# Neurophysiological and neuroinflammatory adaptations to seizure activity in aging

Alicia Janvier, Noemie Cresto, Cristina Nistreanu, Athenais Genin, Tristan Moujellil-Legagneur, Magalie Mathias, Mathieu Vitalis, Paolo Fabene, Edoardo Parrella, Charleine Zussy, et al.

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## To cite this version:

Alicia Janvier, Noemie Cresto, Cristina Nistreanu, Athenais Genin, Tristan Moujellil-Legagneur, et al.. Neurophysiological and neuroinflammatory adaptations to seizure activity in aging. Neurobiology of Disease, 2025, 217, pp.107177. 10.1016/j.nbd.2025.107177. hal-05361610

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# Neurophysiological and neuroinflammatory adaptations to seizure activity in aging

Alicia Janvier<sup>a,1</sup>, Noemie Cresto<sup>a</sup>, Cristina Nistreanu<sup>a,b</sup>, Athenais Genin<sup>a</sup>, Tristan Moujellil-Legagneur<sup>a</sup>, Magalie Mathias<sup>a</sup>, Mathieu Vitalis<sup>a,2</sup>, Paolo Fabene<sup>b,c</sup>, Edoardo Parrella<sup>d,b</sup>, Charleine Zussy<sup>a,3</sup>, Etienne Audinat<sup>a,4</sup>, Laurent Givalois<sup>a,e,5</sup>, Nicola Marchi<sup>a,* ,6</sup>

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ARTICLE INFO

Keywords:
Late-onset
Acute seizures
Inflammating
Astrocytes
Aging

A B S T R A C T

The pathophysiological impact of late-onset seizures on the brain is not well understood. Here, we investigated whether an initial pattern of generalized seizures (GS) with an electrographically defined ictal-interictal con- tinuum, occurring at middle age (12-13 months old) in a mouse model, induces long-term neurophysiological and cellular changes, compared to young-adults (2-3 months old).

In young-adults, the initial patterns of GS were associated with sporadic spike and wave discharges (SWDs) in the long term. In contrast, in late middle-age mice, GS were sufficient to promote spontaneous case-specific seizures over time, together with SWDs. This group presented increased spike activity and alterations in delta-theta wave patterns during both wakefulness and sleep, compared to age-matched sham controls. These long-term electrophysiological changes were accompanied by modifications in open field behavior, but not by his- tological evidence of hippocampal sclerosis or cortical atrophy. Because seizures can induce neuroinflammation, we investigated biomarkers of glial reactivity. The late middle-age group exhibited more pronounced increases over time in hippocampal and cortical GFAP<sup>+</sup> density and IBA1<sup>+</sup> cell number following GS. Finally, we inves- tigate the long-term transcriptomic footprints that may develop in response to seizures and age. RNA sequencing, adjusted for multiple comparisons, revealed elevated immune-related transcripts (Defb1, Pglyrp1, Bdkrb2) and cell cycle/growth regulators (Cdkn1a, PAX7) in late middle-age mice two months after GS compared to young- adults.

The initial GS pattern in middle-age elicits a maladaptive response in the long-term, unlike in young-adults, characterized by spontaneous and abnormal electrographic activity. This outcome was accompanied by inflamming-related cellular and transcriptomic markers, indicating heightened vulnerability of the aging brain to seizures.

<footnote><sup>a</sup> Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France</footnote>

<footnote><sup>b</sup> Section of Innovation Biomedicine, Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy</footnote>

<footnote><sup>c</sup> Section of Anatomy and Histology, Department of Neurosciences, Biomedicine and Movement Sciences, Faculty of Medicine, University of Verona, Verona, Italy</footnote>

<footnote><sup>d</sup> Departmental Faculty of Medicine, Saint Camillus International University of Health Sciences, Rome, Italy</footnote>

<footnote><sup>e</sup> Laval University, Faculty of Medicine, Department of Psychiatry and Neurosciences, CR-CHUQ, Québec City, Canada</footnote>

<footnote>* Corresponding author at: Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France.</footnote>

<footnote>E-mail address: nicola.marchi@igf.cnrs.fr (N. Marchi).</footnote>

<footnote n="1">¹ https://orcid.org/0009-0008-2246-4291</footnote>

<footnote n="2">² https://orcid.org/0009-0001-3450-9003</footnote>

<footnote n="3">³ https://orcid.org/0000-0003-4945-2211</footnote>

<footnote n="4">⁴ https://orcid.org/0000-0002-6389-422X</footnote>

<footnote n="5">⁵ https://orcid.org/0000-0002-6698-5346</footnote>

<footnote n="6">⁶ https://orcid.org/0000-0001-9124-0226</footnote>
# 1. Introduction

Clinical evidence indicates a rise in late-onset seizures, with underlying causes ranging from cerebrovascular accidents to head trauma to unknown origins (Sung et al., 2024; Keret et al., 2020; Ballerini et al., 2024). As age increases, seizures are associated with adverse neurological outcomes (Keret et al., 2020; Hickman et al., 2023; van Vliet and Marchi, 2022; Sarkis et al., 2025). They are linked to cognitive decline in adults with normal cognition as well as those with mild cognitive impairment, independent of other dementia risk factors (Zawar et al., 2024). Furthermore, seizures might serve as a biomarker of underlying neurodegeneration (Fang et al., 2023). This complex clinical picture intersects with neurological frailty, supporting the working hypothesis that, with increasing age, the brain could ill-react to acute insults (Hashmi et al., 2024; Lehner et al., 2024; Joutsa et al., 2017).

Age and seizures are intertwined and heterogeneous (Beghi et al., 2023), complicating the assessment of each factor's impact on brain health and its comparison with adequate young adult patients and age-matched controls (Cresto et al., 2024a). Experimental models could be useful in this regard, although this area of research remains relatively untapped. Pre-clinical studies reported that aging mice, compared to young adults, are acutely more susceptible to pro-convulsants with heightened mortality due to status epilepticus (McCord et al., 2008; Hattiangady et al., 2011). However, this research does not inform whether a set pattern of seizures elicited at different ages leads to distinctive neurological trajectories; it does not provide direct cross-comparisons to isolate age as a variable while keeping a similar initial seizure insult.

Here, we examined whether a pattern of acute seizures elicited in middle-age (12-13 months) mice is associated with long-term neurophysiological, cellular, and transcriptomic changes compared to young-adult (2-3 months) mice under similar conditions. The follow-up period in middle-age mice (up to 14-15 months old) can be considered equivalent to about 50 years of age in humans (Dutta and Sengupta, 2016), with potential implications for clinical late-onset seizures (Morano et al., 2022). Based on existing literature (McCord et al., 2008), we used an age-adjusted intraperitoneal (i.p.) dose of kainic acid (KA) in middle-age mice and, in young-adults, the initial dose necessitated scaling re-injections, as suggested in (Tse et al., 2014). We studied mice showing generalized seizures (GS) at induction, with an ictal-interictal continuum, where the duration and severity of seizures did not reach status epilepticus (SE). From this initial GS pattern, in the selected population, we tracked long-term trajectories by integrating EEG monitoring, behavioral testing, and cellular-to-transcriptomic analyses to investigate cortical and hippocampal changes that emerge as a function of the age of seizure occurrence and compared them to age-matched shams. Our findings highlight that an initial pattern of GS can promote long-term unfavorable neurophysiological changes particularly when it occurs at middle-age stages, accompanied by cellular and transcriptomic adaptations, suggesting an inflammaging framework (Finger et al., 2022) that may underpin neurological risks.

# 2. Materials and methods

All procedures were carried out in accordance with the Directive of the Council of the European Communities, overseen by local animal welfare units, and approved by the French Ministry of Research (APAFIS #33442-2,021,100,109,237,625 v7). Seven weeks and 4-5 months C57BL/6 J male mice were obtained from Charles River Laboratories (Lyon, France), maintained to reach the targeted age ranges (2-3 and 12-13 months) for study start, and fed a standard chow diet. The mice were housed under a 12-h light/12-h dark cycle, with free access to food and water, and in groups of 3-4, with adequate enrichment and daily monitoring of their well-being.

