Faculty Bibliography

OBJECTIVE:To develop and validate a tool for individualised prediction of Sudden Unexpected Death in Epilepsy (SUDEP) risk, we re-analysed data from one cohort and three case-control studies undertaken 1980-2005. METHODS:We entered 1273 epilepsy cases (287 SUDEP, 986 controls) and 22 clinical predictor variables into a Bayesian logistic regression model. RESULTS:Cross-validated individualized model predictions were superior to baseline models developed from only average population risk or from generalised tonic-clonic seizure frequency (pairwise difference in leave-one-subject-out expected log posterior density = 35.9, SEM +/-12.5, and 22.9, SEM +/-11.0 respectively). The mean cross-validated (95% Credibility Interval) Area Under the Receiver Operating Curve was 0.71 (0.68 to 0.74) for our model versus 0.38 (0.33 to 0.42) and 0.63 (0.59 to 0.67) for the baseline average and generalised tonic-clonic seizure frequency models respectively. Model performance was weaker when applied to non-represented populations. Prognostic factors included generalized tonic-clonic and focal-onset seizure frequency, alcohol excess, younger age of epilepsy onset and family history of epilepsy. Anti-seizure medication adherence was associated with lower risk. CONCLUSIONS:Even when generalised to unseen data, model predictions are more accurate than population-based estimates of SUDEP. Our tool can enable risk-based stratification for biomarker discovery and interventional trials. With further validation in unrepresented populations it may be suitable for routine individualized clinical decision-making. Clinicians should consider assessment of multiple risk factors, and not only focus on the frequency of convulsions.

Sudden unexpected death in epilepsy is the leading category of epilepsy-related death and the underlying mechanisms are incompletely understood. Risk factors can include a recent history and high frequency of generalized tonic-clonic seizures, which can depress brain activity postictally, impairing respiration, arousal and protective reflexes. Neuropathological findings in sudden unexpected death in epilepsy cases parallel those in other epilepsy patients, with no implication of novel structures or mechanisms in seizure-related deaths. Few large studies have comprehensively reviewed whole brain examination of such patients. We evaluated 92 North American Sudden unexpected death in epilepsy Registry cases with whole brain neuropathological examination by board-certified neuropathologists blinded to the adjudicated cause of death, with an average of 16 brain regions examined per case. The 92 cases included 61 sudden unexpected death in epilepsy (40 definite, 9 definite plus, 6 probable, 6 possible) and 31 people with epilepsy controls who died from other causes. The mean age at death was 34.4 years and 65.2% (60/92) were male. The average age of death was younger for sudden unexpected death in epilepsy cases than for epilepsy controls (30.0 versus 39.6 years; P = 0.006), and there was no difference in sex distribution respectively (67.3% male versus 64.5%, P = 0.8). Among sudden unexpected death in epilepsy cases, earlier age of epilepsy onset positively correlated with a younger age at death (P = 0.0005) and negatively correlated with epilepsy duration (P = 0.001). Neuropathological findings were identified in 83.7% of the cases in our cohort. The most common findings were dentate gyrus dysgenesis (sudden unexpected death in epilepsy 50.9%, epilepsy controls 54.8%) and focal cortical dysplasia (FCD) (sudden unexpected death in epilepsy 41.8%, epilepsy controls 29.0%). The neuropathological findings in sudden unexpected death in epilepsy paralleled those in epilepsy controls, including the frequency of total neuropathological findings as well as the specific findings in the dentate gyrus, findings pertaining to neurodevelopment (e.g. FCD, heterotopias) and findings in the brainstem (e.g. medullary arcuate or olivary dysgenesis). Thus, like prior studies, we found no neuropathological findings that were more common in sudden unexpected death in epilepsy cases. Future neuropathological studies evaluating larger sudden unexpected death in epilepsy and control cohorts would benefit from inclusion of different epilepsy syndromes with detailed phenotypic information, consensus among pathologists particularly for more subjective findings where observations can be inconsistent, and molecular approaches to identify markers of sudden unexpected death in epilepsy risk or pathogenesis.

Circular RNAs (circRNAs) regulate mRNA translation by binding to microRNAs (miRNAs), and their expression is altered in diverse disorders, including cancer, cardiovascular disease, and Parkinson's disease. Here, we compare circRNA expression patterns in the temporal cortex and hippocampus of patients with pharmacoresistant mesial temporal lobe epilepsy (MTLE) and healthy controls. Nine circRNAs showed significant differential expression, including circRNA-HOMER1, which is expressed in synapses. Further, we identified miRNA binding sites within the sequences of differentially expressed (DE) circRNAs; expression levels of mRNAs correlated with changes in complementary miRNAs. Gene set enrichment analysis of mRNA targets revealed functions in heterocyclic compound binding, regulation of transcription, and signal transduction, which maintain the structure and function of hippocampal neurons. The circRNA-miRNA-mRNA interaction networks illuminate the molecular changes in MTLE, which may be pathogenic or an effect of the disease or treatments and suggests that DE circRNAs and associated miRNAs may be novel therapeutic targets.

