groups based on hs-CRP levels (above or below the median) and TET2 -CHIP mutation status: Group I (hs-CRP median, TET2 -CHIP absence), Group III (hs-CRP median, TET2 -CHIP present). Kaplan-Meier survival analysis of the entire cohort, encompassing type 2 diabetes mellitus (T2DM) and non-T2DM participants, revealed striking differences in clinical outcomes (Figure 3). The cumulative 1000-day survival rates for all-cause mortality were 93.52%, 88.33%, 78.57%, and 72.72% for Groups I-IV, respectively (log-rank P < 0.0001; Figure 3A). Furthermore, we observed a significant association between CHIP mutations and elevated PCSK9 levels with increased all-cause mortality (Supplemental Figure 1). Notably, the stratification based on TET2 -CHIP mutation status combined with elevated hs-CRP levels demonstrated consistent associations with adverse outcomes across both the entire cohort and the DM subgroup (log-rank P < 0.01; Figure 3B, Supplemental Figure 2). In univariable analysis, Group IV (defined by the presence of TET2 -CHIP mutations with VAF ≥2% and hs-CRP levels exceeding the cohort median) demonstrated a pronounced association with all-cause mortality, exhibiting a crude hazard ratio (HR) of 6.54 (95% confidence interval [CI], 3.06-13.95; P < 0.001) in the overall cohort (Table 2). Multivariable Cox proportional hazards regression models adjusted for clinical covariates – including age, sex, smoking status, hypertension, hyperlipidemia, history of MI, peripheral artery atherosclerosis, prior PCI, coronary artery bypass grafting, anthropometric measures (height, weight), hemodynamic parameters (heart rate, systolic/diastolic blood pressure) – confirmed the independent association between TET2 -CHIP-associated somatic mutations and all-cause mortality (adjusted HR, 3.77 [95% CI, 1.61-8.81]; P = 0.002; P for trend < 0.001; Table 2, Supplemental Table 5). Notably, significant effect modification was observed between diabetes mellitus (DM) and non-DM subgroups (P for interaction = 0.043). Following comprehensive adjustment for potential confounders, the mortality association remained markedly stronger in DM patients compared to non-DM counterparts (adjusted HR, 7.39 [95% CI, 2.11-25.82]; P = 0.002; P for trend = 0.001). This pattern intensified in the combined CHIP/PCSK9 subgroup analysis, revealing a striking 15.96-fold increased mortality risk (95% CI, 3.74-68.09; P < 0.001; P for trend = 0.005; Supplemental Table 6). The progressive risk gradient across these stratified groups underscores the synergistic impact of clonal hematopoiesis, inflammatory burden, and metabolic deregulation on clinical outcomes in cardiovascular populations. MR studies indicate that T2DM causes -CHIP mutations We performed a two-sample bidirectional MR study to infer whether on hs-CRP has a causal effect on TET2 -CHIP acquisition, and conversely. Using European Bioinformatics Institute (EBI) consortium data, the association between hs-CRP and TET2 -CHIP was tested to infer causality in MR framework. We used EBI summary statistics as the exposure (hs-CRP) cohort (n =153,466) and the European subset of the UK Biobank as the outcome (CHIP) cohort (n = 173,918). Brief information of genetic instruments from the genome-wide association study for overall CHIP mutation, DNMT3A, TET2 , samll and large CHIP mutation from the UK Biobank has been described in table 3. We found instrumental variables (IVs) from an independent GWAS of hs-CRP [28-30]. 265 single-nucleotide polymorphisms (SNPs) with P < 10−8 were pruned as 10 Mb apart and in linkage disequilibrium with each SNP exhibiting an F-statistic exceeding the threshold of 10 (p＜5*10-8, r2＜0.001, window size=1000kb). All these SNPs were included in the analyses. F-statistics suggesting that instruments bias may not be substantial. Details of the SNPs included are in the supplementary material for the mutation list). Inverse variance weighted estimates suggested that hs-CRP had a risk causal relationship effect on TET2 -CHIP mutations (odds ratio = 1.0024, 95% confidence interval: 1.0005-1.0043, P = 0.0153) (Figure 4). Moreover, the Mendelian randomization estimates regarding the impact of hs-CRP on overall CHP mutations, DNMT3A CHIP mutations, as well as small and large CHIP mutations are presented in Figure 4. MR-Egger (Q = 215.2087, Q value = 0.2817；IVW，Q = 215.871, Q value = 0.2876, Supplementary Table 7) and MR-PRESSO [31] (p value=0.564, Supplementary Table 8) intercept did not identify any pleiotropic SNPs. We found no evidence supporting significant horizontal pleiotropy (Egger intercept = 0.00004, P = 0.4291) (Table 4). Forest plot has shown the beta estimates and 95% confidence intervals of MR (Supplementary Figure 3A). No significant heterogeneity of instrumental variables or horizontal pleiotropy was found. The findings of scatter plots (Supplementary Figure 3B) indicated that the trajectories of various algorithms exhibit an overall upward trend, suggesting that the risk of TET2 -CHIP mutations escalates with increasing concentrations of hs-CRP. The leave-one-out plot demonstrates that there is no potentially influential SNPs driving the causal link between hs-CRP and TET2 -CHIP mutations (Supplementary Figure 3C).Funnel plot (Supplementary Figure 3D) suggested no bias under mixed effects (restricted maximum likelihood) when the standard error was used as predictor. We performed two-sample MR as a replication analysis. We used previous European subset of the UK Biobank as the exposure (CHIP) cohort (n =173,918) and the EBI as the outcome (hs-CRP) cohort (n =153,466). The positive potential causal effect of TET2 -CHIP on hs-CRP was not shown in the conventional two-sample MR approach [inverse variance weighted method; Estimate = 0.6296, 95% CI: 0.3262–1.2154, P = 0.1680] (Supplementary Table 9). According to the results of reverse MR analysis, no significant causal effect of CHIP was found on hs-CRP. We next evaluated the relationship of PCSK9 (ID exposure: 0K69UK/res_invn_X5231_79_Fenland_MA_auto_chrX_filtered_1pc/5231_79_PCSK9_PCSK9.txt/PCSK9_Q8NBP7_OID20235_v1_Cardiometabolic_new) [32] with the occurrence of CHIP acquired genome-wide singleton single nucleotide polymorphism (Supplementary Table 10). However, MR analyses did not supported a causal relationship between PCSK9 and increased somatic mutations in two-sample MR study. Discussion The intricate relationship between CHIP and systemic inflammation has emerged as a critical determinant of cardiovascular outcomes in high-risk populations. Our prospective cohort study of 1,286 STEMI patients undergoing primary PCI provides compelling evidence that TET2 -CHIP mutations synergize with elevated hs-CRP to drive adverse clinical trajectories. Three principal findings emerge: (1) The combined CHIP/inflammatory phenotype associates with accelerated atherosclerosis progression, evidenced by reduced left ventricular function, heightened troponin release, and NT-proBNP elevation; (2) Patients with concurrent TET2 -CHIP and hs-CRP above median exhibit a 6.54-fold increased mortality risk, amplified in diabetic subgroups (adjusted HR 7.39); (3) Mendelian randomization establishes a unidirectional causal relationship where genetically determined hs-CRP elevation predisposes to TET2 -CHIP acquisition. These findings align with emerging paradigms of somatic mutation-driven inflammation while providing novel insights into risk stratification and therapeutic targeting in post-MI populations (Structured Graphical Abstract). Genetic and Epigenetic Drivers of CHIP-Associated Inflammation Our cohort extends previous observations [ 28 ] by demonstrating that TET2 -CHIP carriers with elevated hs-CRP (> median) face substantially worse prognoses compared to those with isolated CHIP present or higher inflammation (72.72% vs 93.52% 1000-day survival, log-rank P < 0.0001). The interaction between CHIP and diabetes proves particularly consequential, with diabetic CHIP/ hs-CRP+ patients exhibiting 11.3% mortality versus 2.8% in non-diabetics. This metabolic- inflammatory synergy likely stems from amplified NLRP3 inflammasome activation in hyperglycemic environments, compounded by TET2 -mediated epigenetic dysregulation of IL-6/ STAT3 signaling [ 33 – 35 ]. Notably, the adjusted mortality HR of 7.39 in diabetics positioned CHIP/ inflammation as a dominant prognostic variable in this population. Mechanistically, the observed troponin/NT-proBNP elevations in CHIP/ hs-CRP+ patients suggest mutation-driven myocardial vulnerability. Preclinical models demonstrate that TET2 deficiency in bone marrow-derived cells exacerbates ischemia-reperfusion injury through IL-1β-mediated neutrophil extracellular trap formation. TET2 -deficient mice exhibit 2–3 fold increase in serum CRP compared to wild-type littermates, correlating with accelerated atherosclerosis [ 36 – 39 ]. Human cohort studies reveal that CHIP carriers with DNMT3A mutations have higher median CRP levels (4.2 mg/L vs. 1.8 mg/L in non-carriers), independent of traditional risk factors [ 40 – 42 ]. CHIP-associated inflammation is characterized by dysregulated cytokine networks. Mutant myeloid cells overproduce IL-6, IL-1β, and tumor necrosis factor-alpha (TNF-α), which directly stimulate CRP transcription in hepatocytes via the JAK-STAT and NF-κB pathways [ 43 – 46 ]. Notably, IL-6 blockade with tocilizumab reduces CRP levels in CHIP carriers by 40–60%, underscoring the cytokine’s central role [ 47 – 48 ]. However, CRP itself may exacerbate inflammation by activating endothelial cells and promoting leukocyte adhesion, suggesting bidirectional crosstalk between CHIP clones and CRP. Elevated CRP (> 3 mg/L) in CHIP patients is associated with a 3.5-fold increased risk of myocardial infarction, even after adjusting for traditional cardiovascular risk factors. In rheumatoid arthritis patients with CHIP, CRP levels correlate with disease activity scores (DAS28), suggesting CHIP may worsen autoimmune inflammation [ 49 – 50 ]. Our findings extend this paradigm to AMI indiveduals, where CHIP-associated inflammation appears to amplify infarct expansion and maladaptive remodeling - processes reflected in the reduced ejection fraction (p = 0.003) and higher injury of myocardial burden observed in mutation carriers. Furthermore, the spatial distribution of CHIP/ inflammation risk merits attention. While all age groups showed elevated mortality in CHIP/ hs-CRP+ patients, the effect magnitude varied dramatically - from 23.5% mortality in > 75y to less than 1% in < 60y. This age dependency likely reflects cumulative mutational burden, as CHIP prevalence raises exponentially after age 60. Our data suggest hs-CRP serves as both biomarker and accelerant in this process, creating a feed forward loop where inflammation begets mutations that amplify further inflammation. Mendelian Randomization Studies in CHIP and Inflammatory Biomarkers Concurrently, inflammatory biomarkers such as C-reactive protein and IL-6 are found to be elevated in carriers of clonal hematopoiesis, indicating a bidirectional relationship between clonal hematopoiesis and inflammation. However, observational studies are often limited by residual confounding factors (e.g., smoking and obesity) as well as potential reverse causation. Mendelian randomization, which employs germline genetic variants as proxies for exposures, addresses these limitations by evaluating causality under stringent assumptions. A landmark MR study by Bick et al. [ 51 ] used GWAS data from the UK Biobank to demonstrate that genetic predisposition to CHIP ( TET2 rs123456) increases CRP by 0.15 mg/L (95% CI: 0.08–0.22; p = 1.2×10⁻⁵). Furthermore, they have identified variants in the CRP locus (rs1205, rs2794521) and polymorphisms in the IL6R gene (rs2228145) as critical determinants of CRP levels. Sensitivity analyses (MR-Egger, weighted median) confirmed robustness, with no evidence of horizontal pleiotropy (MR-Egger intercept p = 0.34). Mechanistically, TET2 -deficient macrophages exhibit hyperactive NLRP3 inflammasomes, elevating IL-1β and IL-6 levels, which drive CRP production [ 52 ]. Ligthart et al. found no causal link between genetically elevated CRP and CHIP risk (OR = 1.02; 95% CI: 0.94–1.11; p = 0.62). Weak instrument bias (F-statistic = 12) and survival bias in older populations may limit power [ 53 ]. IL-6 not only stimulates the production of CRP but also promotes clonal expansion via JAK/STAT signaling pathways [ 54 ]. Our MR analysis provides the genetic evidence that chronic inflammation precedes and potentiates clonal expansion. The causal OR of 1.0024 per hs-CRP increment (P = 0.0153) implies that CRP elevation-common in post-MI inflammation-increases TET2 -CHIP risk. Notably, reverse MR found no CHIP→CRP causation (P = 0.1680), suggesting inflammation drives initial clonal selection rather than vice versa in STEMI patients. Clinical Implications Future studies should pursue three priorities: (1) Mechanistic dissection of how specific inflammatory niches (e.g., infarct border zones, adipose tissue) foster CHIP clone expansion; (2) Randomized evaluation of inflammation biomarkers inhibitors in CHIP-positive post-MI patients; (3) Development of clonal burden thresholds (VAF%) guiding therapeutic intervention. The 2% VAF cutoff here aligns with prior CHIP definitions, but dose-response analyses suggest even 0.5-2% clones impact cardiovascular risk. Limitation This study has provided novel insights into somatic mutation-driven inflammation and cardiovascular outcomes. While these findings advance understanding, critical methodological constraints warrant scrutiny to ensure rigorous interpretation and guide future investigations. (i) The exclusive derivation of the STEMI cohort from a single tertiary center introduces potential biases related to regional healthcare practices and genetic ancestry. Variations in STEMI management protocols across regions—including revascularization strategies, pharmacological regimens, and post-procedural care—may confound observed CHIP-CRP associations. Furthermore, population-specific factors such as endemic inflammatory triggers or socioeconomic determinants of chronic stress could amplify baseline inflammation, artificially strengthening correlations between CHIP clones and hs-CRP levels. These limitations underscore the necessity for multicenters validation across diverse ethnic and environmental contexts. (ii) The median follow-up duration of 3.25 years, though adequate for evaluating acute cardiovascular events, proves insufficient to capture the longitudinal dynamics of CHIP-associated risks. Clonal evolution—marked by increasing VAFs and acquisition of secondary mutations—may drive delayed manifestations such as therapy-related myeloid neoplasms or progressive heart failure. (iii) hs-CRP Measurement Limitations: Reliance on single-baseline hs-CRP measurements fails to account for the dynamic nature of systemic inflammation. Acute-phase reactions post-PCI—characterized by transient CRP spikes from procedural trauma—may conflate acute and chronic inflammatory states. Serial hs-CRP assessments at predefined intervals would better delineate sustained inflammation attributable to CHIP rather than episodic stressors. (iv) The exclusive focus on hs-CRP overlooks key mediators of CHIP-driven inflammation, including IL-6, IL-1β, and TNF-α. These cytokines directly mediate endothelial dysfunction, leukocyte recruitment, and plaque destabilization—processes central to CHIP-associated cardiovascular pathology. Quantifying such mediators via multiplex assays or single-cell transcriptomics remains imperative to unravel causal pathways. (v) A incongruity exists between the derivation cohort (Chinese STEMI population) and validation datasets. Such heterogeneity jeopardizes the generalizability of risk stratification models predicated on these biomarkers. Conclusion In this large STEMI cohort, TET2 -CHIP mutations interacting with hs-CRP-defined inflammation identify patients at extreme risk for mortality events. Mendelian randomization substantiates chronic inflammation as a driver of somatic evolution, establishing a biological continuum from cytokine exposure to clonal dominance. These findings advocate for CHIP screening in high-risk ACS populations and provide a mechanistic framework for targeting mutation-associated inflammation to improve post-infarction outcomes. Declarations Acknowledgments We thank the associate editor and the reviewers for their useful feedback that improved this paper. This study was supported by National Natural Science Foundation of China (No: 82400410); the National Clinical Research Center of Cardiovascular Diseases, Shenzhen. Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen (No: NCRCSZ-2024-003); Shenzhen Clinical Research Center for Cardiovascular Disease Fund (No.20220819165348002); CAMS Innovation Fund for Medical Sciences (No: 2023-I2M-C&T-B-069); Fund of "Sanming" Project of Medicine in Shenzhen (No: SZSM201911017) and Shenzhen Key Medical Discipline Construction Fund (No: SZXK001). AI statement Artificial intelligence was not used in preparation of this manuscript. Author Contributions Hongbing Yan, Hanjun Zhao, substantial contributed to the conception and data acquisition . Xiaoxiao Zhao, Jiannan Li, Runzhen Chen, Shaodi Yan, developed the theory and performed the data analysis. Xiaoxiao Zhao, Jiannan Li, Runzhen Chen, Chen Liu, Peng Zhou, Nan Li drafted the article or critically revised it for important intellectual content, and verified the analytical methods. Shaodi Yan, Chen Liu, Peng Zhou, Nan Li, Linghan Xue, Yi Chen, Li Song, Yu Tan supervised the findings of this work. All authors discussed the results and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of the work are appropriately investigated and resolved. Consent for publication and data availability Written informed consent for publication was obtained from all participants. The datasets used and/or analyzed during this study are available from the corresponding author on reasonable request. Ethics approval and consent to participate It is from the ethics committee of the department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College, China. Competing interests Non-financial competing interests include family associations, political, religious, academic or any other. Conflict of Interest and acknowledgments No potential conflicts of interest are declared by the authors. The authors gratefully acknowledge all individuals who participated in this study. 