Physical activity and diet associations with the gut microbiota in the Coronary Artery Risk Development in Young Adults (CARDIA) study.

BACKGROUND: Gut microbiota may influence metabolic pathways related to chronic health conditions. Evidence for physical activity and diet influences on gut microbial composition exists, but data from diverse population-based cohort studies are limited. OBJECTIVES: We hypothesized that gut microbial diversity and genera are associated with physical activity and diet quality. METHODS: Data were from 537 participants in the Coronary Artery Risk Development in Young Adults (CARDIA) Study, a prospective cohort, who attended the year 30 follow-up examination (2015-2016; aged 47-61 y; 45% Black race/55% White race; 45% men/55% women). The 16S ribosomal RNA marker gene was sequenced from stool DNA, and genus-level taxonomy was assigned. Within-person microbial diversity (α-diversity) was assessed with Shannon diversity index and richness scores; between-person diversity (ß-diversity) measures were generated with principal coordinates analysis (PCoA). Current and long-term physical activity and diet quality measures were derived from data collected over 30 y of follow-up. Multivariable-adjusted regression analysis controlled for: sociodemographic variables (age, race, sex, education, and field center), other health behaviors (smoking, alcohol consumption, and medication use), and adjusted for multiple comparisons with the false discovery rate (<0.20). RESULTS: Based on PCoA ß-diversity, participants' microbial community compositions differed significantly (P < 0.001), with respect to both current and long-term physical activity and diet quality. α-Diversity was associated only with current physical activity (positively) in multivariable-adjusted analysis. Multiple genera (n = 45) were associated with physical activity and fewer with diet (n = 5), including positive associations with Lachnospiraceae UCG-001 and Ruminococcaceae IncertaeSedis with both behaviors. CONCLUSIONS: Physical activity and diet quality were associated with gut microbial composition among 537 participants in the CARDIA study. Multiple genera were associated with physical activity. Physical activity and diet quality were associated with genera consistent with pathways related to inflammation and short-chain fatty acid production.

Characterizing the urban diet: development of an urbanized diet index.

BACKGROUND: In recent decades China has experienced rapid urbanization leading to a major nutrition transition, with increased refined carbohydrates, added sweeteners, edible oils, and animal-source foods, and reduced legumes, vegetables, and fruits. These changes have accompanied increased prevalence of cardiometabolic disease (CMD). There is no single dietary measure that summarizes the distinct food changes across regions and levels of urbanization. METHODS: Using a sample of adults (≥18 years) in the 2015 wave of the China Health and Nutrition Survey (CHNS; n = 14,024), we selected literature-based candidate dietary variables and tested their univariate associations with overall and within-region urbanization. Using iterative exclusion of select diet-related variables, we created six potential urbanized diet indices, which we examined relative to overall urbanization to select a final urbanized diet index based on a priori considerations, strength of association with urbanization, and minimal missingness. We tested stability of the final urbanized diet index across sociodemographic factors. To examine whether our new measure reflected health risk, we used mixed effects logistic regression models to examine associations between the final urbanized diet index and CMD risk factors - hypertension (HTN), overweight, and type 2 diabetes mellitus (T2DM), adjusting for sociodemographics, overall urbanization, physical activity, and including random intercepts to account for correlation at community and household level. RESULTS: We identified a final urbanized diet index that captured dietary information unique to consumption of an urbanized diet and performed well across regions. We found a positive association (R2 = 0.17, 0.01 SE) between the final urbanized diet index and overall urbanization in the fully adjusted model. The new measure was negatively associated with HTN [OR (95% CI) = 0.93 (0.88-0.99)] and positively associated with T2D [OR = 1.13; 1.05-1.21] in minimally adjusted models, but not in the fully adjusted models. CONCLUSION: We derived an urbanized diet index that captured dietary urbanization that was distinct from overall urbanization and performed well across all regions of China. This urbanized diet index provides an alternative to measures of traditional versus urbanized diet that vary across regions due to different cultural dietary traditions. In addition, the new measure is best used in combination with diet quality measures, sociodemographic, and lifestyle measures to examine distinct pathways from urbanization to health in urbanizing countries.

