Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood (n = 6454) and lung (n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank-derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

Abstract Mechanical twisting and untwisting of the left ventricle as well as abnormal hemodynamic aortic‐ventricular coupling are recognized as contributors to left ventricular diastolic function. However, energy associated with proximal aortic stretch during systole can be recovered as diastolic elastic recoil that may facilitate diastolic left ventricular filling. To investigate this “aortic spring” mechanism, we assessed the cross‐sectional and longitudinal associations of systolic atrioventricular plane displacement (AVPD), a surrogate measure of stretch of the mechanically coupled ascending aorta, with measures of left ventricular diastolic function. At two examinations (14 ± 1 years apart) in Framingham Heart Study participants (N = 7117; mean age 50 years, 55% women), we assessed AVPD and left ventricular diastolic function using echocardiography. In cross‐sectional analyses, higher AVPD was associated with higher e' (β per SD ± standard error = 0.49 ± 0.01; p < 0.001) and lower E/e' (β = −0.39 ± 0.01; p < 0.001). In longitudinal models, greater change in (Δ) AVPD between visits was associated with higher Δe' (β = 0.38 ± 0.01; p < 0.001) and lower ΔE/e' (β = −0.19 ± 0.01; p < 0.001). We observed effect modification (interaction p‐values: <0.001 to 0.03) for cross‐sectional and longitudinal associations by median age, sex, obesity status, hypertension treatment, and the extent of aortic stiffness (assessed via carotid‐femoral pulse wave velocity). Thus, the aortic spring function may contribute to left ventricular diastolic function.

Background: Fibrinogen is a critical coagulation factor that plays an essential role in thrombosis and is elevated in individuals with chronic inflammation. Objectives: Here, we used fibrinogen as a representative quantitative measure of procoagulant risk and evaluated metabolites associated with fibrinogen levels using nontargeted plasma metabolomics profiling (Broad and Metabolon platforms). Methods: Our analysis included 10 533 individuals across 6 United States-based cohorts representing diverse population groups. The cross-sectional relationship between each of the 789 metabolites tested and plasma fibrinogen concentration was assessed after adjustment for relevant covariates, including age, cohort-reported sex, body mass index, and circulating lipoprotein levels. Results: Meta-analysis of per-cohort results revealed 270 metabolites significantly associated with fibrinogen levels (false discovery rate-adjusted P value < .05). Lipid species, such as glycerophospholipids, sphingolipids, and fatty acyls, were among the most significantly associated metabolites; some of these may capture effects of inflammation, as supported by sensitivity analyses adjusted for C-reactive protein. Significant associations between fibrinogen levels and serotonin, thyroxine, and sex hormone derivatives may capture endogenous influences on fibrinogen levels. Exogenous compounds and microbial cometabolites were significantly associated with fibrinogen, also implicating lifestyle and microbiome risk factors. Only a portion of fibrinogen-associated metabolites (30%) has been associated with cardiovascular disease outcomes in a prior study, suggesting that the associations discovered here may provide insights into vascular biology that case-control studies may not yet be powered to detect. Conclusion: These findings contribute to the growing list of metabolite biomarkers that may influence coagulation and inflammation pathways and, thereby, vascular risk.

Background:In adults without cardiovascular disease (CVD), there is limited understanding of the association between overall cardiovascular health (CVH) and arterial health. Methods:In 2330 Framingham Heart Study Offspring participants free of CVD (60±9 years; 57% women) with Life's Essential 8 (LE8) and applanation tonometry data (Exam 7), we calculated CVH scores per American Heart Association's LE8 guidelines. Multivariable-adjusted regression analyses examined the relations of LE8 with aortic stiffness and pressure pulsatility [negative inverse carotid-femoral pulse wave velocity (niCFPWV), central pulse pressure (CPP), respectively], and examined effect modification by age and sex. We also evaluated niCFPWV and CPP as mediators of the relation between LE8 and death outcomes (CVD, all-cause mortality). Results:Higher LE8 scores (better CVH) were associated with lower niCFPWV [standardized (std) β= -0.20±0.02, p<0.0001] and CPP (std β= -0.11±0.02, p<0.0001). While age- and sex- interactions were not significant, stratified analysis revealed stronger association of LE8 with arterial health in women (niCFPWV: std β= -0.11±0.02, p<0.0001 vs. std β= -0.06±0.03, p=0.04; CPP: std β= -0.13±0.03, p<0.001 vs. std β= -0.06±0.03, p=0.07 in women vs. men, respectively). niCFPWV and CPP mediated 19% and 10% of the association between LE8 and CVD mortality, respectively, and 17% and 15% of the association between LE8 and all-cause mortality, respectively. Conclusion:Better CVH measured by LE8 was associated with lower arterial stiffness and pressure pulsatility, both of which mediate a significant proportion of the associations between CVH and CVD/death outcomes. These findings underscore the importance of optimal cardiovascular health behaviors and factors in maintaining arterial health.

