Broadcasters, receivers, functional groups of metabolites, and the link to heart failure by revealing metabolomic network connectivity.

BACKGROUND AND OBJECTIVE: Blood-based small molecule metabolites offer easy accessibility and hold significant potential for insights into health processes, the impact of lifestyle, and genetic variation on disease, enabling precise risk prevention. In a prospective study with records of heart failure (HF) incidence, we present metabolite profiling data from individuals without HF at baseline. METHODS: We uncovered the interconnectivity of metabolites using data-driven and causal networks augmented with polygenic factors. Exploring the networks, we identified metabolite broadcasters, receivers, mediators, and subnetworks corresponding to functional classes of metabolites, and provided insights into the link between metabolomic architecture and regulation in health. We incorporated the network structure into the identification of metabolites associated with HF to control the effect of confounding metabolites. RESULTS: We identified metabolites associated with higher and lower risk of HF incidence, such as glycine, ureidopropionic and glycocholic acids, and LPC 18:2. These associations were not confounded by the other metabolites due to uncovering the connectivity among metabolites and adjusting each association for the confounding metabolites. Examples of our findings include the direct influence of asparagine on glycine, both of which were inversely associated with HF. These two metabolites were influenced by polygenic factors and only essential amino acids, which are not synthesized in the human body and are obtained directly from the diet. CONCLUSION: Metabolites may play a critical role in linking genetic background and lifestyle factors to HF incidence. Revealing the underlying connectivity of metabolites associated with HF strengthens the findings and facilitates studying complex conditions like HF.

Plasma Extracellular MicroRNAs Associated With Cardiovascular Disease Risk Factors in Middle-Aged and Older Adults.

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.

Clusters of multidimensional exercise response patterns and estimated heart failure risk in the Framingham Heart Study.

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.

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.

Modifiable risk factors and risk of myocardial infarction in offspring with parental disease.

AIMS: Children of patients with early-onset myocardial infarction (MI) are at increased risk, but the importance of concordant versus 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: 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. RESULTS: 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 versus 3.3% [0; 9.8] for ≥2 parent risk factors at age 40, versus 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.

Life's Essential 8 Cardiovascular Health Score and Cardiorespiratory Fitness in the Community.

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 (V̇O2). 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 V̇O2 (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 V̇O2, 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 V̇O2 (≈1.4 mL/kg per minute at sample mean). All LE8 components were significantly associated with peak V̇O2 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 V̇O2 (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.

Association of Arterial Stiffness With Mid- to Long-Term Home Blood Pressure Variability in the Electronic Framingham Heart Study: Cohort Study.

BACKGROUND: Short-term blood pressure variability (BPV) is associated with arterial stiffness in patients with hypertension. Few studies have examined associations between arterial stiffness and digital home BPV over a mid- to long-term time span, irrespective of underlying hypertension. OBJECTIVE: This study aims to investigate if arterial stiffness traits were associated with subsequent mid- to long-term home BPV in the electronic Framingham Heart Study (eFHS). We hypothesized that higher arterial stiffness was associated with higher home BPV over up to 1-year follow-up. METHODS: At a Framingham Heart Study research examination (2016-2019), participants underwent arterial tonometry to acquire measures of arterial stiffness (carotid-femoral pulse wave velocity [CFPWV]; forward pressure wave amplitude [FWA]) and wave reflection (reflection coefficient [RC]). Participants who agreed to enroll in eFHS were provided with a digital blood pressure (BP) cuff to measure home BP weekly over up to 1-year follow-up. Participants with less than 3 weeks of BP readings were excluded. Linear regression models were used to examine associations of arterial measures with average real variability (ARV) of week-to-week home systolic (SBP) and diastolic (DBP) BP adjusting for important covariates. We obtained ARV as an average of the absolute differences of consecutive home BP measurements. ARV considers not only the dispersion of the BP readings around the mean but also the order of BP readings. In addition, ARV is more sensitive to measurement-to-measurement BPV compared with traditional BPV measures. RESULTS: Among 857 eFHS participants (mean age 54, SD 9 years; 508/857, 59% women; mean SBP/DBP 119/76 mm Hg; 405/857, 47% hypertension), 1 SD increment in FWA was associated with 0.16 (95% CI 0.09-0.23) SD increments in ARV of home SBP and 0.08 (95% CI 0.01-0.15) SD increments in ARV of home DBP; 1 SD increment in RC was associated with 0.14 (95% CI 0.07-0.22) SD increments in ARV of home SBP and 0.11 (95% CI 0.04-0.19) SD increments in ARV of home DBP. After adjusting for important covariates, there was no significant association between CFPWV and ARV of home SBP, and similarly, no significant association existed between CFPWV and ARV of home DBP (P>.05). CONCLUSIONS: In eFHS, higher FWA and RC were associated with higher mid- to long-term ARV of week-to-week home SBP and DBP over 1-year follow-up in individuals across the BP spectrum. Our findings suggest that higher aortic stiffness and wave reflection are associated with higher week-to-week variation of BP in a home-based setting over a mid- to long-term time span.

