Evidence map›Paper›PMID 29708967›Full record

ArticlePLoS neglected tropical diseases2018

Metabolite profiling for biomarkers in Schistosoma haematobium infection and associated bladder pathologies.

Adewale S Adebayo, Swapnil D Mundhe, Henrietta O Awobode, Olugbenga S Onile, Atinuke M Agunloye, Raphael D Isokpehi, Yogesh S Shouche, Bayatigeri Santhakumari, Chiaka I Anumudu

Open access · goldAbstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 17% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
  2. Shared urinary metabolomic signatures as potential biomarkers for early intestinalCurrent research in parasitology & vector-borne diseases · 2026
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  3. Article
  4. Review
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  6. Review
  7. Article
  8. Article
  9. Untargeted serum metabolomic profiling for early detection ofFrontiers in cellular and infection microbiology · 2022
    Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Comparative Metabonomic Investigations ofFrontiers in microbiology · 2019
    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

9 authors at 4 institutions in 3 countries.

Adewale S AdebayoCell Biology and Genetics Unit, Department of Zoology, University of Ibadan, Ibadan, Nigeria.
Swapnil D MundheCentre for Materials Characterization, CSIR-National Chemical Laboratory, Pune, India.
Henrietta O AwobodeParasitology Unit, Department of Zoology, University of Ibadan, Ibadan, Nigeria.
Olugbenga S OnileCell Biology and Genetics Unit, Department of Zoology, University of Ibadan, Ibadan, Nigeria.
Atinuke M AgunloyeDepartment of Radiology, University of Ibadan, Ibadan, Nigeria.
Raphael D IsokpehiCollege of Science, Engineering and Mathematics, Bethune-Cookman University, Daytona Beach, Florida, United States of America.
Yogesh S ShoucheNational Centre for Microbial Resources, National Centre for Cell Science, Pune, India.
Bayatigeri SanthakumariCentre for Materials Characterization, CSIR-National Chemical Laboratory, Pune, India.
Chiaka I AnumuduCell Biology and Genetics Unit, Department of Zoology, University of Ibadan, Ibadan, Nigeria.ORCID 0000-0002-9444-685X
University of Ibadan · NGNational Chemical Laboratory · INBethune-Cookman University · USNational Centre for Cell Science · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetabolic fingerprinting analysis can offer insights into underlying reactions in a biological system; hence it is crucial to the understanding of disease pathogenesis and could provide useful tools for discovering biomarkers. We sought to examine the urine and plasma metabolome in individuals affected by urogenital schistosomiasis and its associated-bladder pathologies. METHODOLOGY: Blood and midstream urine were obtained from volunteers who matched our inclusion criteria among residents from Eggua, southwestern Nigeria. Samples were screened by urinalysis, microscopy, PCR and ultrasonography, and categorised as advanced (urogenital schistosomiasis associated-bladder pathologies), infection-only (urogenital schistosomiasis alone) and controls (no infection and no pathology). Metabolites were extracted and data acquired with ultra high-performance liquid chromatography coupled with Thermo Q-Exactive orbitrap HRMS. Data was analysed with MetaboAnalyst, Workflow4Metabolomics, HMDB, LipidMaps and other bioinformatics tools, with univariate and multivariate statistics for metabolite selection. PRINCIPAL

findingsThere were low levels of host sex steroids, and high levels of several benzenoids, catechols and lipids (including ganglioside, phosphatidylcholine and phosphatidylethanolamine), in infection-only and advanced cases (FDR<0.05, VIP>2, delta>2.0). Metabolites involved in biochemical pathways related to chorismate production were abundant in controls, while those related to choline and sphingolipid metabolism were upregulated in advanced cases (FDR<0.05). Some of these human host and Schistosoma haematobium molecules, including catechol estrogens, were good markers to distinguish infection-only and advanced cases.

conclusionsAltered glycerophospholipid and sphingolipid metabolism could be key factors promoting the development of bladder pathologies and tumours during urogenital schistosomiasis.

Indexed as

Host-Parasite InteractionsMetabolomeAnimalsBiomarkersFemaleGlycerophospholipidsHumansMultivariate AnalysisNigeriaPregnancySchistosoma haematobiumSchistosomiasis haematobiaSphingolipidsUrinary BladderBiomarkersGlycerophospholipidsSphingolipids

Identifiers

PMID29708967
PMCPMC5945272
OpenAlexW2800388527

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.