Evidence map›Paper›PMID 38894850›Full record

ArticleFrontiers in aging neuroscience2024

Bioinformatics analysis of the potential receptor and therapeutic drugs for Alzheimer's disease with comorbid Parkinson's disease.

Xuerong Zhou, Zhifan Liu, Guiqin Bai, Bai Dazhang, Peilin Zhao, Xiaoming Wang, Guohui Jiang

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

7 authors.

Xuerong Zhou *Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Institute of Neurological Diseases, North Sichuan Medical College, Nanchong, China.
Zhifan Liu *Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Institute of Neurological Diseases, North Sichuan Medical College, Nanchong, China.
Guiqin BaiDepartment of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, China.
Bai DazhangDepartment of Neurology, Affiliated Hospital of North Sichuan Medical College, Institute of Neurological Diseases, North Sichuan Medical College, Nanchong, China.
Peilin ZhaoDepartment of Neurology, Affiliated Hospital of North Sichuan Medical College, Institute of Neurological Diseases, North Sichuan Medical College, Nanchong, China.
Xiaoming WangDepartment of Neurology, Affiliated Hospital of North Sichuan Medical College, Institute of Neurological Diseases, North Sichuan Medical College, Nanchong, China.
Guohui JiangDepartment of Neurology, Affiliated Hospital of North Sichuan Medical College, Institute of Neurological Diseases, North Sichuan Medical College, Nanchong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Now, there are no sensitive biomarkers for improving Alzheimer's disease (AD) and comorbid Parkinson's disease (PD). The aim of the present study was to analyze differentially expressed genes (DEGs) in brain tissue from AD and PD patients via bioinformatics analysis, as well as to explore precise diagnostic and therapeutic targets for AD and comorbid PD. Methods: GFE122063 and GSE7621 data sets from GEO in NCBI, were used to screen differentially expressed genes (DEGs) for AD and PD, and identify the intersected genes, respectively. Intersected genes were analyzed by Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Then, STRING site and Cytoscape were used to construct a protein-protein interaction (PPI) network, CytoNCA algorithm to analyze and evaluate centrality, Mcode plug-in to analyze module, and Cytohubba to screen key genes. Combined GO-KEGG enrichment analysis with Cytoscape algorithm to screen the key gene in AD complicated with PD. Then, the DEGs for AD and PD were imported into the Association Map (CMap) online platform to screen out the top 10 small molecule drugs, and using molecular docking techniques to evaluate the interactions between small molecule drugs and key genes receptors. Results: In total, 231 upregulated genes and 300 downregulated genes were identified. GO analysis revealed that the DEGs were highly enriched in signal transduction, and KEGG analysis revealed that the DEGs were associated with the MAPK and PI3K-Akt signaling pathways. Epidermal growth factor receptor (EGFR) was identified as a potential receptor gene in AD and comorbid PD. EGFR was upregulated in both AD and PD, and the proteins that interact with EGFR were enriched in the Ras/Raf/MAPK and PI3K/Akt signaling pathways. Semagacestat was identified as a drug with therapeutic potential for treating AD complicated with PD. There was a high binding affinity between semagacestat and EGFR Discussion: Semagacestat may improve the health of patients with AD complicated with PD through the regulation of the Ras/Raf/MAPK and PI3K/Akt signaling pathways by EGFR, providing evidence supporting the structural modification of semagacestat to develop a more effective drug for treating AD complicated with PD.

Indexed as

Alzheimer’s diseasebioinformaticscomorbidityepidermal growth factor receptorParkinson’s diseaseSemagacestat

Identifiers

PMID38894850
PMCPMC11185263

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.