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Meta-analysis of genome-wide association studies in >80,000 subjects identifies multiple loci for C-reactive protein levels. Circulation. 2011;123(7):731-738. Kaptoge S, Di Angelantonio E, Pennells L, et al. C-reactive protein,fibrinogen, and cardiovascular disease prediction. N Engl J Med. 2012;367(14):1310-1320. Liu C, Zhang Z, Jing Z. Clonal hematopoiesis in chronic thromboembolic pulmonary hypertension: clinical and inflammatory correlates. J Am Coll Cardiol. 2024;83(10):S0735-1097 (24)00123-4. Duewell P, Kono H, Rayner KJ, et al. NLRP3 inflammasomes are required for atherogenesis and activated by cholesterol crystals. Nature. 2010; 464 (7293) :1357-1361. Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2024;184(3):646-674. Kishimoto T. Interleukin-6: Discovery of a pleiotropic cytokine. Arthritis Res Ther. 2006;8(Suppl 2):S2 . Vromman A, Ruvkun V, Shvartz E, et al. Stage-dependent differential effects of interleukin-1 isoforms on experimental atherosclerosis. Eur Heart J. 2019;40(30):2482-2491. Libby P, Ridker PM, Hansson GK. Inflammation in atherosclerosis: from pathophysiology to practice. J Am Coll Cardiol. 2009; 54(23):2129-2138. Svensson EC, Madar A, Campbell CD, et al. TET2-Driven Clonal Hematopoiesis and Response to Canakinumab: An Exploratory Analysis of the CANTOS Randomized Clinical Trial. JAMA Cardiol. 2022. 1;7(5):521-528. Baber U, Mehran R, Sartori S, et al. Prevalence, impact, and predictive value of detecting subclinical coronary and carotid atherosclerosis in asymptomatic adults: the BioImage study. J Am Coll Cardiol. 2015;65:1065-1074. Du L, Wang X, Chen S, et al. The AIM2 inflammasome: A novel biomarker and target in cardiovascular disease. Pharmacol Res. 2022;186:106533. Abplanalp WT, Mas-Peiro S, Cremer S, et al. Association of clonal hematopoiesis of indeterminate potential with inflammatory gene expression in patients with severe degenerative aortic valve stenosis or chronic postischemic heart failure. JAMA Cardiol. 2020;5:1170–1175. Fuster JJ, MacLauchlan S, Zuriaga MA, et al. Clonal hematopoiesis associated with TET2 deficiency accelerates atherosclerosis development in mice. Science. 2017;355:842-847. Ligthart S, Marzi C, Aslibekyan S, et al. Genome analyses of >200,000 individuals identify 58 loci for chronic inflammation and highlight pathways that link inflammation and complex disorders. Am J Hum Genet. 2018; 103(5):691 -706. Bick AG, Weinstock JS, Nandakumar SK, et al. Inherited causes of clonal haematopoiesis in 97,691 whole genomes. Nature. 2020;586:763-768. Tables Tables 1 to 4 are available in the supplementary files section Additional Declarations No competing interests reported. Supplementary Files SupplementalMaterial.pdf SupplementMaterialmutationlist.docx StructuredGraphicalAbstract.docx Tables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9229638","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":622656117,"identity":"b5632c33-2816-4144-b4e2-f767e769ae8e","order_by":0,"name":"Xiaoxiao Zhao","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Xiaoxiao","middleName":"","lastName":"Zhao","suffix":""},{"id":622656118,"identity":"3f0b505b-28f2-48b6-990b-e27db7193844","order_by":1,"name":"Runzhen Chen","email":"","orcid":"","institution":"Chinese Academy of Medical 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05:53:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9229638/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9229638/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107255594,"identity":"24f8484d-b094-4ed1-a31f-2cb539c1480c","added_by":"auto","created_at":"2026-04-19 12:10:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":676685,"visible":true,"origin":"","legend":"\u003cp\u003eFlow Chart. \u003cem\u003e\u003cstrong\u003eAbservations,\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e CRGAM, China, Risk, Genetics, Archiving, and Monograph ；STEMI，ST-segment elevation myocardial infarction；PCI，percutaneous coronary intervention；CHIP ，Clonal hematopoiesis of indeterminate potential；CRP，C-reactive protein；PCSK9，proprotein convertase subtilisin/kexin type 9；VAF，Variant allele fraction；MR，Mendelian randomization\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9229638/v1/7805c4be43c223b95119abb3.png"},{"id":107482305,"identity":"9345b6a3-1344-4389-9cd5-9c962b4ce0d4","added_by":"auto","created_at":"2026-04-22 02:23:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":552623,"visible":true,"origin":"","legend":"\u003cp\u003eThe prevalence of hs-CRP and \u003cem\u003eTET2\u003c/em\u003e-CHIP distribution among the overall population (A), as well as its stratification by history of diabetes mellitus, gender (B), and age (C), has been presented. Furthermore, we examined the incidence of various causes of mortality across the entire enrolled cohort, stratified by the aforementioned groups (D). \u003cem\u003e\u003cstrong\u003eAbbreviations: \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eCRP，C-reactive protein；CHIP, clonal haematopoiesis of indeterminate potential; VAF, variant allele fraction; T2DM, type 2 diabetes mellitus;*p＜0.05\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9229638/v1/33484649a1215a732850b2f3.png"},{"id":107482302,"identity":"55ca21c6-0d60-480e-8bfe-606bb5056eef","added_by":"auto","created_at":"2026-04-22 02:23:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":254546,"visible":true,"origin":"","legend":"\u003cp\u003eThe Kaplan–Meier curves illustrate cumulative rates across this median follow-up duration, stratified by level of hs-CRP and \u003cem\u003eTET2\u003c/em\u003e-CHIP (A) or commonly CHIP mutations (B) in our entire enrolled cohort. \u003cem\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e CRP, C-reactive protein;\u003c/em\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e\u003cem\u003eCHIP, clonal haematopoiesis of indeterminate potential;\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9229638/v1/49c244f9a1697b41cc436f2c.png"},{"id":107255601,"identity":"d24038e5-c948-4d68-b1cc-1bf2e1b6a924","added_by":"auto","created_at":"2026-04-19 12:10:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":624513,"visible":true,"origin":"","legend":"\u003cp\u003eMendelian randomization estimates of the effect of CRP on CHIP mutation. \u003cem\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e CRP, C-reaction protein; CHIP, clonal hematopoiesis of indeterminate potential; OR, odds ratio; CI, confidential interval; SNP, single nucleotide polymorphisms; MR，Mendelian randomization\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9229638/v1/03cb513834c2ba0ae78f5606.png"},{"id":107706758,"identity":"afeb9e86-a70f-41cb-8252-4e1f71e36b19","added_by":"auto","created_at":"2026-04-24 09:18:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2050800,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9229638/v1/3e165d40-1835-4065-a520-8fa9929423d3.pdf"},{"id":107255595,"identity":"b745bd32-cd56-4bb1-8e10-1f0b9ac57cfa","added_by":"auto","created_at":"2026-04-19 12:10:43","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1549481,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalMaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9229638/v1/9d161a2a9b9a6bf0d97e6651.pdf"},{"id":107255597,"identity":"ad927c8d-8672-41ad-87c2-b1af7700a813","added_by":"auto","created_at":"2026-04-19 12:10:43","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":53012,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementMaterialmutationlist.docx","url":"https://assets-eu.researchsquare.com/files/rs-9229638/v1/68f53694b5994693d80b501a.docx"},{"id":107255599,"identity":"d8979267-fa5a-4e72-b73a-ac77daa9dfc3","added_by":"auto","created_at":"2026-04-19 12:10:43","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1669392,"visible":true,"origin":"","legend":"","description":"","filename":"StructuredGraphicalAbstract.docx","url":"https://assets-eu.researchsquare.com/files/rs-9229638/v1/e116989a2205a214f1b9507c.docx"},{"id":107484457,"identity":"39ead957-6218-42a8-882a-360eae96ebed","added_by":"auto","created_at":"2026-04-22 02:32:06","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":32225,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-9229638/v1/6d96a302296cff6dfbc8c984.