Vascular Age Assessed From an Uncalibrated, Noninvasive Pressure Waveform by Using a Deep Learning Approach: The AI-VascularAge Model.

BACKGROUND: Aortic stiffness, assessed as carotid-femoral pulse wave velocity, provides a measure of vascular age and risk for adverse cardiovascular disease outcomes, but it is difficult to measure. The shape of arterial pressure waveforms conveys information regarding aortic stiffness; however, the best methods to extract and interpret waveform features remain controversial. METHODS: We trained a convolutional neural network with fixed-scale (time and amplitude) brachial, radial, and carotid tonometry waveforms as input and negative inverse carotid-femoral pulse wave velocity as label. Models were trained with data from 2 community-based Icelandic samples (N=10 452 participants with 31 126 waveforms) and validated in the community-based Framingham Heart Study (N=7208 participants, 21 624 waveforms). Linear regression rescaled predicted negative inverse carotid-femoral pulse wave velocity to equivalent artificial intelligence vascular age (AI-VA). RESULTS: The AI-VascularAge model predicted negative inverse carotid-femoral pulse wave velocity with R2=0.64 in a randomly reserved Icelandic test group (n=5061, 16%) and R2=0.60 in the Framingham Heart Study. In the Framingham Heart Study (up to 18 years of follow-up; 479 cardiovascular disease, 200 coronary heart disease, and 213 heart failure events), brachial AI-VA was associated with incident cardiovascular disease adjusted for age and sex (model 1; hazard ratio, 1.79 [95% CI, 1.50-2.40] per SD; P<0.0001) or adjusted for age, sex, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, prevalent diabetes, hypertension treatment, and current smoking (model 2; hazard ratio, 1.50 [95% CI, 1.24-1.82] per SD; P<0.0001). Similar hazard ratios were demonstrated for incident coronary heart disease and heart failure events and for AI-VA values estimated from carotid or radial waveforms. CONCLUSIONS: Our results demonstrate that convolutional neural network-derived AI-VA is a powerful indicator of vascular health and cardiovascular disease risk in a broad community-based sample.

Moderate alcohol consumption on the risk of stroke in the Million Veteran Program.

BACKGROUND: There is inconsistent evidence on the association of moderate alcohol consumption and stroke risk in the general population and is not well studied among U.S. Veterans. Furthermore, it is unclear whether primarily drinking beer, wine, or liquor is associated with a difference in stroke risk. METHODS: The study included 185,323 Million Veteran Program participants who self-reported alcohol consumption on the Lifestyle Survey. Moderate consumption was defined as 1-2 drinks/day and beverage preference of beer, wine or liquor was defined if ≥ 50% of total drinks consumed were from a single type of beverage. Strokes were defined using ICD-9 and ICD-10 codes from the participants' electronic health record. RESULTS: The mean (sd) age of the sample was 64 (13) years and 11% were women. We observed 4,339 (94% ischemic; 6% hemorrhagic) strokes over a median follow-up of 5.2 years. In Cox models adjusted for age, sex, race, education, income, body mass index, smoking, exercise, diet, cholesterol, prevalent diabetes, prevalent hypertension, lipid-lowering medication, antihypertensive medication, and diabetes medication, moderate alcohol consumption (1-2 drinks/day) was associated with a 22% lower risk of total stroke compared with never drinking [Hazards ratio (HR) 95% confidence interval (CI): 0.78 (0.67, 0.92)]. When stratifying by stroke type, we observed a similar protective association with moderate consumption and ischemic stroke [HR (95% CI): 0.76 (0.65, 0.90)], but a non-statistically significant higher risk of hemorrhagic stroke [HR (95% CI): 1.29 (0.64, 2.61)]. We did not observe a difference in ischemic or hemorrhagic stroke risk among those who preferred beer, liquor or wine vs. no beverage preference. When stratifying by prior number of hospital visits (≤ 15, 16-33, 34-64, ≥ 65) as a proxy for health status, we observed attenuation of the protective association with greater number of visits [HR (95% CI): 0.87 (0.63, 1.19) for ≥ 65 visits vs. 0.80 (0.59, 1.08) for ≤ 15 visits]. CONCLUSIONS: We observed a lower risk of ischemic stroke, but not hemorrhagic stroke with moderate alcohol consumption and did not observe substantial differences in risk by beverage preference among a sample of U.S. Veterans. Healthy user bias of moderate alcohol consumption may be driving some of the observed protective association.

