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 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.

Dietary quality and dietary greenhouse gas emissions in the USA: a comparison of the planetary health diet index, healthy eating index-2015, and dietary approaches to stop hypertension.

BACKGROUND: The Planetary Health Diet Index (PHDI) measures adherence to the dietary pattern presented by the EAT-Lancet Commission, which aligns health and sustainability targets. There is a need to understand how PHDI scores correlate with dietary greenhouse gas emissions (GHGE) and how this differs from the carbon footprints of scores on established dietary recommendations. The objectives of this study were to compare how the PHDI, Healthy Eating Index-2015 (HEI-2015) and Dietary Approaches to Stop Hypertension (DASH) relate to (a) dietary GHGE and (b) to examine the influence of PHDI food components on dietary GHGE. METHODS: We used life cycle assessment data from the Database of Food Recall Impacts on the Environment for Nutrition and Dietary Studies to calculate the mean dietary GHGE of 8,128 adult participants in the 2015-2016 and 2017-2018 cycles of the National Health and Nutrition Examination Survey (NHANES). Poisson regression was used to estimate the association of (a) quintiles of diet score and (b) standardized dietary index Z-scores with dietary GHGE for PHDI, HEI-2015, and DASH scores. In secondary analyses, we used Poisson regression to assess the influence of individual PHDI component scores on dietary GHGE. RESULTS: We found that higher dietary quality on all three indices was correlated with lower dietary GHGE. The magnitude of the dietary quality-dietary GHGE relationship was larger for PHDI [-0.4, 95% CI (-0.5, -0.3) kg CO2 equivalents per one standard deviation change] and for DASH [-0.5, (-0.4, -0.6) kg CO2-equivalents] than for HEI-2015 [-0.2, (-0.2, -0.3) kg CO2-equivalents]. When examining PHDI component scores, we found that diet-related GHGE were driven largely by red and processed meat intake. CONCLUSIONS: Improved dietary quality has the potential to lower the emissions impacts of US diets. Future efforts to promote healthy, sustainable diets could apply the recommendations of the established DASH guidelines as well as the new guidance provided by the PHDI to increase their environmental benefits.

Adherence to the Planetary Health Diet Index and correlation with nutrients of public health concern: an analysis of NHANES 2003-2018.

BACKGROUND: The Planetary Health Diet Index (PHDI) is a novel measure adapted to quantify alignment with the dietary evidence presented by the EAT-Lancet Commission on Food, Planet, Health. OBJECTIVES: To examine how population-level health and sustainability of diet as measured by the PHDI changed from 2003 to 2018, and to assess how PHDI correlated with inadequacy for nutrients of public health concern (iron, calcium, potassium, and fiber) in the United States. METHODS: We estimated survey-weighted trends in PHDI scores and median intake of PHDI components in a nationally representative sample of 33,859 adults aged 20+ y from 8 cycles (2003-2018) of the National Health and Nutrition Examination Survey with 2 d of dietary recall data. We used the National Cancer Institute method to examine how PHDI correlated with inadequate intake of iron, calcium, potassium, and fiber. RESULTS: Out of a theoretical range of 0-140, the median PHDI value increased by 4.2 points over the study period, from 62.7 (95% confidence interval [CI]: 62.0, 63.4) points in 2003-2004 to 66.9 (66.2, 67.7) points in 2017-2018 (P-trend < 0.001), although most of this change occurred before 2011-2012 and plateaued thereafter. For adequacy components that are encouraged for consumption, nonstarchy vegetable intake significantly decreased over time, whereas whole grains, nuts and seeds, and unsaturated oils increased. For moderation components with recommended limits for consumption, poultry and egg intake increased, but red and processed meat, added sugars, saturated fats, and starchy vegetables decreased over time. Higher PHDI values were associated with a lower probability of iron, fiber, and potassium inadequacy. CONCLUSIONS: Although there have been positive changes over the past 20 y, there is substantial room for improving the health and sustainability of the United States diet. Shifting diets toward EAT-Lancet recommendations would improve nutrient adequacy for iron, fiber, and potassium. Policy action is needed to support healthier, more sustainable diets in the United States and globally.

