ECoG studies of valproate, carbamazepine and halothane in frontal-lobe epilepsy induced by head injury in the rat
Introduction
Numerous anti-epileptic drugs (AEDs) have been introduced over the last 30 years, but the proportion of patients with poor seizure control has remained stable at ∼ 30% (Duncan et al., 2006, French, 2007). In addition, no agent has been identified to cure epilepsy (Temkin, 2009). Thus, many epilepsy patients require chronic administration of AEDs, and suffer from varying side effects that negatively impact quality of life (Gilliam et al., 2004). This failure to broaden AED efficacy significantly has led to doubts about the models most commonly employed in AED development (White, 2002, White, 2003, Stables et al., 2002, Kwan and Brodie, 2003, Schmidt and Rogawski, 2002, Löscher and Schmidt, 2004). These include acute seizure models, in which anti-epileptic activity is assessed by the acute inhibition of chemically- or electrically-induced behavioral seizures in otherwise healthy non-epileptic animals, that may not capture the mechanisms most important for precipitation (and control) of acquired chronic spontaneous recurrent seizures (CSRSs) in humans. In addition, acute assays are poorly suited to detect anti-epileptic effects that develop slowly, over days-to-weeks, such as the time-dependent increase in the efficacy of valproate (VPA; Löscher and Hönack, 1995) or as might be expected with drugs targeting pro-epileptic inflammatory mechanisms (Vezzani and Granata, 2005). The use of epileptic, rather than normal, animals has been recommended to improve the performance of preclinical testing (Meldrum, 2002, White, 2002, White, 2003). Because the pace of therapy development may largely depend on the fidelity of animal models to the human condition (Sloviter, 2005), recent efforts have focused on the development of acquired CSRS models closely reproducing brain insults known to be epileptogenic in humans, and that are thus likely to recruit mechanisms of ictogenesis and epileptogenesis that are relevant to the corresponding human syndrome: stroke (Kelly et al., 2001, Kharlamov et al., 2003), head injury (D'Ambrosio et al., 2004, D'Ambrosio et al., 2005), early-life febrile seizures (Dubé et al., 2006, Oakley et al., 2009), and hypoxia–ischemia (Williams and Dudek, 2007, Klein et al., 2009). Another limitation of current approaches to AED discovery is a reliance on behavioral endpoints of seizure activity, especially clonic behavior (D'Ambrosio and Miller, 2010). In humans, not all epileptic seizures are accompanied by overt or distinctive behavioral output, such as convulsions. Human complex partial seizures (CPSs), which are characterized by an altered cognitive state, represent a much greater challenge for pharmacological treatment than other seizure types (Juul-Jensen, 1986, Mattson et al., 1996, Semah et al., 1998). CPSs often have very subtle behavioral manifestations and, depending on the location of the focus and the spread of the seizure, may be associated with normal-looking but unconscious automatic behavior, staring, memory lapses, muscle twitching, or other impairments in normal function that may go unrecognized by patients and physicians alike (Blum et al., 1996, Tatum et al., 2001). The behavioral correlate of spontaneous CPSs induced by etiologically realistic injuries in animals is similarly subtle (D'Ambrosio et al., 2009) and, thus, difficult to track accurately. Electrocorticography (ECoG), in contrast, permits a sensitive and reliable measurement of seizure frequency and duration that is independent from ictal behavioral output, and is suitable for the extended monitoring required to detect anti-epileptic effects in models with CSRSs. An approach that combines etiologically relevant models of epilepsy, ECoG monitoring, and chronic treatments is, thus, better positioned to identify more effective therapies for epilepsies now refractory to treatment. However, this combined approach is costly and fraught with technical challenges. First, the chronic nature of these models results in significant housing costs because animals must be housed for weeks to months in order to develop epilepsy and evaluate the treatment. In addition, chronic electrodes must be implanted with precision and within sturdy headsets to avoid artifactual damage to the neocortex (D'Ambrosio et al., 2009) and to minimize losses over time. Second, the chronic administration of drugs required to reliably assess slowly developing anti-epileptic activities is often complicated by metabolic autoinduction (Löscher, 2007). Thus, dosing protocols capable of maintaining stable therapeutic drug levels for the duration of the study must be developed empirically, and often are labor intensive, requiring multiple daily doses for days-to-weeks. Third, the frequency of CSRSs is typically highly variable, both among animals and over time (Arida et al., 1999, Bethmann et al., 2007, Grabenstatter et al., 2005), and a complete model of acquired epilepsy would produce pharmacoresistant subjects. These two factors increase the group sizes needed to reach statistically significant conclusions. Finally, in the absence of highly sensitive and specific seizure-detection software, the manual analysis of rat video–ECoG recordings is laborious and requires considerable expertise. Therefore, a systematic investigation of optimized study designs and data-analysis strategies is needed to identify protocols that minimize data collection, labor and costs, while maximizing the power to detect anti-epileptic effects of preclinical interest.