Dietary Cholesterol and Cardiovascular Risk: A Science Advisory From the American Heart Association.

The elimination of specific dietary cholesterol target recommendations in recent guidelines has raised questions about its role with respect to cardiovascular disease. This advisory was developed after a review of human studies on the relationship of dietary cholesterol with blood lipids, lipoproteins, and cardiovascular disease risk to address questions about the relevance of dietary cholesterol guidance for heart health. Evidence from observational studies conducted in several countries generally does not indicate a significant association with cardiovascular disease risk. Although meta-analyses of intervention studies differ in their findings, most associate intakes of cholesterol that exceed current average levels with elevated total or low-density lipoprotein cholesterol concentrations. Dietary guidance should focus on healthy dietary patterns (eg, Mediterranean-style and DASH [Dietary Approaches to Stop Hypertension]-style diets) that are inherently relatively low in cholesterol with typical levels similar to the current US intake. These patterns emphasize fruits, vegetables, whole grains, low-fat or fat-free dairy products, lean protein sources, nuts, seeds, and liquid vegetable oils. A recommendation that gives a specific dietary cholesterol target within the context of food-based advice is challenging for clinicians and consumers to implement; hence, guidance focused on dietary patterns is more likely to improve diet quality and to promote cardiovascular health.

Municipal investment in off-road trails and changes in bicycle commuting in Minneapolis, Minnesota over 10 years: a longitudinal repeated cross-sectional study.

BACKGROUND: We studied the effect of key development and expansion of an off-road multipurpose trail system in Minneapolis, Minnesota between 2000 and 2007 to understand whether infrastructure investments are associated with increases in commuting by bicycle. METHODS: We used repeated measures regression on tract-level (N = 116 tracts) data to examine changes in bicycle commuting between 2000 and 2008-2012. We investigated: 1) trail proximity measured as distance from the trail system and 2) trail potential use measured as the proportion of commuting trips to destinations that might traverse the trail system. All analyses (performed 2015-2016) adjusted for tract-level sociodemographic covariates and contemporaneous cycling infrastructure changes (e.g., bicycle lanes). RESULTS: Tracts that were both closer to the new trail system and had a higher proportion of trips to destinations across the trail system experienced greater 10-year increases in commuting by bicycle. CONCLUSIONS: Proximity to off-road infrastructure and travel patterns are relevant to increased bicycle commuting, an important contributor to overall physical activity. Municipal investment in bicycle facilities, especially off-road trails that connect a city's population and its employment centers, is likely to lead to increases in commuting by bicycle.

Instrumental-Variables Simultaneous Equations Model of Physical Activity and Body Mass Index: The Coronary Artery Risk Development in Young Adults (CARDIA) Study.

We used full-system-estimation instrumental-variables simultaneous equations modeling (IV-SEM) to examine physical activity relative to body mass index (BMI; weight (kg)/height (m)(2)) using 25 years of data (1985/1986 to 2010/2011) from the Coronary Artery Risk Development in Young Adults (CARDIA) Study (n = 5,115; ages 18-30 years at enrollment). Neighborhood environment and sociodemographic instruments were used to characterize physical activity, fast-food consumption, smoking, alcohol consumption, marriage, and childbearing (women) and to predict BMI using semiparametric full-information maximum likelihood estimation to control for unobserved time-invariant and time-varying residual confounding and differential measurement error through model-derived discrete random effects. Comparing robust-variance ordinary least squares, random-effects regression, fixed-effects regression, single-equation-estimation IV-SEM, and full-system-estimation IV-SEM, estimates from random- and fixed-effects models and the full-system-estimation IV-SEM were unexpectedly similar, despite the lack of control for residual confounding with the random-effects estimator. Ordinary least squares tended to overstate the significance of health behaviors in BMI, while results from single-equation-estimation IV-SEM were notably different, revealing the impact of weak instruments in standard instrumental-variable methods. Our robust findings for fixed effects (which does not require instruments but has a high cost in lost degrees of freedom) and full-system-estimation IV-SEM (vs. standard IV-SEM) demonstrate potential for a full-system-estimation IV-SEM method even with weak instruments.

