Evidence map›Paper›PMID 41797877›Full record

ArticleAnnals of neurosciences2026

A Meta-analysis to Identify Common Key Genes Across Ageing, Alzheimer's and Parkinson's Diseases.

Mona Chaurasiya, Sai Nikhith Cholleti, Gajendra Prasad, Vaibhav Vindal

Abstract read
In one paragraph

Article in Annals of neurosciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mona ChaurasiyaUniversity Department of Biotechnology, L. N. Mithila University, Darbhanga, Bihar, India.ORCID https://orcid.org/0009-0003-6961-8968
Sai Nikhith CholletiDepartment of Biotechnology and Bioinformatics, School of Life Sciences, University of Hyderabad, Hyderabad, Telangana, India.ORCID https://orcid.org/0000-0002-4676-6613
Gajendra PrasadUniversity Department of Botany, L. N. Mithila University, Darbhanga, Bihar, India.
Vaibhav VindalDepartment of Biotechnology and Bioinformatics, School of Life Sciences, University of Hyderabad, Hyderabad, Telangana, India.ORCID https://orcid.org/0000-0002-3855-0222

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Ageing (AG) is associated with cognitive decline and an increased risk of developing neurodegenerative diseases (NDs) like Alzheimer's disease (AD) and Parkinson's disease (PD). While individual diseases have been widely studied, cross-condition convergence at the transcriptomic and regulatory levels has not been systematically defined. Objective: To identify a conserved molecular core shared across AG, AD and PD and to understand its functional and regulatory architecture using integrative network biology. Methods: Four independent human brain transcriptomic datasets ( Results: A conserved set of 142 genes was identified across AG, AD and PD, with 94.4% exhibiting consistent directionality of regulation. AG clustered transcriptionally closer to AD than PD, while PD displayed stronger amplitude of dysregulation. Functional enrichment analysis revealed dominant involvement in synaptic signalling, axonal transport, vesicle trafficking and calcium homeostasis. Network analysis identified three essential regulatory hubs, CALM3, CDC42 and RAB3A. They are critical to neuronal signalling and cytoskeletal dynamics. miRNA analysis revealed coordinated regulation of hub genes by disease-associated miRNAs, including miR-29, miR-34, miR-7 and miR-195, and identified shared disease-associated regulators across AG, AD and PD conditions. Conclusion: This study defines a shared neurodegenerative molecular core that bridges physiological AG with pathological neurodegeneration. The integration of transcriptomic, network, and miRNA analyses reveals systems-level convergence and identifies key regulatory nodes as attractive targets for cross-disease therapeutic strategies.

Indexed as

AgeingAlzheimer’s diseaseParkinson’s diseaseprotein–protein interaction networktranscriptomics

Identifiers

PMID41797877
PMCPMC12965890

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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.