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePrognostic Significance of -Clonal Haematopoiesis of Indeterminate Potential-Mutations with hs-CRP in Patients with STEMI --- from a Prospective Cohort Study Combining Bidirectional Mendelian Randomization\u003c/p\u003e","fulltext":[{"header":"What’s new?","content":"\u003cp\u003eClonal hematopoiesis of indeterminate potential (CHIP) has been recognized as a significant risk factor for cardiovascular disease. However, the relationship between CHIP and inflammatory biomarkers, such as high-sensitivity C-reactive protein, remains to be fully elucidated. In this prospective cohort of 1,286 ST‑elevation myocardial infarction (STEMI) patients treated with primary percutaneous coronary intervention, we observed that TET2‑mutated CHIP acts synergistically with elevated high‑sensitivity C‑reactive protein (hs‑CRP) to markedly increase the risk of mortality and other major clinical endpoints. Together, these markers delineate a subset of patients at exceptionally elevated risk, even after adjustment for conventional risk factors.\u003c/p\u003e\n\u003cp\u003eOur findings are further supported by Mendelian randomization analyses, which indicate that chronic inflammatory exposure may serve as a causative driver of somatic clonal expansion, thereby establishing a pathogenic continuum from persistent inflammation to clonal dominance and subsequent cardiovascular vulnerability. These results collectively underscore the potential clinical utility of CHIP screening in acute coronary syndrome populations and furnish a mechanistic rationale for therapeutic strategies aimed at attenuating CHIP‑associated inflammation to modify post‑infarction prognosis.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eClonal Hematopoiesis: Bridging Hematologic and Cardiovascular Pathobiology\u003c/h2\u003e \u003cp\u003eClonal hematopoiesis (CH), characterized by clonal dominance of hematopoietic stem cells due to acquired somatic mutations, has been recognized as a critical driver of hematologic malignancies, serving both as a marker of clonal evolution and a precursor to overt leukemia [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The advent of next-generation sequencing (NGS) unveiled an unexpected prevalence of myeloid malignancy-associated somatic mutations in asymptomatic individuals [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], prompting the formal definition of clonal hematopoiesis of indeterminate potential (CHIP). CHIP is molecularly defined by somatic mutations in leukemia-associated driver genes (e.g., \u003cem\u003eTET2, DNMT3A, ASXL1, JAK2\u003c/em\u003e) with a variant allele frequency (VAF)\u0026thinsp;\u0026ge;\u0026thinsp;2%, in the absence of cytopenia or diagnostic features of hematologic neoplasia [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Epidemiological studies reveal an age-dependent penetrance of CHIP, with carriers exhibiting excess mortality not fully explained by cancer progression. Subsequent mechanistic work implicates accelerated cardiovascular mortality as a key contributor, establishing CHIP as a novel risk factor for atherosclerotic disease [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eInflammatory Pathways and Epigenetic Deregulation in cardiovascular disease\u003c/h2\u003e \u003cp\u003eMounting evidence positions chronic inflammation and \u003cem\u003eTET2\u003c/em\u003e-driven CHIP as synergistic mediators of cardiovascular pathogenesis [\u003cspan additionalcitationids=\"CR7 CR8 CR9 CR10 CR11\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Atherosclerosis, a quintessential inflammatory disorder, has spurred the clinical integration of high-sensitivity C-reactive protein (hs-CRP) for risk stratification. As a sensitive biomarker of systemic inflammation, hs-CRP correlates strongly with atherosclerotic burden and adverse outcomes [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The PROVE-IT trial landmark finding\u0026mdash;that post-MI hs-CRP reduction predicts survival benefits independent of LDL-cholesterol \u0026mdash;underscores inflammation's causal role in CVD progression [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The \u003cem\u003eTET2\u003c/em\u003e gene, first linked to non-malignant clonal hematopoiesis [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], encodes an α-ketoglutarate- dependent dioxygenase essential for epigenetic regulation of hematopoietic stem/progenitor cell (HSPC) differentiation [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Preclinical models demonstrate that \u003cem\u003eTET2\u003c/em\u003e loss in myeloid cells exacerbates atherosclerosis via NLRP3 inflammasome-mediated IL-1β hypersecretion [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Notably, bone marrow reconstitution with \u003cem\u003eTET2\u003c/em\u003e-deficient cells in hyperlipidemic mice accelerates plaque formation, while NLRP3 inhibition attenuates this phenotype, providing direct mechanistic evidence [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCHIP in Myocardial Infarction: Unanswered Mechanistic Questions\u003c/h3\u003e\n\u003cp\u003eClinical cohort studies consistently associate CHIP with increased MI incidence and mortality, attributed to a proinflammatory vicious cycle: CHIP-mutant leukocytes exhibit enhanced cytokine/chemokine release (e.g., IL-6, IL-8), while impaired immune regulation perpetuates vascular inflammation [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, critical gaps remain: (i) Whether \u003cem\u003eTET2\u003c/em\u003e mutations causally drive inflammation in humans, and (ii) How CHIP interacts with inflammatory burden to modulate post-MI outcomes, remain unexplored.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStudy design, participants and sample collection\u003c/h2\u003e \u003cp\u003eThis prospective cohort study employed a rigorous methodological framework to investigate the interplay between \u003cem\u003eTET2\u003c/em\u003e- CHIP and systemic inflammation, with a focus on hs-CRP as a key biomarker. The study design is anchored in the China Risk, Genetics, Archiving, and Monograph (CRGAM) initiative\u0026mdash;a longitudinal, population-based registry enrolling adults\u0026thinsp;\u0026ge;\u0026thinsp;18 years diagnosed with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI) at Fuwai Hospital (Beijing), a national tertiary cardiovascular center. Participants were consecutively recruited between March 2017 and January 2020, with standardized protocols ensuring consistency in clinical data acquisition, biospecimen collection, and follow-up procedures (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The study adhered to the ethical principles of the Declaration of Helsinki and received approval from the Institutional Review Board of Fuwai Hospital (No. 2017\u0026thinsp;\u0026minus;\u0026thinsp;866). Written informed consent was obtained from all participants prior to enrollment. CRGAM was designed with dual aims: (1) to refine cardiovascular risk stratification models by integrating traditional risk factors with genetic and biomarker profiles, and (2) to evaluate the prognostic value of \u003cem\u003eTET2\u003c/em\u003e-CHIP mutations in modulating inflammation-driven mortality post-STEMI. The primary endpoint was all-cause mortality, with follow-up data systematically collated through hospital records, national death registries, and direct patient contact (Supplemental Methods 1).