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.

Longitudinal plasma metabolome patterns and relation to kidney function and proteinuria in pediatric chronic kidney disease.

INTRODUCTION: Understanding plasma metabolome patterns in relation to changing kidney function in pediatric chronic kidney disease (CKD) is important for continued research for identifying novel biomarkers, characterizing biochemical pathophysiology, and developing targeted interventions. There is a limited number of studies of longitudinal metabolomics, and virtually none in pediatric CKD. METHODS: The Chronic Kidney Disease in Children (CKiD) study is a multi-institutional, prospective cohort that enrolled children aged six-months to 16-years with estimated glomerular filtration rate (eGFR) 30-90ml/min/1.73m2. Untargeted metabolomics profiling was performed on plasma samples from the baseline, two-, and four-year study visits. There were technologic updates in the metabolomic profiling platform used between the baseline and follow-up assays. Statistical approaches were adopted to avoid direct comparison of baseline and follow-up measurements.To identify metabolite associations with eGFR or urine protein:creatinine (UPCR) among all three timepoints, we applied linear mixed effects (LME) models. To identify metabolites associated with time, we applied LME models to the two- and four-year follow-up data. We applied linear regression analysis to examine associations between change in metabolite level over time (∆level) and change in eGFR (∆eGFR) and UPCR (∆UPCR). We reported significance based on both the False Discovery Rate (FDR) <0.05 and p<0.05. RESULTS: There were 1156 person-visits (N: baseline=626, 2-year=254, 4-year=276) included. There were 622 metabolites with standardized measurements at all three timepoints. In LME modeling, 406 and 343 metabolites associated with eGFR and UPCR at FDR<0.05 respectively. Among 530 follow-up person-visits, 158 metabolites showed differences over time at FDR<0.05. For participants with complete data at both follow-up visits (N=123), we report 35 metabolites with ∆level∼∆eGFR associations significant at FDR<0.05. There were no metabolites with significant ∆level∼∆UPCR associations at FDR<0.05. We report 16 metabolites with ∆level∼∆UPCR associations at p<0.05 and associations with UPCR in LME modeling at FDR<0.05. CONCLUSION: We characterized longitudinal plasma metabolomic patterns associated with eGFR and UPCR in a large pediatric CKD population. Many of these metabolite signals have been associated with CKD progression, etiology, and proteinuria in previous CKD Biomarkers Consortium studies. There were also novel metabolite associations with eGFR and proteinuria detected.

Atmospheric black carbon aerosol: Long-term characteristics, source apportionment, and trends.

Black carbon (BC) aerosols play a very significant role in influencing air quality, climate, and human health. Large uncertainties still exist in BC emissions due to limited observations on the relative source contributions of fossil fuel (ff) combustion and biomass (wood fuel, wf) burning. Our understanding of long-term changes in BC emissions, especially their source apportionment, is sparse and limited. For the first time, BC characteristics, its source apportionment into ff and wf components, and their trends measured using a multi-wavelength aethalometer over an urban location (Ahmedabad) in India covering a 14 year period (2006-2019) are comprehensively investigated. The average contributions of eBCff and eBCwf concentrations to total eBC are 80 % and 20 %, respectively, which highlights dominance of emissions from fossil fuel combustion processes. A statistically significant increasing trend in eBC and eBCff mass concentrations at the rate of 11 % and 29%yr-1, respectively, and a decreasing trend in eBCwf concentration at the rate of 36%yr-1 are detected. The study reveals a significant decrease in biomass (wood fuel) burning emissions over past decade and an increase in emissions from fossil fuel combustion. However, rates of increase and decrease in eBCff and eBCwf are different, which indicate that rapid urbanization led to an increase in anthropogenic emissions, whereas an increase in usage of non-polluting fuel led to a decreasing trend in wood burning contribution. During weekdays and weekends, eBC and eBCff mass concentrations did not exhibit any statistically significant trends. However, eBCwf concentration shows a statistically significant decreasing trend during weekdays 34%yr-1 and weekends 38%yr-1. Globally, countries are adopting various strategies and mitigation policies on air quality; however, significant gaps exist in their implementation towards cleaner air. This comprehensive study is relevant for understanding the impact of urbanization and devising better BC emission control policies.