Most genetic variants associated with complex traits and diseases occur in non-coding genomic regions and are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterize 14,324 ancestrally diverse RNA-sequencing samples from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and integrate whole genome sequencing data to perform cis and trans expression and splicing quantitative trait locus (cis-/trans-e/sQTL) analyses in six tissues and cell types, most notably whole blood (N=6,454) and lung (N=1,291). We show this dataset enables greater detection of secondary cis-e/sQTL signals than was achieved in previous studies, and that secondary cis-eQTL and primary trans-eQTL signal discovery is not saturated even though eGene discovery is. Most TOPMed trans-eQTL signals colocalize with cis-e/sQTL signals, suggesting many trans signals are mediated by cis signals. We fine-map European UK BioBank GWAS signals from 164 traits and colocalize the resulting 34,107 fine-mapped GWAS signals with TOPMed e/sQTL signals, finding that of 10,611 GWAS signals with a colocalization, 7,096 GWAS signals colocalize with at least one secondary e/sQTL signal. These results demonstrate that larger e/sQTL analyses will continue to uncover secondary e/sQTL signals, and that these new signals will benefit GWAS interpretation.

Circulating metabolite levels partly reflect the state of human health and diseases and can be impacted by genetic determinants. Hundreds of loci associated with circulating metabolites have been identified; however, most findings focus on predominantly European ancestry or single-study analyses. Leveraging the rich metabolomics resources generated by the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) Program, we harmonized and accessibly cataloged 1,729 circulating metabolites among 25,058 ancestrally diverse samples. From our comparison of multiple methods, we provided a set of reasonable strategies for outlier and imputation handling to process metabolite data and show that inverse normalization by study and half-minimum imputation provide mostly similar results for pooled or meta-analysis. Following the practical analysis framework, we further performed a genome-wide association analysis on 1,135 selected metabolites using whole-genome sequencing data from 16,359 individuals passing the quality-control filters and discovered 1,775 independent loci associated with 667 metabolites. Among 160 unreported locus-metabolite pairs, we identified associations with loci locating within previously implicated metabolite-associated genes, as well as associations with loci locating in genes such as GAB3 and VSIG4 (located on the X chromosome) that may play a role in metabolic regulation. In the sex-stratified analysis, we revealed 85 independent locus-metabolite pairs with evidence of sexual dimorphism, which were located in well-known metabolic genes such as FADS2, D2HGDH, SUGP1, and UGT2B17, strongly supporting the importance of exploring sex difference in the human metabolome. Taken together, our study depicted the genetic contribution to circulating metabolite levels, providing additional insight into the understanding of human health.

Background:Energy associated with proximal aortic stretch during systole is recovered as diastolic elastic recoil of the aorta that facilitates left ventricular filling. Impairment of this aortic spring mechanism may contribute to left ventricular diastolic dysfunction. However, cross-sectional and longitudinal inter-relations of cardiovascular disease risk factors, aortic stretch, and left ventricular diastolic function have not been examined. The goal of this study was to assess the cross-sectional and longitudinal associations of cardiovascular disease risk factors and systolic atrioventricular plane displacement (AVPD), a surrogate measure of stretch of the mechanically coupled ascending aorta, with measures of left ventricular diastolic function. Methods:At two examinations (14±1 years apart) in Framingham Heart Study participants (N=7117; mean age 50 years, 55% women), we assessed AVPD and left ventricular diastolic function using echocardiography. We measured systolic AVPD using the integral of the tissue Doppler s' wave. Additionally, we assessed e' (the peak early diastolic tissue velocity of the lateral mitral annulus) and E/e' (the ratio of peak early mitral inflow velocity and e'). Results:In cross-sectional analyses, higher AVPD was associated with higher e' (β per SD±standard error=0.43±0.01; P<0.001) and lower E/e' (β=-0.35±0.01; P<0.001). In longitudinal models (between two examinations), greater change in (Δ) AVPD between visits was associated with higher Δe' (β=0.40±0.01; P<0.001) and lower ΔE/e' (β=-0.23±0.01; P<0.001). We observed significant effect modification (interaction P-values: <0.001 to 0.045) for cross-sectional and longitudinal associations by median age, sex, obesity status, hypertension treatment, and the extent of aortic stiffness (assessed via carotid-femoral pulse wave velocity). Conclusion:The aortic spring function, as assessed via AVPD, may play an important role in maintaining left ventricular diastolic function, with putative effects modified by aortic stiffness, obesity, age, and sex.

