Evidence map›Paper›PMID 17331252›Full record

ArticleBMC genetics2007

Alterations in lipid metabolism gene expression and abnormal lipid accumulation in fibroblast explants from giant axonal neuropathy patients.

Conrad L Leung, Yinghua Pang, Chang Shu, Dmitry Goryunov, Ronald K H Liem

Open access · diamondAbstract read
In one paragraph

Article in BMC genetics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

9 citing papers in PubMed, 20 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

5 authors at 1 institution in 1 country.

Conrad L LeungDepartment of Pathology and Cell Biology, College of Physicians and Surgeons, Columbia University, New York, New York 10032, USA. cl119@columbia.edu <cl119@columbia.edu>
Yinghua Pang
Chang Shu
Dmitry Goryunov
Ronald K H Liem
Columbia University · US

Funding

Satellite Diagnostic and Treatment Clinic CoreP50AG008702 · NIA · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI DE JAGER, PHILIP L · 1989 to 2019
$46.3M
NIA NIH HHS P50 AG008702NIA NIH HHS P50 AG08702PHS HHS NIH15182
6 · The paper itself

Abstract

backgroundGiant axonal neuropathy (GAN) is a hereditary neurological disorder that affects both central and peripheral nerves. The main pathological hallmark of the disease is abnormal accumulations of intermediate filaments (IFs) in giant axons and other cell types. Mutations in the GAN gene, encoding gigaxonin, cause the disease. Gigaxonin is important in controlling protein degradation via the ubiquitin-proteasome system. The goal of this study was to examine global alterations in gene expression in fibroblasts derived from newly identified GAN families compared with normal cells.

resultsWe report the characterization of fibroblast explants obtained from two unrelated GAN patients. We identify three novel putative mutant GAN alleles and show aggregation of vimentin IFs in these fibroblasts. By microarray analysis, we also demonstrate that the expression of lipid metabolism genes of the GAN fibroblasts is disrupted, which may account for the abnormal accumulations of lipid droplets in these cells.

conclusionOur findings suggest that aberrant lipid metabolism in GAN patients may contribute to the progression of the disease.

Indexed as

Codon, NonsenseMutation, MissenseAllelesAxonsCell LineCytoskeletal ProteinsFibroblastsGene Expression ProfilingGenotypeHumansIntermediate FilamentsIntronsLipid MetabolismLipidsOligonucleotide Array Sequence AnalysisReverse Transcriptase Polymerase Chain ReactionCodon, NonsenseCytoskeletal ProteinsGAN protein, humanLipidsVimentin

Identifiers

PMID17331252
PMCPMC1810559
OpenAlexW1584659543

What OpenQuestion holds

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LicenceCC BY
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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.