## 2.1. Experimental groups

Fig. 1 illustrates the experimental flowchart. We started with: i) young-adult mice, *n* = 34. We specifically studied *n* = 23 young-adult mice experiencing generalized seizures (GS; indicated in blue in Fig. 1). Age-matched control groups consisted of *n* = 19 young-adult mice. For the studied population, we used *n* = 5 young-adult mice to electrographically (Video-EEG) validate Racine behaviors (from before to after KA injections; Fig. 2). Age-matched sham (*n* = 4) were included. We performed histology at 48 h post-GS (n = 4 / group; Figs. 6-9). For long-term characterization and to apply the 3Rs principle, we analyzed multiple endpoints on the same animal (reduction). All young-adult mice in the long-term study underwent behavioral testing (Fig. 5), *n* = 11 sham and *n* = 12 post-seizure. Of these, a randomly selected subset was also used for long-term Video-EEG monitoring (Figs. 3-4): *n* = 6 young-adult sham and *n* = 7 young-adult post-seizure. Four mice per group were also randomly selected for long-term immunofluorescence (Figs. 6-9) and RNAseq (Table 1), using both brain hemispheres (one fixed, one snap-frozen). ii) *n* = 38 middle-age mice. We specifically studied *n* = 25 late middle-age mice experiencing GS (indicated in blue in Fig. 1). Age-matched control groups consisted of *n* = 25. For the studied population, to electrographically validate Racine behaviors (from before to after KA injections; Fig. 2), we used *n* = 4 mice. Age-matched sham (*n* = 4) were included. We performed histology at 48 h post-GS (n = 4 / group; Figs. 6-9). All middle-age mice in the long-term study underwent behavioral testing (Fig. 5), *n* = 17 sham and *n* = 17 post-seizure. Of these, a randomly selected subset was also used for long-term EEG monitoring (Figs. 3-4): *n* = 6 sham and *n* = 7 post-seizure. Four mice per group were also randomly selected for long-term immunofluorescence (Figs. 6-9) and RNAseq (Table 1), using both brain hemispheres (one fixed, one snap-frozen).

## 2.2. Induction and neurophysiological seizure characterization

Based on previous literature (McCord et al., 2008) indicating increased susceptibility to pro-convulsants with aging, 15 mg/kg of i.p. KA (Merck; #K0250 in PBS, Sigma-Aldrich; cat n. D8537) was adequate to elicit seizures in 12-13 months old C57BL/6 J male mice. Young-adult (2-3 months) mice necessitated re-injections (5 mg/kg; 20-min intervals; Supplementary Fig. 1 A for KA scaling dosages; see (Tse et al., 2014)) to reach GS patterns comparable to the late middle-age mice. We used Racine stage 0: normal behavior; 1: orofacial movements, immobility; 2: head nodding or myoclonus; 3: forelimb myoclonus; 4: bilateral forelimb myoclonus with rearing; 5: tonic-clonic with rearing and falling (Racine, 1972). We report (Fig. 1) that 65.8 % (*n* = 25) and 67.6 % (*n* = 23) of late middle-age and young-adult mice displayed stages 3 and 4 (see Supplementary Videos 1 and 2), with 7/25 late middle-age and 9/23 young-adult mice presenting isolated episodes of tonic-clonic bilateral seizures with rearing and falling (stage 5; example in Fig. 2C and Supplementary Video 3; see Supplementary Fig. 1B for individual mouse staging). The latter seizures did not reach the temporal or severity criteria for SE (presenting with duration of at least several minutes (Loscher, 2024); frequent repetition of stage 5 (Sharma et al., 2018); see excluded mice section below), and all behavioral changes spontaneously attenuated within approximately 3 h from onset. An earlier report indicates that young mice display tonic extension of the hindlimbs more frequently than old mice (Van Erum et al., 2019). We did not observe differences in this specific behavior in our settings.

An EEG exploration performed on a subset of mice, from before to after KA injections, indicated the cortical-hippocampal electrographic generalized seizure (GS) patterns. Fig. 2A-A1 and B-B1 provide examples of first and subsequent seizures during the induction phase, along with EEG details for pre-ictal and post-ictal patterns (Fig. 2 A2-A3 and B2-B3) and the observed Racine staging. Cortical activity was more pronounced during the first seizure episode, with a progressive engagement of hippocampal structures in the following seizures. We
<figure><img src="image_5.png" /><figcaption>**Fig. 1.** Experimental flowchart: seizure induction and long-term analyses. Graphical representation of the protocol used. Age-adjusted KA scaling injections elicit generalized seizures (indicated in blue, GS; included; see examples in Fig. 2A-B3 and Supplementary Videos 1-2), or status epilepticus (SE, repetitive and prolonged stage 5; excluded; see Fig. 2 C2–C3 and Supplementary Video 6), or no changes (excluded). From the initial GS, long-term trajectories (up to 2 months) were examined. See Supplementary Fig. 1B for mouse-specific Racine stages. See Methods for seizure quantifications. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

report a subsequent emergence of an electrographic ictal-interictal continuum (IIC (Zafar et al., 2020); from 45.26 +/- 10.28 and 38.84 +/- 7.07 min; *p* = 0.302; from the last KA injection for late middle-age and young-adult, respectively), consisting of repetitive high-amplitude spikes and spike-wave discharges, in the cortex and hippocampus (Fig. 2D-D1 and respective Supplementary Videos 4-5). Before the emergence of the IIC patterns, the mean duration for GS was 31.42 ± 3.69 and 56.03 ± 20.24 s (*p* = 0.05), and the seizure number was 5 ± 0.82 and 5 ± 2 (*p* > 0.9) for late middle-age and young-adult, respectively. Then, the IIC was associated with the occurrence of short-duration seizures (EEG examples in Fig. 2D-D1 with Racine stages). Electrographic seizures spontaneously attenuated within approximately 3 h of onset, while sustained spiking persisted overnight (number/h: 121.65 ± 39.97 and 229.75 ± 136.39 hippocampal and cortical spikes, respectively, in late middle-age; number/h: 110.65 ± 65.62 and 137.92 ± 46 hippocampal and cortical spikes, respectively, in young-adults). In the following days, biomarkers of well-being were confirmed (including nesting, weight, and motility), allowing for long-term analysis.

## 2.3. Exclusion criteria: SE or no changes

With this protocol, we report that 31.6 % (n = 12) and 26.5 % (n = 9) of the injected mice (late middle-age and young-adult, respectively; see Supplementary Fig. 1B) displayed a progression to repetitive and long-lasting convulsive behavioral seizures with prolonged and generalized EEG activity, indicative of SE (repetitive stage 5; see examples in Fig. 2 C2–C3, Supplementary Fig. 2, and Supplementary Video 6 for Video-EEG). The latter mice were excluded from this study due to unstable well-being in the aging group, which was not suitable for robust long-term neurophysiological EEG tracking. Finally, 2.6 % (n = 1) and 5.9 % (n = 2) of the injected mice (late middle-age and young-adult, respectively) showed no changes or transient Racine stages ≤2, and they were also excluded from the study (Supplementary Fig. 1B). Generally, our experimental results aligns with a previous study in another model of scaling KA i.p. injections in mice (Tse et al., 2014).