Prognostic Value of Cardiovascular Biomarkers in the Population.

Importance: Identification of individuals at high risk for atherosclerotic cardiovascular disease within the population is important to inform primary prevention strategies. Objective: To evaluate the prognostic value of routinely available cardiovascular biomarkers when added to established risk factors. Design, Setting, and Participants: Individual-level analysis including data on cardiovascular biomarkers from 28 general population-based cohorts from 12 countries and 4 continents with assessments by participant age. The median follow-up was 11.8 years. Exposure: Measurement of high-sensitivity cardiac troponin I, high-sensitivity cardiac troponin T, N-terminal pro-B-type natriuretic peptide, B-type natriuretic peptide, or high-sensitivity C-reactive protein. Main Outcomes and Measures: The primary outcome was incident atherosclerotic cardiovascular disease, which included all fatal and nonfatal events. The secondary outcomes were all-cause mortality, heart failure, ischemic stroke, and myocardial infarction. Subdistribution hazard ratios (HRs) for the association of biomarkers and outcomes were calculated after adjustment for established risk factors. The additional predictive value of the biomarkers was assessed using the C statistic and reclassification analyses. Results: The analyses included 164 054 individuals (median age, 53.1 years [IQR, 42.7-62.9 years] and 52.4% were women). There were 17 211 incident atherosclerotic cardiovascular disease events. All biomarkers were significantly associated with incident atherosclerotic cardiovascular disease (subdistribution HR per 1-SD change, 1.13 [95% CI, 1.11-1.16] for high-sensitivity cardiac troponin I; 1.18 [95% CI, 1.12-1.23] for high-sensitivity cardiac troponin T; 1.21 [95% CI, 1.18-1.24] for N-terminal pro-B-type natriuretic peptide; 1.14 [95% CI, 1.08-1.22] for B-type natriuretic peptide; and 1.14 [95% CI, 1.12-1.16] for high-sensitivity C-reactive protein) and all secondary outcomes. The addition of each single biomarker to a model that included established risk factors improved the C statistic. For 10-year incident atherosclerotic cardiovascular disease in younger people (aged <65 years), the combination of high-sensitivity cardiac troponin I, N-terminal pro-B-type natriuretic peptide, and high-sensitivity C-reactive protein resulted in a C statistic improvement from 0.812 (95% CI, 0.8021-0.8208) to 0.8194 (95% CI, 0.8089-0.8277). The combination of these biomarkers also improved reclassification compared with the conventional model. Improvements in risk prediction were most pronounced for the secondary outcomes of heart failure and all-cause mortality. The incremental value of biomarkers was greater in people aged 65 years or older vs younger people. Conclusions and Relevance: Cardiovascular biomarkers were strongly associated with fatal and nonfatal cardiovascular events and mortality. The addition of biomarkers to established risk factors led to only a small improvement in risk prediction metrics for atherosclerotic cardiovascular disease, but was more favorable for heart failure and mortality.

Association of Aortic Stiffness and Pressure Pulsatility With Noninvasive Estimates of Hepatic Steatosis and Fibrosis: The Framingham Heart Study.

