Faculty Bibliography

Lower socioeconomic status (SES) is related to increased incidence and mortality due to chronic diseases in adults. Association between SES variables and gut microbiome variation has been observed in adults at the population level, suggesting that biological mechanisms may underlie the SES associations; however, there is a need for larger studies that consider individual- and neighborhood-level measures of SES in racially diverse populations. In 825 participants from a multi-ethnic cohort, we investigated how SES shapes the gut microbiome. We determined the relationship of a range of individual- and neighborhood-level SES indicators with the gut microbiome. Individual education level and occupation were self-reported by questionnaire. Geocoding was applied to link participants' addresses with neighborhood census tract socioeconomic indicators, including average income and social deprivation in the census tract. Gut microbiome was measured using 16SV4 region rRNA gene sequencing of stool samples. We compared α-diversity, β-diversity, and taxonomic and functional pathway abundance by SES. Lower SES was significantly associated with greater α-diversity and compositional differences among groups, as measured by β-diversity. Several taxa related to low SES were identified, especially an increasing abundance of Prevotella copri and Catenibacterium sp000437715, and decreasing abundance of Dysosmobacter welbionis in terms of their high log-fold change differences. In addition, nativity and race/ethnicity have emerged as ecosocial factors that also influence the gut microbiota. Together, these results showed that lower SES was strongly associated with compositional and taxonomic measures of the gut microbiome, and may contribute to shaping the gut microbiota.

In this article, we present a flexible model for microbiome count data. We consider a quasi-likelihood framework, in which we do not make any assumptions on the distribution of the microbiome count except that its variance is an unknown but smooth function of the mean. By comparing our model to the negative binomial generalized linear model (GLM) and Poisson GLM in simulation studies, we show that our flexible quasi-likelihood method yields valid inferential results. Using a real microbiome study, we demonstrate the utility of our method by examining the relationship between adenomas and microbiota. We also provide an R package "fql" for the application of our method.

Inter-organelle contact and communication between mitochondria and sarco/endoplasmic reticulum (SR/ER) maintain cellular homeostasis and are profoundly disturbed during tissue ischemia. We tested the hypothesis that the formin Diaphanous-1 (DIAPH1), which regulates actin dynamics, signal transduction and metabolic functions, contributes to these processes. We demonstrate that DIAPH1 interacts directly with Mitofusin-2 (MFN2) to shorten mitochondria-SR/ER distance, thereby enhancing mitochondria-ER contact in cells including cardiomyocytes, endothelial cells and macrophages. Solution structure studies affirm the interaction between the Diaphanous Inhibitory Domain and the cytosolic GTPase domain of MFN2. In male rodent and human cardiomyocytes, DIAPH1-MFN2 interaction regulates mitochondrial turnover, mitophagy, and oxidative stress. Introduction of synthetic linker construct, which shorten the mitochondria-SR/ER distance, mitigated the molecular and functional benefits of DIAPH1 silencing in ischemia. This work establishes fundamental roles for DIAPH1-MFN2 interaction in the regulation of mitochondria-SR/ER contact networks. We propose that targeting pathways that regulate DIAPH1-MFN2 interactions may facilitate recovery from tissue ischemia.

