Next Article in Journal
Identification and Characterization of 5-HT Receptor 1 from Scylla paramamosain: The Essential Roles of 5-HT and Its Receptor Gene during Aggressive Behavior in Crab Species
Previous Article in Journal
Transcriptome Dynamic Analysis Reveals New Candidate Genes Associated with Resistance to Fusarium Head Blight in Two Chinese Contrasting Wheat Genotypes
Previous Article in Special Issue
Na+/K+- and Mg2+-ATPases and Their Interaction with AMPA, NMDA and D2 Dopamine Receptors in an Animal Model of Febrile Seizures
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 24
Issue 4
10.3390/ijms24044223
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Clocking Epilepsies: A Chronomodulated Strategy-Based Therapy for Rhythmic Seizures

by
Sha Sun
1,2 and
Han Wang
1,2,*
1
Center for Circadian Clocks, Soochow University, Suzhou 215123, China
2
School of Biology and Basic Medical Sciences, Suzhou Medical College, Soochow University, Suzhou 215123, China
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2023, 24(4), 4223; https://doi.org/10.3390/ijms24044223
Submission received: 19 December 2022 / Revised: 8 February 2023 / Accepted: 14 February 2023 / Published: 20 February 2023
(This article belongs to the Special Issue Advances in Neurodevelopmental Disorders (NDDs) Research)
Browse Figures
Versions Notes

Abstract

Epilepsy is a neurological disorder characterized by hypersynchronous recurrent neuronal activities and seizures, as well as loss of muscular control and sometimes awareness. Clinically, seizures have been reported to display daily variations. Conversely, circadian misalignment and circadian clock gene variants contribute to epileptic pathogenesis. Elucidation of the genetic bases of epilepsy is of great importance because the genetic variability of the patients affects the efficacies of antiepileptic drugs (AEDs). For this narrative review, we compiled 661 epilepsy-related genes from the PHGKB and OMIM databases and classified them into 3 groups: driver genes, passenger genes, and undetermined genes. We discuss the potential roles of some epilepsy driver genes based on GO and KEGG analyses, the circadian rhythmicity of human and animal epilepsies, and the mutual effects between epilepsy and sleep. We review the advantages and challenges of rodents and zebrafish as animal models for epileptic studies. Finally, we posit chronomodulated strategy-based chronotherapy for rhythmic epilepsies, integrating several lines of investigation for unraveling circadian mechanisms underpinning epileptogenesis, chronopharmacokinetic and chronopharmacodynamic examinations of AEDs, as well as mathematical/computational modeling to help develop time-of-day-specific AED dosing schedules for rhythmic epilepsy patients.

1. Introduction

Epilepsy, resulting from neuronal hypersynchronous activities, is a severe neurological disorder that affects approximately 1% of the population worldwide [1]. The most disabling symptom of epilepsy is its unpredictability. The effective dosages of antiepileptic drugs (AEDs) vary among individual patients [2]; in particular, AED treatment efficacies for patients with the same epilepsy symptoms differ [3], and the prognoses among different types of epilepsy vary [4]. The unpredictability of epilepsy in individual patients may be due to genetic variation and heterogeneity [5]. Several reviews have discussed epilepsy pharmacogenomics or pharmacogenetics [6,7,8], which investigates different responses of individual patients with distinct genotypes to an AED and develops specific therapeutics for epilepsy patients based on their genotypes [8]. The effects of genes, for example, ABCB1 (ATP-binding cassette subfamily B member 1, a drug transporter) [9], on epilepsy and interactions of HLA-A (major histocompatibility complex, class I, A) with adverse AED events [10] were investigated, highlighting the critical roles of genetic variation and heterogeneity in epilepsy treatment.
Although seizures are unpredictable, they are not random events. The circadian rhythms of epilepsy have been documented in earlier studies [11,12]. Findings in diagnostics using long-term EEG (electroencephalogram) recordings [13] and self-reported measures [14] further demonstrated the circadian patterns of epilepsies [15,16,17]. Generally, there are primarily diurnal and nocturnal types of epilepsies [18]. The sleep–wake cycle is also a non-negligible factor [19]. In addition, different epileptogenic regions display daily occurrences in various temporal epilepsy syndromes [20].
Chronotherapy emphasizes that time-of-day-specific treatment is critical for maximizing therapeutic efficacies and minimizing side effects [21]. In epilepsy, differential dosing of AEDs at the circadian-modulated seizure peak is an effective means of chronotherapy [22]. Evidence has demonstrated that differentially dosing AEDs improves seizure control and prevents drug resistance [23,24]. Hence, the prediction of time-dependent drugs and prevention of potential toxicity, based on chronotherapy testing, should help improve the efficacies of AEDs. Despite well-characterized circadian patterns, little is known about circadian roles in seizures and chronotherapeutics for epilepsy.
In this review, we compiled as many as 661 epilepsy-related genes from 2 public databases, focused on 192 epileptic driver genes as a cause of epilepsy, and then divided them into 20 KEGG categories. The molecular circadian system and the circadian rhythms of different human and animal seizures are discussed. Studies that link circadian clock genes and epilepsy are then reviewed, highlighting the role of the circadian clock in epilepsy diagnosis and therapy. The development of animal models for epilepsy studies is summarized. Finally, we emphasize targeting the circadian clock and circadian clock-regulated epileptic processes as a chronomodulated strategy for epilepsy therapy. Highlighting the roles of circadian clock genes and the circadian clock in epilepsy provides novel targets for developing AEDs and effective chronotherapy for the large proportion of rhythmic epilepsy patients.