BACKGROUND: Arterial stiffening may contribute to the pathogenesis of metabolic dysfunction-associated steatotic liver disease. We aimed to assess relations of vascular hemodynamic measures with measures of hepatic steatosis and fibrosis in the community. METHODS: Our sample was drawn from the Framingham Offspring, New Offspring Spouse, Third Generation, Omni-1, and Omni-2 cohorts (N=3875; mean age, 56 years; 54% women). We used vibration-controlled transient elastography to assess controlled attenuation parameter and liver stiffness measurements as measures of liver steatosis and liver fibrosis, respectively. We assessed noninvasive vascular hemodynamics using arterial tonometry. We assessed cross-sectional relations of vascular hemodynamic measures with continuous and dichotomous measures of hepatic steatosis and fibrosis using multivariable linear and logistic regression. RESULTS: In multivariable models adjusting for cardiometabolic risk factors, higher carotid-femoral pulse wave velocity (estimated ß per SD, 0.05 [95% CI, 0.01-0.09]; P=0.003), but not forward pressure wave amplitude and central pulse pressure, was associated with more liver steatosis (higher controlled attenuation parameter). Additionally, higher carotid-femoral pulse wave velocity (ß=0.11 [95% CI, 0.07-0.15]; P<0.001), forward pressure wave amplitude (ß=0.05 [95% CI, 0.01-0.09]; P=0.01), and central pulse pressure (ß=0.05 [95% CI, 0.01-0.09]; P=0.01) were associated with more hepatic fibrosis (higher liver stiffness measurement). Associations were more prominent among men and among participants with obesity, diabetes, and metabolic syndrome (interaction P values, <0.001-0.04). Higher carotid-femoral pulse wave velocity, but not forward pressure wave amplitude and central pulse pressure, was associated with higher odds of hepatic steatosis (odds ratio, 1.16 [95% CI, 1.02-1.31]; P=0.02) and fibrosis (odds ratio, 1.40 [95% CI, 1.19-1.64]; P<0.001). CONCLUSIONS: Elevated aortic stiffness and pressure pulsatility may contribute to hepatic steatosis and fibrosis.

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, 1.13-1.38]; P=6.38×10-6; hazard ratioexpressed 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.

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.

Integrated Proteomic and Metabolomic Modules associated with Risk of Kidney Disease Progression.

BACKGROUND: Proteins and metabolites play crucial roles in various biological functions and are frequently interconnected through enzymatic or transport processes. METHODS: We present an integrated analysis of 4,091 proteins and 630 metabolites in the Chronic Renal Insufficiency Cohort Study (N=1,708; average follow-up for kidney failure [KF], 9.5 years, with 537 events). Proteins and metabolites were integrated using an unsupervised clustering method and we assessed associations between clusters and CKD progression and kidney failure using Cox proportional hazards models. Analyses were adjusted for demographics and risk factors including the estimated glomerular filtration rate (eGFR) and urine protein-creatinine ratio. Associations were identified in a discovery sample (random two-thirds, N=1139) and then evaluated in a replication sample (one-third, N=569). RESULTS: We identified 139 modules of correlated proteins and metabolites, which were represented by their principal components (PC). Modules and PC loadings were projected onto the replication sample which demonstrated a consistent network structure. Two modules, representing a total of 236 proteins and 82 metabolites, were robustly associated with both CKD progression and kidney failure in both discovery and validation samples. Using gene set enrichment, several transmembrane related terms were identified as over-represented in these modules. Transmembrane-ephrin receptor activity displayed the largest odds (OR = 13.2, P-value = 5.5×10 -5 ). A module containing CRIM1 and NPNT expressed in podocytes demonstrated particularly strong associations with kidney failure (P-value = 2.6×10 -5 ). CONCLUSIONS: This study demonstrates that integration of the proteome and metabolome can identify functions of pathophysiologic importance in kidney disease.

Gut microbiome and metabolome profiling in Framingham heart study reveals cholesterol-metabolizing bacteria.

Accumulating evidence suggests that cardiovascular disease (CVD) is associated with an altered gut microbiome. Our understanding of the underlying mechanisms has been hindered by lack of matched multi-omic data with diagnostic biomarkers. To comprehensively profile gut microbiome contributions to CVD, we generated stool metagenomics and metabolomics from 1,429 Framingham Heart Study participants. We identified blood lipids and cardiovascular health measurements associated with microbiome and metabolome composition. Integrated analysis revealed microbial pathways implicated in CVD, including flavonoid, γ-butyrobetaine, and cholesterol metabolism. Species from the Oscillibacter genus were associated with decreased fecal and plasma cholesterol levels. Using functional prediction and in vitro characterization of multiple representative human gut Oscillibacter isolates, we uncovered conserved cholesterol-metabolizing capabilities, including glycosylation and dehydrogenation. These findings suggest that cholesterol metabolism is a broad property of phylogenetically diverse Oscillibacter spp., with potential benefits for lipid homeostasis and cardiovascular health.

