Author response: Early tissue damage and microstructural reorganization predict disease severity in experimental epilepsy (2017)

Article Figures and data Abstract eLife digest Introduction Results Discussion Material and methods References Decision letter Author response Article and author information Metrics Abstract Mesial temporal lobe epilepsy (mTLE) is the most common focal epilepsy in adults and is often refractory to medication. So far, resection of the epileptogenic focus represents the only curative therapy. It is unknown whether pathological processes preceding epilepsy onset are indicators of later disease severity. Using longitudinal multi-modal MRI, we monitored hippocampal injury and tissue reorganization during epileptogenesis in a mouse mTLE model. The prognostic value of MRI biomarkers was assessed by retrospective correlations with pathological hallmarks Here, we show for the first time that the extent of early hippocampal neurodegeneration and progressive microstructural changes in the dentate gyrus translate to the severity of hippocampal sclerosis and seizure burden in chronic epilepsy. Moreover, we demonstrate that structural MRI biomarkers reflect the extent of sclerosis in human hippocampi. Our findings may allow an early prognosis of disease severity in mTLE before its first clinical manifestations, thus expanding the therapeutic window. https://doi.org/10.7554/eLife.25742.001 eLife digest Roughly one percent of people in the world suffer from epilepsy, a disorder in which individuals experience seizures due to abnormal electrical activity in the brain. Seizures can vary from brief episodes of amnesia or déjà-vu to convulsions and loss of consciousness. In adults, the most common form of epilepsy is known as temporal lobe epilepsy. As the name suggests, this type of epilepsy originates in a region of the brain called the temporal lobe, usually within a structure called the hippocampus. Many patients who develop temporal lobe epilepsy will have experienced a head injury or infection earlier in life that damaged their hippocampus. However, damage to the hippocampus does not always lead to epilepsy. Moreover, many years may pass between the damage and the onset of regular seizures. While some patients find that anti-epileptic drugs can control their seizures, others experience no benefit. For these patients, the only effective treatment is to remove the damaged brain tissue. At present, there is no way of knowing which patients with a damaged hippocampus will go on to develop temporal lobe epilepsy. To identify the deciding factors, Janz, Schwaderlapp, Heining et al. treated mice with a toxin that can damage the hippocampus. After roughly two weeks most of the mice were experiencing regular seizures. Imaging the animals’ brains during this two week period revealed that mice whose hippocampi showed more severe cell death shortly after exposure to the toxin surprisingly developed a milder form of epilepsy. The same was also true for animals whose hippocampi showed signs of being extensively reorganized. Further experiments show that samples of hippocampal tissue from the brains of human patients with temporal lobe epilepsy also showed these same cellular features. The next step is to test whether these changes can be used to predict which patients with hippocampal damage will develop epilepsy later in life. Identifying at-risk individuals would allow them to be treated earlier and hopefully prevent them from developing epilepsy in the first place. https://doi.org/10.7554/eLife.25742.002 Introduction Epilepsy is a devastating disease, with a prevalence of about 1%, which makes it one of the most common neurological disorders. Of particular clinical significance is mesial temporal lobe epilepsy (mTLE), in which seizures arise from mesial temporal limbic structures, as it is the most frequent form of epilepsy in adults (40%) and particularly resistant to pharmacological treatment (Engel, 2001). Hippocampal sclerosis (HS), characterized by the loss of CA1 and CA3 pyramidal cells, gliosis and associated with granule cell dispersion (GCD), represents the most common pathological hallmark of intractable mTLE (Thom, 2014; Walker, 2015). HS can emerge secondary to an initial precipitating insult, e.g. status