INTEGRATIVE MULTI-OMICS REVEAL A TWO-ANALYTE BLOOD-BASED SIGNATURE FOR TB DIAGNOSIS IN ADVANCED HIV
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA701263 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13679723.fastq.gz | Fastqsanger.gz | |||
| SRR13679724.fastq.gz | Fastqsanger.gz | |||
| SRR13679725.fastq.gz | Fastqsanger.gz | |||
| SRR13679726.fastq.gz | Fastqsanger.gz | |||
| SRR13679727.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 56 |
Similar Datasets
Project description:Tuberculosis (TB) accounts for disproportionate morbidity and mortality among persons living with HIV (PLWH). Conventional methods of TB diagnosis, including smear microscopy and Xpert MTB/RIF, have lower sensitivity in PLWH. Novel high-throughput approaches, such as miRNAomics and metabolomics, may advance our ability to diagnose subclinical and difficult to diagnose TB, especially in very advanced HIV. We conducted a case-control study leveraging REMEMBER, a multi-country, open-label randomized controlled trial comparing 4-drug empiric standard TB treatment with isoniazid preventive therapy in PLWH initiating ART with CD4 cell counts <50 cells/uL. Twenty-three cases of incident TB were site-matched with 32 controls to identify miRNAs, cytokines/chemokines, and metabolites associated with the development of newly diagnosed TB in PLWH. Differentially expressed miRNA analysis revealed 11 altered miRNAs with a fold change higher than ±1.4 in cases relative to controls (p<0.05). Differentially altered metabolite analysis showed no significant alterations in metabolites between cases and controls. We found higher TNFα and IP-10/CXCL10 in cases (p=0.011, p=0.0005), and higher MDC/CCL22 in controls (p=0.0072). A decision tree algorithm identified gamma-glutamylthreonine and hsa-miR-215-5p as the optimal variables to classify incident TB cases (AUC 0.965). hsa-miR-215-5p, which targets genes in the TGF-β signaling pathway, was downregulated in cases. Gamma-glutamylthreonine, a breakdown product of protein catabolism, was less abundant in cases. To our knowledge, this is one of the first uses of a multi-omics approach to identify incident TB in a severely immunosuppressed PLWH study.
2021-06-30 | GSE166557 | GEO
Project description:Background: Tuberculosis (TB) among persons living with HIV (PLWH) poses diagnostic challenges. Although several transcriptional signatures have recently been identified as promising tool for TB diagnosis, data are limited in persons with advanced HIV. Methodology: Reads were aligned to the human transcriptome (GRCh38 version 100), comprising both mRNA and ncRNA, with Salmon v1.2.0. A Random Forest algorithm with “leave-one-out” cross-validation was applied in the variance stabilizing transformation gene expression. The identified biomarkers were compared to previous TB transcriptional signatures using the Area Under the Curve (AUC). Results: Functional analysis indicated that common upregulated pathways in TB/HIV patients were associated with Toll-like receptor cascades and neutrophil degranulation. A machine learning decision tree algorithm identified the expression values from RAB20 and INSL3 as most informative for classifying TB status in PLWH. Only these two genes were able to correctly classify all samples.
2021-02-02 | GSE162164 | GEO
Project description:A two-gene signature for diagnosis of tuberculosis in persons with advanced HIV
| PRJNA680771 | ENA
Project description:Tuberculosis (TB) accounts for disproportionate morbidity and mortality among persons living with HIV (PLWH). Conventional methods of TB diagnosis, including smear microscopy and Xpert MTB/RIF, have lower sensitivity in PLWH. Novel high-throughput approaches, such as miRNAomics and metabolomics, may advance our ability to recognize subclinical and difficult-to-diagnose TB, especially in very advanced HIV. We conducted a case-control study leveraging REMEMBER, a multi-country, open-label randomized controlled trial comparing 4-drug empiric standard TB treatment with isoniazid preventive therapy in PLWH initiating antiretroviral therapy (ART) with CD4 cell counts <50 cells/μL. Twenty-three cases of incident TB were site-matched with 32 controls to identify microRNAs (miRNAs), metabolites, and cytokines/chemokines, associated with the development of newly diagnosed TB in PLWH. Differentially expressed miRNA analysis revealed 11 altered miRNAs with a fold change higher than 1.4 or lower than -1.4 in cases relative to controls (p<0.05). Our analysis revealed no differentially abundant metabolites between cases and controls. We found higher TNFα and IP-10/CXCL10 in cases (p=0.011, p=0.0005), and higher MDC/CCL22 in controls (p=0.0072). A decision-tree algorithm identified gamma-glutamylthreonine and hsa-miR-215-5p as the optimal variables to classify incident TB cases (AUC 0.965; 95% CI 0.925-1.000). hsa-miR-215-5p, which targets genes in the TGF-β signaling pathway, was downregulated in cases. Gamma-glutamylthreonine, a breakdown product of protein catabolism, was less abundant in cases. To our knowledge, this is one of the first uses of a multi-omics approach to identify incident TB in severely immunosuppressed PLWH.