BACKGROUND:Missing data are common in longitudinal studies. Multiple imputation (MI) is widely used to handle missing data. However, most of the MI methods assume various missing data types as missing at random (MAR) in imputation. Two-stage MI is a flexible method that accounts for two types of missing data in a two-step process, allowing researchers to employ diverse assumptions regarding the mechanisms underlying the missing data. This method has immense potential yet limited application and extension within the field. METHODS:We evaluated the performance of two-stage MI in a novel context, imputing a composite variable constructed from several continuous and binary components in the longitudinal setting while handling missing data due to MAR and missing not at random (MNAR). Additionally, we compared three fully conditional specification (FCS) methods within the two-stage MI framework. Simulation studies were conducted using a longitudinal dataset that mimicked a cohort study. Sensitivity analysis was performed with various ignorability assumptions. RESULTS:In simulation studies, the imputation models within two-stage MI, assuming appropriate ignorability assumptions, exhibited the smallest bias and achieved optimal coverage probabilities for the means, slopes across different time points, and hazard ratios for mortality related to the composite variable. The FCS methods that incorporated longitudinal information yielded the best performance in most scenarios. CONCLUSIONS:In the context of a longitudinal composite variable with missing values due to various missing mechanisms, the selection of imputation methods and ignorability assumptions plays an important role within the two-stage MI framework.

Aims Children of patients with early-onset myocardial infarction (MI) are at increased risk, but the importance of concordant vs. discordant parent-offspring risk factor profiles on MI risk is largely unknown. We quantified the long-term absolute risk of MI according to shared risk factors in adulthood.Methods and results We sampled data on familial predisposed offspring and their parents from the Framingham Heart Study. Early MI was defined as a history of parental MI onset before age 55 in men or 65 in women. Individuals were matched 3:1 with non-predisposed offspring. Cardiovascular risk factors included obesity, smoking, hypertension, high cholesterol, and diabetes. We estimated the absolute 20-year incidence of MI using the Aalen-Johansen estimator. At age 40, the 20-year risk of MI varied by cholesterol level [high cholesterol 25.7% (95% confidence interval 11.2-40.2%) vs. non-high cholesterol 3.4% (0.5-6.4)] among predisposed individuals, and this difference was greater than in controls [high cholesterol 9.3% (1.5-17.0) vs. non-high cholesterol 2.5% (1.1-3.8)]. Similar results were observed for prevalent hypertension [26.7% (10.8-42.5) vs. 4.0% (0.9-7.1) in predisposed vs. 10.8% (3.2-18.3) and 2.1% (0.8-3.4) in controls]. Among offspring without risk factors, parental risk factors carried a residual impact on 20-year MI risk in offspring [0% (0-11.6) for 0-1 parental risk factors vs. 3.3% (0-9.8) for >= 2 parent risk factors at age 40, vs. 2.9% (0-8.4) and 8.5% (0-19.8) at age 50 years].Conclusion Children of patients with early-onset MI have low absolute risks of MI in the absence of midlife cardiovascular risk factors, especially if the parent also had a low risk factor burden prior to MI. Children of patients with early-onset myocardial infarction (MI) are at a higher risk of disease themselves. Cardiovascular risk factor control is important to lower the risk of disease, but little is known about how the offspring's risk differs based on risk factor controls. Using multi-generational data from the Framingham Heart Study, we observed that adult children of people with early-onset MI have low absolute 20-year risk of developing an MI if they do not have any cardiovascular risk factors, especially if the parent also had low risk factor burden prior to MI, suggesting that close surveillance for risk factor development in offspring is warranted. In offspring of parents with early-onset MI who did not have any risk factors, the number of risk factors in the parent seemed to slightly impact the risk of MI. Improved clarity of the interplay between risk factors in parents and offspring can help medical doctors provide accurate guidance in terms of preventing the development of MI. Our findings suggest that in the absence of risk factors, assessment of the parents' risk factors burden may be helpful for further risk stratification. Graphical Abstract

