Delta Power in SLC6A1-Related Neurodevelopmental Disorder: Operationalizing Quantitative EEG Metrics for Biomarker Development

Hamza Dahshi; Marie Varnet; Kimberly Goodspeed; Jacob Tiller; Dallas Armstrong; Deepa Sirsi

doi:10.3390/neurolint18030058

Delta Power in SLC6A1-Related Neurodevelopmental Disorder: Operationalizing Quantitative EEG Metrics for Biomarker Development

Neurol Int. 2026 Mar 18;18(3):58. doi: 10.3390/neurolint18030058.

Authors

Hamza Dahshi^{1

2}, Marie Varnet³, Kimberly Goodspeed^{3

4}, Jacob Tiller^{5

6}, Dallas Armstrong³, Deepa Sirsi³

Affiliations

¹ Medical Scientist Training Program, School of Medicine, Case Western Reserve University, 9501 Euclid Ave, Cleveland, OH 44106, USA.
² O'Donnell Brain Institute, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, USA.
³ Department of Neurology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, USA.
⁴ Ultragenyx Pharmaceutical Inc., 60 Leveroni Court, Novato, CA 94949, USA.
⁵ Division of Biology and Medicine, Department of Neuroscience, Brown University, 1 Prospect St, Providence, RI 02912, USA.
⁶ SLC6A1 Connect, 1939 Temperence Hill Drive, Frisco, TX 75034, USA.

Abstract

Introduction: SLC6A1-related neurodevelopmental disorder (SLC6A1-NDD) is an epileptic encephalopathy linked to mutations in the SLC6A1 gene and is characterized by early-onset seizures and developmental delays. Despite the growing recognition of SLC6A1 as a major cause of early-onset epilepsy, the electrophysiological changes associated with the disorder remain inadequately characterized. This study aims to identify electrophysiological biomarkers of SLC6A1-NDD by characterizing EEG delta power using automated tools, EEGLAB (v2023.1) and Persyst 13, exploring age- and state-related effects.

Methods: We analyzed EEG recordings from 20 patients with SLC6A1-NDD and 20 neurotypical age- and sex-matched controls using EEGLAB and Persyst, quantifying delta power and related metrics. The Wilcoxon signed-rank method tested for differences between patients and controls, area under the curve (AUC) values evaluated patient classifier models, and Pearson's correlation assessed concordance between EEGLAB and Persyst.

Results: Patients with SLC6A1-NDD exhibited significantly elevated delta power (19.4 ± 4.1) compared to controls (14.2 ± 3.0; p < 0.001). The mean delta power showed an age-dependent increasing trend in patients (b = 0.5), contrasting with a decline in controls (b = -1.0; p < 0.001). In Persyst, the frequency of delta activity above an optimized threshold best differentiated patients from controls in wake epochs (AUC = 0.93). Concordance between EEGLAB and Persyst was one-to-one but with moderate variability (R² = 0.644; p < 0.001).

Conclusions: Elevated delta power is a notable feature of SLC6A1-NDD. Cross-platform comparison demonstrates the feasibility of quantitative EEG analysis, while imperfect concordance highlights the need for pipeline standardization. Future work should validate these findings in larger cohorts and, as suitable reference data emerge, benchmark delta power metrics against age-matched children with other developmental and epileptic encephalopathies.

Keywords: EEG; Epilepsy; SLC6A1; delta power.

Abstract

Grants and funding