Faculty Bibliography

The dynamics of viral load (VL) of the 2019 novel coronavirus (severe acute respiratory syndrome coronavirus 2) and its association with different clinical parameters remain poorly characterized in the US patient population. Herein, we investigate associations between VL and parameters, such as severity of symptoms, disposition (admission versus direct discharge), length of hospitalization, admission to the intensive care unit, length of need for oxygen support, and overall survival in a cohort of 205 patients from a tertiary care center in New York City. VL was determined using quantitative PCR and log10 transformed for normalization. Univariate and multivariate regression models were used to test these associations. We found that diagnostic viral load is significantly lower in hospitalized patients than in patients not hospitalized (log10 VL = 3.3 versus 4.0; P = 0.018) after adjusting for age, sex, race, body mass index, and comorbidities. Higher VL was associated with shorter duration of the symptoms in all patients and hospitalized patients only and shorter hospital stay (coefficient = -2.02, -2.61, and -2.18; P < 0.001, P = 0.002, and P = 0.013, respectively). No significant association was noted between VL, admission to intensive care unit, length of oxygen support, and overall survival. Our findings suggest a higher shedding risk in less symptomatic patients, an important consideration for containment strategies in severe acute respiratory syndrome coronavirus 2. Furthermore, we identify a novel association between viral load and history of cancer. Larger studies are warranted to validate our findings.

INTRODUCTION/BACKGROUND:Epidemiological studies that investigate alterations in the gut microbial composition associated with smoking are lacking. This study examined the composition of the gut microbiome in smokers compared with non-smokers. METHODS:Stool samples were collected in a cross-sectional study of 249 participants selected from the Health Effects of Arsenic Longitudinal Study (HEALS) in Bangladesh. Microbial DNA was extracted from the fecal samples and sequenced by 16S rRNA gene sequencing. The associations of smoking status and intensity of smoking with the relative abundance or the absence and presence of individual bacterial taxon from phylum to genus levels were examined. RESULTS:The relative abundance of bacterial taxa along the Erysipelotrichi-to-Catenibacterium lineage was significantly higher in current smokers compared to never smokers. The odds ratio comparing the mean relative abundance in current smokers with that in never smokers was 1.91 (95% confidence interval [CI] = 1.36 to 2.69) for the genus Catenibacterium and 1.89 (95% CI = 1.39 to 2.56) for the family Erysipelotrichaceae, the order Erysipelotrichale, and the class Erysipelotrichi ((FDR-adjusted p-values = 0.0008 to 0.01). A dose-response association was observed for each of these bacterial taxa. The presence of Alphaproteobacteria was significantly greater comparing current with never smokers (OR = 4.85, FDR-adjusted p-values = 0.04). CONCLUSIONS:Our data in a Bangladeshi population are consistent with evidence of an association between smoking status and dosage with change in the gut bacterial composition. IMPLICATIONS/CONCLUSIONS:This study for the first time examined the relationship between smoking and the gut microbiome composition. The data suggest that smoking status may play an important role in the composition of the gut microbiome, especially among individuals with higher levels of tobacco exposure.

Despite advances in lipid-lowering therapies, people with diabetes continue to experience more limited cardiovascular benefits. In diabetes, hyperglycemia sustains inflammation and preempts vascular repair. We tested the hypothesis that the receptor for advanced glycation end-products (RAGE) contributes to these maladaptive processes. We report that transplantation of aortic arches from diabetic, Western diet-fed Ldlr-/- mice into diabetic Ager-/- (Ager, the gene encoding RAGE) versus WT diabetic recipient mice accelerated regression of atherosclerosis. RNA-sequencing experiments traced RAGE-dependent mechanisms principally to the recipient macrophages and linked RAGE to interferon signaling. Specifically, deletion of Ager in the regressing diabetic plaques downregulated interferon regulatory factor 7 (Irf7) in macrophages. Immunohistochemistry studies colocalized IRF7 and macrophages in both murine and human atherosclerotic plaques. In bone marrow-derived macrophages (BMDMs), RAGE ligands upregulated expression of Irf7, and in BMDMs immersed in a cholesterol-rich environment, knockdown of Irf7 triggered a switch from pro- to antiinflammatory gene expression and regulated a host of genes linked to cholesterol efflux and homeostasis. Collectively, this work adds a new dimension to the immunometabolic sphere of perturbations that impair regression of established diabetic atherosclerosis and suggests that targeting RAGE and IRF7 may facilitate vascular repair in diabetes.