2. Epilepsy Genes

Even though state-of-the-art medical management with a number of AEDs has been well developed in recent decades, approximately 40% of epilepsy patients treated with an AED fail to reach long-term remission and instead develop drug-resistant epilepsy (DRE) with frequent seizures and increased mortality [25,26]. In a long-term study of 144 childhood-onset epilepsy patients, only 23 (16%) patients were cured after 1 year of treatment without a relapse for almost 40 years, 46 (32%) patients took an average of 8.5 years of treatment to reach terminal remission, and 28 (19%) patients followed numerous years of a remitting–relapsing course to be cured; whereas 20 (14%) patients displayed remission but failed to reach terminal remission after relapse, and 27 (19%) patients never exhibited remission and were regarded as DRE [27]. In other words, approximately one-third of epilepsy patients eventually developed drug-resistant or refractory epilepsy. Among several hypotheses postulated for unraveling the pathogenesis of DRE, the “genetic hypothesis” assumes that single-nucleotide polymorphism (SNP) variants underpin the differential susceptibility to drug resistance in epilepsy patients [28,29]. Pharmacogenetics refers to designing a specific treatment for a patient based on his/her genotype [30]. Therefore, genetic variations affect the efficacy of drugs, and genetic testing has become necessary for clinical research [31]. Studies from twins have shown that the rate of generalized epilepsy and focal epilepsy is higher in monozygotic twins than in dizygotic twins [32,33]. The first epilepsy gene, CHRNA4 (cholinergic receptor nicotinic alpha 4 subunit), one of the genes responsible for focal epilepsy, was reported in 1995 [34]. CHRNA4 belongs to the ligand-gated ion channel family [35], and its mutations cause nocturnal frontal-lobe epilepsy [36]. These studies underscore the importance of genes and genetics for epilepsy diagnosis and treatment [37].

2.1. Compilation of 661 Epilepsy-Related Genes from 2 Public Databases

Next-generation sequencing (NGS) has facilitated the advancement of human genetics and genomics over the last decade [38]. In 2014, the Epilepsy Genetics Initiative (EGI) was established to help discover novel epilepsy genes and to identify new molecular diagnoses [39]. The Public Health Genomics and Precision Health Knowledge Base (PHGKB, https://phgkb.cdc.gov/, accessed on 9 March 2021) has compiled disease genes from published studies. Approximately 526 genes associated with epilepsy have been listed in the PHGKB—for instance, SCN1A (sodium voltage-gated channel alpha subunit 1) as a drug target gene [40,41,42] and CYP2C9 (cytochrome P450 family 2 subfamily C member 9), which is involved in drug metabolism [43,44], have been examined in epilepsy studies. Furthermore, the Online Mendelian Inheritance in Man (OMIM, https://www.omim.org/, accessed on 9 March, 2021) database also catalogs epilepsy-related genes, listing 194 epileptic-associated genes. We compared epilepsy-related genes from PHGKB and OMIM and obtained a total of 661 epilepsy-related genes (overlapping genes + nonoverlapping genes of the 2 databases; Supplementary Table S1), which is comparable with previous efforts to assemble epilepsy-related genes [45,46]. Interestingly, the circadian clock pathway was enriched in GO analysis, and several circadian clock genes, such as PER2 and PER3, were regarded as epilepsy-related genes (Figure 1A, Supplementary Table S2), indicative of circadian involvement in epilepsies/seizures.

