Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts.

BACKGROUND: Epigenome-wide association studies (EWAS) have identified CpG sites associated with HIV infection in blood cells in bulk, which offer limited knowledge of cell-type specific methylation patterns associated with HIV infection. In this study, we aim to identify differentially methylated CpG sites for HIV infection in immune cell types: CD4+ T-cells, CD8+ T-cells, B cells, Natural Killer (NK) cells, and monocytes. METHODS: Applying a computational deconvolution method, we performed a cell-type based EWAS for HIV infection in three independent cohorts (Ntotal = 1,382). DNA methylation in blood or in peripheral blood mononuclear cells (PBMCs) was profiled by an array-based method and then deconvoluted by Tensor Composition Analysis (TCA). The TCA-computed CpG methylation in each cell type was first benchmarked by bisulfite DNA methylation capture sequencing in a subset of the samples. Cell-type EWAS of HIV infection was performed in each cohort separately and a meta-EWAS was conducted followed by gene set enrichment analysis. RESULTS: The meta-analysis unveiled a total of 2,021 cell-type unique significant CpG sites for five inferred cell types. Among these inferred cell-type unique CpG sites, the concordance rate in the three cohorts ranged from 96% to 100% in each cell type. Cell-type level meta-EWAS unveiled distinct patterns of HIV-associated differential CpG methylation, where 74% of CpG sites were unique to individual cell types (false discovery rate, FDR <0.05). CD4+ T-cells had the largest number of unique HIV-associated CpG sites (N = 1,624) compared to any other cell type. Genes harboring significant CpG sites are involved in immunity and HIV pathogenesis (e.g. CD4+ T-cells: NLRC5, CX3CR1, B cells: IFI44L, NK cells: IL12R, monocytes: IRF7), and in oncogenesis (e.g. CD4+ T-cells: BCL family, PRDM16, monocytes: PRDM16, PDCD1LG2). HIV-associated CpG sites were enriched among genes involved in HIV pathogenesis and oncogenesis that were enriched among interferon-α and -γ, TNF-α, inflammatory response, and apoptotic pathways. CONCLUSION: Our findings uncovered computationally inferred cell-type specific modifications in the host epigenome for people with HIV that contribute to the growing body of evidence regarding HIV pathogenesis.

A positive affect intervention alters leukocyte DNA methylation in sexual minority men with HIV who use methamphetamine.

OBJECTIVE: This epigenomics sub-study embedded within a randomized controlled trial examined whether an evidenced-based behavioral intervention model that decreased stimulant use altered leukocyte DNA methylation (DNAm). METHODS: Sexual minority men with HIV who use methamphetamine were randomized to a five-session positive affect intervention (n = 32) or an attention-control condition (n = 21), both delivered during three months of contingency management for stimulant abstinence. All participants exhibited sustained HIV virologic control - an HIV viral load less than 40 copies/mL at baseline and six months post-randomization. The Illumina EPIC BeadChip measured leukocyte methylation of cytosine-phosphate-guanosine (CpG) sites mapping onto five a priori candidate genes of interest (i.e., ADRB2, BDNF, FKBP5, NR3C1, OXTR). Functional DNAm pathways and soluble markers of immune dysfunction were secondary outcomes. RESULTS: Compared to the attention-control condition, the positive affect intervention significantly decreased methylation of CpG sites on genes that regulate ß2 adrenergic and oxytocin receptors. There was an inconsistent pattern for the direction of the intervention effects on methylation of CpG sites on genes for glucocorticoid receptors and brain-derived neurotrophic factor. Pathway analyses adjusting for the false discovery rate (padj < 0.05) revealed significant intervention-related alterations in DNAm of Reactome pathways corresponding to neural function as well as dopamine, glutamate, and serotonin release. Positive affect intervention effects on DNAm were accompanied by significant reductions in the self-reported frequency of stimulant use. CONCLUSIONS: There is an epigenetic signature of an evidence-based behavioral intervention model that reduced stimulant use, which will guide the identification of biomarkers for treatment responses.

Single-Cell Molecular Profiling of Head and Neck Squamous Cell Carcinoma Reveals Five Dysregulated Signaling Pathways Associated With Circulating Tumor Cells.