Diet and Gut Microbial Function in Metabolic and Cardiovascular Disease Risk.

Over the past decade, the gut microbiome has emerged as a novel and largely unexplored source of variability for metabolic and cardiovascular disease risk, including diabetes. Animal and human studies support several possible pathways through which the gut microbiome may impact health, including the production of health-related metabolites from dietary sources. Diet is considered important to shaping the gut microbiota; in addition, gut microbiota influence the metabolism of many dietary components. In the present paper, we address the distinction between compositional and functional analysis of the gut microbiota. We focus on literature that highlights the value of moving beyond surveys of microbial composition to measuring gut microbial functioning to delineate mechanisms related to the interplay between diet and gut microbiota in cardiometabolic health.

Neighborhood availability of convenience stores and diet quality: findings from 20 years of follow-up in the coronary artery risk development in young adults study.

OBJECTIVES: We examined the association between neighborhood convenience stores and diet outcomes for 20 years of the Coronary Artery Risk Development in Young Adults study. METHODS: We used dietary data from the Coronary Artery Risk Development in Young Adults study years 1985-1986, 1992-1993, and 2005-2006 (n = 3299; Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA) and geographically and temporally matched neighborhood-level food resource and US Census data. We used random effects repeated measures regression to estimate associations between availability of neighborhood convenience stores with diet outcomes and whether these associations differed by individual-level income. RESULTS: In multivariable-adjusted analyses, greater availability of neighborhood convenience stores was associated with lower diet quality (mean score = 66.3; SD = 13.0) for participants with lower individual-level income (b = -2.40; 95% CI = -3.30, -1.51); associations at higher individual-level income were weaker. We observed similar associations with whole grain consumption across time but no statistically significant associations with consumption of sugar-sweetened beverages, artificially sweetened beverages, snacks, processed meats, fruits, or vegetables. CONCLUSIONS: The presence of neighborhood convenience stores may be associated with lower quality diets. Low-income individuals may be most sensitive to convenience store availability.

Identifying unmeasured heterogeneity in microbiome data via quantile thresholding (QuanT).

Microbiome data exhibit technical and biomedical heterogeneity due to varied processing and experimental designs, which may lead to spurious results if uncorrected. Here, we introduce the Quantile Thresholding (QuanT) method, a comprehensive non-parametric hidden variable inference method that accommodates the complex distributions of microbial read counts and relative abundances. We apply QuanT to synthetic and real data sets and demonstrate its ability to identify unmeasured heterogeneity and improve downstream analysis.

Choline metabolites and incident cardiovascular disease in a prospective cohort of adults: Coronary Artery Risk Development in Young Adults (CARDIA) Study.