Heterogeneity in elevated glucose and A1C as predictors of the prediabetes to diabetes transition: Framingham Heart Study, Multi-Ethnic Study on Atherosclerosis, Jackson Heart Study, and Atherosclerosis Risk In Communities.

Introduction: There are a number of glycemic definitions for prediabetes; however, the heterogeneity in diabetes transition rates from prediabetes across different glycemic definitions in major US cohorts has been unexplored. We estimate the variability in risk and relative risk of adiposity based on diagnostic criteria like fasting glucose and hemoglobin A1C% (HA1C%). Research Design and Methods: We estimated transition rate from prediabetes, as defined by fasting glucose between 100-125 and/or 110-125 mg/dL, and HA1C% between 5.7-6.5% in participant data from the Framingham Heart Study, Multi-Ethnic Study on Atherosclerosis, Atherosclerosis Risk in Communities, and the Jackson Heart Study. We estimated the heterogeneity and prediction interval across cohorts, stratifying by age, sex, and body mass index. For individuals who were prediabetic, we estimated the relative risk for obesity, blood pressure, education, age, and sex for diabetes. Results: There is substantial heterogeneity in diabetes transition rates across cohorts and prediabetes definitions with large prediction intervals. We observed the highest range of rates in individuals with fasting glucose of 110-125 mg/dL ranging from 2-18 per 100 person-years. Across different cohorts, the association obesity or hypertension in the progression to diabetes was consistent, yet it varied in magnitude. We provide a database of transition rates across subgroups and cohorts for comparison in future studies. Conclusion: The absolute transition rate from prediabetes to diabetes significantly depends on cohort and prediabetes definitions.

Adjustment for Renal Function Improves the Prognostic Performance of Urinary Thromboxane Metabolites.

BACKGROUND: Systemic thromboxane A2 generation, assessed by quantifying the concentration of stable thromboxane B2 metabolites (TXB2-M) in the urine adjusted for urinary creatinine, is strongly associated with mortality risk. We sought to define optimal TXB2-M cutpoints for aspirin users and nonusers and determine if adjusting TXB2-M for estimated glomerular filtration rate (eGFR) in addition to urinary creatinine improved mortality risk assessment. METHODS: Urinary TXB2-M were measured by competitive ELISA in 1363 aspirin users and 1681 nonusers participating in the Framingham Heart Study. Cutpoints were determined for TXB2-M and TXB2-M/eGFR using log-rank statistics and used to assess mortality risk by Cox proportional hazard modeling and restricted mean survival time. Multivariable models were compared using the Akaike Information Criterion (AIC). A cohort of 105 aspirin users with heart failure was used for external validation. RESULTS: Optimized cutpoints of TXB2-M were 1291 and 5609 pg/mg creatinine and of TXB2-M/eGFR were 16.6 and 62.1 filtered prostanoid units (defined as pg·min/creatinine·mL·1.73 m2), for aspirin users and nonusers, respectively. TXB2-M/eGFR cutpoints provided more robust all-cause mortality risk discrimination than TXB2-M cutpoints, with a larger unadjusted hazard ratio (2.88 vs 2.16, AIC P < 0.0001) and greater differences in restricted mean survival time between exposure groups (1.46 vs 1.10 years), findings that were confirmed in the external validation cohort of aspirin users. TXB2-M/eGFR cutpoints also provided better cardiovascular/stroke mortality risk discrimination than TXB2-M cutpoints (unadjusted hazard ratio 3.31 vs 2.13, AIC P < 0.0001). CONCLUSION: Adjustment for eGFR strengthens the association of urinary TXB2-M with long-term mortality risk irrespective of aspirin use.