OBJECTIVES: To determine the dysregulated signaling pathways of head and neck squamous cell carcinoma associated with circulating tumor cells (CTCs) via single-cell molecular characterization. INTRODUCTION: Head and neck squamous cell carcinoma (HNSCC) has a significant global burden and is a disease with poor survival. Despite trials exploring new treatment modalities to improve disease control rates, the 5 year survival rate remains low at only 60%. Most cancer malignancies are reported to progress to a fatal phase due to the metastatic activity derived from treatment-resistant cancer cells, regarded as one of the most significant obstacles to develope effective cancer treatment options. However, the molecular profiles of cancer cells have not been thoroughly studied. METHODS: Here, we examined in-situ HNSCC tumors and pairwisely followed up with the downstream circulating tumor cells (CTCs)-based on the surrogate biomarkers to detect metastasis that is established in other cancers - not yet being fully adopted in HNSCC treatment algorithms. RESULTS: Specifically, we revealed metastatic HNSCC patients have complex CTCs that could be defined through gene expression and mutational gene profiling derived from completed single-cell RNASeq (scRNASeq) that served to confirm molecular pathways inherent in these CTCs. To enhance the reliability of our findings, we cross-validated those molecular profiles with results from previously published studies. CONCLUSION: Thus, we identified 5 dysregulated signaling pathways in CTCs to derive HNSCC biomarker panels for screening HNSCC in situ tumors.

ObjectivesInvestigating the dysregulated signaling pathways of head and neck squamous cell carcinoma (HNSCC) linked with circulating tumor cells (CTCs) using single-cell molecular characterization.IntroductionHNSCC poses a significant global health burden with poor survival rates despite advancements in treatment. Metastatic activity from treatment-resistant cancer cells remains a major challenge in developing effective treatments. However, the molecular profiles of cancer cells, particularly CTCs, are not well-understood.MethodsWe analyzed in-situ HNSCC tumors and corresponding CTCs using surrogate biomarkers to detect metastasis, a technique not widely used in HNSCC treatment protocols.ResultsOur study revealed complex CTCs in metastatic HNSCC patients characterized by gene expression and mutational gene profiling via single-cell RNASeq (scRNASeq). These profiles confirmed molecular pathways inherent in CTCs, further validated by previous research.ConclusionThrough our research, we identified five dysregulated signaling pathways in CTCs, suggesting potential biomarker panels for HNSCC screening in situ tumors.

DNA methylation-based telomere length is associated with HIV infection, physical frailty, cancer, and all-cause mortality.

Telomere length (TL) is an important indicator of cellular aging. Shorter TL is associated with several age-related diseases including coronary heart disease, heart failure, diabetes, osteoporosis, and cancer. Recently, a DNA methylation-based TL (DNAmTL) estimator has been developed as an alternative method for directly measuring TL. In this study, we examined the association of DNAmTL with cancer prevalence and mortality risk among people with and without HIV in the Veterans Aging Cohort Study Biomarker Cohort (VACS, N = 1917) and Women's Interagency HIV Study Cohort (WIHS, N = 481). We profiled DNAm in whole blood (VACS) or in peripheral blood mononuclear cells (WIHS) using an array-based method. Cancer prevalence was estimated from electronic medical records and cancer registry data. The VACS Index was used as a measure of physiologic frailty. Models were adjusted for self-reported race and ethnicity, batch, smoking status, alcohol consumption, and five cell types (CD4, CD8, NK, B cell, and monocyte). We found that people with HIV had shorter average DNAmTL than those without HIV infection [beta = -0.25, 95% confidence interval (-0.32, -0.18), p = 1.48E-12]. Greater value of VACS Index [beta = -0.002 (-0.003, -0.001), p = 2.82E-05] and higher cancer prevalence [beta = -0.07 (-0.10, -0.03), p = 1.37E-04 without adjusting age] were associated with shortened DNAmTL. In addition, one kilobase decrease in DNAmTL was associated with a 40% increase in mortality risk [hazard ratio: 0.60 (0.44, 0.82), p = 1.42E-03]. In summary, HIV infection, physiologic frailty, and cancer are associated with shortening DNAmTL, contributing to an increased risk of all-cause mortality.

Artificial Intelligence Applications in Oral Cancer and Oral Dysplasia.