Background Abnormal exercise blood pressure (BP) responses are associated with hypertension and cardiovascular disease, but their relationship with home BP over a mid‐ to long‐term time span is unknown. Methods At an FHS (Framingham Heart Study) research examination (2016–2019), participants underwent maximum incremental ramp cycle ergometry cardiopulmonary exercise testing with BP measured every 2 minutes. At the same exam, English‐speaking participants enrolled in the electronic FHS with an iPhone were provided with a digital BP cuff to measure home BP weekly for 1 year. Linear regression models examined associations of exercise BP with average home systolic BP (SBP), home‐based hypertension, and week‐to‐week average real variability of home SBP, over 1‐year follow‐up. Participants with <3 weeks of BP return were excluded. Results Among 808 participants (mean age, 53 years; 58% women; 92% White individuals; 47% hypertension), higher exercise BP responses (peak SBP, SBP at 75 W, SBP/workload slope, peak diastolic BP, and diastolic BP at 75 W) were associated with higher average home SBP. Higher peak diastolic BP was associated with a greater risk for home hypertension. Additionally, higher SBP/workload slope and peak diastolic BP were associated with elevated average real variability of home SBP only in participants without antihypertensive use. Conclusions Higher exercise BP responses were associated with higher average home‐based BP, greater home‐based hypertension risk, and increased home‐based BP variability over a mid‐ to long‐term time span. However, these associations may vary by antihypertensive medication use. Exercise BP may play an important role in hypertension prevention and treatment.

BackgroundResting 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. ObjectiveThis 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. MethodsElectronic 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. ResultsWe 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. ConclusionsOur 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.

Background Sex differences in obesity and fat distribution may in part explain differences in cardiovascular risk in men versus women. We sought to examine sex differences in the associations of obesity and adiposity measures with cardiovascular disease–related protein biomarkers. Methods and Results In a cross‐sectional observational cohort study, we examined whether the association of obesity (body mass index [BMI] and waist circumference) and adiposity measures (visceral adipose tissue) with biomarkers demonstrates effect modification by sex using multiplicative interaction terms in multivariable linear regression models. Among 3143 participants (mean age, 50 years; 49% women), sex modified the association of BMI, waist circumference, and visceral adipose tissue with cardiovascular disease–related protein biomarkers (7 for BMI, 3 for waist circumference, and 23 for visceral adipose tissue, false discovery rate [FDR]‐qint<0.05 for all). For example, higher BMI was associated with lower α1‐microglobulin levels in men but not in women (ß, −0.113; SE, 0.028; P<0.001 in men versus ß, −0.007; SE, 0.024; P=0.78 in women). By contrast, higher BMI was associated with higher adipsin levels in men and women, but the association was more pronounced in women (ß, 0.287; SE, 0.023; P<0.001 in women versus ß, 0.189; SE, 0.026; P<0.001 in men). The associations of higher visceral adipose tissue with biomarkers representing adiposity, inflammation, and fibrosis were more pronounced in women versus men. Conclusions We found that sex modified the associations of obesity and adipose traits with cardiovascular risk ascertained by cardiovascular disease–related biomarkers including markers of adiposity, inflammation, and fibrosis. These findings highlight potential biological pathways that may underlie some of the observed differences in obesity‐related cardiovascular disease between women and men.

