Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease worldwide; therefore, since its initial description, significant progress has been made, yet a mystery remains regarding its pathogenesis and elusive root cause. The widespread distribution of pathological α-synuclein (αSyn) aggregates throughout the body raises inquiries regarding the etiology, which has prompted several hypotheses, with the most prominent one being αSyn-associated proteinopathy. The identification of αSyn protein within Lewy bodies, coupled with genetic evidence linking αSyn locus duplication, triplication, as well as point mutations to familial Parkinson’s disease, has underscored the significance of αSyn in initiating and propagating Lewy body pathology throughout the brain. In monogenic and sporadic PD, the presence of early inflammation and synaptic dysfunction leads to αSyn aggregation and neuronal death through mitochondrial, lysosomal, and endosomal functional impairment. However, much remains to be understood about αSyn pathogenesis, which is heavily grounded in biomarkers and treatment strategies. In this review, we provide emerging new evidence on the current knowledge about αSyn’s pathophysiological impact on PD, and its presumable role as a specific disease biomarker or main target of disease-modifying therapies, highlighting that this understanding today offers the best potential of disease-modifying therapy in the near future.

Background and Objectives: Sleep disorders are highly prevalent in society and require focused attention within healthcare systems. While patient history, reported complaints, and subjective sleep questionnaires can provide initial insights into potential sleep issues, polysomnography (PSG) remains the gold standard for diagnosing various sleep disorders. However, long waiting times for PSG appointments in many healthcare facilities pose challenges for timely diagnosis and treatment. This study aimed to evaluate the diagnostic value of subjective measures, including patient-reported parameters, in comparison to the objective findings of PSG. Materials and Methods: In this study, we retrospectively analysed the data from 562 patients who underwent clinical evaluation and PSG testing at the Hospital of Lithuanian University of Health Sciences Kaunas Clinics between 2018 and 2024. We report the diagnostic accuracy of different sleep questionnaires to detect various sleep disorders in our population. Results: We report the corresponding sensitivity and specificity values: the Epworth Sleepiness Scale (ESS)—73.2% and 44.1% for detecting severe obstructive sleep apnoea and 87.1% and 76.8% for detecting hypersomnia; the Insomnia Severity Index (ISI)—77.2% and 63.3% for detecting insomnia; the Berlin Questionnaire (BQ)—67.8% and 68.8% for detecting obstructive sleep apnoea; the Ullanlina Narcolepsy Scale (UNS)—84.4% and 58.9% for detecting hypersomnia; the Innsbruck REM Sleep Behaviour Disorder Inventory (RBD-I)—93.3% and 52.5% for detecting RBD; the REM Sleep Behaviour Disorder Single-Question Screen (RBD1Q)—73.3% and 81.0% for detecting RBD; and the Paris Arousal Disorder Severity Scale (PADSS)—57.5% and 90.5% for detecting parasomnia. Conclusions: When comparing our findings with the previous literature, we found that the screening tools generally demonstrated a slightly poorer performance in our population. However, our results suggest that certain individual questions from the comprehensive questionnaires may provide comparable diagnostic values, while reducing the patient burden. We propose a targeted screening approach that integrates fundamental clinical parameters, key screening questions, and selected validated questionnaires, enabling primary care and outpatient clinicians to more efficiently identify patients who may require referral for specialised sleep evaluation and treatment.

Background and Objectives: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder characterized by the degeneration of both upper and lower motor neurons, leading to the rapid decline of motor function. In recent years, dysfunction of the autonomic nervous system (ANS) has also been increasingly recognized as a contributing factor in various neurodegenerative diseases, including ALS. This study is the second publication from our ALS research cohort at Kaunas Clinics. Our previous work examined ultrasonographic changes in the phrenic nerve as a supplementary diagnostic approach for ALS. Materials and Methods: In the present study, we investigated ultrasonographic alterations of the vagus nerve within the same ALS cohort, aiming to explore correlations with ANS involvement. We performed high-resolution ultrasonography of the vagus nerve (VN), collected clinical data, conducted heart rate monitoring, and evaluated respiratory function. Results: We prospectively included 32 ALS patients meeting “Gold Coast” criteria and 64 age- and sex-matched control patients. The average onset of ALS was 57.97 ± 9.22 years, and the duration of the disease was15.41 ± 9.04 months. For ALS patients, we found significantly reduced vagus nerve cross-sectional area (CSA) at the level of the carotid artery bifurcation bilaterally compared to controls (right VN 1.86 ± 0.21 vs. 2.07 ± 0.18 mm², p < 0.001; left VN 1.69 ± 0.21 vs. 1.87 ± 0.21 mm², p < 0.001). Reduced values of the left VN positively correlated with the reduced values of FEV1% and sO₂. Conclusions: Our findings revealed a significant bilateral reduction in vagus nerve size in ALS patients compared to controls, suggesting that vagal atrophy may serve as a potential marker of autonomic dysfunction in ALS.

