Evidence map›Paper›PMID 24914583›Full record

ReviewNature reviews. Nephrology2014

Next-generation sequencing for research and diagnostics in kidney disease.

Kirsten Y Renkema, Marijn F Stokman, Rachel H Giles, Nine V A M Knoers

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Nephrology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
12.6field-weighted citation impact, top 1% 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

53 citing papers in PubMed, 101 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Genetic Susceptibility to Chronic Kidney Disease: Links, Risks and Management.International journal of nephrology and renovascular disease · 2023
    Review
  9. Article
  10. Review
  11. Article
  12. OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction.International journal of molecular sciences · 2021
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  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

4 authors at 1 institution in 1 country.

Kirsten Y RenkemaDepartment of Medical Genetics, University Medical Center Utrecht, KC04.048.02, PO Box 85090, Utrecht, 3508 AB, Netherlands.
Marijn F StokmanDepartment of Medical Genetics, University Medical Center Utrecht, KC04.048.02, PO Box 85090, Utrecht, 3508 AB, Netherlands.
Rachel H GilesDepartment of Nephrology and Hypertension, University Medical Center Utrecht, KC04.048.02, PO Box 85090, Utrecht, 3508 AB, Netherlands.
Nine V A M KnoersDepartment of Medical Genetics, University Medical Center Utrecht, KC04.048.02, PO Box 85090, Utrecht, 3508 AB, Netherlands.
Utrecht University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advent of next-generation sequencing technologies has enabled genetic nephrology research to move beyond single gene analysis to the simultaneous investigation of hundreds of genes and entire pathways. These new sequencing approaches have been used to identify and characterize causal factors that underlie inherited heterogeneous kidney diseases such as nephronophthisis and congenital anomalies of the kidney and urinary tract. In this Review, we describe the development of next-generation sequencing in basic and clinical research and discuss the implementation of this novel technology in routine patient management. Widespread use of targeted and nontargeted approaches for gene identification in clinical practice will require consistent phenotyping, appropriate disease modelling and collaborative efforts to combine and integrate data analyses. Next-generation sequencing is an exceptionally promising technique that has the potential to improve the management of patients with inherited kidney diseases. However, identifying the molecular mechanisms that lead to renal developmental disorders and ciliopathies is difficult. A major challenge in the near future will be how best to integrate data obtained using next-generation sequencing with personalized medicine, including use of high-throughput disease modelling as a tool to support the clinical diagnosis of kidney diseases.

Indexed as

Adaptor Proteins, Signal TransducingAnimalsCytoskeletal ProteinsDisclosureHigh-Throughput Nucleotide SequencingHumansIncidental FindingsKidneyKidney Diseases, CysticMembrane ProteinsPolycystic Kidney, Autosomal DominantRenal Insufficiency, ChronicTRPP Cation ChannelsUrinary TractUrogenital AbnormalitiesVesico-Ureteral RefluxAdaptor Proteins, Signal TransducingCytoskeletal ProteinsMembrane ProteinsNPHP1 protein, humanTRPP Cation Channels

Identifiers

PMID24914583
OpenAlexW2043992490

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.