Evidence map›Paper›PMID 32139361›Full record

ReviewClinical journal of the American Society of Nephrology : CJASN2020

Disease Modeling To Understand the Pathomechanisms of Human Genetic Kidney Disorders.

Elisa Molinari, John A Sayer

Open access · bronzeAbstract readReview
In one paragraph

Review in Clinical journal of the American Society of Nephrology : CJASN, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

12 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Principles of Zebrafish Nephron Segment Development.Journal of developmental biology · 2023
    Review
  5. Article
  6. Review
  7. Review
  8. Biomedicines · 2022
    Article
  9. Organs-on-chip technology: a tool to tackle genetic kidney diseases.Pediatric nephrology (Berlin, Germany) · 2022
    Review
  10. Article
  11. Review
  12. 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 at 2 institutions in 1 country.

Elisa MolinariFaculty of Medical Sciences, Translational and Clinical Research Institute, International Centre for Life, Newcastle University, Newcastle upon Tyne, United Kingdom.
John A SayerFaculty of Medical Sciences, Translational and Clinical Research Institute, International Centre for Life, Newcastle University, Newcastle upon Tyne, United Kingdom.ORCID 0000-0003-1881-3782
Centre for Life · GBNational Health Service · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The class of human genetic kidney diseases is extremely broad and heterogeneous. Accordingly, the range of associated disease phenotypes is highly variable. Many children and adults affected by inherited kidney disease will progress to ESKD at some point in life. Extensive research has been performed on various different disease models to investigate the underlying causes of genetic kidney disease and to identify disease mechanisms that are amenable to therapy. We review some of the research highlights that, by modeling inherited kidney disease, contributed to a better understanding of the underlying pathomechanisms, leading to the identification of novel genetic causes, new therapeutic targets, and to the development of new treatments. We also discuss how the implementation of more efficient genome-editing techniques and tissue-culture methods for kidney research is providing us with personalized models for a precision-medicine approach that takes into account the specificities of the patient and the underlying disease. We focus on the most common model systems used in kidney research and discuss how, according to their specific features, they can differentially contribute to biomedical research. Unfortunately, no definitive treatment exists for most inherited kidney disorders, warranting further exploitation of the existing disease models, as well as the implementation of novel, complex, human patient-specific models to deliver research breakthroughs.

Indexed as

Models, BiologicalAnimalsCaenorhabditis elegansCells, CulturedChlamydomonas reinhardtiiDisease Models, AnimalDrosophila melanogasterHumansKidney DiseasesMicePolycystic Kidney, Autosomal DominantZebrafishgenetic renal diseasemolecular geneticstransgenic mousezebrafish

Identifiers

PMID32139361
PMCPMC7274277
OpenAlexW3009193172

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.