Frontiers in neuroscience · 2026
Dimensionality reduction of quantitative EEG and clinical profiles uncover associations with monogenic neurodevelopmental phenotypes in SNAREopathies.
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Sharma Additya, Anand Shilpa, Kooper Cece C, van Putten Michel J A M, Avramiea Arthur-Ervin, Diachenko Marina, Bouman Arianne, Mercken Winde, Ramautar Jennifer R, Mansvelder Huibert D, Verhage Mathijs, Kleefstra Tjitske, Bruining Hilgo, Linkenkaer-Hansen Klaus
Аннотация
INTRODUCTION: Monogenic neurodevelopmental disorders (mNDDs) such as SNAREopathies exhibit complex electrophysiological features and diversity among clinical symptoms, complicating the mapping of electro-clinical relationships, essential for improving diagnosis and treatment monitoring. Establishing robust normative electrophysiological feature distributions from typically developing populations enables precise, individualized quantification of patient-specific abnormalities. Here, we introduce a multivariate framework to reveal patient-specific electrophysiological phenotypes and clinical severity dimensions of direct relevance for individual prognosis and therapeutic tracking.
METHODS: We analyzed resting-state electroencephalography (EEG) data from15 SNAREopathy subjects (STXBP1 and SYT1) and 96 age-matched healthy controls. EEG biomarkers, including absolute power, relative power, and long-range temporal correlations (LRTC), were estimated across frequency bands and functional networks. Normative baselines of EEG features were established using principal component analysis (PCA) on controls. We computed patient deviations from normative distributions using Mahalanobis distances. We summarized clinical severity by applying PCA to assessments of motor, manual, communication, adaptive functioning, and severity ranking of qualitative EEG.
RESULTS: The normative qEEG space identified diffuse, spectro-spatial patterns for absolute power, while relative power and LRTC displayed frequency-specific distributions. Clinical PCA identified a primary dimension of clinical impairment integrating deficits in mobility, hand function, communication, and adaptive behavior, whereas the secondary component captured the severity of qualitative EEG abnormalities. Patient deviations from normative absolute and relative power correlated with the primary, while LRTC deviations aligned with the secondary severity component.
DISCUSSION: Normative qEEG deviance metrics correspond to distinct clinical severity dimensions in SNAREopathies, making them promising for tracking disorder progression and therapeutic response.
METHODS: We analyzed resting-state electroencephalography (EEG) data from15 SNAREopathy subjects (STXBP1 and SYT1) and 96 age-matched healthy controls. EEG biomarkers, including absolute power, relative power, and long-range temporal correlations (LRTC), were estimated across frequency bands and functional networks. Normative baselines of EEG features were established using principal component analysis (PCA) on controls. We computed patient deviations from normative distributions using Mahalanobis distances. We summarized clinical severity by applying PCA to assessments of motor, manual, communication, adaptive functioning, and severity ranking of qualitative EEG.
RESULTS: The normative qEEG space identified diffuse, spectro-spatial patterns for absolute power, while relative power and LRTC displayed frequency-specific distributions. Clinical PCA identified a primary dimension of clinical impairment integrating deficits in mobility, hand function, communication, and adaptive behavior, whereas the secondary component captured the severity of qualitative EEG abnormalities. Patient deviations from normative absolute and relative power correlated with the primary, while LRTC deviations aligned with the secondary severity component.
DISCUSSION: Normative qEEG deviance metrics correspond to distinct clinical severity dimensions in SNAREopathies, making them promising for tracking disorder progression and therapeutic response.