Faculty Bibliography

Respiratory failure is associated with increased mortality in COVID-19 patients. There are no validated lower airway biomarkers to predict clinical outcome. We investigated whether bacterial respiratory infections were associated with poor clinical outcome of COVID-19 in a prospective, observational cohort of 589 critically ill adults, all of whom required mechanical ventilation. For a subset of 142 patients who underwent bronchoscopy, we quantified SARS-CoV-2 viral load, analysed the lower respiratory tract microbiome using metagenomics and metatranscriptomics and profiled the host immune response. Acquisition of a hospital-acquired respiratory pathogen was not associated with fatal outcome. Poor clinical outcome was associated with lower airway enrichment with an oral commensal (Mycoplasma salivarium). Increased SARS-CoV-2 abundance, low anti-SARS-CoV-2 antibody response and a distinct host transcriptome profile of the lower airways were most predictive of mortality. Our data provide evidence that secondary respiratory infections do not drive mortality in COVID-19 and clinical management strategies should prioritize reducing viral replication and maximizing host responses to SARS-CoV-2.

BACKGROUND:The human microbiome is inherently dynamic and its dynamic nature plays a critical role in maintaining health and driving disease. With an increasing number of longitudinal microbiome studies, scientists are eager to learn the comprehensive characterization of microbial dynamics and their implications to the health and disease-related phenotypes. However, due to the challenging structure of longitudinal microbiome data, few analytic methods are available to characterize the microbial dynamics over time. RESULTS:We propose a microbial trend analysis (MTA) framework for the high-dimensional and phylogenetically-based longitudinal microbiome data. In particular, MTA can perform three tasks: 1) capture the common microbial dynamic trends for a group of subjects at the community level and identify the dominant taxa; 2) examine whether or not the microbial overall dynamic trends are significantly different between groups; 3) classify an individual subject based on its longitudinal microbial profiling. Our extensive simulations demonstrate that the proposed MTA framework is robust and powerful in hypothesis testing, taxon identification, and subject classification. Our real data analyses further illustrate the utility of MTA through a longitudinal study in mice. CONCLUSIONS:The proposed MTA framework is an attractive and effective tool in investigating dynamic microbial pattern from longitudinal microbiome studies.

BACKGROUND/OBJECTIVES/OBJECTIVE:The incidence of obesity continues to increase worldwide and while the underlying pathogenesis remains largely unknown, nutrient excess, manifested by "Westernization" of the diet and reduced physical activity have been proposed as key contributing factors. Western-style diets, in addition to higher caloric load, are characterized by excess of advanced glycation end products (AGEs), which have been linked to the pathophysiology of obesity and related cardiometabolic disorders. AGEs can be "trapped" in adipose tissue, even in the absence of diabetes, in part due to higher expression of the receptor for AGEs (RAGE) and/or decreased detoxification by the endogenous glyoxalase (GLO) system, where they may promote insulin resistance. It is unknown whether the expression levels of genes linked to the RAGE axis, including AGER (the gene encoding RAGE), Diaphanous 1 (DIAPH1), the cytoplasmic domain binding partner of RAGE that contributes to RAGE signaling, and GLO1 are differentially regulated by the degree of obesity and/or how these relate to inflammatory and adipocyte markers and their metabolic consequences. SUBJECTS/METHODS/METHODS:We sought to answer this question by analyzing gene expression patterns of markers of the AGE/RAGE/DIAPH1 signaling axis in abdominal subcutaneous (SAT) and omental (OAT) adipose tissue from obese and morbidly obese subjects. RESULTS:In SAT, but not OAT, expression of AGER was significantly correlated with that of DIAPH1 (n = 16; [Formula: see text], [0.260, 1.177]; q = 0.008) and GLO1 (n = 16; [Formula: see text], [0.364, 1.182]; q = 0.004). Furthermore, in SAT, but not OAT, regression analyses revealed that the expression pattern of genes in the AGE/RAGE/DIAPH1 axis is strongly and positively associated with that of inflammatory and adipogenic markers. Remarkably, particularly in SAT, not OAT, the expression of AGER positively and significantly correlated with HOMA-IR (n = 14; [Formula: see text], [0.338, 1.249]; q = 0.018). CONCLUSIONS:These observations suggest associations of the AGE/RAGE/DIAPH1 axis in the immunometabolic pathophysiology of obesity and insulin resistance, driven, at least in part, through expression and activity of this axis in SAT.

