Faculty Bibliography

Background: Type 2 diabetes (T2D) has an immense disease burden, affecting millions of people worldwide and costing billions of dollars in treatment. As T2D is a multifactorial disease with both genetic and nongenetic influences, accurate risk assessments for patients are difficult to perform. Machine learning has served as a useful tool in T2D risk prediction, as it can analyze and detect patterns in large and complex data sets like that of RNA sequencing. However, before machine learning can be implemented, feature selection is a necessary step to reduce the dimensionality in high-dimensional data and optimize modeling results. Different combinations of feature selection methods and machine learning models have been used in studies reporting disease predictions and classifications with high accuracy. Objective: The purpose of this study was to assess the use of feature selection and classification approaches that integrate different data types to predict weight loss for the prevention of T2D. Methods: The data of 56 participants (ie, demographic and clinical factors, dietary scores, step counts, and transcriptomics) were obtained from a previously completed randomized clinical trial adaptation of the Diabetes Prevention Program study. Feature selection methods were used to select for subsets of transcripts to be used in the selected classification approaches: support vector machine, logistic regression, decision trees, random forest, and extremely randomized decision trees (extra-trees). Data types were included in different classification approaches in an additive manner to assess model performance for the prediction of weight loss. Results: Average waist and hip circumference were found to be different between those who exhibited weight loss and those who did not exhibit weight loss (P=.02 and P=.04, respectively). The incorporation of dietary and step count data did not improve modeling performance compared to classifiers that included only demographic and clinical data. Optimal subsets of transcripts identified through feature selection yielded higher prediction accuracy than when all available transcripts were included. After comparison of different feature selection methods and classifiers, DESeq2 as a feature selection method and an extra-trees classifier with and without ensemble learning provided the most optimal results, as defined by differences in training and testing accuracy, cross-validated area under the curve, and other factors. We identified 5 genes in two or more of the feature selection subsets (ie, CDP-diacylglycerol-inositol 3-phosphatidyltransferase [CDIPT], mannose receptor C type 2 [MRC2], PAT1 homolog 2 [PATL2], regulatory factor X-associated ankyrin containing protein [RFXANK], and small ubiquitin like modifier 3 [SUMO3]). Conclusions: Our results suggest that the inclusion of transcriptomic data in classification approaches for prediction has the potential to improve weight loss prediction models. Identification of which individuals are likely to respond to interventions for weight loss may help to prevent incident T2D. Out of the 5 genes identified as optimal predictors, 3 (ie, CDIPT, MRC2, and SUMO3) have been previously shown to be associated with T2D or obesity.

Introduction: Integrated transcriptome and microRNA differential gene expression (DEG) analyses may help to explain type 2 diabetes (T2D) pathogenesis in at-risk populations. The purpose of this study was to characterize DEG in banked biospecimens from underactive adult participants who responded to a randomized clinical trial measuring the effects of lifestyle interventions on T2D risk factors. DEGs were further examined within the context of annotated biological pathways. Methods: Participants (n = 52) in a previously completed clinical trial that assessed a 12-week behavioural intervention for T2D risk reduction were included. Participants who showed >6mg/dL decrease in fasting blood glucose were identified as responders. Gene expression was measured by RNASeq, and overrepresentation analysis within KEGG pathways and weighted gene correlation network analysis (WGCNA) were performed. Results: No genes remained significantly differentially expressed after correction for multiple comparisons. One module derived by WGCNA related to body mass index was identified, which contained genes located in KEGG pathways related to known mechanisms underlying risk for T2D as well as pathways related to neurodegeneration and protein misfolding. A network analysis showed indirect connections between genes in this module and islet amyloid polypeptide (IAPP), which has previously been hypothesized as a mechanism for T2D. Discussion: We validated prior studies that showed pathways related to metabolism, inflammation/immunity, and endocrine/hormone function are related to risk for T2D. We identified evidence for new potential mechanisms that include protein misfolding. Additional studies are needed to determine whether these are potential therapeutic targets to decrease risk for T2D.