Proteome Network Analysis Identifies Potential Biomarkers for Brain Aging.

BACKGROUND: Alzheimer's disease and related dementias (ADRD) involve biological processes that begin years to decades before onset of clinical symptoms. The plasma proteome can offer insight into brain aging and risk of incident dementia among cognitively healthy adults. OBJECTIVE: To identify biomarkers and biological pathways associated with neuroimaging measures and incident dementia in two large community-based cohorts by applying a correlation-based network analysis to the plasma proteome. METHODS: Weighted co-expression network analysis of 1,305 plasma proteins identified four modules of co-expressed proteins, which were related to MRI brain volumes and risk of incident dementia over a median 20-year follow-up in Framingham Heart Study (FHS) Offspring cohort participants (n = 1,861). Analyses were replicated in the Cardiovascular Health Study (CHS) (n = 2,117, mean 6-year follow-up). RESULTS: Two proteomic modules, one related to protein clearance and synaptic maintenance (M2) and a second to inflammation (M4), were associated with total brain volume in FHS (M2: p = 0.014; M4: p = 4.2×10-5). These modules were not significantly associated with hippocampal volume, white matter hyperintensities, or incident all-cause or AD dementia. Associations with TCBV did not replicate in CHS, an older cohort with a greater burden of comorbidities. CONCLUSIONS: Proteome networks implicate an early role for biological pathways involving inflammation and synaptic function in preclinical brain atrophy, with implications for clinical dementia.

Arterial Stiffness and Cardiorespiratory Fitness Impairment in the Community.

Background During exercise, a healthy arterial system facilitates increased blood flow and distributes it effectively to essential organs. Accordingly, we sought to understand how arterial stiffening might impair cardiorespiratory fitness in community-dwelling individuals. Methods and Results Arterial tonometry and maximum effort cardiopulmonary exercise testing were performed on Framingham Heart Study participants (N=2898, age 54±9 years, 53% women, body mass index 28.1±5.3 kg/m2). We related 5 arterial stiffness measures (carotid-femoral pulse wave velocity [CFPWV]: a measure of aortic wall stiffness; central pulse pressure, forward wave amplitude, characteristic impedance: measures of pressure pulsatility; and augmentation index: a measure of relative wave reflection) to multidimensional exercise responses using linear models adjusted for age, sex, resting heart rate, habitual physical activity, and clinical risk factors. Greater CFPWV, augmentation index, and characteristic impedance were associated with lower peak oxygen uptake (VO2; all P<0.0001). We observed consistency of associations of CFPWV with peak oxygen uptake across age, sex, and cardiovascular risk profile (interaction P>0.05). However, the CFPWV-peak oxygen uptake relation was attenuated in individuals with obesity (P=0.002 for obesity*CFPWV interaction). Higher CPFWV, augmentation index, and characteristic impedance were also related to cardiopulmonary exercise testing measures reflecting adverse O2 kinetics and lower stroke volume and peripheral O2 extraction but not to ventilatory efficiency, a prognostic measure of right ventricular-pulmonary vascular performance. Conclusions Our findings delineate relations of arterial stiffness and cardiorespiratory fitness in community-dwelling individuals. Future studies are warranted to evaluate whether the physiological measures implicated here may represent potential targets for improving cardiorespiratory fitness in the general population.

Broadcasters, receivers, functional groups of metabolites and the link to heart failure progression using polygenic factors.

