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Populations change in size over time due to factors such as population growth, migration, bottleneck events, natural disasters, and disease. The historical effective size of a population affects the power and resolution of genetic association studies. For admixed populations, it is not only the overall effective population size that is of interest, but also the effective sizes of the component ancestral populations. We use identity by descent and local ancestry inferred from genome-wide genetic data to estimate overall and ancestry-specific effective population size during the past hundred generations for nine admixed American populations from the Hispanic Community Health Study/Study of Latinos, and for African-American and European-American populations from two US cities. In these populations, the estimated pre-admixture effective sizes of the ancestral populations vary by sampled population, suggesting that the ancestors of different sampled populations were drawn from different sub-populations. In addition, we estimate that overall effective population sizes dropped substantially in the generations immediately after the commencement of European and African immigration, reaching a minimum around 12 generations ago, but rebounded within a small number of generations afterwards. Of the populations that we considered, the population of individuals originating from Puerto Rico has the smallest bottleneck size of one thousand, while the Pittsburgh African-American population has the largest bottleneck size of two hundred thousand.

Background Hispanics living in the USA may have unrecognized potential birthplace and lifestyle influences on the gut microbiome. We report a cross-sectional analysis of 1674 participants from four centers of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), aged 18 to 74 years old at recruitment. Results Amplicon sequencing of 16S rRNA gene V4 and fungal ITS1 fragments from self-collected stool samples indicate that the host microbiome is determined by sociodemographic and migration-related variables. Those who relocate from Latin America to the USA at an early age have reductions in Prevotella to Bacteroides ratios that persist across the life course. Shannon index of alpha diversity in fungi and bacteria is low in those who relocate to the USA in early life. In contrast, those who relocate to the USA during adulthood, over 45 years old, have high bacterial and fungal diversity and high Prevotella to Bacteroides ratios, compared to USA-born and childhood arrivals. Low bacterial diversity is associated in turn with obesity. Contrasting with prior studies, our study of the Latino population shows increasing Prevotella to Bacteroides ratio with greater obesity. Taxa within Acidaminococcus, Megasphaera, Ruminococcaceae, Coriobacteriaceae, Clostridiales, Christensenellaceae, YS2 (Cyanobacteria), and Victivallaceae are significantly associated with both obesity and earlier exposure to the USA, while Oscillospira and Anaerotruncus show paradoxical associations with both obesity and late-life introduction to the USA. Conclusions Our analysis of the gut microbiome of Latinos demonstrates unique features that might be responsible for health disparities affecting Hispanics living in the USA.

Background Obesity and related comorbidities are major health concerns among many US immigrant populations. Emerging evidence suggests a potential involvement of the gut microbiome. Here, we evaluated gut microbiome features and their associations with immigration, dietary intake, and obesity in 2640 individuals from a population-based study of US Hispanics/Latinos. Results The fecal shotgun metagenomics data indicate that greater US exposure is associated with reduced ɑ-diversity, reduced functions of fiber degradation, and alterations in individual taxa, potentially related to a westernized diet. However, a majority of gut bacterial genera show paradoxical associations, being reduced with US exposure and increased with fiber intake, but increased with obesity. The observed paradoxical associations are not explained by host characteristics or variation in bacterial species but might be related to potential microbial co-occurrence, as seen by positive correlations among Roseburia , Prevotella , Dorea , and Coprococcus . In the conditional analysis with mutual adjustment, including all genera associated with both obesity and US exposure in the same model, the positive associations of Roseburia and Prevotella with obesity did not persist, suggesting that their positive associations with obesity might be due to their co-occurrence and correlations with obesity-related taxa, such as Dorea and Coprococcus . Conclusions Among US Hispanics/Latinos, US exposure is associated with unfavorable gut microbiome profiles for obesity risk, potentially related to westernized diet during acculturation. Microbial co-occurrence could be an important factor to consider in future studies relating individual gut microbiome taxa to environmental factors and host health and disease.

In a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called “PRSsum”, forming the HTN-PRS. The HTN-PRS is associated with both prevalent and incident hypertension at 4-6 years of follow up. This association is further confirmed in age-stratified analysis. In an independent biobank of 40,201 individuals, the HTN-PRS is confirmed to be predictive of increased risk for coronary artery disease, ischemic stroke, type 2 diabetes, and chronic kidney disease. Polygenic risk scores have potential to predict an individual’s risk of disease based on genetic markers. Here, the authors develop a polygenic risk score for hypertension and test it in a multi-ethnic cohort, finding that the score is associated with higher likelihood of hypertension development 4-6 years later.