## 2.4. EEG surgery and analyses

For EEG microelectrode placement (Boux et al., 2021; Canet et al., 2022), mice were subcutaneously injected with buprenorphine (0.05 mg/kg) 30 min before the procedure, followed by isoflurane anesthesia (induced with 5 % isoflurane for 5 min and maintained at 2 % in a mixture of 70 % air and 30 % O₂). Local anesthesia was administered via

a subcutaneous injection of lidocaine (4 mg/kg). Animals were maintained on a heating pad, and the depth of anesthesia was continuously monitored. In a sterile surgical environment, after making an incision in the subcutaneous tissue over the skull and clearing the periosteum, a bipolar electrode consisting of two isolated and twisted tungsten wires was inserted into the hippocampus (anteroposterior = -2 mm, lateral = +1.5 mm, depth = -2 mm, according to Paxinos and Franklin). For cortical recordings, two micro-screws (Pinnacle Technology Inc., #8209) were anchored in the fronto-parietal region of the skull. All wires were connected to a prefabricated micro-connector (6-Pin Surface Mount Connector for Mouse, Pinnacle Technology Inc., #8235-SM), secured and insulated using dental acrylic cement (Palladur). The incision was closed with two 5/0 non-absorbable silk sutures (Ethicon), one placed anterior and the other posterior to the connector. Post-surgery mice were closely monitored for well-being (weight loss, mobility, food/water intake, presence of infections, etc.). Enrichment, such as cotton nests and nest boxes, was always provided. Video-EEG was performed using Sirenia acquisition software (Pinnacle Technology Inc., Lawrence, KS, USA) with an analog low-pass filter (25 Hz). Recordings were continuously performed before, during, and post-KA injection into the following night (up to 36 h) or long-term twice a week (both days and nights) from two weeks to two months post-GS. This schedule allowed for maximizing animal welfare over time, especially considering the use of aging mice. Each recording session was performed at a consistent period (between 9 a.m. and 5 p.m. and 10:30 p.m. and 5:30 a.m.). Before each recording, the mice were placed in circular Plexiglas boxes (Rohm, Philadelphia, PA, USA) for habituation with food, water, and enrichment. For EEG examinations and quantifications, we proceeded as follows: first, we conducted a blind review of EEG alongside Video. We visually identified and manually excluded major artifacts, such as signal instability due to hardware issues, head mount scratching, and proximity to a water bottle that causes interference, among others. We then applied a seizure detection routine using Neuroscore (Canet et al., 2022), skipping the regions visually identified as gross artifacts. Subsequently, we tested whether Neuroscore's seizure selection (graphically identified on the EEG) agrees with manually and qualitatively identified seizure patterns (establishing seizure start, e.g., pre-ictal spikes; end, e.g., EEG flattening), systematically cross-validated using the Racine behaviors observed in the Video. After this double validation, we extracted the values of seizure duration specific to cortical-hippocampal seizures, corresponding to bilateral forelimb clonus and rearing. This process was repeated twice by two independent operators in cases of difficult-to-read EEG traces or when incongruences
<figure><img src="image_6.png" /><figcaption>**Fig. 2.** Seizure induction: EEG traces and associated Racine stages. A-A3) Examples of hippocampal and cortical seizures (generalized, GS; first and subsequent) emerging in the young-adult and B-B3) late middle-age groups, along with details indicated by numbers (1) and (2) for pre-ictal and post-ictal patterns. See Methods for seizure quantifications. C-C1) Example of a short-lasting stage 5, with EEG traces, as observed in a subset of mice, and included in the study (*asterisk* indicates trace detail; see Supplementary Video 3 and Methods). C2-C3) EEG example of repetitive stage 5 with continuous electrographic SE, excluded from the study (double asterisks indicate trace detail; see Supplementary Fig. 2 and Supplementary Video 6D-D1) Example of ictal-interictal continuum (ICC; see Supplementary Videos 4-5) detected in the cortex and hippocampus, emerging shortly after GS.</figcaption></figure>
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Racine stages corresponding to seizures

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Spontaneous seizures late middle-age post-GS (long term)

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**Fig. 3.** Initial GS in late middle-age promote mouse-specific spontaneous seizures and SWDs in the long-term. **A)** Long-term (2-months) EEG monitoring, starting 14 days post-GS induction, was performed on four groups, capturing seizures specifically in late middle-age post-GS mice over time (light purple). Racine scores relative to the captured spontaneous seizures are provided. **A1)** Total number of hippocampal-cortical spontaneous seizures that occurred long-term during the entire monitoring period, color-coded to each mouse, along with the initial Racine stage at induction. **A2)** Description of individual seizure duration (seconds), color-coded to each mouse. **A3)** SWDs number color-coded to each mouse. **B—C)** EEG examples of spontaneous seizure activity (color-coded to A1-A2) detected in the long term in the late middle-age group (see Supplementary Videos 7-8). **D)** Example of SWDs captured in a late middle-age post-GS. **E)** SWD recorded in a late middle-age sham. In A-A3: young-adult sham, *n* = 6; young-adult post-GS, *n* = 7; late middle-age sham, *n* = 6; late middle-age post-GS, *n* = 7. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

with Video analyses arise. Spike and wave discharges (SWDs) (Letts et al., 2014) were visually identified based on specific behavior (Racine stage 1, characterized by an arrest of locomotor activity, which resumed as the discharge ended) and electrographic characteristics, such as morphology and high amplitude activity (3-5 Hz), lasting approximately 5-10 s. For spike activity, we combined visual and Neuroscore detections (excluding seizures and SWDs), with the latter set at 3 times the baseline. The automatic detection was then visually re-inspected (Video) to remove artifacts associated with movements, proximity to the water bottle holder, scratching in the vicinity of the implant, etc. The spike number/min was calculated for the long-term EEG monitoring, arbitrarily splitting into 4 periods of approximately the same duration, with data available depending on the technical success of continuous recordings (Fig. 4A-C). Spectrogram analyses (fast Fourier transform, FTT) were used to quantify frequency (Hz) relative abundances. EEG extracts of approximately one minute (a total of 15 min for each mouse) were selected based on the absence of seizure or spike activities on EEG during the period 50-60 days post-GS, differentiating between wakefulness/exploration and sleep/immobility, and avoiding artifacts (Video). Frequency ranges were selected based on the EEG sampling rate and the Nyquist theorem, with a focus on the 0.5 to 20 Hz band for analysis. Within this range, we quantified the relative abundance of delta, theta, and alpha waves. The periodogram was calculated using Neuroscore, and the relative abundance of each wave was plotted.

## 2.5. Behavioral tests

These tests are pertinent to models of neurodegenerative disorders (Webster et al., 2014). All behavioral experiments were conducted between 8:00 a.m. and 4:00 p.m. in a room with light-colored walls and controlled lighting (Cresto et al., 2024b; Sakkaki et al., 2023). Open Field (OF; 50 cm × 45 cm) and Novel Object Recognition (NOR) were determined with a video tracking system (EthoVision XT, Noldus, Wageningen, Netherlands). Each mouse was placed at the periphery of the OF and allowed to explore the arena freely for 10 min with the experimenter out of view. The distance traveled and time spent in the center region (an anxiety index) were tracked by Video. The following day, mice underwent the NOR test. During a 10-min acquisition trial, they were placed in the same arena with two identical familiar objects (F), and the time spent exploring each object (sniffing) was automatically recorded. A 10-min retention trial was conducted 24 h later, where one F object was replaced with a new one (N), and the exploration times for both objects (tF and tN) were recorded. The recognition ratio was defined as tN / (tF + tN). To assess anxiety-like behaviors, we used an O-maze test. Mice were placed in a circular corridor (“O” shape) with two closed and two open sections. Mice were allowed to explore for 5 min, and the time spent in each section was recorded automatically with EthoVision XT. After each session, the arena was cleaned with 70 % ethanol.

## 2.6. Tissue preparation

After inducing deep anesthesia, mice underwent transcardial perfusion with 10 mL of cold PBS. The brains were then dissected. The right hemisphere was separated to isolate the hippocampus and cortex, rapidly frozen in liquid nitrogen, and stored at -80 °C. The left hemisphere was fixed overnight in 4 % paraformaldehyde (PFA, Sigma,

P6148) at 4 °C (24 h). Subsequently, the tissues were cryoprotected by submersion in PBS containing increasing sucrose concentrations (Sigma, S7903), starting with 15 % and then 30 %. The brains were frozen in isopentane at -50 °C (Merck, No. 320404) and stored at -80 °C.

