The Fast and the Very Fast: High-Frequency Oscillations in Alzheimer's Disease

Abstract

High-Frequency Oscillations in Epileptic and Non-Epileptic Alzheimer's Disease Patients and the Differential Effect of Levetiracetam on the Oscillations

Shandilya MCV, Addo-Osafo K, Ranasinghe KG, Shamas M, Staba R, Nagarajan SS, Vossel K. Brain Commun. 2025;7(1):fcaf041. https://doi.org/10.1093/braincomms/fcaf041

Alzheimer's disease increases the risk of developing epilepsy together with cognitive decline. Early diagnosis or prediction of parameters associated with epileptic activity can greatly help in managing disease outcomes. Network hyperexcitability is a candidate of interest as a neurophysiological biomarker of Alzheimer's disease. High-frequency oscillations are increasingly recognized as potential biomarkers of hyperexcitability and epileptic activity. However, they have not yet been identified in Alzheimer's disease. In this study, we measured high-frequency oscillations via magnetoencephalography recordings in Alzheimer's disease patients with and without epileptic activity, as part of a Phase 2a randomized, double blind clinical trial of the efficacy of levetiracetam to improve cognitive functions in Alzheimer's disease. To measure the high-frequency oscillations, we used 10-minute magnetoencephalography recordings (275-channel and sampling rate 1200–4000 Hz) during awake resting periods in participants with Alzheimer's disease and healthy controls. Recordings from 14 Alzheimer's disease participants, with six having non-epileptic Alzheimer's disease (median age: 60.8, 2M/4F), eight having sub-clinical epileptic activity (median age: 54.9, 5M/3F) and eight as control (median age: 71, 5M/3F), were analysed using two software scripts: Delphos and a custom-made script, for detecting high-frequency oscillations. Levetiracetam 125 mg twice-a-day or placebo was administered for 4 weeks in between two magnetoencephalography recordings, and 4 weeks of washout before switching levetiracetam/placebo phases for each participant. High-frequency oscillations were categorized into ripples (80 to 250 Hz) and fast ripples (250 to 500 Hz). At baseline, Alzheimer's disease participants, both epileptic and non-epileptic had higher rate of ripples and fast ripples than controls in several left/right hemispheric sensor regions (P < 0.05). Additionally, compared to epileptic, non-epileptic had higher rate of ripples in left-frontal, left-temporal and cerebral fissure regions and higher rate of fast ripples in left-frontal regions (P < 0.05). In epileptic type, levetiracetam decreased ripples in bilateral–frontal, bilateral–occipital regions and cerebral fissure, whereas in non-epileptic type, levetiracetam increased both ripples and fast ripples in right central and left parietal regions, and ripples in the right parietal region (P < 0.05). Additionally, we found hemisphere asymmetry in epileptic type, with right temporal/occipital having more high-frequency oscillations than their counterpart region. Overall, Alzheimer's disease had a high level of high-frequency oscillations, with higher numbers observed in non-epileptic type. Levetiracetam decreased high-frequency oscillations in epileptic but increased high-frequency oscillations in non-epileptic. Thus, high-frequency oscillations can function as a biomarker of hyperexcitability in Alzheimer's disease and may be more pathological when asymmetric and coinciding with presence of epileptic activity. Levetiracetam has the potential for treating hyperactivity in patients with epileptic Alzheimer's disease.

Commentary

Epilepsy occurs with increased incidence in individuals with Alzheimer's disease (AD) ¹ and may shape some aspects of disease progression. When present, epileptiform activity is associated with accelerated cognitive decline in individuals with AD. ² Consequently, addressing epileptiform activity and network hyperexcitability in AD patients has become a compelling therapeutic avenue that holds potential for delaying the appearance and/or progression of cognitive symptoms.

A few decades ago, high-frequency oscillations (HFOs) were identified in patients with temporal lobe epilepsy ³ and became a novel marker of network hyperexcitability. HFOs, brain oscillations over 80 Hz, include two generally recognized categories: ripples (80-250 Hz) and fast ripples (250-500 Hz). Ripples are a feature of normal brain function linked to learning and memory that occur in healthy brains. Ripples also occur in epileptic brains, often in association with epileptiform spikes. ⁴ On the other hand, fast ripples, considered to be of pathological nature, are typically limited to epileptogenic zones. ⁴ In the context of epilepsy, HFOs can be helpful for identifying epileptogenic zones, and their abundance correlates with disease severity ⁵ in both patients and mouse models of epilepsy.

