Evidence map›Paper›PMID 23695285›Full record

ArticleEuropean journal of human genetics : EJHG2013

Stargardt disease: towards developing a model to predict phenotype.

Laura Heathfield, Miguel Lacerda, Christel Nossek, Lisa Roberts, Rajkumar S Ramesar

Erratum issuedOpen access · bronzeAbstract read
In one paragraph

Article in European journal of human genetics : EJHG, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

4 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Laura HeathfieldUCT/MRC Human Genetics Research Unit, Division of Human Genetics, Institute of Infectious Diseases and Molecular Medicine, Faculty of Health Science, University of Cape Town, Cape Town, South Africa.
Miguel Lacerda
Christel Nossek
Lisa Roberts
Rajkumar S Ramesar
University of Cape Town · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stargardt disease is an ABCA4-associated retinopathy, which generally follows an autosomal recessive inheritance pattern and is a frequent cause of macular degeneration in childhood. ABCA4 displays significant allelic heterogeneity whereby different mutations can cause retinal diseases with varying severity and age of onset. A genotype-phenotype model has been proposed linking ABCA4 mutations, purported ABCA4 functional protein activity and severity of disease, as measured by degree of visual loss and the age of onset. It has, however, been difficult to verify this model statistically in observational studies, as the number of individuals sharing any particular mutation combination is typically low. Seven founder mutations have been identified in a large number of Caucasian Afrikaner patients in South Africa, making it possible to test the genotype-phenotype model. A generalised linear model was developed to predict and assess the relative pathogenic contribution of the seven mutations to the age of onset of Stargardt disease. It is shown that the pathogenicity of an individual mutation can differ significantly depending on the genetic context in which it occurs. The results reported here may be used to identify suitable candidates for inclusion in clinical trials, as well as guide the genetic counselling of affected individuals and families.

Indexed as

Genetic Predisposition to DiseaseModels, GeneticPhenotypeAge FactorsATP-Binding Cassette TransportersGenotypeHumansMacular DegenerationMutationStargardt DiseaseABCA4 protein, humanATP-Binding Cassette Transporters

Identifiers

PMID23695285
PMCPMC3778365
OpenAlexW2127855707

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.