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Purpose: Progress in the management of patients with medically intractable epilepsy is impeded because we do not fully understand why pharmacoresistance happens and how it can be predicted. The presence of multiple seizures prior to medical treatment has been suggested as a potential predictor of poor outcome. In the present study, we used an animal model of temporal lobe epilepsy to investigate whether pharmacoresistant rats differ in seizure frequency from pharmacoresponsive animals.
Methods: Epilepsy with spontaneous recurrent seizures (SRS) was induced by status epilepticus. Frequency of SRS was determined by video/EEG (electroencephalography) monitoring in a total of 33 epileptic rats before onset of treatment with phenobarbital (PB).
Results: Thirteen (39%) rats did not respond to treatment with PB. Before treatment with PB, average seizure frequency in PB nonresponders was significantly higher than seizure frequency in responders, which, however, was due to six nonresponders that exhibited > 3 seizures per day. Such high seizure frequency was not observed in responders, demonstrating that high seizure frequency predicts pharmacoresistance in this model, but does not occur in all nonresponders.
Discussion: The data from this study are in line with clinical experience that the frequency of seizures in the early phase of epilepsy is a dominant risk factor that predicts refractoriness. However, resistance to treatment also occurred in rats that did not differ in seizure frequency from responders, indicating that disease severity alone is not sufficient to explain antiepileptic drug (AED) resistance. These data provide further evidence that epilepsy models are useful in the search for predictors and mechanisms of pharmacoresistance.
Despite the availability of numerous effective antiepileptic drugs (AEDs), about 20–40% of patients with epilepsy continue to have frequent seizures during treatment (French, 2007). Such pharmacoresistant epilepsy (also known as medically intractable or refractory epilepsy) is often a chronic, lifelong problem, associated with increased psychosocial and physical morbidity and increased mortality (Devinsky, 1999). Identifying clinical predictors for pharmacoresistant epilepsy early in the course of the disorder may be important for directing epilepsy patients to more aggressive pharmacotherapy or an effective nonpharmacologic treatment, such as surgery or vagus nerve stimulation (Arroyo et al., 2002; French, 2002; Hitiris et al., 2007; Rogawski & Johnson, 2008). Factors that have been repeatedly identified as potential predictors of refractory epilepsy include high frequency, density, or clustering of seizures before onset of treatment; a history of psychiatric comorbidity; brain lesions such as hippocampal sclerosis; and failure of response to the first AED (Camfield & Camfield, 1996; Kwan & Brodie, 2000; French, 2002; Kwan & Brodie, 2002, 2004; French, 2007; Hitiris et al., 2007). However, in the absence of understanding the mechanisms of resistance to treatment, more work is needed to determine the causes and predictors of pharmacoresistance. Animal models of epilepsy that allow direct comparison of pharmacoresistant and pharmacoresponsive animals in the absence of the various confounding factors that complicate epidemiologic studies may be valuable tools for understanding the biologic basis of drug resistance and whether or how it can be predicted (Löscher, 2006).
Over the last 20 years we have developed and characterized two rat models of pharmacoresistant temporal lobe epilepsy (TLE): phenytoin-resistant kindled rats and phenobarbital (PB)–resistant epileptic rats (Löscher, 2006). In the latter model, spontaneous recurrent seizures (SRS) occur after a latency period following induction of status epilepticus (SE) via electrical stimulation of the basolateral amygdala (BLA) (Brandt et al., 2003). By prolonged treatment of such epileptic rats with PB, two subgroups of rats can be differentiated: PB responders and nonresponders (Brandt et al., 2004). Greater than 80% of the PB nonresponders are also resistant to treatment with a second AED (Bethmann et al., 2007), so that—in parallel to the clinical situation—inadequate seizure control after initial treatment is a predictor for subsequent failure to other AEDs in this model. In the present study, we investigated whether PB-resistant rats differ from PB-responsive rats in seizure frequency before treatment. In previous studies on this model, we had repeatedly observed a trend for higher pretreatment seizure frequency in PB-nonresponders, but this difference from responders was not statistically significant because of the small sample size (Brandt et al., 2004; Bethmann et al., 2007). Therefore, we combined rats from three separate experiments for the present study, thereby increasing the statistical power for such a comparison. This allowed us to evaluate whether intrinsic disease severity is a determinant of AED refractoriness, as recently suggested from clinical data (Rogawski & Johnson, 2008).