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.

BACKGROUND:Despite robust cholesterol lowering, cardiovascular disease risk remains increased in patients with diabetes mellitus. Consistent with this, diabetes mellitus impairs atherosclerosis regression after cholesterol lowering in humans and mice. In mice, this is attributed in part to hyperglycemia-induced monocytosis, which increases monocyte entry into plaques despite cholesterol lowering. In addition, diabetes mellitus skews plaque macrophages toward an atherogenic inflammatory M1 phenotype instead of toward the atherosclerosis-resolving M2 state typical with cholesterol lowering. Functional high-density lipoprotein (HDL), typically low in patients with diabetes mellitus, reduces monocyte precursor proliferation in murine bone marrow and has anti-inflammatory effects on human and murine macrophages. Our study aimed to test whether raising functional HDL levels in diabetic mice prevents monocytosis, reduces the quantity and inflammation of plaque macrophages, and enhances atherosclerosis regression after cholesterol lowering. METHODS:mice were transplanted into either wild-type, diabetic wild-type, or diabetic mice transgenic for human apolipoprotein AI, which have elevated functional HDL. Recipient mice all had low levels of low-density lipoprotein cholesterol to promote plaque regression. After 2 weeks, plaques in recipient mouse aortic grafts were examined. RESULTS:Diabetic wild-type mice had impaired atherosclerosis regression, which was normalized by raising HDL levels. This benefit was linked to suppressed hyperglycemia-driven myelopoiesis, monocytosis, and neutrophilia. Increased HDL improved cholesterol efflux from bone marrow progenitors, suppressing their proliferation and monocyte and neutrophil production capacity. In addition to reducing circulating monocytes available for recruitment into plaques, in the diabetic milieu, HDL suppressed the general recruitability of monocytes to inflammatory sites and promoted plaque macrophage polarization to the M2, atherosclerosis-resolving state. There was also a decrease in plaque neutrophil extracellular traps, which are atherogenic and increased by diabetes mellitus. CONCLUSIONS:Raising apolipoprotein AI and functional levels of HDL promotes multiple favorable changes in the production of monocytes and neutrophils and in the inflammatory environment of atherosclerotic plaques of diabetic mice after cholesterol lowering and may represent a novel approach to reduce cardiovascular disease risk in people with diabetes mellitus.

Over the past decade, there has been a change in the epidemiology of oral cavity squamous cell cancer (OC-SCC). Many new cases of OC-SCC lack the recognized risk factors of smoking, alcohol and human papilloma virus. The aim of this study was to determine if the oral microbiome may be associated with OC-SCC in nonsmoking HPV negative patients. We compared the oral microbiome of HPV-negative nonsmoker OC-SCC( n=18), premalignant lesions(PML) (n=8) and normal control patients (n=12). Their oral microbiome was sampled by oral wash and defined by 16S rRNA gene sequencing. We report that the periodontal pathogens Fusobacterium, Prevotella, Alloprevotella were enriched while commensal Streptococcus depleted in OC-SCC. Based on the four genera plus a marker genus Veillonella for PML, we classified the oral microbiome into two types. Gene/pathway analysis revealed a progressive increase of genes encoding HSP90 and ligands for TLRs 1, 2 and 4 along the controls→PML→OC-SCC progression sequence. Our findings suggest an association between periodontal pathogens and OC-SCC in non smoking HPV negative patients.