In a prospective study with records of heart failure (HF) incidence, we present metabolite profiling data from individuals without HF at baseline. We uncovered the interconnectivity of metabolites using data-driven and causal networks augmented with polygenic factors. Exploring the networks, we identified metabolite broadcasters, receivers, mediators, and subnetworks corresponding to functional classes of metabolites, and provided insights into the link between metabolomic architecture and regulation in health. We incorporated the network structure into the identification of metabolites associated with HF to control the effect of confounding metabolites. We identified metabolites associated with higher or lower risk of HF incidence, the associations that were not confounded by the other metabolites, such as glycine, ureidopropionic and glycocholic acids, and LPC 18:2. We revealed the underlying relationships of the findings. For example, asparagine directly influenced glycine, and both were inversely associated with HF. These two metabolites were influenced by polygenic factors and only essential amino acids which are not synthesized in the human body and come directly from the diet. Metabolites may play a critical role in linking genetic background and lifestyle factors to HF progression. Revealing the underlying connectivity of metabolites associated with HF strengthens the findings and facilitates a mechanistic understanding of HF progression.

Protein Biomarkers of Early Menopause and Incident Cardiovascular Disease.

Background Premature and early menopause are independently associated with greater risk of cardiovascular disease (CVD). However, mechanisms linking age of menopause with CVD remain poorly characterized. Methods and Results We measured 71 circulating CVD protein biomarkers in 1565 postmenopausal women enrolled in the FHS (Framingham Heart Study). We examined the association of early menopause with biomarkers and tested whether early menopause modified the association of biomarkers with incident cardiovascular outcomes (heart failure, major CVD, and all-cause death) using multivariable-adjusted linear regression and Cox models, respectively. Among 1565 postmenopausal women included (mean age 62 years), 395 (25%) had a history of early menopause. Of 71 biomarkers examined, we identified 7 biomarkers that were significantly associated with early menopause, of which 5 were higher in women with early menopause including adrenomedullin and resistin, and 2 were higher in women without early menopause including insulin growth factor-1 and CNTN1 (contactin-1) (Benjamini-Hochberg adjusted P<0.1 for all). Early menopause also modified the association of specific biomarkers with incident cardiovascular outcomes including adrenomedullin (Pint<0.05). Conclusions Early menopause is associated with circulating levels of CVD protein biomarkers and appears to modify the association between select biomarkers with incident cardiovascular outcomes. Identified biomarkers reflect several distinct biological pathways, including inflammation, adiposity, and neurohormonal regulation. Further investigation of these pathways may provide mechanistic insights into the pathogenesis, prevention, and treatment of early menopause-associated CVD.

Longitudinal Hemodynamic Correlates of and Sex Differences in the Evolution of Blood Pressure Across the Adult Lifespan: The Framingham Heart Study.

Background Systolic blood pressure increases with age after midlife, particularly in women, and contributes to development of wide pulse pressure hypertension in middle-aged and older adults. Relative contributions of aortic stiffness and premature wave reflection to increases in pulse pressure remain controversial. Methods and Results We evaluated visit-specific values and change in key correlates of pulse pressure, aortic characteristic impedance, forward and backward wave amplitude, and global reflection coefficient, at 3 sequential examinations of the Framingham Generation 3 (N=4082), Omni-2 (N=410), and New Offspring Spouse (N=103) cohorts (53% women). Data were analyzed using repeated-measures linear mixed models adjusted for age, sex, and risk factor exposures. Pulse pressure increased markedly with age after midlife (age and age-squared terms, P<0.0001), particularly in women (age slope 3.1±0.2 mm Hg/decade higher in women, P<0.0001). In sex-specific models, change in pulse pressure was closely related (all P<0.0001) to baseline (6.7±0.2 and 7.3±0.2 mm Hg/SD in men and women, respectively) and change (11.8±0.1 and 11.7±0.1 mm Hg/SD) in forward wave amplitude, whereas relations with baseline (2.1±0.15 and 2.0±0.14 mm Hg/SD) and change (4.0±0.13 and 3.4±0.11 mm Hg/SD) in global reflection coefficient were weaker. Global reflection coefficient fell as aortic characteristic impedance increased (P<0.0001), consistent with the hypothesis that impedance matching reduces relative wave reflection in the arterial system. Conclusions Proximal aortic stiffening, as assessed by higher aortic characteristic impedance and larger forward wave amplitude, is strongly associated with longitudinal increase in pulse pressure, especially in women, whereas wave reflection has more modest relations.

Systemic Markers of Lung Function and Forced Expiratory Volume in 1 Second Decline across Diverse Cohorts.

