Novel Biomarkers of Neurodegenerative Diseases

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Human Genomics and Genetic Diseases".

Deadline for manuscript submissions: 1 April 2026 | Viewed by 1011

Special Issue Editor


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Guest Editor
Division of Cognitive and Behavioral Therapy Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA
Interests: neurodegenerative diseases; biomarker discovery; Alzheimer's disease; neuroinflammation; precision medicine

Special Issue Information

Dear Colleagues,

Neurodegenerative diseases represent one of the most pressing medical challenges of our time, affecting millions worldwide and imposing enormous burdens on patients, families, and healthcare systems. The rising prevalence of conditions such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis underscores the urgent need for early detection, accurate diagnosis, and effective monitoring strategies. Central to addressing these challenges is the identification and validation of genetic biomarkers that can transform our approach to neurodegenerative disease management through precision medicine approaches.

This Special Issue aims to showcase cutting-edge research in the discovery, development, and clinical application of genetic biomarkers for neurodegenerative diseases, with a particular focus on those enabling earlier diagnosis, differential diagnosis, risk stratification, and the monitoring of disease progression. We invite submissions that explore diverse genetic biomarker approaches, including polygenic risk scores and their clinical implementation, rare variant discovery and functional validation, gene expression signatures and transcriptomic biomarkers, epigenetic modifications (DNA methylation, histone modifications, and non-coding RNAs), pharmacogenomic markers for treatment response prediction, and multi-omics integration that incorporates genetic data with proteomic, metabolomic, and neuroimaging findings to enhance diagnostic accuracy and prognostic value.

Of particular interest are studies that demonstrate translational potential, moving from genetic discoveries to clinical applications, including validation in diverse populations, consideration of genetic ancestry and population stratification, assessment of scalability and cost-effectiveness of genetic testing platforms, and evaluation of potential pathways to regulatory approval. We also welcome research on gene–environment interactions, genetic modifiers of disease penetrance and progression, and novel computational approaches for genetic biomarker discovery and validation in neurodegenerative diseases.

Dr. Arash Salardini
Guest Editor

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Keywords

  • neurodegenerative diseases
  • biomarker discovery
  • Alzheimer's disease
  • Parkinson's disease
  • precision medicine
  • machine learning

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Published Papers (1 paper)

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Research

22 pages, 4657 KB  
Article
Multi-Transcriptome-Informed Network Pharmacology Reveals Novel Biomarkers and Therapeutic Candidates for Parkinson’s Disease
by Md. Al Amin Pappu, Md. Alamin, Md Al Noman, Most. Humaira Sultana, Md. Foysal Ahmed, Md. Sanoar Hossain, Md. Abdul Latif, Md. Fahim Faysal, AKM Azad, Salem A. Alyami, Naif Alotaibi and Md. Nurul Haque Mollah
Genes 2025, 16(12), 1459; https://doi.org/10.3390/genes16121459 - 7 Dec 2025
Viewed by 573
Abstract
Background: Parkinson’s disease (PD) is a complex neurodegenerative disorder in aged people with multifaceted molecular underpinnings. It poses a severe threat to millions of older adults worldwide. The understanding of the molecular mechanisms of PD development and the performance of its therapeutic strategies [...] Read more.
Background: Parkinson’s disease (PD) is a complex neurodegenerative disorder in aged people with multifaceted molecular underpinnings. It poses a severe threat to millions of older adults worldwide. The understanding of the molecular mechanisms of PD development and the performance of its therapeutic strategies has not yet reached a satisfactory level. Methods: This study integrated six transcriptomic datasets to uncover key genes (KGs) and their underlying pathogenic mechanisms, providing insights into potential therapeutic strategies for PD. We designed a comprehensive computational pipeline using various bioinformatics tools and databases to investigate PD-causing KGs, focusing on their functions, pathways, regulatory mechanisms, and potential therapeutic drug molecules. Results: In order to explore PD-causing KGs, we initially identified 303 differentially expressed genes (DEGs) between PD and control samples with 204 upregulated and 99 downregulated DEGs using the LIMMA approach with threshold values at Adj. p-value < 0.05 and abs (log2FC) ≥ 1.0. Then, protein–protein interaction (PPI) network analysis pinpointed seven top-ranked DEGs (GAPDH, PTEN, CCND1, APOE, ESR1, MAPK3/ERK1, and SNCA) as KGs or central modulators of PD pathogenesis. Regulatory network analysis of KGs identified 3 top-ranked transcription factors (FOXC1, NFKB1, and TFAP2A) and 6 microRNAs (hsa-let-7b-5p, hsa-mir-16-5p, and others) as the pivotal regulators of KGs. Gene Ontology (GO) terms and KEGG pathway enrichment analyses with KGs revealed several crucial biological processes, molecular functions, cellular components, and neurodegenerative pathways associated with the development of PD. Finally, the top five molecules guided by KGs (Nilotinib, Bromocriptine, Withaferin-A, Celastrol, and Donepezil) were identified as promising drug candidates against PD and validated computationally through ADME/T analysis and molecular dynamics simulation studies. Conclusions: The findings of this study may serve as valuable resources for developing effective treatment strategies for PD patients. Full article
(This article belongs to the Special Issue Novel Biomarkers of Neurodegenerative Diseases)
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