Closing the Last Mile Gap in Access to Multimodality Imaging in Rural Settings: Design of the Imaging Core of the Risk Underlying Rural Areas Longitudinal Study.

Achieving optimal cardiovascular health in rural populations can be challenging for several reasons including decreased access to care with limited availability of imaging modalities, specialist physicians, and other important health care team members. Therefore, innovative solutions are needed to optimize health care and address cardiovascular health disparities in rural areas. Mobile examination units can bring imaging technology to underserved or remote communities with limited access to health care services. Mobile examination units can be equipped with a wide array of assessment tools and multiple imaging modalities such as computed tomography scanning and echocardiography. The detailed structural assessment of cardiovascular and lung pathology, as well as the detection of extracardiac pathology afforded by computed tomography imaging combined with the functional and hemodynamic assessments acquired by echocardiography, yield deep phenotyping of heart and lung disease for populations historically underrepresented in epidemiological studies. Moreover, by bringing the mobile examination unit to local communities, innovative approaches are now possible including engagement with local professionals to perform these imaging assessments, thereby augmenting local expertise and experience. However, several challenges exist before mobile examination unit-based examinations can be effectively integrated into the rural health care setting including standardizing acquisition protocols, maintaining consistent image quality, and addressing ethical and privacy considerations. Herein, we discuss the potential importance of cardiac multimodality imaging to improve cardiovascular health in rural regions, outline the emerging experience in this field, highlight important current challenges, and offer solutions based on our experience in the RURAL (Risk Underlying Rural Areas Longitudinal) cohort study.

Familial Hypercholesterolemia Variant and Cardiovascular Risk in Individuals With Elevated Cholesterol.

Importance: Familial hypercholesterolemia (FH) is a genetic disorder that often results in severely high low-density lipoprotein cholesterol (LDL-C) and high risk of premature coronary heart disease (CHD). However, the impact of FH variants on CHD risk among individuals with moderately elevated LDL-C is not well quantified. Objective: To assess CHD risk associated with FH variants among individuals with moderately (130-189 mg/dL) and severely (≥190 mg/dL) elevated LDL-C and to quantify excess CHD deaths attributable to FH variants in US adults. Design, Setting, and Participants: A total of 21 426 individuals without preexisting CHD from 6 US cohort studies (Atherosclerosis Risk in Communities study, Coronary Artery Risk Development in Young Adults study, Cardiovascular Health Study, Framingham Heart Study Offspring cohort, Jackson Heart Study, and Multi-Ethnic Study of Atherosclerosis) were included, 63 of whom had an FH variant. Data were collected from 1971 to 2018, and the median (IQR) follow-up was 18 (13-28) years. Data were analyzed from March to May 2023. Exposures: LDL-C, cumulative past LDL-C, FH variant status. Main Outcomes and Measures: Cox proportional hazards models estimated associations between FH variants and incident CHD. The Cardiovascular Disease Policy Model projected excess CHD deaths associated with FH variants in US adults. Results: Of the 21 426 individuals without preexisting CHD (mean [SD] age 52.1 [15.5] years; 12 041 [56.2%] female), an FH variant was found in 22 individuals with moderately elevated LDL-C (0.3%) and in 33 individuals with severely elevated LDL-C (2.5%). The adjusted hazard ratios for incident CHD comparing those with and without FH variants were 2.9 (95% CI, 1.4-6.0) and 2.6 (95% CI, 1.4-4.9) among individuals with moderately and severely elevated LDL-C, respectively. The association between FH variants and CHD was slightly attenuated when further adjusting for baseline LDL-C level, whereas the association was no longer statistically significant after adjusting for cumulative past LDL-C exposure. Among US adults 20 years and older with no history of CHD and LDL-C 130 mg/dL or higher, more than 417 000 carry an FH variant and were projected to experience more than 12 000 excess CHD deaths in those with moderately elevated LDL-C and 15 000 in those with severely elevated LDL-C compared with individuals without an FH variant. Conclusions and Relevance: In this pooled cohort study, the presence of FH variants was associated with a 2-fold higher CHD risk, even when LDL-C was only moderately elevated. The increased CHD risk appeared to be largely explained by the higher cumulative LDL-C exposure in individuals with an FH variant compared to those without. Further research is needed to assess the value of adding genetic testing to traditional phenotypic FH screening.

