Evidence map›Paper›PMID 38315405›Full record

ArticleJournal of applied genetics2025

Bioinformatics to analyze the differentially expressed genes in different degrees of Alzheimer's disease and their roles in progress of the disease.

Yanfang Niu, Yunyun Zhang, Qin Zha, Jingfei Shi, Qiuyan Weng

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Article in Journal of applied genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. Pathway Analysis Interpretation in the Multi-Omic Era.Biotech (Basel (Switzerland)) · 2025
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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

5 authors.

Yanfang NiuDepartment of Neurology, The First Affiliated Hospital of Ningbo University, Ningbo, 315020, China.
Yunyun ZhangDepartment of Neurology, The First Affiliated Hospital of Ningbo University, Ningbo, 315020, China.
Qin ZhaDepartment of Neurology, The First Affiliated Hospital of Ningbo University, Ningbo, 315020, China.
Jingfei ShiCerebrovascular and Neuroscience Research Institute, Capital Medical University, Beijing, 100069, China.
Qiuyan WengDepartment of Neurology, The First Affiliated Hospital of Ningbo University, Ningbo, 315020, China. fywengqiuyan@nbu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Employing bioinformatics approaches, this investigation pinpointed pivotal differentially expressed genes (DEGs) across the spectrum of Alzheimer's disease (AD), from incipient to severe stages, using the GSE28146 dataset from the GEO repository. Analytical methods included DEG identification via the limma package in R, coupled with GO and KEGG pathway analyses through clusterProfiler, to discern biological processes and pathway involvements. Key findings spotlighted the roles of proteasome subunits PSMB4, PSMB8, PSMC4, and PSMD6 in the early stage, ribosomal proteins RPS3 and RPL11 during moderate AD, and mitochondrial components COX5B, COX6B2, and COX7A2 in severe AD, underscoring their importance in the disease's pathogenesis. Conclusively, these results not only delineate the dynamic genetic shifts accompanying AD progression but also propose critical biomarkers for potential therapeutic targeting, offering a consolidated basis for future AD research and treatment development. This offered a novel idea for analyzing the pathogenesis and development of AD and investigation of targeted drugs.

Indexed as

Alzheimer DiseaseComputational BiologyDatabases, GeneticDisease ProgressionGene Expression ProfilingHumansTranscriptomeAlzheimer’s diseaseBioinformatics analysis methodsDifferentially expressed genesDifferent levels of diseaseOccurrence and progression of disease

Identifiers

PMID38315405

What OpenQuestion holds

Textmetadata
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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.