epilepticus (SE), head trauma, febrile seizures or limbic encephalitis (Engel, 2001). To date, resection of the lesioned, epileptogenic tissue is the only therapeutic intervention. However, not all patients remain seizure-free (Ryvlin and Kahane, 2005). In this context, non-invasive MRI techniques have become an important method to identify sclerotic tissue as a biomarker in both human patients (Gomes and Shinnar, 2011; Urbach et al., 2014) and rodent TLE models (Nehlig, 2011; Shultz et al., 2014; Sierra et al., 2015a). Up to now, this has been, however, restricted to the chronic stage of epilepsy when seizures have already emerged. A promising notion is to start medical treatment during early epileptogenesis before the first seizure arises. This stands in contrast to current anti-epileptic treatments that target clinical symptoms, namely the seizures themselves, but do not cure the underlying disease. However, progress in this direction is impeded by the impossibility to identify patients before they develop epilepsy and experience their first seizure. In mTLE patients, the period between the initial epileptogenic insult and chronic epilepsy spans many years (Lukasiuk and Becker, 2014), severely hindering the search for and validation of predictive biomarkers in human studies. Conversely, in animal models, epileptogenesis can be induced within weeks to months (Lévesque and Avoli, 2013), providing an excellent opportunity to identify putative anatomical and physiological biomarkers of epileptogenesis. Considering that multiple cellular and molecular processes accompany the progression of HS, it may be possible to image early pathological changes during epileptogenesis that may prospect the later state. So far, a few MRI biomarkers have been identified that indicate epilepsy onset or seizure susceptibility secondary to pilocarpine-induced SE (Roch et al., 2002; Choy et al., 2010), traumatic brain injury (Kharatishvili et al., 2007; Immonen et al., 2013) or prolonged febrile seizures (Choy et al., 2014). However, since distinct unilateral HS is lacking in these animal models, prognostic MRI biomarkers for the most common etiology of pharmacoresistant epilepsy have not been identified yet. To address this issue, we applied longitudinal multi-modal MRI in the intrahippocampal kainate mouse model that replicates the major features of human mTLE (i.e. the development of HS and of spontaneous recurrent seizures during epileptogenesis; Bouilleret et al., 1999; Riban et al. (2002); Heinrich et al., 2011). We monitored distinct features of the pathogenesis focusing on the hippocampus (Figure 1—figure supplement 2), which is mainly affected in pharmacoresistant mTLE (Malmgren and Thom, 2012; Cendes et al., 2014; Walker, 2015). We performed a retrospective correlation of MRI measures with structural changes identified by immunohistology, and determined the prognostic value of imaging biomarkers with respect to the severity of HS. Moreover, we applied multivariate data analysis to evaluate and compare the performance of individual biomarkers to predict also the seizure severity. Our study demonstrates for the first time that the extent of epileptogenesis-associated tissue alterations in the hippocampus directly mirrors the ensuing severity of intractable mTLE. Results Inter-individual variability of histological changes associated with mTLE Little is known about the variability of histopathological changes across kainate-injected mice; yet this information is critical to relate early imaging biomarkers to HS severity in mTLE. Therefore, we quantified the degree of histopathological features associated with HS (i.e. cell death-associated microgliosis and GCD) in all injected mice individually (Figure 1). Figure 1 with 2 supplements see all Download asset Open asset The severity of histological changes associated with HS varies in chronically epileptic mice. (A) Representative DAPI-stained sections at different levels along the rostro-caudal hippocampal axis showing the extent of GCD (arrow indicates the transition to non-dispersed regions). (B) Corresponding quantitative analysis of the GCD area along the rostro-caudal axis, and (C) the calculated mean GCD volume from all analyzed sections tested for individual kainate-injected mice (one-way