# Dimensionality reduction of quantitative EEG and clinical profiles uncover associations with monogenic neurodevelopmental phenotypes in SNAREopathies

**Authors:** Additya Sharma, Shilpa Anand, Cece C. Kooper, Michel J. A. M. van Putten, Arthur-Ervin Avramiea, Marina Diachenko, Arianne Bouman, Winde Mercken, Jennifer R. Ramautar, Huibert D. Mansvelder, Mathijs Verhage, Tjitske Kleefstra, Hilgo Bruining, Klaus Linkenkaer-Hansen

PMC · DOI: 10.3389/fnins.2025.1725623 · Frontiers in Neuroscience · 2026-01-27

## TL;DR

This study uses EEG data and clinical assessments to uncover how brain activity patterns relate to symptom severity in a rare group of neurodevelopmental disorders called SNAREopathies.

## Contribution

A novel multivariate framework links quantitative EEG deviations to clinical severity dimensions in SNAREopathies.

## Key findings

- Normative qEEG baselines revealed distinct spectro-spatial patterns in absolute power, relative power, and LRTC.
- Clinical PCA identified two severity dimensions: one integrating motor and communication deficits, and another reflecting EEG abnormalities.
- qEEG deviations correlated with specific clinical severity components, suggesting potential for tracking disease progression.

## Abstract

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.

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.

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.

Normative qEEG deviance metrics correspond to distinct clinical severity dimensions in SNAREopathies, making them promising for tracking disorder progression and therapeutic response.

## Linked entities

- **Genes:** STXBP1 (syntaxin binding protein 1) [NCBI Gene 6812], SYT1 (synaptotagmin 1) [NCBI Gene 6857]

## Full-text entities

- **Genes:** SYT1 (synaptotagmin 1) [NCBI Gene 6857] {aka BAGOS, P65, SVP65, SYT}, STXBP1 (syntaxin binding protein 1) [NCBI Gene 6812] {aka DEE4, MUNC18-1, N-Sec1, NSEC1, P67, RBSEC1}
- **Diseases:** deficits in mobility, hand function (MESH:D014086), Monogenic neurodevelopmental disorders (MESH:D002658), Clinical (MESH:D000075902)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

111 references — full list in the complete paper: https://tomesphere.com/paper/PMC12886349/full.md

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Source: https://tomesphere.com/paper/PMC12886349