Evidence map›Paper›PMID 32154224›Full record

ArticleFrontiers in bioengineering and biotechnology2020

Transcriptomic Analyses for Identification and Prioritization of Genes Associated With Alzheimer's Disease in Humans.

Yuchen Shi, Hui Liu, Changbo Yang, Kang Xu, Yangyang Cai, Zhao Wang, Zheng Zhao, Tingting Shao, Yixue Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 17% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Biomolecules · 2025
    Article
  4. Article
  5. Article
  6. Review
  7. Long Non-Coding RNAs: New Insights in Neurodegenerative Diseases.International journal of molecular sciences · 2024
    Review
  8. Article
  9. Review
  10. Omics-based biomarkers discovery for Alzheimer's disease.Cellular and molecular life sciences : CMLS · 2022
    Review
  11. Article
  12. Review
  13. MissingGenes · 2021
    Review
  14. Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. 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

9 authors at 2 institutions in 1 country.

Yuchen ShiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Hui LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Changbo YangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Kang XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yangyang CaiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Zhao WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Zheng ZhaoBeijing Neurosurgical Institute, Capital Medical University, Beijing, China.
Tingting ShaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yixue LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Harbin Medical University · CNBeijing Institute of Neurosurgery · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs), as important ncRNA regulators, play crucial roles in the regulation of various biological processes, and their aberrant expression is related to the occurrence and development of diseases, which is gradually validated by more and more studies. Alzheimer's disease (AD) is a chronic neurodegenerative disease that often develops slowly and gradually deteriorates over time. However, which functions the lncRNAs perform in AD are almost unknown. In this study, we performed transcriptome analysis in AD, containing 12,892 known lncRNAs and 19,053 protein-coding genes (PCGs). Further, 14 down-regulated and 39 up-regulated lncRNAs were identified, compared with normal brain samples, which indicated that these lncRNAs might play critical roles in the pathogenesis of AD. In addition, 19 down-regulated and 28 up-regulated PCGs were also detected. Using the differentially expressed lncRNAs and PCGs through the WGCNA method, an lncRNA-mRNA co-expressed network was constructed. The results showed that lncRNAs RP3-522J7, MIR3180-2, and MIR3180-3 were frequently co-expressed with known AD risk PCGs. Interestingly, PCGs in the network are significantly enriched in brain- or AD-related biological functions, including the brain renin-angiotensin system, cell adhesion, neuroprotective role of THOP1 in AD, and so on. Furthermore, it was shown that 18 lncRNAs and 7 PCGs were highly expressed in normal brain tissue relative to other normal tissue types, suggesting their potential as diagnostic markers of AD, especially RP3-522J7, MIR3180-2, MIR3180-3, and CTA-929C8. In total, our study identified a compendium of AD-related dysregulated lncRNAs and characterized the corresponding biological functions of these lncRNAs in AD, which will be helpful to understand the molecular basis and pathogenesis of AD.

Indexed as

Alzheimer’s diseasedifferential expression analysislong non-coding RNARNA-seqtranscriptomic analyses

Identifiers

PMID32154224
PMCPMC7047416
OpenAlexW3007080627

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.