Our understanding of mesial temporal lobe epilepsy (MTLE), one of the most common form of drug-resistant epilepsy in humans, is derived mainly from clinical, imaging, and physiological data from humans and animal models. High-throughput gene expression studies of human MTLE have the potential to uncover molecular changes underlying disease pathogenesis along with novel therapeutic targets. Using RNA- and small RNA-sequencing in parrallel, we explored differentially expressed genes in the hippocampus and cortex of MTLE patients who had undergone surgical resection and non-epileptic controls. We identified differentially expressed genes in the hippocampus of MTLE patients and differentially expressed small RNAs across both the cortex and hippocampus. We found significant enrichment for astrocytic and microglial genes among up-regulated genes, and down regulation of neuron specific genes in the hippocampus of MTLE patients. The transcriptome profile of the small RNAs reflected disease state more robustly than mRNAs, even across brain regions which show very little pathology. While mRNAs segregated predominately by brain region for MTLE and controls, small RNAs segregated by disease state. In particular, our data suggest that specific miRNAs (e.g., let-7b-3p and let-7c-3p) may be key regulators of multiple pathways related to MTLE pathology. Further, we report a strong association of other small RNA species with MTLE pathology. As such we have uncovered novel elements that may contribute to the establishment and progression of MTLE pathogenesis and that could be leveraged as therapeutic targets.

Cholinergic and GABAergic projections from the horizontal diagonal band (HDB) and medial preoptic area (MCPO) of the basal forebrain to the olfactory system are associated with odor discrimination and odor learning, as well as modulation of neural responses in olfactory structures. Whereas pharmacological and lesion studies give insights into the functional role of these modulatory inputs on a slow timescale, the response dynamics of neurons in the HDB/MCPO during olfactory behaviors have not been investigated. In this study we examined how these neurons respond during two olfactory behaviors: spontaneous investigation of odorants and odor-reward association learning. We observe rich heterogeneity in the response dynamics of individual HDB/MCPO neurons, with a substantial fraction of neurons exhibiting task-related modulation. HDB/MCPO neurons show both rapid and transient responses during bouts of odor investigation and slow, long-lasting modulation of overall response rate based on behavioral demands. Specifically, baseline rates were higher during the acquisition phase of an odor-reward association than during spontaneous investigation or the recall phase of an odor reward association. Our results suggest that modulatory projections from the HDB/MCPO are poised to influence olfactory processing on multiple timescales, from hundreds of milliseconds to minutes, and are therefore capable of rapidly setting olfactory network dynamics during odor processing and learning.

In the olfactory system, cholinergic modulation has been associated with contrast modulation and changes in receptive fields in the olfactory bulb, as well the learning of odor associations in olfactory cortex. Computational modeling and behavioral studies suggest that cholinergic modulation could improve sensory processing and learning while preventing pro-active interference when task demands are high. However, how sensory inputs and/or learning regulate incoming modulation has not yet been elucidated. We here use a computational model of the olfactory bulb, piriform cortex (PC) and horizontal limb of the diagonal band of Broca (HDB) to explore how olfactory learning could regulate cholinergic inputs to the system in a closed feedback loop. In our model, the novelty of an odor is reflected in firing rates and sparseness of cortical neurons in response to that odor and these firing rates can directly regulate learning in the system by modifying cholinergic inputs to the system. In the model, cholinergic neurons reduce their firing in response to familiar odors-reducing plasticity in the PC, but increase their firing in response to novel odor-increasing PC plasticity. Recordings from HDB neurons in awake behaving rats reflect predictions from the model by showing that a subset of neurons decrease their firing as an odor becomes familiar.

The olfactory bulb (OB) and piriform cortex receive dense cholinergic projections from the basal forebrain. Cholinergic modulation within the piriform cortex has long been proposed to serve important functions in olfactory learning and memory. We here investigate how olfactory discrimination learning is regulated by cholinergic modulation of the OB inputs to the piriform cortex. We examined rats' performance on a two-alternative choice odor discrimination task following local, bilateral blockade of cholinergic nicotinic and/or muscarinic receptors in the OB. Results demonstrate that acquisition, but not recall, of novel discrimination problems is impaired following blockade of OB cholinergic receptors, although the relative contribution of muscarinic and nicotinic receptors depends on task difficulty. Blocking muscarinic receptors impairs learning for nearly all odor sets, whereas blocking nicotinic receptors only affects performance for perceptually similar odors. This pattern of behavioral effects is consistent with predictions from a model of cholinergic modulation in the OB and piriform cortex (de Almeida et al., 2013). Model simulations suggest that muscarinic and nicotinic receptors may serve complementary roles in regulating coherence and sparseness of the OB network output, which in turn differentially regulate the strength and overlap in cortical odor representations. Overall, our results suggest that muscarinic receptor blockade results in a bona fide learning impairment that may arise because cortical neurons are activated less often. Behavioral impairment following nicotinic receptor blockade may not be due to the inability of the cortex to learn, but rather arises because the cortex is unable to resolve highly overlapping input patterns.