Abstract
Magana-Tellez O, Maganti R, Hupp NJ, Luo X, Rani S, Hampson JP, Ochoa-Urrea M, Tallavajhula SS, Sainju RK, Friedman D, Nei M, Gehlbach BK, Schuele S, Harper RM, Diehl B, Bateman LM, Devinsky O, Richerson GB, Lhatoo SD, Lacuey N. Lancet Neurol. 2025;24(10):840–849. https://www.thelancet.com/journals/laneur/article/PIIS1474-4422(25)00273-X/abstract Background: Sudden unexpected death in epilepsy (SUDEP) is the most common category of epilepsy-related mortality. Centrally mediated respiratory dysfunction has been observed to lead to death in the majority of cases of SUDEP. SUDEP also mainly occurs during nighttime sleep. This study seeks to identify sleep EEG and sleep-related respiratory biomarkers of SUDEP risk. Methods: In this case–control study, we compared demographic, clinical, EEG, and respiratory data from people with epilepsy who later died of SUDEP (the SUDEP group) with data from age and sex-matched living people with epilepsy, classified as high risk of SUDEP (with ≥1 generalised tonic–clonic seizure [GTCS] per year), low risk of SUDEP (no history of GTCS), and non-epilepsy controls. These data were prospectively collected as part of a multicentre National Institutes of Health study. We analysed sleep macroarchitecture and microarchitecture features and measured sleep homeostasis by calculating overnight change in slow wave activity (SWA; 0.5–4.0 Hz) in non-rapid eye movement (NREM) sleep during seizure-free nights using linear regression models. We also analysed sleep respiratory metrics, including inter-breath interval variability. We used receiver operating characteristic analysis to assess the individual discriminative performance of demographic, clinical, sleep EEG, and sleep-related respiratory features to predict the risk of SUDEP. Findings: Between Sept 1, 2011, and Oct 15, 2022, 41 participants who later died of SUDEP and 123 matched controls (41 people living with epilepsy at high risk of SUDEP, 41 people living with epilepsy at low risk of SUDEP, and 41 non-epilepsy controls) were enrolled. The SUDEP group showed an abnormal lack of overnight decline and an increase in the slope of SWA power compared with the other groups (SUDEP group mean 0.005, standardized error of the mean [SEM] 0.003; high-SUDEP risk group −0.005, 0.002; low-SUDEP risk group −0.003, 0.002; non-epilepsy controls −0.007, 0.003; p = 0.017). The overnight increase in the SWA slope was more pronounced in males compared with females (males mean 0.012, SEM 0.001; females 0.001, 0.002; p = 0.005). The variability of the inter-breath interval was significantly higher in the SUDEP (coefficient of variation mean 0.15, SD 0.09; SD mean 0.54 s, SD 0.35 s) and high-SUDEP risk groups (0.11, 0.03; 0.46 s, 0.19 s) compared with low- SUDEP risk group (0.08, 0.03; 0.30 s, 0.14 s) and non-epilepsy controls (0.08, 0.02; 0.31 s, 0.11 s; p < 0.0001). The coefficient of variation of inter-breath interval had the greatest predictive power of SUDEP risk (between-group point estimate difference 0.30, AUC 0.80; 95% CI 0.70–0.90; p < 0.0001). Interpretation: This study identifies impaired sleep homeostasis in the form of altered SWA progression during NREM sleep overnight in people with epilepsy who later died of SUDEP, and an increase in respiratory variability during NREM sleep in people with epilepsy who later died of SUDEP and in people with epilepsy at high risk of SUDEP. Multiday polysomnography studies are needed to validate sleep homeostasis and respiratory variability during sleep as potential biomarkers of SUDEP risk. Further studies are required to explore possible sleep interventions that could mitigate SUDEP risk.
Commentary
Sudden unexpected death in epilepsy (SUDEP) remains an enigma in neurology, claiming lives unpredictably and representing the leading cause of epilepsy-related mortality. SUDEP is defined as “sudden, unexpected, witnessed or unwitnessed, non-traumatic and non-drowning death in patients with epilepsy, with or without evidence for a seizure and excluding documented status epilepticus in which postmortem examination does not reveal a toxicologic or anatomic cause of death.” 1 With an incidence of approximately 1 in 1000 patient-years among adults with epilepsy, rising to 1 in 150 in those with refractory disease, SUDEP underscores the urgent need for risk-stratification and preventive strategies. Traditionally, risk factors have centered on clinical features such as frequent generalized tonic–clonic seizures (GTCS), nocturnal seizures, and poor seizure control. However, mechanistic insights point to a triad of postictal phenomena: profound respiratory depression, cardiac arrhythmias, and central autonomic dysfunction, often culminating during sleep. This nocturnal predominance, accounting for over 70% of cases, suggests that disrupted sleep physiology may be a potential harbinger. 2 Yet, biomarkers that bridge sleep architecture, brain activity, and respiration have been elusive.