BACKGROUND: The potential role for choline metabolite trimethylamine N-oxide (TMAO) in cardiovascular disease (CVD) has garnered much attention, but there have been limited data from diverse population-based cohorts. Furthermore, few studies have included circulating choline and betaine, which can serve as precursors to TMAO and may independently influence CVD. OBJECTIVE: We quantified prospective associations between 3 choline metabolites and 19-y incident CVD in a population-based cohort and tested effect modification of metabolite-CVD associations by kidney function. METHODS: Data were from the Coronary Artery Risk Development in Young Adults (CARDIA) Study, a prospective cohort with recruitment from 4 US urban centers (year 0: 1985-1986, n = 5115, ages 18-30). The analytic sample included 3444 White and Black males and females, aged 33 to 45, who attended the year 15 follow-up exam and did not have prevalent CVD. TMAO, choline, and betaine were quantitated from stored plasma (-70°C) using liquid-chromatography mass-spectrometry. Nineteen-year incident CVD events (n = 221), including coronary heart disease and stroke, were identified through adjudicated hospitalization records and linkage with the National Death Register. RESULTS: Plasma choline was positively associated with CVD in Cox proportional hazards regression analysis adjusted for demographics, health behaviors, CVD risk factors, and metabolites (hazard ratio: 1.24; 95% CI: 1.09, 1.40 per standard deviation-unit choline). TMAO and betaine were not associated with CVD in an identically adjusted analysis. There was statistical evidence for effect modification by kidney function with CVD positively associated with TMAO and negatively associated with betaine at lower values of estimated glomerular filtration rate (interaction P values: 0.0046 and 0.020, respectively). CONCLUSIONS: Our findings are consistent with a positive association between plasma choline and incident CVD. Among participants with lower kidney function, TMAO was positively, and betaine negatively, associated with CVD. These results further our understanding of the potential role for choline metabolism on CVD risk.

Choline Metabolites and 15-Year Risk of Incident Diabetes in a Prospective Cohort of Adults: Coronary Artery Risk Development in Young Adults (CARDIA) Study.

OBJECTIVE: The potential for choline metabolism to influence the development of diabetes has received increased attention. Previous studies on circulating choline metabolites and incident diabetes have been conducted in samples of older adults, often with a high prevalence of risk factors. RESEARCH DESIGN AND METHODS: Participants were from year 15 of follow-up (2000-2001) in the Coronary Artery Risk Development in Young Adults (CARDIA) Study (n = 3,133, aged 33-45 years) with plasma choline metabolite (choline, betaine, and trimethylamine N-oxide [TMAO]) data. We quantified associations between choline metabolites and 15-year risk of incident diabetes (n = 387) among participants free of diabetes at baseline using Cox proportional hazards regression models adjusted for sociodemographics, health behaviors, and clinical variables. RESULTS: Betaine was inversely associated with 15-year risk of incident diabetes (hazard ratio 0.76 [95% CI 0.67, 0.88] per 1-SD unit betaine), and TMAO was positively associated with 15-year risk of incident diabetes (1.11 [1.01, 1.22] per 1-SD unit). Choline was not significantly associated with 15-year risk of incident diabetes (1.05 [0.94, 1.16] per 1-SD). CONCLUSIONS: Our findings are consistent with other published literature supporting a role for choline metabolism in diabetes. Our study extends the current literature by analyzing a racially diverse population-based cohort of early middle-aged individuals in whom preventive activities may be most relevant.

Simple Nutrient-Based Rules vs. a Nutritionally Rich Plant-Centered Diet in Prediction of Future Coronary Heart Disease and Stroke: Prospective Observational Study in the US.

To better understand nutrition paradigm shift from nutrients to foods and dietary patterns, we compared associations of a nutrient-based blood cholesterol-lowering diet vs. a food-based plant-centered diet with risk of coronary heart disease (CHD) and stroke. Participants were 4701 adults aged 18-30 years and free of cardiovascular disease at baseline, followed for clinical events from 1985 and 86 to 2018. A plant-centered diet was represented by higher A Priori Diet Quality Score (APDQS). A blood cholesterol-lowering diet was represented by lower Keys Score. Proportional hazards regression was used to calculate hazard ratios (HR). Higher APDQS showed a nutrient-dense composition that is low in saturated fat but high in fiber, vitamins and minerals. Keys Score and APDQS changes were each inversely associated with concurrent plasma low-density lipoprotein cholesterol (LDL-C) change. Over follow-up, 116 CHD and 80 stroke events occurred. LDL-C predicted CHD, but not stroke. APDQS, but not Keys Score, predicted lower risk of CHD and of stroke. Adjusted HRs (95% CIs) for each 1-SD higher APDQS were 0.73 (0.55-0.96) for CHD and 0.70 (0.50-0.99) for stroke. Neither low dietary fat nor low dietary carbohydrate predicted these events. Our findings support the ongoing shift in diet messages for cardiovascular prevention.

