Marian Acera

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex disorder characterized by heterogeneous symptoms, which lack specific biomarkers for its diagnosis. This study aimed to investigate plasma neurofilament light chain (NfL) levels as a potential biomarker for ME/CFS and explore associations with cognitive, autonomic, and neuropathic symptoms. Here, 67 ME/CFS patients and 43 healthy controls (HCs) underwent comprehensive assessments, including neuropsychological evaluation, autonomic nervous system (ANS) testing, and plasma NfL level analysis. ME/CFS patients exhibited significantly higher plasma NfL levels compared to HC (F = 4.30, p < 0.05). Correlations were observed between NfL levels and cognitive impairment, particularly in visuospatial perception (r = −0.42; p ≤ 0.001), verbal memory (r = −0.35, p ≤ 0.005), and visual memory (r = −0.26; p < 0.05) in ME/CFS. Additionally, higher NfL levels were associated with worsened autonomic dysfunction in these patients, specifically in parasympathetic function (F = 9.48, p ≤ 0.003). In ME/CFS patients, NfL levels explained up to 17.2% of the results in cognitive tests. Unlike ME/CFS, in HC, NfL levels did not predict cognitive performance. Elevated plasma NfL levels in ME/CFS patients reflect neuroaxonal damage, contributing to cognitive dysfunction and autonomic impairment. These findings support the potential role of NfL as a biomarker for neurological dysfunction in ME/CFS. Further research is warranted to elucidate underlying mechanisms and clinical implications.

Background: We aimed to characterize subtypes of synucleinopathies using a clustering approach based on cognitive and other nonmotor data and to explore structural and functional magnetic resonance imaging (MRI) brain differences between identified clusters. Methods: Sixty-two patients (n = 6 E46K-SNCA, n = 8 dementia with Lewy bodies (DLB) and n = 48 idiopathic Parkinson’s disease (PD)) and 37 normal controls underwent nonmotor evaluation with extensive cognitive assessment. Hierarchical cluster analysis (HCA) was performed on patients’ samples based on nonmotor variables. T1, diffusion-weighted, and resting-state functional MRI data were acquired. Whole-brain comparisons were performed. Results: HCA revealed two subtypes, the mild subtype (n = 29) and the severe subtype (n = 33). The mild subtype patients were slightly impaired in some nonmotor domains (fatigue, depression, olfaction, and orthostatic hypotension) with no detectable cognitive impairment; the severe subtype patients (PD patients, all DLB, and the symptomatic E46K-SNCA carriers) were severely impaired in motor and nonmotor domains with marked cognitive, visual and bradykinesia alterations. Multimodal MRI analyses suggested that the severe subtype exhibits widespread brain alterations in both structure and function, whereas the mild subtype shows relatively mild disruptions in occipital brain structure and function. Conclusions: These findings support the potential value of incorporating an extensive nonmotor evaluation to characterize specific clinical patterns and brain degeneration patterns of synucleinopathies.

Introduction: The use of non-motor Parkinson’s disease (PD) features and genetic PD variants for clustering analyses may refine the phenotypic classification of idiopathic Lewy body (LB) diseases. Methods: One-hundred participants [n=7 E46K-SNCA (n=5 symptomatic and n=2 asymptomatic), n=4 PARK2, n=3 LRRK2, n=8 dementia with Lewy bodies (DLB), n=48 idiopathic PD (iPD), n=30 healthy controls (HC)] underwent a comprehensive evaluation of non-motor and motor PD features. Non-motor features were used to perform a hierarchical clustering analysis with patients and HC using a Scikit-learn toolkit. Results: Clustering analysis suggested three clusters of subjects including Cluster 1 or “ Normal-to-mild ”: young iPD (< 60 years) classified together with most HC and the variable LB burden genetic PD variants (PARK2 and LRRK2) characterized by having normal-to-mild cognitive disabilities and mild-to-moderate motor disability with few axial symptoms; Cluster 2 or “ Mild-to-moderate ”: old iPD patients (>60 years) classified together with the lowest symptomatic E46K-SNCA, PARK2 carriers and HCs, characterizing by having mild-to-moderate cognitive and motor disabilities with few axial symptoms; and Cluster 3 or “ Severe ”: old iPD (>60 years) classified together with all DLB and the most symptomatic E46K-SNCA carriers, characterized by having severe pattern-specific cognitive disabilities (visual attention, perception, processing speed, memory and executive functions) and severe motor PD manifestations with marked axial symptoms. Conclusions: Our study supports the potential value of incorporating genetic PD variants in data-driven iPD classification algorithms and the usefulness of non-motor PD features, especially visual cognition abnormalities, to facilitate the identification of aggressive LB diseases.