Evidence map›Paper›PMID 31976312›Full record

ArticleInternational journal of genomics2020

Metabonomic-Transcriptome Integration Analysis on Osteoarthritis and Rheumatoid Arthritis.

Ningyang Gao, Li Ding, Jian Pang, Yuxin Zheng, Yuelong Cao, Hongsheng Zhan, Yinyu Shi

Open access · goldAbstract read
In one paragraph

Article in International journal of genomics, 2020. 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
0.8field-weighted citation impact, top 31% 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, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. 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

7 authors at 1 institution in 1 country.

Ningyang GaoShi's Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of TCM, No. 528 Zhangheng Road, Shanghai 201203, China.ORCID https://orcid.org/0000-0001-5065-6436
Li DingInstitute of Traumatology & Orthopedics, Shanghai Academy of TCM, No. 528 Zhangheng Road, Shanghai 201203, China.
Jian PangInstitute of Traumatology & Orthopedics, Shanghai Academy of TCM, No. 528 Zhangheng Road, Shanghai 201203, China.
Yuxin ZhengShi's Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of TCM, No. 528 Zhangheng Road, Shanghai 201203, China.
Yuelong CaoInstitute of Traumatology & Orthopedics, Shanghai Academy of TCM, No. 528 Zhangheng Road, Shanghai 201203, China.ORCID https://orcid.org/0000-0001-5883-0347
Hongsheng ZhanShi's Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of TCM, No. 528 Zhangheng Road, Shanghai 201203, China.
Yinyu ShiShi's Center of Orthopedics and Traumatology, Shuguang Hospital Affiliated to Shanghai University of TCM, No. 528 Zhangheng Road, Shanghai 201203, China.
Shanghai University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study is aimed at exploring the potential metabolite/gene biomarkers, as well as the differences between the molecular mechanisms, of osteoarthritis (OA) and rheumatoid arthritis (RA).

methodsTranscriptome dataset GSE100786 was downloaded to explore the differentially expressed genes (DEGs) between OA samples and RA samples. Meanwhile, metabolomic dataset MTBLS564 was downloaded and preprocessed to obtain metabolites. Then, the principal component analysis (PCA) and linear models were used to reveal DEG-metabolite relations. Finally, metabolic pathway enrichment analysis was performed to investigate the differences between the molecular mechanisms of OA and RA.

resultsA total of 976 DEGs and 171 metabolites were explored between OA samples and RA samples. The PCA and linear module analysis investigated 186 DEG-metabolite interactions including Glycogenin 1- (GYG1-) asparagine_54, hedgehog acyltransferase- (HHAT-) glucose_70, and TNF receptor-associated factor 3- (TRAF3-) acetoacetate_35. Finally, the KEGG pathway analysis showed that these metabolites were mainly enriched in pathways like gap junction, phagosome, NF-kappa B, and IL-17 pathway.

conclusionsGenes such as HHAT, GYG1, and TRAF3, as well as metabolites including glucose, asparagine, and acetoacetate, might be implicated in the pathogenesis of OA and RA. Metabolites like ethanol and tyrosine might participate differentially in OA and RA progression via the gap junction pathway and phagosome pathway, respectively. TRAF3-acetoacetate interaction may be involved in regulating inflammation in OA and RA by the NF-kappa B and IL-17 pathway.

Identifiers

PMID31976312
PMCPMC6961787
OpenAlexW2998595288

What OpenQuestion holds

Textmetadata
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.