OBJECTIVE:Sexual minority men (e.g., gay, bisexual, and other men who have sex with men) experience stigma and sexual minority stress, which are theorized to drive negative health outcomes. Sexual minority men with treated HIV display persistent immune dysregulation, which could be amplified by sexual minority stress responses to potentiate cellular aging. METHODS:This cross-sectional study included 52 sexual minority men living with HIV who had undetectable viral load (<40 copies/mL) and biologically confirmed recent methamphetamine use. Participants completed measures assessing sexual minority stress and openness about sexual minority status (i.e., outness). DNA methylation-derived outcomes included the following: the extrinsic epigenetic age acceleration clock, telomere length, naive CD4+ T-helper cells, and naive CD8+ T-cytotoxic/suppressor cells. RESULTS:After adjusting for negative affect and recent stimulant use, higher sexual minority stress was associated with a faster extrinsic epigenetic age acceleration clock ( β = 0.29, p = .030), shorter telomere length ( β = -0.43, p = .002), and fewer naive CD4+ (β = -0.57, p < .001) and naive CD8+ T cells ( β = -0.57, p < .001). Greater outness was associated with higher naive CD4+ ( β = 0.32, p = .030) and naive CD8+ T cells ( β = 0.38, p = .008) as well as lower plasma interleukin 6 ( β = -0.33, p = .027). CONCLUSIONS:Sexual minority stress processes are associated with markers of cellular aging and inflammation in methamphetamine-using sexual minority men living with HIV. Longitudinal research should elucidate biobehavioral mechanisms linking sexual minority stress processes with accelerated cellular aging in those with and without HIV.

OBJECTIVES:This study of people with HIV (PWH) and those without HIV conducted during the COVID-19 pandemic in the United States in 2020 examines the impact of posttraumatic stress disorder (PTSD) on COVID-19 burden, defined as pandemic-related disruptions. METHODS:Data consisted of survey responses on PTSD among participants (N = 2434) enrolled in the Multicenter AIDS Cohort Study (MACS) and the Women's Interagency HIV (WIHS) cohorts. Unadjusted and adjusted regression models were used to examine the association of PTSD with COVID-19 burden (overall and domain-specific burdens). Quasi-Poisson regression models were used to assess associations with the COVID-19 burden score and 2 domain-specific burdens: (1) changes in resources and (2) interruptions in health care. Analyses was adjusted for age, race/ethnicity, HIV serostatus, current smoking status, number of comorbidities, education, and study regions. RESULTS:Study participants were a median age of 58 (interquartile range, 52-65) years. In both bivariate and multivariable models, PTSD severity was associated with greater overall COVID-19 burden. PTSD severity was associated with the number of resource changes and number of interruptions in medical care. These findings were also consistent across cohorts (MACS/WIHS) and across HIV serostatus, suggesting a greater risk for COVID-19 burden with greater PTSD severity, which remained significant after controlling for covariates. CONCLUSIONS:This study builds on emerging literature demonstrating the impact of mental health on the burden and disruption associated with the COVID-19 pandemic, providing context specific to PWH. The ongoing pandemic requires structural and social interventions to decrease disruption to resources and health resource needs among these vulnerable populations.

Oral squamous cell carcinoma (OSCC) patients suffer from poor survival due to metastasis or locoregional recurrence, processes that are both facilitated by perineural invasion (PNI). OSCC has higher rates of PNI than other cancer subtypes, with PNI present in 80% of tumors. Despite the impact of PNI on oral cancer prognosis and pain, little is known about the genes that drive PNI, which in turn drive pain, invasion, and metastasis. In this study, clinical data, preclinical, and in vitro models are leveraged to elucidate the role of neurotrophins in OSCC metastasis, PNI, and pain. The expression data in OSCC patients with metastasis, PNI, or pain demonstrate dysregulation of neurotrophin genes. TrkA and nerve growth factor receptor (NGFR) are focused, two receptors that are activated by NGF, a neurotrophin expressed at high levels in OSCC. It is demonstrated that targeted knockdown of these two receptors inhibits proliferation and invasion in an in vitro and preclinical model of OSCC, and metastasis, PNI, and pain. It is further determined that TrkA knockdown alone inhibits thermal hyperalgesia, whereas NGFR knockdown alone inhibits mechanical allodynia. Collectively the results highlight the ability of OSCC to co-opt different components of the neurotrophin pathway in metastasis, PNI, and pain.

