Evidence map›Paper›PMID 22008521›Full record

ArticleBMC nephrology2011

High Resolution Melt analysis for mutation screening in PKD1 and PKD2.

Stanislas Bataille, Yvon Berland, Michel Fontes, Stéphane Burtey

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in BMC nephrology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

10 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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

4 authors at 2 institutions in 1 country.

Stanislas BatailleEA 4263 Thérapie des Maladies Génétiques, Faculté de Médecine, Université de la Méditerranée, Boulevard Jean Moulin 13005 Marseille, France.
Yvon Berland
Michel Fontes
Stéphane Burtey
Hôpital de la Conception · FRInstitut de Neurobiologie de la Méditerranée · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAutosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disorder. It is characterized by focal development and progressive enlargement of renal cysts leading to end-stage renal disease. PKD1 and PKD2 have been implicated in ADPKD pathogenesis but genetic features and the size of PKD1 make genetic diagnosis tedious.

methodsWe aim to prove that high resolution melt analysis (HRM), a recent technique in molecular biology, can facilitate molecular diagnosis of ADPKD. We screened for mutations in PKD1 and PKD2 with HRM in 37 unrelated patients with ADPKD.

resultsWe identified 440 sequence variants in the 37 patients. One hundred and thirty eight were different. We found 28 pathogenic mutations (25 in PKD1 and 3 in PKD2 ) within 28 different patients, which is a diagnosis rate of 75% consistent with literature mean direct sequencing diagnosis rate. We describe 52 new sequence variants in PKD1 and two in PKD2.

conclusionHRM analysis is a sensitive and specific method for molecular diagnosis of ADPKD. HRM analysis is also costless and time sparing. Thus, this method is efficient and might be used for mutation pre-screening in ADPKD genes.

Indexed as

AdultDNA Mutational AnalysisExonsFemaleGenetic TestingHumansIntronsMaleMiddle AgedNucleic Acid DenaturationPolycystic Kidney, Autosomal DominantPolymorphism, GeneticReal-Time Polymerase Chain ReactionSensitivity and SpecificityTRPP Cation ChannelsTRPP Cation Channels

Identifiers

PMID22008521
PMCPMC3206831
OpenAlexW2082205683

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.