ANOVA, Bonferroni’s post-test; ***p<0.001; n = 8). (D) Representative photomicrographs of NeuN (turquoise; neurons) and Iba-1 (magenta; microglia) double immunostaining (upper panel) and Fluoro-Jade B (FJB) staining in consecutive sections. Clusters of amoeboid microglia are tightly associated with FJB-stained dying neurons (arrows and asterisks). (E) Quantitative analysis of cell death-associated microglial scarring in different regions (CA1 ipsi and contra; CA3 ipsi). (F) Regression analysis for the degree of GCD and the extent of microgliosis (summed for all regions) in kainate-injected mice (n = 8; Pearson’s correlation). Kainate-injected mice (NP10, NP11, NP14, NP26, NP27, NP31, NP34) are color-coded. Scale bars in A, 1 mm; in D, 200 µm. (G) Schematic of the mouse brain adapted from Witter and Amaral, 2004. Representative EEG traces of non-epileptic mice (controls or mice displaying only single epileptic spikes, NP10) and one example of an epileptic mouse displaying both epileptic spikes and paroxysmal discharges (NP31). Horizontal scale bars (left) 50 s, (middle) 5 s, (right) 0.5 s; vertical scale bar 2 mV. (H–I) Quantitative analysis of the total GCL volume (summed for all analyzed sections) and extent of microgliosis for epileptic (dark grey) and non-epileptic mice (light grey), respectively. Student’s t-test; **p<0.01, ***p<0.001; nnon-epi = 6, nepi = 7. All values are presented as the mean ± SEM. https://doi.org/10.7554/eLife.25742.003 The extent of GCD (Figure 1A–C) and cell death-associated microgliosis (Figure 1D,E) varied substantially across kainate-injected mice (nKA = 8), but was positively correlated with each other (Figure 1F; r² = 0.69, p<0.01). In addition, intrahippocampal EEG recordings validated the presence of epileptiform activity in all kainate-injected mice (Figure 1G). However, one kainate-injected mouse (NP10) had no paroxysmal discharges, even though it exhibited single epileptic spikes, and therefore it was considered as non-epileptic. All epileptic mice showed robust GCD indicated by an increase in the total GCL volume compared to non-epileptic mice (Figure 1H; non-epi.: 415.8 ± 9.6 * 106 µm³; epi.: 1379.0 ± 164.5 * 108 µm³, p<0.01) and a high spatial extent of cell death-associated microgliosis (Figure 1I; non-epi.: 563.8 ± 493.7 µm; epi.: 6965.0 ± 811.8 µm, p<0.001). To monitor the temporal development of epileptic activity another set of mice was implanted with electrodes directly after kainate injection and recorded at different time points during 2 (n = 3) or 3 weeks (n = 5) of disease progression (Figure 1—figure supplement 1). Consistent with previous studies in the same animal model (Riban et al., 2002; Arabadzisz et al., 2005; Heinrich et al., 2011), we observed prolonged seizures during SE, followed by a period exhibiting mainly isolated epileptic spikes and low-amplitude bursts. The first high-amplitude recurrent paroxysmal episodes were recorded consistently after approximately two weeks (Figure 1—figure supplement 1H; number of epileptic discharges, 1d: 0.014 ± 0.004; 0.5w: 0.002 ± 0.002; 1w: 0.036 ± 0.019; 2w: 0.240 ± 0.065, p<0.01 vs 1w; 3w: 0.274 ± 0.070, p<0.01 vs 1w). In only two out of eight mice regular paroxysmal episodes were already evident at one week after SE. In conclusion, this shows that although the speed of disease progression varies among mice, the chronic epileptic stage is reached within the second week after SE in this animal model. Early neuronal cell death determines disease severity in chronic epilepsy Considering the inter-individual histopathological differences observed in kainate-injected mice during the chronic stage of mTLE, we investigated the extent to which high-resolution T2-weighted imaging reflects SE-induced hippocampal injury and whether observed early tissue damage and anatomical changes during epileptogenesis might predict the subsequent HS severity in chronically epileptic mice (Figure 2). Figure 2 with 1 supplement see all Download asset Open asset Initial hippocampal damage detected by T2 imaging predicts the degree of HS. (A1-6) Overview of whole-brain T2 intensity maps along the rostro-caudal axis before (pre) and at distinct time-points following kainate-induced SE (1d, 4d, 8d, 16d and 31d). (B1-6) Enlarged view of the ipsilateral