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Background Kidney disease is common in heart failure with preserved ejection fraction (HFpEF). However, the biologic correlates and prognostic significance of kidney injury (KI), in HFpEF, beyond the estimated glomerular filtration rate (eGFR), are unclear. Methods and Results Using baseline plasma samples from the TOPCAT (Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist) trial, we measured the following KI biomarkers: cystatin‐C, fatty acid‐binding protein‐3, Beta‐2 microglobulin, neutrophil gelatinase‐associated lipocalin, and kidney‐injury molecule‐1. Factor analysis was used to extract the common variability underlying these biomarkers. We assessed the relationship between the KI‐factor score and the risk of death or HF‐related hospital admission in models adjusted for the Meta‐Analysis Global Group in Chronic Heart Failure risk score and eGFR. We also assessed the relationship between the KI factor score and ~5000 plasma proteins, followed by pathway analysis. We validated our findings among HFpEF participants in the Penn Heart Failure Study. KI was associated with the risk of death or HF‐related hospital admission independent of the Meta‐Analysis Global Group in Chronic Heart Failure risk score and eGFR. Both the risk score and eGFR were no longer associated with death or HF‐related hospital admission after adjusting for the KI factor score. KI was predominantly associated with proteins and biologic pathways related to complement activation, inflammation, fibrosis, and cholesterol homeostasis. KI was associated with 140 proteins, which reproduced across cohorts. Findings regarding biologic associations and the prognostic significance of KI were also reproduced in the validation cohort. Conclusions KI is associated with adverse outcomes in HFpEF independent of baseline eGFR. Patients with HFpEF and KI exhibit a plasma proteomic signature indicative of complement activation, inflammation, fibrosis, and impaired cholesterol homeostasis.

Background The role of cellular senescence in human heart failure (HF) remains unclear. The senescence‐associated secretory phenotype (SASP) is composed of proteins released by senescent cells. We assessed the prognostic significance and biologic pathways associated with the SASP in human HF using a plasma proteomics approach. Methods and Results We measured 25 known SASP proteins among 2248 PHFS (Penn HF Study) participants using the SOMAScan V4 assay. We extracted the common variance in these proteins to generate SASP factor scores and assessed the relationship between these SASP factor scores and (1) all‐cause death and (2) the composite of death or HF hospital admission. We also assessed the relationship of each SASP factor to 4746 other proteins, correcting for multiple comparisons, followed by pathway analyses. Two SASP factors were identified. Both factors were associated with older age, lower estimated glomerular filtration rate, and more advanced New York Heart Association class, among other clinical variables. Both SASP factors exhibited a significant positive association with the risk of death independent of the Meta‐Analysis of Global‐Group in Chronic HF score and NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) levels. The 2 identified SASP factors were associated with 1201 and 1554 proteins, respectively, belonging to various pathways including the coagulation system, complement system, acute phase response signaling, and retinoid X receptor–related pathways that regulate cell metabolism. Conclusions Increased SASP components are independently associated with adverse outcomes in HF. Biologic pathways associated with SASP are predominantly related to coagulation, inflammation, and cell metabolism.

Background Although several studies have addressed plasma proteomics in heart failure with preserved ejection fraction, limited data are available on the prognostic value of urinary proteomics. The objective of our study was to identify urinary proteins/peptides associated with death and heart failure admission in patients with heart failure with preserved ejection fraction. Methods and Results The study population included participants enrolled in TOPCAT (Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist Trial). The relationship between urine protein levels and the risk of death or heart failure admission was assessed using Cox regression, in both nonadjusted analyses and adjusting for urine creatinine levels, and the MAGGIC (Meta‐Analysis Global Group in Chronic Heart Failure) score. A total of 426 (12.4%) TOPCAT participants had urinary protein data and were included. There were 40 urinary proteins/peptides significantly associated with death or heart failure admission in nonadjusted analyses, 21 of which were also significant adjusted analyses. Top proteins in the adjusted analysis included ANGPTL2 (angiopoietin‐like protein 2) (hazard ratio [HR], 0.5731 [95% CI, 0.47–0.7]; P=3.13E‐05), AMY2A (α amylase 2A) (HR, 0.5496 [95% CI, 0.44–0.69]; P=0.0001), and DNASE1 (deoxyribonuclease‐1) (HR, 0.5704 [95% CI, 0.46–0.71]; P=0.0002). Higher urinary levels of proteins involved in fibrosis (collagen VI α‐1, collagen XV α‐1), metabolism (pancreatic α‐amylase 2A/B, mannosidase α class 1A member 1), and inflammation (heat shock protein family D member 1, inducible T cell costimulatory ligand) were associated with a lower risk of death or heart failure admission. Conclusions Our study identifies several novel associations between urinary proteins/peptides and outcomes in heart failure with preserved ejection fraction. Many of these associations are independent of clinical risk scores and may aid in risk stratification in this patient population.

Background Identifying novel molecular drivers of disease progression in heart failure (HF) is a high‐priority goal that may provide new therapeutic targets to improve patient outcomes. The authors investigated the relationship between plasma proteins and adverse outcomes in HF and their putative causal role using Mendelian randomization. Methods and Results The authors measured 4776 plasma proteins among 1964 participants with HF with a reduced left ventricular ejection fraction enrolled in PHFS (Penn Heart Failure Study). Assessed were the observational relationship between plasma proteins and (1) all‐cause death or (2) death or HF‐related hospital admission (DHFA). The authors replicated nominally significant associations in the Washington University HF registry (N=1080). Proteins significantly associated with outcomes were the subject of 2‐sample Mendelian randomization and colocalization analyses. After correction for multiple testing, 243 and 126 proteins were found to be significantly associated with death and DHFA, respectively. These included small ubiquitin–like modifier 2 (standardized hazard ratio [sHR], 1.56; P

Objective To characterise cardiac remodelling, exercise capacity and fibroinflammatory biomarkers in patients with aortic stenosis (AS) with and without diabetes, and assess the impact of diabetes on outcomes.Methods Patients with moderate or severe AS with and without diabetes underwent echocardiography, stress cardiovascular magnetic resonance (CMR), cardiopulmonary exercise testing and plasma biomarker analysis. Primary endpoint for survival analysis was a composite of cardiovascular mortality, myocardial infarction, hospitalisation with heart failure, syncope or arrhythmia. Secondary endpoint was all-cause death.Results Diabetes (n=56) and non-diabetes groups (n=198) were well matched for age, sex, ethnicity, blood pressure and severity of AS. The diabetes group had higher body mass index, lower estimated glomerular filtration rate and higher rates of hypertension, hyperlipidaemia and symptoms of AS. Biventricular volumes and systolic function were similar, but the diabetes group had higher extracellular volume fraction (25.9%±3.1% vs 24.8%±2.4%, p=0.020), lower myocardial perfusion reserve (2.02±0.75 vs 2.34±0.68, p=0.046) and lower percentage predicted peak oxygen consumption (68%±21% vs 77%±17%, p=0.002) compared with the non-diabetes group. Higher levels of renin (log10renin: 3.27±0.59 vs 2.82±0.69 pg/mL, p