Evidence map›Paper›PMID 35869994›Full record

ReviewMolecular genetics and genomics : MGG2022

ARNSHL gene identification: past, present and future.

Ayesha Imtiaz

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular genetics and genomics : MGG, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
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  4. Review
  5. 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

1 author at 1 institution in 1 country.

Ayesha ImtiazSchool of Biological Sciences, University of the Punjab, Lahore, 54590, Pakistan. ayeshasbs@gmail.com.ORCID http://orcid.org/0000-0002-2643-6879
University of the Punjab · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autosomal recessive non-syndromic hearing loss (ARNSHL) is the most common hereditary deafness. It is genetically highly heterogeneous and about 89 gene loci and 76 gene's mutations have been implicated in the etiology of ARNSHL. Molecular basis of ARNSHL remains unresolved in 60% of cases and gene mutations are unknown for 23 of 89 reported loci. Techniques used to identify reported ARNSHL gene mutations can be divided into position-dependent and position-independent approaches. The localization of the loci has been facilitated by homozygosity mapping or linkage studies using STR or SNP genotyping in large consanguineous families. First few genes identified for hearing loss exhibited such wide diversity of function and expression patterns that candidate gene approach was not a viable option. The mapping of the disorder to a chromosomal location has been followed by Sanger sequencing of all genes in the target region or confining of the massively parallel sequencing data analyses to the linkage region. Sometimes genes located in the linkage interval were prioritized because there was a reported orthologs with mutations causing hearing loss in mouse or when mutations in the gene caused a related disorder. Position-independent approaches involving use of mouse subtractive cochlear libraries, forward genetic screening, and position-independent analyses of massively parallel sequencing data have helped identify 17 of 68 reported ARNSHL gene mutations. A thorough study of the strategies used in the identification of reported ARNSHL genes and of their relative success can help increase the success rate of future studies.

Indexed as

DeafnessHearing LossAnimalsGenes, RecessiveMiceMutationPedigreeARNSHLExome sequencingGene identification techniques

Identifiers

PMID35869994
OpenAlexW4286684952

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.