Association analysis of mitochondrial DNA heteroplasmic variants: methods and application.

We rigorously assessed a comprehensive association testing framework for heteroplasmy, employing both simulated and real-world data. This framework employed a variant allele fraction (VAF) threshold and harnessed multiple gene-based tests for robust identification and association testing of heteroplasmy. Our simulation studies demonstrated that gene-based tests maintained an appropriate type I error rate at α=0.001. Notably, when 5% or more heteroplasmic variants within a target region were linked to an outcome, burden-extension tests (including the adaptive burden test, variable threshold burden test, and z-score weighting burden test) outperformed the sequence kernel association test (SKAT) and the original burden test. Applying this framework, we conducted association analyses on whole-blood derived heteroplasmy in 17,507 individuals of African and European ancestries (31% of African Ancestry, mean age of 62, with 58% women) with whole genome sequencing data. We performed both cohort- and ancestry-specific association analyses, followed by meta-analysis on both pooled samples and within each ancestry group. Our results suggest that mtDNA-encoded genes/regions are likely to exhibit varying rates in somatic aging, with the notably strong associations observed between heteroplasmy in the RNR1 and RNR2 genes (p<0.001) and advance aging by the Original Burden test. In contrast, SKAT identified significant associations (p<0.001) between diabetes and the aggregated effects of heteroplasmy in several protein-coding genes. Further research is warranted to validate these findings. In summary, our proposed statistical framework represents a valuable tool for facilitating association testing of heteroplasmy with disease traits in large human populations.

Plasma Metabolomics of Dietary Intake of Protein-Rich Foods and Kidney Disease Progression in Children.

OBJECTIVE: Evidence regarding the efficacy of a low-protein diet for patients with CKD is inconsistent and recommending a low-protein diet for pediatric patients is controversial. There is also a lack of objective biomarkers of dietary intake. The purpose of this study was to identify plasma metabolites associated with dietary intake of protein and to assess whether protein-related metabolites are associated with CKD progression. METHODS: Nontargeted metabolomics was conducted in plasma samples from 484 Chronic Kidney Disease in Children (CKiD) participants. Multivariable linear regression estimated the cross-sectional association between 949 known, nondrug metabolites and dietary intake of total protein, animal protein, plant protein, chicken, dairy, nuts and beans, red and processed meat, fish, and eggs, adjusting for demographic, clinical, and dietary covariates. Cox proportional hazards models assessed the prospective association between protein-related metabolites and CKD progression defined as the initiation of kidney replacement therapy or 50% eGFR reduction, adjusting for demographic and clinical covariates. RESULTS: One hundred and twenty-seven (26%) children experienced CKD progression during 5 years of follow-up. Sixty metabolites were significantly associated with dietary protein intake. Among the 60 metabolites, 10 metabolites were significantly associated with CKD progression (animal protein: n = 1, dairy: n = 7, red and processed meat: n = 2, nuts and beans: n = 1), including one amino acid, one cofactor and vitamin, 4 lipids, 2 nucleotides, one peptide, and one xenobiotic. 1-(1-enyl-palmitoyl)-2-oleoyl-glycerophosphoethanolamine (GPE, P-16:0/18:1) was positively associated with dietary intake of red and processed meat, and a doubling of its abundance was associated with 88% higher risk of CKD progression. 3-ureidopropionate was inversely associated with dietary intake of red and processed meat, and a doubling of its abundance was associated with 48% lower risk of CKD progression. CONCLUSIONS: Untargeted plasma metabolomic profiling revealed metabolites associated with dietary intake of protein and CKD progression in a pediatric population.