Oral squamous cell carcinoma (OSCC) is a highly unpredictable disease with devastating mortality rates that have not changed over the past decades, in the face of advancements in treatments and biomarkers, which have improved survival for other cancers. Delays in diagnosis are frequent, leading to more disfiguring treatments and poor outcomes for patients. The clinical challenge lies in identifying those patients at the highest risk of developing OSCC. Oral epithelial dysplasia (OED) is a precursor of OSCC with highly variable behavior across patients. There is no reliable clinical, pathological, histological, or molecular biomarker to determine individual risk in OED patients. Similarly, there are no robust biomarkers to predict treatment outcomes or mortality in OSCC patients. This review aims to highlight advancements in artificial intelligence (AI)-based methods to develop predictive biomarkers of OED transformation to OSCC or predictive biomarkers of OSCC mortality and treatment response. Biomarkers such as S100A7 demonstrate promising appraisal for the risk of malignant transformation of OED. Machine learning-enhanced multiplex immunohistochemistry workflows examine immune cell patterns and organization within the tumor immune microenvironment to generate outcome predictions in immunotherapy. Deep learning (DL) is an AI-based method using an extended neural network or related architecture with multiple "hidden" layers of simulated neurons to combine simple visual features into complex patterns. DL-based digital pathology is currently being developed to assess OED and OSCC outcomes. The integration of machine learning in epigenomics aims to examine the epigenetic modification of diseases and improve our ability to detect, classify, and predict outcomes associated with epigenetic marks. Collectively, these tools showcase promising advancements in discovery and technology, which may provide a potential solution to addressing the current limitations in predicting OED transformation and OSCC behavior, both of which are clinical challenges that must be addressed in order to improve OSCC survival.

Factors Associated With the Cardiovascular Health of Black and Latino Adults With Type 2 Diabetes.

AIMS: The purpose of this study was to assess the levels of cardiovascular health (CVH) of Black and Latino adults with type 2 diabetes (T2D) and examine the association of individual and microsystem level factors with their CVH score. METHODS: This was a cross-sectional design in 60 Black and Latino Adults aged 18-40 with T2D. Data were collected on sociodemographic, individual (sociodemographic, diabetes self-management, sleep disturbance, depressive symptoms, quality of life, and the inflammatory biomarkers IL-6 and hs-CRP) and microsystem factors (family functioning), and American Heart Association's Life's Simple 7 metrics of CVH. Factors significantly associated with the CVH score in the bivariate analyses were entered into a linear regression model. RESULTS: The sample had a mean age 34 ± 5 years and was primarily female (75%) with a mean CVH score was 8.6 ± 2.2 (possible range of 0-14). The sample achieved these CVH factors at ideal levels: body mass index <25 kg/m2 (8%); blood pressure <120/80 (42%); hemoglobin A1c < 7% (57%); total cholesterol <200 mg/dL (83%); healthy diet (18%); never or former smoker > one year (95%); and physical activity (150 moderate-to-vigorous minutes/week; 45%). In the multivariable model, two factors were significantly associated with cardiovascular health: hs-CRP (B = -0.11621, p < .0001) and the general health scale (B = 0.45127, p = .0013). CONCLUSIONS: This sample had an intermediate level of CVH, with inflammation and general health associated with overall CVH score.

Longitudinal Associations Between MicroRNAs and Weight in the Diabetes Prevention Program.

OBJECTIVE: Circulating microRNAs show cross-sectional associations with overweight and obesity. Few studies provided data to differentiate between a snapshot perspective on these associations versus how microRNAs characterize prodromal risk from disease pathology and complications. This study assessed longitudinal relationships between circulating microRNAs and weight at multiple time-points in the Diabetes Prevention Program trial. RESEARCH DESIGN AND METHODS: A subset of participants (n=150) from the Diabetes Prevention Program were included. MicroRNAs were measured from banked plasma using a Fireplex Assay. We used generalized linear mixed models to evaluate relationships between microRNAs and changes in weight at baseline, year-1, and year-2. Logistic regression was used to evaluate whether microRNAs at baseline were associated with weight change after 2 years. RESULTS: In fully adjusted models that included relevant covariates, seven miRs (i.e., miR-126, miR-15a, miR-192, miR-23a, and miR-27a) were statistically associated with weight over 2 years. MiR-197 and miR-320a remained significant after adjustment for multiple comparisons. Baseline levels of let-7f, miR-17, and miR-320c were significantly associated with 3% weight loss after 2 years in fully adjusted models. DISCUSSION: This study provided evidence for longitudinal relationships between circulating microRNAs and weight. Because microRNAs characterize the combined effects of genetic determinants and responses to behavioral determinants, they may provide insights about the etiology of overweight and obesity in the context or risk for common, complex diseases. Additional studies are needed to validate the potential genes and biological pathways that might be targeted by these microRNA biomarkers and have mechanistic implications for weight loss and disease prevention.

