Small RNA Sequencing across Diverse Biofluids Identifies Optimal Methods for exRNA Isolation.

Poor reproducibility within and across studies arising from lack of knowledge regarding the performance of extracellular RNA (exRNA) isolation methods has hindered progress in the exRNA field. A systematic comparison of 10 exRNA isolation methods across 5 biofluids revealed marked differences in the complexity and reproducibility of the resulting small RNA-seq profiles. The relative efficiency with which each method accessed different exRNA carrier subclasses was determined by estimating the proportions of extracellular vesicle (EV)-, ribonucleoprotein (RNP)-, and high-density lipoprotein (HDL)-specific miRNA signatures in each profile. An interactive web-based application (miRDaR) was developed to help investigators select the optimal exRNA isolation method for their studies. miRDar provides comparative statistics for all expressed miRNAs or a selected subset of miRNAs in the desired biofluid for each exRNA isolation method and returns a ranked list of exRNA isolation methods prioritized by complexity, expression level, and reproducibility. These results will improve reproducibility and stimulate further progress in exRNA biomarker development.

exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids.

To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously. To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.

Proteomics, Human Environmental Exposure, and Cardiometabolic Risk.

BACKGROUND: The biological mechanisms linking environmental exposures with cardiovascular disease pathobiology are incompletely understood. We sought to identify circulating proteomic signatures of environmental exposures and examine their associations with cardiometabolic and respiratory disease in observational cohort studies. METHODS: We tested the relations of >6500 circulating proteins with 29 environmental exposures across the built environment, green space, air pollution, temperature, and social vulnerability indicators in ≈3000 participants of the CARDIA study (Coronary Artery Risk Development in Young Adults) across 4 centers using penalized and ordinary linear regression. In >3500 participants from FHS (Framingham Heart Study) and JHS (Jackson Heart Study), we evaluated the prospective relations of proteomic signatures of the envirome with cardiovascular disease and mortality using Cox models. RESULTS: Proteomic signatures of the envirome identified novel/established cardiovascular disease-relevant pathways including DNA damage, fibrosis, inflammation, and mitochondrial function. The proteomic signatures of the envirome were broadly related to cardiometabolic disease and respiratory phenotypes (eg, body mass index, lipids, and left ventricular mass) in CARDIA, with replication in FHS/JHS. A proteomic signature of social vulnerability was associated with a composite of cardiovascular disease/mortality (1428 events; FHS: hazard ratio, 1.16 [95% CI, 1.08-1.24]; P=1.77×10-5; JHS: hazard ratio, 1.25 [95% CI, 1.14-1.38]; P=6.38×10-6; hazard ratio expressed as per 1 SD increase in proteomic signature), robust to adjustment for known clinical risk factors. CONCLUSIONS: Environmental exposures are related to an inflammatory-metabolic proteome, which identifies individuals with cardiometabolic disease and respiratory phenotypes and outcomes. Future work examining the dynamic impact of the environment on human cardiometabolic health is warranted.

Differences in Cardiometabolic Proteins in Pregnancy Prioritize Relevant Targets of Preeclampsia.

BACKGROUND: Preeclampsia is a hypertensive disorder of pregnancy characterized by widespread vascular inflammation. It occurs frequently in pregnancy, often without known risk factors, and has high rates of maternal and fetal morbidity and mortality. Identification of biomarkers that predict preeclampsia and its cardiovascular sequelae before clinical onset, or even before pregnancy, is a critical unmet need for the prevention of adverse pregnancy outcomes. METHODS: We explored differences in cardiovascular proteomics (Olink Explore 384) in 256 diverse pregnant persons across 2 centers (26% Hispanic, 21% Black). RESULTS: We identified significant differences in plasma abundance of markers associated with angiogenesis, blood pressure, cell adhesion, inflammation, and metabolism between individuals delivering with preeclampsia and controls, some of which have not been widely described previously and are not represented in the preeclampsia placental transcriptome. While we observed a broadly similar pattern in early (<34 weeks) versus late (≥34 weeks) preeclampsia, several proteins related to hemodynamic stress, hemostasis, and immune response appeared to be more highly dysregulated in early preeclampsia relative to late preeclampsia. CONCLUSIONS: These results demonstrate the value of performing targeted proteomics using a panel of cardiovascular biomarkers to identify biomarkers relevant to preeclampsia pathophysiology and highlight the need for larger multiomic studies to define modifiable pathways of surveillance and intervention upstream to preeclampsia diagnosis.