Head and neck cancer (HNC) is the seventh most common cancer worldwide, the majority being oral squamous cell carcinoma. Despite advances in cancer diagnosis and treatment, the survival rate of patients with HNC remains stagnant. The cancer-nerve interaction has been recognized as an important driver of cancer progression. Schwann cells, a type of peripheral glia, have been implicated in promoting cancer cell growth, migration, dispersion, and invasion into the nerve in many cancers. Here, it is demonstrated that the presence of Schwann cells makes oral cancer cells more aggressive by promoting their proliferation, extracellular matrix breakdown, and altering cell metabolism. Furthermore, oral cancer cells became larger, more circular, with more projections and nuclei following co-culturing with Schwann cells. RNA-sequencing analysis in oral cancer cells following exposure to Schwann cells shows corresponding changes in genes involved in the hallmarks of cancer and cell metabolism; the enriched KEGG pathways are spliceosome, RNA transport, cell cycle, axon guidance, signaling pathways regulating pluripotency of stem cells, cAMP signaling, WNT signaling, proteoglycans in cancer and PI3K-Akt signaling. Taken together, these results suggest a significant role for Schwann cells in facilitating oral cancer progression, highlighting their potential as a target to treat oral cancer progression.

BACKGROUND:Neurologic complications of the human immunodeficiency virus (HIV) are common in treated individuals and toxicity of certain antiretroviral therapies (ART) may contribute to cognitive impairment. We investigated exposures to specific ART and cognition among women living with HIV (WLWH). METHODS:Virologically suppressed (viral load <200 copies/mL during at least two semi-annual visits) WLWH and age/race matched HIV-seronegative controls enrolled in the Women's Interagency HIV Study (WIHS) who completed at least two biennial cognitive assessments were included. Analysis of WLWH was restricted to those with exposure to the drug class of interest and a nucleoside reverse transcriptase inhibitor backbone (NRTI). Generalized estimating equations were used to evaluate repeated measures of cognition over time in association with ART class exposure. RESULTS:Among 1,242 eligible WLWH, 20% (n=247) had isolated drug exposure to non-nucleoside reverse transcriptase inhibitors (NNRTI), 18% (n=219) to protease inhibitors (PI), and 6% (n=79) to integrase inhibitors (INSTI) with a NRTI backbone. Cognitive assessments were performed at a median of 3 biennial visits {IQR 2-4 visits}. At the index assessment, 21% of WLWH demonstrated global cognitive impairment versus 29% at their last cognitive assessment. In multivariable analyses adjusted, WLWH exposed to NNRTIs demonstrated verbal learning improvements (mean T-score change 1.3, p=0.020) as compared to other treated women. Compared to HIV-seronegative women, WLWH exposed to PIs had worse verbal learning (mean T-score difference -2.62, p=0.002) and verbal memory performance (mean T-score difference -1.74, p=0.032) at baseline. Compared to HIV-seronegative women, WLWH exposed to PIs had improvements in verbal learning (mean T-score slope difference 0.36, p=0.025) and verbal memory (mean T-score slope difference 0.32, p=0.042). CONCLUSIONS:We noted emerging trends in cognition in WLWH exposed to specific ART. Ongoing study of this relatively young group is important to characterize long term cognitive outcomes and effect of antiretrovirals as treatment guidelines evolve.

BACKGROUND:Alterations in gut microbiota and blood metabolomic profiles have been implicated in HIV infection and cardiovascular disease. However, it remains unclear whether alterations in gut microbiota may contribute to disrupted host blood metabolomic profiles in relation to atherosclerosis, especially in the context of HIV infection. METHODS:We analyzed cross-sectional associations between gut microbiota features and carotid artery plaque in 361 women with or at high risk of HIV (67% HIV+), and further integrated plaque-associated microbial features with plasma lipidomic/metabolomic profiles. Furthermore, in 737 women and men, we examined prospective associations of baseline gut bacteria-associated lipidomic and metabolomic profiles with incident carotid artery plaque over 7-year follow-up. RESULTS:were associated with multiple lipids/metabolites which were clustered into 8 modules in network. A module comprised of 9 lysophosphatidylcholines and lysophosphatidylethanolamines and a module comprised of 9 diglycerides were associated with increased risk of carotid artery plaque (risk ratio [95% CI], 1.34 [1.09-1.64] and 1.24 [1.02-1.51] per SD increment, respectively). Functional analyses identified bacterial enzymes in lipid metabolism associated with these plasma lipids. In particular, phospholipase A1 and A2 are the key enzymes in the reactions producing lysophosphatidylcholines and lysophosphatidylethanolamines. CONCLUSIONS:Among individuals with or at high risk of HIV infection, we identified altered gut microbiota and related functional capacities in the lipid metabolism associated with disrupted plasma lipidomic profiles and carotid artery atherosclerosis.