HFOs have previously been detected and studied in mouse models of AD neuropathology, ⁶ which also exhibit spontaneous seizures. Bridging the gap between knowledge generated in animal models and human disease, Shandilya et al now demonstrate that HFOs are present in AD patients as well. ⁷ In a study conducted on magnetoencephalographic (MEG) recordings from patients and healthy control individuals, the authors found an increased rate of ripples and fast ripples in several cortical regions spanning the frontal, central, parietal, temporal and occipital cortices, as well as the cerebral fissure. ⁷ Interestingly, HFOs were found in both epileptic and non-epileptic patients, which supports the tantalizing possibility that network hyperexcitability could be a generalized hallmark of AD, present even when epileptiform activity is not detected. The pervasiveness of fast ripples, which were increased in AD patients compared to control patients across multiple regions of the cortex, is also noteworthy. Considering that fast ripples are typically associated with epileptic tissue, their broad distribution across the cortex of AD patients could be a consequence of AD's widespread and diffuse neuropathology.

The MEG recordings from individuals with AD examined in this study are part of the dataset generated during the Levetiracetam for Alzheimer's Disease-Associated Network Hyperexcitability (LEV-AD) study, a randomized, double-blinded, placebo-controlled phase 2a clinical trial in which patients with AD were treated with the antiseizure medication levetiracetam to assess its effects on cognitive function. ⁸ A critical strength of the LEV-AD trial is that it included both epileptic and non-epileptic AD patients, which enabled the authors to perform a stratified evaluation of the treatment response of the two patient subpopulations. This stratification is especially opportune in the context of AD, which is a heterogeneous disease in many ways. A very small proportion (<5%) of AD cases are caused by autosomal dominant gene mutations, while the majority are sporadic. Risk alleles, environmental factors, exposures and lifestyle have profound effects on AD risk and progression. Individuals with classical AD-related neuropathology develop progressive cognitive decline, but some of them, sometimes referred to as “resilient” individuals, remain cognitively intact despite the presence of histological hallmarks of disease such as amyloid-β plaques and neurofibrillary tangles in their brains. ⁹ The presence or absence of epileptiform activity adds yet another layer of complexity to the disease, with practical implications on treatment outcomes: in the LEV-AD study, some aspects of cognitive function improved in individuals with both AD and epileptiform activity upon treatment with levetiracetam, while individuals without epileptiform activity did not exhibit any improvements. ⁸ This dichotomy has now been found to extend to HFOs. Shandilya et al found that levetiracetam reduced the incidence of HFOs in the ripple frequency range in multiple regions of the cortex only in patients with epileptic AD, whereas patients with non-epileptic AD experienced an increased rate of ripples and fast ripples in some of the analyzed regions. ⁷ While the practical consequences of these divergent outcomes are unclear for now, this phenomenon brings attention to the importance of addressing AD not as a singular entity but as a constellation of disease phenotypes, each perhaps best suited to specific therapeutic interventions. If an association between the rate of HFOs and treatment outcomes is confirmed, measuring the rate of HFOs before and after initiating treatment could contribute to segregating responders from non-responders that might benefit from a different medication or therapy.

In light of the growing prominence of HFOs in epilepsy research and clinical practice, further investigation of HFOs in the context of AD and AD-related epilepsy is warranted. At least on paper, retrospectively studying HFOs in recordings from AD patients would be feasible, provided that the recordings were carried out with appropriate sampling rates and low-pass filters. And, given that HFOs can be detected in noninvasive recordings, prospective studies would potentially have few requirements beyond the usual ones in electroencephalographic (EEG) or MEG studies.

HFOs are present in awake individuals and occur somewhat frequently (in this study, Shandilya et al reported a rate of several ripples and a few fast ripples per hour ⁷ ), which could facilitate their evaluation in short, routine recordings. Nonetheless, epileptiform activity is known to be heavily influenced by the sleep–wake cycle. In AD patients, epileptiform activity is most abundant during nonrapid eye movement (NREM) sleep and occurs less frequently during wakefulness and rapid eye movement (REM) sleep. ¹⁰ Similarly, HFOs are known to show modulation associated with the sleep–wake states in epilepsy patients. ⁵ Therefore, studying HFOs during sleep could be especially informative. Evidence in mouse models of AD neuropathology points to a preferential occurrence of HFOs during NREM sleep, ⁶ which further suggests that HFOs could be temporally segregated in AD patients as well. Of note, Shandilya et al identified wakefulness and sleep in the analyzed recordings according to eye blinks and the presence of low-frequency waves in the EEG of patients, which was recorded concurrently with MEG, and observed that a subset of the recordings contained phase N1 and N2 sleep. Although the authors did not report different incidences of HFOs in wakefulness and light sleep, a future study exploring a larger cohort in which individuals attain deep NREM and REM sleep could shed light on this matter. A comprehensive investigation may reveal whether the differences observed by the authors in individuals with AD and healthy controls, or in epileptic and non-epileptic AD patients, are preserved in discrete sleep–wake states.