Integrated microbiome and metabolomics analyses hold the potential to reveal interactions between host and microbiota in relation to disease risks. However, there are few studies evaluating how field methods influence fecal microbiome characterization and metabolomics profiling. Five fecal collection methods [immediate freezing at -20°C without preservative, OMNIgene GUT, 95% ethanol, RNA , and Flinders Technology Associates (FTA) cards] were used to collect 40 fecal samples from eight healthy volunteers. We performed gut microbiota 16S rRNA sequencing, untargeted metabolomics profiling, and targeted metabolomics focusing on short chained fatty acids (SCFAs). Metrics included α-diversity and β-diversity as well as distributions of predominant phyla. To evaluate the concordance with the \"gold standard\" immediate freezing, the intraclass correlation coefficients (ICCs) for alternate fecal collection systems were calculated. Correlations between SCFAs and gut microbiota were also examined. The FTA cards had the highest ICCs compared to the immediate freezing method for α-diversity indices (ICCs = 0.96, 0.96, 0.76 for Shannon index, Simpson's Index, Chao-1 Index, respectively), followed by OMNIgene GUT, RNA , and 95% ethanol. High ICCs (all >0.88) were observed for all methods for the β-diversity metric. For untargeted metabolomics, in comparison to immediate freezing which detected 621 metabolites at ≥75% detectability level, 95% ethanol showed the largest overlapping set of metabolites ( = 430; 69.2%), followed by FTA cards ( = 330; 53.1%) and OMNIgene GUT ( = 213; 34.3%). Both OMNIgene GUT (ICCs = 0.82, 0.93, 0.64) and FTA cards (ICCs = 0.87, 0.85, 0.54) had acceptable ICCs for the top three predominant SCFAs (butyric acid, propionic acid and acetic acid). Nominally significant correlations between bacterial genera and SCFAs ( < 0.05) were observed in fecal samples collected by different methods. Of note, a high correlation between the genus (known butyrate producer) and butyric acid was observed for both immediate freezing ( = 0.83) and FTA cards ( = 0.74). Four alternative fecal collection methods are generally comparable with immediate freezing, but there are differences in certain measures of the gut microbiome and fecal metabolome across methods. Choice of method depends on the research interests, simplicity of fecal collection procedures and ease of transportation to the lab, especially for large epidemiological studies.

We assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare “clumping-and-thresholding” (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals. Here, the authors assess performance and limitations to polygenic risk scores in different race/ethnic groups. They find that polygenic risk score performance improves with diverse training data, and a better understanding of varying genetic backgrounds, social and environmental factors, and gene-environment interactions, is needed to enhance PRS performance for all groups.

Aims/hypothesisWe aimed to evaluate associations of multiple recommended dietary patterns (i.e. the alternate Mediterranean diet [aMED], the Healthy Eating Index [HEI]-2015 and the healthful Plant-based Diet Index [hPDI]) with serum metabolite profile, and to examine dietary-pattern-associated metabolites in relation to incident diabetes.MethodsWe included 2842 adult participants free from diabetes, CVD and cancer during baseline recruitment of the Hispanic Community Health Study/Study of Latinos. Metabolomics profiling of fasting serum was performed using an untargeted approach. Dietary pattern scores were derived using information collected by two 24 h dietary recalls. Dietary-pattern-associated metabolites were identified using multivariable survey linear regressions and their associations with incident diabetes were assessed using multivariable survey Poisson regressions with adjustment for traditional risk factors.ResultsWe identified eight metabolites (mannose, γ/β-tocopherol, N1-methylinosine, pyrraline and four amino acids) that were inversely associated with all dietary scores. These metabolites were detrimentally associated with various cardiometabolic risk traits, especially insulin resistance. A score comprised of these metabolites was associated with elevated risk of diabetes (RRper SD 1.54 [95% CI 1.29, 1.83]), and this detrimental association appeared to be attenuated or eliminated by having a higher score for aMED (pinteraction = 0.0001), HEI-2015 (pinteraction = 0.020) or hPDI (pinteraction = 0.023). For example, RR (95% CI) of diabetes for each SD increment in the metabolite score was 1.99 (1.44, 2.37), 1.67 (1.17, 2.38) and 1.08 (0.86, 1.34) across the lowest to the highest tertile of aMED score, respectively.Conclusions/interpretationVarious recommended dietary patterns were inversely related to a group of metabolites that were associated with elevated risk of diabetes. Adhering to a healthful eating pattern may attenuate or eliminate the detrimental association between metabolically unhealthy serum metabolites and risk of diabetes.