Proteomic Risk Score of Increased Respiratory Susceptibility: A Multi-Cohort Study.

RATIONALE: Accelerated decline in lung function is associated with incident COPD, hospitalizations and death. However, identifying this trajectory with longitudinal spirometry measurements is challenging in clinical practice. OBJECTIVE: To determine whether a proteomic risk score trained on accelerated decline in lung function can assess risk of future respiratory disease and mortality. METHODS: In CARDIA, a population-based cohort starting in young adulthood, longitudinal measurements of FEV1 percent predicted (up to six timepoints over 30 years) were used to identify accelerated and normal decline trajectories. Protein aptamers associated with an accelerated decline trajectory were identified with multivariable logistic regression followed by LASSO regression. The proteomic respiratory susceptibility score was derived based on these circulating proteins and applied to the UK Biobank and COPDGene studies to examine associations with future respiratory morbidity and mortality. MEASUREMENTS AND RESULTS: Higher susceptibility score was independently associated with all-cause mortality (UKBB: HR 1.56, 95%CI 1.50-1.61; COPDGene: HR 1.75, 95%CI 1.63-1.88), respiratory mortality (UKBB: HR 2.39, 95% CI 2.16-2.64; COPDGene: HR 1.83, 95%CI 1.33-2.51), incident COPD (UKBB: HR 1.84, 95%CI 1.71-1.98), incident respiratory exacerbation (COPDGene: OR 1.11, 95%CI 1.03-1.20), and incident exacerbation requiring hospitalization (COPDGene: OR 1.18, 95%CI 1.08-1.28). CONCLUSIONS: A proteomic signature of increased respiratory susceptibility identifies people at risk of respiratory death, incident COPD, and respiratory exacerbations. This susceptibility score is comprised of proteins with well-known and novel associations with lung health and holds promise for the early detection of lung disease without requiring years of spirometry measurements.

Decreased postpartum exercise capacity after a diagnosis of pre-eclampsia: Implications for CVD risk prediction.

BACKGROUND: Hypertensive disorders of pregnancy (HDP) are associated with increased long-term risk for cardiometabolic risk factors (chronic hypertension [HTN], obesity, diabetes) and heart failure. Exercise capacity is a known predictor of heart failure in patients with normal resting cardiac filling pressures. In this prospective observational cohort study, we sought to identify predictors of reduced postpartum exercise capacity in participants with normotensive vs preeclamptic pregnancies. METHODS: Preeclampsia (PreE) and normotensive subjects were enrolled to undergo bedside echocardiography within 48 hours of delivery, and rest/exercise echocardiography 12 weeks postpartum. RESULTS: Recruited subjects (n = 68) were grouped according to their blood pressure as: a) normotensive pregnancy n = 15; b) PreE with normotensive postpartum (PreE-Resolved, n = 36); c) PreE with persistent postpartum HTN (PreE-HTN, n = 17). At enrollment, a significantly higher percentage of subjects in the PreE-HTN group were Black. Compared to normotensive and PreE-Resolved subjects, those with PreE-HTN demonstrated higher resting systolic blood pressure (SBP, 112 [normotensive] vs 112 [PreE-Resolved] vs 134 [PreE-HTN], P < .001) and diastolic blood pressure (DBP, 70.0 vs 72.5 vs 85.0, P < .001), and significantly less postpartum weight loss (9.6% vs 13.6% vs 3.8%, P < .001). Following Bruce protocol stress testing, PreE-HTN subjects demonstrated achieved significantly lower exercise duration (10.4 vs 10.2 vs 7.9 minutes, P = .001). Subjects with PreE-HTN also demonstrated evidence of exercise-induced diastolic dysfunction as assessed by peak exercise lateral e' (18.0 vs 18.0 vs 13.5, P = .045) and peak exercise tricuspid regurgitation velocity (TR Vm, 2.4 vs 3.0 vs 3.1, P = 0.045). Exercise duration was negatively associated with gravidity (R = -0.27, P = .029) and postpartum LV mass index (R = -0.45, P < .001), resting average E/e' (R = -0.51, P < .001), BMI (R = -0.6, P < .001) and resting SBP (R = -0.51, P < .001). CONCLUSIONS: Postpartum exercise stress testing capacity is related to readily available clinical markers including pregnancy factors, echocardiographic parameters and unresolved cardiometabolic risk factors.