2.2. Epileptic Driver Genes, Passenger Genes, and Undetermined Genes

Through interrogating the published relevant studies, these 661 genes were then divided into 3 groups: 192 driver genes, 176 passenger genes, and 293 undetermined genes (Supplementary Table S1). A driver gene is defined as one whose mutation or loss causes seizures. In contrast, the passenger gene is defined as one that exhibits altered expression during seizures or causes neurological diseases accompanying epilepsy. We classified the remaining genes into undetermined genes, which do not yet play a clear role in epilepsy, including those involved in drug metabolism. For example, protein SZT2 (seizure threshold 2) deficiency resulted in hyperactivation of mTORC1 (mechanistic/mammalian target of rapamycin complex 1) signaling in HEK293 and HeLa cells, leading to neonatal death in mice [47], and the homozygous mutation of its gene is responsible for epilepsy in a Saudi family [48]. Therefore, we classify this gene as an epilepsy driver gene. Even though the mutations of some genes were revealed in epileptic patients, whether these genetic mutations are responsible for epilepsy is unclear. For instance, GNAO1 (G protein subunit alpha o1), whose loss-of-function (LOF) mutations are associated with epileptic encephalopathy but whose gain-of-function (GOF) and synonymous mutations are associated with patients with movement disorders that may not display epilepsy [49] or SLC7A6OS (solute carrier family 7 member 6 opposite strand), has recently been found in two unrelated progressive myoclonus epilepsy families, but its role in epilepsy is unknown [50]. Hence, the two genes are regarded as epilepsy passenger genes. Furthermore, some genes were associated with epilepsy, such as SLC22A1 (solute carrier family 22 member 1), a cation transporter gene essential for removing environmental toxins and drugs [51]. SLC22A1 was shown to contribute to altered lamotrigine (LTG) plasma concentrations during AED treatment [52], but no SLC22A1 variants have been shown to cause or affect epilepsy to date; thus, we regard it as an undetermined gene.
We then employed KOBAS (KEGG Orthology-Based Annotation System, http://kobas.cbi.pku.edu.cn/kobas3, accessed on 8 August 2022) to classify these 192 epilepsy driver genes into several clusters based on biological processes (Table 1). The top 20 ranked pathways were sorted and merged according to upper-level categories (Figure 1B). We then focus on discussing the epileptic driver genes involved in ion channels, the mTOR pathway, synaptic support proteins, and transcription regulation, as well as the effects of some epileptic genes on circadian rhythms and the sleep–wake cycle [37], as many of the same pathways are also enriched in epileptic passenger genes.

