Evidence map›Paper›PMID 34402383›Full record

ArticleBioengineered2021

Systematic analysis of Long non-coding RNAs reveals diagnostic biomarkers and potential therapeutic drugs for intervertebral disc degeneration.

Jiawen Zhan, Shangquan Wang, Xu Wei, Minshan Feng, Xunlu Yin, Jie Yu, Tao Han, Guangwei Liu, Wangwen Xuan, Xiaobo Wang and 3 more

Open access · goldAbstract read
In one paragraph

Article in Bioengineered, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.3field-weighted citation impact, top 53% 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

6 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Circ_0005918 Sponges miR-622 to Aggravate Intervertebral Disc Degeneration.Frontiers in cell and developmental biology · 2022
    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

13 authors at 4 institutions in 1 country.

Jiawen ZhanGeneral Orthopedic, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Shangquan WangGeneral Orthopedic, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Xu WeiScientific Research, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Minshan FengSpine Department2, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Xunlu YinSpine Department2, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Jie YuSpine Department2, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Tao HanSpine Department2, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Guangwei LiuSpine Department2, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Wangwen XuanSpine Department2, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Xiaobo WangOrthopedic, Tianjing University of Traditional Chinese Medicine, Tianjin, China.
Rui XieSpine Department2, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Kai SunSpine Department2, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Liguo ZhuSpine Department2, Wangjing Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
China Academy of Chinese Medical Sciences · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNWangjing Hospital of China Academy of Chinese Medical Sciences · CNTianjin University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) are related to a variety of human diseases. However, little is known about the role of lncRNA in intervertebral disc degeneration (IDD). LncRNA expression profile of human IDD were downloaded from Gene Expression Omnibus (GEO) database. Potential biomarkers and therapeutic drugs for IDD were analyzed by weighted gene co-expression network analysis (WGCNA), R software package Limma, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). We identified 1455 differentially expressed genes and 423 differentially expressed lncRNAs. Twenty-six co-expression modules were obtained, among them, the tan, brown, and turquoise modules were most closely related to IDD. The turquoise module contained a large number of differential expressed lncRNAs and genes, these genes were mainly enriched in the MAPK signaling pathway, TGF-beta signaling pathway. Furthermore, we obtained 11,857 LmiRM-Degenerated, these lncRNAs and genes showed higher differential expression multiples and higher expression correlation. After constructing a disease-gene interaction network, 25 disease-specific genes and 9 disease-specific lncRNAs were identified. Combined with the drug-target gene interaction network, three drugs, namely, Calcium citrate, Calcium Phosphate, and Calcium phosphate dihydrate, which may have curative effects on IDD, were determined. Finally, a genetic diagnosis model and lncRNA diagnosis model with 100% diagnostic performance in both the training data set and the validation data set were established based on these genes and lncRNA. This study provided new diagnostic features for IDD and could help design personalized treatment of IDD.

Indexed as

Drug DiscoveryIntervertebral Disc DegenerationRNA, Long NoncodingBiomarkersDatabases, GeneticGene Expression ProfilingHumansMAP Kinase Signaling SystemSupport Vector MachineTranscriptomeBiomarkersRNA, Long NoncodingIntervertebral disc degenerationlncRNAsupport vector machineweighted gene co-expression network analysis

Identifiers

PMID34402383
PMCPMC8806434
OpenAlexW3193371533

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.