Asthma is a heterogeneous condition that is often comorbid with obesity and influenced by diverse risk factors. Elucidating the association of gut microbial characteristics with asthma could improve our understanding of the pathophysiology. Here, we investigate relationships of host genetics and stool microbiota characteristics with asthma among US Hispanic/Latino adults, while considering the influence of obesity status, using host whole genome sequencing and stool shotgun metagenomic microbiota data from participants of the Hispanic Community Health Study/Study of Latinos. We evaluate cross-sectional associations of microbiota characteristics with asthma and analyse whether they are modified by obesity status (body mass index≥30 kg/m 2 ). We assess differences in alpha diversity, beta diversity, and taxonomic abundance with asthma, independent of obesity, and interactions between asthma and obesity using covariate-adjusted regression-based methods. We generate an asthma polygenic risk score (PRS) and compare the classification accuracy of genetic and microbial factors for asthma status. We report that asthma is associated with differences in overall taxonomic composition (beta diversity; p = 0.001), which is not dependent on obesity status (p = 0.31). Asthma is not associated with alpha diversity metrics (p > 0.17), though obesity is associated with lower alpha diversity (p < 0.01). We identify multiple taxa that are associated with asthma, including decreased abundance of Lactobacillus and Enterococcus species, and some taxonomic associations vary by obesity status. Compared to models including baseline risk factors and an asthma PRS, microbial information improves classification accuracy of asthma (p = 0.04). Our results support that there are microbiota characteristics associated with asthma in Hispanic/Latino adults independent of obesity. The host microbiome may influence asthma susceptibility differently across diverse geographic or ethnic populations. Here the authors perform a microbiome study of asthma in US Hispanic/Latino adults and evaluate the influence of obesity and genetic factors on the relationship between microbiome characteristics and asthma.

The menopausal transition, marked by declining ovarian hormones, is recognized as a pivotal period of cardiometabolic risk. Gut microbiota metabolically interact with sex hormones, but large population studies associating menopause with the gut microbiome are lacking. Menopause is a pivotal period during which loss of ovarian hormones increases cardiometabolic risk and may also influence the gut microbiome. However, the menopause-microbiome relationship has not been examined in a large study, and its implications for cardiometabolic disease are unknown. In the Hispanic Community Health Study/Study of Latinos, a population with high burden of cardiometabolic risk factors, shotgun metagenomic sequencing was performed on stool from 2,300 participants (295 premenopausal women, 1,027 postmenopausal women, and 978 men), and serum metabolomics was available on a subset. Postmenopausal women trended toward lower gut microbiome diversity and altered overall composition compared to premenopausal women, while differing less from men, in models adjusted for age and other demographic/behavioral covariates. Differentially abundant taxa for post- versus premenopausal women included Bacteroides sp. strain Ga6A1 , Prevotella marshii , and Sutterella wadsworthensis (enriched in postmenopause) and Escherichia coli -Shigella spp., Oscillibacter sp. strain KLE1745 , Akkermansia muciniphila , Clostridium lactatifermentans , Parabacteroides johnsonii , and Veillonella seminalis (depleted in postmenopause); these taxa similarly differed between men and women. Postmenopausal women had higher abundance of the microbial sulfate transport system and decreased abundance of microbial β-glucuronidase; these functions correlated with serum progestin metabolites, suggesting involvement of postmenopausal gut microbes in sex hormone retention. In postmenopausal women, menopause-related microbiome alterations were associated with adverse cardiometabolic profiles. In summary, in a large U.S. Hispanic/Latino population, menopause is associated with a gut microbiome more similar to that of men, perhaps related to the common condition of a low estrogen/progesterone state. Future work should examine similarity of results in other racial/ethnic groups. IMPORTANCE The menopausal transition, marked by declining ovarian hormones, is recognized as a pivotal period of cardiometabolic risk. Gut microbiota metabolically interact with sex hormones, but large population studies associating menopause with the gut microbiome are lacking. Our results from a large study of Hispanic/Latino women and men suggest that the postmenopausal gut microbiome in women is slightly more similar to the gut microbiome in men and that menopause depletes specific gut pathogens and decreases the hormone-related metabolic potential of the gut microbiome. At the same time, gut microbes may participate in sex hormone reactivation and retention in postmenopausal women. Menopause-related gut microbiome changes were associated with adverse cardiometabolic risk in postmenopausal women, indicating that the gut microbiome contributes to changes in cardiometabolic health during menopause.

Purpose of Review To synthesize recent evidence relating the gut microbiome and microbial metabolites to cardiovascular disease (CVD) in people living with HIV (PLWH). Recent Findings A few cross-sectional studies have reported on the gut microbiome and cardiovascular outcomes in the context of HIV, with no consistent patterns emerging. The largest such study found that gut Fusobacterium was associated with carotid artery plaque. More studies have evaluated microbial metabolite trimethylamine N-oxide with CVD risk in PLWH, but results were inconsistent, with recent prospective analyses showing null effects. Studies of other microbial metabolites are scarce. Microbial translocation biomarkers (e.g., lipopolysaccharide binding protein) have been related to incident CVD in PLWH. Summary Microbial translocation may increase CVD risk in PLWH, but there is insufficient and/or inconsistent evidence regarding specific microbial species and microbial metabolites associated with cardiovascular outcomes in PLWH. Further research is needed in large prospective studies integrating the gut microbiome, microbial translocation, and microbial metabolites with cardiovascular outcomes in PLWH.