Blood Pressure Responses During Exercise: Physiological Correlates and Clinical Implications.

BACKGROUND: Abnormal blood pressure (BP) responses to exercise can predict adverse cardiovascular outcomes, but their optimal measurement and definitions are poorly understood. We combined frequently sampled BP during cardiopulmonary exercise testing with vascular stiffness assessment to parse cardiac and vascular components of exercise BP. METHODS: Cardiopulmonary exercise testing with BP measured every two minutes and resting vascular tonometry were performed in 2858 Framingham Heart Study participants. Linear regression was used to analyze sex-specific exercise BP patterns as a function of arterial stiffness (carotid-femoral pulse wave velocity) and cardiac-peripheral performance (defined by peak O2 pulse). RESULTS: Our sample was balanced by sex (52% women) with mean age 54±9 years and 47% with hypertension. We observed variability in carotid-femoral pulse wave velocity and peak O2 pulse across individuals with clinically defined exercise hypertension (peak systolic BP [SBP] in men ≥210 mm Hg; in women ≥190 mm Hg). Despite similar resting SBP and cardiometabolic profiles, individuals with higher peak O2 pulse displayed higher peak SBP (P≤0.017) alongside higher fitness levels (P<0.001), suggesting that high peak exercise SBP in the context of high peak O2 pulse may in fact be favorable. Although both higher (favorable) O2 pulse and higher (adverse) arterial stiffness were associated with greater peak SBP (P<0.0001 for both), the magnitude of association of carotid-femoral pulse wave velocity with peak SBP was higher in women (sex-carotid-femoral pulse wave velocity interaction P<0.0001). In sex-specific models, exercise SBP measures accounting for workload (eg, SBP during unloaded exercise, SBP at 75 watts, and SBP/workload slope) were directly associated with the adverse features of greater arterial stiffness and lower peak O2 pulse. CONCLUSIONS: Higher peak exercise SBP reflects a complex trade-off between arterial stiffness and cardiac-peripheral performance that differs by sex. Studies of BP responses to exercise accounting for vascular and cardiac physiology may illuminate mechanisms of hypertension and clarify clinical interpretation of exercise BP.

Association of Smartwatch-Based Heart Rate and Physical Activity With Cardiorespiratory Fitness Measures in the Community: Cohort Study.