BACKGROUND:Recent studies have demonstrated considerable interindividual variability in postprandial glucose response (PPGR) to the same foods, suggesting the need for more precise methods for predicting and controlling PPGR. In the Personal Nutrition Project, the investigators tested a precision nutrition algorithm for predicting an individual's PPGR. OBJECTIVE:This study aimed to compare changes in glycemic variability (GV) and HbA1c in 2 calorie-restricted weight loss diets in adults with prediabetes or moderately controlled type 2 diabetes (T2D), which were tertiary outcomes of the Personal Diet Study. METHODS:The Personal Diet Study was a randomized clinical trial to compare a 1-size-fits-all low-fat diet (hereafter, standardized) with a personalized diet (hereafter, personalized). Both groups received behavioral weight loss counseling and were instructed to self-monitor diets using a smartphone application. The personalized arm received personalized feedback through the application to reduce their PPGR. Continuous glucose monitoring (CGM) data were collected at baseline, 3 mo and 6 mo. Changes in mean amplitude of glycemic excursions (MAGEs) and HbA1c at 6 mo were assessed. We performed an intention-to-treat analysis using linear mixed regressions. RESULTS:We included 156 participants [66.5% women, 55.7% White, 24.1% Black, mean age 59.1 y (standard deviation (SD) = 10.7 y)] in these analyses (standardized = 75, personalized = 81). MAGE decreased by 0.83 mg/dL per month for standardized (95% CI: 0.21, 1.46 mg/dL; P = 0.009) and 0.79 mg/dL per month for personalized (95% CI: 0.19, 1.39 mg/dL; P = 0.010) diet, with no between-group differences (P = 0.92). Trends were similar for HbA1c values. CONCLUSIONS:Personalized diet did not result in an increased reduction in GV or HbA1c in patients with prediabetes and moderately controlled T2D, compared with a standardized diet. Additional subgroup analyses may help to identify patients who are more likely to benefit from this personalized intervention. This trial was registered at clinicaltrials.gov as NCT03336411.

BACKGROUND:Emerging evidence suggests the potential mediating role of microbiome in health disparities. However, no analytic framework can be directly used to analyze microbiome as a mediator between health disparity and clinical outcome, due to the non-manipulable nature of the exposure and the unique structure of microbiome data, including high dimensionality, sparsity, and compositionality. METHODS:Considering the modifiable and quantitative features of the microbiome, we propose a microbial causal mediation model framework, SparseMCMM_HD, to uncover the mediating role of microbiome in health disparities, by depicting a plausible path from a non-manipulable exposure (e.g., ethnicity or region) to the outcome through the microbiome. The proposed SparseMCMM_HD rigorously defines and quantifies the manipulable disparity measure that would be eliminated by equalizing microbiome profiles between comparison and reference groups and innovatively and successfully extends the existing microbial mediation methods, which are originally proposed under potential outcome or counterfactual outcome study design, to address health disparities. RESULTS:Through three body mass index (BMI) studies selected from the curatedMetagenomicData 3.4.2 package and the American gut project: China vs. USA, China vs. UK, and Asian or Pacific Islander (API) vs. Caucasian, we exhibit the utility of the proposed SparseMCMM_HD framework for investigating the microbiome's contributions in health disparities. Specifically, BMI exhibits disparities and microbial community diversities are significantly distinctive between reference and comparison groups in all three applications. By employing SparseMCMM_HD, we illustrate that microbiome plays a crucial role in explaining the disparities in BMI between ethnicities or regions. 20.63%, 33.09%, and 25.71% of the overall disparity in BMI in China-USA, China-UK, and API-Caucasian comparisons, respectively, would be eliminated if the between-group microbiome profiles were equalized; and 15, 18, and 16 species are identified to play the mediating role respectively. CONCLUSIONS:The proposed SparseMCMM_HD is an effective and validated tool to elucidate the mediating role of microbiome in health disparity. Three BMI applications shed light on the utility of microbiome in reducing BMI disparity by manipulating microbial profiles. Video Abstract.

OBJECTIVE:Optimal body mass and composition as well as metabolic fitness require tightly regulated and interconnected mechanisms across tissues. Disturbances in these regulatory networks tip the balance between metabolic health versus overweight and obesity and their complications. The authors previously demonstrated roles for the receptor for advanced glycation end products (RAGE) in obesity, as global- or adipocyte-specific deletion of Ager (the gene encoding RAGE) protected mice from high-fat diet-induced obesity and metabolic dysfunction. METHODS:To explore translational strategies evoked by these observations, a small molecule antagonist of RAGE signaling, RAGE229, was administered to lean mice and mice with obesity undergoing diet-induced weight loss. Body mass and composition and whole body and adipose tissue metabolism were examined. RESULTS:This study demonstrates that antagonism of RAGE signaling reduced body mass and adiposity and improved glucose, insulin, and lipid metabolism in lean male and female mice and in male mice with obesity undergoing weight loss. In adipose tissue and in human and mouse adipocytes, RAGE229 enhanced phosphorylation of protein kinase A substrates, which augmented lipolysis, mitochondrial function, and thermogenic programs. CONCLUSIONS:Pharmacological antagonism of RAGE signaling is a potent strategy to optimize healthful body mass and composition and metabolic fitness.