Here we adapt the rostral parasagittal fluid percussion injury (rpFPI) model of posttraumatic epilepsy (PTE) in the adolescent rat to the identification of anti-epileptic activity. In humans, the risk of traumatic brain injury is highest in the young (Kraus and McArthur, 2000), and rpFPI is mechanically identical to human contusive closed head injury, reproduces key histopathological and pathophysiological sequelae (Thompson et al., 2005), and reliably results, within weeks after injury, in a high incidence of PTE with frequent partial seizures that are readily detected by ECoG (D'Ambrosio et al., 2004, D'Ambrosio et al., 2005, D'Ambrosio et al., 2009). Before progressing to a dual pathology several months post-injury (D'Ambrosio et al., 2005), rpFPI-induced PTE first appears as frontal-lobe neocortical partial seizures (D'Ambrosio et al., 2004, D'Ambrosio et al., 2009) that differ from typical motor seizures currently used for AED screening but are similar to corresponding human frontal-lobe seizures from both the electrical (Williamson and Spencer, 1986, Bancaud and Talairach, 1992, D'Ambrosio et al., 2009), and behavioral standpoint (Williamson et al., 1985, Williamson and Spencer, 1986, Bancaud and Talairach, 1992, Lüders et al., 1992). Similar frontal-lobe partial seizures are also observed in the rat chronically after photothrombotic stroke (Kelly et al., 2001). In addition, rpFPI-induced epilepsy incorporates all the risk factors for pharmacoresistant epilepsy that were summarized by French (2007) for the human: epilepsy is acquired (Semah et al., 1998, Hitiris et al., 2007; Callaghan et al., 2007), it is associated with dual pathology (Semah et al., 1998), it is induced before adulthood (Berg et al., 2001), and it presents with frequent seizures (Collaborative Group for the Study of Epilepsy, 1992).Thus, rpFPI in the adolescent rat is a particularly promising model for pharmacological studies of CSRSs and seems well-suited to help identify novel classes of anti-epileptics.
To optimize the use of the model, we employed a data-driven non-parametric bootstrap strategy to examine the performance of raw and transformed ECoG-based CSRS frequency data in the detection of defined anti-epileptic effects using different experimental designs and statistical tests, under varying conditions of data variance and treatment responsiveness. Bootstrap methods are well-suited to conduct power analyses (Efron and Tibshirani, 1998) and, in contrast to parametric power analyses, they permit both comparison of the performance of different statistics, regardless of their underlying distributions, and evaluation of the impact of non-responsive subjects on statistical power. Our results provide guidelines useful in minimizing animal use and costs, and demonstrate that modest numbers of rpFPI-injured subjects provide good statistical power to detect preclinically interesting reductions in seizure frequency even in the presence of non-responders. We then employ the optimized protocol to test the sensitivity of neocortical partial seizures to chronic exposures to carbamazepine (CBZ) and valproic acid (VPA), and acute exposures to halothane. Our results demonstrate that, while halothane abolishes all CSRSs, PTE 5 weeks after rpFPI is insensitive to carbamazepine (CBZ) and controlled by valproate (VPA) in only ∼ 40% of the animals. A comparison of the PTE syndrome in VPA-induced responders vs non-responders provides support for the recent hypothesis that links pharmacoresistance to the severity of epilepsy, and suggests VPA may be more effective than CBZ on CSRSs that appear in the first weeks to months after contusive closed head injury in humans.
Section snippets
Power analyses
Monte-Carlo methods were used to estimate the power to detect specified reductions in seizure frequency using several statistics and study designs, under various experimental conditions (Fig. 1A; Table 1). ECoG-based CSRS data were used, as detailed below, to provide the best available estimate of the distribution of seizure frequencies in epileptic rpFPI rats. Experimental group sizes, the ranges of group members' pre-treatment frequencies of seizure, the magnitude of the anti-epileptic effect
Results
In accord with observations in other models of CSRSs (Arida et al., 1999, Bethmann et al., 2007, Grabenstatter et al., 2005), identically-injured rpFPI rats vary widely in baseline seizure frequency. In 45 epileptic rpFPI animals, the frequency of seizure 4 weeks post-injury spanned 3 orders of magnitude (0.014–31 events/h) with a distribution that was weighted toward lower values (Fig. 2A). Logarithmically transformed frequency data approximate the sigmoid cumulative histogram of a normal
Discussion
This study is the first effort to adapt the FPI model of PTE to ECoG-based AED testing, and it departs from most previous preclinical AED studies in several respects. First, anti-epileptic effects are evaluated on CSRSs that arise as a consequence of an etiologically realistic model injury. Second, animals are chronically exposed to AEDs. Third, seizures are sensitively detected and quantitated by chronic ECoG recording. Fourth, all detectable seizures, rather than only those that exceed an
Conclusions
ECoG monitoring and chronic epilepsy models based on etiologically realistic epileptogenic insults are expected to provide superior prediction of the anti-epileptic effects of investigational therapies, but they are costly in comparison to conventional modes of drug testing. We show that rpFPI-induced PTE can provide adequate statistical power to detect clinically meaningful anti-epileptic effects with modest numbers of experimental animals. Thus, CSRSs induced by head injury in the rat may be
Acknowledgments
This work was supported by National Institutes of Health [NS053928 to RD]. We thank Drs. Shahin Hakimian, John W. Miller and Emilio Perucca for helpful discussion and review of the manuscript.
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