Background: Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by both motor and non-motor symptoms, including autonomic dysfunction. Structural alterations in the vagus nerve (VN) may contribute to PD pathophysiology, though existing data remain inconsistent. Objective: This study aimed to evaluate morphological changes in the VN using high-resolution ultrasound (USVN) and to investigate associations with autonomic symptoms, heart rate variability (HRV), and clinical characteristics in PD patients. Methods: A cross-sectional study was conducted involving 60 PD patients and 60 age- and sex-matched healthy controls. USVN was performed to assess VN cross-sectional area (CSA), echogenicity, and homogeneity bilaterally. Autonomic symptoms were measured using the Composite Autonomic Symptom Scale 31 (COMPASS-31). HRV parameters—SDNN, RMSSD, and pNN50—were obtained via 24 h Holter monitoring. Additional clinical data included Unified Parkinson’s Disease Rating Scale (UPDRS) scores, transcranial sonography findings, and third ventricle width. Results: PD patients showed significantly reduced VN CSA compared to controls (right: 1.90 ± 0.19 mm² vs. 2.07 ± 0.18 mm²; left: 1.74 ± 0.21 mm² vs. 1.87 ± 0.22 mm²; p < 0.001 and p < 0.02). Altered echogenicity and decreased homogeneity were also observed. Right VN CSA correlated with body weight, third ventricle size, and COMPASS-31 scores. Left VN CSA was associated with body size parameters and negatively correlated with RMSSD (p = 0.025, r = −0.21), indicating reduced vagal tone. Conclusions: USVN detects structural VN changes in PD, correlating with autonomic dysfunction. These findings support its potential as a non-invasive biomarker for early autonomic involvement in PD.

Background and Objectives: According to the literature, Restless Legs Syndrome (RLS) often remains underdiagnosed, with only a small proportion of individuals experiencing symptoms receiving an official diagnosis, highlighting the need for effective screening and diagnostic tools. The International Restless Legs Syndrome Study Group Rating Scale (IRLS) is a widely used tool for assessing the severity of Restless Legs Syndrome (RLS). However, a validated Lithuanian version has not yet been established. This study aimed to validate the Lithuanian version of the IRLS and assess its reliability, diagnostic performance, and correlation with clinical and demographic factors. Materials and Methods: This retrospective study included 136 patients who completed the Lithuanian version of the IRLS and underwent polysomnographic and clinical evaluations at the Department of Neurology of the Lithuanian University of Health Sciences between 2018 and 2024. A total of 134 patients were analyzed: 66 with clinically confirmed RLS and 68 controls without sleep disorders. Statistical analysis included the Mann–Whitney U test, chi-squared tests, Receiver Operating Characteristics (ROC) curve analysis, multivariate logistic regression, and Akaike Information Criterion (AIC). Results: The Lithuanian IRLS demonstrated good diagnostic accuracy with an Area Under the Curve (AUC) value of 0.843 (95% CI: 0.782–0.904), with an optimal cut-off score of 7.50, resulting in high sensitivity (92.4%) and moderate specificity (66.2%). Multivariate regression identified higher IRLS scores (OR = 1.212, 95% CI: 1.084–1.356, p < 0.001) and a higher periodic limb movements of sleep arousal index (PLMSAI) (OR = 1.961, 95% CI: 1.036–3.712, p = 0.039) as significant independent predictors of RLS. After adjustments for age and sex, both IRLS scores and PLMSAI remained statistically significant predictors. Conclusions: the Lithuanian version of IRLS is a valid and reliable instrument for assessing RLS severity. Its diagnostic performance supports its use in clinical and research settings for identifying and monitoring RLS in Lithuanian population.

Sleep disorders are highly prevalent in society and require focused attention within healthcare systems. While patient history, reported complaints, and subjective sleep questionnaires can provide initial insights into the potential sleep issues, polysomnography (PSG) remains the gold standard for diagnosing various sleep disorders. However, long waiting times for PSG appointments in many healthcare facilities pose challenges for timely diagnosis and treatment. This study aimed to evaluate the diagnostic value of subjective measures, including patient-reported parameters, in comparison to the objective findings of PSG. This study included 562 patients who underwent clinical evaluation and PSG testing at the Hospital of Lithuanian University of Health Sciences Kaunas Clinics between 2018 and 2024. We report diagnostic accuracy of different sleep questionnaires (Epworth Sleepiness Scale (ESS), Insomnia Severity Index (ISI), Berlin Questionnaire (BQ), Ullanlina Narcolepsy Scale (UNS), Innsbruck REM Sleep Behaviour Disorder Inventory (RBD-I), REM Sleep Behaviour Disorder Single-Question Screen (RBD1Q), Paris Arousal Disorders Severity Scale (PADSS)) to detect various sleep disorders in our population. When comparing our findings with previous literature, we found that the screening tools generally demonstrated slightly lower performance in our population. However, our results suggest that certain individual questions from comprehensive questionnaires may provide comparable diagnostic value while reducing patient burden. We propose a targeted screening approach that integrates fundamental clinical parameters, key screening questions, and selected validated questionnaires, enabling primary care and outpatient clinicians to more efficiently identify patients who may require referral for specialized sleep evaluation and treatment.