Elicit: Biomarkers in Lennox-Gastaut Syndrome Seizures (public)
Biomarkers in Lennox-Gastaut Syndrome Seizures
Which biomarkers are most commonly used for seizures associated with Lennox-Gastaut syndrome?
The most frequent biomarkers for Lennox-Gastaut syndrome seizures are electroencephalographic measurements, specifically slow spike-wave (SSW) and generalized paroxysmal fast activity (GPFA) patterns.
Abstract
Electroencephalography metrics appear most frequently for seizures in Lennox-Gastaut syndrome. Ten studies report slow spike‐wave (SSW) patterns, and seven document generalized paroxysmal fast activity (GPFA). Other EEG features also support diagnosis and treatment assessment. Standard, video, sleep, intracranial, and automated EEG methods serve as the primary detection techniques.
Imaging biomarkers (MRI, fMRI, PET), serum and cerebrospinal fluid markers, and measures of autonomic or cortical excitability are used less often. Studies employing these varied approaches link EEG findings to seizure type, network mapping, and treatment response, thereby establishing SSW and GPFA as the most common biomarkers in this context.
Methods
We analyzed 34 sources from an initial pool of 998, using six screening criteria. Each paper was reviewed for five key aspects relevant to our research question.
Papers identified with Elicit search
- n = 998
Papers screened out
- n = 964
Papers included for extraction
- n = 34
Data extraction
We asked a large language model to extract data from each paper, focusing on the following columns:
Study Design
- Identify the type of study design used:
- Observational studies (e.g., cross-sectional, cohort, case-control)
- Experimental studies (e.g., randomized controlled trial, interventional study)
- If the design is not clearly stated, write "Not clearly specified".
Biomarkers Investigated
- List ALL biomarkers examined related to Lennox-Gastaut syndrome:
- Include full names and abbreviations
- Specify the biological source (e.g., serum, cerebrospinal fluid)
- Note the measurement method used (e.g., ELISA, immunoassay)
Participant Demographics
- Total number of participants with Lennox-Gastaut syndrome
- Age range or mean age
- Gender distribution (if reported)
- Inclusion/exclusion criteria
- Any specific subgroups within the LGS population
Biomarker Findings
- Report statistical significance of findings for each biomarker investigated
- Note any correlations with clinical features (e.g., seizure severity, EEG characteristics)
Clinical Implications
- Extract conclusions about potential diagnostic or prognostic value of identified biomarkers
Results
Characteristics of Included Studies
| Study | Study Design | Population Size | Biomarker Types Studied | Primary Outcomes |
|---|---|---|---|---|
| Romero Milà et al., 2025 | Observational cohort study | 15 | EEG functional connectivity | Evolution from IESS to LGS, treatment response |
| Kobayashi et al., 2009 | Observational cross-sectional | 20 | EEG gamma rhythms | Pathophysiology of tonic seizures |
| Bare et al., 1998 | Observational cross-sectional | 38 | Video EEG | Identification of atypical absence seizures |
| Hödl et al., 2021 | Observational cross-sectional | 7 | Heart rate variability | Autonomic imbalance, VNS response |
Summary of Study Characteristics
- Study Design: 25 observational, 4 interventional, 2 systematic reviews, 3 unspecified.
- Biomarker Types Studied: EEG-based (26), Imaging-based (8), Blood/serum/CSF-based (3), Genetic (1).
- Primary Outcomes: Treatment response (12), network mapping (12), seizure types/features (11).
Primary Biomarker Categories
EEG-Based Biomarkers
| Study | Biomarker Pattern | Detection Method | Clinical Validation Status | Frequency of Use |
|---|---|---|---|---|
| Romero Milà et al., 2025 | Functional connectivity | Cross-correlation EEG | Correlates with LGS evolution, treatment response | Moderate |
| Kobayashi et al., 2009 | Gamma rhythms | Spectral EEG | Pathophysiology of tonic seizures | Moderate |
| Bare et al., 1998 | Atypical absence, SSW | Video EEG | Diagnostic accuracy | High |
| Deering et al., 2024 | SSW | EEG | Early biomarker | High |
Key findings from included studies
- Most frequent patterns: SSW (10 studies), GPFA (7 studies).
- Detection methods: Standard EEG (9 studies), video EEG (2).
- Frequency of use: High in 11 studies, Moderate in 10, Low in 2.
Clinical Applications and Validation
Diagnostic Applications
- EEG-based biomarkers: SSW and GPFA essential for diagnosis with high sensitivity and specificity.
Treatment Monitoring
- Automated EEG analysis reported to allow for more rapid assessment of treatment efficacy.
Prognostic Value
- Longer SSW discharges associated with poorer outcomes.
Summary
- SSW and GPFA are the most commonly reported and validated biomarkers for seizures associated with Lennox-Gastaut syndrome in included studies.