Project description:Genome wide DNA methylation profiling of IDU+/HCV+ and IDV-/HCV- individuals for DNA samples extracted from peripheral blood. The Illumina Infinium Human DNA methylation 450 Beadchip was used to obtain DNA methylation profiles across approximately 480,000 CpGs. Samples included 216 IDU+/HCV+ and 170 IDU-/HCV- individuals. The goal was to identify genome-wide differentially methylated CpG sites between IDU+/HCV+ and IDU-/HCV- samples.
Project description:This dataset is used as replication set for Illumina 450k. Genome wide DNA methylation profiling of IDU+/HCV+ and IDV-/HCV- individuals for DNA samples extracted from peripheral blood. The Illumina Infinium Human DNA methylation 450 Beadchip was used to obtain DNA methylation profiles across approximately 480,000 CpGs. Samples included 216 IDU+/HCV+ and 170 IDU-/HCV- individuals. The goal was to identify genome-wide differentially methylated CpG sites between IDU+/HCV+ and IDU-/HCV- samples.
Project description:The illicit use of synthetic opioids such as fentanyl has led to a serious public health crisis in the US. People with opioid use disorder are more likely to contract infections such as HIV and viral hepatitis and experience more severe disease. While several drugs of abuse are known to enhance viral replication and to suppress immunologic responses, the effects of synthetic opioids on HIV pathogenesis have not been investigated thoroughly. Thus, we examined the impact of fentanyl on macrophage cell line U937 and monocyte derived macrophage cells and chemokine receptor expression in vitro.
Project description:Methcathinone (ephedrone) is relatively easily accessible for abuse. Its users develop an extrapyramidal syndrome and it is not known if this is caused by methcathinone itself, by side-ingredients (manganese), or both. In the present study we aimed to clarify molecular mechanisms underlying this condition. We used microarrays to analyze whole genome gene expression patterns of peripheral blood from 20 methcathinone users and 20 matched controls. Gene expression profile data were analyzed by Bayesian modelling and functional annotation. Of 28,869 genes on the microarrays, 326 showed statistically significant differential expression with FDR adjusted p-values below 0.05. Quantitative RT-PCR confirmed differential expression for the most of the genes selected for validation. Functional annotation and network analysis indicated activation of a gene network that included immunological disease, cellular movement and cardiovascular disease functions (enrichment score 42). As HIV and HCV infections were confounding factors, we performed additional stratification of patients. A similar functional activation of the “immunological disease” category was evident when we compared patients according to injection status (past versus current users, balanced for HIV and HCV infection). However, this difference was not large therefore the major effect was related to the HIV status of the patients. Mn-methcathinone abusers have blood RNA expression patterns that mostly reflect their HIV and HCV infections. However, despite the strong confounding effect from infection, some modest drug abuse effects on gene expression were detected. 40 samples, 20 healthy volunteers and 20 illicit methcathinone users
Project description:The aim of this study was to identify differential gene and protein expression associated with GBV-C that may be of importance in reduction of HCV-related liver disease. GB virus C (GBV-C) infection leads to improved outcomes in human immunodeficiency virus (HIV) infection. Furthermore, GBV-C has been shown to reduce hepatitis C virus (HCV)-related liver disease in HCV/HIV co-infection.
Project description:The aim of this study was to identify differential gene and protein expression associated with GBV-C that may be of importance in reduction of HCV-related liver disease. GB virus C (GBV-C) infection leads to improved outcomes in human immunodeficiency virus (HIV) infection. Furthermore, GBV-C has been shown to reduce hepatitis C virus (HCV)-related liver disease in HCV/HIV co-infection. We aimed to identify differential gene expression associated with GBV-C in HCV/HIV co-infection by comparing RNA expression from liver biopsies of HCV/HIV co-infected patients with and without GBV-C infection. Liver biopsies were obtained from 10 Patients with HCV/HIV co-infection; 4 of these patients were positive for GBV-C infection and 6 were negative for GBV-C infection. The tissue was stored in RNAlater and RNA was extracted for hybridisation to Affymetrix Human Genome U133 plus 2.0 microarrays at the University of Texas Medical Branch Molecular Genomics Core Laboratory. The data was analysed for genes differentially expressed between GBV-C positive and negative patients using Partek Genomics suite and applying a custom CDF file (Hs133P_Hs_UG_8), available from Molecular and Behavioural Neuroscience Institute, University of Michigan.
Project description:Chronic liver disease is becoming a leading cause of illness and mortality in people living with human immunodeficiency virus (HIV) (PLWH) undergoing suppressive anti-retroviral therapy. Its main etiology has been reported to be coinfection with hepatitis B (HBV) and C (HCV) viruses. Accumulating evidence indicate chronic liver inflammation and fibrosis can potentially lead to the development of hepatocellular carcinoma (HCC). Therefore, monitoring of the disease progression in PLWH is required. The present study aimed to explore the plasma protein profiles of patients with HIV infection and those coinfected with HBV and HCV using shotgun proteomics.
Project description:Smoking is common in people who live with HIV infection and has significant adverse effects on HIV outcomes. The impacts of smoking on methylome has been well established in non-HIV populations. However, the smoking’s effects on host methylome in HIV-positive population has not been investigated and it is unknown if smoking-associated DNA methylation link to HIV outcomes. In this study, we applied machine learning methods selected smoking-associated DNA methylation features to predict HIV related frailty and mortality.