## 2.7. Immunofluorescence

Brains were cut into 20 µm thick serial coronal sections using a cryostat (Microm, NX70DV) and stored free-floating in cryoprotection buffer (30 % water, ethylene glycol, glycerol, and 10 % Tris buffer 1 M) at -20 °C until use (Garcia et al., 2023). For each animal (4/group; Figs. 6-9), three brain sections were used. After three washes with PBS, the sections were permeabilized and blocked for 1 h in a blocking solution consisting of 0.25 % Triton and 20 % horse serum in PBS. The sections were incubated overnight at 4 °C with the primary antibodies: glial fibrillary acidic protein (GFAP, chicken, 1:500, Abcam, ab4674) for astrocyte labeling and ionized calcium-bound adaptor molecule 1 (IBA-1, rabbit, 1:1000, Wako 019-19,741) for microglia labeling. The next day, the sections were washed three times and incubated with the anti-chicken (Alexa Fluor 488) and anti-rabbit (Cyanine3) secondary antibodies, diluted 1:1000, for 2 h in a blocking solution at room temperature. Following three washes with PBS, the sections were mounted onto Polysine slides with a Mounting Medium containing DAPI (Abcam, ab104139). Z-stack images (10 µm total, from 17 serial acquisitions at 0.60 µm each) were acquired. An automated imaging system (20× image montage using AxioScan microscopy, Zeiss, Montpellier Resources Imagerie) was used to obtain regional maps. Four regions of interest (ROI) were selected (hippocampal CA1, CA3, DG; somatosensory cortex) and analyzed. Image analysis was carried out blind. ImageJ was used to quantify the width of pyramidal cell layers in CA3 and granule cells in the DG, and the cortical thickness from layer I to VI (DAPI-positive cells; Fig. 6; *n* = 4 mice / group; 3 sections for each mouse and 3 measurements for each slice in CA3 and DG). For astrocytes, using ImageJ, after image 8-bit conversion, a threshold (>45, ImageJ arbitrary units) was applied to all images to distinguish the specific fluorescence signal from background noise. This step defined a minimum intensity value above which pixels were considered representative of the biological signal of interest. For each image, the acquired GFAP-positive signal was then mathematically divided by the ROI area analyzed, yielding a value we named optical density. In the graphs (Fig. 7), results are presented as optical density normalized to the mean value of the young-adult sham group, which was assigned a reference value of 100 %. The number of microglial cells was manually quantified for each constant ROI by counting colocalization of IBA1 and DAPI with the aid of a cell counter tool in ImageJ. In the graphs (Fig. 9), results are presented as microglial cell counts for the ROI normalized to the mean value of the young-adult sham group, which was assigned a reference value of 100 %.

## 2.8. RNA extraction and transcriptomic analyses

Hippocampi were lysed within the Lysing Matrix D tube into the Fast-Prep sample preparation system (MP Biomedicals, Santa Ana, USA 6913500). Total RNA was extracted and purified using the RNeasy Plus Mini Kit (Qiagen #74136). The RNA concentration of each sample was measured with a Nanodrop 2000c spectrophotometer (Thermo Fisher Scientific, Waltham, USA). RNA quality was assessed using a
A

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C

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Awake

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F

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Sleep

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F1

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**Fig. 4.** Initial GS in late middle-age is associated with the long-term emergence of abnormal spike activity and spectrogram adaptations. **A)** Quantification of spike activity captured from intra-hippocampal electrodes. In the long term, late middle-age mice post-GS exhibit increased spike activity compared to young adults and age-matched sham mice. Data refer to the aggregation of recordings separated into four periods (days) counted from the initial GS (specific groups excluded due to technically non-exploitable EEG traces). Each point indicates the number of spikes from one EEG recording. **B–C)** Examples of intra-hippocampal EEG recordings representative of the spike activities across groups. **D–D3)** Comparisons of the spectrograms (no spike activity) in awake/exploratory phases and sleep (E-E3), obtained from cumulating datasets in the long-term. **F–F1)** Examples of analyzed traces. Over time, late middle-age post-GS mice showed increased theta waves during the awake/exploratory phase (D1 and D3). Late middle-age post-GS and sham mice showed increased delta waves during sleep (E2-E3). Statistical analyses: **A)** Multiple Mann-Whitney test follow by Holm-Sídák method were performed: 14-25: Young-adult Sham vs. Young-adult post-GS: $U_{1,52} = 309$ (ns); late middle-age Sham vs. late middle-age post-GS $U_{1,53} = 164$ (*p* < 0.01); 37-51: Young-adult Sham vs. Young post-GS: $U_{1,61} = 443$ (ns); late middle-age Sham vs. late middle-age post-GS $U_{1,49} = 172.5$ (*p* < 0.05); 26-36: A Kruskal-Wallis test followed by Dunn's multiple comparisons test were performed: Young-adult Sham vs. Young post-GS (*p* = 0.1524); Young-adult Sham vs. late middle-age Sham (*p* = 0.0308); 52-61: A Mann-Whitney were performed: Young post-GS vs. late middle-age post-GS (*p* < 0.01). **D–D3 and E-E3)** Two-way ANOVA followed by Tukey's test. For all data: young-adult sham, *n* = 6; young-adult post-GS, *n* = 7; late middle-age sham, *n* = 6; late middle-age post-GS, *n* = 7. (*p* < 0.05; **p* < 0.01; ***p* < 0.001; ****p* < 0.0001).

bioanalyzer instrument 2100 (Agilent) (Garcia et al., 2023). For each experimental condition, *n* = 4 samples were generated and analyzed. Total RNA was sequenced using a NovaSeq 6000 (Illumina) at the GenomIX platform at the Institute for Functional Genomics. Briefly, mRNA library preparation was carried out using the Illumina Stranded mRNA Prep Ligation Kit, following the manufacturer's instructions, yielding between 50 and 80 million reads per sample. The libraries were validated by assessing DNA concentration and fragment size using a Fragment Analyzer with the Standard Sensitivity NGS Kit and by qPCR using a Roche LightCycler 480. Clustering and sequencing were conducted on an Illumina NovaSeq 6000 system using the Sequence-By-Synthesis technology with NovaSeq Reagent Kits. Image analysis, including cluster position identification, signal intensity measurement, and noise evaluation, was performed with Illumina's NovaSeq Control Software. Base calling was conducted using the Real-Time Analysis (RTA) software. Reads were aligned to the reference genome using HISAT2 with spliced alignment and pseudogene avoidance options. HISAT2 is a fast and memory-efficient splice-aware aligner used to map RNA-seq reads to a reference genome. It employs a hierarchical indexing strategy based on the Burrows-Wheeler transform and FM index, enabling accurate alignment of reads across exon-exon junctions. HISAT2 is particularly well-suited for transcriptome data, supporting spliced alignment and detection of alternative splicing events.

## 2.9. Statistics

Analyses were conducted using GraphPad Prism 10.2.2 (GraphPad Software, San Diego, USA). Data are presented as the mean ± standard deviation (SD). The normality of the data was assessed with the Shapiro-Wilk test. Statistical outputs and specific tests are specified in each figure legend. Generally, we used a two-way ANOVA when data were normally distributed, and the Kruskal-Wallis or Mann-Whitney test was used otherwise. A one-sample *t*-test was used for normally distributed data. A correlation matrix was computed to cross-correlate behavioral and V-EEG datasets. R packages were used to identify differentially expressed genes: the EdgeR model counts data using a negative binomial distribution; testing is based on a generalized linear model; the DESeq2 model counts data using a negative binomial distribution; testing is also based on a generalized linear model.

# 3. Results

## 3.1. Long-term neurophysiological outcomes depend on the age of seizure onset

Within the experimental framework detailed in the Methods Section (Figs. 1-2, Supplementary Figs. 1-2, and Supplementary Videos 1-6), we investigated whether, depending on the age of onset, the initial pattern of GS promotes specific long-term neurophysiological alterations. In young-adult mice, the initial GS pattern was associated only with sporadic SWDs over the long-term (Fig. 3A3) (Rusina et al., 2021) (Levesque et al., 2016). In contrast, in the middle-age group, it was associated with

the long-term emergence of mouse-specific hippocampal-cortical seizures, together with SWDs. The temporal seizure distribution and duration, and SWD number are quantified in Fig. 3A-A3 along with color-coded EEG examples in Fig. 3B-C (including Racine scores; see Supplementary Videos 7-8). With the EEG schedule utilized, we captured seizures in the long-term in 3 out of 7 middle-aged mice. Seizures occurred during day and night (*n* = 7 late middle-age mice; total number of days with EEG recordings = 50, detected: 6 seizures; total number of nights with EEG recordings = 47, detected: 11 seizures). One other middle-age mouse displayed 8 SWDs, the highest incidence among all mice. During seizure induction, young-adult and middle-aged mice exhibited similar Racine behaviors (stages 3-5; Fig. 3A1) and the long-term pathological patterns were detected only in late middle-age mice. The remaining mice displayed varying SWDs (Fig. 3A3), including late middle-aged shams (examples shown in Fig. 3D-E).