Batch effects removal for microbiome data via conditional quantile regression.

Batch effects in microbiome data arise from differential processing of specimens and can lead to spurious findings and obscure true signals. Strategies designed for genomic data to mitigate batch effects usually fail to address the zero-inflated and over-dispersed microbiome data. Most strategies tailored for microbiome data are restricted to association testing or specialized study designs, failing to allow other analytic goals or general designs. Here, we develop the Conditional Quantile Regression (ConQuR) approach to remove microbiome batch effects using a two-part quantile regression model. ConQuR is a comprehensive method that accommodates the complex distributions of microbial read counts by non-parametric modeling, and it generates batch-removed zero-inflated read counts that can be used in and benefit usual subsequent analyses. We apply ConQuR to simulated and real microbiome datasets and demonstrate its advantages in removing batch effects while preserving the signals of interest.

Invited commentary: on population subgroups, mathematics, and interventions.

New sex-specific equations, each with race/ethnic-specific intercept, for predicted lung function illustrate a methodological point, that complex differences between groups may not imply interactions with other predictors, such as age and height. The new equations find that race/ethnic identity does not interact with either age or height in the prediction equations, although there are race/ethnic-specific offsets. Further study is warranted of the effect of possible small race/ethnic interactions on disease classification. Additional study of repeated measures of lung function is warranted, given that the new equations were developed in cross-sectional designs. Predicting lung function is more than a methodological exercise. Predicted values are important in disease diagnosis and monitoring. It is suggested that measurement and tracking of lung function throughout young adulthood could be used to provide an early warning of potential long-term lung function losses to encourage improvement of risky behaviors including smoking and failure to maintain normal body weight in the general population.

Body fat is differentially related to body mass index in U.S.-born African-American and East African immigrant girls.

OBJECTIVE: To examine ethnic differences in adiposity at a given body mass index (BMI) in a sample of U.S.-born African-American and East African immigrant adolescent girls. METHODS: In a sample of black adolescent girls (n = 79; ages 14-20) we compared measures of adiposity across the range of BMI-for-age among 55 U.S.-born African-American (mean BMI: 30.4; age: 15.4) and 24 East African immigrant girls (mean BMI: 21.8; age: 16.7). Fat and fat-free mass were assessed with dual-energy X-ray absorptiometry (DXA). We used spline regression to examine the distributions of fat mass index and percent body fat across the range of BMI-for-age z-scores. RESULTS: Compared with African-American girls, East African girls were smaller on all body measures, but appeared to have higher fat mass index and percent body fat at the same BMI-for-age. CONCLUSIONS: Our findings indicate that at a given BMI East African immigrants may have greater adiposity than African-American girls. If corroborated in larger samples, our data suggest that the cardiometabolic risks attendant to elevated adiposity may affect East African girls at a lower BMI than in African-American girls.

Powerful and robust non-parametric association testing for microbiome data via a zero-inflated quantile approach (ZINQ).

BACKGROUND: Identification of bacterial taxa associated with diseases, exposures, and other variables of interest offers a more comprehensive understanding of the role of microbes in many conditions. However, despite considerable research in statistical methods for association testing with microbiome data, approaches that are generally applicable remain elusive. Classical tests often do not accommodate the realities of microbiome data, leading to power loss. Approaches tailored for microbiome data depend highly upon the normalization strategies used to handle differential read depth and other data characteristics, and they often have unacceptably high false positive rates, generally due to unsatisfied distributional assumptions. On the other hand, many non-parametric tests suffer from loss of power and may also present difficulties in adjusting for potential covariates. Most extant approaches also fail in the presence of heterogeneous effects. The field needs new non-parametric approaches that are tailored to microbiome data, robust to distributional assumptions, and powerful under heterogeneous effects, while permitting adjustment for covariates. METHODS: As an alternative to existing approaches, we propose a zero-inflated quantile approach (ZINQ), which uses a two-part quantile regression model to accommodate the zero inflation in microbiome data. For a given taxon, ZINQ consists of a valid test in logistic regression to model the zero counts, followed by a series of quantile rank-score based tests on multiple quantiles of the non-zero part with adjustment for the zero inflation. As a regression and quantile-based approach, the method is non-parametric and robust to irregular distributions, while providing an allowance for covariate adjustment. Since no distributional assumptions are made, ZINQ can be applied to data that has been processed under any normalization strategy. RESULTS: Thorough simulations based on real data across a range of scenarios and application to real data sets show that ZINQ often has equivalent or higher power compared to existing tests even as it offers better control of false positives. CONCLUSIONS: We present ZINQ, a quantile-based association test between microbiota and dichotomous or quantitative clinical variables, providing a powerful and robust alternative for the current microbiome differential abundance analysis. Video Abstract.