Dietary quality and cardiometabolic indicators in the USA: A comparison of the Planetary Health Diet Index, Healthy Eating Index-2015, and Dietary Approaches to Stop Hypertension.

BACKGROUND: The Planetary Health Diet Index (PHDI) measures adherence to the sustainable dietary guidance proposed by the EAT-Lancet Commission on Food, Planet, Health. To justify incorporating sustainable dietary guidance such as the PHDI in the US, the index needs to be compared to health-focused dietary recommendations already in use. The objectives of this study were to compare the how the Planetary Health Diet Index (PHDI), the Healthy Eating Index-2015 (HEI-2015) and Dietary Approaches to Stop Hypertension (DASH) relate to cardiometabolic risk factors. METHODS AND FINDINGS: Participants from the National Health and Nutrition Examination Survey (2015-2018) were assigned a score for each dietary index. We examined disparities in dietary quality for each index. We used linear and logistic regression to assess the association of standardized dietary index values with waist circumference, blood pressure, HDL-C, fasting plasma glucose (FPG) and triglycerides (TG). We also dichotomized the cardiometabolic indicators using the cutoffs for the Metabolic Syndrome and used logistic regression to assess the relationship of the standardized dietary index values with binary cardiometabolic risk factors. We observed diet quality disparities for populations that were Black, Hispanic, low-income, and low-education. Higher diet quality was associated with improved continuous and binary cardiometabolic risk factors, although higher PHDI was not associated with high FPG and was the only index associated with lower TG. These patterns remained consistent in sensitivity analyses. CONCLUSIONS: Sustainability-focused dietary recommendations such as the PHDI have similar cross-sectional associations with cardiometabolic risk as HEI-2015 or DASH. Health-focused dietary guidelines such as the forthcoming 2025-2030 Dietary Guidelines for Americans can consider the environmental impact of diet and still promote cardiometabolic health.

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.

The association between the Mediterranean Diet Score and death from cancer of the head and neck.

PURPOSE: The association between diet quality, captured by the Mediterranean Diet Score (MDS), and mortality was studied among 1184 individuals diagnosed with head and neck cancer (HNC) who reflected on the year preceding diagnosis about their usual diet using National Cancer Institute's Diet History Questionnaire (DHQ). METHODS: Intakes of nine dietary components were scored and summed to construct the MDS (sample: median = 4; range (0-9); lower MDS reflected poorer diet quality; 5-year survival probability = 0.62). Cox regression estimated 5-year hazard ratios (HR) and 95% confidence intervals (95CI) for all-cause mortality and for HNC-specific death for contrasts of MDS quintiles. Effect measure modification (EMM) by tumor features [human papillomavirus (HPV) positivity; anatomic site] and sociodemographic behavioral factors [race, body mass index (BMI), smoking, alcohol consumption] was explored. RESULTS: The 5-year [HR (95CI); P-trend] for all-cause mortality and HNC-specific mortality for highest versus lowest MDS quintile contrasts were [0.51 (0.33, 0.80); 0.014] and [0.43 (0.22, 0.85); 0.004], respectively. A unit increase in MDS adherence resulted in a 15% reduction of the 5-year HR for HNC-specific death for tumors located at the oral cavity [HR (95CI): 0.85 (0.75, 0.96)]. Poor diet quality (MDS ≤ 4) interacted with lower BMI (kg/m2 < 25) and separately with ever-using alcohol to produce 5-year HRs for all-cause and HNC-specific mortality that were statistically significantly larger than the sum of the individual HRs representing each combination (Poor diet quality + lower BMI; Poor diet quality + ever-using alcohol). CONCLUSION: Greater adherence to a Mediterranean diet pattern prior to HNC diagnosis may reduce post-diagnosis mortality.

