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A two-gene signature for diagnosis of tuberculosis in persons with advanced HIV

ABSTRACT: A two-gene signature for diagnosis of tuberculosis in persons with advanced HIV

PROVIDER: PRJNA680771 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR13142271_1.fastq.gz	Fastqsanger.gz
	SRR13142271_2.fastq.gz	Fastqsanger.gz
	SRR13142272_1.fastq.gz	Fastqsanger.gz
	SRR13142272_2.fastq.gz	Fastqsanger.gz
	SRR13142273_1.fastq.gz	Fastqsanger.gz

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A two-gene signature for diagnosis of tuberculosis in persons with advanced HIV

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.

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INTEGRATIVE MULTI-OMICS REVEAL A TWO-ANALYTE BLOOD-BASED SIGNATURE FOR TB DIAGNOSIS IN ADVANCED HIV

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.

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INTEGRATIVE MULTI-OMICS REVEAL A TWO-ANALYTE BLOOD-BASED SIGNATURE FOR TB DIAGNOSIS IN ADVANCED HIV

Project description:INTEGRATIVE MULTI-OMICS REVEAL A TWO-ANALYTE BLOOD-BASED SIGNATURE FOR TB DIAGNOSIS IN ADVANCED HIV

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Increased expression of immune regulatory mediators independently detects tuberculosis in advanced HIV

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.

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A Two-Gene Signature for Tuberculosis Diagnosis in Persons With Advanced HIV.

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.

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