hippocampus. Dashed lines denote the hippocampal fissure. Open arrows mark the GCD. (C–D, E–F) Direct comparison between T2 images and NeuN (turquoise) and Iba-1 (magenta) double-stained sections. Upper and lower panels show the septal and temporal regions of the hippocampus, respectively. Arrows indicate the transition from the dispersed to the non-dispersed GCL. (D1-3, F1-3) High-magnification confocal images corresponding to photomicrographs in D and F display the loss of neurons and accompanied microglial scarring in the CA1 region and the hilus. Principal neurons in the GCL remain intact but are highly dispersed. H, hilus; gcl, granule cell layer. Scale bars: A, 2 mm; B,E,F, 200 µm; F3, 20 µm. (G, I) Quantitative analysis of T2 changes in CA1 and the DG during epileptogenesis plotted for individual animals (left panel: controls, black, n = 5; kainate-injected mice, color-coded), and (right panel) statistically tested for the epileptic (dark grey) and non-epileptic group (light grey). Source data is provided in ‘Figure 2—source data 1'. Two-way ANOVA; Bonferroni’s post-test; *p<0.05, ***p<0.001, nnon-epi = 6, nepi = 7. Values are presented as the mean ± SEM. (H, J) Corresponding linear regression analysis of T2 intensity at distinct time points during epileptogenesis (color-coded) with region-specific histopathological changes in epileptic and non-epileptic mice (n = 13; Pearson’s correlation; corrected for multiple testing; *p<0.05, **p<0.01, ***p<0.001). https://doi.org/10.7554/eLife.25742.006 Figure 2—source data 1 Summary of T2 metrics. Quantitative values of T2 measurements are listed for individual mice (saline-injected: N12, NP13, NP17, NP28, NP29; kainate-injected: NP10, NP11, NP14, NP25, NP26, NP27, NP31, NP34) and longitudinal time points (pre, 1d, 4d, 8d, 16d, 31d following injection). https://doi.org/10.7554/eLife.25742.007 Download elife-25742-fig2-data1-v1.docx T2-weighted imaging revealed a biphasic rise in hippocampal T2 intensity, characterized by a transient increase at day 1, followed by a drop to baseline at day 4 and a subsequent increase at 8 days after SE (Figure 2A,B). The early increase of T2 intensity was observed in the dentate gyrus (DG) (Figure 2I; 1d: 10.6%) and the CA1 region (Figure 2G; 1d: 26.9%; both p<0.001), whereas in the late phase it was restricted to the DG (8d: 7.8%; 31d: 7.9%, both p<0.05). Accordingly, in chronically epileptic mice both regions showed distinct histopathological changes. Extensive death of CA1 pyramidal cells was associated with dense microglial scarring (Figure 2F,F1). Moreover, hilar interneurons (Figure 2F,F3) were also lost. Dentate granule cells, however, remained intact but dispersed broadly (Figure 2F2). Importantly, 1 day following SE, T2 intensity in the CA1 region significantly correlated with cell death-associated microgliosis (Figure 2H; r² = 0.88, p<0.001). Similarly, in the DG both early (at 1 day) and subsequent T2 hyperintensities (at 8–31 days) were related to the later degree of GCD (Figure 2J). No significant change of T2 intensity was found in the piriform cortex or the amygdala (Figure 2—figure supplement 1). The dynamics of neurodegeneration during epileptogenesis were further characterized by 1H-MR spectroscopy (Figure 3). N-acetyl aspartate (NAA), serving as a surrogate marker for neurons, and the neurotransmitters glutamate and GABA were measured to differentiate between excitatory principal neurons and inhibitory interneurons, respectively. As early as 1 day following SE, the concentrations of NAA (−45.3%), glutamate (−35.1%) and GABA (−39.4%; all p<0.001) decreased substantially (Figure 3C,E,G) which was correlated with the later extent of cell death-associated microgliosis (Figure 3D,F,H; for NAA: r² = 0.89; for glutamate: r² = 0.93; for GABA: r² = 0.77; all p<0.001). In contrast to glutamate, GABA concentrations remained correlated also at day 4 (r² = 0.74; p<0.01), but this disappeared from 8 days onward, which was accompanied by a gradual increase of GABA above control values after 31 days. Conversely, NAA and glutamate concentrations remained low during subsequent epileptogenesis correlating with microgliosis. We also found an early upregulation of lactate and a delayed rise of myoinositol (Figure 3I,K), serving as markers for