BACKGROUND: Resting heart rate (HR) and routine physical activity are associated with cardiorespiratory fitness levels. Commercial smartwatches permit remote HR monitoring and step count recording in real-world settings over long periods of time, but the relationship between smartwatch-measured HR and daily steps to cardiorespiratory fitness remains incompletely characterized in the community. OBJECTIVE: This study aimed to examine the association of nonactive HR and daily steps measured by a smartwatch with a multidimensional fitness assessment via cardiopulmonary exercise testing (CPET) among participants in the electronic Framingham Heart Study. METHODS: Electronic Framingham Heart Study participants were enrolled in a research examination (2016-2019) and provided with a study smartwatch that collected longitudinal HR and physical activity data for up to 3 years. At the same examination, the participants underwent CPET on a cycle ergometer. Multivariable linear models were used to test the association of CPET indices with nonactive HR and daily steps from the smartwatch. RESULTS: We included 662 participants (mean age 53, SD 9 years; n=391, 59% women, n=599, 91% White; mean nonactive HR 73, SD 6 beats per minute) with a median of 1836 (IQR 889-3559) HR records and a median of 128 (IQR 65-227) watch-wearing days for each individual. In multivariable-adjusted models, lower nonactive HR and higher daily steps were associated with higher peak oxygen uptake (VO2), % predicted peak VO2, and VO2 at the ventilatory anaerobic threshold, with false discovery rate (FDR)-adjusted P values <.001 for all. Reductions of 2.4 beats per minute in nonactive HR, or increases of nearly 1000 daily steps, corresponded to a 1.3 mL/kg/min higher peak VO2. In addition, ventilatory efficiency (VE/VCO2; FDR-adjusted P=.009), % predicted maximum HR (FDR-adjusted P<.001), and systolic blood pressure-to-workload slope (FDR-adjusted P=.01) were associated with nonactive HR but not associated with daily steps. CONCLUSIONS: Our findings suggest that smartwatch-based assessments are associated with a broad array of cardiorespiratory fitness responses in the community, including measures of global fitness (peak VO2), ventilatory efficiency, and blood pressure response to exercise. Metrics captured by wearable devices offer a valuable opportunity to use extensive data on health factors and behaviors to provide a window into individual cardiovascular fitness levels.

Dietary metabolic signatures and cardiometabolic risk.

AIMS: Observational studies of diet in cardiometabolic-cardiovascular disease (CM-CVD) focus on self-reported consumption of food or dietary pattern, with limited information on individual metabolic responses to dietary intake linked to CM-CVD. Here, machine learning approaches were used to identify individual metabolic patterns related to diet and relation to long-term CM-CVD in early adulthood. METHODS AND RESULTS: In 2259 White and Black adults (age 32.1 ± 3.6 years, 45% women, 44% Black) in the Coronary Artery Risk Development in Young Adults (CARDIA) study, multivariate models were employed to identify metabolite signatures of food group and composite dietary intake across 17 food groups, 2 nutrient groups, and healthy eating index-2015 (HEI2015) diet quality score. A broad array of metabolites associated with diet were uncovered, reflecting food-related components/catabolites (e.g. fish and long-chain unsaturated triacylglycerols), interactions with host features (microbiome), or pathways broadly implicated in CM-CVD (e.g. ceramide/sphingomyelin lipid metabolism). To integrate diet with metabolism, penalized machine learning models were used to define a metabolite signature linked to a putative CM-CVD-adverse diet (e.g. high in red/processed meat, refined grains), which was subsequently associated with long-term diabetes and CVD risk numerically more strongly than HEI2015 in CARDIA [e.g. diabetes: standardized hazard ratio (HR): 1.62, 95% confidence interval (CI): 1.32-1.97, P < 0.0001; CVD: HR: 1.55, 95% CI: 1.12-2.14, P = 0.008], with associations replicated for diabetes (P < 0.0001) in the Framingham Heart Study. CONCLUSION: Metabolic signatures of diet are associated with long-term CM-CVD independent of lifestyle and traditional risk factors. Metabolomics improves precision to identify adverse consequences and pathways of diet-related CM-CVD.

Clonal hematopoiesis of indeterminate potential and outcomes after heart transplantation: A multicenter study.

Cardiac allograft vasculopathy (CAV) is a leading cause of late graft failure and mortality after heart transplantation (HT). Sharing some features with atherosclerosis, CAV results in diffuse narrowing of the epicardial coronaries and microvasculature, with consequent graft ischemia. Recently, clonal hematopoiesis of indeterminate potential (CHIP) has emerged as a risk factor for cardiovascular disease and mortality. We aimed to investigate the relationship between CHIP and posttransplant outcomes, including CAV. We analyzed 479 HT recipients with stored DNA samples at 2 high-volume transplant centers, Vanderbilt University Medical Center and Columbia University Irving Medical Center. We explored the association between the presence of CHIP mutations with CAV and mortality after HT. In this case-control analysis, carriers of CHIP mutations were not at increased risk of CAV or mortality after HT. In a large multicenter genomics study of the heart transplant population, the presence of CHIP mutations was not associated with an increased risk of CAV or posttransplant mortality.