Rationale:: Few studies have systematically assessed the influence of gut microbiota on cardiovascular disease (CVD) risk. Objective:: To examine the association between gut microbiota and lifetime CVD risk profile among 55 Bogalusa Heart Study participants with the highest and 57 with the lowest lifetime burdens of CVD risk factors. Methods and Results:: 16S ribosomal RNA sequencing was conducted on microbial DNA extracted from stool samples of the Bogalusa Heart Study participants. α Diversity, including measures of richness and evenness, and individual genera were tested for associations with lifetime CVD risk profile. Multivariable regression techniques were used to adjust for age, sex, and race (model 1), along with body mass index (model 2) and both body mass index and diet (model 3). In model 1, odds ratios (95% confidence intervals) for each SD increase in richness, measured by the number of observed operational taxonomic units, Chao 1 index, and abundance-based coverage estimator, were 0.62 (0.39–0.99), 0.61 (0.38–0.98), and 0.63 (0.39–0.99), respectively. Associations were consistent in models 2 and 3. Four genera were enriched among those with high versus low CVD risk profile in all models. Model 1 P values were 2.12×10 ⁻³ , 7.95×10 ⁻⁵ , 4.39×10 ⁻⁴ , and 1.51×10 ⁻⁴ for Prevotella 2, Prevotella 7 , Tyzzerella , and Tyzzerella 4 , respectively. Two genera were depleted among those with high versus low CVD risk profile in all models. Model 1 P values were 2.96×10 ⁻⁶ and 1.82×10 ⁻⁴ for Alloprevotella and Catenibacterium , respectively. Conclusions:: The current study identified associations of overall microbial richness and 6 microbial genera with lifetime CVD risk.

Results from clinical trials examining the effect of intensive glucose control on cardiovascular disease have been conflicting. To summarize clinical benefits and harms of intensive versus conventional glucose control for adults with type 2 diabetes. Studies were retrieved by systematically searching the MEDLINE database (January 1950 to April 2009) with no language restrictions. Two independent reviewers screened abstracts or full-text articles to identify randomized trials that compared clinical outcomes in patients with type 2 diabetes receiving intensive glucose control and those receiving conventional glucose control. Two investigators independently abstracted data on study variables and outcomes, including severe hypoglycemia, cardiovascular disease, and all-cause mortality. 5 trials involving 27 802 adults were included. Intensive glucose targets were lower in the 3 most recent trials. Summary analyses showed that compared with conventional control, intensive glucose control reduced the risk for cardiovascular disease (relative risk [RR], 0.90 [95% CI, 0.83 to 0.98]; risk difference per 1000 patients per 5 years [RD], −15 [CI, −24 to −5]) but not cardiovascular death (RR, 0.97 [CI, 0.76 to 1.24]; RD, −3 [CI, −14 to 7]) or all-cause mortality (RR, 0.98 [CI, 0.84 to 1.15]; RD, −4 [CI, −17 to 10]). Intensive glucose control increased the risk for severe hypoglycemia (RR, 2.03 [CI, 1.46 to 2.81]; RD, 39 [CI, 7 to 71]). As was seen in the overall analyses, pooled findings from the early and more recent trials showed that intensive glucose control reduced the risk for cardiovascular disease and increased the risk for severe hypoglycemia. Summary rather than individual data were pooled across trials. Intensive glucose control reduced the risk for some cardiovascular disease outcomes (such as nonfatal myocardial infarction), did not reduce the risk for cardiovascular death or all-cause mortality, and increased the risk for severe hypoglycemia.