2.2.1. Ion Channel Genes

Not surprisingly, numerous nervous-system-related processes/pathways are enriched in these epilepsy driver genes, and we first focus on genes involved in the cholinergic and GABAergic synapses. As described above, CHRNA4 involved in the cholinergic synapse was the first identified epilepsy gene causing autosomal dominant nocturnal frontal-lobe epilepsy (ADFLE), which occurs mainly during NREM (non-rapid eye movement) sleep [34]. Ever since, CHRNA2 and CHRNB2, as well as an additional CHRNA4 mutation, have been reported in sleep-related FLE (frontal lobe epilepsy) [53,54,55] (Figure 1B). The 3 genes CHRNA2, CHRNA4, and CHRNB2 encode the α2, α4, and β2 subunits of the nicotinic acetylcholine receptor (nAChR), respectively, which, as members of a family of ligand-gated ion channels, form cation-selective ion channels for sodium and potassium in response to ligands such as nicotine and acetylcholine [56]. Although the 3 subunits α2, α4, and β2 are all highly expressed in the cerebral cortex of monkeys [57,58], only α2 is highly expressed in GABAergic cells of the deep layers in rodents [59,60,61]. A CHRNB2 mutation (V287M) near the extracellular end of the M2 (second transmembrane) domain of the nAChR β2 subunit likely destroys the walls of the ion channel and was revealed in a Scottish family [54], indicating that the structural integrity of ion channels/receptors is important for resisting seizures. Furthermore, GABAergic synapses have been reported to contribute to seizure regulation (Figure 1B, Table 1) [62]. As one of the first targets of epilepsy gene therapy, increasing GABA levels in the epileptogenic area elevates the threshold of neuronal excitability, which reduces seizures [63]. GAD (glutamic acid decarboxylase), the catalytic enzyme of GABA biosynthesis, has been used to enhance GABA levels [64]. GAD1 encodes a 67 KD molecular weight protein, i.e., GAD67, which produces up to 90% of the GABA in the CNS [65,66]. GAD1 mutations are associated with neurodegenerative diseases such as schizophrenia, bipolar disorder, and other movement disorders [67,68], and Gad67−/− knockout mice display neonatal death [65]. A recent study found that biallelic GAD1 mutation was associated with seizures and reduced muscle tone in six unrelated families [69]. Animal studies have also shown that GAD1 mutations result in reduced GABA synthesis and induce seizures that reduce GABA release and, in turn, cause imbalanced brain activity [70]. In addition, GABA receptors mediate the activity of downstream neurons. GABA(A) receptors possess 18 subunits, including α(1–6), β(1–3), γ(1–3), δ, ε(1–3), θ, and π, and they mediate fast inhibitory actions in the brain [71,72]. While malfunction of GABA(A) receptors (such as α1) has been shown to contribute to human epilepsy disorders [73], downregulation of synaptic GABA(A) receptors, as well as the reduced phosphorylation of the β3 subunit, was observed in lithium-pilocarpine-induced status epilepticus rats [74,75]. However, upregulation of the GABA(A) receptors has been observed in the dentate gyrus of temporal lobe epilepsy (TLE) mice [76]. Thus, GABA(A) receptors have become a therapeutic target of epilepsy.
In addition to the ligand-gated ion channels, the voltage-gated ion channels, including sodium (Na+), potassium (K+), and calcium (Ca2+) channels [77], are also involved in epilepsy. Genetic variants in SCN1A, SCN2A, and SCN1B, encoding voltage-gated sodium channels, contributed to early-onset epilepsy [78]. Missense mutations or deletion of SCN1A have been shown to lead to loss of sodium current in GABA-mediated inhibitory interneurons, resulting in Dravet syndrome (DS), which often occurs in the first year of life) [79,80]. In contrast, gain-of-function SCN2A missense mutations have recently been reported to be associated with early infantile seizures, such as developmental and epileptic encephalopathy (DEE), which usually occur as early as three months of life) [78,81]. The patient with early infantile seizures was also shown to harbor the SCN1B p.C121W mutation [82], and mice engineered to carry the SCN1B p.C121W mutation display reduced dendrites of pyramidal neurons and hyperexcitability of the specific brain region [83]. Benign familial neonatal seizures (BFNS) as another early-onset epilepsy have been revealed to be associated with loss-of-function mutations of voltage-gated potassium channel genes, including KCNQ2 (potassium voltage-gated channel subfamily Q member 2) and KCNQ3 [84]. KCNQ2 and KCNQ3 are expressed in the whole brain region, form homo- and heterotetrameric channels, and produce the M-current important for controlling membrane potentials [85]. Whereas homozygous Kcnq2−/− knockout mice die after birth due to pulmonary atelectasis, heterozygous Kcnq2+/− mice are viable and sensitive to pentylenetetrazole (PTZ) [86]. CACNA1A (Cav2.1 α1 subunit) encodes P/Q type channels, whose mutations are associated with absence seizures [87]. Thus, various mutations of ion channel genes have been shown to result in epilepsies [88].

2.2.2. Genes Involved in the mTOR Pathway

In recent years, inhibition of the mTOR pathway has become a new therapeutic strategy in epilepsy [89,90] because the mTOR pathway is associated with malformations of cortical development (MCD) coupled with intractable epilepsy [91]. DEPDC5 (DEP domain containing 5), NPRL2 (nitrogen permease regulator-like 2), and NPRL3 (nitrogen permease regulator-like 3) are 3 components of the GATOR1 (GTPase-activating protein (GAP) activity toward Rags 1) protein complex, and their loss-of-function mutations have been identified in MCD-associated epilepsies [92,93,94]. In particular, these mutations lead to the upregulation of mTORC1, thereby contributing to focal epilepsy [95].

