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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 study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P

BACKGROUND: While the gut microbiota is relatively stable through adulthood, its composition is influenced by various host and environmental factors, including changes in health, gastrointestinal processes (e.g., transit time, gastric acidity), medication use, and diet. The association of habitual diet, in the form of a posteriori-derived dietary patterns, and microbiota composition has not been adequately studied, particularly in older men. OBJECTIVE: The objective was to investigate the association of dietary patterns with the composition and diversity of the gut bacterial microbiota in community-dwelling, older men. METHODS: This cross-sectional study included 517 men who were participants in the Osteoporotic Fractures in Men (MrOS) Study (≥65 y of age at baseline in 2000-2002) and who provided a stool sample and completed an FFQ at MrOS Visit 4 in 2014-2016. Dietary patterns were derived by factor analysis. 16S ribosomal RNA target gene sequencing was performed and taxonomy assignments were derived using the Greengenes database. Linear regression and permutational multivariate analysis of variance (PERMANOVA) considered variations in alpha and beta diversity by dietary pattern, and a model that implements a 0-inflated Gaussian distribution of mean group abundance for each taxa (metagenomeSeq) assessed taxonomic variations by dietary pattern. RESULTS: In multivariable-adjusted models, greater adherence to the Western pattern was positively associated with families Mogibacteriaceae and Veillonellaceae and genera Alistipes, Anaerotruncus, CC-115, Collinsella, Coprobacillus, Desulfovibrio, Dorea, Eubacterium, and Ruminococcus, while greater adherence to the prudent pattern was positively associated with order Streptophyta, family Victivallaceae, and genera Cetobacterium, Clostridium, Faecalibacterium, Lachnospira, Paraprevotella, and Veillonella. The relative abundance of the dominant gut bacterial phyla, Bacteroidetes and Firmicutes, did not differ between participants with greater adherence to the Western pattern, compared with those with greater adherence to the prudent pattern. Dietary patterns were not associated with measures of alpha diversity, but beta diversity measures were significantly associated with both Western and prudent patterns. CONCLUSIONS: We observed significant associations between dietary patterns and measures of gut microbial composition in this sample of community-dwelling, older men.

BackgroundWe 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.MethodsWe 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).ResultsTracts 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.ConclusionsProximity 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.

BackgroundWhile many studies have found the built environment to be associated with walking, most have used cross-sectional research designs and few have examined more distal cardiometabolic outcomes. This study contributes longitudinal evidence based on changes in walking, body mass index (BMI), and cardiometabolic risk following residential relocation.MethodsWe examined 1,079 participants in the CARDIA study who moved residential locations between 2000 and 2006 (ages 32-46 in 2000, 49% white/51% black, 55% female). We created a walkability index from measures of population density, street connectivity, and food and physical activity resources, measured at participants' pre- and post-move residential locations. Outcomes measured before and after the move included walking, BMI, waist circumference, blood pressure, insulin resistance, triglycerides, cholesterol, atherogenic dyslipidemia, and C-reactive protein. Fixed effects (FE) models were used to estimate associations between within-person change in walkability and within-person change in each outcome. These estimates were compared to those from random effects (RE) models to assess the implications of unmeasured confounding.ResultsIn FE models, a one-SD increase in walkability was associated with a 0.81 mmHg decrease in systolic blood pressure [95% CI: (-1.55, -0.07)] and a 7.36 percent increase in C-reactive protein [95% CI: (0.60, 14.57)]. Although several significant associations were observed in the RE models, Hausman tests suggested that these estimates were biased for most outcomes. RE estimates were most commonly biased away from the null or in the opposite direction of effect as the FE estimates.ConclusionsGreater walkability was associated with lower blood pressure and higher C-reactive protein in FE models, potentially reflecting competing health risks and benefits in dense, walkable environments. RE models tended to overstate or otherwise misrepresent the relationship between walkability and health. Approaches that base estimates on variation between individuals may be subject to bias from unmeasured confounding, such as residential self-selection.

BackgroundClinical studies implicate trimethylamine N-oxide (TMAO; a gut microbiota-dependent nutrient metabolite) in cardiovascular disease risk. There is a lack of population-based data on the role of TMAO in advancing early atherosclerotic disease. We tested the prospective associations between TMAO and coronary artery calcium (CAC) and carotid intima-media thickness (cIMT).Methods and resultsData were from the Coronary Artery Risk Development in Young Adults Study (CARDIA), a biracial cohort of US adults recruited in 1985-1986 (n=5115). We randomly sampled 817 participants (aged 33-55 years) who attended examinations in 2000-2001, 2005-2006, and 2010-2011, at which CAC was measured by computed tomography and cIMT (2005-2006) by ultrasound. TMAO was quantified using liquid chromotography mass spectrometry on plasma collected in 2000-2001. Outcomes were incident CAC, defined as Agatston units=0 in 2000-2001 and >0 over 10-year follow-up, CAC progression (any increase over 10-year follow-up), and continuous cIMT. Over the study period, 25% (n=184) of those free of CAC in 2000-2001 (n=746) developed detectable CAC. In 2000-2001, median (interquartile range) TMAO was 2.6 (1.8-4.2) μmol/L. In multivariable-adjusted models, TMAO was not associated with 10-year CAC incidence (rate ratio=1.03; 95% CI: 0.71-1.52) or CAC progression (0.97; 0.68-1.38) in Poisson regression, or cIMT (beta coefficient: -0.009; -0.03 to 0.01) in linear regression, comparing the fourth to the first quartiles of TMAO.ConclusionsIn this population-based study, TMAO was not associated with measures of atherosclerosis: CAC incidence, CAC progression, or cIMT. These data indicate that TMAO may not contribute significantly to advancing early atherosclerotic disease risk among healthy early-middle-aged adults.

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.