The incidence of kidney stones is increasing in the US population. Oxalate, a major factor for stone formation, is degraded by gut bacteria reducing its intestinal absorption. Intestinal O. formigenes colonization has been associated with a lower risk for recurrent kidney stones in humans. In the current study, we used a clinical trial of the eradication of Helicobacter pylori to assess the effects of an antibiotic course on O. formigenes colonization, urine electrolytes, and the composition of the intestinal microbiome. Of 69 healthy adult subjects recruited, 19 received antibiotics for H. pylori eradication, while 46 were followed as controls. Serial fecal samples were examined for O. formigenes presence and microbiota characteristics. Urine, collected serially fasting and following a standard meal, was tested for oxalate and electrolyte concentrations. O. formigenes prevalence was 50%. Colonization was significantly and persistently suppressed in antibiotic-exposed subjects but remained stable in controls. Urinary pH increased after antibiotics, but urinary oxalate did not differ between the control and treatment groups. In subjects not on antibiotics, the O. formigenes-positive samples had higher alpha-diversity and significantly differed in Beta-diversity from the O. formigenes-negative samples. Specific taxa varied in abundance in relation to urinary oxalate levels. These studies identified significant antibiotic effects on O. formigenes colonization and urinary electrolytes and showed that overall microbiome structure differed in subjects according to O. formigenes presence. Identifying a consortium of bacterial taxa associated with urinary oxalate may provide clues for the primary prevention of kidney stones in healthy adults.

Antibody responses serve as the primary protection against SARS-CoV-2 infection through neutralization of viral entry into cells. We have developed a two-dimensional multiplex bead binding assay (2D-MBBA) that quantifies multiple antibody isotypes against multiple antigens from a single measurement. Here, we applied our assay to profile IgG, IgM and IgA levels against the spike antigen, its receptor-binding domain and natural and designed mutants. Machine learning algorithms trained on the 2D-MBBA data substantially improve the prediction of neutralization capacity against the authentic SARS-CoV-2 virus of serum samples of convalescent patients. The algorithms also helped identify a set of antibody isotypeâ€"antigen datasets that contributed to the prediction, which included those targeting regions outside the receptor-binding interface of the spike protein. We applied the assay to profile samples from vaccinated, immune-compromised patients, which revealed differences in the antibody profiles between convalescent and vaccinated samples. Our approach can rapidly provide deep antibody profiles and neutralization prediction from essentially a drop of blood without the need of BSL-3 access and provides insights into the nature of neutralizing antibodies. It may be further developed for evaluating neutralizing capacity for new variants and future pathogens.

OBJECTIVE:The objective of the study was to evaluate the feasibility and acceptability of mobile health (mHealth) phosphorus management programs in hemodialysis (HD) patients. METHODS:Patients receiving thrice-weekly HD who had 3-month average serum phosphorus of >5.5 mg/dL were randomized to one of the three self-directed phosphorus management programs delivered using tablet PCs: (1) educational videos and handouts (Education), (2) education intervention plus mobile self-monitoring with email feedback (Monitoring), or (3) education and monitoring interventions plus social cognitive theory-based behavioral videos (Combined). Feasibility and acceptability were assessed based on enrollment and retention and training needs (feasibility) and adherence to self-monitoring and reported satisfaction (acceptability). RESULTS:Of 312 patients, 56 expressed interest, and 40 were enrolled. The majority of participants (80%) completed the 6-month study; none withdrew for intervention-related reasons. The Monitoring and Combined groups received 44 ± 15 minutes of technology training, which was considered adequate by most (75%). Self-monitoring rates were initially high, with 78% and 71% of the participants recording at least one meal and phosphate binder in week 1, respectively, but decreased over time to 15% and 9% in the final week. Most participants reported that self-monitoring helped them stay motivated (64%), track nutrients (80%), and understand how to change diet (76%), and nearly two-thirds of participants (64%) stated that they would like to continue using the tablet PC to manage their health. However, few participants (16%) indicated that self-monitoring was worth the effort. The Monitoring and Combined groups did not differ from the Education group in study outcomes. CONCLUSION/CONCLUSIONS:Although the mHealth programs were generally well received, self-monitoring rates decreased substantially over time and were unaffected by social cognitive theory-based videos. Self-directed mHealth programs may be a useful adjunct to standard care but should be compared to more resource intensive programs (e.g., involving more "live" contact with a dietitian) to determine overall cost-effectiveness and role in HD care.

