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Background The association of circulating trimethylamine-N-oxide (TMAO) with stroke has received limited attention. To address this gap, we examined the associations of serial measures of plasma TMAO with incident ischemic stroke. Methods and Results We used a prospective cohort design with data pooled from 2 cohorts. The settings were the CHS (Cardiovascular Health Study), a cohort of older adults, and the MESA (Multi-Ethnic Study of Atherosclerosis), both in the United States. We measured plasma concentrations of TMAO at baseline and again during the follow-up using high-performance liquid chromatography and mass spectrometry. We assessed the association of plasma TMAO with incident ischemic stroke using proportional hazards regression adjusted for risk factors. The combined cohorts included 11 785 participants without a history of stroke, on average 73 (CHS) and 62 (MESA) years old at baseline, including 60% (CHS) and 53% (MESA) women. We identified 1031 total incident ischemic strokes during a median 15-year follow-up in the combined cohorts. In multivariable analyses, TMAO was significantly associated with incident ischemic stroke risk (hazard ratios comparing a doubling of TMAO: 1.11 [1.03-1.18], P=0.004). The association was linear over the range of TMAO concentrations and appeared restricted to those without diagnosed coronary heart disease. An association with hemorrhagic stroke was not found. Conclusions Plasma TMAO levels are associated with incident ischemic stroke in a diverse population. Registration URL: https://www.clinicaltrials.gov. Unique identifier: NCT00005133.

American Indian (AI) communities experience persistent diabetes-related disparities, yet few nutrition interventions are designed for AI with type 2 diabetes or address socio-contextual barriers to healthy eating. We describe our process of adapting the evidence-based Cooking Matters® program for use by AI adults with type 2 diabetes in a rural and resource-limited setting in the North-Central United States. We conducted three focus groups with AI adults with diabetes to (i) identify Cooking Matters® adaptations and (ii) gather feedback on appropriateness of the adapted intervention using Barrera and Castro's cultural adaptation framework. Transcripts were coded using an inductive, constant comparison approach. Queries of codes were reviewed to identify themes. Contextual considerations included limited access to grocery stores and transportation barriers, reliance on government food assistance and the intergenerational burden of diabetes. Adaptations to content and delivery included incorporating traditional and locally available foods; appealing to children or others in multigenerational households and prioritizing visual over written content. Our use of Barrera and Castro's framework adds rigor and structure to the cultural adaptation process and increases the likelihood of future intervention success. Other researchers may benefit from using this framework to guide the adaptation of evidence-based interventions in AI communities.

The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults comprising 14 established US prospective cohort studies. Starting as early as 1971, investigators in the C4R cohort studies have collected data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R links this pre-coronavirus disease 2019 (COVID-19) phenotyping to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and postacute COVID-related illness. C4R is largely population-based, has an age range of 18-108 years, and reflects the racial, ethnic, socioeconomic, and geographic diversity of the United States. C4R ascertains SARS-CoV-2 infection and COVID-19 illness using standardized questionnaires, ascertainment of COVID-related hospitalizations and deaths, and a SARS-CoV-2 serosurvey conducted via dried blood spots. Master protocols leverage existing robust retention rates for telephone and in-person examinations and high-quality event surveillance. Extensive prepandemic data minimize referral, survival, and recall bias. Data are harmonized with research-quality phenotyping unmatched by clinical and survey-based studies; these data will be pooled and shared widely to expedite collaboration and scientific findings. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and outcomes, including postacute sequelae, and assessment of the social and behavioral impact of the pandemic on long-term health trajectories.

To evaluate the association of nonesterified fatty acids (NEFA) with dysglycemia in older adults, NEFA levels were measured among participants in the Cardiovascular Health Study (United States; enrolled 1989-1993). Associations with insulin sensitivity and pancreatic β-cell function, and with incident type 2 diabetes mellitus (DM), were examined. The sample comprised 2,144 participants (aged 77.9 (standard deviation, 4.5) years). Participant data from the Cardiovascular Health Study visit in 1996-1997 was used with prospective follow-up through 2010. Fasting and postload NEFA showed significant associations with lower insulin sensitivity and pancreatic β-cell function, individually and on concurrent adjustment. Over median follow-up of 9.7 years, 236 cases of DM occurred. Postload NEFA were associated with risk of DM (per standard deviation, hazard ratio = 1.18, 95% confidence interval: 1.08, 1.29), but fasting NEFA were not (hazard ratio = 1.12, 95% confidence interval: 0.97, 1.29). The association for postload NEFA persisted after adjustment for putative intermediates, and after adjustment for fasting NEFA. Sex and body mass index modified these associations, which were stronger for fasting NEFA with DM in men but were accentuated for postload NEFA in women and among leaner individuals. Fasting and postload NEFA were related to lower insulin sensitivity and pancreatic β-cell function, but only postload NEFA were associated with increased DM. Additional study into NEFA metabolism could uncover novel potential targets for diabetes prevention in elders.