A Scoping Review of Diagnosis of Autism Spectrum Disorder in Primary Care.

INTRODUCTION: This scoping review was performed to collect, examine, and present literature on interventions promoting the diagnosis of Autism Spectrum Disorder (ASD) in U.S. primary health care settings. METHOD: The literature searched was from 2011-2022, in the English language, in PubMed, CINAHL, Psych INFO, Cochrane, and Web of Science, for persons with autism or ASD aged ≤ 18 years. RESULTS: Six studies met the search criteria, including a quality improvement project, a feasibility study, a pilot study, and three primary care provider (PCP) intervention trials. Measured outcomes included: accuracy of diagnosis (n = 4), practice change maintenance (n = 3), time to diagnosis (n = 2), specialty clinic appointment wait time (n = 1), PCP comfort making ASD diagnosis (n = 1), and increased ASD diagnosis (n = 1). DISCUSSION: Results inform future implementation of PCP ASD diagnosis for the most obvious cases of ASD and research evaluating PCP training, using longitudinal measures of PCP knowledge of ASD and intention to diagnose.

Conjugated bile acids are nutritionally re-programmable antihypertensive metabolites.

BACKGROUND: Hypertension is the largest risk factor affecting global mortality. Despite available medications, uncontrolled hypertension is on the rise, whereby there is an urgent need to develop novel and sustainable therapeutics. Because gut microbiota is now recognized as an important entity in blood pressure regulation, one such new avenue is to target the gut-liver axis wherein metabolites are transacted via host-microbiota interactions. Knowledge on which metabolites within the gut-liver axis regulate blood pressure is largely unknown. METHOD: To address this, we analyzed bile acid profiles of human, hypertensive and germ-free rat models and report that conjugated bile acids are inversely correlated with blood pressure in humans and rats. RESULTS: Notably intervening with taurine or tauro-cholic acid rescued bile acid conjugation and reduced blood pressure in hypertensive rats. Subsequently, untargeted metabolomics uncovered altered energy metabolism following conjugation of bile acids as a mechanism alleviating high blood pressure. CONCLUSION: Together this work reveals conjugated bile acids as nutritionally re-programmable anti-hypertensive metabolites.

Cultivating COVID-19 Vaccine Confidence in Pharmacy Professionals.

Pharmacists promote vaccinations and challenge misconceptions about vaccine hesitancy, yet pharmacists' knowledge of vaccine confidence has not been assessed. The objective of this study was to compare pharmacists' knowledge of coronavirus disease 2019 (COVID-19) vaccine confidence before and after a live continuing education (CE) session. This pretest-posttest study evaluated the differences before and after a live CE session on COVID-19 vaccine confidence provided to pharmacists at a nationwide health technology company. Participants' total pretest and posttest scores were compared using paired t-tests, while pretest and posttest scores for each item were compared using chi-squared tests. A Bonferroni correction was applied, resulting in an alpha level of 0.005. A total of 279 pharmacists participated in this study. After the CE session, mean knowledge scores increased (5.2 ± 1.5 to 7.4 ± 1.35, p < 0.0001). After the CE session, there was no significant increase in pharmacists' knowledge about the approach that is not recommended when discussing vaccination beliefs with a patient (71.3% to 77.4%, p = 0.099), determinants of vaccine uptake (83.9% to 87.8%, p = 0.182), and social determinants of health that can influence vaccination rates (93.6% to 96.4%, p = 0.121). There was a significant change in pre- and posttest knowledge for the remaining seven items.

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.

Gut microbiome and stages of diabetes in middle-aged adults: CARDIA microbiome study.

