Cohort Profile: The Framingham Heart Study (FHS): overview of milestones in cardiovascular epidemiology

Animal Models Relevant for Geroscience: Current Trends and Future Perspectives in Biomarkers, and Measures of Biological Aging

For centuries, aging was considered inevitable and immutable. Geroscience provides the conceptual framework to shift this focus toward a new view that regards aging as an active biological process, and the biological age of an individual as a modifiable entity. Significant steps forward have been made toward the identification of biomarkers for and measures of biological age, yet knowledge gaps in geroscience are still numerous. Animal models of aging are the focus of this perspective, which discusses how experimental design can be optimized to inform and refine the development of translationally relevant measures and biomarkers of biological age. We provide recommendations to the field, including: the design of longitudinal studies in which subjects are deeply phenotyped via repeated multilevel behavioral/social/molecular assays; the need to consider sociobehavioral variables relevant for the species studied; and finally, the importance of assessing age of onset, severity of pathologies, and age-at-death. We highlight approaches to integrate biomarkers and measures of functional impairment using machine learning approaches designed to estimate biological age as well as to predict future health declines and mortality. We expect that advances in animal models of aging will be crucial for the future of translational geroscience but also for the next chapter of medicine.

Obstructive Sleep Apnea, Platelet Aggregation, and Cardiovascular Risk

BACKGROUND

Although related, the precise mechanisms linking obstructive sleep apnea (OSA) and cardiovascular disease (CVD) are unclear. Platelets are mediators of CVD risk and thrombosis and prior studies suggested associations of OSA and platelet activity. The aim of this study is to assess the link between OSA, platelet activity, and CVD-related risk factors.

METHODS AND RESULTS

We studied the association of OSA-measures and platelet aggregation in participants dually enrolled in the SHHS (Sleep Heart and Health Study) and FHS (Framingham Heart Study). We applied linear regression models with adjustment for demographic and clinical covariates and explored interactions with OSA and CVD-related factors, including age, sex, body mass index, hypertension, OSA diagnosis (apnea-hypopnea index 4%≥5), and aspirin use. Our final sample was of 482 participants (60 years [14.00], 50.4% female). No associations were observed between apnea-hypopnea index 4% and platelet aggregation in the main sample. Stratified analysis revealed an association in aspirin users (n=65) for our primary exposure (apnea-hypopnea index 4%, β=0.523; P<0.001; n=65), and secondary exposures: hypoxic burden (β=0.358; P<0.001), minimum saturation (β=-0.519; P=0.026), and oxygen desaturation index 3% (β=74.672; P=0.002). No associations were detected in nonaspirin users (n=417).

CONCLUSIONS

No associations were detected between OSA and platelet aggregation in a community sample. Our finding that OSA associates with increased platelet aggregation in the aspirin group, most of whom use it for primary prevention of CVD, suggests that platelet aggregation may mediate the adverse impact of OSA on vascular health in individuals with existing CVD risk, supporting further investigation.

Adverse cardiac events of hypercholesterolemia are enhanced by sitagliptin in sprague dawley rats

BACKGROUND

Cardiovascular disease (CVD) affects millions worldwide and is the leading cause of death among non-communicable diseases. Western diets typically comprise of meat and dairy products, both of which are rich in cholesterol (Cho) and methionine (Met), two well-known compounds with atherogenic capabilities. Despite their individual effects, literature on a dietary combination of the two in the context of CVD are limited. Therefore, studies on the combined effects of Cho and Met were carried out using male Sprague Dawley rats. An additional interest was to investigate the cardioprotective potential of sitagliptin, an anti-type 2 diabetic drug. We hypothesized that feeding a dietary combination of Cho and Met would result in adverse cardiac effects and would be attenuated upon administration of sitagliptin.

METHODS

Adult male Sprague-Dawley rats were fed either a control (Con), high Met (1.5%), high Cho (2.0%), or high Met (1.5%) + high Cho (2.0%) diet for 35 days. They were orally gavaged with an aqueous preparation of sitagliptin (100 mg/kg/d) or vehicle (water) from day 10 through 35. On day 36, rats were euthanized, and tissues were collected for analysis.

RESULTS

Histopathological evaluation revealed a reduction in myocardial striations and increased collagen deposition in hypercholesterolemia (HChol), responses that became exacerbated upon sitagliptin administration. Cardiac pro-inflammatory and pro-fibrotic responses were adversely impacted in similar fashion. The addition of Met to Cho (MC) attenuated all adverse structural and biochemical responses, with or without sitagliptin.

CONCLUSIONS

Adverse cardiac outcomes in HChol were enhanced by the administration of sitagliptin, and such effects were alleviated by Met. Our findings could be significant for understanding or revisiting the risk-benefit evaluation of sitagliptin in type 2 diabetics, and especially those who are known to consume atherogenic diets.

Epigenome-wide DNA Methylation Association Study of CHIP Provides Insight into Perturbed Gene Regulation

With age, hematopoietic stem cells can acquire somatic mutations in leukemogenic genes that confer a proliferative advantage in a phenomenon termed "clonal hematopoiesis of indeterminate potential" (CHIP). How these mutations confer a proliferative advantage and result in increased risk for numerous age-related diseases remains poorly understood. We conducted a multiracial meta-analysis of epigenome-wide association studies (EWAS) of CHIP and its subtypes in four cohorts (N=8196) to elucidate the molecular mechanisms underlying CHIP and illuminate how these changes influence cardiovascular disease risk. The EWAS findings were functionally validated using human hematopoietic stem cell (HSC) models of CHIP. A total of 9615 CpGs were associated with any CHIP, 5990 with DNMT3A CHIP, 5633 with TET2 CHIP, and 6078 with ASXL1 CHIP (P <1×10-7). CpGs associated with CHIP subtypes overlapped moderately, and the genome-wide DNA methylation directions of effect were opposite for TET2 and DNMT3A CHIP, consistent with their opposing effects on global DNA methylation. There was high directional concordance between the CpGs shared from the meta-EWAS and human edited CHIP HSCs. Expression quantitative trait methylation analysis further identified transcriptomic changes associated with CHIP-associated CpGs. Causal inference analyses revealed 261 CHIP-associated CpGs associated with cardiovascular traits and all-cause mortality (FDR adjusted p-value <0.05). Taken together, our study sheds light on the epigenetic changes impacted by CHIP and their associations with age-related disease outcomes. The novel genes and pathways linked to the epigenetic features of CHIP may serve as therapeutic targets for preventing or treating CHIP-mediated diseases.

Prevalence and characteristics of chronic kidney disease in people with type 2 diabetes mellitus in the Autonomous Community of Aragon

AIMS

The main objective in this study was to determine the prevalence of Chronic Kidney Disease (CKD) in people with Type 2 Diabetes Mellitus (T2DM) in the Autonomous Community (AC) of Aragon (Spain) and to detect whether or not there is under-registration in the patient's history. As a secundary objetive, it was proposed to study the most relevant demographic and clinical characteristics of people with CKD.

METHODS

Observational and retrospective real world data study of the population over 18 years of age with a diagnosis of T2DM, between January 2017 and December 2021. A descriptive analysis of qualitative and quantitative variables, and a comparison using the parametric Student's t-test or the non-parametric Mann-Whitney U-test between both groups was performed.

RESULTS

The prevalence of T2DM was 8.07 % and that of CKD 31.4 %, with an under-reporting of 47 %. The main risk factor associated with CKD was arterial hypertension (p<0.001), followed by dyslipidemia (p<0.001). The main treatment used for diabetes control was metformin, both in patients with and without CKD (p<0.001). A total of 56.81 % of people with T2DM and CKD did not undergo annual monitoring of their renal function (glomerular filtration rate) or determination of albuminuria.

CONCLUSIONS

The prevalence of CKD increases in patients with T2DM (31.4 %), and in almost half of patients the diagnosis is not registered (47 %). This under-reporting delays the implementation of measures needed to prevent CKD progression.

Brain Cell-based Genetic Subtyping and Drug Repositioning for Alzheimer Disease

Alzheimer's Disease (AD) is characterized by its complex and heterogeneous etiology and gradual progression, leading to high drug failure rates in late-stage clinical trials. In order to better stratify individuals at risk for AD and discern potential therapeutic targets we employed a novel procedure utilizing cell-based co-regulated gene networks and polygenic risk scores (cbPRSs). After defining genetic subtypes using extremes of cbPRS distributions, we evaluated correlations of the genetic subtypes with previously defined AD subtypes defined on the basis of domain-specific cognitive functioning and neuroimaging biomarkers. Employing a PageRank algorithm, we identified priority gene targets for the genetic subtypes. Pathway analysis of priority genes demonstrated associations with neurodegeneration and suggested candidate drugs currently utilized in diabetes, hypertension, and epilepsy for repositioning in AD. Experimental validation utilizing human induced pluripotent stem cell (hiPSC)-derived astrocytes demonstrated the modifying effects of estradiol, levetiracetam, and pioglitazone on expression of APOE and complement C4 genes, suggesting potential repositioning for AD.

