Bradley E. Aouizerat

Abstract

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.

Abstract

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.

Abstract

Within-host HIV populations continually diversify during untreated infection, and this diversity persists within infected cell reservoirs during antiretroviral therapy (ART). Achieving a better understanding of on-ART proviral evolutionary dynamics, and a better appreciation of how the overall persisting pool of (largely genetically defective) proviruses differs from the much smaller replication-competent HIV reservoir, is critical to HIV cure efforts. We reconstructed within-host HIV evolutionary histories in blood from seven participants of the Women’s Interagency HIV Study who experienced HIV seroconversion, and used these data to characterize the diversity, lineage origins, and ages of proviral env-gp120 sequences sampled longitudinally up to 12 years on ART. We also studied HIV sequences emerging from the reservoir in two participants. We observed that proviral clonality generally increased over time on ART, with clones frequently persisting long term. While on-ART proviral integration dates generally spanned the duration of untreated infection, HIV emerging in plasma was exclusively younger (i.e., dated to the years immediately pre-ART). The genetic and age distributions of distinct proviral sequences remained stable during ART in all but one participant, in whom there was evidence that younger proviruses had been preferentially eliminated after 12 years on ART. Analysis of the gag region in three participants corroborated our env-gp120-based observations, indicating that our observations are not influenced by the HIV region studied. Our results underscore the remarkable genetic stability of the distinct proviral sequences that persist in blood during ART. Our results also suggest that the replication-competent HIV reservoir is a genetically restricted, younger subset of this overall proviral pool. IMPORTANCE Characterizing the genetically diverse HIV sequences that persist in the reservoir despite antiretroviral therapy (ART) is critical to cure efforts. Our observations confirm that proviruses persisting in blood on ART, which are largely genetically defective, broadly reflect the extent of within-host HIV evolution pre-ART. Moreover, on-ART clonal expansion is not appreciably accompanied by the loss of distinct proviral lineages. In fact, on-ART proviral genetic composition remained stable in all but one participant, in whom, after 12 years on ART, proviruses dating to around near ART initiation had been preferentially eliminated. We also identified recombinant proviruses between parental sequence fragments of different ages. Though rare, such sequences suggest that reservoir cells can be superinfected with HIV from another infection era. Overall, our finding that the replication-competent reservoir in blood is a genetically restricted, younger subset of all persisting proviruses suggests that HIV cure strategies will need to eliminate a reservoir that differs in key respects from the overall proviral pool.

Abstract

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.

Abstract

Co-occurrence of injection drug use (IDU) and hepatitis C virus infection (HCV) is common in people living with HIV (PLWH) and leads to significantly increased mortality. Epigenetic clocks derived from DNA methylation (DNAm) are associated with disease progression and all-cause mortality. In this study, we hypothesized that epigenetic age mediates the relationships between the co-occurrence of IDU and HCV with mortality risk among PLWH. We tested this hypothesis in the Veterans Aging Cohort Study (n = 927) by using four established epigenetic clocks of DNAm age (i.e., Horvath, Hannum, Pheno, Grim). Compared to individuals without IDU and HCV (IDU-HCV-), participants with IDU and HCV (IDU+HCV+) showed a 2.23-fold greater risk of mortality estimated using a Cox proportional hazards model (hazard ratio: 2.23; 95% confidence interval: 1.62–3.09; p = 1.09E–06). IDU+HCV+ was associated with a significantly increased epigenetic age acceleration (EAA) measured by 3 out of 4 epigenetic clocks, adjusting for demographic and clinical variables (Hannum: p = 8.90E–04, Pheno: p = 2.34E–03, Grim: p = 3.33E–11). Furthermore, we found that epigenetic age partially mediated the relationship between IDU+HCV+ and all-cause mortality, up to a 13.67% mediation proportion. Our results suggest that comorbid IDU with HCV increases EAA in PLWH that partially mediates the increased mortality risk.

Abstract

Purpose: To examine if gut microbial taxa abundances and predicted functional pathways correlate with Bristol Stool Form Scale (BSFS) classification at the end of neoadjuvant chemotherapy and radiation therapy (CRT) for rectal cancer. Methods: Rectal cancer patients (n = 39) provided stool samples for 16S rRNA gene sequencing. Stool consistency was evaluated using the BSFS. Gut microbiome data were analyzed using QIIME2. Correlation analysis were performed in R. Results: At the genus level, Staphylococcus positively correlates (Spearman’s rho = 0.26), while Anaerofustis, Roseburia, Peptostreptococcaceae unclassified, Ruminococcaceae UBA1819, Shuttleworthia, Ca. Soleaferrea, Anaerostignum, Oscillibacter, and Akkermansia negatively correlate with BSFS scores (Spearman’s rho −0.20 to −0.42). Predicted pathways, including mycothiol biosynthesis and sucrose degradation III (sucrose invertase), were positively correlated with BSFS (Spearman’s rho = 0.03–0.21). Conclusion: The data support that in rectal cancer patients, stool consistency is an important factor to include in microbiome studies. Loose/liquid stools may be linked to Staphylococcus abundance and to mycothiol biosynthesis and sucrose degradation pathways.

