Evidence map›Paper›PMID 27992487›Full record

ArticlePloS one2016

Changes in Host Cytokine Patterns of TB Patients with Different Bacterial Loads Detected Using 16S rRNA Analysis.

Rhiannon Heslop, Adama L Bojang, Sheikh Jarju, Joseph Mendy, Sarah Mulwa, Ousman Secka, Francis S Mendy, Olumuyiwa Owolabi, Beate Kampmann, Jayne S Sutherland

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 27% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Treatment Response in Pediatric Pulmonary Tuberculosis-A Prospective Longitudinal Study.Journal of the Pediatric Infectious Diseases Society · 2022
    Article
  10. Article
  11. Article
  12. Changes inFrontiers in immunology · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 2 countries.

Rhiannon HeslopVaccines and Immunity Theme, Medical Research Council (MRC) Unit, Banjul, The Gambia.
Adama L BojangVaccines and Immunity Theme, Medical Research Council (MRC) Unit, Banjul, The Gambia.
Sheikh JarjuVaccines and Immunity Theme, Medical Research Council (MRC) Unit, Banjul, The Gambia.
Joseph MendyVaccines and Immunity Theme, Medical Research Council (MRC) Unit, Banjul, The Gambia.
Sarah MulwaVaccines and Immunity Theme, Medical Research Council (MRC) Unit, Banjul, The Gambia.
Ousman SeckaVaccines and Immunity Theme, Medical Research Council (MRC) Unit, Banjul, The Gambia.
Francis S MendyVaccines and Immunity Theme, Medical Research Council (MRC) Unit, Banjul, The Gambia.
Olumuyiwa OwolabiVaccines and Immunity Theme, Medical Research Council (MRC) Unit, Banjul, The Gambia.
Beate KampmannVaccines and Immunity Theme, Medical Research Council (MRC) Unit, Banjul, The Gambia.
Jayne S SutherlandVaccines and Immunity Theme, Medical Research Council (MRC) Unit, Banjul, The Gambia.
MRC Unit the Gambia · GMUniversity of Manchester · GB

Funding

Department of Health SRF-2009-02-07Medical Research Council MC_U190071468Medical Research Council MC_UP_A900_1122
6 · The paper itself

Abstract

backgroundTuberculosis (TB) has overtaken HIV as the biggest infectious disease killer, with the majority of deaths occurring in sub-Saharan Africa. However it is unknown how differences in bacterial load alter host immune profiles in the sputum and blood of TB patients.

methods16S ribosomal RNA analysis was used to determine bacterial load in sputum samples obtained from 173 patients with active TB (57 pre-treatment and 116 post-treatment). Host analyte concentrations in sputum and Mycobacterium tuberculosis (Mtb) antigen stimulated whole blood assay supernatants were analysed using multiplex cytokine arrays.

resultsMultiple logistic regression adjusting for age, sex and HIV status showed highly significant correlation of bacterial load with IL1β, IL2, IL1RA, IL4, IL6, IL8, IL9, IL15, IL17, EOTAX, FGF, IFN-γ, GCSF, MCP1, M1P1α, M1P1β, PDGF, TNFα, VEGF in sputum. With increasing time on treatment, FGF levels in sputum displayed the most significant inverse correlation with reduction in bacterial load.

conclusionsWe show that differences in bacterial load correlates with changes in several host biomarkers. These findings have implications for development of tests for TB diagnosis and treatment response.

Indexed as

AdultAfrica South of the SaharaAntitubercular AgentsBacterial LoadCytokinesFemaleGambiaHumansMaleMolecular Diagnostic TechniquesMycobacterium tuberculosisRNA, BacterialRNA, Ribosomal, 16SSputumTreatment OutcomeTuberculosisAntitubercular AgentsCytokinesRNA, BacterialRNA, Ribosomal, 16S

Identifiers

PMID27992487
PMCPMC5161358
OpenAlexW2562018541

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.