ObjectiveTrans fatty acids (TFAs) have harmful biologic effects that could increase the risk of type 2 diabetes (T2D), but evidence remains uncertain. We aimed to investigate the prospective associations of TFA biomarkers and T2D by conducting an individual participant-level pooled analysis.Research design and methodsWe included data from an international consortium of 12 prospective cohorts and nested case-control studies from six nations. TFA biomarkers were measured in blood collected between 1990 and 2008 from 25,126 participants aged ≥18 years without prevalent diabetes. Each cohort conducted de novo harmonized analyses using a prespecified protocol, and findings were pooled using inverse-variance weighted meta-analysis. Heterogeneity was explored by prespecified between-study and within-study characteristics.ResultsDuring a mean follow-up of 13.5 years, 2,843 cases of incident T2D were identified. In multivariable-adjusted pooled analyses, no significant associations with T2D were identified for trans/trans-18:2, relative risk (RR) 1.09 (95% CI 0.94-1.25); cis/trans-18:2, 0.89 (0.73-1.07); and trans/cis-18:2, 0.87 (0.73-1.03). Trans-16:1n-9, total trans-18:1, and total trans-18:2 were inversely associated with T2D (RR 0.81 [95% CI 0.67-0.99], 0.86 [0.75-0.99], and 0.84 [0.74-0.96], respectively). Findings were not significantly different according to prespecified sources of potential heterogeneity (each P ≥ 0.1).ConclusionsCirculating individual trans-18:2 TFA biomarkers were not associated with risk of T2D, while trans-16:1n-9, total trans-18:1, and total trans-18:2 were inversely associated. Findings may reflect the influence of mixed TFA sources (industrial vs. natural ruminant), a general decline in TFA exposure due to policy changes during this period, or the relatively limited range of TFA levels.

ObjectiveComprehensive assessment of alterations in lipid species preceding type 2 diabetes (T2D) is largely unknown. We aimed to identify plasma molecular lipids associated with risk of T2D in American Indians.Research design and methodsUsing untargeted liquid chromatography-mass spectrometry, we repeatedly measured 3,907 fasting plasma samples from 1,958 participants who attended two examinations (∼5.5 years apart) and were followed up to 16 years in the Strong Heart Family Study. Mixed-effects logistic regression was used to identify lipids associated with risk of T2D, adjusting for traditional risk factors. Repeated measurement analysis was performed to examine the association between change in lipidome and change in continuous measures of T2D, adjusting for baseline lipids. Multiple testing was controlled by false discovery rate at 0.05.ResultsHigher baseline level of 33 lipid species, including triacylglycerols, diacylglycerols, phosphoethanolamines, and phosphocholines, was significantly associated with increased risk of T2D (odds ratio [OR] per SD increase in log2-transformed baseline lipids 1.50-2.85) at 5-year follow-up. Of these, 21 lipids were also associated with risk of T2D at 16-year follow-up. Aberrant lipid profiles were also observed in prediabetes (OR per SD increase in log2-transformed baseline lipids 1.30-2.19 for risk lipids and 0.70-0.78 for protective lipids). Longitudinal changes in 568 lipids were significantly associated with changes in continuous measures of T2D. Multivariate analysis identified distinct lipidomic signatures differentiating high- from low-risk groups.ConclusionsLipid dysregulation occurs many years preceding T2D, and novel molecular lipids (both baseline level and longitudinal change over time) are significantly associated with risk of T2D beyond traditional risk factors. Our findings shed light on the mechanisms linking dyslipidemia to T2D and may yield novel therapeutic targets for early intervention tailored to American Indians.

Background Trimethylamine N-oxide (TMAO) is a gut microbiota-dependent metabolite of dietary choline, L-carnitine, and phosphatidylcholine-rich foods. On the basis of experimental studies and patients with prevalent disease, elevated plasma TMAO may increase risk of atherosclerotic cardiovascular disease (ASCVD). TMAO is also renally cleared and may interact with and causally contribute to renal dysfunction. Yet, how serial TMAO levels relate to incident and recurrent ASCVD in community-based populations and the potential mediating or modifying role of renal function are not established. Methods and Results We investigated associations of serial measures of plasma TMAO, assessed at baseline and 7 years, with incident and recurrent ASCVD in a community-based cohort of 4131 (incident) and 1449 (recurrent) older US adults. TMAO was measured using stable isotope dilution liquid chromatography-tandem mass spectrometry (laboratory coefficient of variation,

Psychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from 5 ancestry groups. In the combined meta-analyses of Stages 1 and 2, we identified 59 loci (p value

Coronary heart disease (CHD) is one of the leading causes of mortality and morbidity in the United States. Accurate time-to-event CHD prediction models with high-dimensional DNA methylation and clinical features may assist with early prediction and intervention strategies. We developed a state-of-the-art deep learning autoencoder survival analysis model (AESurv) to effectively analyze high-dimensional blood DNA methylation features and traditional clinical risk factors by learning low-dimensional representation of participants for time-to-event CHD prediction. We demonstrated the utility of our model in two cohort studies: the Strong Heart Study cohort (SHS) , a prospective cohort studying cardiovascular disease and its risk factors among American Indians adults; the Women's Health Initiative (WHI) , a prospective cohort study including randomized clinical trials and observational study to improve postmenopausal women's health with one of the main focuses on cardiovascular disease. Our AESurv model effectively learned participant representations in low-dimensional latent space and achieved better model performance (concordance index-C index of 0.864 ± 0.009 and time-to-event mean area under the receiver operating characteristic curve-AUROC of 0.905 ± 0.009) than other survival analysis models (Cox proportional hazard, Cox proportional hazard deep neural network survival analysis, random survival forest, and gradient boosting survival analysis models) in the SHS. We further validated the AESurv model in WHI and also achieved the best model performance. The AESurv model can be used for accurate CHD prediction and assist health care professionals and patients to perform early intervention strategies. We suggest using AESurv model for future time-to-event CHD prediction based on DNA methylation features. [ABSTRACT FROM AUTHOR]