Novel Loci (EIF4A2, ADIPOQ, TPRG1) for Triglyceride / High-density Lipoprotein Cholesterol Ratio Longitudinal Change (ΔTHR) among Subjects without Type 2 Diabetes: Evidence from the Long Life Family Study (LLFS) and the Framingham Heart Study (FHS) Offspring Cohort (OS)

Aims/hypothesis

Triglyceride (TG) /High density lipoprotein cholesterol (HDL-C) ratio (THR) represents a single surrogate predictor of hyperinsulinemia or insulin resistance that is associated with premature aging processes, risk of diabetes and increased mortality. To identify novel genetic loci for THR change over time (ΔTHR), we conducted genome-wide association study (GWAS) and genome-wide linkage scan (GWLS) among subjects of European ancestry who had complete data from two exams collected about seven years apart from the Long Life Family Study (LLFS, n=1384), a study with familial clustering of exceptional longevity in the US and Denmark.

Methods

Subjects with diabetes or using medications for dyslipidemia were excluded from this analysis. ΔTHR was derived using growth curve modeling, and adjusted for age, sex, field centers, and principal components (PCs). GWAS was conducted using a linear mixed model accounted for familial relatedness. Our linkage scan was built on haplotype-based IBD estimation with 0.5 cM average spacing.

Results

Heritability of ΔTHR was moderate (46%). Our GWAS identified a significant locus at the LPL (p=1.58e-9) for ΔTHR; this gene locus has been reported before influencing baseline THR levels. Our GWLS found evidence for a significant linkage with a logarithm of the odds (LODs) exceeding 3 on 3q28 (LODs=4.1). Using a subset of 25 linkage enriched families (pedigree-specific LODs>0.1), we assessed sequence elements under 3q28 and identified two novel variants (EIF4A2/ADIPOQ-rs114108468, p=5e-6, MAF=1.8%; TPRG1-rs16864075, p=3e-6, MAF=8%; accounted for ~28% and ~29% of the linkage, respectively, and 57% jointly). While the former variant was associated with EIF4A2 (p=7e-5) / ADIPOQ (p=3.49e-2) RNA transcriptional levels, the latter variant was not associated with TPRG1 (p=0.23) RNA transcriptional levels. Replication in FHS OS observed modest effect of these loci on ΔTHR. Of 188 metabolites from 13 compound classes assayed in LLFS, we observed multiple metabolites (e.g., DG.38.5, PE.36.4, TG.58.3) that were significantly associated with the variants (p<3e-4).

Conclusions

our linkage-guided sequence analysis approach permitted our discovery of two novel gene variants EIF4A2/ADIPOQ-rs114108468 and TPRG1-rs16864075 on 3q28 for ΔTHR among subjects without diabetes selected for exceptional survival and healthy aging.

Epidemiologic Features of Recovery From SARS-CoV-2 Infection

Importance

Persistent symptoms and disability following SARS-CoV-2 infection, known as post-COVID-19 condition or "long COVID," are frequently reported and pose a substantial personal and societal burden.

Objective

To determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days.

Design, Setting, and Participants

For this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health-funded cohorts that have enrolled and followed participants since 1971. This report includes data collected through February 28, 2023, on adults aged 18 years or older with self-reported SARS-CoV-2 infection.

Exposure

Preinfection health conditions and lifestyle factors assessed before and during the pandemic via prepandemic examinations and pandemic-era questionnaires.

Main Outcomes and Measures

Probability of nonrecovery by 90 days and restricted mean recovery times were estimated using Kaplan-Meier curves, and Cox proportional hazards regression was performed to assess multivariable-adjusted associations with recovery by 90 days.

Results

Of 4708 participants with self-reported SARS-CoV-2 infection (mean [SD] age, 61.3 [13.8] years; 2952 women [62.7%]), an estimated 22.5% (95% CI, 21.2%-23.7%) did not recover by 90 days post infection. Median (IQR) time to recovery was 20 (8-75) days. By 90 days post infection, there were significant differences in restricted mean recovery time according to sociodemographic, clinical, and lifestyle characteristics, particularly by acute infection severity (outpatient vs critical hospitalization, 32.9 days [95% CI, 31.9-33.9 days] vs 57.6 days [95% CI, 51.9-63.3 days]; log-rank P < .001). Recovery by 90 days post infection was associated with vaccination prior to infection (hazard ratio [HR], 1.30; 95% CI, 1.11-1.51) and infection during the sixth (Omicron variant) vs first wave (HR, 1.25; 95% CI, 1.06-1.49). These associations were mediated by reduced severity of acute infection (33.4% and 17.6%, respectively). Recovery was unfavorably associated with female sex (HR, 0.85; 95% CI, 0.79-0.92) and prepandemic clinical cardiovascular disease (HR, 0.84; 95% CI, 0.71-0.99). No significant multivariable-adjusted associations were observed for age, educational attainment, smoking history, obesity, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, or elevated depressive symptoms. Results were similar for reinfections.

Conclusions and Relevance

In this cohort study, more than 1 in 5 adults did not recover within 3 months of SARS-CoV-2 infection. Recovery within 3 months was less likely in women and those with preexisting cardiovascular disease and more likely in those with COVID-19 vaccination or infection during the Omicron variant wave.

Physical Activity, Cardiovascular Status, Mortality, and Prediabetes in Hispanic and Non-Hispanic Adults

Importance

Data are limited on the association of physical activity (PA) with incident cardiovascular disease (CVD) and mortality in prediabetes, especially in racial and ethnic minority groups, including Hispanic and Latino populations.

Objective

To determine the association of PA with incident CVD and mortality by prediabetes status among Hispanic or Latino and non-Hispanic adults.

Design, Setting, and Participants

This cohort study included data from 2 cohorts of adults with prediabetes or normoglycemia who were free of CVD at baseline visit: the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) from baseline examination through 2017, with median (IQR) follow-up of 7.8 (7.2-8.5) years, and the Framingham Heart Study (FHS) with non-Hispanic participants from index examination through 2019, with median (IQR) follow-up of 9.6 (8.1-10.7) years. Analyses were conducted between September 1, 2022, and January 10, 2024.

Exposure

The primary exposure was baseline accelerometry-measured moderate to vigorous PA, insufficient vs sufficient to meet 2018 Physical Activity Guidelines for Americans (PAG) in both cohorts; additional accelerometer-measured exposures in HCHS/SOL were steps per day, sedentary behavior, and counts per min.

Main Outcomes and Measures

The outcome was a composite of incident CVD or all-cause mortality, whichever came first.

Results

This cohort study included 13 223 participants: from HCHS/SOL, there were 9456 adults (all self-identified Hispanic or Latino ethnicity; survey-adjusted mean [SD] age, 38.3 [13.9] years, unweighted counts 5673 (60.0%) female; 4882 [51.6%] with normoglycemia; 4574 [48.4%] with prediabetes), and from FHS there were 3767 adults (3623 [96.2%] non-Hispanic and 140 [3.7%] Hispanic or Latino ethnicity, with 4 [0.1%] participants missing ethnicity; mean [SD] age, 54.2 [13.6] years; 2128 (56.5%) female; 2739 [72.7%] with normoglycemia; 1028 [27.3%] with prediabetes). Not meeting PAG was associated with higher risk of the composite outcome among participants with normoglycemia (vs PAG met; hazard ratio [HR], 1.85 [95% CI, 1.12-3.06]), but not among participants with prediabetes (HR, 1.07 [95% CI, 0.72-1.58]). For HCHS/SOL, no statistically significant association was found between the composite outcome and other PA metrics, although estimated HRs tended to be higher for lower activity in the normoglycemia group but not for the prediabetes group (eg, for steps less than vs at least 7000 per day, the HR was 1.58 [95% CI, 0.85-2.93] for normoglycemia vs 1.08 [95% CI 0.67-1.74] for prediabetes). While there was also no association in HCHS/SOL between the composite outcome and sedentary behavior, results were similar in the prediabetes group (HR per 30 minutes per day of sedentary behavior, 1.05 [95% CI 0.99-1.12]) and in the normoglycemia group (HR, 1.07 [95% CI 0.98-1.16]).

Conclusions and Relevance

In this cohort study of US Hispanic or Latino and non-Hispanic adults, lower moderate to vigorous PA levels were associated with CVD or mortality among participants with normoglycemia but not participants with prediabetes. Adults with prediabetes may benefit from reducing sedentary behavior and improving multiple lifestyle factors beyond improving moderate to vigorous PA alone.

Integration of a polygenic score into guideline-recommended prediction of cardiovascular disease

BACKGROUND AND AIMS

It is not clear how a polygenic risk score (PRS) can be best combined with guideline-recommended tools for cardiovascular disease (CVD) risk prediction, e.g. SCORE2.

METHODS

A PRS for coronary artery disease (CAD) was calculated in participants of UK Biobank (n = 432 981). Within each tenth of the PRS distribution, the odds ratios (ORs)-referred to as PRS-factor-for CVD (i.e. CAD or stroke) were compared between the entire population and subgroups representing the spectrum of clinical risk. Replication was performed in the combined Framingham/Atherosclerosis Risk in Communities (ARIC) populations (n = 10 757). The clinical suitability of a multiplicative model 'SCORE2 × PRS-factor' was tested by risk reclassification.

RESULTS

In subgroups with highly different clinical risks, CVD ORs were stable within each PRS tenth. SCORE2 and PRS showed no significant interactive effects on CVD risk, which qualified them as multiplicative factors: SCORE2 × PRS-factor = total risk. In UK Biobank, the multiplicative model moved 9.55% of the intermediate (n = 145 337) to high-risk group increasing the individuals in this category by 56.6%. Incident CVD occurred in 8.08% of individuals reclassified by the PRS-factor from intermediate to high risk, which was about two-fold of those remained at intermediate risk (4.08%). Likewise, the PRS-factor shifted 8.29% of individuals from moderate to high risk in Framingham/ARIC.

