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Diagnostics
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Genetic Diagnosis of Rare Neurological Disorders: Advances, Challenges, and Clinical...
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Genetic Diagnosis of Rare Neurological Disorders: Advances, Challenges, and Clinical Impact

A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Pathology and Molecular Diagnostics".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 1110

Special Issue Editor

Dr. Georgia Xiromerisiou

E-Mail Website
Guest Editor
Institute of Preventive Neurology and Brain Helath, Thessaloniki, Greece
Interests: neuodegenerative disorders; neurogenetics; movement disorders
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, the diagnosis of rare neurological disorders has been revolutionized by advances in genetic testing and molecular research. What was once a diagnostic odyssey for many patients is now a process guided by powerful genomic tools, which help clinicians and researchers uncover the underlying causes of complex conditions.

This Special Issue, “Genetic Diagnosis of Rare Neurological Disorders: Advances, Challenges, and Clinical Impact”, brings together diverse perspectives on how genetic discoveries are reshaping the way we understand, diagnose, and manage rare neurological diseases. We welcome contributions that highlight new gene findings, cutting-edge diagnostic technologies, clinical case studies, and real-world challenges in implementing genetic testing in clinical practice.

We are especially interested in work that bridges the gap between research and patient care, from improved diagnostic accuracy to implications for treatment, counseling, and long-term management. Our goal is to create a Special Issue that reflects the collaborative nature of this field and inspires continued innovation in the service of patients and families living with rare neurological conditions.

Dr. Georgia Xiromerisiou
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. Diagnostics is an international peer-reviewed open access semimonthly 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

  • rare neurological disorders
  • genetic diagnosis
  • neurogenetics
  • next-generation sequencing
  • genotype–phenotype correlation
  • molecular diagnostics
  • clinical impact
  • personalized medicine
  • translational research
  • undiagnosed diseases

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Published Papers (2 papers)

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30 pages, 2492 KB  
Article
Phenotype Correlations of Neurological Manifestations in Wolfram Syndrome: Predictive Modeling in a Spanish Cohort
by Gema Esteban-Bueno, Luisa-María Botella and Juan Luis Fernández-Martínez
Diagnostics 2025, 15(24), 3213; https://doi.org/10.3390/diagnostics15243213 - 16 Dec 2025
Abstract
Background: Wolfram syndrome (WS) is an ultrarare neuroendocrine disorder caused by pathogenic variants in WFS1, frequently leading to progressive neurological, autonomic, and cognitive impairment. Anticipating neurological trajectories remains challenging due to marked phenotypic variability and limited genotype–phenotype data. Methods: Forty-five genetically confirmed patients [...] Read more.
Background: Wolfram syndrome (WS) is an ultrarare neuroendocrine disorder caused by pathogenic variants in WFS1, frequently leading to progressive neurological, autonomic, and cognitive impairment. Anticipating neurological trajectories remains challenging due to marked phenotypic variability and limited genotype–phenotype data. Methods: Forty-five genetically confirmed patients with WS were evaluated between 1998 and 2024 in Spain. All WFS1 variants were systematically classified by exon, zygosity, protein-level functional impact, and predicted wolframin production (Classes 0–3). Machine learning models (Random Forests with engineered gene–gene interaction terms) were applied to predict neurological manifestations and identify the strongest genetic determinants of symptom severity. Results: Neurological involvement was present in 93% of patients. The most prevalent manifestations were absence of gag reflex (67%), gait instability (64%), dysphagia (60%), and sialorrhea (60%), followed by dysmetria (56%), impaired tandem gait (53%), anosmia (44%), dysarthria (44%), and adiadochokinesia (42%). Most symptoms emerged in early adulthood (23–26 years), whereas cognitive decline occurred later (29.9 ± 12.2 years). Homozygosity for truncating variants—particularly c.409_424dup16 (Val142fsX110)—and complete loss of wolframin production (Class 0; 67–83% across symptoms) were the strongest predictors of early and severe neurological involvement. Machine learning models achieved high discrimination for ataxia, gait instability, and absent gag reflex (AUC 0.63–0.86; calibrated AUC up to 0.97), identifying Mut1_Protein_Class and Mut2_Protein_Class as dominant predictors across all phenotypes, followed by coherent secondary effects from zygosity × exon interaction terms (Prod_mgm). Conclusions: Integrating detailed genetic classification with machine learning methods enables accurate prediction of neurological outcomes in WS. Protein-level dysfunction and allele interaction structure are the principal drivers of neurological vulnerability. This framework enhances precision diagnosis and offers a foundation for individualized surveillance, clinical risk stratification, and future therapeutic trial design in WFS1-related disorders. Full article
(This article belongs to the Special Issue Genetic Diagnosis of Rare Neurological Disorders: Advances, Challenges, and Clinical Impact)
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17 pages, 1314 KB  
Case Report
Isolated Non-Progressive Hemidystonia in a Patient Homozygous for H63D Variant of Hereditary Hemochromatosis: A Case Report and Systematic Literature Review of Movement Disorders in Hereditary Hemochromatosis
by Stefania Kalampokini, Andreas Plaitakis, Cleanthe Spanaki and Georgia Xiromerisiou
Diagnostics 2025, 15(17), 2275; https://doi.org/10.3390/diagnostics15172275 - 8 Sep 2025
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Abstract
Background: Hereditary hemochromatosis (HH) is a genetic disorder of iron metabolism, characterized by progressive iron accumulation. Neurological involvement, which can manifest with various symptoms, including movement disorders, is uncommon. Methods: We describe a case of a 50-year-old male patient homozygous for [...] Read more.
Background: Hereditary hemochromatosis (HH) is a genetic disorder of iron metabolism, characterized by progressive iron accumulation. Neurological involvement, which can manifest with various symptoms, including movement disorders, is uncommon. Methods: We describe a case of a 50-year-old male patient homozygous for the H63D variant of the HFE gene (encoding the human homeostatic iron regulator protein), who also carried the c.340+4T>C polymorphism in the same gene and has been affected since the age of 13 years by hemidystonia involving primarily his right upper extremity. His brain MRI, obtained approximately 35 years after initial symptoms, revealed iron deposition predominantly in the contralateral pallidum. The patient has shown no progression of his neurologic syndrome and no systemic manifestations over the 35 years of follow-up. Moreover, we conducted a comprehensive literature search in Pubmed and Web of Science in English of all previously reported cases of movement disorders due to HH. Results: We found 19 studies including 69 patients with movement disorders. Movement disorders associated with HH were, in most cases, hypokinetic and less commonly hyperkinetic. The most common movement disorders were tremor, parkinsonism, ataxia, and less frequent dystonia, chorea, and myoclonus. Movement disorders could either precede the diagnosis of HH, or they could occur with a variable latency ranging from a few months up to 12 years after disease onset. Iron deposition on brain MRI in the basal ganglia or cerebellum was found in few of those cases. Conclusions: The association between hemochromatosis and movement disorders is rare. Blood analysis, including serum iron, ferritin, and transferrin saturation levels, should be investigated in patients with movement disorders of unknown etiology or with iron deposition on neuroimaging. A better understanding of genotype-phenotype correlations would facilitate the early diagnosis of HH. Full article
(This article belongs to the Special Issue Genetic Diagnosis of Rare Neurological Disorders: Advances, Challenges, and Clinical Impact)
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