| S-EPMC8217878 | biostudies-literature
Project description:Tuberculosis (TB) is the major cause of death in HIV-infected individuals. However, diagnosis of TB in HIV remains challenging. The aim of this study was to determine the performance of published gene signatures in distinguishing active TB in advanced HIV. We concluded that gene expression of FcGR1A and BATF2, and plasma protein levels of IFNγ and CXCL10 can singly classify active TB in HIV-infected with advanced HIV.
2018-05-23 | GSE107104 | GEO
Project description:The pathogenesis of Colorectal cancer (CRC) metastasis remains unclear.We collect clinical data from our center and use Integrative omics to analyze and predict candidate biomarkers of colorectal cancer and distant metastasis.
| 2743637 | ecrin-mdr-crc
Project description:BACKGROUND:People with advanced HIV (CD4<50) remain at high risk of TB or death despite the initiation of antiretroviral therapy. We aimed to identify immunological profiles that were most predictive of incident TB disease and death. METHODS:The REMEMBER randomized clinical trial enrolled 850 participants with HIV (CD4<50 cells/µL) at ART initiation to receive either empiric TB treatment or isoniazid preventive therapy (IPT). A case-cohort study (n=257) stratified by country and treatment arm was performed. Cases were defined as incident TB or all-cause death within 48 weeks after ART initiation. Using multiplexed immunoassay panels and ELISA, 26 biomarkers were assessed in plasma. RESULTS:52 (6.1%) of 850 participants developed TB; 47 (5.5%) died (13 of whom had antecedent TB). Biomarkers associated with incident TB overlapped with those associated with death (IL-1?, IL-6). Biomarker levels declined over time in individuals with incident TB while remaining persistently elevated in those who died. Dividing the cohort into development and validation sets, the final model of 6 biomarkers (CXCL10, IL-1?, IL-10, sCD14, TNF-?, and TNF-?) achieved a sensitivity of 0.90 (95% CI: 0.87-0.94) and a specificity of 0.71(95% CI: 0.68-0.75) with an area under the curve (AUC) of 0.81 (95% CI: 0.78-0.83) for incident TB. CONCLUSION:Among people with advanced HIV, a parsimonious inflammatory biomarker signature predicted those at highest risk for developing TB despite initiation of ART and TB preventive therapies. The signature may be a promising stratification tool to select patients who may benefit from increased monitoring and novel interventions.
| S-EPMC7744990 | biostudies-literature
Project description:Interventions: Gold Standard:Pathological diagnosis;Index test:Construction of an accurate diagnosis system for colorectal cancer basing on omics research of intestinal microecosystem
Primary outcome(s): Intestinal flora
Study Design: Factorial
| 2694490 | ecrin-mdr-crc
Project description:Characterization of Tuberculosis (TB) progression, diagnosis and treatment response with blood transcriptional RNA-seq analyses. Focus and underlying host immunological response and identification of new signatures for TB early diagnosis and treatment monitoring response.
2021-09-04 | GSE157657 | GEO
Project description:Background: Transcriptomic signatures for tuberculosis (TB) have been proposed and represent a promising diagnostic tool. Data remain limited in persons with advanced HIV. Methods: We enrolled 30 patients with advanced HIV (CD4 <100 cells/mm3) in India; 16 with active TB and 14 without. Whole-blood RNA sequencing was performed; these data were merged with a publicly available dataset from Uganda (n = 33; 18 with TB and 15 without). Transcriptomic profiling and machine learning algorithms identified an optimal gene signature for TB classification. Receiver operating characteristic analysis was used to assess performance. Results: Among 565 differentially expressed genes identified for TB, 40 were shared across India and Uganda cohorts. Common upregulated pathways reflect Toll-like receptor cascades and neutrophil degranulation. The machine-learning decision-tree algorithm selected gene expression values from RAB20 and INSL3 as most informative for TB classification. The signature accurately classified TB in discovery cohorts (India AUC 0.95 and Uganda AUC 1.0; p < 0.001); accuracy was fair in external validation cohorts. Conclusions: Expression values of RAB20 and INSL3 genes in peripheral blood compose a biosignature that accurately classified TB status among patients with advanced HIV in two geographically distinct cohorts. The functional analysis suggests pathways previously reported in TB pathogenesis.
| S-EPMC7937880 | biostudies-literature