micro- and astroglial activation, respectively (Nehlig, 2011). However, changes in both metabolites showed weak correlations with chronic histopathological changes (Figure 3J,L). Figure 3 Download asset Open asset Early decline of glutamate and GABA predict HS. (A) Representative horizontal and coronal T2 images illustrating the region-of-interest in the ipsilateral hippocampus (turquoise boxes) for 1H-MR-spectroscopy. N-acetyl aspartate (NAA) served as a marker for neurons. Glutamate (Glu) and gamma-aminobutyric acid (GABA) allowed to estimate the loss of excitatory and inhibitory neurons, respectively. Lactate (Lac) and myoinositol (Myoi) were used as surrogate markers for microglial and astroglial activation. (B) Representative photomicrographs of NeuN (turquoise, neurons) and Iba-1 (magenta, microglia) double-stained sections from one saline- (control) and two kainate-injected mice exhibiting different degrees of hippocampal sclerosis (NP26, moderate; NP34, strong) for qualitative comparison with the degree of metabolic alterations. Arrow, borders of the GCD; Asterisks, cell loss and microglial scarring in CA1. Scale bar in A, 2 mm; B, 200 µm. (C, E, G, I, K) Quantitative analysis of NAA, Glu, GABA, Lac and Myoi concentrations plotted for individual mice (left panel; controls, black, n = 5; kainate-injected animals color-coded) and groups (right panel; epileptic, dark grey; non-epileptic, light grey) during epileptogenesis. Source data is provided in ‘Figure 3—source data 1'. Two-way ANOVA; Bonferroni’s post-test; *p<0.05, **p<0.01, ***p<0.001; nnon-epi = 6, nepi = 7. Values are presented as the mean ± SEM. (D, F, H, J, L) Corresponding linear regression analysis of metabolite concentrations at distinct time-points during epileptogenesis (color-coded) with the extent of cell death-associated microgliosis in epileptic and non-epileptic mice (n = 13; Pearson’s correlation, corrected for multiple comparison; *p<0.05, **p<0.01, ***p<0.001). https://doi.org/10.7554/eLife.25742.009 Figure 3—source data 1 Summary of 1H-MR metrics. Quantitative values of 1H-MR spectroscopy are listed for individual mice (saline-injected: N12, NP13, NP17, NP28, NP29; kainate-injected: NP10, NP11, NP14, NP25, NP26, NP27, NP31, NP34) and longitudinal time points (pre, 1d, 4d, 8d, 16d, 31d following injection). https://doi.org/10.7554/eLife.25742.010 Download elife-25742-fig3-data1-v1.docx These results show that the magnitude of initial neurodegeneration following SE, as quantified by MR biomarkers, predicts the severity of HS in the chronic stage of epilepsy. Dynamics of microstructural alterations in the dentate gyrus during epileptogenesis SE-induced neurodegeneration is known to trigger various cellular responses, including inflammatory processes, synaptic plasticity and migration of surviving neurons and glial cells. To probe our hypothesis that these responses might entail microstructural alterations detectable by MRI, specifically diffusion-weighted imaging (DWI), we first identified the morphological changes of granule cells and radial glia cells, two major cell populations which survive in the sclerotic hippocampus (Figure 4). We used transgenic Thy1-eGFP mice, in which a subset of dentate granule cells is intrinsically labeled by eGFP, to investigate their dendritic and axonal morphology as well as the progression of GCD. Accordingly, quantitative analysis revealed a continuous increase of the GCL width at day 7, reaching significance at 14 and 21 days after SE when compared to controls (Figure 4A,B; control: 67.8 ± 2.5 µm; 14d: 132.6 ± 13.8 µm; ± µm, both p<0.001). This increase was accompanied by a of their in the molecular whereas dendritic within the GCL and more due to by GCD. significantly as early as day ± µm, ± µm, in volume only during later of epileptogenesis at 14 and 21 days after SE (Figure control: ± 14d: ± µm; ± µm, both p<0.001). Figure 4 Download asset Open asset alterations in the DG during epileptogenesis. and Representative confocal images show changes in the of the DG arrows denote the dispersion of the and morphological features of individual granule cells, respectively (left panel: and lower High-magnification of granule cell or initial dendritic granule cells. (B) of the GCL width = 7, = = = 6, = = and (D) the of