Evidence map›Paper›PMID 33028957›Full record

ReviewNature reviews. Nephrology2021

The tissue proteome in the multi-omic landscape of kidney disease.

Markus M Rinschen, Julio Saez-Rodriguez

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Nephrology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

34 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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  7. Article
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  14. Gene regulatory networks in disease and ageing.Nature reviews. Nephrology · 2024
    Review
  15. Review
  16. Minimal Change Disease: Pathogenetic Insights from Glomerular Proteomics.International journal of molecular sciences · 2024
    Article
  17. Article
  18. Article
  19. Review
  20. 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

2 authors.

Markus M RinschenDepartment of Biomedicine, Aarhus University, Aarhus, Denmark. rinschen@biomed.au.dk.ORCID http://orcid.org/0000-0002-9252-1342
Julio Saez-RodriguezInstitute for Computational Biomedicine, Faculty of Medicine, Heidelberg University, and Heidelberg University Hospital, Bioquant, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-8552-8976

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Kidney research is entering an era of 'big data' and molecular omics data can provide comprehensive insights into the molecular footprints of cells. In contrast to transcriptomics, proteomics and metabolomics generate data that relate more directly to the pathological symptoms and clinical parameters observed in patients. Owing to its complexity, the proteome still holds many secrets, but has great potential for the identification of drug targets. Proteomics can provide information about protein synthesis, modification and degradation, as well as insight into the physical interactions between proteins, and between proteins and other biomolecules. Thus far, proteomics in nephrology has largely focused on the discovery and validation of biomarkers, but the systematic analysis of the nephroproteome can offer substantial additional insights, including the discovery of mechanisms that trigger and propagate kidney disease. Moreover, proteome acquisition might provide a diagnostic tool that complements the assessment of a kidney biopsy sample by a pathologist. Such applications are becoming increasingly feasible with the development of high-throughput and high-coverage technologies, such as versatile mass spectrometry-based techniques and protein arrays, and encourage further proteomics research in nephrology.

Indexed as

BiomarkersComputational BiologyHumansKidney DiseasesProteomeProteomicsBiomarkersProteome

Identifiers

What OpenQuestion holds

Textmetadata
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.