CONCLUSIONS

This study demonstrates that absolute CVD risk, determined by a clinical risk score, and relative genetic risk, determined by a PRS, provide independent information. The two components may form a simple multiplicative model improving precision of guideline-recommended tools in predicting incident CVD.

Risk factors for incident cardiovascular events and their population attributable fractions in rural India: The Rishi Valley Prospective Cohort Study

OBJECTIVE

We prospectively determined incident cardiovascular events and their association with risk factors in rural India.

METHODS

We followed up with 7935 adults from the Rishi Valley Prospective Cohort Study to identify incident cardiovascular events. Using Cox proportional hazards regression, we estimated hazard ratios (HRs) with 95% confidence intervals (95% CI) for associations between potential risk factors and cardiovascular events. Population attributable fractions (PAFs) for risk factors were estimated using R ('averisk' package).

RESULTS

Of the 4809 participants without prior cardiovascular disease, 57.7% were women and baseline mean age was 45.3 years. At follow-up (median of 4.9 years, 23,180 person-years [PYs]), 202 participants developed cardiovascular events, equating to an incidence of 8.7 cardiovascular events/1000 PYs. Incidence was greater in those with hypertension (hazard ratio [HR] [95% CI] 1.73 [1.21-2.49], adjusted PAF 18%), diabetes (1.96 [1.15-3.36], 4%) or central obesity (1.77 [1.23, 2.54], 9%) which together accounted for 31% of the PAF. Non-traditional risk factors such as night sleeping hours and number of children accounted for 16% of the PAF.

CONCLUSIONS

Both traditional and non-traditional cardiovascular risk factors are important contributors to incident cardiovascular events in rural India. Interventions targeted to these factors could assist in reducing the incidence of cardiovascular events.

Association Between Young Adult Characteristics and Blood Pressure Trajectories

BACKGROUND

Blood pressure (BP) trajectories from young adulthood through middle age are associated with cardiovascular risk. We examined the associations of hypertension risk factors with BP trajectories among a large diverse sample.

METHODS AND RESULTS

We analyzed data from young adults, aged 18 to 39 years, with untreated BP <140/90 mm Hg at baseline from Kaiser Permanente Southern California (N=355 324). We used latent growth curve models to identify 10-year BP trajectories and to assess the associations between characteristics in young adulthood and BP trajectories. We identified the following 5 distinct systolic BP trajectories, which appeared to be determined mainly by the baseline BP with progressively higher BP at each year: group 1 (lowest BP trajectory, 7.9%), group 2 (26.5%), group 3 (33.0%), group 4 (25.4%), and group 5 (highest BP trajectory, 7.3%). Older age (adjusted odds ratio for 30-39 versus 18-29 years, 1.23 [95% CI, 1.18-1.28]), male sex (13.38 [95% CI, 12.80-13.99]), obesity (body mass index ≥30 versus 18.5-24.9 kg/m2, 14.81 [95% CI, 14.03-15.64]), overweight (body mass index 25-29.9 versus 18.5-24.9 kg/m2, 3.16 [95% CI, 3.00-3.33]), current smoking (1.58 [95% CI, 1.48-1.67]), prediabetes (1.21 [95% CI, 1.13-1.29]), diabetes (1.60 [95% CI, 1.41-1.81]) and high low-density lipoprotein cholesterol (≥160 versus <100 mg/dL, 1.52 [95% CI, 1.37-1.68]) were associated with the highest BP trajectory (group 5) compared with the reference group (group 2).

CONCLUSIONS

Traditional hypertension risk factors including smoking, diabetes, and elevated lipids were associated with BP trajectories in young adults, with obesity having the strongest association with the highest BP trajectory group.

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.

A blood biomarker of the pace of aging is associated with brain structure: replication across three cohorts

Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3380; total N individuals=2322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, greater burden of white matter microlesions, and thinner cortex. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.

Mediation of the association between depression and coronary heart disease by metabolic syndrome components

BACKGROUND

Depression is associated with incident coronary heart disease (CHD) via a pathway that may be causal, but the mechanisms underlying this association are unclear. We assessed the extent to which metabolic syndrome (MetS) and its components (i.e., elevated waist circumference, low high-density lipoprotein [HDL] cholesterol, elevated triglycerides, elevated blood pressure, and elevated fasting plasma glucose) may mediate this association.

METHODS

Data were Framingham Heart Study Research Materials obtained from the National Heart, Lung, and Blood Institute (NHLBI) Biologic Specimen and Data Repository Information Coordinating Center. We used Cox proportional hazards regression to estimate adjusted hazard ratios (aHR) representing the total effect (aHRTE) of probable depression, measured via the Centers for Epidemiological Studies - Depression scale, on incident CHD over approximately 18 years. Using inverse odds ratio weighting, we decomposed this estimate into natural direct effects (aHRNDE) and natural indirect effects (aHRNIE) through potential mediators (measured approximately three years after depression).

RESULTS

Probable depression was associated with incident CHD (aHRTE=1.45, 95% confidence interval [CI]: 0.93, 2.25), and elevated waist circumference partially mediated this association (aHRNDE=1.34, 95% CI: 0.76-2.32; aHRNIE=1.08, 95% CI: 0.63-1.91). We did not find evidence of additional mediation by additional MetS components.

CONCLUSIONS

Elevated waist circumference appears to play a role in the association between depression and CHD.

Vitamin B12 status and folic acid supplementation influence mitochondrial heteroplasmy levels in mice

One-carbon metabolism is a complex network of metabolic reactions that are essential for cellular function including DNA synthesis. Vitamin B12 and folate are micronutrients that are utilized in this pathway and their deficiency can result in the perturbation of one-carbon metabolism and subsequent perturbations in DNA replication and repair. This effect has been well characterized in nuclear DNA but to date, mitochondrial DNA (mtDNA) has not been investigated extensively. Mitochondrial variants have been associated with several inherited and age-related disease states; therefore, the study of factors that impact heteroplasmy are important for advancing our understanding of the mitochondrial genome's impact on human health. Heteroplasmy studies require robust and efficient mitochondrial DNA enrichment to carry out in-depth mtDNA sequencing. Many of the current methods for mtDNA enrichment can introduce biases and false-positive results. Here, we use a method that overcomes these limitations and have applied it to assess mitochondrial heteroplasmy in mouse models of altered one-carbon metabolism. Vitamin B12 deficiency was found to cause increased levels of mitochondrial DNA heteroplasmy across all tissues that were investigated. Folic acid supplementation also contributed to elevated mitochondrial DNA heteroplasmy across all mouse tissues investigated. Heteroplasmy analysis of human data from the Framingham Heart Study suggested a potential sex-specific effect of folate and vitamin B12 status on mitochondrial heteroplasmy. This is a novel relationship that may have broader consequences for our understanding of one-carbon metabolism, mitochondrial-related disease and the influence of nutrients on DNA mutation rates.

Adverse Cardiac Events of Hypercholesterolemia Are Enhanced by Sitagliptin Administration in Sprague Dawley Rats

Background

Cardiovascular disease (CVD) affects millions worldwide and is the leading cause of death among non-communicable diseases. Western diets typically comprise of meat and dairy products, both of which are rich in cholesterol (Cho) and methionine (Met), two well-known compounds with atherogenic capabilities. Despite their individual effects, literature on a dietary combination of the two in the context of CVD are limited. An additional interest was to investigate the cardioprotective potential of sitagliptin, an anti-type 2 diabetic drug. Thus, we hypothesized that atherogenic feeding would result in adverse cardiac effects and would attenuate upon sitagliptin administration.

Methods

Six-week-old adult male Sprague-Dawley rats were fed either a control (Con), high Met (1.5%), high Cho (2.0%), or high Met (1.5%) + high Cho (2.0%) diet for 35 days. They were orally gavaged with vehicle (water) or sitagliptin (100 mg/kg/d) from day 10 through 35. On day 36, rats were euthanized, and tissues were collected for analysis.

Results

Histopathological evaluation revealed a reduction in myocardial striations and increased collagen deposition in hypercholesterolemia (HChol), responses that became exacerbated upon sitagliptin administration. Cardiac pro-inflammatory and pro-fibrotic responses were adversely impacted in similar fashion. The addition of Met to Cho (MC) attenuated all adverse structural and biochemical responses, with or without sitagliptin.

Conclusion

Adverse cardiac outcomes in HChol were enhanced with sitagliptin administration and such effects were alleviated by Met. Our findings could be significant for understanding the risk-benefit of sitagliptin in type 2 diabetics who are known to consume atherogenic diets.

Muscle Reference Values From Thoracic and Abdominal CT for Sarcopenia Assessment: The Framingham Heart Study

BACKGROUND

Loss of muscle mass is a known feature of sarcopenia and predicts poor clinical outcomes. Although muscle metrics can be derived from routine computed tomography (CT) images, sex-specific reference values at multiple vertebral levels over a wide age range are lacking.

OBJECTIVE

The aim of this study was to provide reference values for skeletal muscle mass and attenuation on thoracic and abdominal CT scans in the community-based Framingham Heart Study cohort to aid in the identification of sarcopenia.