Rationale: Chronic obstructive pulmonary disease (COPD) is a complex disease characterized by airway obstruction and accelerated lung function decline. Our understanding of systemic protein biomarkers associated with COPD remains incomplete. Objectives: To determine what proteins and pathways are associated with impaired pulmonary function in a diverse population. Methods: We studied 6,722 participants across six cohort studies with both aptamer-based proteomic and spirometry data (4,566 predominantly White participants in a discovery analysis and 2,156 African American cohort participants in a validation). In linear regression models, we examined protein associations with baseline forced expiratory volume in 1 second (FEV1) and FEV1/forced vital capacity (FVC). In linear mixed effects models, we investigated the associations of baseline protein levels with rate of FEV1 decline (ml/yr) in 2,777 participants with up to 7 years of follow-up spirometry. Results: We identified 254 proteins associated with FEV1 in our discovery analyses, with 80 proteins validated in the Jackson Heart Study. Novel validated protein associations include kallistatin serine protease inhibitor, growth differentiation factor 2, and tumor necrosis factor-like weak inducer of apoptosis (discovery ß = 0.0561, Q = 4.05 × 10-10; ß = 0.0421, Q = 1.12 × 10-3; and ß = 0.0358, Q = 1.67 × 10-3, respectively). In longitudinal analyses within cohorts with follow-up spirometry, we identified 15 proteins associated with FEV1 decline (Q < 0.05), including elafin leukocyte elastase inhibitor and mucin-associated TFF2 (trefoil factor 2; ß = -4.3 ml/yr, Q = 0.049; ß = -6.1 ml/yr, Q = 0.032, respectively). Pathways and processes highlighted by our study include aberrant extracellular matrix remodeling, enhanced innate immune response, dysregulation of angiogenesis, and coagulation. Conclusions: In this study, we identify and validate novel biomarkers and pathways associated with lung function traits in a racially diverse population. In addition, we identify novel protein markers associated with FEV1 decline. Several protein findings are supported by previously reported genetic signals, highlighting the plausibility of certain biologic pathways. These novel proteins might represent markers for risk stratification, as well as novel molecular targets for treatment of COPD.

Metabolomic Profiles, Ideal Cardiovascular Health, and Risk of Heart Failure and Atrial Fibrillation: Insights From the Framingham Heart Study.

Background The American Heart Association's framework "ideal cardiovascular health" (CVH) focuses on modifiable risk factors to reduce cardiovascular disease (CVD). Metabolomics provides important pathobiological insights into risk factors and CVD development. We hypothesized that metabolomic signatures associate with CVH status, and that metabolites, at least partially, mediate the association of CVH score with atrial fibrillation (AF) and heart failure (HF). Methods and Results We studied 3056 adults in the FHS (Framingham Heart Study) cohort to evaluate CVH score and incident outcomes of AF and HF. Metabolomics data were available in 2059 participants; mediation analysis was performed to evaluate the mediation of metabolites in the association of CVH score and incident AF and HF. In the smaller cohort (mean age, 54 years; 53% women), CVH score was associated with 144 metabolites, with 64 metabolites shared across key cardiometabolic components (body mass index, blood pressure, and fasting blood glucose) of the CVH score. In mediation analyses, 3 metabolites (glycerol, cholesterol ester 16:1, and phosphatidylcholine 32:1) mediated the association of CVH score with incident AF. Seven metabolites (glycerol, isocitrate, asparagine, glutamine, indole-3-proprionate, phosphatidylcholine C36:4, and lysophosphatidylcholine 18:2), partly mediated the association between CVH score and incident HF in multivariable-adjusted models. Conclusions Most metabolites that associated with CVH score were shared the most among 3 cardiometabolic components. Three main pathways: (1) alanine, glutamine, and glutamate metabolism; (2) citric acid cycle metabolism; and (3) glycerolipid metabolism mediated CVH score with HF. Metabolomics provides insights into how ideal CVH status contributes to the development of AF and HF.

Association Between Electrocardiographic Age and Cardiovascular Events in Community Settings: The Framingham Heart Study.