Gut Microbiota and Host Plasma Metabolites in Association with Blood Pressure in Chinese Adults.

Animal studies have revealed gut microbial and metabolic pathways of blood pressure (BP) regulation, yet few epidemiological studies have collected microbiota and metabolomics data in the same individuals. In a population-based, Chinese cohort who did not report antihypertension medication use (30-69 years, 54% women), thus minimizing BP treatment effects, we examined multivariable-adjusted (eg, diet, physical activity, smoking, kidney function), cross-sectional associations between measures of gut microbiota (16S rRNA [ribosomal ribonucleic acid], N=1003), and plasma metabolome (liquid chromatography-mass spectrometry, N=434) with systolic (SBP, mean [SD]=126.0 [17.4] mm Hg) and diastolic BP (DBP [80.7 (10.7) mm Hg]). We found that the overall microbial community assessed by principal coordinate analysis varied by SBP and DBP (permutational multivariate ANOVA P<0.05). To account for strong correlations across metabolites, we first examined metabolite patterns derived from principal component analysis and found that a lipid pattern was positively associated with SBP (linear regression coefficient [95% CI] per 1 SD pattern score: 2.23 [0.72-3.74] mm Hg) and DBP (1.72 [0.81-2.63] mm Hg). Among 1104 individual metabolites, 34 and 39 metabolites were positively associated with SBP and DBP (false discovery rate-adjusted linear model P<0.05), respectively, including linoleate, palmitate, dihomolinolenate, 8 sphingomyelins, 4 acyl-carnitines, and 2 phosphatidylinositols. Subsequent pathway analysis showed that metabolic pathways of long-chain saturated acylcarnitine, phosphatidylinositol, and sphingomyelins were associated with SBP and DBP (false discovery rate-adjusted Fisher exact test P<0.05). Our results suggest potential roles of microbiota and metabolites in BP regulation to be followed up in prospective and clinical studies.

Circulating trimethylamine N-oxide in association with diet and cardiometabolic biomarkers: an international pooled analysis.