We also report increased hippocampal spike activity long-term in the late middle-age group post-GS, cumulatively quantified at intervals of approximately 10 days of aggregated EEG monitoring (Fig. 4A), although with missing datasets due to technical setbacks. From a qualitative standpoint, we show hippocampal sharp waves with higher amplitude and spike and wave complexes in this group (Fig. 4C) as compared to young-adults or shams (Fig. 4B). Next, we computed spectrogram analyses on EEG portions obtained over the long term (see Methods) from all the groups (Fig. 4D-D3, E-E3; output examples Fig. 4F-F1). We found an increase in theta waves (7-8 Hz) in awake late middle-age mice post-GS compared to late middle-age sham and to young-adult post-GS (Fig. 4D1-D3). During sleep, middle-age post-GS mice displayed changes in the abundance of the delta frequency range compared to young-adult post-GS (3.5-4 Hz; Fig. 4 E3). Differences also existed when comparing the sham groups (Fig. 4 E2). We executed a correlation matrix using the neurophysiological datasets (Fig. 5-J). We report a significant positive correlation between the number of the initial GS and long-term (2-months) SWDs and seizures, specifically in late middle-age mice.

Specific behavioral tests were conducted at the end of the EEG monitoring period. Locomotor activity was increased in the post-GS groups, irrespective of age, compared to age-matched sham, with sham late middle-age mice displaying a trend toward reduced movement (Fig. 5A-B). Passages and the time spent in the open field center area, normalized by distance, remained unchanged in young-adults and displayed a trend or significant decrease for late middle-age mice long-term post-GS (Fig. 5C-D). The O-Maze test did not indicate changes in the duration of visits to the open segment (Fig. 5E-F). The novel object recognition test revealed data dispersion, which was more pronounced in late middle-age mice, with no significant differences observed between groups. However, when each group was tested individually against a chance-level preference ratio of 50 %, the late middle-age post-GS group exhibited a discrimination deficit (Fig. 5H). The correlation matrix analyses mouse-specific EEG and behavioral post-GS datasets (Fig. 5I-J). We report a significant and inverse correlation between passage in the center of the open field arena and behavioral seizures during the acute phase, long-term seizure duration, and spike number in
<caption>**Table 1**</caption>

RNA sequencing was performed in the hippocampus two months post-GS, comparing late middle-age and young-adult groups.

<table><thead><tr><th>Long-term (2 months) post-GS (late middle-age vs. young-adult)</th><th>log2 Fold Change</th><th>adjusted p-value</th></tr></thead><tbody><tr><td>ENSMUSG00000104572|-Fbxw23</td><td>4,225</td><td>8,43E-09</td></tr><tr><td>ENSMUSG0000028736|Pax7</td><td>24,215</td><td>8,73E-09</td></tr><tr><td>ENSMUSG0000028023|Pitx2</td><td>22,904</td><td>9,23E-08</td></tr><tr><td>ENSMUSG0000023959|224,796|Clic5</td><td>0,897</td><td>3,16E-07</td></tr><tr><td>ENSMUSG0000042622|17,133|Maff</td><td>1,782</td><td>8,72E-07</td></tr><tr><td>ENSMUSG0000001815|14,029|Evx2</td><td>21,131</td><td>1,58E-06</td></tr><tr><td>ENSMUSG00000021070|12,062|Bdkrb2</td><td>2,405</td><td>2,50E-06</td></tr><tr><td>ENSMUSG00000031285|13,193|Dcx</td><td>-0,791</td><td>3,62E-05</td></tr><tr><td>ENSMUSG00000121500|236,604|-</td><td>0,844</td><td>6,15E-05</td></tr><tr><td>ENSMUSG00000028434|54,357|Epb411b</td><td>0,519</td><td>0,0002</td></tr><tr><td>ENSMUSG00000097649|-Gm10561</td><td>-0,898</td><td>0,0004</td></tr><tr><td>ENSMUSG00000115529|319,903|9630013A20Rik</td><td>-1,873</td><td>0,0018</td></tr><tr><td>ENSMUSG00000033383|239,766|Rtp1</td><td>3,128</td><td>0,0019</td></tr><tr><td>ENSMUSG00000023795|-Pisd-ps2</td><td>0,722</td><td>0,0019</td></tr><tr><td>ENSMUSG00000037708|381,350|Spag6</td><td>1,162</td><td>0,0020</td></tr><tr><td>ENSMUSG00000114189|319,466|9330199G10Rik</td><td>2,136</td><td>0,0021</td></tr><tr><td>ENSMUSG00000104093|102,637,797|A330015K06Rik</td><td>0,962</td><td>0,0027</td></tr><tr><td>ENSMUSG00000002831|57,435|Plin4</td><td>3,790</td><td>0,0027</td></tr><tr><td>ENSMUSG00000052229|574,402|Gpr17</td><td>-0,809</td><td>0,0027</td></tr><tr><td>ENSMUSG00000104674|-Gm42756</td><td>1,620</td><td>0,0033</td></tr><tr><td>ENSMUSG00000020571|71,853|Pdia6</td><td>-0,354</td><td>0,0038</td></tr><tr><td>ENSMUSG00000045498|93,874|Pcdhb3</td><td>0,610</td><td>0,0052</td></tr><tr><td>ENSMUSG00000085925|353,326|Rtl1</td><td>3,591</td><td>0,0056</td></tr><tr><td>ENSMUSG00000023067|12,575|Cdkn1a</td><td>1,240</td><td>0,0073</td></tr><tr><td>ENSMUSG00000006411|71,740|Nectin4</td><td>0,680</td><td>0,0084</td></tr><tr><td>ENSMUSG00000038963|108,115|Slco4a1</td><td>1,295</td><td>0,0093</td></tr><tr><td>ENSMUSG00000027452|68,738|Acs1</td><td>-0,404</td><td>0,0093</td></tr><tr><td>ENSMUSG00000055148|16,598|Klf2</td><td>-0,792</td><td>0,0093</td></tr><tr><td>ENSMUSG00000015468|18,132|Notch4</td><td>0,880</td><td>0,0124</td></tr><tr><td>ENSMUSG00000044748|13,214|Defb1</td><td>6,450</td><td>0,0139</td></tr><tr><td>ENSMUSG00000048752|235,631|Prss50</td><td>1,530</td><td>0,0139</td></tr><tr><td>ENSMUSG00000111971|-Gm48678</td><td>-1,273</td><td>0,0139</td></tr><tr><td>ENSMUSG00000041828|217,258|Abca8a</td><td>0,833</td><td>0,0146</td></tr><tr><td>ENSMUSG00000054252|14,184|Fgfr3</td><td>0,545</td><td>0,0168</td></tr><tr><td>ENSMUSG00000055150|330,463|Zfp78</td><td>-0,856</td><td>0,0168</td></tr><tr><td>ENSMUSG00000072825|217,882|Cep170b</td><td>0,252</td><td>0,0206</td></tr><tr><td>ENSMUSG00000044361|271,278|BC024139</td><td>1,519</td><td>0,0228</td></tr><tr><td>ENSMUSG00000030834|27,421|Abcc6</td><td>-1,160</td><td>0,0236</td></tr><tr><td>ENSMUSG00000042644|16,440|Itpr3</td><td>0,700</td><td>0,0237</td></tr><tr><td>ENSMUSG00000030048|68,888|Gkn3</td><td>-1,784</td><td>0,0307</td></tr><tr><td>ENSMUSG00000027833|20,429|Shox2</td><td>7,962</td><td>0,0320</td></tr><tr><td>ENSMUSG00000051599|93,873|Pcdhb2</td><td>0,753</td><td>0,0320</td></tr><tr><td>ENSMUSG00000047216|227,485|Cdh19</td><td>0,927</td><td>0,0326</td></tr><tr><td>ENSMUSG00000029491|18,587|Pde6b</td><td>3,343</td><td>0,0364</td></tr><tr><td>ENSMUSG00000030096|21,366|Slc6a6</td><td>0,438</td><td>0,0366</td></tr><tr><td>ENSMUSG00000030413|21,946|Pglyrp1</td><td>1,452</td><td>0,0395</td></tr><tr><td>ENSMUSG00000026864|14,828|Hspa5</td><td>-0,327</td><td>0,0425</td></tr><tr><td>ENSMUSG00000029570|16,848|Lnf</td><td>0,919</td><td>0,0425</td></tr><tr><td>ENSMUSG000000092035|170,676|Peg10</td><td>1,296</td><td>0,0425</td></tr><tr><td>ENSMUSG00000100837|78,500|1700063D05Rik</td><td>1,684</td><td>0,0425</td></tr><tr><td>ENSMUSG00000085622|-3110056K07Rik</td><td>-0,656</td><td>0,0425</td></tr><tr><td>ENSMUSG00000022462|67,760|Slc38a2</td><td>0,526</td><td>0,0425</td></tr><tr><td>ENSMUSG00000064340|17,735|mt-Tl1</td><td>0,764</td><td>0,0425</td></tr><tr><td>ENSMUSG00000046764|208,079|A530053G22Rik</td><td>4,211</td><td>0,0476</td></tr><tr><td>ENSMUSG00000036357|245,424|Gpr101</td><td>0,994</td><td>0,0498</td></tr><tr><td>ENSMUSG00000041534|19,661|Rbp3</td><td>3,735</td><td>0,0498</td></tr></tbody></table>