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A history of high seizure frequency, density, or clustering prior to onset of treatment is widely accepted as a negative predictor of treatment outcome (French, 2007; Rogawski & Johnson, 2008). However, such multiple seizures often occur in difficult-to-treat localization-related epilepsies, so that it is not clear whether it is the high seizure frequency or the type of epilepsy, or both, that predicts pharmacoresistance in such patients. In the present study in a rat model of TLE, all rats with multiple seizures prior to treatment were resistant to PB, so that high seizure frequency was a powerful predictor of pharmacoresistance. However, such high seizure frequency was observed in only 46% of nonresponders, whereas the other 54% (7 of 13 nonresponders) did not differ in predrug seizure frequency from PB-responders. Therefore, factors other than high seizure frequency were obviously involved in drug resistance in this model.
We have previously reported that the majority (90%) of PB-nonresponders exhibit hippocampal damage, whereas such damage is determined in only 7% of PB-responders, so that neuron loss in the hippocampus, particularly in the dentate hilus, is a characteristic feature of PB-resistant rats (Volk et al., 2006; Bethmann et al., 2008). Again, this observation in our rat model is in line with clinical experience, in that hippocampal sclerosis in patients with TLE carries a poor prognosis (French, 2007). In addition to hippocampal damage, PB nonresponders differ from responders in increased brain expression of the efflux transporter P-glycoprotein (Pgp) (Volk & Löscher, 2005) and subunit expression and binding characteristics of γ-aminobutyric acid (GABA)A receptors (Volk et al., 2006; Bethmann et al., 2008), which may be critically involved in the lack of antiepileptic efficacy of PB in nonresponders. These clear differences between PB-responders and PB-nonresponders also indicate that the strict definition of response that we chose for selection was suitable for differentiating between pharmacoresistant and pharmacoresponsive rats, despite the low seizure frequency of many epileptic rats in the model used for our experiments. This conclusion is substantiated by the recent finding that most of the PB-nonresponders were also resistant to another AED, that is, phenytoin (Bethmann et al., 2007), which is in line with the clinical experience that failure to respond to initial treatment predicts failure of response to other AEDs (Kwan & Brodie, 2000; French, 2002).
As previously reported (Brandt et al., 2004; Volk et al., 2006; Bethmann et al., 2007), differences in the frequency of SRS or the pharmacologic response of SRS to PB was not a consequence of differences in the severity of the initial brain insult, that is, the SE. Detailed analyses of the video and EEG recordings performed during SE demonstrated that the clinical seizure activity and the number and type of paroxysmal EEG alterations did not differ significantly between responders and nonresponders (Volk et al., 2006). The duration of SE was 4 h in all rats, because it was terminated by diazepam (10–20 mg/kg) after this period of convulsive activity. Furthermore, nonresponders did not require more diazepam than responders to terminate the SE. Recurrence of SE activity was excluded by EEG recordings following SE termination. Therefore, the finding that a comparable or equivalent brain insult results in major interindividual differences in the severity and pharmacologic responsiveness of epilepsy developing after the insult can be explained only by genetic differences between the age-matched rats of the outbred strain (Sprague-Dawley) used for our experiments.
The subgroup of six epileptic rats with extremely high seizure frequency (> 3 seizures per day) in the population of 33 epileptic animals examined in the present study differed in several aspects from all other rats. First, whereas rats of the present model are normally easy to handle without any obvious behavioral abnormalities, these six rats were hyperexcitable and aggressive, resembling epileptic rats of chemical models of TLE, such as the pilocarpine or kainate models. Second, these rats differed in their response to PB from all other rats in that PB significantly increased seizure frequency, that is, exerted a proconvulsant effect in such animals. This increase in seizure frequency was particularly due to the occurrence of nonconvulsive seizures, which were observed only rarely before treatment with PB. These observations indicate that epileptic rats with a high frequency of PB-resistant seizures represent a condition that is distinct from resistant rats with lower frequency of seizures.
Two of the six rats with frequent pharmacoresistant seizures died suddenly and unexpectedly after 6.5 and 8.5 months following the SE, which was also observed in one rat with less frequent pharmacoresistant seizures, but none of the rats with pharmacoresponsive seizures. In patients with epilepsy, uncontrolled partial or generalized convulsive seizures are a risk factor for sudden unexpected death in epilepsy (SUDEP), which is the most important direct epilepsy-related cause of death (Tomson et al., 2005; Nashef et al., 2007). The mechanisms of SUDEP are unclear but most probably involve seizure-induced changes in respiratory and cardiac function (Leung et al., 2006; Nashef et al., 2007). To our knowledge, the present data are the first evidence that sudden death also occurs in rats with pharmacoresistant spontaneous seizures.
