Dataset Information

Elucidating the Gene Signatures and Immune Cell Types in HIV-Infected Immunological Non-Responders by Bioinformatics Analyses.

ABSTRACT:

Objective

Numerous studies have reported on the pathogenesis of poor immune reconstitution (PIR) after antiretroviral treatment in human immunodeficiency virus (HIV) patients. However, fewer studies focused on both immune-related genes (IRGs) and immune cells, and the correlation between IRGs and immune cells was evaluated via bioinformatics analyses.

Methods

Gene expression profiling of GSE143742 from the Gene Expression Omnibus (GEO) database was analyzed to get differentially expressed immune-related genes (DEIRGs). The enrichment analysis and protein-protein interaction (PPI) networks of DEIRGs were established. The relative fractions of 22 immune cell types were detected using the "CIBERSORT". The correlation analysis between DEIRGs and immune cells was constructed to discover the potential IRGs associated with immune cells. A logistic regression diagnostic model was built, and a receiver operating characteristic (ROC) curve was performed to evaluate the model's diagnostic efficacy. The CMap database was used to find molecules with therapeutic potential. RT-qPCR was used to verify the expression of the hub DEIRGs.

Results

We identified eight types of significantly changed immune cells and five hub IRGs in INRs. The DEIRGs were mainly enriched in lymphocyte activation, receptor-ligand activity, and T cell receptor signaling pathway. The correlation analysis showed that the expression of TNF, CXCR4 and TFRC correlate with CD8 cells, resting mast cells, activated NK cells, and naïve CD4 cells in INRs. Meanwhile, TFRC and IL7R relate to activated NK cells and resting memory CD4 cells respectively in IRs. A diagnostic model was constructed using multiple logistic regression and nine small molecules were identified as possible drugs.

Conclusion

In this study, we suggested that the process of PIR might be related to TNF, CXCR4, TFRC, CD48, and IL7R. And these IRGs play roles in regulating immune-competent cells. And our constructed diagnostic model has excellent effectiveness. Moreover, some small-molecule drugs are screened to alleviate PIR.

SUBMITTER: Xiao Q

PROVIDER: S-EPMC9741855 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Elucidating the Gene Signatures and Immune Cell Types in HIV-Infected Immunological Non-Responders by Bioinformatics Analyses.

Xiao Qing Q Han Junyan J Yu Fengting F Yan Liting L Li Qun Q Lao Xiaojie X Zhao Hongxin H Zhang Fujie F

International journal of general medicine 20221207

<h4>Objective</h4>Numerous studies have reported on the pathogenesis of poor immune reconstitution (PIR) after antiretroviral treatment in human immunodeficiency virus (HIV) patients. However, fewer studies focused on both immune-related genes (IRGs) and immune cells, and the correlation between IRGs and immune cells was evaluated via bioinformatics analyses.<h4>Methods</h4>Gene expression profiling of GSE143742 from the Gene Expression Omnibus (GEO) database was analyzed to get differentially e ...[more]

PMID: 36514742

Similar Datasets

Project description:PurposeHIV-infected immunological non-responders (INRs) failed to achieve the normalization of CD4+ T cell counts despite their undetectable viral load. INRs have an increased risk of clinical progressions of Acquired Immunodeficiency Syndrome (AIDS) and non-AIDS events, accompanied by higher mortality rates than immunological responders (IRs). This study aimed to discover the genes, which help to distinguish INRs from IRs and explore the possible mechanism of INRs.MethodsScreening DEGs between INRs and IRs using GEO microarray dataset GSE143742. DEG biological functions were investigated using GO and KEGG analysis. DEGs and WGCNA linked modules were intersected to find common genes. Key genes were identified using SVM-RFE and LASSO regression models. ROC analysis was done to evaluate key gene diagnostic effectiveness using GEO database dataset GSE106792. Cytoscape created a miRNA-mRNA-TF network for diagnostic genes. CIBERSORT and flow cytometry examined the INRs and IRs immune microenvironments. In 10 INR and 10 IR clinical samples, diagnostic gene expression was verified by RT-qPCR and Western blot.ResultsWe obtained 190 DEGs between the INR group and IR group. Functional enrichment analysis found a significant enrichment in mitochondria and apoptosis-related pathways. CD69 and ZNF207 were identified as potential diagnostic genes. CD69 and ZNF207 shared a transcription factor, NCOR1, in the miRNA-mRNA-TF network. Immune microenvironment analysis by CIBERSORT showed that IRs had a higher level of resting memory CD4+ T cells, lower level of activated memory CD4+ T cells and resting dendritic cells than INRs, as confirmed by flow cytometry analysis. In addition, CD69 and ZNF207 were correlated with immune cells. Experiments confirmed the expression of the diagnostic genes in INRs and IRs.ConclusionCD69 and ZNF207 were identified as potential diagnostic genes to discriminate INRs from IRs. Our findings offered new clues to diagnostic and therapeutic targets for INRs.