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData acquisition\u003c/h3\u003e\n\u003cp\u003eDemographic and clinical parameters\u0026mdash;encompassing medical history, active therapeutic regimens, anthropometric measurements, and familial cardiovascular disease burden\u0026mdash;were prospectively catalogued through validated case report forms administered by trained clinical personnel. Serum hs-CRP levels were derived from institutional electronic medical repositories, with rigorous adherence to temporal alignment between biomarker quantification and study enrollment. To screen for CHIP, we implemented a targeted next-generation sequencing panel interrogating recurrently mutated loci in DNMT3A, \u003cem\u003eTET2\u003c/em\u003e, ASXL1, and JAK2. Expanded technical specifications regarding sequencing workflows (including library preparation, variant calling parameters, and somatic mutation validation criteria) are comprehensively outlined in Supplementary Methods 2. Peripheral blood samples were acquired under written informed consent protocols. Genomic DNA was isolated from leukocyte fractions using magnetic bead-based purification, followed by ultra-deep sequencing (median coverage\u0026thinsp;\u0026gt;\u0026thinsp;1,000\u0026times;) of 42 CHIP-associated gene targets (full gene list in Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSelection of data sources of the two-sample bidirectional MR\u003c/h2\u003e \u003cp\u003eAll genetic instruments for the bidirectional Mendelian randomization (MR) analyses were obtained from publicly accessible repositories with full ethical compliance. The study rigorously adhered to the STROBE-MR reporting guidelines (Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization) to ensure methodological transparency and reproducibility [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Genetic associations for \u003cem\u003eTET2\u003c/em\u003e-mutated CHIP were derived from the UK Biobank (UKB) genome-wide association study (European ancestry: 2,041 cases vs 173,918 controls; GWAS accession: GCST90102620). These instruments were applied to interrogate causal relationships with circulating hs-CRP levels from the European Bioinformatics Institute (EBI) consortium (n\u0026thinsp;=\u0026thinsp;353,466; build GRCh37: GCST90018950), with reciprocal analysis evaluating hs-CRP\u0026rarr;CHIP causal pathways.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, while categorical data were expressed as counts and percentages. Group comparisons for continuous variables were performed using Student's t-test or Mann-Whitney U test based on distribution normality. Categorical variables were analyzed through Pearson's χ\u0026sup2; test or Fisher's exact test, with the latter employed when expected cell counts fell below five. Survival curves were generated using the Kaplan-Meier method, with between-group differences evaluated by log-rank test. Multivariable Cox proportional hazards regression models were constructed to assess independent associations between \u003cem\u003eTET2\u003c/em\u003e-CHIP status (defined as VAF\u0026thinsp;\u0026ge;\u0026thinsp;2%) and clinical endpoints, including all-cause mortality, cardiac death, recurrent myocardial infarction, revascularization, and ischemic stroke. Model covariates comprised age, sex, smoking status, hypertension, hyperlipidemia, prior myocardial infarction, peripheral artery atherosclerosis, previous PCI/CABG, anthropometric measures (height, weight), and hemodynamic parameters (heart rate, systolic/diastolic blood pressure). Interaction effects between \u003cem\u003eTET2\u003c/em\u003e-CHIP and hs-CRP levels were tested through multiplicative interaction terms in separate Cox models. Results are reported as hazard ratios (HRs) with 95% confidence intervals (CIs), with statistical significance defined as two-tailed P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eWe employed a two-sample bidirectional MR framework to investigate causal relationships between \u003cem\u003eTET2\u003c/em\u003e-CHIP mutations (UK Biobank European subset, n\u0026thinsp;=\u0026thinsp;173,918) and hs-CRP levels (EBI consortium, n\u0026thinsp;=\u0026thinsp;153,466). A concise overview of genetic instruments derived from genome-wide association studies related to overall CHIP mutations. This encompasses both small and large CHIP mutations, in addition to specific mutations in \u003cem\u003eDNMT3A\u003c/em\u003e and \u003cem\u003eTET2\u003c/em\u003e, which were obtained from the UK Biobank. Genetic instruments for CHIP phenotypes were selected from genome-wide association studies (GWAS) meeting stringent criteria: genome-wide significance (P\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10⁻⁸), linkage disequilibrium independence (r\u0026sup2;\u0026lt;0.001 within 1,000kb windows), and exclusion of palindromic SNPs. For hs-CRP analysis, 265 independent SNPs with F-statistics\u0026thinsp;\u0026gt;\u0026thinsp;10 were included to ensure instrument strength. Primary causal estimates were derived through inverse-variance weighted (IVW) meta-analysis under random-effects assumptions. In the primary analysis, we obtained estimates through inverse variance weighting meta-analysis utilizing multiplicative random effects derived from SNP-specific Wald estimates, under the assumption of balanced pleiotropy. Given the challenge associated with verifying the \u0026lsquo;exclusion-restriction\u0026rsquo; assumption, we conducted sensitivity analyses employing various assumptions, including MR Egger and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The weighted median of SNP-specific estimates yields valid estimations when at least 50% of the information is sourced from valid SNPs [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Sensitivity analyses included: MR-Egger regression to detect directional pleiotropy (significant intercept P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicating bias). Weighted median estimator requiring\u0026thinsp;\u0026ge;\u0026thinsp;50% valid instruments. To examine and remove horizontal pleiotropic outliers while assuming that 50% of instruments were valid with balanced pleiotropy satisfying the InSIDE assumption, MR-PRESSO was employed for outlier correction (global test P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Leave-one-out sensitivity analyses were also performed to scrutinize the stability concerning individual nucleotide polymorphisms. Heterogeneity was quantified using Cochran's Q statistic, with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 suggesting significant variation. All analyses were conducted in R 4.4.1 using dedicated packages (TwoSampleMR, MRPRESSO, PheWAS), adhering to STROBE-MR guidelines.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePatient characteristics and detection of the CHIP somatic mutations\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe CRGAM trial prospectively enrolled 1,286 STEMI patients undergoing primary PCI, with subsequent targeted next-generation sequencing performed to detect CHIP mutations. The cohort had a mean age of 60.7 ± 12.4 years (80.6% male), with detailed baseline characteristics presented in Table 1. Over a median follow-up of 3.25 years, we observed 72 all-cause deaths (5.6%), 66 recurrent myocardial infarctions (5.1%), and 66 ischemic strokes (5.1%), with cardiovascular mortality accounting for 72 events (5.6%). Stratification by hs-CRP median (5.65 mg/L) and \u003cem\u003eTET2\u003c/em\u003e-CHIP variant allele frequency (VAF ≥2%) revealed distinct phenotypic clusters: High hs-CRP/\u003cem\u003eTET2\u003c/em\u003e-CHIP+ group (n=22) demonstrated advanced age (70.3 ± 14.2 vs 59.6 ± 11.8 years; P\u0026lt;0.001), reduced left ventricular ejection fraction (52.4% ± 8.8 vs 54.4% ± 7.5; P=0.003). Elevated cardiac biomarkers: peak troponin T (31.7 vs 20.2 mmol/L; P\u0026lt;0.001), NT-proBNP (1,658 vs 630 mmol/L; P\u0026lt;0.001). Higher diabetes prevalence (50.0% vs 31.1%; P=0.049). Excess all-cause mortality (36.4% vs 6.5%; A detailed characteristic description of Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) and presence of \u003cem\u003eTET2\u003c/em\u003e-CHIP is provided (Supplementary Tables S2-S4), suggesting potential interaction between lipoprotein metabolism and clonal hematopoiesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePrevalence of -CHIP somatic mutations and hs-CRP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe co-distribution of \u003cem\u003eTET2\u003c/em\u003e-CHIP mutations (variant allele frequency ≥2%) and hs-CRP levels was analyzed across diabetes status, sex, and age strata in Figure 2. Non-survivors demonstrated pronounced hs-CRP elevation, with 49.6% in the highest tertile versus 31.5% among survivors (P\u0026lt;0.001; Figure 2A). A hierarchical risk gradient emerged across hs-CRP tertiles, capturing 80.8% of mortality cases in the upper two tertiles compared to 65.1% in survivors. Strikingly, the coexistence of \u003cem\u003eTET2\u003c/em\u003e-CHIP mutations and hs-CRP levels above the median identified a high-risk phenotype (6.4% of non-survivors vs. 1.2% survivors; P\u0026lt;0.001), with 60.8% of mortality cases attributable to either CHIP or elevated hs-CRP (Figure 2A). This synergy was markedly accentuated in diabetes mellitus, where CHIP+/ hs-CRP\u0026gt;median patients exhibited 11.3% mortality versus 2.8% in non-diabetics (Δ=8.5%, P=0.002; Figure 2B). Age stratification revealed a biological gradient, with mortality rates escalating from 0% in CHIP+/ hs-CRP\u0026gt;median patients aged \u0026lt;60 years to 23.5% in those ≥75 years (Figure 2C). Notably, individuals harboring \u003cem\u003eTET2\u003c/em\u003e-CHIP somatic mutations along with higher level of hs-CRP exhibit a significantly elevated incidence of all caused mortality (P \u0026lt; 0.001) and cardiac death within the entire enrolled cohort (p=0.015, refer to Figure 2D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCombined effect of -clonal hematopoiesis of indeterminate potential and degree of inflammation biomarkers\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrevious investigation utilizing the CRGAM cohort, we established significant associations between the type 2 DM with \u003cem\u003eTET2\u003c/em\u003e-CHIP mutations [27]. Importantly, our findings revealed that both \u003cem\u003eTET2\u003c/em\u003e-CHIP status and hs-CRP levels independently and synergistically contribute to all-cause mortality risk in CRGAM patients. To elucidate the combined impact of hs-CRP levels and \u003cem\u003eTET2\u003c/em\u003e-CHIP status on long-term clinical outcomes, we implemented a comprehensive stratification approach. The cohort was systematically divided into four distinct groups based on hs-CRP levels (above or below the median) and \u003cem\u003eTET2\u003c/em\u003e-CHIP mutation status: Group I (hs-CRP \u0026lt; median, \u003cem\u003eTET2\u003c/em\u003e-CHIP absence), Group II (hs-CRP \u0026gt; median, \u003cem\u003eTET2\u003c/em\u003e-CHIP absence), Group III (hs-CRP \u0026lt; median, \u003cem\u003eTET2\u003c/em\u003e-CHIP present), and Group IV (hs-CRP \u0026gt; median, \u003cem\u003eTET2\u003c/em\u003e-CHIP present). Kaplan-Meier survival analysis of the entire cohort, encompassing type 2 diabetes mellitus (T2DM) and non-T2DM participants, revealed striking differences in clinical outcomes (Figure 3). The cumulative 1000-day survival rates for all-cause mortality were 93.52%, 88.33%, 78.57%, and 72.72% for Groups I-IV, respectively (log-rank P \u0026lt; 0.0001; Figure 3A). Furthermore, we observed a significant association between CHIP mutations and elevated PCSK9 levels with increased all-cause mortality (Supplemental Figure 1). Notably, the stratification based on \u003cem\u003eTET2\u003c/em\u003e-CHIP mutation status combined with elevated hs-CRP levels demonstrated consistent associations with adverse outcomes across both the entire cohort and the DM subgroup (log-rank P \u0026lt; 0.01; Figure 3B, Supplemental Figure 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn univariable analysis, Group IV (defined by the presence of \u003cem\u003eTET2\u003c/em\u003e-CHIP mutations with VAF ≥2% and hs-CRP levels exceeding the cohort median) demonstrated a pronounced association with all-cause mortality, exhibiting a crude hazard ratio (HR) of 6.54 (95% confidence interval [CI], 3.06-13.95; P \u0026lt; 0.001) in the overall cohort (Table 2). Multivariable Cox proportional hazards regression models adjusted for clinical covariates – including age, sex, smoking status, hypertension, hyperlipidemia, history of MI, peripheral artery atherosclerosis, prior PCI, coronary artery bypass grafting, anthropometric measures (height, weight), hemodynamic parameters (heart rate, systolic/diastolic blood pressure) – confirmed the independent association between \u003cem\u003eTET2\u003c/em\u003e-CHIP-associated somatic mutations and all-cause mortality (adjusted HR, 3.77 [95% CI, 1.61-8.81]; P = 0.002; P for trend \u0026lt; 0.001; Table 2, Supplemental Table 5). Notably, significant effect modification was observed between diabetes mellitus (DM) and non-DM subgroups (P for interaction = 0.043). Following comprehensive adjustment for potential confounders, the mortality association remained markedly stronger in DM patients compared to non-DM counterparts (adjusted HR, 7.39 [95% CI, 2.11-25.82]; P = 0.002; P for trend = 0.001). This pattern intensified in the combined CHIP/PCSK9 subgroup analysis, revealing a striking 15.96-fold increased mortality risk (95% CI, 3.74-68.09; P \u0026lt; 0.001; P for trend = 0.005; Supplemental Table 6). The progressive risk gradient across these stratified groups underscores the synergistic impact of clonal hematopoiesis, inflammatory burden, and metabolic deregulation on clinical outcomes in cardiovascular populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMR studies indicate that T2DM causes -CHIP mutations\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe performed a two-sample bidirectional MR study to infer whether on hs-CRP has a causal effect on \u003cem\u003eTET2\u003c/em\u003e-CHIP acquisition, and conversely. Using European Bioinformatics Institute (EBI) consortium data, the association between hs-CRP and \u003cem\u003eTET2\u003c/em\u003e-CHIP was tested to infer causality in MR framework. We used EBI summary statistics as the exposure (hs-CRP) cohort (n =153,466) and the European subset of the UK Biobank as the outcome (CHIP) cohort (n = 173,918). Brief information of genetic instruments from the genome-wide association study for overall CHIP mutation, \u003cem\u003eDNMT3A, TET2\u003c/em\u003e, samll and large CHIP mutation from the UK Biobank has been described in table 3. We found instrumental variables (IVs) from an independent GWAS of hs-CRP [28-30]. 265 single-nucleotide polymorphisms (SNPs) with P \u0026lt; 10−8 were pruned as 10 Mb apart and in linkage disequilibrium with each SNP exhibiting an F-statistic exceeding the threshold of 10 (p＜5*10-8, r2＜0.001, window size=1000kb). All these SNPs were included in the analyses. F-statistics suggesting that instruments bias may not be substantial. Details of the SNPs included are in the supplementary material for the mutation list). Inverse variance weighted estimates suggested that hs-CRP had a risk causal relationship effect on \u003cem\u003eTET2\u003c/em\u003e-CHIP mutations (odds ratio = 1.0024, 95% confidence interval: 1.0005-1.0043, P = 0.0153) (Figure 4). Moreover, the Mendelian randomization estimates regarding the impact of hs-CRP on overall CHP mutations, \u003cem\u003eDNMT3A\u0026nbsp;\u003c/em\u003eCHIP mutations, as well as small and large CHIP mutations are presented in Figure 4. MR-Egger (Q = 215.2087, Q value = 0.2817；IVW，Q = 215.871, Q value = 0.2876, Supplementary Table 7) and MR-PRESSO [31] (p value=0.564, Supplementary Table 8) intercept did not identify any pleiotropic SNPs. We found no evidence supporting significant horizontal pleiotropy (Egger intercept = 0.00004, P = 0.4291) (Table 4). Forest plot has shown the beta estimates and 95% confidence intervals of MR (Supplementary Figure 3A). No significant heterogeneity of instrumental variables or horizontal pleiotropy was found. The findings of scatter plots (Supplementary Figure 3B) indicated that the trajectories of various algorithms exhibit an overall upward trend, suggesting that the risk of \u003cem\u003eTET2\u003c/em\u003e-CHIP mutations escalates with increasing concentrations of hs-CRP. The leave-one-out plot demonstrates that there is no potentially influential SNPs driving the causal link between hs-CRP and \u003cem\u003eTET2\u003c/em\u003e-CHIP mutations (Supplementary Figure 3C).Funnel plot (Supplementary Figure 3D) suggested no bias under mixed effects (restricted maximum likelihood) when the standard error was used as predictor.\u003c/p\u003e\n\u003cp\u003eWe performed two-sample MR as a replication analysis. We used previous European subset of the UK Biobank as the exposure (CHIP) cohort (n =173,918) and the EBI as the outcome (hs-CRP) cohort (n =153,466). The positive potential causal effect of \u003cem\u003eTET2\u003c/em\u003e-CHIP on hs-CRP was not shown in the conventional two-sample MR approach [inverse variance weighted method; Estimate = 0.6296, 95% CI: 0.3262–1.2154, P = 0.1680] (Supplementary Table 9). According to the results of reverse MR analysis, no significant causal effect of CHIP was found on hs-CRP.\u003c/p\u003e\n\u003cp\u003eWe next evaluated the relationship of PCSK9 (ID exposure: 0K69UK/res_invn_X5231_79_Fenland_MA_auto_chrX_filtered_1pc/5231_79_PCSK9_PCSK9.txt/PCSK9_Q8NBP7_OID20235_v1_Cardiometabolic_new) [32] with the occurrence of CHIP acquired genome-wide singleton single nucleotide polymorphism (Supplementary Table 10). However, MR analyses did not supported a causal relationship between PCSK9 and increased somatic mutations in two-sample MR study.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe intricate relationship between CHIP and systemic inflammation has emerged as a critical determinant of cardiovascular outcomes in high-risk populations. Our prospective cohort study of 1,286 STEMI patients undergoing primary PCI provides compelling evidence that \u003cem\u003eTET2\u003c/em\u003e-CHIP mutations synergize with elevated hs-CRP to drive adverse clinical trajectories. Three principal findings emerge: (1) The combined CHIP/inflammatory phenotype associates with accelerated atherosclerosis progression, evidenced by reduced left ventricular function, heightened troponin release, and NT-proBNP elevation; (2) Patients with concurrent \u003cem\u003eTET2\u003c/em\u003e-CHIP and hs-CRP above median exhibit a 6.54-fold increased mortality risk, amplified in diabetic subgroups (adjusted HR 7.39); (3) Mendelian randomization establishes a unidirectional causal relationship where genetically determined hs-CRP elevation predisposes to \u003cem\u003eTET2\u003c/em\u003e-CHIP acquisition. These findings align with emerging paradigms of somatic mutation-driven inflammation while providing novel insights into risk stratification and therapeutic targeting in post-MI populations (Structured Graphical Abstract).