Ruggles, Kelly V

Introduction/Background: CHIP is a risk factor for cardiovascular (CV) disease, cancer, and all-cause mortality. Previous work has shown that CHIP, and particularly larger CHIP clones, are associated with adverse CV outcomes, yet the molecular pathways through which CHIP impacts CV risk are poorly defined. Hypothesis/Research Question: We hypothesize that the integration of whole blood transcriptomics and methylomics will provide novel insights into the pathophysiology of CHIP. Methods/Approach: Whole blood DNA methylation profiling, transcriptomics, and whole exome sequencing with CHIP calling for variant allele frequencies (VAF) of ≥2% (CHIP) and ≥10% (large CHIP) were performed for 507 ISCHEMIA and ISCHEMIA-CKD participants with moderate-severe ischemia. We identified transcriptomic and methylomic differences between participants with CHIP and large CHIP vs no CHIP using DESeq2 and limma, adjusted for age, sex, and race/ethnicity. Gene set enrichment analysis (GSEA) and probe set enrichment analysis (PSEA) were performed to identify pathway-level alterations in transcription and methylation, respectively. Results/Data: Clinical characteristics of study participants are described in Fig 1A . Compared to no CHIP (n=391), transcriptomics identified 6 differentially expressed genes (DEGs) in CHIP (n=116) and 27 DEGs in large CHIP (n=35) (p-adj<0.05; abs(logFC)>0.25) (Fig 1B) . Compared to no CHIP, methylation identified no differentially methylated probes in CHIP and 6 in large CHIP (padj<0.20, abs(logFC)>0.03). GSEA identified 137 pathways significantly different in both CHIP and large CHIP vs. no CHIP (padj<0.05), while PSEA identified 724 and 2356 pathways (padj<0.20), respectively. Given its stronger relationship with methylation and transcription, downstream analyses focused on large CHIP. Integrating these data, we found 58 pathways to be both hypomethylated and transcriptionally upregulated in large CHIP, including azurophil granule-related pathways implicated in neutrophil degranulation (Fig 1C) . Further investigation into the gene-probe pairs driving the azurophil granule pathway enrichment in large CHIP revealed hypomethylation and increased transcription of genes implicated in neutrophil extracellular trap formation, including ELANE, PTRN3, AZU1, and CTSG (Fig 1D) . Conclusions: Integration of the methylome and transcriptome suggests large CHIP is linked to neutrophil-mediated immune pathways in patients with stable coronary artery disease.

Introduction: Higher mtDNA-CN reflects better mitochondrial function, while lower levels indicate mtDNA release and increased inflammation. Although mtDNA-CN serves as a marker of cardiovascular health, the importance and mechanism of risk associated with mtDNA in high-risk individuals with chronic coronary artery disease (CAD) remains poorly understood. To address this gap, we leveraged the ISCHEMIA Biorepository to: (1) evaluate the association between mtDNA-CN and all-cause death (ACD); and (2) define a transcriptomic profile associated with high mtDNA-CN and ACD risk for high-risk patients with CAD. Hypothesis: Higher mtDNA-CN is associated with reduced ACD risk and inflammation in high-risk patients enrolled in the ISCHEMIA Biorepository. Methods: Low pass whole genome sequencing and whole blood RNA-Seq were performed on 594 ISCHEMIA and ISCHEMIA-CKD participants with moderate-severe ischemia. Data were processed using the NYU deciphEHR pipeline and mtDNA was quantified using mitoAnalyzer. mtDNA-CN was median split, with samples having values ≤ median classified as the 'low' group and those > median as the 'high' group. Unadjusted group differences were assessed using Chi-squared tests. Survival analysis was performed using Cox proportional hazard models, adjusted for age, sex, diabetes, eGFR, dialysis status, ischemia severity, and left ventricular ejection fraction. Adjusted differential gene expression (DGE) and gene set enrichment analysis (GSEA) were performed to explore molecular mechanisms underlying mtDNA-CN. Results: Median age was 67 (IQR: 57–78); 19% were female, 84% white, and 6% Hispanic. Hypertension (84%), diabetes (43%), and obesity (45%) were common; 26% had eGFR <60 mL/min/1.73 m 2 . Median mtDNA-CN was 153 counts per sample. After multivariate adjustment , mtDNA-CN > median was associated with a 48% reduction in ACD (aHR = 0.52, 95% CI: 0.30–0.90; P = 0.020) (Figure 1A) . DGE revealed downregulation of inflammatory genes in the mtDNA-CN group, including S100A9 (FC=-.41, p=3.32e-10) and S100A12 (FC=-.56, p=3.32e-10). Inflammatory pathways such as the inflammasome complex (NES=-2.17, p=9.32e-03) and interleukin-1 production (NES= -2.02, p=6.60e-03) were downregulated among participants in the high mtDNA-CN ( Figure 1B) . Conclusion: Higher mtDNA-CN is associated with lower risk of ACD and reduced inflammasome activity, suggesting that enhanced mitochondrial health may mitigate inflammasome-related pathology linked to ACD in patients with CAD.