Background: There is limited understanding of the association of the AHA's Life's Essential 8 (LE8), reflecting cardiovascular health (CVH) behaviors and factors, with vascular stiffness and hemodynamics in adults without cardiovascular diseases (CVD). Methods: In 2330 Framingham Heart Study Offspring participants (Exam 7, 1998-2002) with applanation tonometry and LE8 data (diet, physical activity, smoking, sleep health, BMI, lipids, glucose, blood pressure), we calculated CVH scores per AHA guidelines. In multivariable linear regression analyses adjusting for CV risk factors, we analyzed LE8 as a predictor of vascular health, assessed by carotid femoral pulse wave velocity (PWV) and central pulse pressure (CPP). We examined for effect modification by age (dichotomized at median) and sex in the associations between LE8 and arterial stiffness. We set p=0.05 and p=0.10 as thresholds for significance in primary and secondary analyses, respectively. Mediation analysis was utilized to discern the indirect effects of PWV and CPP on the relationship between LE8 and both all-cause and CVD mortality. Results: In our sample (60±9 years; 57% women; LE8 = 69±12), higher LE8 indicating better CVH, was associated with lower PWV and CPP (Table). Age and sex interactions were noted for PWV (p=0.01 and 0.07, respectively). Higher LE8 was associated with lower PWV in adults ≥59 years and women but not in <59 years or men (Table). With low CVH category as referent, intermediate CVH category had no significant association with PWV and high CVH category had lower PWV. CPP was lower in the intermediate and high CVH categories compared to low CVH category (Table). PWV mediated 19% and CPP 10% of the association between LE8 and CVD mortality and 17% and 15%, respectively, for all-cause mortality. Conclusion: In our community cohort, we observed age and sex differences in the relationship between CVH and vascular health. Mediation analyses revealed indirect effects on mortality, warranting further study. Table

AIMS:New tools are needed to identify heart failure (HF) risk earlier in its course. We evaluated the association of multidimensional cardiopulmonary exercise testing (CPET) phenotypes with subclinical risk markers and predicted long-term HF risk in a large community-based cohort. METHODS AND RESULTS:We studied 2532 Framingham Heart Study participants [age 53 ± 9 years, 52% women, body mass index (BMI) 28.0 ± 5.3 kg/m2, peak oxygen uptake (VO2) 21.1 ± 5.9 kg/m2 in women, 26.4 ± 6.7 kg/m2 in men] who underwent maximum effort CPET and were not taking atrioventricular nodal blocking agents. Higher peak VO2 was associated with a lower estimated HF risk score (Spearman correlation r: -0.60 in men and -0.55 in women, P < 0.0001), with an observed overlap of estimated risk across peak VO2 categories. Hierarchical clustering of 26 separate CPET phenotypes (values residualized on age, sex, and BMI to provide uniformity across these variables) identified three clusters with distinct exercise physiologies: Cluster 1-impaired oxygen kinetics; Cluster 2-impaired vascular; and Cluster 3-favourable exercise response. These clusters were similar in age, sex distribution, and BMI but displayed distinct associations with relevant subclinical phenotypes [Cluster 1-higher subcutaneous and visceral fat and lower pulmonary function; Cluster 2-higher carotid-femoral pulse wave velocity (CFPWV); and Cluster 3-lower CFPWV, C-reactive protein, fat volumes, and higher lung function; all false discovery rate < 5%]. Cluster membership provided incremental variance explained (adjusted R2 increment of 0.10 in women and men, P < 0.0001 for both) when compared with peak VO2 alone in association with predicted HF risk. CONCLUSIONS:Integrated CPET response patterns identify physiologically relevant profiles with distinct associations to subclinical phenotypes that are largely independent of standard risk factor-based assessment, which may suggest alternate pathways for prevention.

Breast cancer is the second leading cause of cancer deaths among women. Multiple microRNAs (miRNAs) have been reported to be associated with breast cancer progression or metastasis. The purpose of the current study was to identify plasma extracellular miRNAs associated with incident breast cancer. Levels of 166 plasma miRNA were measured using qRT-PCR in 2140 Framingham Heart Study female participants with a median follow up of 15.7 years. Prospective analyses of the associations of miRNAs with the occurrence of 56 new-onset breast cancer events were conducted using proportional hazards regression. The expression levels miR-134-5p (P=0.002) and miR-505-3p (P=0.005) were found to be positively associated with incident breast cancer after adjusting for age, body mass index, and cigarette smoking. These results highlight plasma miRNAs as potential biomarkers of breast cancer risk. Validation of these findings in larger and more diverse cohorts is warranted.