ScopeBody weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter-individual variability in associations between body weight and dairy consumption.Methods and resultsA genome-wide interaction study to discover genetic variants that account for variation in BMI in the context of low-fat, high-fat and total dairy intake in cross-sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta-analyzed. Twenty-six genetic variants reached the selected significance threshold (p-interaction

BACKGROUND: Growing evidence indicates that trimethylamine N-oxide, a gut microbial metabolite of dietary choline and carnitine, promotes both cardiovascular disease and chronic kidney disease risk. It remains unclear how circulating concentrations of trimethylamine N-oxide and its related dietary and gut microbe-derived metabolites (choline, betaine, carnitine, γ-butyrobetaine, and crotonobetaine) affect incident heart failure (HF). METHODS: We evaluated 11 768 participants from the Cardiovascular Health Study and the Multi-Ethnic Study of Atherosclerosis with serial measures of metabolites. Cox proportional hazard models were used to examine the associations between metabolites and incident HF, adjusted for cardiovascular disease risk factors. RESULTS: In all, 2102 cases of HF occurred over a median follow-up of 15.9 years. After adjusting for traditional risk factors, higher concentrations of trimethylamine N-oxide (hazard ratio, 1.15 [95% CI, 1.09-1.20]; P<0.001), choline (hazard ratio, 1.44 [95% CI, 1.26-1.64]; P<0.001), and crotonobetaine (hazard ratio, 1.24 [95% CI, 1.16-1.32]; P<0.001) were associated with increased risk for incident HF. After further adjustment for renal function (potential confounder or mediator), these associations did not reach Bonferroni-corrected statistical significance (P=0.01, 0.049, and 0.006, respectively). Betaine and carnitine were nominally associated with a higher incidence of HF (P<0.05). In exploratory analyses, results were similar for subtypes of HF based on left ventricular ejection fraction, and associations appeared generally stronger among Black and Hispanic/Latino versus White adults, although there were no interactions for any metabolites with race. CONCLUSIONS: In this pooled analysis of 2 well-phenotyped, diverse, community-based cohorts, circulating concentrations of gut microbe-derived metabolites such as trimethylamine N-oxide, choline, and crotonobetaine were independently associated with a higher risk of developing HF. [ABSTRACT FROM AUTHOR]

Background/objectives Previous studies consistently report that diet quality is inversely associated with risk of cardiovascular disease (CVD) and type 2 diabetes. However, few studies have assessed the association of diet quality with serum lipoproteins, an intermediate marker of cardio-metabolic health, or assessed whether type 2 diabetes modifies these associations. This study assessed associations of diet quality (evaluated using the Alternative Healthy Eating Index (AHEI)), and the interaction of diet quality with diabetes, on total cholesterol (TC), triglycerides (TG), low-density lipoprotein (LDL-C), high-density lipoprotein (HDL-C), apolipoprotein A (apoA1), and apolipoprotein B (apoB) among American Indians (AIs). Subjects/methods Participants comprised AIs who participated in the Strong Heart Family Study (SHFS)--a study of CVD and its risk factors in 12 AI communities. Generalized estimated equations (GEEs) were used to examine the following associations: (1) the cross-sectional associations of diet quality (as determined by AHEI) with serum lipoproteins (n = 2200); and (2) the prospective associations of the AHEI measured at baseline with serum lipoproteins (n = 1899). Results In cross-sectional analyses, associations of AHEI with TC (p < 0.0001) LDL-C (p = 0.005), and ApoB (p = 0.002) differed according to diabetes status. In prospective analysis, AHEI was associated with more favorable levels of TC (p = 0.029) and LDL-C (p = 0.008) among participants with diabetes independent of other demographic, behavioral, and health factors; associations of diet quality with TC, LDL-C, and ApoB were much weaker among participants without diabetes. There was no association of diet quality with TG, HDL-C, or ApoA. Conclusions The associations of diet quality with TC, LDL-C, and ApoB differ according to diabetes status., Author(s): Sophie A. E. Kauffman [sup.1], Michelle M. Averill [sup.2], Joseph A. C Delaney [sup.3] [sup.4], Rozenn N. Lemaitre [sup.4] [sup.5], Barbara V. Howard [sup.6] [sup.7], Amanda M. Fretts [sup.3] [...]

BackgroundRecent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.ObjectiveWe investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.DesignFourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.ResultsProcessed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.ConclusionThe association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).