Abstract

Aims/Hypothesis: Our prior analysis of the Diabetes Prevention Program study identified a subset of five miRNAs that predict incident type 2 diabetes. The purpose of this study was to identify mRNAs and biological pathways targeted by these five miRNAs to elucidate potential mechanisms of risk and responses to the tested interventions. Methods: Using experimentally validated data from miRTarBase version 8.0 and R (2021), we identified mRNAs with strong evidence to be regulated by individual or combinations of the five predictor miRNAs. Overrepresentation of the mRNA targets was assessed in pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation database. Results: The five miRNAs targeted 167 pathways and 122 mRNAs. Nine of the pathways have known associations with type 2 diabetes: Insulin signaling, Insulin resistance, Diabetic cardiomyopathy, Type 2 diabetes, AGE-RAGE signaling in diabetic complications, HIF-1 signaling, TGF-beta signaling, PI3K/Akt signaling, and Adipocytokine signaling pathways. Vascular endothelial growth factor A (VEGFA) has prior genetic associations with risk for type 2 diabetes and was the most commonly targeted mRNA for this set of miRNAs. Conclusions/Interpretation: These findings show that miRNA predictors of incident type 2 diabetes target mRNAs and pathways known to underlie risk for type 2 diabetes. Future studies should evaluate miRNAs as potential therapeutic targets for preventing and treating type 2 diabetes.

Abstract

CONTEXT: MicroRNAs (miRs) are short (ie, 18-26 nucleotide) regulatory elements of messenger RNA translation to amino acids. OBJECTIVE: The purpose of this study was to assess whether miRs are predictive of incident type 2 diabetes (T2D) in the Diabetes Prevention Program (DPP) trial. METHODS: This was a secondary analysis (n = 1000) of a subset of the DPP cohort that leveraged banked biospecimens to measure miRs. We used random survival forest and Lasso methods to identify the optimal miR predictors and the Cox proportional hazards to model time to T2D overall and within intervention arms. RESULTS: We identified 5 miRs (miR-144, miR-186, miR-203a, miR-205, miR-206) that constituted the optimal predictors of incident T2D after adjustment for covariates (hazard ratio [HR] 2.81, 95% CI 2.05, 3.87; P < .001). Predictive risk scores following cross-validation showed the HR for the highest quartile risk group compared with the lowest quartile risk group was 5.91 (95% CI 2.02, 17.3; P < .001). There was significant interaction between the intensive lifestyle (HR 3.60, 95% CI 2.50, 5.18; P < .001) and the metformin (HR 2.72; 95% CI 1.47, 5.00; P = .001) groups compared with placebo. Of the 5 miRs identified, 1 targets a gene with prior known associations with risk for T2D. CONCLUSION: We identified 5 miRs that are optimal predictors of incident T2D in the DPP cohort. Future directions include validation of this finding in an independent sample in order to determine whether this risk score may have potential clinical utility for risk stratification of individuals with prediabetes, and functional analysis of the potential genes and pathways targeted by the miRs that were included in the risk score.

Abstract

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.

Abstract

Background: Accurate prediction of risk for chronic diseases like type 2 diabetes (T2D) is challenging due to the complex underlying etiology. Integration of more complex data types from sensors and leveraging technologies for collection of -omics datasets may provide greater insights into the specific risk profile for complex diseases. Methods: We performed a literature review to identify feature selection methods and machine learning models for prediction of weight loss in a previously completed clinical trial (NCT02278939) of a behavioral intervention for weight loss in Filipinos at risk for T2D. Features included demographic and clinical characteristics, dietary factors, physical activity, and transcriptomics. Results: We identified four feature selection methods: Correlation-based Feature Subset Selection (CfsSubsetEval) with BestFirst, Kolmogorov–Smirnov (KS) test with correlation featureselection (CFS), DESeq2, and max-relevance-min-relevance (MRMR) with linear forward search and mutual information (MI) and four machine learning algorithms: support vector machine, decision tree, random forest, and extra trees that are applicable to prediction of weight loss using the specified feature types. Conclusion: More accurate prediction of risk for T2D and other complex conditions may be possible by leveraging complex data types from sensors and -omics datasets. Emerging methods for feature selection and machine learning algorithms make this type of modeling feasible.