Evidence map›Paper›PMID 28558710›Full record

ArticleMalaria journal2017

A metabolomic analytical approach permits identification of urinary biomarkers for Plasmodium falciparum infection: a case-control study.

Salah Abdelrazig, Catharine A Ortori, Gail Davey, Wakgari Deressa, Dhaba Mulleta, David A Barrett, Alemayehu Amberbir, Andrew W Fogarty

Open access · goldAbstract read
In one paragraph

Article in Malaria journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

15 citing papers in PubMed, 33 citations in OpenAlex.

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  2. Diagnosis of cerebral malaria: Tools to reduceFrontiers in cellular and infection microbiology · 2023
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  4. Multi-Omics Advancements towardsDiagnostics (Basel, Switzerland) · 2021
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  13. Review
  14. Rainfall Trends and Malaria Occurrences in Limpopo Province, South Africa.International journal of environmental research and public health · 2019
    Article
  15. 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

8 authors at 4 institutions in 2 countries.

Salah AbdelrazigCentre for Analytical Bioscience, School of Pharmacy, University of Nottingham, Nottingham, NG7 2RD, UK.
Catharine A OrtoriCentre for Analytical Bioscience, School of Pharmacy, University of Nottingham, Nottingham, NG7 2RD, UK.
Gail DaveyWellcome Trust Centre for Global Health Research, Brighton and Sussex Medical School, Brighton, UK.
Wakgari DeressaDepartment of Preventive Medicine, School of Public Health, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia. deressaw@gmail.com.
Dhaba MulletaEast Shewa Zone Health Department, Oromia Regional State, Adama, Ethiopia.
David A BarrettCentre for Analytical Bioscience, School of Pharmacy, University of Nottingham, Nottingham, NG7 2RD, UK.
Alemayehu AmberbirSchool of Medicine, University of Nottingham, Nottingham, UK.
Andrew W FogartySchool of Medicine, University of Nottingham, Nottingham, UK.
University of Nottingham · GBAddis Ababa University · ETBrighton and Sussex Medical School · GBOromiyaa Regional Health Bureau · ET

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCurrently available diagnostic techniques of Plasmodium falciparum infection are not optimal for non-invasive, population-based screening for malaria. It was hypothesized that a mass spectrometry-based metabolomics approach could identify urinary biomarkers of falciparum malaria.

methodsThe study used a case-control design, with cases consisting of 21 adults in central Ethiopia with a diagnosis of P. falciparum infection confirmed with microscopy, and 25 controls of adults with negative blood smears for malaria matched on age and sex. Urinary samples were collected from these individuals during presentation at the clinic, and a second sample was collected from both cases and controls 4 weeks later, after the cases had received anti-malarial medication. The urine samples were screened for small molecule urinary biomarkers, using mass spectrometry-based metabolomics analyses followed by multivariate analysis using principal component analysis and orthogonal partial least square-discriminant analysis. The chemical identity of statistically significant malaria biomarkers was confirmed using tandem mass spectrometry.

resultsThe urinary metabolic profiles of cases with P. falciparum infection were distinct from healthy controls. After treatment with anti-malarial medication, the metabolomic profile of cases resembled that of healthy controls. Significantly altered levels of 29 urinary metabolites were found. Elevated levels of urinary pipecolic acid, taurine, N-acetylspermidine, N-acetylputrescine and 1,3-diacetylpropane were identified as potential biomarkers of falciparum malaria.

conclusionThe urinary biomarkers of malaria identified have potential for the development of non-invasive and rapid diagnostic test of P. falciparum infection.

Indexed as

AdolescentAdultAntimalarialsBiomarkersCase-Control StudiesEthiopiaFemaleHumansMalaria, FalciparumMaleMass SpectrometryMetabolomeMetabolomicsMiddle AgedMultivariate AnalysisPlasmodium falciparumAntimalarialsBiomarkersBiomarkerFalciparumMalariaMetabolomicsUrine

Identifiers

PMID28558710
PMCPMC5450092
OpenAlexW2618565934

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.