initial and = = = = = = Representative confocal images of staining in the DG to the dynamics of = = = = = = of granule cell are (F) Quantitative analysis of Representative confocal images of sections (upper panel) and corresponding in the GCL hilus; gcl, granule cell molecular (H–I) Quantitative analysis of the mean and total volume of processes from radial glia cells in the GCL = = = = = = All were performed with ANOVA, to *p<0.05, **p<0.01, K) Representative sections for (turquoise) and (magenta) in controls and chronic epileptic mice following kainate respectively. Dashed lines denote the borders of the GCL. Quantitative analysis for the of in individual sections from controls and in sections from kainate-injected mice exhibiting weak and GCD (one-way ANOVA, post-test; *p<0.05, **p<0.01, ***p<0.001; number of = = 6, = Corresponding linear regression analysis for the and the area of the GCL correlation). Scale bars in A, 50 µm; in µm; in µm; in µm; in µm; in G, µm; in 200 µm. we determined the time of axonal within the by the of A few were already evident at days 4 and in the but a significant increase of was only detected at 14 and 21 days after SE (Figure control: ± 14d: ± ± p<0.001). of is it is important to that these are not their by In processes of radial glia cells are known to the GCL in a highly et al., Accordingly, we radial glia processes in to quantitative the mean volume of radial glia processes significantly as early as 4 days after SE (Figure control: ± µm³, ± µm³, p<0.001). to controls this increase was further at later time points during epileptogenesis ± 14d: ± ± all p<0.001). Moreover, the of was correlated with the of the GCL in chronically epileptic mice (Figure r² = showing that radial gliosis is tightly associated with GCD. our results demonstrate that during epileptogenesis distinct microstructural alterations emerge at different time points within the gliosis early after SE, whereas neuronal dendritic and accompany GCD at later alterations during epileptogenesis to disease progression we monitored the dynamics of microstructural alterations in in to test whether they predict the later extent of histopathological changes (Figure Figure 5 with 2 supplements see all Download asset Open asset reorganization quantified by during epileptogenesis predicts disease (A1-6) Representative coronal sections from diffusion-weighted at different time points during epileptogenesis injection = 1d, 4d, and 31d following (B1-6) Enlarged images of the ipsilateral hippocampus at different levels along the rostro-caudal The of is Representative image and a from and The in of corresponding brain regions for anatomical relate to major axonal and brain regions exhibiting highly Enlarged images the distinct of in different hippocampal pyramidal molecular gcl, granule cell denote the region of pyramidal cell Corresponding DAPI-stained sections. Scale bars in A, 2 mm; µm; µm. Quantitative analysis of radial and in the plotted for individual mice (left panel; controls, black, n = 5; kainate-injected animals color-coded) and for groups (right panel; epileptic, dark grey; non-epileptic, light grey) during epileptogenesis. Source data is provided in ‘Figure data 1'. Two-way ANOVA, Bonferroni’s ***p<0.001; nnon-epi = 6, nepi = 7. Values are presented as the mean ± SEM. Corresponding linear regression analysis of at distinct time points during epileptogenesis with the total GCL volume in epileptic and non-epileptic mice (n = 13; Pearson’s correlation, corrected for multiple comparison; *p<0.05, **p<0.01, ***p<0.001). to ‘Figure supplement for in CA1. Figure data 1 Summary of metrics. Quantitative values of measurements are listed for individual mice (saline-injected: N12, NP13, NP17, NP28, NP29; kainate-injected: NP10, NP11, NP14, NP25, NP26, NP27, NP31, NP34) and longitudinal time points (pre, 1d, 4d, 8d, 16d, 31d following injection). Download In the changes of hippocampal during epileptogenesis (Figure characterized by a robust increase of in the GCL and a in the of CA1 (Figure a of tissue was in the DG during late epileptogenesis (Figure 31d: p<0.001), but exhibited an early and transient in the CA1 region (Figure supplement 1d: p<0.05). Direct histological analysis that these changes to GCD and the loss of CA1 pyramidal cell