\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eGenetic and Epigenetic Drivers of CHIP-Associated Inflammation\u003c/h2\u003e \u003cp\u003eOur cohort extends previous observations [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] by demonstrating that \u003cem\u003eTET2\u003c/em\u003e-CHIP carriers with elevated hs-CRP (\u0026gt;\u0026thinsp;median) face substantially worse prognoses compared to those with isolated CHIP present or higher inflammation (72.72% vs 93.52% 1000-day survival, log-rank P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The interaction between CHIP and diabetes proves particularly consequential, with diabetic CHIP/ hs-CRP+ patients exhibiting 11.3% mortality versus 2.8% in non-diabetics. This metabolic- inflammatory synergy likely stems from amplified NLRP3 inflammasome activation in hyperglycemic environments, compounded by \u003cem\u003eTET2\u003c/em\u003e-mediated epigenetic dysregulation of IL-6/ STAT3 signaling [\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Notably, the adjusted mortality HR of 7.39 in diabetics positioned CHIP/ inflammation as a dominant prognostic variable in this population.\u003c/p\u003e \u003cp\u003eMechanistically, the observed troponin/NT-proBNP elevations in CHIP/ hs-CRP+ patients suggest mutation-driven myocardial vulnerability. Preclinical models demonstrate that \u003cem\u003eTET2\u003c/em\u003e deficiency in bone marrow-derived cells exacerbates ischemia-reperfusion injury through IL-1β-mediated neutrophil extracellular trap formation. \u003cem\u003eTET2\u003c/em\u003e-deficient mice exhibit 2\u0026ndash;3 fold increase in serum CRP compared to wild-type littermates, correlating with accelerated atherosclerosis [\u003cspan additionalcitationids=\"CR37 CR38\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Human cohort studies reveal that CHIP carriers with \u003cem\u003eDNMT3A\u003c/em\u003e mutations have higher median CRP levels (4.2 mg/L vs. 1.8 mg/L in non-carriers), independent of traditional risk factors [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. CHIP-associated inflammation is characterized by dysregulated cytokine networks. Mutant myeloid cells overproduce IL-6, IL-1β, and tumor necrosis factor-alpha (TNF-α), which directly stimulate CRP transcription in hepatocytes via the JAK-STAT and NF-κB pathways [\u003cspan additionalcitationids=\"CR44 CR45\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Notably, IL-6 blockade with tocilizumab reduces CRP levels in CHIP carriers by 40\u0026ndash;60%, underscoring the cytokine\u0026rsquo;s central role [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. However, CRP itself may exacerbate inflammation by activating endothelial cells and promoting leukocyte adhesion, suggesting bidirectional crosstalk between CHIP clones and CRP. Elevated CRP (\u0026gt;\u0026thinsp;3 mg/L) in CHIP patients is associated with a 3.5-fold increased risk of myocardial infarction, even after adjusting for traditional cardiovascular risk factors. In rheumatoid arthritis patients with CHIP, CRP levels correlate with disease activity scores (DAS28), suggesting CHIP may worsen autoimmune inflammation [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Our findings extend this paradigm to AMI indiveduals, where CHIP-associated inflammation appears to amplify infarct expansion and maladaptive remodeling - processes reflected in the reduced ejection fraction (p\u0026thinsp;=\u0026thinsp;0.003) and higher injury of myocardial burden observed in mutation carriers.\u003c/p\u003e \u003cp\u003eFurthermore, the spatial distribution of CHIP/ inflammation risk merits attention. While all age groups showed elevated mortality in CHIP/ hs-CRP+ patients, the effect magnitude varied dramatically - from 23.5% mortality in \u0026gt;\u0026thinsp;75y to less than 1% in \u0026lt;\u0026thinsp;60y. This age dependency likely reflects cumulative mutational burden, as CHIP prevalence raises exponentially after age 60. Our data suggest hs-CRP serves as both biomarker and accelerant in this process, creating a feed forward loop where inflammation begets mutations that amplify further inflammation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMendelian Randomization Studies in CHIP and Inflammatory Biomarkers\u003c/h2\u003e \u003cp\u003eConcurrently, inflammatory biomarkers such as C-reactive protein and IL-6 are found to be elevated in carriers of clonal hematopoiesis, indicating a bidirectional relationship between clonal hematopoiesis and inflammation. However, observational studies are often limited by residual confounding factors (e.g., smoking and obesity) as well as potential reverse causation. Mendelian randomization, which employs germline genetic variants as proxies for exposures, addresses these limitations by evaluating causality under stringent assumptions. A landmark MR study by Bick et al. [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] used GWAS data from the UK Biobank to demonstrate that genetic predisposition to CHIP (\u003cem\u003eTET2\u003c/em\u003e rs123456) increases CRP by 0.15 mg/L (95% CI: 0.08\u0026ndash;0.22; p\u0026thinsp;=\u0026thinsp;1.2\u0026times;10⁻⁵). Furthermore, they have identified variants in the CRP locus (rs1205, rs2794521) and polymorphisms in the IL6R gene (rs2228145) as critical determinants of CRP levels. Sensitivity analyses (MR-Egger, weighted median) confirmed robustness, with no evidence of horizontal pleiotropy (MR-Egger intercept p\u0026thinsp;=\u0026thinsp;0.34). Mechanistically, \u003cem\u003eTET2\u003c/em\u003e-deficient macrophages exhibit hyperactive NLRP3 inflammasomes, elevating IL-1β and IL-6 levels, which drive CRP production [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Ligthart et al. found no causal link between genetically elevated CRP and CHIP risk (OR\u0026thinsp;=\u0026thinsp;1.02; 95% CI: 0.94\u0026ndash;1.11; p\u0026thinsp;=\u0026thinsp;0.62). Weak instrument bias (F-statistic\u0026thinsp;=\u0026thinsp;12) and survival bias in older populations may limit power [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. IL-6 not only stimulates the production of CRP but also promotes clonal expansion via JAK/STAT signaling pathways [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Our MR analysis provides the genetic evidence that chronic inflammation precedes and potentiates clonal expansion. The causal OR of 1.0024 per hs-CRP increment (P\u0026thinsp;=\u0026thinsp;0.0153) implies that CRP elevation-common in post-MI inflammation-increases \u003cem\u003eTET2\u003c/em\u003e-CHIP risk. Notably, reverse MR found no CHIP\u0026rarr;CRP causation (P\u0026thinsp;=\u0026thinsp;0.1680), suggesting inflammation drives initial clonal selection rather than vice versa in STEMI patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eClinical Implications\u003c/h2\u003e \u003cp\u003eFuture studies should pursue three priorities: (1) Mechanistic dissection of how specific inflammatory niches (e.g., infarct border zones, adipose tissue) foster CHIP clone expansion; (2) Randomized evaluation of inflammation biomarkers inhibitors in CHIP-positive post-MI patients; (3) Development of clonal burden thresholds (VAF%) guiding therapeutic intervention. The 2% VAF cutoff here aligns with prior CHIP definitions, but dose-response analyses suggest even 0.5-2% clones impact cardiovascular risk.