Evidence map›Paper›PMID 28649440›Full record

ArticleNPJ systems biology and applications2017

Cross-species gene modules emerge from a systems biology approach to osteoarthritis.

Alan James Mueller, Elizabeth G Canty-Laird, Peter D Clegg, Simon R Tew

Abstract read
In one paragraph

Article in NPJ systems biology and applications, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
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

15 citing papers in PubMed.

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  15. Systems approaches in osteoarthritis: Identifying routes to novel diagnostic and therapeutic strategies.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2017
    Article
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

4 authors.

Alan James MuellerDepartment of Musculoskeletal Biology, Institute of Ageing and Chronic Disease, Faculty of Health and Life Sciences, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX UK.
Elizabeth G Canty-LairdDepartment of Musculoskeletal Biology, Institute of Ageing and Chronic Disease, Faculty of Health and Life Sciences, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX UK.
Peter D CleggDepartment of Musculoskeletal Biology, Institute of Ageing and Chronic Disease, Faculty of Health and Life Sciences, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX UK.
Simon R TewDepartment of Musculoskeletal Biology, Institute of Ageing and Chronic Disease, Faculty of Health and Life Sciences, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool, L7 8TX UK.

Funding

Medical Research Council MR/P020941/1
6 · The paper itself

Abstract

Complexities in degenerative disorders, such as osteoarthritis, arise from multiscale biological, environmental, and temporal perturbations. Animal models serve to provide controlled representations of the natural history of degenerative disorders, but in themselves represent an additional layer of complexity. Comparing transcriptomic networks arising from gene co-expression data across species can facilitate an understanding of the preservation of functional gene modules and establish associations with disease phenotypes. This study demonstrates the preservation of osteoarthritis-associated gene modules, described by immune system and system development processes, across human and rat studies. Class prediction analysis establishes a minimal gene signature, including the expression of the Rho GDP dissociation inhibitor

Identifiers

PMID28649440
PMCPMC5460168

What OpenQuestion holds

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LicenceCC BY
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.