MOTIVATION/BACKGROUND:As the resolution of metagenomic analysis increases, the evolution of microbial genomes in longitudinal metagenomic data has become a research focus. Some software has been developed for the simulation of complex microbial communities at the strain level. However, the tool for simulating within-strain evolutionary signals in longitudinal samples is still lacking. RESULTS:In this study, we introduce STEMSIM, a user-friendly command-line simulator of short-term evolutionary mutations for longitudinal metagenomic data. The input is simulated longitudinal raw sequencing reads of microbial communities or single species. The output is the modified reads with within-strain evolutionary mutations and the relevant information of these mutations. STEMSIM will be of great use for the evaluation of analytic tools that detect short-term evolutionary mutations in metagenomic data. AVAILABILITY/BACKGROUND:STEMSIM and its tutorial are freely available online at https://github.com/BoyanZhou/STEMSim. SUPPLEMENTARY INFORMATION/BACKGROUND:Supplementary data are available at Bioinformatics online.

Atherosclerosis evolves through dysregulated lipid metabolism interwoven with exaggerated inflammation. Previous work implicating the receptor for advanced glycation end products (RAGE) in atherosclerosis prompted us to explore if Diaphanous 1 (DIAPH1), which binds to the RAGE cytoplasmic domain and is important for RAGE signaling, contributes to these processes. We intercrossed atherosclerosis-prone Ldlr^-/- mice with mice devoid of Diaph1 and fed them Western diet for 16 weeks. Compared to male Ldlr^-/- mice, male Ldlr^-/- Diaph1^-/- mice displayed significantly less atherosclerosis, in parallel with lower plasma concentrations of cholesterol and triglycerides. Female Ldlr^-/- Diaph1^-/- mice displayed significantly less atherosclerosis compared to Ldlr^-/- mice and demonstrated lower plasma concentrations of cholesterol, but not plasma triglycerides. Deletion of Diaph1 attenuated expression of genes regulating hepatic lipid metabolism, Acaca, Acacb, Gpat2, Lpin1, Lpin2 and Fasn, without effect on mRNA expression of upstream transcription factors Srebf1, Srebf2 or Mxlipl in male mice. We traced DIAPH1-dependent mechanisms to nuclear translocation of SREBP1 in a manner independent of carbohydrate- or insulin-regulated cues but, at least in part, through the actin cytoskeleton. This work unveils new regulators of atherosclerosis and lipid metabolism through DIAPH1.

OBJECTIVES/OBJECTIVE:Although technology-supported interventions are effective for reducing chronic disease risk, little is known about the relative and combined efficacy of mobile health strategies aimed at multiple lifestyle factors. The purpose of this clinical trial is to evaluate the efficacy of technology-supported behavioral intervention strategies for managing multiple lifestyle-related health outcomes in overweight adults with type 2 diabetes (T2D) and chronic kidney disease (CKD). DESIGN AND METHODS/METHODS:, age ≥40 years), T2D, and CKD stages 2-4 were randomized to an advice control group, or remotely delivered programs consisting of synchronous group-based education (all groups), plus (1) Social Cognitive Theory-based behavioral counseling and/or (2) mobile self-monitoring of diet and physical activity. All programs targeted weight loss, greater physical activity, and lower intakes of sodium and phosphorus-containing food additives. RESULTS:Of 256 randomized participants, 186 (73%) completed 6-month assessments. Compared to the ADVICE group, mHealth interventions did not result in significant changes in weight loss, or urinary sodium and phosphorus excretion. In aggregate analyses, groups receiving mobile self-monitoring had greater weight loss at 3 months (P = .02), but between 3 and 6 months, weight losses plateaued, and by 6 months, the differences were no longer statistically significant. CONCLUSIONS:When engaging patients with T2D and CKD in multiple behavior changes, self-monitoring diet and physical activity demonstrated significantly larger short-term weight losses. Theory-based behavioral counseling alone was no better than baseline advice and demonstrated no interaction effect with self-monitoring.