Interestingly, in PB-resistant rats with high seizure frequency, the type of seizures changed during treatment from secondary generalized convulsive (stages 4–6) to focal (stages 1–2), which did not occur in the rest of the group. In rat models of TLE, sustained or frequent seizures have been shown to induce a locally restricted increase in the expression of the drug efflux transporter Pgp in epileptogenic brain regions, which locally decreases concentrations of AEDs that are substrates of Pgp (Löscher & Potschka, 2005; van Vliet et al., 2007). Therefore, one explanation for the present findings could be that levels of PB, which is a Pgp substrate (Löscher & Potschka, 2005), are decreased in such brain regions, so that PB does not affect focal seizures originating in these regions but still inhibits seizure generalization in brain regions adjacent to the focal areas. This, however, does not explain the proconvulsant effects of PB observed in several PB-nonresponders.
The anticonvulsant effect of PB is thought to be related primarily to enhancement of GABA-mediated inhibitory synaptic transmission via modulation of GABAA receptors (Olsen, 2002; Rogawski & Löscher, 2004). We have reported previously that the subunit expression and binding characteristics of GABAA receptors are significantly altered in PB nonresponders (Volk et al., 2006; Bethmann et al., 2008). However, whereas such alterations in the expression and function of GABAA receptors are likely involved in resistance to PB, they cannot explain the different response to PB in nonresponders with high or low seizure frequency. When we reexamined the autoradiographic and immunohistochemical data on GABAA receptors in nonresponders, no obvious differences between animals with high or low seizure frequency were observed (unpublished data). Therefore, other explanations for the proconvulsant effect of PB in epileptic rats with frequent seizures must be sought after. A likely explanation would be a shift from inhibitory to excitatory GABAA receptors, so that GABAA receptor agonists such as PB exert proconvulsant instead of anticonvulsant activity. Such a shift in GABAergic response polarity from hyperpolarizing to depolarizing has been described both in patients with TLE and animal models of TLE (Cohen et al., 2002; Staley, 2004; Pathak et al., 2007; Li et al., 2008). We currently plan to examine whether such changes may be involved in the different response to PB in nonresponders with high or low seizure frequency.
We performed all experiments in female rats, because these animals are easier to handle during long-term pharmacologic studies, and drug elimination is typically slower than in males, which is an advantage for maintenance of effective drug levels (Löscher, 2007). However, estrous cycle variations, typically 4–5 days in rats, may affect seizure incidence and possibly also drug responses. Indeed, it is well known that seizure frequency in women largely varies with the stage of estrous cycle, and steroid hormones influence neuronal excitability (Scharfman & MacLusky, 2006). However, previous experiments of our group in female rats did not indicate any marked effects of estrous cycle on seizures or drug responses in models of TLE. First, in the amygdala kindling model of TLE, the estrous cycle did not significantly affect seizure threshold or response to phenytoin (Rundfeldt et al., 1990; Wahnschaffe & Löscher, 1992). Second, although phenytoin was less effective in male than in female kindled rats, phenytoin-resistant and phenytoin-responsive animals could be selected from both genders (Ebert et al., 1994). Third, the female epileptic rats with high seizure frequency evaluated in the present and previous studies exhibited about the same number of seizures per day without any indication of estrous cycle variations (see figures of individual rats in Brandt et al., 2004, 2006). In this respect, it is important to note that hormonal changes during the estrous cycle in rats are much less pronounced than in humans, and that the most marked changes in sex hormone levels occur during a relatively short period in the early afternoon of the 4–5 day cycle (Butcher et al., 1974). For the present study, SE induction was always performed in the morning, so that it is unlikely that the differences observed between responders and nonresponders originate in a difference in excitability related to the level of sex hormones at the time of induction of SE.
In conclusion, the present study provides further evidence that our rat model of TLE bears several interesting similarities to human TLE and can be used in the search for predictors and mechanisms of pharmacoresistance. Why the same brain insult, that is, a SE of similar severity and duration, produces epilepsy with such divergent features in age-matched rats of the same strain is not clear at present, but this is most likely due to genetic differences between animals, which are known to be present in outbred strains of rats, such as Sprague-Dawley (Festing, 1993). The clarification of these genetic differences will surely enhance our understanding of how or why pharmacoresistance develops in a particular individual. Rogawski and Johnson (2008) have recently suggested that intrinsic disease severity, characterized by high frequency of seizures in the early phase of epilepsy, is a major determinant of AED refractoriness, which is substantiated by the present experimental data. However, our data also demonstrated that there is no necessary link between seizure frequency and AED resistance, because part of the PB nonresponders did not differ in seizure frequency from PB responders, indicating that disease severity alone is not sufficient to explain AED resistance. This, again, is in line with clinical findings, in that epilepsy patients starting with few seizures do not always respond to AED treatment (Schmidt & Löscher, 2009). Therefore, the current hypotheses of drug resistance should be discussed in an integrative rather than exclusive fashion, which will be critical to the development of strategies to overcome pharmacoresistance.