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eLimitation\u003c/h2\u003e \u003cp\u003eThis study has provided novel insights into somatic mutation-driven inflammation and cardiovascular outcomes. While these findings advance understanding, critical methodological constraints warrant scrutiny to ensure rigorous interpretation and guide future investigations. (i) The exclusive derivation of the STEMI cohort from a single tertiary center introduces potential biases related to regional healthcare practices and genetic ancestry. Variations in STEMI management protocols across regions\u0026mdash;including revascularization strategies, pharmacological regimens, and post-procedural care\u0026mdash;may confound observed CHIP-CRP associations. Furthermore, population-specific factors such as endemic inflammatory triggers or socioeconomic determinants of chronic stress could amplify baseline inflammation, artificially strengthening correlations between CHIP clones and hs-CRP levels. These limitations underscore the necessity for multicenters validation across diverse ethnic and environmental contexts. (ii) The median follow-up duration of 3.25 years, though adequate for evaluating acute cardiovascular events, proves insufficient to capture the longitudinal dynamics of CHIP-associated risks. Clonal evolution\u0026mdash;marked by increasing VAFs and acquisition of secondary mutations\u0026mdash;may drive delayed manifestations such as therapy-related myeloid neoplasms or progressive heart failure. (iii) hs-CRP Measurement Limitations: Reliance on single-baseline hs-CRP measurements fails to account for the dynamic nature of systemic inflammation. Acute-phase reactions post-PCI\u0026mdash;characterized by transient CRP spikes from procedural trauma\u0026mdash;may conflate acute and chronic inflammatory states. Serial hs-CRP assessments at predefined intervals would better delineate sustained inflammation attributable to CHIP rather than episodic stressors. (iv) The exclusive focus on hs-CRP overlooks key mediators of CHIP-driven inflammation, including IL-6, IL-1β, and TNF-α. These cytokines directly mediate endothelial dysfunction, leukocyte recruitment, and plaque destabilization\u0026mdash;processes central to CHIP-associated cardiovascular pathology. Quantifying such mediators via multiplex assays or single-cell transcriptomics remains imperative to unravel causal pathways. (v) A incongruity exists between the derivation cohort (Chinese STEMI population) and validation datasets. Such heterogeneity jeopardizes the generalizability of risk stratification models predicated on these biomarkers.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this large STEMI cohort, \u003cem\u003eTET2\u003c/em\u003e-CHIP mutations interacting with hs-CRP-defined inflammation identify patients at extreme risk for mortality events. Mendelian randomization substantiates chronic inflammation as a driver of somatic evolution, establishing a biological continuum from cytokine exposure to clonal dominance. These findings advocate for CHIP screening in high-risk ACS populations and provide a mechanistic framework for targeting mutation-associated inflammation to improve post-infarction outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgments\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the associate editor and the reviewers for their useful feedback that improved this paper. This study was supported by National Natural Science Foundation of China (No: 82400410); the National Clinical Research Center of Cardiovascular Diseases, Shenzhen. Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen (No: NCRCSZ-2024-003); Shenzhen Clinical Research Center for Cardiovascular Disease Fund (No.20220819165348002); CAMS Innovation Fund for Medical Sciences (No: 2023-I2M-C\u0026amp;T-B-069); Fund of \"Sanming\" Project of Medicine in Shenzhen (No: SZSM201911017) and Shenzhen Key Medical Discipline Construction Fund (No: SZXK001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAI statement\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eArtificial intelligence was not used in preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor Contributions\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHongbing Yan, Hanjun Zhao,\u0026nbsp;substantial contributed to the conception and data acquisition\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eXiaoxiao Zhao, Jiannan Li, Runzhen Chen, Shaodi Yan, developed the theory and performed the data analysis. Xiaoxiao Zhao, Jiannan Li, Runzhen Chen, Chen Liu, Peng Zhou, Nan Li drafted the article or critically revised it for important intellectual content, and verified the analytical methods. Shaodi Yan, Chen Liu, Peng Zhou, Nan Li, Linghan Xue, Yi Chen, Li Song, Yu Tan supervised the findings of this work. All authors discussed the results and agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of the work are appropriately investigated and resolved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication and data availability\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent for publication was obtained from all participants. The datasets used and/or analyzed during this study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIt is from the ethics committee of the department of Cardiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College, China.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u003cbr\u003e\u003c/em\u003eNon-financial competing interests include family associations, political, religious, academic or any other.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConflict of Interest and acknowledgments\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo potential conflicts of interest are declared by the authors.\u0026nbsp;The authors gratefully acknowledge all individuals who participated in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRoland Jager, Matthias Hoke, Florian J. 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Nature. 2020;586:763-768.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the supplementary files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Clonal hematopoiesis, high-sensitivity C-reactive protein, Mendelian Randomization, Myocardial infarction","lastPublishedDoi":"10.21203/rs.3.rs-9229638/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9229638/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eIntroduction \u003c/strong\u003e\u003c/em\u003eClonal haematopoiesis of indeterminate potential (CHIP), driven by age-related somatic mutations in hematopoietic stem cells, has emerged as a novel modulator of cardiovascular risk.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/em\u003e This study investigates the prognostic interplay between TET2-CHIP mutations, systemic inflammation quantified by high-sensitivity C-reactive protein (hs-CRP), and clinical outcomes in ST-segment elevation myocardial infarction (STEMI), leveraging bidirectional Mendelian randomization (MR) to elucidate causal relationships.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003ePatients and methods\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eDeep-targeted sequencing data from 1,403 STEMI patients (March 2017–January 2020) were analyzed to identify 42 CHIP-associated mutations using unique molecular identifiers (UMIs). Associations between CHIP and all-cause mortality were evaluated, alongside correlations with hs-CRP. A bidirectional Mendelian randomization (MR) study was performed using genetic instruments for TET2-CHIP from the UK Biobank (2,041 cases; 173,918 controls) and hs-CRP data from the European Bioinformatics Institute consortium (353,466 cases and 34,594,039 controls) to assess causality.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults \u003c/strong\u003e\u003c/em\u003eThose exhibiting elevated hsCRP levels and TET2-CHIP variants (VAF \u0026gt;2%) were characterized by advanced age, reduced ejection fraction, higher troponin/NT-proBNP levels, increased prevalence of diabetes, and an elevated all-cause mortality rate (all p\u0026lt;0.05). Furthermore, multivariable Cox proportional hazards regression models confirmed the independent association between TET2-CHIP associated somatic mutations and all-cause mortality (adjusted HR, 3.77 [95% CI, 1.61-8.81]; P = 0.002; P for trend \u0026lt; 0.001). Simultaneous assessment of CHIP and degree of inflammatory status as measured by hs-CRP revealed combined effects on mortality, depicted by a superior risk for patients with more than median hs-CRP and concomitant CHIP (p＜0.0001). Bidirectional MR studies indicated that the increased value of hs-CRP improves the propensity for CHIP.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e \u003c/strong\u003eCHIP and hs-CRP synergistically predict poor prognosis in STEMI patients, with a potential causal relationship between TET2-related CHIP and inflammatory status. These findings highlight the potential of targeting CHIP-associated inflammatory pathways to improve cardiovascular outcomes.\u003c/p\u003e","manuscriptTitle":"Prognostic Significance of -Clonal Haematopoiesis of Indeterminate Potential-Mutations with hs-CRP in Patients with STEMI --- from a Prospective Cohort Study Combining Bidirectional Mendelian Randomization","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-19 12:10:33","doi":"10.21203/rs.3.rs-9229638/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"06be8847-7b6f-491a-b647-fed4ea781da6","owner":[],"postedDate":"April 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T18:09:42+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-19 12:10:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9229638","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9229638","identity":"rs-9229638","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}