Introduction: CHIP is associated with CAD and mortality. The prognostic relevance of CHIP for high-risk patients with confirmed CAD is unknown. Hypothesis: CHIP variants are associated with cardiovascular (CV) events and mortality in high-risk patients with known CAD in the ISCHEMIA Trials Biorepository. Methods: 895 ISCHEMIA and ISCHEMIA-CKD (hereafter, ISCHEMIA Trials) participants with moderate-severe ischemia and next-generation sequencing performed for CHIP variant allele fractions of ≥2% (CHIP) and ≥10% (large CHIP) were included. Unadjusted and multivariable adjusted (age, sex, diabetes, eGFR not on HD, HD, and LVEF) associations of CHIP and large CHIP with a) ISCHEMIA Trials initial phase primary endpoint (CV death, myocardial infarction (MI), or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest, RCA) and b) ISCHEMIA Trials combined initial and extended follow-up phase (hereafter, Cumulative) endpoint of all-cause death . Results: Median (IQR) age of sequenced participants was 67 (56 – 79) years, 19% were female, 83% white, and 6% Hispanic. Hypertension (84%), diabetes (45%) and obesity (47%) were common, 26% had an eGFR <60 ml/min/1.73m 2 . The prevalence of CHIP and large CHIP was 23% and 7%, and both increased with age ( Figure 1a ). CHIP mutations in DNMT3A were detected in 106 (12%), TET2 CHIP in 44 (5%), and ASXL1 CHIP in 21 (2%) participants ( Figure 1b ). DNMT3A, TET2, and CREBBP mutations collectively comprised 199 (52%) of overall CHIP mutations, including individuals with multiple mutations in the same gene (N overall = 385); 67 participants (7%) had mutations in >1 gene. Over 3.1 years of RCT follow-up there were 135 (20%), 32 (16%) and 15 (18%) primary endpoints for no CHIP, CHIP and large CHIP, respectively. Over 6.8 years of EXTEND follow-up, there were 126 (18%), 47 (23%) and 24 (29%) deaths in the no CHIP, CHIP and large CHIP groups, respectively. After multivariable adjustment there was no association between CHIP or large CHIP and CV events or mortality ( Figure 1c ). Conclusion: Neither CHIP nor large CHIP was associated with adverse outcomes in 895 high-risk individuals with confirmed CAD, despite a high prevalence of these mutations.

Introduction: Circulating biomarkers may improve prediction of cardiovascular (CV) events in chronic coronary disease (CCD). The incremental value of biomarkers in CCD after adjustment for clinical factors, inducible ischemia and coronary artery disease (CAD) severity is uncertain. Methods: 756 ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches) participants with site-determined moderate-severe ischemia and 9 assayed biomarkers (Figure) were included. Among participants with interpretable stress tests for ischemia and CAD by computed coronary tomography angiography (CCTA) (N=507), associations of biomarkers with the primary (CV death, myocardial infarction (MI), or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest) or secondary endpoints (CV death or MI) were evaluated using sequentially adjusted multivariable Cox proportional hazards models (Model 1=unadjusted, Model 2=clinical features, Model 3=Model 2 + multivessel CAD by CCTA, and Model 4=Model 3 + severe ischemia). Results: Median (IQR) participant age was 64 (57-70) years, 19% were female, 81% white, and 5% Hispanic. Hypertension (85%), diabetes (46%) and obesity (45%) were common, 28% had an estimated glomerular filtration rate <60 ml/min/1.73m 2 . Severe ischemia was present in 44%, and 39% had multivessel CAD (≥70% stenosis) by CCTA. Over 3.5 (2.4-4.7) years of follow-up there were 146 (19%) primary and 128 (17%) secondary endpoints. Soluble CD40L, GDF-15, NT-proBNP, hsTnT were associated with the primary and secondary endpoints in univariable and multivariable (adjusting for clinical features, multivessel CAD and severe ischemia) models. Conclusion: Biomarkers of inflammation (GDF-15), thrombosis (sCD40L), myocardial stretch (NT-proBNP) and injury (hs-troponin) were associated with CV endpoints in the ISCHEMIA trial independent of clinical features, multivessel CAD and severe ischemia.

Introduction: Chronic coronary disease (CCD) is a leading cause of death worldwide. Whole blood (WB) transcriptomic (RNA-seq) and methylation ‘omics’ data can discern molecular underpinnings of CCD and create molecular subtypes to aid risk prediction. Methods: Of 1,064 participants with moderate-severe ischemia (Age: 67.1±6.2, 19.4% Female, 17% non-White) from the ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches) biorepository, 646 participants had available WB RNA-seq and 737 had WB methylation data ( Fig 1A ). Unsupervised clustering and differential analyses identified omics-derived molecular subtypes. We identified co-regulated gene modules of each subtype, performed subtype-level enrichment of clinical variables, and performed Kaplan-Meier analyses for time to cardiovascular (CV) death or myocardial infarction (MI). Results: Multi-omic analysis revealed 4 RNA-seq-derived subtypes (RS) and 3 methylation-derived subtypes (MS). RNA-seq Subtype 1 (RS1) was enriched for molecular drivers indicative of an adaptive immune response, had clinical enrichment of female sex, statin use, and greater ischemia, and had decreased risk of CV death or MI ( Fig 1B ). RNA-seq Subtype 2 (RS2) was enriched for innate immune response pathway, and patients who were older and White, and was associated with increased risk of CV death or MI. Similarly, methylation subtypes also yielded a high-risk subtype (MS3) and a low-risk subtype (MS2) ( Fig 1C ). Integration of transcriptomic and methylomic subtypes led to further distinction of resilient and vulnerable subgroups. Conclusions: WB RNA-seq and methylation data identified molecularly-defined subtypes that informed the underlying disease pathology of CCD patients in ISCHEMIA. These subgroups were differentially enriched for clinical characteristics and event outcomes, demonstrating the potential use for blood-based omics tests to aid in the prognosis of CCD.