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11–34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count 86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10^-15] in African populations, rs11549407 with lower HGB [p = 1.5x10^-12] and HCT [p = 8.8x10^-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations. Admixed African and Hispanic/Latino populations remain understudied in genetic studies of complex diseases. These populations have more complex linkage disequilibrium (LD) structure that can impair mapping of variants. Genotype imputation represents an approach to improve genome coverage, especially for rare or ancestry-specific variation; however, these understudied populations also have smaller relevant imputation reference panels. In this study, we leveraged >100,000 phased sequences generated from the multi-ethnic NHLBI TOPMed project for imputation in ~21,600 individuals of African ancestry (AAs) and ~21,700 Hispanics/Latinos. We demonstrated substantially higher imputation quality for low frequency and rare variants in comparison to the 1000 Genomes Project and Haplotype Reference Consortium reference panels. Analysis of quantitative hematological traits led to the discovery of associations with two rare variants in the HBB gene; one of these variants was replicated in an independent sample, and the other is known to cause anemia in the homozygous state. By comparison, the same HBB variants would not have been genome-wide significant using current reference panels due to lower imputation quality. Our findings demonstrate the power of TOPMed whole genome sequencing data for imputation and subsequent association analysis in admixed African and Hispanic/Latino populations.

Key differences exist between men and women in the determinants and manifestations of cardiovascular and cardiometabolic diseases. Recently, gut microbiome-host relations have been implicated in cardiovascular disease and associated metabolic conditions; therefore, gut microbiota may be key mediators or modulators driving the observed sexual dimorphism in disease onset and progression. While current evidence regarding pure physiological sex differences in gut microbiome composition is modest, robust research suggests that gut microbiome-dependent metabolites may interact with important biological pathways under sex hormone control, including toll-like receptor and flavin monooxygenase signaling. Here, we review key sex differences in gut microbiome interactions with four primary determinants of cardiovascular disease, impaired glucose regulation, dyslipidemia, hypertension, and obesity. Through this process, we propose important sex differences in downstream metabolic pathways that may be at the interface of the gut microbiome and cardiovascular disease.

The authors conducted a meta-analysis of randomized controlled trials to evaluate the association of dietary protein intake with blood pressure. To identify articles published before April 2011, the authors searched electronic databases, conducted a manual bibliography review, and consulted experts in the field. Forty trials (including 3,277 participants in total) met the eligibility criteria and were included. Using a standardized form, 2 investigators independently abstracted data on study design, participant characteristics, and treatment outcomes. Net change estimates were pooled across trials using random-effects models. Compared with carbohydrate, dietary protein intake was associated with significant changes in mean systolic and diastolic blood pressure of −1.76 mm Hg (95% confidence interval (CI): −2.33, −1.20) and −1.15 mm Hg (95% CI: −1.59, −0.71), respectively (both P 's < 0.001). Both vegetable protein and animal protein were associated with significant blood pressure changes of −2.27 mm Hg (95% CI: −3.36, −1.18) and −2.54 mm Hg (95% CI: −3.55, −1.53), respectively, for systolic blood pressure (both P 's < 0.001) and −1.26 mm Hg (95% CI: −2.26, −0.26) and −0.95 mm Hg (95% CI: −1.72, −0.19), respectively, for diastolic blood pressure (both P 's = 0.014). Blood pressure reduction was not significantly different when vegetable protein was compared directly with animal protein. These findings indicate that partially replacing dietary carbohydrate with protein may be important for the prevention and treatment of hypertension.

We conducted a meta-analysis of randomized controlled trials to examine the association of mobile phone intervention with net change in weight-related measures among overweight and obese adults. We searched electronic databases and conducted a bibliography review to identify articles published between the inception date of each database and March 27, 2014. Fourteen trials (including 1,337 participants in total) that met the eligibility criteria were included. Two investigators independently abstracted information on study characteristics and study outcomes. Net change estimates comparing the intervention group with the control group were pooled across trials using random-effects models. Compared with the control group, mobile phone intervention was associated with significant changes in body weight and body mass index (weight (kg)/height (m)²) of −1.44 kg (95% confidence interval (CI): −2.12, −0.76) and −0.24 units (95% CI: −0.40, −0.08), respectively. Subgroup analyses revealed that the associations were consistent across study-duration and intervention-type subgroups. For example, net body weight changes were −0.92 kg (95% CI: −1.58, −0.25) and −1.85 kg (95% CI: −2.99, −0.71) in trials of shorter (<6 months) and longer (≥6 months) duration, respectively. These findings provide evidence that mobile phone intervention may be a useful tool for promoting weight loss among overweight and obese adults.