BACKGROUND: Trimethylamine N-oxide (TMAO), a diet-derived, gut microbial-host cometabolite, has been linked to cardiometabolic diseases. However, the relations remain unclear between diet, TMAO, and cardiometabolic health in general populations from different regions and ethnicities. OBJECTIVES: To examine associations of circulating TMAO with dietary and cardiometabolic factors in a pooled analysis of 16 population-based studies from the United States, Europe, and Asia. METHODS: Included were 32,166 adults (16,269 white, 13,293 Asian, 1247 Hispanic/Latino, 1236 black, and 121 others) without cardiovascular disease, cancer, chronic kidney disease, or inflammatory bowel disease. Linear regression coefficients (ß) were computed for standardized TMAO with harmonized variables. Study-specific results were combined by random-effects meta-analysis. A false discovery rate <0.10 was considered significant. RESULTS: After adjustment for potential confounders, circulating TMAO was associated with intakes of animal protein and saturated fat (ß = 0.124 and 0.058, respectively, for a 5% energy increase) and with shellfish, total fish, eggs, and red meat (ß = 0.370, 0.151, 0.081, and 0.056, respectively, for a 1 serving/d increase). Plant protein and nuts showed inverse associations (ß = -0.126 for a 5% energy increase from plant protein and -0.123 for a 1 serving/d increase of nuts). Although the animal protein-TMAO association was consistent across populations, fish and shellfish associations were stronger in Asians (ß = 0.285 and 0.578), and egg and red meat associations were more prominent in Americans (ß = 0.153 and 0.093). Besides, circulating TMAO was positively associated with creatinine (ß = 0.131 SD increase in log-TMAO), homocysteine (ß = 0.065), insulin (ß = 0.048), glycated hemoglobin (ß = 0.048), and glucose (ß = 0.023), whereas it was inversely associated with HDL cholesterol (ß = -0.047) and blood pressure (ß = -0.030). Each TMAO-biomarker association remained significant after further adjusting for creatinine and was robust in subgroup/sensitivity analyses. CONCLUSIONS: In an international, consortium-based study, animal protein was consistently associated with increased circulating TMAO, whereas TMAO associations with fish, shellfish, eggs, and red meat varied among populations. The adverse associations of TMAO with certain cardiometabolic biomarkers, independent of renal function, warrant further investigation.

Associations of circulating choline and its related metabolites with cardiometabolic biomarkers: an international pooled analysis.

BACKGROUND: Choline is an essential nutrient; however, the associations of choline and its related metabolites with cardiometabolic risk remain unclear. OBJECTIVE: We examined the associations of circulating choline, betaine, carnitine, and dimethylglycine (DMG) with cardiometabolic biomarkers and their potential dietary and nondietary determinants. METHODS: The cross-sectional analyses included 32,853 participants from 17 studies, who were free of cancer, cardiovascular diseases, chronic kidney diseases, and inflammatory bowel disease. In each study, metabolites and biomarkers were log-transformed and standardized by means and SDs, and linear regression coefficients (ß) and 95% CIs were estimated with adjustments for potential confounders. Study-specific results were combined by random-effects meta-analyses. A false discovery rate <0.05 was considered significant. RESULTS: We observed moderate positive associations of circulating choline, carnitine, and DMG with creatinine [ß (95% CI): 0.136 (0.084, 0.188), 0.106 (0.045, 0.168), and 0.128 (0.087, 0.169), respectively, for each SD increase in biomarkers on the log scale], carnitine with triglycerides (ß = 0.076; 95% CI: 0.042, 0.109), homocysteine (ß = 0.064; 95% CI: 0.033, 0.095), and LDL cholesterol (ß = 0.055; 95% CI: 0.013, 0.096), DMG with homocysteine (ß = 0.068; 95% CI: 0.023, 0.114), insulin (ß = 0.068; 95% CI: 0.043, 0.093), and IL-6 (ß = 0.060; 95% CI: 0.027, 0.094), but moderate inverse associations of betaine with triglycerides (ß = -0.146; 95% CI: -0.188, -0.104), insulin (ß = -0.106; 95% CI: -0.130, -0.082), homocysteine (ß = -0.097; 95% CI: -0.149, -0.045), and total cholesterol (ß = -0.074; 95% CI: -0.102, -0.047). In the whole pooled population, no dietary factor was associated with circulating choline; red meat intake was associated with circulating carnitine [ß = 0.092 (0.042, 0.142) for a 1 serving/d increase], whereas plant protein was associated with circulating betaine [ß = 0.249 (0.110, 0.388) for a 5% energy increase]. Demographics, lifestyle, and metabolic disease history showed differential associations with these metabolites. CONCLUSIONS: Circulating choline, carnitine, and DMG were associated with unfavorable cardiometabolic risk profiles, whereas circulating betaine was associated with a favorable cardiometabolic risk profile. Future prospective studies are needed to examine the associations of these metabolites with incident cardiovascular events.

Collaborative Cohort of Cohorts for COVID-19 Research (C4R) Study: Study Design.

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