the late middle-age group. In summary, the initial GS was sufficient to promote long-term adverse neurophysiological changes in late middle-age mice, unlike young-adult individuals who did not exhibit such trajectories in response to a similar initial GS pattern.

## 3.2. Seizures and neuroinflammatory changes in young-adult and late middle-age brain

First, we tested whether tissue damage could emerge in response to

the initial GS pattern and the neurophysiological trajectories discovered. At the histological level, neither age group exhibited hippocampal sclerosis (Fig. 6A-A1) over time due to seizures, while somatosensory cortex thickness reduction was associated with age only (Fig. 6D-D1). Furthermore, we did not identify quantifiable DG granule cell dispersion or CA3 pyramidal cell loss (Fig. 6B and C-C1) over time post-GS, extending previous evidence in this mouse strain (McCord et al., 2008). Next, because seizure conditions are often associated with neu- roinflammation (Vezzani et al., 2022), we examined the presence of glial cell reactivity. At 48 h post-GS, GFAP⁺ fluorescence (Fig. 7A-A1 and Fig. 8A-A1) increased in the sub-hippocampal regions; the magnitude of this increase differed between the two age groups, with a more pro- nounced surge in the older cohort compared to young-adults (Fig. 7B-D). A trend increase was detected in the cortex of late middle-age mice, compared to age-matched shams (Fig. 7E). In the long term (2 months post-GS; Fig. 7F-F1 and Fig. 8B-B1), a non-significant trend toward GFAP increase was observed in late middle-age animals across regions, compared to young-adults post-GS and age-matched shams (Fig. 7G-J). When analyzing IBA1⁺ microglial cells (Fig. 9A-A1), we found an increased cell count (Fig. 9B-D) in the CA1, CA3, and DG regions of late middle-age mice 48 h post-GS. Qualitatively, we report morphological indicators of reactivity, such as ramification retraction in the CA1 of late middle-age mice (Fig. 9J). In long-term post-GS, the number of IBA1⁺ cells was comparable across groups (Fig. 9F-I). Qualitative increased soma size and retraction of cell ramifications were observed in the CA regions long-term in late middle-age mice (Fig. 9J1). Taken together, these results reveal trajectories of glial cell activation that depend on age and abnormal neurophysiology.

## 3.3. Seizures, age, and long-term transcriptomic changes

Finally, we investigated the presence of transcriptomic alterations in the long term, resulting from the initial GS as a function of age and the neurophysiological trajectories discovered. We specifically performed RNA sequencing on whole hippocampi from late middle-age and young-adult mice. After adjusting for multiple comparisons, 55 genes were identified as differentially regulated between the two groups (Table 1). Among these, we report a subset of five transcripts upregulated in late middle-age compared to young-adult mice long-term post-GS with fold-changes >1 and adjusted p-value <0.05 with identified functions in the mammalian brain: beta-defensin 1 (Defb1), a member of a family of immunomodulatory peptides (Williams et al., 2013); peptidoglycan recognition protein 1 (Pglyrp1), an emerging immune mediator expressed by glial cells (Bhusal et al., 2024); bradykinin receptor B2 (Bdkrb2), with implications edema formation (Rouhiainen et al., 2019); cyclin-dependent kinase inhibitor 1 A (Cdkn1a), a negative regulator of cell cycle and PAX7, a cell growth modulator (Robson et al., 2006). These findings highlight the involvement of a distinct set of genes that regulate immune responses and cell cycle dynamics in the late middle-age brain and consequent to neurophysiopathology.

# 4. Discussion

## 4.1. Neurophysiological maladaptations emerge as a function of age of seizure onset

We report age-dependent adverse neurophysiological sequelae emerging long-term after an initial pattern of GS, associated with neu- roinflammatory activations and transcriptomic footprints. These results provide experimental insights that may contribute to our understanding of the trajectories promoted by clinical late-onset seizures. It is impor- tant to elucidate how seizure activity interacts with age and neurological frailty (Hashmi et al., 2024), comparing younger and older populations to implement management strategies that are age-dependent (Cresto et al., 2024a; Romoli et al., 2021; Stefanidou et al., 2024).

From the initial GS pattern (Figs. 1-2), spontaneous sporadic seizures
A

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**Fig. 5.** Long-term behavioral patterns in the four groups studied. **A-B)** Locomotion, **C—F)** anxiety-like behavior, and **G-H)** memory were measured (6-8 weeks post-GS) using the open field and the O-maze. **C—D)** Passages and time spent in the center zone were measured (over 10 min) and normalized over the distance traveled. The passages and time spent in the open field center area remained unchanged or showed a trend of decrease for late middle-age mice in the long-term post-GS. **F)** Anxiety-like behavior was evaluated using the O-maze. No differences in visit duration between the open and closed segments. **G-H)** Mice were exposed to two similar objects in the arena, and 24 h later, one familiar object (F) was replaced by a new one (N). No significant differences observed between groups, except for late middle-age post-GS showing chance-level preference ratio closer to 50%. **I-J)** Correlation matrix between long-term behavioral and EEG measures for young-adult and late middle-age mice (Pearson's r correlation; *p*-values indicated when significant). **Statistics:** **B)** Two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,52} = 21.07$ for seizure model (P < 0.0001); $F_{1,52} = 8.710$ for age (P < 0.01); and $F_{1,52} = 0.1963$ for interaction (ns); **C)** Two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,52} = 0.3786$ for seizure model (ns); $F_{1,52} = 7.796$ for age (P < 0.01); and $F_{1,52} = 0.5142$ for interaction (ns); **D)** Two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,52} = 0.7185$ for seizure model (ns); $F_{1,52} = 1.866$ for age (ns); and $F_{1,52} = 6.495$ for interaction (P < 0.05). **F—H)** One sample *t*-test (hypothetical mean: 0.5) or a two-way ANOVA followed by a Tukey's multiple comparison were performed; for **panel F:** $F_{1,52} = 0,6602$ for seizure model (ns); $F_{1,52} = 0,6663$ for age (ns); and $F_{1,52} = 0,0020$ for interaction (ns); for **panel H:** $F_{1,52} = 0.8756$ for seizure model (ns); $F_{1,52} = 2.793$ for age (ns); and $F_{1,52} = 0.0092$ for interaction (ns). For all data: young-adult sham, *n* = 11; young-adult post-GS, *n* = 12; late middle-age sham, *n* = 16; late middle-age post-GS, *n* = 17 (*p* < 0.05; ** *p* < 0.01; *** *p* < 0.001). **** *p* < 0.0001; ns = not significant).