MATERIALS AND METHODS

This secondary analysis of a prospective trial describes muscle metrics by age and sex for participants from the Framingham Heart Study without prior history of cancer who underwent at least 1 CT scan between 2002 and 2011. Using 2 previously validated machine learning algorithms followed by human quality assurance, skeletal muscle was analyzed on a single axial CT image per level at the 5th, 8th, 10th thoracic, and 3rd lumbar vertebral body (T5, T8, T10, L3). Cross-sectional muscle area (cm 2 ), mean skeletal muscle radioattenuation (SMRA, in Hounsfield units), skeletal muscle index (SMI, in cm 2 /m 2 ), and skeletal muscle gauge (SMRA·SMI) were calculated. Measurements were summarized by age group (<45, 45-54, 55-64, 65-74, ≥75 years), sex, and vertebral level. Models enabling the calculation of age-, sex-, and vertebral-level-specific reference values were created and embedded into an open access online Web application.

RESULTS

The cohort consisted of 3804 participants (1917 [50.4%] males; mean age, 55.6 ± 11.8 years; range, 33-92 years) and 7162 CT scans. Muscle metrics qualitatively decreased with increasing age and female sex.

CONCLUSIONS

This study established age- and sex-specific reference values for CT-based muscle metrics at thoracic and lumbar vertebral levels. These values may be used in future research investigating the role of muscle mass and attenuation in health and disease, and to identify sarcopenia.

Relative predictive value of sociodemographic factors for chronic diseases among All of Us participants: a descriptive analysis

BACKGROUND

Although sociodemographic characteristics are associated with health disparities, the relative predictive value of different social and demographic factors remains largely unknown. This study aimed to describe the sociodemographic characteristics of All of Us participants and evaluate the predictive value of each factor for chronic diseases associated with high morbidity and mortality.

METHODS

We performed a cross-sectional analysis using de-identified survey data from the All of Us Research Program, which has collected social, demographic, and health information from adults living in the United States since May 2018. Sociodemographic data included self-reported age, sex, gender, sexual orientation, race/ethnicity, income, education, health insurance, primary care provider (PCP) status, and health literacy scores. We analyzed the self-reported prevalence of hypertension, coronary artery disease, any cancer, skin cancer, lung disease, diabetes, obesity, and chronic kidney disease. Finally, we assessed the relative importance of each sociodemographic factor for predicting each chronic disease using the adequacy index for each predictor from logistic regression.

RESULTS

Among the 372,050 participants in this analysis, the median age was 53 years, 59.8% reported female sex, and the most common racial/ethnic categories were White (54.0%), Black (19.9%), and Hispanic/Latino (16.7%). Participants who identified as Asian, Middle Eastern/North African, and White were the most likely to report annual incomes greater than $200,000, advanced degrees, and employer or union insurance, while participants who identified as Black, Hispanic, and Native Hawaiian/Pacific Islander were the most likely to report annual incomes less than $10,000, less than a high school education, and Medicaid insurance. We found that age was most predictive of hypertension, coronary artery disease, any cancer, skin cancer, diabetes, obesity, and chronic kidney disease. Insurance type was most predictive of lung disease. Notably, no two health conditions had the same order of importance for sociodemographic factors.

CONCLUSIONS

Age was the best predictor for the assessed chronic diseases, but the relative predictive value of income, education, health insurance, PCP status, race/ethnicity, and sexual orientation was highly variable across health conditions. Identifying the sociodemographic groups with the largest disparities in a specific disease can guide future interventions to promote health equity.

Performance of FRAX in older adults with frailty: the Framingham Heart Study

We compared the performance of FRAX according to frailty status in 3554 individuals from the Framingham Study. During 10-year follow-up, 6.9% and 3.0% of participants with and without frailty experienced MOF. Discrimination profiles were lower in participants with frailty compared to those without, but they improved when FRAX included BMD.

INTRODUCTION

Frailty increases fracture risk. FRAX was developed to predict fractures but never validated in individuals with frailty. We aimed to compare the predictive performance of FRAX (v4.3) in individuals with and without frailty.

METHODS

We conducted a cohort study using the Framingham Heart Study. Frailty was defined by the Fried phenotype. Major osteoporotic fractures (MOF) were ascertained from medical records during 10-year follow-up. To evaluate discrimination and calibration of FRAX, we calculated the area-under-the-receiver-operating characteristics curves (AUC) using logistic regression models and observed-to-predicted fracture probabilities. Analyses were stratified by frailty status.

RESULTS

Frailty was present in 550/3554 (15.5%) of participants. Participants with frailty were older (81.1 vs. 67.6 years), female (68.6% vs. 55.1%), and had greater mean FRAX scores (MOF: 15.9% vs. 10.1%) than participants without frailty. During follow-up, 38 participants with frailty (6.9%) and 91 without (3.0%) had MOFs. The AUC for FRAX (without BMD) was lower in participants with frailty (0.584; 95% CI 0.504-0.663) compared to those without (0.695; 95% CI 0.649-0.741); p value = 0.02. Among participants with frailty, the AUC improved when FRAX included BMD (AUC 0.658, p value < 0.01). FRAX overestimated MOF risk, with larger overestimations in individuals without frailty. Performance of FRAX for hip fracture was similar.

CONCLUSION

FRAX may have been less able to identify frail individuals at risk for fracture, as compared with individuals without frailty, unless information on BMD is available. This suggests that BMD captures features important for fracture prediction in frail persons. Future fracture prediction models should be developed among persons with frailty.

Maximizing utility of neuropsychological measures in sex-specific predictive models of incident Alzheimer's disease in the Framingham Heart Study

INTRODUCTION

Sex differences in neuropsychological (NP) test performance might have important implications for the diagnosis of Alzheimer's disease (AD). This study investigates sex differences in neuropsychological performance among individuals without dementia at baseline.

METHODS

Neuropsychological assessment data, both standard test scores and process coded responses, from Framingham Heart Study participants were analyzed for sex differences using regression model and Cox proportional hazards model. Optimal NP profiles were identified by machine learning methods for men and women.

RESULTS

Sex differences were observed in both summary scores and composite process scores of NP tests in terms of adjusted means and their associations with AD incidence. The optimal NP profiles for men and women have 10 and 8 measures, respectively, and achieve 0.76 mean area under the curve for AD prediction.

DISCUSSION

These results suggest that NP tests can be leveraged for developing more sensitive, sex-specific indices for the diagnosis of AD.

Digital Clock Drawing as an Alzheimer's Disease Susceptibility Biomarker: Associations with Genetic Risk Score and APOE in Older Adults

BACKGROUND

Alzheimer's disease (AD) is the leading cause of dementia in older adults, but most people are not diagnosed until significant neuronal loss has likely occurred along with a decline in cognition. Non-invasive and cost-effective digital biomarkers for AD have the potential to improve early detection.

OBJECTIVE

We examined the validity of DCTclockTM (a digitized clock drawing task) as an AD susceptibility biomarker.

DESIGN

We used two primary independent variables, Apolipoprotein E (APOE) ε4 allele carrier status and polygenic risk score (PRS). We examined APOE and PRS associations with DCTclockTM composite scores as dependent measures.

SETTING

We used existing data from the Framingham Heart Study (FHS), a community-based study with the largest dataset of digital clock drawing data to date.

PARTICIPANTS

The sample consisted of 2,398 older adults ages 60-94 with DCTclockTM data (mean age of 72.3, 55% female and 92% White).

MEASUREMENTS

PRS was calculated using 38 variants identified in a recent large genome-wide association study (GWAS) and meta-analysis of late-onset AD (LOAD).

RESULTS

Results showed that DCTclockTM performance decreased with advancing age, lower education, and the presence of one or more copies of APOE ε4. Lower DCTclockTM Total Score as well as lower composite scores for Information Processing Speed (both command and copy conditions) and Drawing Efficiency (command condition) were significantly associated with higher PRS levels and more copies of APOE ε4. APOE and PRS associations displayed similar effect sizes in both men and women.

CONCLUSIONS

Our results indicate that higher AD genetic risk is associated with poorer DCTclockTM performance in older adults without dementia. This is the first study to demonstrate significant differences in clock drawing performance on the basis of APOE status or PRS.

Thrombosis in patients with immune thrombocytopenia: incidence, risk, and clinical outcomes

Background

There is evidence that patients with immune thrombocytopenia (ITP) are at increased risk of thrombosis. However, the association of clinical- and treatment-related factors with thrombosis remains controversial.

Objectives

To evaluate the incidence and impact of risk factors for arterial and venous thromboembolism (VTE) in patients with ITP and characterize the clinical features and management of patients.

Methods

We performed a retrospective cohort study (January 1, 2011, to October 30, 2022) of adult patients diagnosed with ITP from an Australian tertiary hospital. The incidence rates of thrombosis were calculated in terms of person-years of follow-up. Multiadjusted Cox regression was used to estimate associations.