Stimulator of Interferon Genes Pathway Activation through the Controlled Release of STINGel Mediates Analgesia and Anti-Cancer Effects in Oral Squamous Cell Carcinoma.

Oral squamous cell carcinoma (OSCC) presents significant treatment challenges due to its poor survival and intense pain at the primary cancer site. Cancer pain is debilitating, contributes to diminished quality of life, and causes opioid tolerance. The stimulator of interferon genes (STING) agonism has been investigated as an anti-cancer strategy. We have developed STINGel, an extended-release formulation that prolongs the availability of STING agonists, which has demonstrated an enhanced anti-tumor effect in OSCC compared to STING agonist injection. This study investigates the impact of intra-tumoral STINGel on OSCC-induced pain using two separate OSCC models and nociceptive behavioral assays. Intra-tumoral STINGel significantly reduced mechanical allodynia in the orofacial cancer model and alleviated thermal and mechanical hyperalgesia in the hind paw model. To determine the cellular signaling cascade contributing to the antinociceptive effect, we performed an in-depth analysis of immune cell populations via single-cell RNA-seq. We demonstrated an increase in M1-like macrophages and N1-like neutrophils after STINGel treatment. The identified regulatory pathways controlled immune response activation, myeloid cell differentiation, and cytoplasmic translation. Functional pathway analysis demonstrated the suppression of translation at neuron synapses and the negative regulation of neuron projection development in M2-like macrophages after STINGel treatment. Importantly, STINGel treatment upregulated TGF-ß pathway signaling between various cell populations and peripheral nervous system (PNS) macrophages and enhanced TGF-ß signaling within the PNS itself. Overall, this study sheds light on the mechanisms underlying STINGel-mediated antinociception and anti-tumorigenic impact.

Substance Use Over Time Among Sexual and Gender Minority People: Differences at the Intersection of Sex and Gender.

Purpose: Sexual and gender minority (SGM) people are at greater risk for substance use than heterosexual and cisgender people, but most prior work is limited by cross-sectional analyses or the examination of single substance use. This study examined substance use over time among SGM people to identify patterns of polysubstance use at the intersection of sex and gender. Methods: Data were collected annually over 4 years from SGM respondents (n = 11,822) in The Population Research in Identity and Disparities for Equality (PRIDE) Study. Differences in substance use patterns (any prior 30-day use of 15 substances) by gender subgroup were examined with latent class analysis, and multinomial regression models tested relationships between gender subgroup and substance use. Results: Eight classes of substance use were observed. The three most common patterns were low substance use (49%), heavy episodic alcohol use (≥5 alcoholic drinks on one occasion) with some cannabis and tobacco use (14%), and cannabis use with some tobacco and declining heavy episodic alcohol use (13%). Differences observed included lower odds of patterns defined by heavy episodic alcohol use with some cannabis and tobacco use in all gender subgroups relative to cisgender men and persons with low substance use (odds ratios [ORs] 0.26-0.60). Gender expansive people assigned female at birth, gender expansive people assigned male at birth, and transgender men had greater odds of reporting cannabis use with small percentages of heavy episodic alcohol and tobacco use (ORs: 1.41-1.60). Conclusion: This study suggests that there are unique patterns of polysubstance use over time among gender subgroups of SGM people.

