Evidence map›Paper›PMID 35524895›Full record

ArticleJournal of muscle research and cell motility2022

Tissue-specific isoform expression of GNE gene in human tissues.

Kapila Awasthi, Sudha Bhattacharya, Alok Bhattacharya

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Article in Journal of muscle research and cell motility, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 37% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Kapila AwasthiSchool of Life Sciences, Jawaharlal Nehru University, New Delhi, 110067, India.
Sudha BhattacharyaAshoka University, Plot No. 2, Rajiv Gandhi Education City, P.O.Rai, Sonepat, Haryana, 131029, India.
Alok BhattacharyaAshoka University, Plot No. 2, Rajiv Gandhi Education City, P.O.Rai, Sonepat, Haryana, 131029, India. alok.bhattacharya@gmail.com.ORCID 0000-0001-7907-6355
Ashoka University · INJawaharlal Nehru University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mutations in the sialic acid biosynthesis enzyme GNE lead to a late-onset, debilitating neuromuscular disorder, GNE myopathy, characterized by progressive skeletal muscle weakness. The mechanisms responsible for skeletal muscle specificity, late-onset, and disease progression are unknown. Our main aim is to understand the reason for skeletal muscle-specific phenotype. To answer this question, we have analyzed the expression profile of the GNE gene and its multiple mRNA variants in different human tissues. A combinatorial approach encompassing bioinformatics tools and molecular biology techniques was used. NCBI, Ensembl, and GTEx were used for data mining. The expression analysis of GNE and its variants was performed with cDNA tissue panel using PCR and targeted RNA-seq. Among nine different GNE isoforms reported in this study, transcript variants 1, X1, and X2 were not tissue specific. Transcript variants 1, 6, X1, and X2, were found in skeletal muscles suggesting their possible role in GNE myopathy. In the current study, we present new data about GNE expression patterns in human tissues. Our results suggest that there may be a link between tissue-specific pathology and isoform pattern in skeletal muscles, which could provide clues for the development of new treatment strategies for GNE myopathy.

Indexed as

Distal MyopathiesHumansMuscle, SkeletalMutationN-Acetylneuraminic AcidProtein IsoformsN-Acetylneuraminic AcidProtein IsoformsGene expressionGNE myopathyIsoformsSialic acidSkeletal muscles

Identifiers

PMID35524895
OpenAlexW4229074531

What OpenQuestion holds

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Registered trials

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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.