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Utilizing Multi-Omics to Investigate Neurodegenerative Disorders
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Utilizing Multi-Omics to Investigate Neurodegenerative Disorders

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Neurogenomics".

Deadline for manuscript submissions: closed (25 March 2026) | Viewed by 2349

Special Issue Editor

Dr. Muhammad Ali

E-Mail Website
Guest Editor
School of Medicine, Washington University, St. Louis, MI 63110, USA
Interests: proteomics; transcriptomics; neurodegeneration; Alzheimer’s disease; gene regulatory networks

Special Issue Information

Dear Colleagues,

Neurodegenerative disorders, including Alzheimer's disease (AD), Parkinson's disease (PD), Dementia with Lewy bodies (DLB), Frontotemporal dementia (FTD), and Amyotrophic Lateral Sclerosis (ALS), present significant challenges due to their complex and multifactorial nature. Understanding the intricate molecular mechanisms driving these diseases requires comprehensive approaches that integrate data across multiple biological layers.

The advent of multi-omics technologies—encompassing genomics, transcriptomics, proteomics, metabolomics, and epigenomics—has revolutionized our ability to explore disease biology. By combining these diverse datasets, researchers can uncover novel biomarkers, identify therapeutic targets, and enhance disease classification. Multi-omics integration also offers a systems-level perspective on the pathological pathways contributing to neurodegeneration, leading to a deeper understanding of disease progression and heterogeneity.

This Special Issue of Genes invites original research articles, reviews, and methodological advancements focused on applying multi-omics approaches to investigate neurodegenerative disorders. We encourage submissions that explore the following topics:

  • Integrative analyses linking genetic, transcriptomic, and proteomic data to uncover molecular signatures of neurodegeneration.
  • Biomarker discovery and validation using omics datasets.
  • Pathway enrichment and network-based analyses to identify dysregulated biological processes.
  • Novel computational approaches for multi-omics data integration and interpretation.
  • Studies investigating the role of genetic variants and regulatory mechanisms in disease progression.

By bringing together interdisciplinary research, this Special Issue aims to foster collaboration and advance our understanding of the complex biology underlying neurodegenerative diseases. We look forward to receiving contributions that push the boundaries of multi-omics research and offer insights into potential therapeutic strategies.

Dr. Muhammad Ali
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • neurodegeneration
  • central nervous system
  • diagnosis
  • prognosis
  • biomarkers
  • predictive modeling
  • brain
  • cerebrospinal fluid
  • plasma
  • multi-omics

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Published Papers (3 papers)