Prevalence of Aortic Valve Calcium and the Long-Term Risk of Incident Severe Aortic Stenosis.

BACKGROUND: Aortic valve calcification (AVC) is a principal mechanism underlying aortic stenosis (AS). OBJECTIVES: This study sought to determine the prevalence of AVC and its association with the long-term risk for severe AS. METHODS: Noncontrast cardiac computed tomography was performed among 6,814 participants free of known cardiovascular disease at MESA (Multi-Ethnic Study of Atherosclerosis) visit 1. AVC was quantified using the Agatston method, and normative age-, sex-, and race/ethnicity-specific AVC percentiles were derived. The adjudication of severe AS was performed via chart review of all hospital visits and supplemented with visit 6 echocardiographic data. The association between AVC and long-term incident severe AS was evaluated using multivariable Cox HRs. RESULTS: AVC was present in 913 participants (13.4%). The probability of AVC >0 and AVC scores increased with age and were generally highest among men and White participants. In general, the probability of AVC >0 among women was equivalent to men of the same race/ethnicity who were approximately 10 years younger. Incident adjudicated severe AS occurred in 84 participants over a median follow-up of 16.7 years. Higher AVC scores were exponentially associated with the absolute risk and relative risk of severe AS with adjusted HRs of 12.9 (95% CI: 5.6-29.7), 76.4 (95% CI: 34.3-170.2), and 380.9 (95% CI: 169.7-855.0) for AVC groups 1 to 99, 100 to 299, and ≥300 compared with AVC = 0. CONCLUSIONS: The probability of AVC >0 varied significantly by age, sex, and race/ethnicity. The risk of severe AS was exponentially higher with higher AVC scores, whereas AVC = 0 was associated with an extremely low long-term risk of severe AS. The measurement of AVC provides clinically relevant information to assess an individual's long-term risk for severe AS.

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.

Nonalcoholic fatty liver disease, liver fibrosis, and structural brain imaging: The Cross-Cohort Collaboration.

BACKGROUND AND PURPOSE: Prior studies reported conflicting findings regarding the association of nonalcoholic fatty liver disease (NAFLD) and liver fibrosis with measures of brain health. We examined whether NAFLD and liver fibrosis are associated with structural brain imaging measures in middle- and old-age adults. METHODS: In this cross-sectional study among dementia- and stroke-free individuals, data were pooled from the Offspring and Third Generation cohorts of the Framingham Heart Study (FHS), the Rotterdam Study (RS), and the Study of Health in Pomerania. NAFLD was assessed through abdominal imaging. Transient hepatic elastography (FibroScan) was used to assess liver fibrosis in FHS and RS. Linear regression models were used to explore the relation of NAFLD and liver fibrosis with brain volumes, including total brain, gray matter, hippocampus, and white matter hyperintensities, adjusting for potential confounders. Results were combined using fixed effects meta-analysis. RESULTS: In total, 5660 and 3022 individuals were included for NAFLD and liver fibrosis analyses, respectively. NAFLD was associated with smaller volumes of total brain (ß = -3.5, 95% confidence interval [CI] = -5.4 to -1.7), total gray matter (ß = -1.9, 95% CI = -3.4 to -0.3), and total cortical gray matter (ß = -1.9, 95% CI = -3.7 to -0.01). In addition, liver fibrosis (defined as liver stiffness measure ≥8.2 kPa) was related to smaller total brain volumes (ß = -7.3, 95% CI = -11.1 to -3.5). Heterogeneity between studies was low. CONCLUSIONS: NAFLD and liver fibrosis may be directly related to brain aging. Larger and prospective studies are warranted to validate these findings and identify liver-related preventive strategies for neurodegeneration.

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.