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Biomedicines
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Diagnosis and Treatment of Neurodegenerative Diseases in the Era of...
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Diagnosis and Treatment of Neurodegenerative Diseases in the Era of Precision Medicine

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Neurobiology and Clinical Neuroscience".

Deadline for manuscript submissions: closed (28 February 2025) | Viewed by 1331

Special Issue Editor

Dr. Rohan Gupta

E-Mail Website
Guest Editor
School of Medicine Columbia, University of South Carolina, Columbia, SC, USA
Interests: machine learning; neurodegeneration; inflammation; artificial intelligence; bioinformatics

Special Issue Information

Dear Colleagues,

Neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, Amyotrophic Lateral Sclerosis, and Multiple Sclerosis, are characterized by the loss of neuronal cells that hampers the learning and cognitive abilities of the brain. Studies have suggested that multiple factors, such as oxidative stress, environmental pollutants, mitochondrial dysfunction, inflammatory molecules, internal genetic factors, post-translational modifications, and others, contribute to the pathogenesis and progression of neurodegenerative diseases. However, a clear mechanism is still exclusive. The aggregation of toxic proteins, followed by the apoptosis of neuronal cells in the brain, is believed to be the main cause of disease etiology. Despite extensive research on the subject matter, early diagnosis and treatment strategies of the diseases are still unknown. Further, the era of technology and the involvement of artificial intelligence have led to the era of precision medicine.

The current Special Issue is to understand the mechanism of disease pathology to identify novel therapeutic and diagnostic biomarkers of neurodegenerative diseases. Furthermore, the Special Issue aims to understand the drug–protein interaction that enhances the knowledge of therapeutics required for neurodegenerative diseases. This issue also welcomes studies on drug discovery, developing novel AI-based algorithms for drug discovery, identifying therapeutic and diagnostic biomarkers, and novel neuroimaging algorithms and techniques. We cordially invite authors and investigators within this complex field of universal interest to submit original research or review articles pertaining to this Special Issue.

Dr. Rohan Gupta
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Biomedicines 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

  • drug discovery and development
  • machine learning
  • precision medicine
  • neurodegenerative diseases
  • artificial intelligence
  • diagnostic biomarkers

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Published Papers (2 papers)

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Research

15 pages, 1467 KiB  
Article
Modelling Population Genetic Screening in Rare Neurodegenerative Diseases
by Thomas P. Spargo, Alfredo Iacoangeli, Mina Ryten, Francesca Forzano, Neil Pearce and Ammar Al-Chalabi
Biomedicines 2025, 13(5), 1018; https://doi.org/10.3390/biomedicines13051018 - 23 Apr 2025
Viewed by 260
Abstract
Importance: Genomic sequencing enables the rapid identification of a breadth of genetic variants. For clinical purposes, sequencing for small genetic variations is considered a solved problem, while challenges remain for structural variants, given the lower sensitivity and specificity. Interest has recently risen among [...] Read more.
Importance: Genomic sequencing enables the rapid identification of a breadth of genetic variants. For clinical purposes, sequencing for small genetic variations is considered a solved problem, while challenges remain for structural variants, given the lower sensitivity and specificity. Interest has recently risen among governing bodies in developing protocols for population-wide genetic screening. However, usefulness is constrained when the probability of being affected by a rare disease remains low, despite a positive genetic test. This is a common scenario in neurodegenerative disorders. The problem is recognised among statisticians and statistical geneticists but is less well-understood by clinicians and researchers who will act on these results, and by the general public who might access screening services directly without the appropriate support for interpretation. Observations: We explore the probability of subsequent disease following genetic screening of several variants, both single nucleotide variants (SNVs) and larger repeat expansions, for two neurological conditions, Huntington’s disease (HD) and amyotrophic lateral sclerosis (ALS), comparing these results with screening for phenylketonuria, which is well-established. The risk following a positive screening test was 0.5% for C9orf72 in ALS and 0.4% for HTT in HD when testing repeat expansions, for which the test had sub-optimal performance (sensitivity = 99% and specificity = 90%), and 12.7% for phenylketonuria and 10.9% for ALS SOD1 when testing pathogenic SNVs (sensitivity = 99.96% and specificity = 99.95%). Subsequent screening confirmation via PCR for C9orf72 led to a 2% risk of developing ALS as a result of the reduced penetrance (44%). Conclusions and Relevance: We show that risk following a positive screening test result can be strikingly low for rare neurological diseases, even for fully penetrant variants such as HTT, if the test has sub-optimal performance. Accordingly, to maximise the utility of screening, it is vital to prioritise protocols with very high sensitivity and specificity, and a careful selection of markers for screening, giving regard to clinical interpretability, actionability, high penetrance, and secondary testing to confirm positive findings. Full article
(This article belongs to the Special Issue Diagnosis and Treatment of Neurodegenerative Diseases in the Era of Precision Medicine)
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14 pages, 983 KiB  
Article
Associations of Abnormal Sleep Duration and Chronotype with Higher Risk of Incident Amyotrophic Lateral Sclerosis: A UK Biobank Prospective Cohort Study
by Gan Zhang, Wen Cao, Zhuoya Wang, Kailin Xia, Binbin Deng and Dongsheng Fan
Biomedicines 2025, 13(1), 49; https://doi.org/10.3390/biomedicines13010049 - 28 Dec 2024
Viewed by 674
Abstract
Background: The occurrence of sleep disturbances in amyotrophic lateral sclerosis (ALS) patients is widely reported. However, there is still a lack of reliable evidence of a relationship between sleep disturbances and the risk of developing ALS. The aim of this study was to [...] Read more.
Background: The occurrence of sleep disturbances in amyotrophic lateral sclerosis (ALS) patients is widely reported. However, there is still a lack of reliable evidence of a relationship between sleep disturbances and the risk of developing ALS. The aim of this study was to prospectively investigate the longitudinal associations between sleep traits and the risk of incident ALS. Methods: We included information from 409,045 individuals from the prospective cohort of the UK Biobank. Sleep traits at baseline were measured using a standardized questionnaire. All sleep traits were analyzed in relation to the subsequent incidence of ALS using Cox proportional hazards models. Results: Multivariate analysis showed that 6–7 h of sleep was related to the lowest risk for ALS. A long sleep duration (≥8 h) was associated with an increased risk of ALS incidence (HR: 1.31, 95% CI: 1.07–1.61; p = 0.009). A short sleep duration (<6 h) was associated with an increased risk of ALS incidence (HR: 1.91, 95% CI: 1.10–3.30, p = 0.021) in females. In participants aged ≥65 years, eveningness was associated with increased ALS risk (HR: 1.32, 95% CI: 1.08–1.61; p = 0.006). Conclusion: Our results hint at a sleep duration that is too short or too long, and certain chronotypes might be related to the risk of developing ALS. Despite the limitations imposed by the study design and the subjectivity of sleep information, our findings suggest that sleep disturbances may influence the risk of developing ALS. Full article
(This article belongs to the Special Issue Diagnosis and Treatment of Neurodegenerative Diseases in the Era of Precision Medicine)
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