Results

A total of 220 patients with 1365 person-years of follow-up since ITP diagnosis revealed 26 (11.8%) patients with a total of 37 thrombosis events, 29 (78%) VTE and 8 (22%) arterial thromboembolism (ATE). The incidence rate of thrombosis was 2.71 (95% CI, 1.97-3.72) (0.66 [95% CI, 0.33-1.26] for arterial thromboembolism and 2.05 [95% CI, 1.42-2.95] for VTE) per 100 person-years. Mean age and median time to first thrombosis diagnosis was 56 and 2.13 years, respectively. Age, secondary ITP, lines of therapy, thrombosis risk factors, and thrombopoietin receptor agonist therapy were independently associated with thrombosis. Almost all patients (25 of 26, [96%]) had good ITP disease control prior to thrombosis diagnosis, and antithrombotic therapy was deliverable and well tolerated.

Conclusion

Diagnosis of thrombosis in patients with ITP, while infrequent, is of clinical significance. We identified from a heterogeneous real-world cohort that older patients with multiply-treated secondary ITP receiving thrombopoietin receptor agonists are at the highest risk.

Ethnic Disparities in the Burden of Cardiovascular Disease Among Immigrants in Canada

Canada has the highest level of immigration, with one in four Canadians being immigrants. And little is known about the ethnic differences and cardiovascular disease (CVD) risk in the Canadian immigrant population. The high level of immigration has resulted in significant ethnic diversity in Canada, with each presenting a CVD risk profile unique to their ethnicity and country of birth. A better understanding of the ethnic differences in the risk of CVD could help navigate effective health promotion and targeted interventions, which can mitigate the burden of morbidity and mortality associated with the disease.

APOL1 Risk Variants Associate With the Prevalence of Stroke in African American Current and Past Smokers

BACKGROUND

African American smokers have 2.5 times higher risk for stroke compared with nonsmokers (higher than other races). About 50% of the African American population carry 1 or 2 genetic variants (G1 and G2; rare in other races) of the apolipoprotein L1 gene (APOL1). Studies showed these variants may be associated with stroke. However, the role of the APOL1 risk variants in tobacco-related stroke is unknown.

METHODS AND RESULTS

In a cross-sectional study, we examined whether APOL1 risk variants modified the relationship between tobacco smoking and stroke prevalence in 513 African American adults recruited at University of California, San Francisco. Using DNA, plasma, and questionnaires we determined APOL1 variants, smoking status, and stroke prevalence. Using logistic regression models, we examined the association between smoking (ever versus never smokers) and stroke overall, and among carriers of APOL1 risk variants (1 or 2 risk alleles), and noncarriers, separately. Among participants, 41% were ever (current and past) smokers, 54% were carriers of the APOL1 risk variants, and 41 had a history of stroke. The association between smoking and stroke differed by APOL1 genotype (Pinteraction term=0.014). Among carriers, ever versus never smokers had odds ratio (OR) 2.46 (95% CI, 1.08-5.59) for stroke (P=0.034); OR 2.00 (95% CI, 0.81-4.96) among carriers of 1 risk allele, and OR 4.72 (95% CI, 0.62-36.02) for 2 risk alleles. Among noncarriers, smoking was not associated with a stroke.

CONCLUSIONS

Current and past smokers who carry APOL1 G1 and/or G2 risk variants may be more susceptible to stroke among the African American population.

Age and the Residual Risk of Cardiovascular Disease following Low Density Lipoprotein-Cholesterol Exposure

We believe that there is sufficient evidence from basic science, longitudinal cohort studies and randomised controlled trials which validates the low-density lipoprotein cholesterol (LDL-C) or lipid hypothesis. It is important that we can communicate details of the cardiovascular disease (CVD) risk reduction that the average patient could expect depending on the scale of LDL-C decrease following lipid lowering therapy. It is also essential that residual risk (ResR) of CVD be highlighted. To achieve this aim by using existing trial evidence, we developed mathematical models initially for relative risk reduction (RRR) and absolute risk (AR) reduction and then showed that despite optimising LDL-C levels, a considerable degree of ResR remains that is dependent on AR. Age is significantly associated with AR (odds ratio: 1.02, 95% confidence intervals: 1.01-1.04) as was previously demonstrated by analysing the Whickham study cohort using a logistic regression model (age remaining significant even when all the other significant risk factors such as sex, smoking, systolic blood pressure, diabetes and family history were included in the regression model). A discussion of a paper by Ference et al. provided detailed evidence of the relationship between age and AR, based on lifetime LDL-C exposure. Finally, we discussed non-traditional CVD risk factors that may contribute to ResR based on randomised controlled trials investigating drugs improving inflammation, thrombosis, metabolic and endothelial status.

Association of dyslipidemia with single nucleotide polymorphisms of the cholesteryl ester transfer protein gene and cardiovascular disease risk factors in a highly admixed population

BACKGROUND AND AIMS

Cardiovascular diseases (CVD) are major causes of mortality worldwide, leading to premature deaths, loss of quality of life, and extensive socioeconomic impacts. Alterations in normal plasma lipid concentrations comprise important risk factors associated with CVD due to mechanisms involved in the pathophysiology of atherosclerosis. Genetic markers such as single nucleotide polymorphisms (SNPs) are known to be associated with lipid metabolism, including variants in the cholesteryl ester transfer protein (CETP) gene. Thus, the study's objective was to assess the relationship among lipid profile, socioeconomic and demographic characteristics, health status, inflammatory biomarkers, and CETP genetic variants in individuals living in a highly admixed population.

METHODS

The study comprises an analysis of observational cross-sectional data representative at the population level from a highly admixed population, encompassing 901 individuals from three age groups (adolescents, adults, and older adults). Socioeconomic, demographic, health, and lifestyle characteristics were collected using semi-structured questionnaires. In addition, biochemical markers and lipid profiles were obtained from individuals' blood samples. After DNA extraction, genotyping, and quality control according to Affymetrix's guidelines, information on 15 SNPs in the CETP gene was available for 707 individuals. Lipid profile and CVD risk factors were evaluated by principal component analysis (PCA), and associations between lipid traits and those factors were assessed through multiple linear regression and logistic regression.

RESULTS

There were low linear correlations between lipid profile and other individuals' characteristics. Two principal components were responsible for 80.8 % of the total variance, and there were minor differences in lipid profiles among individuals in different age groups. Non-HDL-c, total cholesterol, and LDL-c had the highest loadings in the first PC, and triacylglycerols, VLDL-c and HDL-c were responsible for a major part of the loading in the second PC;, whilst HDL-c and LDL-c/HDL-c ratio were significant in the third PC. In addition, there were minor differences between groups of individuals with or without dyslipidemia regarding inflammatory biomarkers (IL-1β, IL- 6, IL-10, TNF-α, CRP, and MCP-1). Being overweight, insulin resistance, and lifestyle characteristics (calories from solid fat, added sugar, alcohol and sodium, leisure physical activity, and smoking) were strong predictors of lipid traits, especially HDL-c and dyslipidemia (p < 0.05). The CETP SNPs rs7499892 and rs12691052, rs291044, and rs80180245 were significantly associated with HDL-c (p < 0.05), and their inclusion in the multiple linear regression model increased its accuracy (adjusted R2 rose from 0.12 to 0.18).

CONCLUSION

This study identified correlations between lipid traits and other CVD risk factors. In addition, similar lipid and inflammatory profiles across age groups in the population suggested that adolescents might already present a significant risk for developing cardiovascular diseases in the population. The risk can be primarily attributed to decreased HDL-c concentrations, which appear to be influenced by genetic factors, as evidenced by associations between SNPs in the CETP gene and HDL-c concentrations, as well as potential gene-diet interactions. Our findings underscore the significant impact of genetic and lifestyle factors on lipid profile within admixed populations in developing countries.

Association Between Slow-Wave Sleep Loss and Incident Dementia

Importance

Slow-wave sleep (SWS) supports the aging brain in many ways, including facilitating the glymphatic clearance of proteins that aggregate in Alzheimer disease. However, the role of SWS in the development of dementia remains equivocal.

Objective

To determine whether SWS loss with aging is associated with the risk of incident dementia and examine whether Alzheimer disease genetic risk or hippocampal volumes suggestive of early neurodegeneration were associated with SWS loss.

Design, Setting, and Participants

This prospective cohort study included participants in the Framingham Heart Study who completed 2 overnight polysomnography (PSG) studies in the time periods 1995 to 1998 and 2001 to 2003. Additional criteria for individuals in this study sample were an age of 60 years or older and no dementia at the time of the second overnight PSG. Data analysis was performed from January 2020 to August 2023.

Exposure

Changes in SWS percentage measured across repeated overnight sleep studies over a mean of 5.2 years apart (range, 4.8-7.1 years).

Main Outcome

Risk of incident all-cause dementia adjudicated over 17 years of follow-up from the second PSG.

Results

From the 868 Framingham Heart Study participants who returned for a second PSG, this cohort included 346 participants with a mean age of 69 years (range, 60-87 years); 179 (52%) were female. Aging was associated with SWS loss across repeated overnight sleep studies (mean [SD] change, -0.6 [1.5%] per year; P < .001). Over the next 17 years of follow-up, there were 52 cases of incident dementia. In Cox regression models adjusted for age, sex, cohort, positivity for at least 1 APOE ε4 allele, smoking status, sleeping medication use, antidepressant use, and anxiolytic use, each percentage decrease in SWS per year was associated with a 27% increase in the risk of dementia (hazard ratio, 1.27; 95% CI, 1.06-1.54; P = .01). SWS loss with aging was accelerated in the presence of Alzheimer disease genetic risk (ie, APOE ε4 allele) but not hippocampal volumes measured proximal to the first PSG.

