Evidence map›Paper›PMID 32083293›Full record

ArticleHuman molecular genetics2020

Longitudinal measures of RNA expression and disease activity in FSHD muscle biopsies.

Chao-Jen Wong, Leo H Wang, Seth D Friedman, Dennis Shaw, Amy E Campbell, Chris B Budech, Leann M Lewis, Richard J F L Lemmers, Jeffrey M Statland, Silvère M van der Maarel and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in Human molecular genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 7% 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

51 citing papers in PubMed, 1 synthesis or guideline pooled it, 76 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

12 authors at 6 institutions in 2 countries.

Chao-Jen WongHuman Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Leo H WangDepartment of Neurology, University of Washington, Seattle, WA 98105, USA.
Seth D FriedmanDepartment of Radiology, Seattle Children's Hospital, Seattle, WA 98105, USA.
Dennis ShawDepartment of Radiology, Seattle Children's Hospital, Seattle, WA 98105, USA.
Amy E CampbellHuman Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Chris B BudechDepartment of Radiology, Seattle Children's Hospital, Seattle, WA 98105, USA.
Leann M LewisDepartment of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Richard J F L LemmersDepartment of Human Genetics, Leiden University Medical Center, 2333, Leiden, The Netherlands.
Jeffrey M StatlandDepartment of Neurology, University of Kansas Medical Center, Kansas City, KA 66160, USA.
Silvère M van der MaarelDepartment of Human Genetics, Leiden University Medical Center, 2333, Leiden, The Netherlands.
Rabi N TawilDepartment of Human Genetics, Leiden University Medical Center, 2333, Leiden, The Netherlands.
Stephen J TapscottHuman Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
Leiden University Medical Center · NLSeattle Children's Hospital · USFred Hutch Cancer Center · USUniversity of Washington · USUniversity of Kansas Medical Center · USUniversity of Rochester Medical Center · US

Funding

Wellstone Muscular Dystrophy Specialized Research Center (Seattle)P50AR065139 · NIAMS · UNIVERSITY OF WASHINGTON · PI JEFFREY S CHAMBERLAIN · 2018 to 2026
$15.9M
The Pathogenesis of Facioscapulohumeral Muscular DystrophyP01NS069539 · NINDS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI TAWIL, RABI · 2010 to 2019
$12.3M
NIAMS NIH HHS P50 AR065139NINDS NIH HHS P01 NS069539
6 · The paper itself

Abstract

Advances in understanding the pathophysiology of facioscapulohumeral dystrophy (FSHD) have led to the discovery of candidate therapeutics, and it is important to identify markers of disease activity to inform clinical trial design. For drugs that inhibit DUX4 expression, measuring DUX4 or DUX4-target gene expression might be an interim measure of drug activity; however, only a subset of FHSD muscle biopsies shows evidence of DUX4 expression. Our prior study showed that MRI T2-STIR-positive muscles had a higher probability of showing DUX4 expression than muscles with normal MRI characteristics. In the current study, we performed a 1-year follow-up assessment of the same muscle with repeat MRI and muscle biopsy. There was little change in MRI characteristics over the 1-year period and, similar to the initial evaluation, MRI T2-STIR-postive muscles had a higher expression of DUX4-regulated genes, as well as genes associated with inflammation, extracellular matrix and cell cycle. Compared to the initial evaluation, overall the level of expression in these gene categories remained stable over the 1-year period; however, there was some variability for each individual muscle biopsied. The pooled data from both the initial and 1-year follow-up evaluations identified several FSHD subgroups based on gene expression, as well as a set of genes-composed of DUX4-target genes, inflammatory and immune genes and cell cycle control genes-that distinguished all of the FSHD samples from the controls. These candidate markers of disease activity need to be replicated in independent datasets and, if validated, may provide useful measures of disease progression and response to therapy.

Indexed as

Gene Expression RegulationAdultAgedBiomarkersCase-Control StudiesFemaleHomeodomain ProteinsHumansLongitudinal StudiesMaleMiddle AgedMuscle, SkeletalMuscular Dystrophy, FacioscapulohumeralRNA-SeqYoung AdultBiomarkersDUX4L1 protein, humanHomeodomain Proteins

Identifiers

PMID32083293
PMCPMC7158378
OpenAlexW3006720768

What OpenQuestion holds

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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.