The study by Magana-Tellez et al 3 tries to bridge this gap and identifies interictal sleep and respiratory biomarkers using simultaneous prolonged video-EEG and cardiorespiratory monitoring in patients who subsequently died of SUDEP, using case–control methods. The study breaks new ground by leveraging prospectively collected polysomnography (PSG) data from a multicenter cohort to distinguish sleep EEG and respiratory biomarkers between individuals who succumbed to SUDEP from matched controls. By focusing on seizure-free nights, the authors isolate baseline sleep perturbations, sidestepping the confounding effects of acute ictal events. This approach is particularly insightful, as it shifts the lens from peri-ictal chaos to chronic vulnerabilities in sleep homeostasis and breathing stability, which may predispose to fatal decompensation during seizures. Following a meta-analysis of studies relevant to SUDEP biomarkers, the authors identified 158 articles; however, none evaluated sleep EEG or respiratory variability. Most witnessed SUDEP cases reported in the literature occurred after a GTCS, with most individuals found in or near a bed. Having a history of nocturnal GTCS within the past year increased the risk of SUDEP 15-fold. Centrally mediated respiratory dysfunction after GTCS is thought to be the root cause of SUDEP. 4 Evidence suggests that seizures arising during sleep might result in greater respiratory suppression than seizures arising during wakefulness. 5 Therefore, the distinctive characteristics of sleep EEG and sleep-related breathing in people with epilepsy might help predict the risk of SUDEP. The study analyzed 3 sleep-related models. (1) Slow-wave activity (SWA) progression during all non-rapid eye movement (NREM) episodes during the night; (2) rise in SWA in NREM episodes preceded by at least 15 min of awake state, and (3) the exponential decline constant (τ) of SWA in each NREM cycle, by the time spent in it.
At the heart of the EEG findings is an aberration in slow-wave activity (SWA) dynamics during NREM sleep. SWA, encompassing delta frequencies (0.5–4 Hz), serves as a hallmark of sleep homeostasis, the brain's mechanism for restorative sleep. In healthy individuals, SWA peaks early in the night, corresponding to sleep pressure, and declines exponentially as the sleep pressure dissipates, reflecting efficient recovery from wakeful demands on brain activity. Disruptions in this pattern have been linked to various neurological disorders, 6 including epilepsy, where interictal epileptiform discharges can fragment sleep and impair cognitive function. Strikingly, the SUDEP group exhibited a paradoxical increase in SWA slope overnight, contrasting the expected decline seen in high-risk, low-risk epilepsy, and non-epilepsy controls. This suggests a failure in homeostatic regulation, possibly stemming from underlying brainstem or cortical network dysfunction that amplifies sleep instability. The sex-specific accentuation in males aligns with epidemiological data showing higher SUDEP rates in men, potentially tied to hormonal influences on sleep or autonomic control, though the study did not delve into mechanisms. Complementing these EEG insights, the respiratory analysis revealed heightened inter-breath interval variability in SUDEP and high-risk groups, quantified via coefficient of variation and standard deviation. This metric's robust discriminatory power (AUC 0.80) highlights its potential as a biomarker, capturing subtle instabilities in breathing rhythm during NREM sleep. Respiratory variability in this context may reflect impaired central control, echoing observations from animal models where serotonergic brainstem deficits lead to apnea susceptibility in epilepsy. 7 Indeed, central apnea following convulsions has been proposed as a SUDEP biomarker, with postictal hypoxemia exacerbating fatal outcomes. 8 By demonstrating this variability in baseline sleep, the study implies a pre-existing vulnerability that could interact with seizure-induced suppression to trigger terminal events.
Methodologically, the study's strengths lie in its rigorous design: age- and sex-matched controls across risk strata, including non-epilepsy participants, enhancing comparability. The use of linear regression for SWA trends and receiver operating characteristic analysis for predictive utility provides statistical rigor while focusing on NREM sleep, where SUDEP often strikes, adding relevance. The cohort size (41 per group) is commendable for a rare outcome such as SUDEP, drawn from a National Institutes of Health-funded registry, ensuring data quality. The single-night PSG protocol, while practical, may, however, not capture night-to-night variability in sleep parameters, a known issue in epilepsy where sleep fragmentation can fluctuate and therefore remains a caveat. The authors acknowledge this, advocating for multiday studies, but this limitation could inflate type I errors or miss dynamic biomarkers. Potential confounders, such as antiepileptic drugs (many of which depress respiration or alter sleep architecture), comorbidities such as obstructive sleep apnea (OSA), or subtle undiagnosed sleep disorders, are not fully dissected. For instance, OSA is prevalent in epilepsy and heightens SUDEP risk via nocturnal hypoxemia, 9 yet the analysis does not stratify by apnea–hypopnea index. Moreover, the high-risk group's shared respiratory variability with SUDEP cases raises questions about specificity: does this marker truly predict death, or merely GTCS frequency? Longitudinal validation in larger cohorts is essential to clarify causality and refine cutoffs.
Clinically, these findings hold transformative potential; they bridge basic neuroscience, SWA as a proxy for synaptic plasticity and recovery, with bedside risk assessment. For basic researchers, the findings open avenues to probe the molecular underpinnings, such as serotonergic or GABAergic pathways linking epilepsy to respiratory control in models with spontaneous GTCS associated with similar sleep EEG biomarkers. If validated, integrating these biomarkers into routine PSG could enable personalized interventions: continuous positive airway pressure for those with high respiratory variability, or sleep-enhancing therapies to normalize SWA. Wearable devices monitoring EEG and respiration could extend this to home settings, 10 empowering patients and reducing SUDEP's impact in high-risk patients. In summary, Magana-Tellez et al 3 illuminate a path toward demystifying SUDEP by spotlighting sleep as a modifiable vulnerability. While not yet ready for prime time, these biomarkers invite a paradigm shift from reactive seizure management to proactive nocturnal safeguarding, potentially saving lives in this vulnerable population.