In the past decade, genome-wide association studies have identified thousands of susceptible variants associated with complex human diseases and traits. Conducting follow-up genetic association studies has become a standard approach to validate the findings of genome-wide association studies. One problem of high interest in genetic association studies is to accurately estimate the strength of the association, which is often quantified by odds ratios in case-control studies. However, estimating the association directly by follow-up studies is inefficient since this approach ignores information from the genome-wide association studies. In this article, an estimator called GFcom, which integrates information from genome-wide association studies and follow-up studies, is proposed. The estimator includes both the point estimate and corresponding confidence interval. GFcom is more efficient than competing estimators regarding MSE and the length of confidence intervals. The superiority of GFcom is particularly evident when the genome-wide association study suffers from severe selection bias. Comprehensive simulation studies and applications to three real follow-up studies demonstrate the performance of the proposed estimator. An R package, "GFcom", implementing our method is publicly available at https://github.com/JiyuanHu/GFcom .

Our objective was to investigate the relationship between the gut microbiota and anthropometric measurements among 248 participants from the Health Effects of Arsenic Longitudinal Study (HEALS) in Bangladesh. Our cohort represents a unique population that allows for the investigation of the gut microbiota and anthropometric measurements in lean individuals. We measured height, weight, arm, thigh, hip, and waist circumferences, and collected fecal samples. Microbial DNA was extracted from the stool samples and sequenced by 16S rRNA gene sequencing. We examined associations between relative abundance of individual bacterial taxa from phylum to genus levels and anthropometric measurements. We found that higher BMI, mid-upper arm circumference, waist circumference, and waist-to-hip ratio were associated with a lower alpha diversity of fecal bacteria. Relative abundance of the genus Oscillospira and the family S24-7 were inversely related to all measurements after correction for multiple testing. Relative abundance of genus Acidaminococcus and family Ruminococcaceae were also associated with several measurements. The positive associations of the genus Acidaminococcus with BMI, as well as waist and hip circumferences, were stronger in women than in men. Our data in this lean Bangladeshi population found a correlation between Oscillospira and leanness, as measured using multiple anthropometric measures.

BACKGROUND:Emerging data suggest that inorganic arsenic exposure and gut microbiome are associated with the risk of cardiovascular disease. The gut microbiome may modify disease risk associated with arsenic exposure. Our aim was to examine the inter-relationships between arsenic exposure, the gut microbiome, and carotid intima-media thickness (IMT)-a surrogate marker for atherosclerosis. METHODS:We recruited 250 participants from the Health Effects of Arsenic Longitudinal Study in Bangladesh, measured IMT and collected fecal samples in year 2015-2016. 16S rRNA gene sequencing was conducted on microbial DNA extracted from the fecal samples. Arsenic exposure was measured using data on arsenic concentration in drinking water wells over time to derive a time-weighted water arsenic index. Multivariable linear regression models were used to test the inter-relationships between arsenic exposure, relative abundance of selected bacterial taxa from phylum to genus levels, and IMT. RESULTS:We identified nominally significant associations between arsenic exposure, measured using either time-weighted water arsenic or urinary arsenic, and the relative abundances of several bacterial taxa from the phylum Tenericutes, Proteobacteria, and Firmicutes. However, none of the associations retained significance after correction for multiple testing. The relative abundances of the family Aeromonadaceae and genus Citrobacter were significantly associated with IMT after correction for multiple testing (P-value = 0.02 and 0.03, respectively). Every 1% increase in the relative abundance of Aeromonadaceae and Citrobacter was related to an 18.2-μm (95% CI: 7.8, 28.5) and 97.3-μm (95% CI: 42.3, 152.3) difference in IMT, respectively. These two taxa were also the only selected family and genus using the LASSO variable selection method. There was a significant interaction between Citrobacter and time-weighted water arsenic in IMT (P for interaction = 0.04). CONCLUSIONS:Our findings suggest a role of Citrobacter in the development of atherosclerosis, especially among individuals with higher levels of arsenic exposure.

Guidelines to reduce cardiovascular risk in diabetes include aggressive LDL lowering, but benefits are attenuated compared to those in patients without diabetes. Consistent with this, we have reported in mice that hyperglycemia impaired atherosclerosis regression. Aldose reductase (AR) is thought to contribute to clinical complications of diabetes by directing glucose into pathways producing inflammatory metabolites. Mice have low levels of AR, thus, raising them to human levels would be a more clinically relevant model to study changes in diabetes under atherosclerosis regression conditions. Donor aortae from western diet-fed Ldlr