ArticleSaudi medical journal2020
Combining bioinformatics and biological detection to identify novel biomarkers for diagnosis and prognosis of pulmonary tuberculosis.
Article in Saudi medical journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Biomarkers That Correlate with Active Pulmonary Tuberculosis Treatment Response: a Systematic Review and Meta-analysis.Journal of clinical microbiology · 2022Pooled it
- Leukocyte immunoglobulin-like receptor B4: A keystone in immune modulation and therapeutic target in cancer and beyond.Cancer innovation · 2024Review
- Identification and Validation of Novel Biomarkers for Hepatocellular Carcinoma, Liver Fibrosis/Cirrhosis and Chronic Hepatitis B via Transcriptome Sequencing Technology.Journal of hepatocellular carcinoma · 2022Article
- Leukocyte immunoglobulin-like receptor subfamily B: therapeutic targets in cancer.Antibody therapeutics · 2021Review
- A bioinformatics analysis to identify novel biomarkers for prognosis of pulmonary tuberculosis.BMC pulmonary medicine · 2020Article
- LILRB4, from the immune system to the disease target.American journal of translational research · 2020Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo identify the novel and promising indicators for pulmonary tuberculosis (PTB) patients.
methodsThe study was carried out between June 2016 and June 2019. Three RNA sequencing or microarray datasets of TB infection were used to identify the potential genes showing a common expression trend. The expression level of screened targets was determined by reverse transcription polymerase chain reaction and ELISA using samples of whole blood and peripheral blood mononuclear cells (PBMCs) isolated from 69 PTB patients and 69 healthy volunteers. The potential of the identified targets to predict the treatment outcomes was further studied.
resultsBioinformatics analysis demonstrated that a total of 91 genes were up-regulated in all the 3 datasets; among them, the expression of SLAMF8, LILRB4, and IL-10Ra was significantly increased at both the mRNA and protein levels in whole blood and PBMC samples of PTB patients compared with the healthy controls. The mortality rate increased significantly in SLAMF8 or LILRB4 high expression group compared with SLAMF8 or LILRB4 low expression group. Further, the decrease rate of bacteria in patients with SLAMF8 or LILRB4 high expression was slower than that in patients with SLAMF8 or LILRB4 low expression.
conclusionThis study provides a promising way to identify novel indicators for PTB. Moreover, the LILRB4 expression may play a role in predicting the outcome of treatments on PTB patients.
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