Many animal prototypes illustrating the various attributes of human temporal lobe epilepsy (TLE) are available. These models have been invaluable for comprehending multiple epileptogenic processes, modifications in electrophysiological properties, neuronal hyperexcitability, neurodegeneration, neural plasticity, and chronic neuroinflammation in TLE. Some models have also uncovered the efficacy of new antiepileptic drugs or biologics for alleviating epileptogenesis, cognitive impairments, or spontaneous recurrent seizures (SRS). Nonetheless, the suitability of these models for testing candidate therapeutics in conditions such as chronic TLE is debatable because of a lower frequency of SRS and an inconsistent pattern of SRS activity over days, weeks or months. An ideal prototype of chronic TLE for investigating novel therapeutics would need to display a large number of SRS with a dependable frequency and severity and related co-morbidities. This study presents a new kainic acid (KA) model of chronic TLE generated through induction of status epilepticus (SE) in 6-8 weeks old male F344 rats. A rigorous characterization in the chronic epilepsy period validated that the animal prototype mimicked the most salient features of robust chronic TLE. Animals displayed a constant frequency and intensity of SRS across weeks and months in the 5th and 6th month after SE, as well as cognitive and mood impairments. Moreover, SRS frequency displayed a rhythmic pattern with 24-hour periodicity and a consistently higher number of SRS in the daylight period. Besides, the model showed many neuropathological features of chronic TLE, which include a partial loss of inhibitory interneurons, reduced neurogenesis with persistent aberrant migration of newly born neurons, chronic neuroinflammation typified by hypertrophied astrocytes and rod-shaped microglia, and a significant aberrant mossy fiber sprouting in the hippocampus. This consistent chronic seizure model is ideal for investigating the efficacy of various antiepileptic drugs and biologics as well as understanding multiple pathophysiological mechanisms underlying chronic epilepsy.
These authors contributed equally to this work. Current address, DU: Centre for Molecular Neurosciences, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, India; OWC and DG: Institute Biological Sciences and Health, Federal University of Alagoas (UFAL), Maceio, AL, Brazil; GZ: Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, RS, Brazil.
Just Accepted Date: 07 August 2019Issue Date: 27 September 2019
Upadhya Dinesh,Kodali Maheedhar,Gitai Daniel, et al. A Model of Chronic Temporal Lobe Epilepsy Presenting Constantly Rhythmic and Robust Spontaneous Seizures, Co-morbidities and Hippocampal Neuropathology[J]. Aging and disease,
2019, 10(5): 915-936.
Figure 1. Analysis of time-locked video-EEG tracings from chronically epileptic rats (CERs) in the 5th month after induction of status epilepticus (SE). Data from 3 weeks of continues EEG recordings are illustrated. (A) An example of EEG tracings during a spontaneous recurrent seizure (SRS). The bar charts in B1-B4 compare daily SRS activity occurring over 21 consecutive days. Note that, the number of SRS per day (B1), the number of stage-V SRS/day (B2), the duration of individual SRS (B3), and the percentage of time spent in SRS activity (B4) were comparable across 21 days (p>0.05, repeated measures ANOVA, RM-ANOVA). The bar charts in C1-C4 compare weekly SRS activity occurring over 3 consecutive weeks. Note that, the number of SRS per week (C1), the number of stage-V SRS/week (C2), the duration of individual SRS (C3), and the percentage of time spent in SRS activity (C4) were comparable across 3 weeks (p>0.05, RM-ANOVA).
Figure 2. Analysis of time-locked video-EEG tracings from chronically epileptic rats (CERs) in the 6th month after induction of status epilepticus (SE). Data from 3 weeks of continues EEG recordings are illustrated. (A) An example of EEG tracings during a spontaneous recurrent seizure (SRS). The bar charts in B1-B4 compare daily SRS activity occurring over 21 consecutive days. Note that, the number of SRS per day (B1), the number of stage-V SRS/day (B2), the duration of individual SRS (B3) , and the percentage of time spent in SRS activity (B4) were comparable across 21 days (p>0.05, repeated measures ANOVA, RM-ANOVA). The bar charts in C1-C4 compare weekly SRS activity occurring over 3 consecutive weeks. Note that, the number of SRS per week (C1), the number of stage-V SRS/week (C2), the duration of individual SRS (C3), and the percentage of time spent in SRS activity (C4) were comparable across 3 weeks (p>0.05, RM-ANOVA).
Figure 3. Comparison of EEG data taken from chronically epileptic rats (CERs) in the 5th and 6th month after status epilepticus (SE). The bar charts in A1-A4 compare the average daily SRS activity occurring over 21 consecutive days. Note that, the number of SRS per day (A1) , the average number of stage-V SRS/day (A2), the duration of individual SRS (A3), and the percentage of time spent in SRS activity (A4) were comparable between CERs recorded in the 5th month after SE and CERs recorded in the 6th month after SE (p>0.05, two-tailed, unpaired Student’s t-test). The bar charts in B1-B4 compare the average weekly SRS activity occurring over 3 weeks. Note that, the number of SRS per week (B1), the number of stage-V SRS per week (B2), the duration of individual SRS (B3), and the percentage of time spent in SRS activity (B4) were comparable across 3 weeks (p>0.05, two-tailed, unpaired Student’s t-test). NS, not significant.
Figure 4. Comparison of daily EEG data from daylight (6 AM to 6 PM) and night (6 PM to 6 AM) periods in the 5th and 6th month after status epilepticus (SE). The bar charts in A1 and A3 illustrate consistently higher frequencies of SRS (A1) and Stage-V SRS (A3) in daylight periods than night periods in the 5th month after SE. The bar charts in A2 and A4 compare the average frequency of SRS (A2) and Stage-V SRS (A4) over 21 consecutive days between the daylight and night periods in the 5th month after SE. The bar charts in B1 and B3 illustrate higher frequencies of SRS (B1) and Stage-V SRS (B3) in daylight periods than night periods in the 6th month after SE. The bar charts in B2 and B4 compare the average frequency of SRS (B2) and Stage-V SRS (B4) between the daylight and night periods in the 6th month after SE. *, p< 0.05; **, p< 0.01; ***, p<0.001; NS, not significant.