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**Fig. 6.** Absence of seizure-dependent hippocampal sclerosis or cortical atrophy long-term in late middle-age and young-adult brains. **A-A1)** Examples of hippocampal DAPI maps showing absence of hippocampal sclerosis in young-adult and late middle-age mice post-GS (48 h and 2 months). **B)** Examples of DG and CA3 regions from late middle-age mice over time post-GS and sham (white lines indicate measurement for quantifications). **C—C1)** Quantifications for DG and CA3 thickness, showing no pathological cell (granular or pyramidal) dispersion, two specific regions with reported damage in experimental epilepsy. **D—D1)** Examples (2 months post-GS) and quantifications of cortical thickness across experimental conditions. Statistical analyses. **C)** DG 48 h; two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 0.3229$ for seizure model (ns); $F_{1,12} = 1.028$ for age (ns); and $F_{1,12} = 3.889$ for interaction (ns). DG 2-months; two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 0.8914$ for seizure model (ns); $F_{1,12} = 1.202$ for age (ns); and $F_{1,12} = 2.699$ for interaction (ns). **C1)** CA3 48 h; two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 0.0198$ for seizure model (ns); $F_{1,12} = 1.911$ for age (ns); and $F_{1,12} = 0.055$ for interaction (ns). CA3 2-months; two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 0.7534$ for seizure model (ns); $F_{1,12} = 0.0724$ for age (ns); and $F_{1,12} = 7.905$ for interaction (P < 0.05). **D1)** Cortex 48 h; two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 0.8473$ for seizure model (ns); $F_{1,12} = 20.62$ for age (P < 0.001); and $F_{1,12} = 0.8473$ for interaction (ns). Cortex 2-months; two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 2.309$ for seizure model (ns); $F_{1,12} = 15.18$ for age (P < 0.05); and $F_{1,12} = 0.16$ for interaction (ns).
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**Fig. 7.** Distinct astrocyte reactivity patterns in late middle-age compared to young-adult brains post-GS. **A-A1)** Examples of 20× images (GFAP/DAPI) from the dorsal hippocampal CA1 region and somatosensory cortex obtained 48 h post-GS in young-adult and late middle-age and age-matched sham mice. **B-E)** Quantification of GFAP optical density (% of young-adult sham) 48 h post-GS in young-adult and late middle-age groups. Late middle-age mice showed the most increase in GFAP at this early time. **F—F1)** Examples of 20× images (GFAP/DAPI) from the dorsal hippocampal CA1 region and somatosensory cortex 2-months post-GS in young-adult and late middle-age and age-matched sham mice. **G-J)** Quantification of GFAP optical density 2-months post-GS in young-adult and late middle-age groups. Statistical analyses: **B)** Two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 60.94$ for seizure model (P < 0.0001); $F_{1,12} = 44.75$ for age (P < 0.0001); $F_{1,12} = 13.91$ for interaction (P < 0.01); **C)** Two-way ANOVA followed by a Tukey's multiple comparison were performed $F_{1,12} = 56.87$ (P < 0.0001) for seizure model; $F_{1,12} = 13.48$ (P < 0.01) for age; $F_{1,12} = 7.493$ for interaction (P < 0.05); **D)** Two-way ANOVA followed by a Tukey's multiple comparison were performed $F_{1,12} = 38.33$ (P < 0.0001) for seizure model; $F_{1,12} = 7.603$ (P < 0.05) for age; $F_{1,12} = 5.294$ for interaction (P < 0.05); **E)** Two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 3.130$ (ns) for seizure model; $F_{1,12} = 14.24$ (P < 0.01) for age; $F_{1,12} = 4.013$ for interaction (ns); **G)** Two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 3.673$ (ns) for seizure model; $F_{1,12} = 1.143$ (ns) for age; $F_{1,12} = 0.9322$ for interaction (ns); **H)** Multiple Mann-Whitney test follow by Holm-Sídák method were performed: Young-adult Sham vs. Young-adult post-GS: $U_{1,7} = 4$ (ns); late middle-age Sham vs. late middle-age post-GS $U_{1,7} = 3$; **I)** Two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 2.912$ (ns) for seizure model; $F_{1,12} = 1.142$ (ns) for age; $F_{1,12} = 3.316$ for interaction (ns); **J)** Two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 9.386$ (P < 0.01) for seizure model; $F_{1,12} = 0.3275$ (ns) for age; $F_{1,12} = 0.3829$ for interaction (ns). For all data: *n* = 4 mice per groups with three slices per mice (*p* < 0.05; **p** < 0.01; ***p** < 0.001; ****p** < 0.0001; ns = not significant).

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<figure><img src="image_56.png" /><figcaption>**Fig. 8.** DG and CA3 histological examples (quantifications in Fig. 7) of astrocyte reactivity patterns in late middle-age compared to young-adult brains post-GS. **A-A1)** Examples of 20× images (GFAP/DAPI) from DG and CA3 regions obtained 48 h post-GS in young-adult and late middle-age and age-matched sham mice. **B—B1)** Examples of 20× images (GFAP/DAPI) from DG and CA3 regions obtained 2-months post-GS in young-adult and late middle-age and age-matched sham mice.</figcaption></figure>

or the highest number of SWDs emerged over time in four out of seven late middle-age mice (Fig. 3). This group displayed the highest spike activity (Fig. 4) and modifications of theta waves during awake stages (Fig. 4 D1, D3) or delta during sleep (Fig. 4 E3) in the long term. Seizures were nevertheless infrequent compared with those observed in typical

epileptogenic models (Rusina et al., 2021; Riban et al., 2002). Yet, as epilepsy is defined as the occurrence of at least two seizures over time, one could argue that a subset of late middle-age mice may have undergone epileptogenesis, also considering that the EEG schedule applied here could underestimate the long-term spontaneous events. Our results
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**Fig. 9.** Microglia numbers and morphological changes in young-adults and late middle-age post-GS mice. **A-A1)** Examples of 20× images (IBA1) from hippocampal regions and the somatosensory cortex obtained 48 h post-GS in young-adult and late middle-age and age-matched sham mice. **B-E)** Quantification of the number of microglial cells 48 h post-GS in young-adult and late middle-age groups in specific regions of interest. The GS pattern was associated with an increased number of microglia cells in the short-term (48 h post-GS) only in late middle-age mice and in selected areas. **F-I)** Quantification of the number of microglial cells 2-months post-GS in young-adult and late middle-age groups. No changes were observed in the long-term. Long-term post-GS images are not shown. **J-J1)** Morphological signs of microglial activation (arrow) are present 48 h post-GS and specifically in late middle-age mice 2 months post-GS, as compared to young-adult and age-matched sham. Statistics: **B)** Two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 10.63$ for seizure model (P < 0.01); $F_{1,12} = 32.52$ for age (P < 0.0001); $F_{1,12} = 10.63$ for interaction (ns); **C)** Two-way ANOVA followed by a Tukey's multiple comparison were performed $F_{1,12} = 7.966$ (P < 0.05) for seizure model; $F_{1,12} = 9.684$ (P < 0.01) for age; $F_{1,12} = 1.728$ for interaction (ns); **D)** Two-way ANOVA followed by a Tukey's multiple comparison were performed $F_{1,12} = 7.991$ (P < 0.05) for seizure model; $F_{1,12} = 9.916$ (P < 0.01) for age; $F_{1,12} = 5.474$ for interaction (P < 0.05); **E)** Two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 0.005$ (ns) for seizure model; $F_{1,12} = 0.032$ (ns) for age; $F_{1,12} = 0.1723$ for interaction (ns). **F)** Multiple Mann-Whitney test follow by Holm-Sídák method were performed: Young-adult Sham vs. Young-adult post-GS: $U_{1,7} = 6$ (ns); late middle-age Sham vs. late middle-age post-GS $U_{1,7} = 8$; **G)** Two-way ANOVA followed by a Tukey's multiple comparisons were performed: $F_{1,12} = 0.7041$ (ns) for seizure model; $F_{1,12} = 7.532$ (P < 0.05) for age; $F_{1,12} = 0.8083$ for interaction (ns); **H)** Two-way ANOVA followed by a Tukey's multiple comparisons were performed: $F_{1,12} = 0.7018$ (ns) for seizure model; $F_{1,12} = 0.3944$ (ns) for age; $F_{1,12} = 0.9937$ for interaction (ns); **I)** Two-way ANOVA followed by a Tukey's multiple comparison were performed: $F_{1,12} = 0.2389$ (ns) for seizure model; $F_{1,12} = 0.3375$ (ns) for age; $F_{1,12} = 0.8431$ for interaction (ns). For all data: n = 4 mice per groups with three slices per mice (*p* < 0.05; ns = not significant).

extend to clinical contexts where SWDs, brief seizures, and spike activity can be undiagnosed, particularly with advancing age, where they could accelerate a decline in cognitive functions (Keret et al., 2020; Somes, 2024). In this respect, we report some adaptations in behavioral outputs emerging in the long term in late middle-age mice that experienced initial GS (Fig. 5). As a corollary, we observed increased EEG spike activity in late middle-age sham mice compared to young-adult sham (Fig. 4A), capturing SWDs (Figs. 3A3-3E). Notably, hippocampal excitability is increased in late middle-age mice, with relevance to augmented seizure susceptibility (El-Hayek et al., 2013). During sleep, late middle-age sham mice presented with an increase in delta wave (2.5-3.5 Hz) compared to young-adult sham (Fig. 4E2). These analyses of sham mice reveal specific EEG patterns that emerge due to aging, perhaps indicating biomarkers of pre-existing neurophysiological weakness (Lehner et al., 2024). A propensity to neuronal and cognitive changes emphasizes the need for targeted surveillance biomarkers and interventions in the aging population. Using late middle-age mice to discover mechanisms and targets tailored to late-onset seizures represents a valuable tool (Del Pozo et al., 2022).