BACKGROUND: Deep neural networks have been used to estimate age from ECGs, the electrocardiographic age (ECG-age), which predicts adverse outcomes. However, this prediction ability has been restricted to clinical settings or relatively short periods. We hypothesized that ECG-age is associated with death and cardiovascular outcomes in the long-standing community-based FHS (Framingham Heart Study). METHODS: We tested the association of ECG-age with chronological age in the FHS cohorts in ECGs from 1986 to 2021. We calculated the gap between chronological and ECG-age (Δage) and classified individuals as having normal, accelerated, or decelerated aging, if Δage was within, higher, or lower than the mean absolute error of the model, respectively. We assessed the associations of Δage, accelerated and decelerated aging with death or cardiovascular outcomes (atrial fibrillation, myocardial infarction, and heart failure) using Cox proportional hazards models adjusted for age, sex, and clinical factors. RESULTS: The study population included 9877 FHS participants (mean age, 55±13 years; 54.9% women) with 34 948 ECGs. ECG-age was correlated to chronological age (r=0.81; mean absolute error, 9±7 years). After 17±8 years of follow-up, every 10-year increase of Δage was associated with 18% increase in all-cause mortality (hazard ratio [HR], 1.18 [95% CI, 1.12-1.23]), 23% increase in atrial fibrillation risk (HR, 1.23 [95% CI, 1.17-1.29]), 14% increase in myocardial infarction risk (HR, 1.14 [95% CI, 1.05-1.23]), and 40% increase in heart failure risk (HR, 1.40 [95% CI, 1.30-1.52]), in multivariable models. In addition, accelerated aging was associated with a 28% increase in all-cause mortality (HR, 1.28 [95% CI, 1.14-1.45]), whereas decelerated aging was associated with a 16% decrease (HR, 0.84 [95% CI, 0.74-0.95]). CONCLUSIONS: ECG-age was highly correlated with chronological age in FHS. The difference between ECG-age and chronological age was associated with death, myocardial infarction, atrial fibrillation, and heart failure. Given the wide availability and low cost of ECG, ECG-age could be a scalable biomarker of cardiovascular risk.

Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations.

Circulating metabolite levels may reflect the state of the human organism in health and disease, however, the genetic architecture of metabolites is not fully understood. We have performed a whole-genome sequencing association analysis of both common and rare variants in up to 11,840 multi-ethnic participants from five studies with up to 1666 circulating metabolites. We have discovered 1985 novel variant-metabolite associations, and validated 761 locus-metabolite associations reported previously. Seventy-nine novel variant-metabolite associations have been replicated, including three genetic loci located on the X chromosome that have demonstrated its involvement in metabolic regulation. Gene-based analysis have provided further support for seven metabolite-replicated loci pairs and their biologically plausible genes. Among those novel replicated variant-metabolite pairs, follow-up analyses have revealed that 26 metabolites have colocalized with 21 tissues, seven metabolite-disease outcome associations have been putatively causal, and 7 metabolites might be regulated by plasma protein levels. Our results have depicted the genetic contribution to circulating metabolite levels, providing additional insights into understanding human disease.

Association of healthy dietary patterns and cardiorespiratory fitness in the community.

AIMS: To evaluate the associations of dietary indices and quantitative cardiorespiratory fitness (CRF) measures in a large, community-based sample harnessing metabolomic profiling to interrogate shared biology. METHODS AND RESULTS: Framingham Heart Study (FHS) participants underwent maximum effort cardiopulmonary exercise tests for CRF quantification (via peak VO2) and completed semi-quantitative food frequency questionnaires. Dietary quality was assessed by the Alternative Healthy Eating Index (AHEI) and Mediterranean-style Diet Score (MDS), and fasting blood concentrations of 201 metabolites were quantified. In 2380 FHS participants (54 ± 9 years, 54% female, body mass index 28 ± 5 kg/m2), 1 SD higher AHEI and MDS were associated with 5.2% (1.2 mL/kg/min, 95% CI 4.3-6.0%, P < 0.0001) and 4.5% (1.0 mL/kg/min, 95% CI 3.6-5.3%, P < 0.0001) greater peak VO2 in linear models adjusted for age, sex, total daily energy intake, cardiovascular risk factors, and physical activity. In participants with metabolite profiling (N = 1154), 24 metabolites were concordantly associated with both dietary indices and peak VO2 in multivariable-adjusted linear models (FDR < 5%). Metabolites that were associated with lower CRF and poorer dietary quality included C6 and C7 carnitines, C16:0 ceramide, and dimethylguanidino valeric acid, and metabolites that were positively associated with higher CRF and favourable dietary quality included C38:7 phosphatidylcholine plasmalogen and C38:7 and C40:7 phosphatidylethanolamine plasmalogens. CONCLUSION: Higher diet quality is associated with greater CRF cross-sectionally in a middle-aged community-dwelling sample, and metabolites highlight potential shared favourable effects on cardiometabolic health.

This study seeks to address whether healthy dietary patterns relate to gold-standard measures of physical fitness in community-dwelling adults and how circulating metabolites can demonstrate biological relationships between diet and fitness. Healthy diet is associated with greater physical fitness in middle-aged adults. The beneficial relationship between diet and fitness may be partly explained by favourable metabolic health.