2.2.3. Genes Encoding Synaptic Support Proteins

The synaptic vesicle cycle is also included in the top 20 KEGG pathways in our analysis (Figure 1B). We will discuss several genes, such as DNM1, STX1B, and STXBP1. DNM1 (dynamin 1) encodes a GTP-binding protein involved in synaptic vesicle fission on the presynaptic membrane [96]. Mutations in the GTPase and the middle domains of DNM1 result in impaired endocytosis of synaptic vesicles, leading to severe seizures with intellectual disability and hypotonia [97]. STX1B (syntaxin 1b) and STXBP1 (syntaxin-binding protein 1) play a role in exocytosis; specifically, STX1B mainly mediates releasing the Ca2+-dependent synaptic vesicle, whereas STXBP1 secures the correct position of syntaxin-1 [98]. STX1B mutations result in tonic–clonic seizures, absence seizures, and myoclonic seizures [99]. STX1B and STXBP1 mutations are often found in infant seizures [98].

2.2.4. Transcriptional Regulators

Several epileptic driver genes involved in transcription have also been studied. The ARX (Aristaless-related homeobox) encodes a transcription factor important for neuronal development [100], whose loss-of-function variants/mutations contribute to X-linked intellectual disability and epilepsy [101,102], while increasing the gene copy number of the other X-linked gene MECP2 (methyl-CpG binding protein 2) leads to MECP2 duplication syndrome (MDS) [103]. Up to 90% of children with MDS have been shown to have seizures during adolescence [104]. These studies suggest that transcription regulation also contributes to epileptogenesis.

2.2.5. Effects of Epileptic Genes on Circadian Rhythms and the Sleep–Wake Cycle

Several epileptic driver genes have been known to affect circadian rhythms and the sleep–wake cycle. Scn1a+/− DS mice display impaired sleep, characteristic of an extended sleep period and fragmented non-rapid eye movement (NREM) sleep [105], whereas Scn2a−/− mice result in reduced NREM sleep and increased wakefulness, accompanied by a disrupted spontaneous firing pattern in SCN and altered expression of core circadian clock genes [106]. Epileptic Kcna1−/− mice exhibit a lengthened circadian period with an extended wake period and reduced sleep time, as well as damped oscillations of core circadian clock genes such as Clock, Bmal1, and Per1 [107]. Similarly, loss of Drosophila cac (cacophony) (an ortholog of CACNA1A) also results in reduced sleep time [108]. Furthermore, MECP2 is likely regulated by the circadian clock, and its disrupted expression is expected to be responsible for sleep disorders during pathological stages [109]. Therefore, identifying these circadian-clock-related epileptic genes and further elucidating their functions should shed light on the reciprocal effects between epileptogenesis and the circadian clock, provide novel targets for drug development, and contribute to precise epilepsy treatment.