BACKGROUND: Animal and human studies suggest the gut microbiome is linked to diabetes but additional data are needed on the associations of the gut microbiome to specific diabetes characteristics. The aim of this study was to examine the associations of gut microbiome composition to insulin resistance [Homeostatic Model Assessment of Insulin Resistance (HOMA-IR)], duration of diabetes, and 4 stages of diabetes [normoglycemia, pre-diabetes, and diabetes with (+) and without (-) medication for diabetes]. METHODS: Data are from a sub-sample (n = 605) of Black and White participants from the 30-year follow-up exam of the prospectively followed community-based Coronary Artery Risk Development in Young Adults cohort (2015-2016; aged 48-60 years). Stool samples were collected and sequenced using the 16S ribosomal RNA method. Microbial measures included: α diversity (within-person), ß diversity (between-person), and taxonomies. All analyses were adjusted for demographic, clinical, lifestyle factors, and use of relevant medications (full adjustment). Multivariate linear regression models were used to assess the association of diabetes characteristics with α diversity and genera abundance, while the association with ß diversity was analyzed using permutational multivariate analysis of variance. Statistical significance was set to p-value < 0.05 for α and ß diversity analyses and to q-value < 0.1 for genera abundance analyses. RESULTS: There were 16.7% of participants with pre-diabetes, and 14.4% with diabetes (9% diabetes+) with median (interquartile range) diabetes duration of 5 (5-10) years. In the fully adjusted models, compared to those with no diabetes, longer diabetes duration and the diabetes + group had a lower α diversity. There were significant differences in ß diversity across diabetes-related characteristics. A significantly reduced abundance of butyrate-producing genera was associated with higher HOMA-IR (ex., Anaerostipes and Lachnospiraceae_UCG.004), longer diabetes duration (ex., Agathobacter and Ruminococcus), and diabetes + (ex., Faecalibacterium and Romboutsia). CONCLUSIONS: Our results suggest that an adverse alteration of gut microbiome composition is related to higher insulin resistance, longer diabetes duration, and is present in those persons with diabetes using medications. These diabetes-related characteristics were also associated with lower levels of certain butyrate-producing bacteria that produce health-promoting short-chain fatty acids. Understanding the role of gut microbiota in glucose regulation may provide new strategies to reduce the burden of diabetes.

Dietary metabolic signatures and cardiometabolic risk.

AIMS: Observational studies of diet in cardiometabolic-cardiovascular disease (CM-CVD) focus on self-reported consumption of food or dietary pattern, with limited information on individual metabolic responses to dietary intake linked to CM-CVD. Here, machine learning approaches were used to identify individual metabolic patterns related to diet and relation to long-term CM-CVD in early adulthood. METHODS AND RESULTS: In 2259 White and Black adults (age 32.1 ± 3.6 years, 45% women, 44% Black) in the Coronary Artery Risk Development in Young Adults (CARDIA) study, multivariate models were employed to identify metabolite signatures of food group and composite dietary intake across 17 food groups, 2 nutrient groups, and healthy eating index-2015 (HEI2015) diet quality score. A broad array of metabolites associated with diet were uncovered, reflecting food-related components/catabolites (e.g. fish and long-chain unsaturated triacylglycerols), interactions with host features (microbiome), or pathways broadly implicated in CM-CVD (e.g. ceramide/sphingomyelin lipid metabolism). To integrate diet with metabolism, penalized machine learning models were used to define a metabolite signature linked to a putative CM-CVD-adverse diet (e.g. high in red/processed meat, refined grains), which was subsequently associated with long-term diabetes and CVD risk numerically more strongly than HEI2015 in CARDIA [e.g. diabetes: standardized hazard ratio (HR): 1.62, 95% confidence interval (CI): 1.32-1.97, P < 0.0001; CVD: HR: 1.55, 95% CI: 1.12-2.14, P = 0.008], with associations replicated for diabetes (P < 0.0001) in the Framingham Heart Study. CONCLUSION: Metabolic signatures of diet are associated with long-term CM-CVD independent of lifestyle and traditional risk factors. Metabolomics improves precision to identify adverse consequences and pathways of diet-related CM-CVD.

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.

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.

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.

Association of the Gut Microbiota With Cognitive Function in Midlife.

