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Identification of an eight-protein biosignature for the diagnosis of tuberculosis II

ABSTRACT: Identification of an eight-protein biosignature for the diagnosis of tuberculosis II

PROVIDER: PRJNA594955 | ENA |

REPOSITORIES: ENA

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Identification of an eight-protein biosignature for the diagnosis of tuberculosis II

Project description:Mycobacterium tuberculosis (Mtb) antigen-specific cellular response is promising for detectionof Mtb infection, but not efficient for diagnosis of TB. We firstly identified 16 TB disease-specific protein markers measured in the culture supernatant of Mtb-stimulated whole blood using a 640 human proteins array, the highest throughput antibody-based protein array available at the time when we did this study. Potential TB-related proteins were then analyzed across three different patient cohorts comprised of healthy controls, LTBI, non-TB pneumonia, and TB patients to evaluate how the biomarkers performed in diagnosing TB in the real clinical setting. The data finally reveal an eight-protein biosignature of TB.

2019-12-12 | GSE141848 | GEO

Identification of an eight-protein biosignature for the diagnosis of tuberculosis

Project description:Identification of an eight-protein biosignature for the diagnosis of tuberculosis

| PRJNA550450 | ENA

Identification of an eight-protein biosignature for the diagnosis of tuberculosis

2019-06-25 | GSE133249 | GEO

Identification of novel salivary candidate protein biomarkers for tuberculosis diagnosis: a preliminary biomarker discovery study.

Project description:Abstract Background There is an urgent need for new, accurate, rapid, and affordable tuberculosis (TB) diagnostic tests. The aim of the present study was to use mass spectrometry to identify new preliminary candidate TB diagnostic protein biomarkers in saliva obtained from individuals with TB, and patients with other respiratory diseases (ORD). Methods Saliva samples were collected from 22 individuals who self-presented with symptoms suggestive of TB as part of a larger TB biomarker project. Purified salivary proteins were subjected to tryptic digestion peptides were analysed using a QExactive Orbitrap Mass Spectrometer. Identified proteins were subjected to gene ontology and ingenuity pathway analysis for functional enrichment analysis. Results 26 of the 652 identified proteins significantly discriminated individuals with TB from those with ORD after Benjamini Hochberg correction (5% FDR), with five of these proteins diagnosing TB with an AUC ≥ 0.80. A 5-protein biosignature comprising of P01011, Q8NCW5, P28072, A0A2Q2TTZ9, and Q99574 diagnosed TB with an AUC of 1.00 (95% CI, 1.00-1.00), sensitivity of 100% (95% CI, 76.2-100%) and specificity of 90.9% (95% CI, 58.7-99.8%) after leave-one-out cross validation. Conclusions We identified novel candidate salivary protein biomarkers and biosignatures with strong potential as TB diagnostic candidates. Our results are preliminary and require validation in larger studies.

2021-08-05 | PXD027294 | Pride

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Project description:eight coral species Transcriptome or Gene expression

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RNA-seq analysis of the eight Drosophila SR protein family members

Project description:Using RNA-seq, we characterize the global AS regulation of the eight Drosophila SR protein family members

2014-11-23 | GSE63263 | GEO

Blood transcriptomics for diagnosis, risk, and treatment monitoring in tuberculosis reveal the evolution and resolution of TB disease: Does one signature capture all?

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

Eight shrimp farm soil sediment metagenomes

Project description:Eight shrimp farm soil sediment metagenomes

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Transcriptional profiles predict treatment outcome in patients with tuberculosis and diabetes at diagnosis and at two weeks after initiation of anti-tuberculosis treatment

Project description:Globally, the anti-tuberculosis (TB) treatment success rate is approximately 85%, with treatment failure, relapse and death occurring in a significant proportion of pulmonary TB patients. Treatment success rates are lower among people with diabetes mellitus (DM). Predicting treatment failure early after diagnosis would allow early treatment adaptation and may improve global TB control. Methods Samples were collected in a longitudinal cohort study of adult TB patients with or without concomitant DM from South Africa and Indonesia to characterize whole blood transcriptional profiles before and during anti-TB treatment, using unbiased RNA-Seq and targeted gene dcRT-MLPA. Findings We report differences in whole blood transcriptome profiles between patients with a good versus poor anti-TB treatment outcome, which were observed before initiation of treatment and throughout treatment. An eight-gene and 22-gene blood transcriptional signatures distinguished patients with a good treatment outcome from patients with a poor treatment outcome at diagnosis (AUC=0·815) or two weeks (AUC=0·834) after initiation of anti-TB treatment, respectively. Importantly, high accuracy was obtained by cross-validating this signature in an external cohort (AUC=0·749). Interpretation These findings suggest that transcriptional profiles can be used as a prognostic biomarker for treatment failure and success, even in patients with concomitant DM.

2022-08-02 | GSE193979 | GEO

Expression data from whole blood sample of eight kinds of TCM syndromes of rheumatoid arthritis patients.

Project description:To explore the biological connotation of eight syndromes of Rheumatoid Arthritis (RA) from the syndrome-symptom association network, and the relationship between the clinical characteristics of various syndromes and their key network target genes and pathways, which may offer clinicians auxiliary tools for diagnosis and treatment of RA patients with various traditional Chinese medicine (TCM) syndromes and promoting the developments of TCM Syndrome Theory. We used microarrays to detail the biological connotation of five syndromes (D-H, N) of Rheumatoid Arthritis (RA) and identified distinct classes of up-regulated and down-regulated genes during this process.

2023-01-01 | GSE205962 | GEO

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