Background The relation of cardiorespiratory fitness (CRF) to lifestyle behaviors and factors linked with cardiovascular health remains unclear. We aimed to understand how the American Heart Association's Life's Essential 8 (LE8) score (and its changes over time) relate to CRF and complementary exercise measures in community‐dwelling adults. Methods and Results Framingham Heart Study (FHS) participants underwent maximum effort cardiopulmonary exercise testing for direct quantification of peak oxygen uptake (V̇O 2 ). A 100‐point LE8 score was constructed as the average across 8 factors: diet, physical activity, nicotine exposure, sleep, body mass index, lipids, blood glucose, and blood pressure. We related total LE8 score, score components, and change in LE8 score over 8 years with peak V̇O 2 (log‐transformed) and complementary CRF measures. In age‐ and sex‐adjusted linear models (N=1838, age 54±9 years, 54% women, LE8 score 76±12), a higher LE8 score was associated favorably with peak V̇O 2 , ventilatory efficiency, resting heart rate, and blood pressure response to exercise (all P <0.0001). A clinically meaningful 5‐point higher LE8 score was associated with a 6.0% greater peak V̇O 2 (≈1.4 mL/kg per minute at sample mean). All LE8 components were significantly associated with peak V̇O 2 in models adjusted for age and sex, but blood lipids, diet, and sleep health were no longer statistically significant after adjustment for all LE8 components. Over an ≈8‐year interval, a 5‐unit increase in LE8 score was associated with a 3.7% higher peak V̇O 2 ( P <0.0001). Conclusions Higher LE8 score and improvement in LE8 over time was associated with greater CRF, highlighting the importance of the LE8 factors in maintaining CRF.

Background Extracellular microRNAs (miRNAs) are a class of noncoding RNAs that remain stable in the extracellular milieu, where they contribute to various physiological and pathological processes by facilitating intercellular signaling. Previous studies have reported associations between miRNAs and cardiovascular diseases (CVDs); however, the plasma miRNA signatures of CVD and its risk factors have not been fully elucidated at the population level. Methods and Results Plasma miRNA levels were measured in 4440 FHS (Framingham Heart Study) participants. Linear regression analyses were conducted to test the cross‐sectional associations of each miRNA with 8 CVD risk factors. Prospective analyses of the associations of miRNAs with new‐onset obesity, hypertension, type 2 diabetes, CVD, and all‐cause mortality were conducted using proportional hazards regression. Replication was carried out in 1999 RS (Rotterdam Study) participants. Pathway enrichment analyses were conducted and target genes were predicted for miRNAs associated with ≥5 risk factors in the FHS. In the FHS, 6 miRNAs (miR‐193b‐3p, miR‐122‐5p, miR‐365a‐3p, miR‐194‐5p, miR‐192‐5p, and miR‐193a‐5p) were associated with ≥5 risk factors. This miRNA signature was enriched for pathways associated with CVD and several genes annotated to these pathways were predicted targets of the identified miRNAs. Furthermore, miR‐193b‐3p, miR‐194‐5p, and miR‐193a‐5p were each associated with ≥2 risk factors in the RS. Prospective analysis revealed 8 miRNAs associated with all‐cause mortality in the FHS. Conclusions These findings highlight associations between miRNAs and CVD risk factors that may provide valuable insights into the underlying pathogenesis of CVD.

Introduction: Hypertension (HTN) is a leading cause of cardiovascular disease and premature death. A few circulating metabolites have been associated with blood pressure or HTN; however, findings from multi-ethnic populations are limited. Methods: Discovery analysis included eight population-based cohorts from the Trans-Omics for Precision Medicine (TOPMed) consortium, including adults of White, Black and Hispanic/Latino ancestries. Replication analyses were performed in six independent studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) and TOPMed. Fixed-effect inverse variance weighted meta-analysis was applied, on study- and ethnic-specific linear and logistic regression results, to estimate circulating metabolites association with systolic (SBP), diastolic blood pressure (DBP), and HTN cross-sectionally, adjusting for age, sex, body mass index, smoking status, lipids, kidney function, and diabetes prevalence. Global metabolomic analysis and pathway enrichment were performed to identify potentially altered metabolic pathways, and two-sample Mendelian randomization (MR) was performed to test for causal relationships between replicated metabolites and SBP, DBP, and HTN. Results: Out of 1,055 meta-analyzed metabolites, 336 were significantly associated (FDR<0.05) with all three BP traits among 17,767 participants (7,097 White, 5,406 Black, and 5,264 Hispanic/Latino). Xanthopterin had the strongest positive association (SBP: β=3.16, DBP: β=1.78, HTN: OR=1.34), and NH4_C18:2 CE had the strongest inverse association (SBP: β=-2.31, DBP: β=-1.49, HTN: OR=0.75), per SD increase of the metabolite level. The directions of associations were generally consistent across sex and racial/ethnic groups. Pathway enrichment analysis identified two enriched pathways (FDR<0.05): alanine, aspartate and glutamate metabolism and citrate cycle. Of 222 metabolites available for replication, 114 metabolites associated with all three traits (FDR<0.05) among 20,567 participants. MR analysis identified 18 potentially causal associations between metabolites and BP traits, including palmitoylcarnitine - a carnitine derivative that showed consistent positive causal associations across SBP, DBP and HTN (FDR<0.05).