Conclusions and Relevance

This cohort study found that slow-wave sleep percentage declined with aging and Alzheimer disease genetic risk, with greater reductions associated with the risk of incident dementia. These findings suggest that SWS loss may be a modifiable dementia risk factor.

Trends among platelet function, arterial calcium, and vascular function measures

Arterial tonometry and vascular calcification measures are useful in cardiovascular disease (CVD) risk assessment. Prior studies found associations between tonometry measures, arterial calcium, and CVD risk. Activated platelets release angiopoietin-1 and other factors, which may connect vascular structure and platelet function. We analyzed arterial tonometry, platelet function, aortic, thoracic and coronary calcium, and thoracic and abdominal aorta diameters measured in the Framingham Heart Study Gen3/NOS/OMNI-2 cohorts (n = 3,429, 53.7% women, mean age 54.4 years ±9.3). Platelet reactivity in whole blood or platelet-rich plasma was assessed using 5 assays and 7 agonists. We analyzed linear mixed effects models with platelet reactivity phenotypes as outcomes, adjusting for CVD risk factors and family structure. Higher arterial calcium trended with higher platelet reactivity, whereas larger aortic diameters trended with lower platelet reactivity. Characteristic impedance (Zc) and central pulse pressure positively trended with various platelet traits, while pulse wave velocity and Zc negatively trended with collagen, ADP, and epinephrine traits. All results did not pass a stringent multiple test correction threshold (p < 2.22e-04). The diameter trends were consistent with lower shear environments invoking less platelet reactivity. The vessel calcium trends were consistent with subclinical atherosclerosis and platelet activation being inter-related.

Association Between Acoustic Features and Brain Volumes: the Framingham Heart Study

Introduction

Although brain magnetic resonance imaging (MRI) is a valuable tool for investigating structural changes in the brain associated with neurodegeneration, the development of non-invasive and cost-effective alternative methods for detecting early cognitive impairment is crucial. The human voice has been increasingly used as an indicator for effectively detecting cognitive disorders, but it remains unclear whether acoustic features are associated with structural neuroimaging.

Methods

This study aims to investigate the association between acoustic features and brain volume and compare the predictive power of each for mild cognitive impairment (MCI) in a large community-based population. The study included participants from the Framingham Heart Study (FHS) who had at least one voice recording and an MRI scan. Sixty-five acoustic features were extracted with the OpenSMILE software (v2.1.3) from each voice recording. Nine MRI measures were derived according to the FHS MRI protocol. We examined the associations between acoustic features and MRI measures using linear regression models adjusted for age, sex, and education. Acoustic composite scores were generated by combining acoustic features significantly associated with MRI measures. The MCI prediction ability of acoustic composite scores and MRI measures were compared by building random forest models and calculating the mean area under the receiver operating characteristic curve (AUC) of 10-fold cross-validation.

Results

The study included 4,293 participants (age 57 ± 13 years, 53.9% women). During 9.3±3.7 years follow-up, 106 participants were diagnosed with MCI. Seven MRI measures were significantly associated with more than 20 acoustic features after adjusting for multiple testing. The acoustic composite scores can improve the AUC for MCI prediction to 0.794, compared to 0.759 achieved by MRI measures.

Discussion

We found multiple acoustic features were associated with MRI measures, suggesting the potential for using acoustic features as easily accessible digital biomarkers for the early diagnosis of MCI.

Validation of an Integrated Genetic-Epigenetic Test for the Assessment of Coronary Heart Disease

BACKGROUND

Coronary heart disease (CHD) is the leading cause of death in the world. Unfortunately, many of the key diagnostic tools for CHD are insensitive, invasive, and costly; require significant specialized infrastructure investments; and do not provide information to guide postdiagnosis therapy. In prior work using data from the Framingham Heart Study, we provided in silico evidence that integrated genetic-epigenetic tools may provide a new avenue for assessing CHD.

METHODS AND RESULTS

In this communication, we use an improved machine learning approach and data from 2 additional cohorts, totaling 449 cases and 2067 controls, to develop a better model for ascertaining symptomatic CHD. Using the DNA from the 2 new cohorts, we translate and validate the in silico findings into an artificial intelligence-guided, clinically implementable method that uses input from 6 methylation-sensitive digital polymerase chain reaction and 10 genotyping assays. Using this method, the overall average area under the curve, sensitivity, and specificity in the 3 test cohorts is 82%, 79%, and 76%, respectively. Analysis of targeted cytosine-phospho-guanine loci shows that they map to key risk pathways involved in atherosclerosis that suggest specific therapeutic approaches.

CONCLUSIONS

We conclude that this scalable integrated genetic-epigenetic approach is useful for the diagnosis of symptomatic CHD, performs favorably as compared with many existing methods, and may provide personalized insight to CHD therapy. Furthermore, given the dynamic nature of DNA methylation and the ease of methylation-sensitive digital polymerase chain reaction methodologies, these findings may pave a pathway for precision epigenetic approaches for monitoring CHD treatment response.

Circulating metabolites may illustrate relationship of alcohol consumption with cardiovascular disease

BACKGROUND

Metabolite signatures of long-term alcohol consumption are lacking. To better understand the molecular basis linking alcohol drinking and cardiovascular disease (CVD), we investigated circulating metabolites associated with long-term alcohol consumption and examined whether these metabolites were associated with incident CVD.

METHODS

Cumulative average alcohol consumption (g/day) was derived from the total consumption of beer, wine, and liquor on average of 19 years in 2428 Framingham Heart Study Offspring participants (mean age 56 years, 52% women). We used linear mixed models to investigate the associations of alcohol consumption with 211 log-transformed plasma metabolites, adjusting for age, sex, batch, smoking, diet, physical activity, BMI, and familial relationship. Cox models were used to test the association of alcohol-related metabolite scores with fatal and nonfatal incident CVD (myocardial infarction, coronary heart disease, stroke, and heart failure).

RESULTS

We identified 60 metabolites associated with cumulative average alcohol consumption (p < 0.05/211 ≈ 0.00024). For example, 1 g/day increase of alcohol consumption was associated with higher levels of cholesteryl esters (e.g., CE 16:1, beta = 0.023 ± 0.002, p = 6.3e - 45) and phosphatidylcholine (e.g., PC 32:1, beta = 0.021 ± 0.002, p = 3.1e - 38). Survival analysis identified that 10 alcohol-associated metabolites were also associated with a differential CVD risk after adjusting for age, sex, and batch. Further, we built two alcohol consumption weighted metabolite scores using these 10 metabolites and showed that, with adjustment age, sex, batch, and common CVD risk factors, the two scores had comparable but opposite associations with incident CVD, hazard ratio 1.11 (95% CI = [1.02, 1.21], p = 0.02) vs 0.88 (95% CI = [0.78, 0.98], p = 0.02).

CONCLUSIONS

We identified 60 long-term alcohol consumption-associated metabolites. The association analysis with incident CVD suggests a complex metabolic basis between alcohol consumption and CVD.

An individualized Bayesian method for estimating genomic variants of hypertension

BACKGROUND

Genomic variants of the disease are often discovered nowadays through population-based genome-wide association studies (GWAS). Identifying genomic variations potentially underlying a phenotype, such as hypertension, in an individual is important for designing personalized treatment; however, population-level models, such as GWAS, may not capture all the important, individualized factors well. In addition, GWAS typically requires a large sample size to detect the association of low-frequency genomic variants with sufficient power. Here, we report an individualized Bayesian inference (IBI) algorithm for estimating the genomic variants that influence complex traits, such as hypertension, at the level of an individual (e.g., a patient). By modeling at the level of the individual, IBI seeks to find genomic variants observed in the individual's genome that provide a strong explanation of the phenotype observed in this individual.

RESULTS

We applied the IBI algorithm to the data from the Framingham Heart Study to explore the genomic influences of hypertension. Among the top-ranking variants identified by IBI and GWAS, there is a significant number of shared variants (intersection); the unique variants identified only by IBI tend to have relatively lower minor allele frequency than those identified by GWAS. In addition, IBI discovered more individualized and diverse variants that explain hypertension patients better than GWAS. Furthermore, IBI found several well-known low-frequency variants as well as genes related to blood pressure that GWAS missed in the same cohort. Finally, IBI identified top-ranked variants that predicted hypertension better than GWAS, according to the area under the ROC curve.

CONCLUSIONS

The results support IBI as a promising approach for complementing GWAS, especially in detecting low-frequency genomic variants as well as learning personalized genomic variants of clinical traits and disease, such as the complex trait of hypertension, to help advance precision medicine.

Cohort profile: the longitudinal National Growth and Health Study (NGHS) of black and white girls from Northern California tracking how behavioural and psychosocial risk factors predict cardiovascular risk and biological ageing in midlife and in offspring

PURPOSE

The National Heart, Lung and Blood Institute Growth and Health Study (NGHS) prospectively collected anthropometric, biospecimens, clinical, health behaviour and psychosocial measures associated with cardiovascular disease from childhood to young adulthood. The aim of the current study was to assess the impact of stress, dysregulated eating and social genomic biomarkers on cardiometabolic risk factors among the original participants now in midlife and their children.