Perineural Invasion Is Associated With Function-evoked Pain and Altered Extracellular Matrix in Patients With Head and Neck Squamous Cell Carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is painful, and perineural invasion (PNI) has been associated with the worst pain. Pain due to HNSCC is diverse and may vary based on clinicopathological factors. This study aims to characterize different pain patterns linked with PNI, its influence on daily functioning, and gain insights into molecular changes and pathways associated with PNI-related pain in HNSCC patients. We conducted a cross-sectional study across 3 medical centers (n = 114), assessing pain phenotypes and their impact on daily functioning using 2 self-reported pain questionnaires, given to patients prior to their cancer surgery. Furthermore, we conducted RNA-seq analysis utilizing the The Cancer Genome Atlas dataset of HNSCC tumor from patients (n = 192) to identify genes relevant to both PNI and pain. Upon adjusting for demographic and clinicopathological variables using linear regression models, we found that PNI independently predicted function-evoked pain according to the University of Calfornia San Francisco Oral Cancer Pain Questionnaire, as well as the worst pain intensity reported in the Brief Pain Inventory. Distinct pain patterns were observed to be associated with daily activities in varying manners. Our molecular analyses revealed significant disruptions in pathways associated with the extracellular matrix structure and organization. The top differentially expressed genes linked to the extracellular matrix are implicated in cancer development, pain, and neurodegenerative diseases. Our data underscore the importance of properly categorizing pain phenotypes in future studies aiming to uncover mechanistic underpinnings of pain. Additionally, we have compiled a list of genes of interest that could serve as targets for both cancer and cancer pain management. PERSPECTIVE: PNI independently predicts function-evoked pain. Different pain phenotypes affect daily activities differently. We identified a list of candidate genes involved in the extracellular matrix structure and function that can be targeted for both cancer and cancer pain control.

Cannabis use trajectories over time in relation to minority stress and gender among sexual and gender minority people.

Substance use disparities among sexual and gender minority (SGM) people are attributed to minority stress, but few studies have examined minority stress and cannabis use over time or investigated differences in cannabis use trajectories by less-studied gender subgroups. We examined if longitudinal cannabis use trajectories are related to baseline minority stressors and if gender differences persisted after accounting for minority stress. Cannabis use risk was measured annually over four years (2017-2021) within a longitudinal cohort study of SGM adults in the United States (N = 11,813). Discrimination and victimization, internalized stigma, disclosure and concealment, and safety and acceptance comprised minority stress (n = 5,673). Latent class growth curve mixture models identified five cannabis use trajectories: 'low or no risk', 'low moderate risk', 'high moderate risk', 'steep risk increase', and 'highest risk'. Participants who reported past-year discrimination and/or victimization at baseline had greater odds of membership in any cannabis risk category compared to the 'low risk' category (odds ratios [OR] 1.17-1.33). Internalized stigma was related to 'high moderate' and 'highest risk' cannabis use (ORs 1.27-1.38). After accounting for minority stress, compared to cisgender men, gender expansive people and transgender men had higher odds of 'low moderate risk' (ORs 1.61, 1.67) or 'high moderate risk' (ORs 2.09, 1.99), and transgender men had higher odds of 'highest risk' (OR 2.36) cannabis use. This study indicates minority stress is related to prospective cannabis use risk trajectories among SGM people, and transgender men and gender expansive people have greater odds of trajectories reflecting cannabis use risk.

Artificial intelligence-based epigenomic, transcriptomic and histologic signatures of tobacco use in oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) biomarker studies rarely employ multi-omic biomarker strategies and pertinent clinicopathologic characteristics to predict mortality. In this study we determine for the first time a combined epigenetic, gene expression, and histology signature that differentiates between patients with different tobacco use history (heavy tobacco use with ≥10 pack years vs. no tobacco use). Using The Cancer Genome Atlas (TCGA) cohort (n = 257) and an internal cohort (n = 40), we identify 3 epigenetic markers (GPR15, GNG12, GDNF) and 13 expression markers (IGHA2, SCG5, RPL3L, NTRK1, CD96, BMP6, TFPI2, EFEMP2, RYR3, DMTN, GPD2, BAALC, and FMO3), which are dysregulated in OSCC patients who were never smokers vs. those who have a ≥ 10 pack year history. While mortality risk prediction based on smoking status and clinicopathologic covariates alone is inaccurate (c-statistic = 0.57), the combined epigenetic/expression and histologic signature has a c-statistic = 0.9409 in predicting 5-year mortality in OSCC patients.