The microbiome plays an important role in human health by mediating the path from environmental exposures to health outcomes. The relative abundances of the high-dimensional microbiome data have an unit-sum restriction, rendering standard statistical methods in the Euclidean space invalid. To address this problem, we use the isometric log-ratio transformations of the relative abundances as the mediator variables. To select significant mediators, we consider a closed testing-based selection procedure with desirable confidence. Simulations are provided to verify the effectiveness of our method. As an illustrative example, we apply the proposed method to study the mediation effects of murine gut microbiome between subtherapeutic antibiotic treatment and body weight gain, and identify Coprobacillus and Adlercreutzia as two significant mediators.

The genome-wide association studies aim at identifying common or rare variants associated with common diseases and explaining more heritability. It is well known that common diseases are influenced by multiple single nucleotide polymorphisms (SNPs) that are usually correlated in location or function. In order to powerfully detect association signals, it is highly desirable to take account of correlations or linkage disequilibrium (LD) information among multiple SNPs in testing for association. In this article, we propose a test SLIDE that depicts the difference of the average multi-locus genotypes between cases and controls and derive its variance-covariance matrix in the retrospective design. This matrix is composed of the pairwise LD between SNPs. Thus SLIDE can borrow the strength from an external database in the population of interest with a few thousands to hundreds of thousands individuals to improve the power for detecting association. Extensive simulations show that SLIDE has apparent superiority over the existing methods, especially in the situation involving both common and rare variants, both protective and deleterious variants. Furthermore, the efficiency of the proposed method is demonstrated in the application to the data from the Wellcome Trust Case Control Consortium.

MOTIVATION/BACKGROUND:Recent microbiome association studies have revealed important associations between microbiome and disease/health status. Such findings encourage scientists to dive deeper to uncover the causal role of microbiome in the underlying biological mechanism, and have led to applying statistical models to quantify causal microbiome effects and to identify the specific microbial agents. However, there are no existing causal mediation methods specifically designed to handle high dimensional and compositional microbiome data. RESULTS:We propose a rigorous Sparse Microbial Causal Mediation Model (SparseMCMM) specifically designed for the high dimensional and compositional microbiome data in a typical three-factor (treatment, microbiome and outcome) causal study design. In particular, linear log-contrast regression model and Dirichlet regression model are proposed to estimate the causal direct effect of treatment and the causal mediation effects of microbiome at both the community and individual taxon levels. Regularization techniques are used to perform the variable selection in the proposed model framework to identify signature causal microbes. Two hypothesis tests on the overall mediation effect are proposed and their statistical significance is estimated by permutation procedures. Extensive simulated scenarios show that SparseMCMM has excellent performance in estimation and hypothesis testing. Finally, we showcase the utility of the proposed SparseMCMM method in a study which the murine microbiome has been manipulated by providing a clear and sensible causal path among antibiotic treatment, microbiome composition and mouse weight. AVAILABILITY/BACKGROUND:https://sites.google.com/site/huilinli09/software and https://github.com/chanw0/SparseMCMM. SUPPLEMENTARY INFORMATION/BACKGROUND:Supplementary data are available at Bioinformatics online.

There has been increasing interest in the human anaerobic colonic bacterium Oxalobacter formigenes because of its ability to metabolize oxalate, and its potential contribution to protection from calcium oxalate kidney stones. Prior studies examining the prevalence of this organism have focused on subjects in developed countries and on adults. Now using O. formigenes-specific PCR, we have compared the prevalence of these organisms among subjects in two remote areas in which modern medical practices have hardly been present with a USA group of mothers and their infants for the first three years of life. Among the Amerindians of the Yanomami-Sanema and Yekwana ethnic groups in Venezuela and the Hadza in Tanzania, O. formigenes was detected in 60-80% of the adult subjects, higher than found in adults from USA in this and prior studies. In young children, the prevalence was much lower in USA than in either tribal village. These data extend our understanding of the epidemiology of O. formigenes carriage, and are consistent with the hypothesis that the rising incidence of kidney stones is associated with the progressive loss of O. formigenes colonization in populations that have been highly impacted by modern medical practices.