Importance: Animal experiments and small clinical studies support a role for the gut microbiota in cognitive functioning. Few studies have investigated gut microbiota and cognition in large community samples. Objective: To examine associations of gut microbial composition with measures of cognition in an established population-based study of middle-aged adults. Design, Setting, and Participants: This cross-sectional study analyzed data from the prospective Coronary Artery Risk Development in Young Adults (CARDIA) cohort in 4 US metropolitan centers between 2015 and 2016. Data were analyzed in 2019 and 2020. Exposures: Stool DNA were sequenced, and the following gut microbial measures were gathered: (1) ß-diversity (between-person) derived with multivariate principal coordinates analysis; (2) α-diversity (within-person), defined as richness (genera count) and the Shannon index (integrative measure of genera richness and evenness); and (3) taxonomy (107 genera, after filtering). Main Outcomes and Measures: Cognitive status was assessed using 6 clinic-administered cognitive tests: Montreal Cognitive Assessment (MoCA), Digit Symbol Substitution Test (DSST), Rey-Auditory Verbal Learning Test (RAVLT), Stroop, category fluency, and letter fluency. A global score measure derived using principal components analysis was also assessed; the first principal component explained 56% of variability. Results: Microbiome data were available on 597 CARDIA participants; mean (SD) age was 55.2 (3.5) years, 268 participants (44.7%) were men, and 270 (45.2%) were Black. In multivariable-adjusted principal coordinates analysis, permutational multivariate analysis of variance tests for ß-diversity were statistically significant for all cognition measures (principal component analysis, P = .001; MoCA, P = .001; DSST, P = .001; RAVLT, P = .001; Stroop, P = .007; category fluency, P = .001) with the exception of letter fluency (P = .07). After adjusting for sociodemographic variables (age, race, sex, education), health behaviors (physical activity, diet, smoking, medication use), and clinical covariates (body mass index, diabetes, hypertension), Barnesiella was positively associated with the first principal component (ß, 0.16; 95% CI, 0.08-0.24), DSST (ß, 1.18; 95% CI, 0.35-2.00), and category fluency (ß, 0.59; 95% CI, 0.31-0.87); Lachnospiraceae FCS020 group was positively associated with DSST (ß, 2.67; 95% CI, 1.10-4.23), and Sutterella was negatively associated with MoCA (ß, -0.27; 95% CI, -0.44 to -0.11). Conclusions and Relevance: In this cross-sectional study, microbial community composition, based on ß-diversity, was associated with all cognitive measures in multivariable-adjusted analysis. These data contribute to a growing body of literature suggesting that the gut microbiota may be associated with cognitive aging, but must be replicated in larger samples and further researched to identify relevant pathways.

The prospective association between periodontal disease and brain imaging outcomes: The Atherosclerosis Risk in Communities study.

AIM: We investigate if periodontal disease is prospectively associated with cerebrovascular and neurodegenerative markers of dementia and Alzheimer's pathology. MATERIALS AND METHODS: N = 1306 participants (Visit 5 mean age = 76.5 [standard deviation = 5.4] years) in the Atherosclerosis Risk in Communities study with completed dental exams at Visit 4 underwent brain magnetic resonance imaging scans at Visit 5 while N = 248 underwent positron emission tomography scans. Participants were classified as edentulous or, among the dentate, by the modified Periodontal Profile Class. Brain volumes were regressed on periodontal status in linear regressions. Cerebrovascular measures and ß-amyloid positivity were regressed on periodontal status in logistic regressions. RESULTS: Periodontal disease was not associated with brain volumes, microhaemorrhages, or elevated ß-amyloid. Compared with periodontally healthy individuals, odds ratios [95% confidence interval] for all-type infarcts were 0.37 [0.20, 0.65] for severe tooth loss and 0.56 [0.31, 0.99] for edentulous participants. CONCLUSIONS: Within the limitations of this study, periodontal disease was not associated with altered brain volumes, microhaemorrhages, or ß-amyloid positivity. Tooth loss was associated with lower odds of cerebral infarcts.

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.