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Research

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18 pages, 1145 KB  
Article
Genetic Associations of Parkinson’s Disease Clinical, Pathological, and Data-Driven Subtypes
by Ahmed Negida, Moaz Elsayed Abouelmagd, Belal Mohamed Hamed, Yousef Hawas, Aya Dziri, Yasmin Negida, Brian D. Berman and Matthew J. Barrett
Genes 2026, 17(4), 449; https://doi.org/10.3390/genes17040449 - 13 Apr 2026
Viewed by 408
Abstract
Background: Parkinson’s disease (PD) is clinically heterogeneous, yet the genetic architecture underlying this heterogeneity remains incompletely understood. We examined the genetic correlates of four complementary PD subtyping frameworks: the clinical motor subtype (tremor-dominant [TD] vs. postural instability/gait difficulty [PIGD]), alpha-synuclein seed amplification assay [...] Read more.
Background: Parkinson’s disease (PD) is clinically heterogeneous, yet the genetic architecture underlying this heterogeneity remains incompletely understood. We examined the genetic correlates of four complementary PD subtyping frameworks: the clinical motor subtype (tremor-dominant [TD] vs. postural instability/gait difficulty [PIGD]), alpha-synuclein seed amplification assay status (SAA+ vs. SAA−), the pathological subtype (brain-first vs. body-first, based on the presence of REM sleep behavior disorder), and the data-driven subtype (diffuse malignant [DM] vs. mild-motor predominant [MMP] vs. intermediate [IM]). Methods: We analyzed 1390 PD patients from the Parkinson’s Progression Markers Initiative (PPMI) with genotypes available for seven PD-associated genes (LRRK2, GBA1, SNCA, PRKN, PINK1, PARK7, VPS35), including specific variant resolutions (LRRK2 G2019S, R1441G/C/H; GBA1 N409S, severe variants; SNCAA53T), and APOE (ε2/ε3/ε4 alleles). Genetic variant frequencies were compared across subtypes using chi-square or Fisher’s exact tests with the Benjamini–Hochberg false discovery rate (FDR) correction. Effect sizes were quantified using Cramér’s V. multivariable logistic regression estimated adjusted odds ratios with Wald-based 95% confidence intervals. Results: Among genotyped PD patients, LRRK2 carriers constituted 13.7% (190/1390; 170 G2019S, 18 R1441G/C/H), GBA1 8.6% (119/1390; 96 N409S, 23 severe), and SNCA 2.0% (28/1390; all A53T). APOE ε4 carriers comprised 23.4% (323/1380). SAA-negative patients were markedly enriched for LRRK2 variants (37.1% vs. 10.2%, p = 3.7 × 10−19, q < 0.001, V = 0.25), specifically G2019S (28.5% vs. 9.6%, p = 4.9 × 10−11, q < 0.001) and R1441G/C/H (7.9% vs. 0.5%, p = 2.7 × 10−12, q < 0.001). Body-first PD was enriched for GBA1 carriers (12.3% vs. 6.7%, p = 0.004, q = 0.021) and had less LRRK2 carriers (7.9% vs. 15.0%, p = 0.002, q = 0.013). The DM subtype had the highest GBA1 frequency (14.0% vs. MMP 5.9%, p < 0.001, q = 0.003). After FDR correction, 10 out of 48 univariate tests remained significant. Clinical subtypes (TD vs. PIGD) showed only nominal LRRK2 differences that did not survive FDR correction. The APOE genotype did not differ across any framework. Conclusions: PD subtypes defined by alpha-synuclein pathology (SAA), pathological onset pattern (brain-first/body-first), and data-driven classification (DM/MMP/IM) show distinct genetic profiles that survive multiple comparison correction. LRRK2 variants strongly associate with SAA negativity (V = 0.25); GBA1 variants associate with the severe body-first onset and the diffuse malignant subtype. Full article
(This article belongs to the Special Issue Utilizing Multi-Omics to Investigate Neurodegenerative Disorders)
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14 pages, 1905 KB  
Article
Region-Specific NRF2 Signaling in HIV-Associated Neurocognitive Disorders: A Transcriptomic and Computational Histology Study
by Grazia Scuderi, Serena Spampinato, Michelino Di Rosa, Paolo Fagone and Giuseppe Nunnari
Genes 2026, 17(2), 195; https://doi.org/10.3390/genes17020195 - 5 Feb 2026
Viewed by 509
Abstract
Background/Objectives. Oxidative stress is a key contributor to HIV-associated neurocognitive disorders (HANDs), yet the regional organization and functional engagement of the NRF2 antioxidant pathway in the human brain remain incompletely defined. This study aimed to characterize NRF2 pathway architecture, baseline brain expression, and [...] Read more.
Background/Objectives. Oxidative stress is a key contributor to HIV-associated neurocognitive disorders (HANDs), yet the regional organization and functional engagement of the NRF2 antioxidant pathway in the human brain remain incompletely defined. This study aimed to characterize NRF2 pathway architecture, baseline brain expression, and disease-associated transcriptional and coexpression remodeling across HAND stages. Methods. The NRF2 signaling network was reconstructed using curated pathway data and protein–protein interaction analysis to identify central hub genes. Baseline expression in the normal human cortex was assessed using the Human Protein Atlas. Transcriptomic profiling of postmortem brain samples from individuals with HAND (GSE35864) was performed using differential expression, hierarchical clustering, and region-specific coexpression analyses across white matter, frontal cortex, and basal ganglia. Results. Low-to-medium baseline expression of NRF2-related genes was observed in the normal cortex. Bulk differential expression revealed minimal NRF2 pathway modulation in the frontal cortex and basal ganglia. On the other hand, white matter exhibited robust NRF2 transcriptional activation specifically in HIV encephalitis (HIVE). Coexpression analysis performed specifically within HAND samples revealed a highly coordinated transcriptional organization of the NRF2 signaling network across all analyzed brain regions. Conclusions. NRF2 signaling in HAND is preserved as a coordinated transcriptional network but is selectively activated in white matter during encephalitic disease, highlighting region- and cell-type-targeted therapeutic opportunities. Full article
(This article belongs to the Special Issue Utilizing Multi-Omics to Investigate Neurodegenerative Disorders)
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Review

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16 pages, 1791 KB  
Review
Application of Omics Analysis in the Clinical Practice and Research of Transthyretin Amyloidosis
by Hidenori Moriyama, Faiyza Akil Shaikh and Toshifumi Yokota
Genes 2026, 17(3), 333; https://doi.org/10.3390/genes17030333 - 18 Mar 2026
Viewed by 543
Abstract
Transthyretin amyloidosis (ATTR) is a progressive disease characterized by systemic deposition of transthyretin-derived amyloid. Although the recent advent of disease-modifying therapies has expanded treatment options, substantial unmet needs remain, such as understanding disease heterogeneity, predicting treatment response, and prognostic stratification. In this review, [...] Read more.
Transthyretin amyloidosis (ATTR) is a progressive disease characterized by systemic deposition of transthyretin-derived amyloid. Although the recent advent of disease-modifying therapies has expanded treatment options, substantial unmet needs remain, such as understanding disease heterogeneity, predicting treatment response, and prognostic stratification. In this review, we highlight the current and emerging roles of omics technologies in both clinical and research settings of ATTR, including genomics and its integration with other modalities. Currently, omics technologies are applied in clinical settings for accurate disease typing. Clinical samples are utilized to identify risk factors beyond specific transthyretin variants via genomics and epigenomics and to discover promising biomarkers via proteomics. Accumulating findings from omics analyses using cell and animal models are also facilitating the elucidation of the complex pathology of ATTR. Nevertheless, the application of omics analysis in ATTR research is still developing. Moving forward, it is expected to play a central role in accumulating datasets, leveraging cutting-edge technologies, utilizing integrated multi-omics, and bridging basic and clinical research. These advancements are expected to further accelerate the implementation of next-generation therapeutic strategies and precision medicine. Full article
(This article belongs to the Special Issue Utilizing Multi-Omics to Investigate Neurodegenerative Disorders)
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