PARTICIPANTS

Beginning in 1987-1988, NGHS recruited black and white girls (age 9-10 years) from socioeconomically diverse backgrounds from from three sites: Cincinnati, Ohio; Washington, DC; and Western Contra Costa County, California (N=2379) and followed them for 10 years. The study maintained an 89% retention rate. The current study is 30 years after the start of the original study and focused on the participants of California (n=887) and their children aged 2-17 years. We re-enrolled 624 of 852 eligible participants (73%): 49.2% black and 50.8% white. The mean age was 39.5 years. Among the 645 eligible biological children, 553 were enrolled; 49% black and 51% white, with 51.5% girls and 48.5% boys. The mean age was 9.3 years.

FINDINGS TO DATE

Longitudinal analysis of adolescent drive for thinness predicted higher scores for drive for thinness during midlife, which was indirectly associated with greater adult body mass index through adult drive for thinness. Latent trajectory modelling of adolescent growth over 10 years found that women with persistently high weight trajectory had twice the odds of having children who met the definition for obesity compared with the persistently normal group, adjusting for adult weight.

FUTURE PLANS

New studies on neighbourhood socioeconomic status, food insecurity and additional biomarkers of chronic stress, microbiome and accelerated ageing (ie, telomere length and epigenetic clock) are underway. We are developing a 10-year follow-up to understand changes in ageing biomarkers of the participants and their children.

TRIAL REGISTRATION NUMBER

NCT00005132.

Association Between Whole Blood-Derived Mitochondrial DNA Copy Number, Low-Density Lipoprotein Cholesterol, and Cardiovascular Disease Risk

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross-sectional and prospective association analyses of blood-derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole-genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). P<0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1-SD unit lower level of mtDNA CN was associated with 1.08 (95% CI, 1.04-1.12; P<0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (β=0.091; P=0.11) or in the reverse direction (β=-0.012; P=0.076). Additional bidirectional Mendelian randomization analyses revealed that low-density lipoprotein cholesterol had a causal effect on mtDNA CN (β=-0.084; P<0.001), but the reverse direction was not significant (P=0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low-density lipoprotein cholesterol level (P=0.52), whereas there was a strong direct causal effect of higher low-density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (β=-0.092; P<0.001). Conclusions Our findings indicate that high low-density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.

Cardiovascular disease risk models and dementia or cognitive decline: a systematic review

Background

Health cognitive promotion and protection is a critical topic. With the world's aging population and rising life expectancy, there will be many people living with highly age-related dementia illnesses. Cardiovascular disease (CVD) and dementia share the same risk factors, such as unhealthy lifestyles and metabolic factors. These recognized risks associated with CVD and dementia frequently co-occur. CVD risk models may have a close association with dementia and cognitive decline. So, this systematic review aimed to determine whether CVD risk models were connected with dementia or cognitive decline and compare the predictive ability of various models.

Methods

PubMed, Web of Science, PsychINFO, Embase, Cochrane Library, CNKI, Sinomed, and WanFang were searched from 1 January 2014 until 16 February 2023. Only CVD risk models were included. We used the Newcastle-Ottawa scale (NOS) for the quality assessment of included cohort studies and the Agency for Healthcare Research and Quality (AHRQ) for cross-sectional studies. The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement's guidelines were followed in this systematic study.

Results

In all, 9,718 references were screened, of which 22 articles were included. A total of 15 CVD risk models were summarized. Except for the Cardiovascular Health in Ambulatory Care Research Team (CANHEART) health index, the other 14 CVD risk models were associated with dementia and cognitive decline. In comparison, different CVD risk models and domain-specific cognitive function correlation variation depended on cohort characteristics, risk models, cognitive function tests, and study designs. Moreover, it needed to be clarified when comparing the predicting performance of different CVD risk models.

Conclusion

It is significant for public health to improve disease risk prediction and prevention and mitigate the potential adverse effects of the heart on the brain. More cohort studies are warranted to prove the correlation between CVD risk models and cognitive function. Moreover, further studies are encouraged to compare the efficacy of CVD risk models in predicting cognitive disorders.

Long-term blood pressure patterns in midlife and dementia in later life: Findings from the Framingham Heart Study

INTRODUCTION

Long-term blood pressure (BP) measures, such as visit-to-visit BP variability (BPV) and cumulative BP, are strong indicators of cardiovascular risks. This study modeled up to 20 years of BP patterns representative of midlife by using BPV and cumulative BP, then examined their associations with development of dementia in later life.

METHODS

For 3201 individuals from the Framingham Heart Study, multivariate logistic regression analyses were performed to examine the association between long-term BP patterns during midlife and the development of dementia (ages ≥ 65).

RESULTS

After adjusting for covariates, every quartile increase in midlife cumulative BP was associated with a sequential increase in the risk of developing dementia (e.g., highest quartile of cumulative systolic blood pressure had approximately 2.5-fold increased risk of all-cause dementia). BPV was not significantly associated with dementia.

DISCUSSION

Findings suggest that cumulative BP over the course of midlife predicts risk of dementia in later life. HIGHLIGHTS Long-term blood pressure (BP) patterns are strong indicators of vascular risks. Cumulative BP and BP variability (BPV) were used to reflect BP patterns across midlife. High cumulative BP in midlife is associated with increased dementia risk. Visit-to-visit BPV was not associated with the onset of dementia.

Study protocol for development and validation of a single tool to assess risks of stroke, diabetes mellitus, myocardial infarction and dementia: DemNCD-Risk

INTRODUCTION

Current efforts to reduce dementia focus on prevention and risk reduction by targeting modifiable risk factors. As dementia and cardiometabolic non-communicable diseases (NCDs) share risk factors, a single risk-estimating tool for dementia and multiple NCDs could be cost-effective and facilitate concurrent assessments as compared with a conventional single approach. The aim of this study is to develop and validate a new risk tool that estimates an individual's risk of developing dementia and other NCDs including diabetes mellitus, stroke and myocardial infarction. Once validated, it could be used by the public and general practitioners.

METHODS AND ANALYSIS

Ten high-quality cohort studies from multiple countries were identified, which met eligibility criteria, including large representative samples, long-term follow-up, data on clinical diagnoses of dementia and NCDs, recognised modifiable risk factors for the four NCDs and mortality data. Pooled harmonised data from the cohorts will be used, with 65% randomly allocated for development of the predictive model and 35% for testing. Predictors include sociodemographic characteristics, general health risk factors and lifestyle/behavioural risk factors. A subdistribution hazard model will assess the risk factors' contribution to the outcome, adjusting for competing mortality risks. Point-based scoring algorithms will be built using predictor weights, internally validated and the discriminative ability and calibration of the model will be assessed for the outcomes. Sensitivity analyses will include recalculating risk scores using logistic regression.

ETHICS AND DISSEMINATION

Ethics approval is provided by the University of New South Wales Human Research Ethics Committee (UNSW HREC; protocol numbers HC200515, HC3413). All data are deidentified and securely stored on servers at Neuroscience Research Australia. Study findings will be presented at conferences and published in peer-reviewed journals. The tool will be accessible as a public health resource. Knowledge translation and implementation work will explore strategies to apply the tool in clinical practice.

Survey response over 15 years of follow-up in the Millennium Cohort Study

BACKGROUND

Patterns of survey response and the characteristics associated with response over time in longitudinal studies are important to discern for the development of tailored retention efforts aimed at minimizing response bias. The Millennium Cohort Study, the largest and longest running cohort study of military personnel and veterans, is designed to examine the long-term health effects of military service and experiences and thus relies on continued participant survey responses over time. Here, we describe the response rates for follow-up survey data collected over 15 years and identify characteristics associated with follow-up survey response and mode of response (paper vs. web).

METHOD

Patterns of follow-up survey response and response mode (web, paper, none) were examined among eligible participants (n=198,833), who were initially recruited in four panels from 2001 to 2013 in the Millennium Cohort Study, for a follow-up period of 3-15 years (2004-2016). Military and sociodemographic factors (i.e., enrollment panel, sex, birth year, race and ethnicity, educational attainment, marital status, service component, service branch, pay grade, military occupation, length of service, and time deployed), life experiences and health-related factors (i.e., military deployment/combat experience, life stressors, mental health, physical health, and unhealthy behaviors) were used to examine follow-up response and survey mode over time in multivariable generalized estimating equation models.

RESULTS

Overall, an average response rate of 60% was observed across all follow-up waves. Factors associated with follow-up survey response over time included increased educational attainment, married status, female sex, older age, military deployment (regardless of combat experience), and higher number of life stressors, mental health issues, and physical health diagnoses.

CONCLUSION

Despite the challenges associated with collecting multiple waves of follow-up survey data from members of the U.S. military during and after service, the Millennium Cohort Study has maintained a relatively robust response rate over time. The incorporation of tailored messages and outreach to those groups least likely to respond over time may improve retention and thereby increase the representativeness and generalizability of collected survey data.

A blood biomarker of accelerated aging in the body associates with worse structural integrity in the brain: replication across three cohorts

Biological aging is the correlated decline of multi-organ system integrity central to the etiology of many age-related diseases. A novel epigenetic measure of biological aging, DunedinPACE, is associated with cognitive dysfunction, incident dementia, and mortality. Here, we tested for associations between DunedinPACE and structural MRI phenotypes in three datasets spanning midlife to advanced age: the Dunedin Study (age=45 years), the Framingham Heart Study Offspring Cohort (mean age=63 years), and the Alzheimer's Disease Neuroimaging Initiative (mean age=75 years). We also tested four additional epigenetic measures of aging: the Horvath clock, the Hannum clock, PhenoAge, and GrimAge. Across all datasets (total N observations=3,380; total N individuals=2,322), faster DunedinPACE was associated with lower total brain volume, lower hippocampal volume, and thinner cortex. In two datasets, faster DunedinPACE was associated with greater burden of white matter hyperintensities. Across all measures, DunedinPACE and GrimAge had the strongest and most consistent associations with brain phenotypes. Our findings suggest that single timepoint measures of multi-organ decline such as DunedinPACE could be useful for gauging nervous system health.

