Evidence map›Paper›PMID 31385015›Full record

ArticleJournal of molecular medicine (Berlin, Germany)2019

Novel plasma peptide markers involved in the pathology of CKD identified using mass spectrometric approach.

Prathibha R Gajjala, Heike Bruck, Heidi Noels, Georg Heinze, Francesco Ceccarelli, Andreas Kribben, Julio Saez-Rodriguez, Nikolaus Marx, Walter Zidek, Joachim Jankowski and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of molecular medicine (Berlin, Germany), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.1field-weighted citation impact, top 11% 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

6 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. MS-Based Proteomics of Body Fluids: The End of the Beginning.Molecular & cellular proteomics : MCP · 2023
    Article
  5. Article
  6. Review
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

11 authors at 8 institutions in 3 countries.

Prathibha R GajjalaInstitute of Molecular Cardiovascular Research, University Hospital RWTH Aachen, Aachen, Germany.
Heike BruckDepartment of Internal Medicine, Nephrology, Rheumatology, Diabetology and Endocrinology, Helios Hospital Krefeld, Krefeld, Germany.
Heidi NoelsInstitute of Molecular Cardiovascular Research, University Hospital RWTH Aachen, Aachen, Germany.
Georg HeinzeSection for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
Francesco CeccarelliJoint Research Centre for Computational Biomedicine, RWTH Aachen University, Aachen, Germany.
Andreas KribbenDepartment of Nephrology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
Julio Saez-RodriguezJoint Research Centre for Computational Biomedicine, RWTH Aachen University, Aachen, Germany.
Nikolaus MarxDepartment of Internal Medicine I, University Hospital Aachen, Aachen, Germany.
Walter ZidekCharité-Universitätsmedizin Berlin, Berlin, Germany.
Joachim JankowskiInstitute of Molecular Cardiovascular Research, University Hospital RWTH Aachen, Aachen, Germany.
Vera JankowskiInstitute of Molecular Cardiovascular Research, University Hospital RWTH Aachen, Aachen, Germany. vjankowski@ukaachen.de.
RWTH Aachen University · DECharité - Universitätsmedizin Berlin · DEHeidelberg University · DEHelios Klinikum Krefeld · DEJoint Research Centre · DEMedical University of Vienna · ATUniversitätsklinikum Aachen · DEUniversity of Duisburg-Essen · DE

Funding

Deutsche Forschungsgemeinschaft SFB/TRR219 S-03, C-04, IHST 948/4S-1 FU6.6
6 · The paper itself

Abstract

Chronic kidney disease (CKD) may progress to end-stage renal disease (ESRD) at different pace. Early markers of disease progression could facilitate and improve patient management. However, conventional blood and urine chemistry have proven unable to predict the progression of disease at early stages. Therefore, we performed untargeted plasma peptidome analysis to select the peptides involved in progression, which are suitable for long prospective studies in future. The study consists of non-CKD (n = 66) and CKD (n = 106) patients with different stages. We performed plasma peptidomics on these subjects using chromatography and mass spectrometric approaches. Initially, we performed LC-ESI-MS and applied least absolute shrinkage and selection operator logistic regressions to select the peptides that are differentially expressed and we generated a peptidomic score for each subject. Later, we identified and sequenced the peptides with MALDI-MS/MS and also performed univariate and multivariate analyses with the clinical variables and peptidomic score to reveal their association with progression of renal disease. A logistic regression model selected 14 substances showing different concentrations according to renal function, of which seven substances were most likely occur in CKD patients. The peptidomic model had a global P value of < 0.01 with R

Indexed as

AgedBiomarkersCohort StudiesC-Reactive ProteinDisease ProgressionFemaleHumansKidney Failure, ChronicMaleMiddle AgedPeptidesRenal Insufficiency, ChronicSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationTandem Mass SpectrometryUric AcidBiomarkersC-Reactive ProteinPeptidesUric AcidChronic kidney diseaseDisease progressionEnd-stage renal diseasepeptidomicsproteomicsSystems medicine

Identifiers

PMID31385015
PMCPMC6746684
OpenAlexW2966636262

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Registered trials

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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.