MicroRNAs, crucial in regulating protein-coding gene expression, are implicated in various diseases. We performed a genome-wide association study of plasma miRNAs (ex-miRNAs) in 3,743 Framingham Heart Study (FHS) participants and identified 1,027 cis-ex-miRNA-eQTLs (cis-exQTLs) for 37 ex-miRNAs, with 55% replication in an independent study. Colocalization analyses suggested potential genetic coregulation of ex-miRNAs with whole blood mRNAs. Mendelian randomization indicated 29 ex-miRNAs potentially influencing 35 traits. Notably, the chromosome 14q23 and 14q32 miRNA clusters emerged as the top signal, contributing over 50% of the significant cis-exQTL results, and were associated with a diverse range of traits including platelet count. Correlations of 10 ex-miRNAs (such as miR-376c-3p) in 14q32 with platelet count and volume were confirmed in FHS participants. These findings shed light on the genetic basis of ex-miRNA expression and their involvement in complex traits.

BACKGROUND:Traditional diagnostic tools that assess resting cardiac function and structure fail to accurately reflect cardiovascular alterations in patients with chronic kidney disease (CKD). This study sought to determine whether multidimensional exercise response patterns related to cardiovascular functional capacity can detect abnormalities in mild-to-moderate CKD. METHODS:In a cross-sectional study, we examined 3,075 participants from the Framingham Heart Study (FHS) and 451 participants from the Massachusetts General Hospital Exercise Study (MGH-ExS) who underwent cardiopulmonary exercise testing (CPET). Participants were stratified by estimated glomerular filtration rate (eGFR): eGFR ≥90; eGFR 60-89; eGFR 30-59. Our primary outcomes of interest were peak oxygen uptake (VO 2 Peak),VO 2 at anaerobic threshold (VO 2 AT), and the ratio of minute ventilation to carbon dioxide production (VE/VCO 2 ). Multiple linear regression models were fitted to evaluate the associations between eGFR group and each outcome variable adjusted for covariates. RESULTS:In the FHS cohort, N=1,712 (56%) had an eGFR ≥90 ml/min/1.73m 2 , N=1,271 (41%) had an eGFR 60-89 ml/min/1.73m 2 , and N=92 (3%) had an eGFR 30-59 ml/min/1.73m 2 . In the MGH-ExS cohort, N=247 (55%) had an eGFR ≥90 ml/min/1.73m 2 , N=154 (34%) had an eGFR 60-89 ml/min/1.73m 2 , and N=50 (11%) had an eGFR 30-59 ml/min/1.73m 2 . In FHS, VO 2 Peak and VO 2 AT were incrementally impaired with declining kidney function ( p <0.001); however this pattern was attenuated following adjustment for age. Percent-predicted VO 2 Peak at AT was higher in the lower eGFR groups ( p <0.001). In MGH-ExS, VO 2 Peak and VO 2 AT were incrementally impaired with declining kidney function in unadjusted and adjusted models ( p <0.05). VO 2 Peak was associated with eGFR ( p <0.05) in all models even after adjusting for age. On further mechanistic analysis, we directly measured cardiac output (CO) at peak exercise via right heart catheterization and found impaired CO in the lower eGFR groups ( p ≤0.007). CONCLUSION:CPET-derived indices may detect impairment in cardiovascular functional capacity and track cardiac output declines in mild to moderate CKD.