Figure 5. 24-hour periodicity of seizures occurring in the 5th month (A) and 6th month (B) after status epilepticus (SE). In each month, EEG data from 21 consecutive days were used for plotting the periodicity of seizures. Note that, the SRS activity peaks during the daylight period and drops in the night period, in both the 5th month (p<0.05) and 6th month (p<0.001) after SE.
Figure 6. Chronically epileptic rats (CERs) displayed cognitive, memory, and mood impairments. The results of an object location test (OLT, A1-A3), a novel object recognition test (NORT, B1-B3), a pattern separation test (PST, C1-C3), and a sucrose preference test (SPT, D1-D4). The bar charts in A1-A2 compare percentages of time spent with the object in a familiar place (OIFP) and the object in a novel place (OINP) in naïve rats (A1) and CERs (A2) whereas, the bar chart in A3 compares the total object exploration time between naïve rats and CERs. Note that, naïve rats showed a higher propensity to explore OINP over OIFP (p<0.01) whereas, CERs showed no such preference in an OLT (p>0.05). The bar charts in B1-B2 compare percentages of time spent with the familiar object (FO) and the novel object (NO) in naïve rats (B1) and CERs (B2) whereas, the bar chart in B3 compares the total object exploration time between naïve rats and CERs. Note that, naïve rats showed higher propensity to explore NO over FO (p<0.05) whereas, CERs showed no such preference in a NORT (p>0.05). The bar charts in C1-C2 compare percentage of times spent with the familiar object on pattern 2 (FO of P2) and the novel object on pattern 2 (NO on P2) in naïve rats (C1) and CERs (C2) whereas, the bar chart in C3 compares the total object exploration time between naïve rats and CERs. Note that, naïve rats spent a greater amount of time with the NO on P2, in comparison to FO on P2 (p<0.001) whereas, CERs showed no such bias in a PST (p>0.05). The bar charts in D1-D2 compare consumption of regular water and sucrose-containing water in naïve rats (D1) and chronically epileptic rats (CERs). Note that, naïve rats preferred to drink sucrose-containing water (D1) whereas CERs showed no such preference (D2). The bar chart in D3 illustrates that the total consumption of fluid was comparable between naïve rats and CERs. The bar chart in D4 shows that the sucrose preference rate is greater in naïve rats in comparison to CERs (p<0.001). *, p< 0.05; **, p< 0.01; ***, p<0.001; NS, not significant.
Figure 7. Chronically epileptic rats (CERs) demonstrated reduced numbers of interneurons positive for parvalbumin (PV) and neuropeptide Y (NPY) in the dentate gyrus (DG). (A1-A4) illustrate the distribution of PV+ interneurons in a naïve control DG (A1) and a CER (A3). (A2) and (A4) are magnified views of regions from A1 and B1. (B1-B4) illustrate the distribution of PV+ interneurons in the DG of a naïve control rat (B1) and a CER (B3). (B2) and (B4) are magnified views of regions from B1 and B3. The bar charts show that interneurons positive for PV (A5) and NPY (B5) are reduced in number in the DG of CERs. *, p<0.05; ***, p<0.001. Scale bar, A1, A3, B1 and B3, 50 μm; A2, A4, B2 and B4, 25 μm.
Figure 8. Chronically epileptic rats (CERs) demonstrated reduced neurogenesis in the dentate subgranular zone-granule cell layer (SGZ-GCL). (A1-A4) illustrate the distribution of doublecortin-positive (DCX+) newly born neurons from a naïve control rat (A1) and a CER (A3). A2 and A4 are magnified views of regions from (A1) and (A3). The bar chart in (A5) shows that the number of newly born DCX+ neurons is reduced in the hippocampus of CERs. (B1) illustrates the abnormal migration of newly born DCX+ neurons into the dentate hilus. (B2) is a magnified of a region from B1. ***, p<0.001. Scale bar, A1, A3 and B1, 50 μm; A2, A4 and B2, 25 μm.
Figure 9. Chronically epileptic rats (CERs) showed hypertrophy of astrocytes, activated microglia, and abnormal sprouting of mossy fibers in the hippocampus. A1-A4) illustrate the distribution of glial-fibrillary acidic protein-positive (GFAP+) astrocytes in the dentate gyrus (DG) of a naïve control rat (A1) and a CER (A3). A2) and B4) are magnified views of regions from A1 and A3. The bar chart in A5 shows that the area fraction of GFAP+ elements is increased in the entire hippocampus (EH) of CERs. Figures B1-B4 illustrate the distribution of IBA-1 positive microglia in the CA1 subfield of a naïve control rat (B1), and a CER (B3). B2) and B4) are magnified views of regions from B1 and B3. Note that, the CA1 stratum radiatum in the CER displays rod-shaped activated microglia. The bar chart in A5 shows that the number of IBA-1+ microglia is increased in the entire hippocampus (EH) of CERs. C1-C4) illustrate the distribution of ZnT3+ positive mossy fibers in the DG of a naïve control rat (C1), and a CER (C3). (C2) and (C4) are magnified views of regions from C1 and C3. Note abnormal sprouting of mossy fibers into the inner molecular layer (IML) of the DG in the CER. **, p<0.01; ***, p<0.001. Scale bar, A1, A3, B1, B3, C1 and C3, 50 μm; A2, A4, B2, B4, C2 and C4, 25 μm.
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