We highlight that late middle-age mice, which exhibited more pronounced changes in the long-term, received lower doses of KA compared to young-adults (Supplementary Fig. 1). This fact suggests that the observed long-term effects in older mice are unlikely to result from KA-induced toxicity during the acute phase. As mentioned, we did not study the effect of SE. Notably, the impact of SE in late middle-age has been examined in previous studies, showing a loss of hippocampal CA1 pyramidal neurons compared to young individuals, with a risk of temporal lobe epilepsy (Hattiangady et al., 2011; Kuruba et al., 2011) and indicators of adverse neurological outcomes (Rao et al., 2008; Cavarsan et al., 2011). Our results outline the neurophysiological and cellular impact of an acute insult less severe than SE, with a focus on previously unexamined long-term trajectories and at the neuroinflammatory and transcriptomic levels. Importantly, the reported modifications in the late middle-age brains occurred in the absence of hippocampal sclerosis or cortical damage.

## 4.2. Glial cell changes, seizures, and an inflammatogenic framework

As causes or epiphenomena, astrocytes and microglial cells modify their morphology and molecular makeup in various forms of epilepsy, contributing to neuroinflammation (van Vliet and Marchi, 2022; Vezzani et al., 2022; Klement et al., 2018; Sweeney et al., 2018). Short-term, we report greater astrocyte activation in late middle-age animals in response to GS than in the other groups (Figs. 7-8). In the long term (2 months), late middle-age post-GS mice exhibited a non-statistically significant trend toward increased GFAP signal in the cortex and DG. This result indicates the intrinsic and regional susceptibility of aging astrocytes to this acute insult and its pathological trajectories (Knox et al., 2022; Matias et al., 2019). As mentioned, our data reflect the

impact of seizures that are less severe than SE (Rusina et al., 2021; Riban et al., 2002). Thus, following SE, marked and prolonged microglial and astrocyte activations were reported (van Vliet and Marchi, 2022; Vezzani et al., 2022). Our results are consistent with the fact that aging alone can alter glial cells, possibly reducing their ability to maintain homeostatic balance or withstand an insult, therefore supporting an inflammatogenic context (Finger et al., 2022) in late-onset seizures (Matias et al., 2019; Palmer and Ousman, 2018; Clarke et al., 2018).

## 4.3. Age-dependent long-term molecular signatures of frailty and seizures

We report a long-term increase in specific transcripts (Table 1) associated with immune response and cell cycle homeostasis in late middle-age mice following seizures, as compared to young-adults. We emphasize the upregulation of three genes involved in immune homeostasis, namely Defb1, Pglyrp1, and Bdkrb2. In particular, Pglyrp1 is a pattern-recognition protein implicated in the innate immune response in the brains of humans and mice. Its levels increase during inflammation, recombinant Pglyrp1 protein augments neuroinflammation, while its shRNA-mediated knockdown presents beneficial effects (Bhusal et al., 2024). Relevant to aging and neurodegeneration, the immunomodulatory peptide Defb1 was previously found to be upregulated in an experimental model of Alzheimer's disease, accompanied by glial activation and iron deposition in the brain (Williams et al., 2013). Finally, we found increased Bdkrb2 transcript levels, a factor previously linked to disrupted vascular homeostasis, and reported to modulate neurological stress responses (Rouhiainen et al., 2019). We reported increased Cdkn1a and PAX7, which are negative regulators of the cell-cycle G1 phase and respond to stress stimuli, including inflammation, as well as cell growth modulators (Robson et al., 2006; Florkowska et al., 2021). These findings illustrate the persistence of specific cellular stress and immunological biomarkers in the context of late-onset seizures, possibly disclosing targetable candidates or biomarkers applicable to the clinic (Nader et al., 2023).

## 4.4. Study limitations

Our study has several limitations that we would like to acknowledge. For instance, we studied males only. This choice was in part a consequence of the initial studies we used as roadmaps for performing kainic acid injections during aging (McCord et al., 2008). Examining whether outcome differences exist between males and females within this framework is important and warrants further study. Furthermore, other chemical models (e.g., PTZ) could have been used, while we cannot perform electrical kindling, which is a model that could fit this research endeavor. One could also argue that our study lacks sufficient control for seizure variability; it also assumes that acute seizures in young-adult and late middle-age mice are mechanistically comparable despite inherent differences in KA susceptibility. The latter remains an unavoidable and
intrinsic characteristic of this type of modeling. We acknowledge that the exact biological relevance of the reported transcript changes necessitates further research. Although seizure activity was detected at the cortical-hippocampal level, transcriptomic analysis was performed only in the hippocampus, a choice we made due to the role of this structure in KA-induced seizures, circuit remodeling, and the possible neurodegenerative changes that often arise from this region. Furthermore, we did not examine cellular biomarkers of neurodegeneration, frailty, or senescence, nor did we investigate the involvement of blood-brain barrier permeability in its pathological remodeling as a function of age and seizures (van Vliet and Marchi, 2022). Finally, our EEG protocol did not allow us to evaluate high-frequency oscillations, an important biomarker reported in experimental Alzheimer's disease (Lisgaras and Scharfman, 2023). The latter represents a potential research avenue.

## 5. Conclusions

We show that an initial pattern of GS can induce neurophysiological and neuroinflammatory alterations that become more pronounced with advancing age (Hashmi et al., 2024; Palmer and Ousman, 2018; Clarke et al., 2018). Understanding the interaction between age-related vulnerability, inflamming, and abnormal neuronal network activity is important for anticipating neurological sequelae and identifying new disease biomarkers or targets, ultimately informing clinical decision-making in an aging population.

Supplementary data to this article can be found online at https://doi.org/10.1016/j.nbd.2025.107177.

## Ethical publication

We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.

## CRediT authorship contribution statement

**Alicia Janvier:** Validation, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Noémie Cresto:** Methodology, Investigation, Formal analysis, Data curation. **Cristina Nistreanu:** Validation, Methodology, Investigation, Formal analysis. **Athenais Genin:** Validation, Methodology, Investigation. **Tristan Moujellil-Legagneur:** Data curation. **Magalie Mathias:** Methodology, Investigation, Formal analysis. **Mathieu Vitalis:** Supervision, Methodology, Investigation. **Paolo Fabene:** Writing – original draft, Validation, Supervision, Data curation. **Edoardo Parrella:** Writing – original draft, Validation, Supervision, Data curation, Conceptualization. **Charleine Zussy:** Methodology, Investigation. **Etienne Audinat:** Writing – original draft, Validation, Supervision, Data curation, Conceptualization. **Laurent Givalois:** Writing – review & editing, Writing – original draft, Validation, Supervision, Project administration, Methodology, Funding acquisition, Formal analysis, Data curation, Conceptualization. **Nicola Marchi:** Writing – review & editing, Writing – original draft, Validation, Project administration, Investigation, Funding acquisition, Data curation, Conceptualization.

## Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work, the Author (s) used Grammarily only to perform a final spell-check. After using this tool/service, the Author (s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

## Declaration of competing interest

None of the authors has any conflict of interest to disclose.

## Acknowledgments

This work was supported, as a whole or in part, by ANR-EpiNeurAge to NM and LG; ANR-EpiCatcher and ANR-CEST-Focus to NM.

## Data availability

Data will be made available on request.

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