Predicting the risk of neurodegenerative diseases based on clinical microsignals
Bondarenko YD, Kauk OI (2026)
Publication Type: Journal article
Publication year: 2026
Book Volume: 32
Pages Range: 32-50
Journal Issue: 2
DOI: 10.25305/unj.341180
Abstract
Background: Neurodegenerative diseases, in particular Parkinson’s disease, remain difficult to diagnose due to the late manifestation of classical motor symptoms, when significant neuronal degeneration has already occurred. A growing body of evidence suggests that subtle non-motor prodromal symptoms — so-called phenotypic microsignals (PMS) may precede the clinical manifestation of neurodegenerative diseases by several years. These symptoms reflect early neurochemical disturbances and disruptions of neural networks, especially in evolutionarily ancient brain structures vulnerable to α-synuclein pathology. Objective: To identify and systematize early clinical phenotypic microsignals observed during initial outpatient visits and potentially associated with neurodegenerative processes, as well as to develop a clinical risk stratification tool for the prodromal stage based on retrospective analysis and prospective observation. Materials and methods: A combined retrospective-prospective observational study conducted at Kharkiv National Medical University during the period from January 2020 to August 2025. The study involved 112 patients aged 48 to 76 years, who were divided into three groups: group 1 (n=28, prodromal/non-manifest pathology), group 2 (n=56, manifest pathology (Alzheimer’s disease (n=16), Parkinson’s disease (n=28), dementia with Lewy bodies (n=9), progressive supranuclear palsy (n=3)), group 3 (control, n=28, individuals without clinical signs of neurodegenerative pathology, matched by age and sex). A 48-point PMS scale was developed and validated, assessing 30 clinical markers across cognitive, motor, autonomic, sensory and affective domains. Patients underwent comprehensive neurological examination, cognitive testing (MMSE — Mini-Mental State Examination, MoCA — Montreal Cognitive Assessment, FAB — Frontal Assessment Battery), magnetic resonance imaging and standardized assessment of non-motor symptoms. ROC analysis was used to evaluate the predictive accuracy of the scale. Results: Patients with manifest neurodegenerative diseases had significantly higher PMS scale scores (mean value ‒ 27.8±6.3 points) compared with the prodromal group (11.4±3.8, p<0.001) and control (2.8±2.1). ROC analysis demonstrated excellent diagnostic accuracy for comparison of manifest pathology with control (area under the curve (AUC) ‒ 0.982, sensitivity ‒ 96.4%, specificity ‒ 92.9% at a threshold value ≥13 points), good accuracy for prodromal pathology compared with control (AUC ‒ 0.956, sensitivity ‒ 89.3%, specificity ‒ 89.3% at a threshold value ≥7 points) and for differentiation of manifest and prodromal pathology (AUC ‒ 0.891, sensitivity ‒ 78.6%, specificity ‒ 85.7% at a threshold value ≥21 points). Risk stratification identified three categories: low risk (0–12 points, <5% probability of conversion within 24 months), moderate risk (13–24 points, 20–30% conversion) and high risk (≥25 points, >50% conversion). In the prodromal group, the most frequent microsignals were REM sleep behavior disorder (67.9%), hyposmia (71.4%), chronic constipation (78.6%), subjective cognitive decline (82.1%), reduced arm swing during walking (46.4%) and hypomimia (42.9%). Conclusions: The PMS scale is a clinically effective and low-cost tool for identifying individuals at risk of developing neurodegenerative diseases years before the manifestation of classical symptoms. Its use does not require specialized equipment and is feasible at the level of primary medical care through history taking, observation and basic neurological examination. The scale demonstrates high psychometric properties and provides risk stratification, enabling individualized monitoring and early intervention strategies. This approach marks a transition to proactive diagnostic models in neurology. It has significant value for screening programs among middle-aged and older individuals with subclinical neurobehavioral complaints. Early detection using PMS assessment allows timely application of neuroprotective and preventive interventions, potentially altering the course of the disease before irreversible neuronal loss.
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Ukraine (UA)How to cite
APA:
Bondarenko, Y.D., & Kauk, O.I. (2026). Predicting the risk of neurodegenerative diseases based on clinical microsignals. , 32(2), 32-50. https://doi.org/10.25305/unj.341180
MLA:
Bondarenko, Yaroslav D., and Oksana I. Kauk. "Predicting the risk of neurodegenerative diseases based on clinical microsignals." 32.2 (2026): 32-50.
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