Association between 5-year change in cardiovascular risk and the incidence of atherosclerotic cardiovascular diseases: a multi-cohort study

BACKGROUND

The influence of the historical cardiovascular risk status on future risk of atherosclerotic cardiovascular disease (ASCVD) is poorly understood. We aimed to investigate the association between 5-year changes in cardiovascular risk and ASCVD incidence.

METHODS

We analyzed pooled data from seven community-based prospective cohort studies with up to 20 years of follow-up data. The study populations included White or Black participants aged 40-75 years without prevalent ASCVD. Cardiovascular risk was assessed using the pooled cohort equation and was categorized into non-high (< 20%) or high risk (≥ 20%). Changes in cardiovascular disease (CVD) risk over a 5-year interval were recorded. The main outcome was incident ASCVD.

RESULTS

Among 11,026 participants (mean [SD] age, 60.0 [8.1] years), 4272 (38.7%) were female and 3127 (28.4%) were Black. During a median follow-up period of 9.9 years, 2560 (23.2%) ASCVD events occurred. In comparison with individuals showing a consistently high CVD risk, participants whose CVD risk changed from non-high to high (hazard ratio [HR], 0.67; 95% confidence interval [CI] 0.59-0.77) or high to non-high (HR, 0.57; 95% CI 0.41-0.80) and those with a consistently non-high risk (HR, 0.33; 95% CI 0.29-0.37) had a lower risk of incident ASCVD. In comparison with individuals showing a consistently non-high CVD risk, participants whose CVD risk changed from high to non-high (HR, 1.74; 95% CI 1.26-2.41) or from non-high to high risk (HR, 2.04; 95% CI 1.84-2.27) and those with a consistently high risk (HR 3.03; 95% CI 2.69-3.42) also showed an increased risk of incident ASCVD.

CONCLUSIONS

Individuals with the same current CVD risk status but different historical CVD risks exhibited varying risks of future ASCVD incidents. Dynamic risk evaluation may enable more accurate cardiovascular risk stratification, and decision-making regarding preventive interventions should take the historical risk status into account.

The MARS PETCARE BIOBANK protocol: establishing a longitudinal study of health and disease in dogs and cats

BACKGROUND

The veterinary care of cats and dogs is increasingly embracing innovations first applied to human health, including an increased emphasis on preventative care and precision medicine. Large scale human population biobanks have advanced research in these areas; however, few have been established in veterinary medicine. The MARS PETCARE BIOBANK™ (MPB) is a prospective study that aims to build a longitudinal bank of biological samples, with paired medical and lifestyle data, from 20,000 initially healthy cats and dogs (10,000 / species), recruited through veterinary hospitals over a ten-year period. Here, we describe the MPB protocol and discuss its potential as a platform to increase understanding of why and how diseases develop and how to advance personalised veterinary healthcare.

METHODS

At regular intervals, extensive diet, health and lifestyle information, electronic medical records, clinicopathology and activity data are collected, genotypes, whole genome sequences and faecal metagenomes analysed, and blood, plasma, serum, and faecal samples stored for future research.

DISCUSSION

Proposed areas for research include the early detection and progression of age-related disease, risk factors for common conditions, the influence of the microbiome on health and disease and, through genome wide association studies, the identification of candidate loci for disease associated genetic variants. Genomic data will be open access and research proposals for access to data and samples will be considered. Over the coming years, the MPB will provide the longitudinal data and systematically collected biological samples required to generate important insights into companion animal health, identifying biomarkers of disease, supporting earlier identification of risk, and enabling individually tailored interventions to manage disease.

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.

Expression quantitative trait methylation analysis elucidates gene regulatory effects of DNA methylation: the Framingham Heart Study

Expression quantitative trait methylation (eQTM) analysis identifies DNA CpG sites at which methylation is associated with gene expression. The present study describes an eQTM resource of CpG-transcript pairs derived from whole blood DNA methylation and RNA sequencing gene expression data in 2115 Framingham Heart Study participants. We identified 70,047 significant cis CpG-transcript pairs at p < 1E-7 where the top most significant eGenes (i.e., gene transcripts associated with a CpG) were enriched in biological pathways related to cell signaling, and for 1208 clinical traits (enrichment false discovery rate [FDR] ≤ 0.05). We also identified 246,667 significant trans CpG-transcript pairs at p < 1E-14 where the top most significant eGenes were enriched in biological pathways related to activation of the immune response, and for 1191 clinical traits (enrichment FDR ≤ 0.05). Independent and external replication of the top 1000 significant cis and trans CpG-transcript pairs was completed in the Women's Health Initiative and Jackson Heart Study cohorts. Using significant cis CpG-transcript pairs, we identified significant mediation of the association between CpG sites and cardiometabolic traits through gene expression and identified shared genetic regulation between CpGs and transcripts associated with cardiometabolic traits. In conclusion, we developed a robust and powerful resource of whole blood eQTM CpG-transcript pairs that can help inform future functional studies that seek to understand the molecular basis of disease.

Predictors of Response to Hydroxyurea and Switch to Ruxolitinib in HU-Resistant Polycythaemia VERA Patients: A Real-World PV-NET Study

In polycythemia vera (PV), the prognostic relevance of an ELN-defined complete response (CR) to hydroxyurea (HU), the predictors of response, and patients' triggers for switching to ruxolitinib are uncertain. In a real-world analysis, we evaluated the predictors of response, their impact on the clinical outcomes of CR to HU, and the correlations between partial or no response (PR/NR) and a patient switching to ruxolitinib. Among 563 PV patients receiving HU for ≥12 months, 166 (29.5%) achieved CR, 264 achieved PR, and 133 achieved NR. In a multivariate analysis, the absence of splenomegaly (p = 0.03), pruritus (p = 0.002), and a median HU dose of ≥1 g/day (p < 0.001) remained associated with CR. Adverse events were more frequent with a median HU dose of ≥1 g/day. Overall, 283 PR/NR patients (71.3%) continued HU, and 114 switched to ruxolitinib. In the 449 patients receiving only HU, rates of thrombosis, hemorrhages, progression, and overall survival were comparable among the CR, PR, and NR groups. Many PV patients received underdosed HU, leading to lower CR and toxicity rates. In addition, many patients continued HU despite a PR/NR; however, splenomegaly and other symptoms were the main drivers of an early switch. Better HU management, standardization of the criteria for and timing of responses to HU, and adequate intervention in poor responders should be advised.

Accelerometer-Measured Physical Activity Data Sets (Global Physical Activity Data Set Catalogue) That Include Markers of Cardiometabolic Health: Systematic Scoping Review

BACKGROUND

Cardiovascular disease accounts for 17.9 million deaths globally each year. Many research study data sets have been collected to answer questions regarding the relationship between cardiometabolic health and accelerometer-measured physical activity. This scoping review aimed to map the available data sets that have collected accelerometer-measured physical activity and cardiometabolic health markers. These data were then used to inform the development of a publicly available resource, the Global Physical Activity Data set (GPAD) catalogue.

OBJECTIVE

This review aimed to systematically identify data sets that have measured physical activity using accelerometers and cardiometabolic health markers using either an observational or interventional study design.

METHODS

Databases, trial registries, and gray literature (inception until February 2021; updated search from February 2021 to September 2022) were systematically searched to identify studies that analyzed data sets of physical activity and cardiometabolic health outcomes. To be eligible for inclusion, data sets must have measured physical activity using an accelerometric device in adults aged ≥18 years; a sample size >400 participants (unless recruited participants in a low- and middle-income country where a sample size threshold was reduced to 100); used an observational, longitudinal, or trial-based study design; and collected at least 1 cardiometabolic health marker (unless only body mass was measured). Two reviewers screened the search results to identify eligible studies, and from these, the unique names of each data set were recorded, and characteristics about each data set were extracted from several sources.

RESULTS

A total of 17,391 study reports were identified, and after screening, 319 were eligible, with 122 unique data sets in these study reports meeting the review inclusion criteria. Data sets were found in 49 countries across 5 continents, with the most developed in Europe (n=53) and the least in Africa and Oceania (n=4 and n=3, respectively). The most common accelerometric brand and device wear location was Actigraph and the waist, respectively. Height and body mass were the most frequently measured cardiometabolic health markers in the data sets (119/122, 97.5% data sets), followed by blood pressure (82/122, 67.2% data sets). The number of participants in the included data sets ranged from 103,712 to 120. Once the review processes had been completed, the GPAD catalogue was developed to house all the identified data sets.

CONCLUSIONS

This review identified and mapped the contents of data sets from around the world that have collected potentially harmonizable accelerometer-measured physical activity and cardiometabolic health markers. The GPAD catalogue is a web-based open-source resource developed from the results of this review, which aims to facilitate the harmonization of data sets to produce evidence that will reduce the burden of disease from physical inactivity.

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.