Project description:BackgroundCD4+ T cell counts in certain human immunodeficiency virus (HIV)-infected patients called immunological non-responders (INRs) could not return to a normal level even with sustained antiretroviral therapy (ART) because of persistent immune activation, which is associated with pro-inflammatory cytokines production and an altered intestinal microbiome profile. Changes in gut bacterial composition have been linked to low CD4+ T cell counts in HIV-infected individuals. However, the association between CD4+ T cell counts and gut microbiota community composition and cytokines levels in INRs (CD4+ T cell counts < 500 cells/μL) from Yunnan Province, China, has not been previously investigated.MethodsTo address this issue, we carried out a cross-sectional study of 34 HIV-infected INRs. The patients were divided into CD4 count > 200 cells/μL group and CD4 count < 200 cells/μL group. The gut microbiota composition of each subject was analyzed by 16S rRNA gene sequencing. We also compared CD8+ T cell counts, pro-inflammatory cytokines levels, and nutritional status between the two groups.ResultsCompared to INRs with CD4 count > 200 cells/μL, those with CD4 count < 200 cells/μL had a lower CD4/CD8 ratio, lower nutritional status and higher serum levels of tumor necrosis factor (TNF)-α, interferon-γ-inducible protein (IP)-10 and interleukin (IL)-1α. Ruminococcaceae was less abundant in the CD4 count < 200 cells/μL group than in the CD4 count > 200 cells/μL group, and difference in alpha diversity was observed between the two groups. Moreover, CD4+ T cell counts were negatively associated with TNF-α and IL-1α levels and positively associated with the relative abundance of Ruminococcaceae.ConclusionsOur study demonstrated that lower CD4+ T cell counts in INRs are associated with a reduced abundance of Ruminococcaceae in the gut and elevated serum pro-inflammatory cytokines levels. Thus, interventions targeting gut microbiota to increase CD4+ T cell counts are a potential strategy for promoting immune reconstitution in HIV-infected INRs.

Project description:The prevalence of AIDS and mortality rates among HIV-infected individuals in Guangxi remain relatively high, potentially due to impaired CD4 + cell recovery. This study aims to identify factors hindering CD4 + cell recovery in people living with HIV. We conducted a retrospective study on people living with HIV in Guangxi, China, with data collection extending to the end of 2023. CD4 + T cells were categorized into "immunological responders" and "non-responders" based on CD4 + cell recovery after treatment. Multivariate logistic regression was used to analyze factors associated with the development of immunological non-responders. Recovery of CD4 + T lymphocytes was assessed using the Generalized Additive Mixed Model (GAMM) and Generalized Estimating Equations (GEE). Additionally, multivariate Cox regression identified factors influencing survival rates. Our findings indicated a 52.44% incidence of immunological non-responders after two years of treatment. Factors such as age, sex, education, occupation, infection route, pre-treatment CD4 + T cell count, HIV subtype, and treatment regimen were linked to immunological non-response. Specifically, male gender, education up to high school, farming occupation, heterosexual transmission, CRF01_AE subtype, pre-treatment CD4 + T cell count < 200/µL, and the 3TC + EFV + TDF regimen were identified as significant risk factors. Statistically significant differences in CD4 + T lymphocyte recovery rates were observed among different HIV subtypes (P < 0.05). Beyond age, sex, ethnicity, occupation, subtype, and treatment regimen, being an immunological non-responder was found to be a risk factor for both mortality and accelerated disease progression. The study highlights the complexity of factors affecting CD4 + cell recovery post-HIV treatment in Guangxi and underscores the need for vigilant clinical monitoring of people living with HIV, particularly those with low pre-treatment CD4 + T cell levels.

Dataset Information

Elucidating the Gene Signatures and Immune Cell Types in HIV-Infected Immunological Non-Responders by Bioinformatics Analyses.

Objective

Methods

Results

Conclusion

Publications

Elucidating the Gene Signatures and Immune Cell Types in HIV-Infected Immunological Non-Responders by Bioinformatics Analyses.

Similar Datasets

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