Evidence map›Paper›PMID 24790760›Full record

ArticleInternational journal of nephrology2014

The novel diagnostic biomarkers for focal segmental glomerulosclerosis.

Mohsen Nafar, Shiva Kalantari, Shiva Samavat, Mostafa Rezaei-Tavirani, Dorothea Rutishuser, Roman A Zubarev

Open access · goldAbstract read
In one paragraph

Article in International journal of nephrology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.8field-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

21 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Urinary Protein and Peptide Markers in Chronic Kidney Disease.International journal of molecular sciences · 2021
    Review
  9. Article
  10. Review
  11. Article
  12. Review
  13. Review
  14. Article
  15. Proteomics Applications in Health: Biomarker and Drug Discovery and Food Industry.Iranian journal of pharmaceutical research : IJPR · 2018
    Article
  16. Article
  17. A kidney-specific genome-scale metabolic network model for analyzing focal segmental glomerulosclerosis.Mammalian genome : official journal of the International Mammalian Genome Society · 2016
    Article
  18. Article
  19. Review
  20. 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

6 authors at 2 institutions in 2 countries.

Mohsen NafarDepartment of Nephrology, Shahid Labbafinejad Medical Center, Shahid Beheshti University of Medical Sciences, Tehran 1666694516, Iran ; Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran ; Chronic Kidney Disease Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Shiva KalantariDepartment of Basic Sciences, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID 0000-0001-7690-141X
Shiva SamavatDepartment of Nephrology, Shahid Labbafinejad Medical Center, Shahid Beheshti University of Medical Sciences, Tehran 1666694516, Iran ; Urology and Nephrology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran ; Chronic Kidney Disease Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID 0000-0001-6707-7844
Mostafa Rezaei-TaviraniClinical Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Dorothea RutishuserDepartment of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden ; SciLifeLab, Stockholm, Sweden.
Roman A ZubarevDepartment of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden ; SciLifeLab, Stockholm, Sweden.
Shahid Beheshti University of Medical Sciences · IRScience for Life Laboratory · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background. Focal segmental glomerulosclerosis (FSGS) is a glomerular injury with various pathogenic mechanisms. Urine proteome panel might help in noninvasive diagnosis and better understanding of pathogenesis of FSGS. Method. We have analyzed the urine sample of 11 biopsy-proven FSGS subjects, 8 healthy controls, and 6 patients with biopsy-proven IgA nephropathy (disease controls) by means of liquid chromatography tandem mass spectrometry (nLC-MS/MS). Multivariate analysis of quantified proteins was performed by principal component analysis (PCA) and partial least squares (PLS). Results. Of the total number of 389 proteins, after multivariate analysis and additional filter criterion and comparing FSGS versus IgA nephropathy and healthy subjects, 77 proteins were considered as putative biomarkers of FSGS. CD59, CD44, IBP7, Robo4, and DPEP1 were the most significant differentially expressed proteins. These proteins are involved in pathogenic pathways: complement pathway, sclerosis, cell proliferation, actin cytoskeleton remodeling, and activity of TRPC6.There was complete absence of DPEP1 in urine proteome of FSGS subjects compared with healthy and disease controls. DPEP1 acts via leukotrienes on TRPC6 and results in increased podocyte motility and proteinuria. Conclusion. The results suggest a panel of candidate biomarkers for noninvasive diagnosis of FSGS, while complete absence of DPEP1 might represent a novel marker of FSGS.

Identifiers

PMID24790760
PMCPMC3984796
OpenAlexW2068771590

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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.