3. Circadian Rhythms in Human Epilepsies

As early as 1885, William R. Gowers observed three groups of epilepsy patients in daily patterns: diurnal, nocturnal, and diffuse [12]. Diurnal seizures occur at certain times of the day, whereas nocturnal seizures tend to occur primarily at bedtime and at night [110]. Recently, SeizureTracker (Springfield, VA, USA) and NeuroVista (Melbourne, VIC, Australia) were employed to analyze the rhythmic patterns of seizures and found that the seizure rates of approximately 80% of 1118 patients displayed daily variations [111]. The mechanisms underpinning why seizures display daily variation are not clear. A legitimate hypothesis is that the circadian clock contributes to seizure rhythmicity. However, little is known about the circadian roles in epilepsy and seizures.
The International League Against Epilepsy (ILAE) broadly categorizes seizures into focal seizures, generalized seizures, and seizures of unknown onset [112,113,114]. Focal seizures occur only in discrete brain regions limited to one hemisphere, generalized seizures involve large bilateral brain areas, even the whole brain cortex, and seizures of unknown onset do not belong to the focal or generalized categories (Figure 2) [112,114,115]. EEG recordings of generalized seizures have been revealed to be significantly more robust in the morning than in the afternoon [116]. Furthermore, focal seizures have been shown to manifest a predictable daily pattern (Table 2) [16]. Parietal lobe epilepsy (PLE) occurs primarily around the end of sleep in the morning [15,20]. Two peaks of PLE were found in Hofstra’s study of 450 times of seizures: one peaking around 05:00 to 11:00, and the other peaking around 17:00–23:00 [117]. In contrast, occipital and temporal lobe epilepsy often occurs in the afternoon [18,20,118]. Temporal lobe epilepsy has been classified into mesial (MTLE), lesional (LTLE), and neocortical temporal lobe (NTLE) epilepsy. MTLE displays two peaks, 07:00–08:00 and 16:00–17:00 [20,117,119,120], respectively, whereas LTLE peaks around 11:00, and NTLE peaks around 11:00–17:00 [117] and early morning [120]. On the other hand, interictal epileptiform discharges (IEDs), sharp waves in the EEG background between seizures, show a nocturnal predominance and often occur during NREM sleep [16,121,122]. However, recent studies have shown that the peak of nocturnal predominance in interictal epileptiform activity (IEA) was independent of the region of seizure irritability, monitored by an implantable brain stimulator (RNS® system, Neuropace, Mountain View, CA, USA) continuously for a more extended period [120,123]. Together, these studies indicated that the circadian rhythm of seizures was robust and endogenous, independent of antiseizure dosing [111,124], indicating a possible circadian role in epileptic pathogenesis.
However, relatively little is known about disrupted circadian rhythms in epilepsy patients. Analysis of the sleep–wake cycle of 20 patients with TLE and 20 patients with juvenile myoclonic epilepsy (JME) showed that JME patients tend to sleep later at night and get up later in the morning, whereas TLE patients are morning-types [19]. Twenty-four-hour EEG (electrocardiography) recording of the interictal circadian rhythm of heart rate (HR) variability revealed no nocturnal increase in heart rate variability in TLE patients, highlighting the attenuated circadian heart rate rhythm in TLE patients [125]. Furthermore, epileptic patients produced significantly elevated melatonin levels during the nighttime with an altered phase, even though they maintained melatonin secretion rhythms [126]. Hence, elucidation of the mechanisms underlying circadian roles in epileptic pathogenesis is critically important for providing novel targets for AED development and developing a novel chronomodulated strategy-based treatment for these rhythmic epilepsy patients.
Table 2. Circadian rhythms of human epilepsies.
Table 2. Circadian rhythms of human epilepsies.
SeizuresPeak in 24-h CycleSubjects No. (Seizure No.)References
TLE11:00–17:00
11:00–19:00
11:00–15:00		176 (808)
26 (90)
1 (694)		Hofstra et al. (2009) [118]
Pavlova et al. (2004) [18]
Quigg et al. (2000) [15]
LTLEMorning8 (48)Quigg et al. (1998) [127]
MTLE05:00–11:00 and 11:00–17:00
15:00
07:00–10:00 and 16:00–19:00
06:00–08:00 and 15:00–17:00
03:00 and 17:00–20:00		33 (450)
64 (774)
131 (669)
60 (694)
72 (No mention)		Hofstra et al. (2009) [117]
Quigg et al. (1998) [127]
Durazzo et al. (2008) [20]
Karafin et al. (2010) [119]
Spencer et al. (2016) [120]
NTLE11:00–17:00
03:00–07:00		33 (450)
18 (No mention)		Hofstra et al. (2009) [117]
Spencer et al. (2016) [120]
XTLEMorning26 (465)Quigg et al. (1998) [127]
FLE23:00–05:00
19:00–23:00
04:00–07:00
around 03:00		33 (450)
26 (90)
131 (669)
17 (No mention)		Hofstra et al. (2009) [117]
Pavlova et al. (2004) [18]
Durazzo et al. (2008) [20]
Spencer et al. (2016) [120]
PLE05:00–11:00 and 17:00–23:00
04:00–07:00
01:00–06:00		33 (450)
131 (669)
1 (315)		Hofstra et al. (2009) [117]
Durazzo et al. (2008) [20]
Quigg et al. (2000) [15]
OLE19:00–23:00
16:00–19:00		26 (90)
131 (669)		Pavlova et al. (2004) [18]
Durazzo et al. (2008) [20]
GEDMorning29 (No mention)Labate et al. (2007) [116]
MTLE = mesial temporal lobe epilepsy; XTLE = extratemporal lobe epilepsy; LTLE = lesional temporal lobe epilepsy; NTLE = neocortical temporal lobe epilepsy; FLE = frontal lobe epilepsy; PLE = parietal lobe epilepsy; OLE = occipital lobe epilepsy; GED = generalized epileptiform discharge.

4. The Circadian Clock

Circadian rhythms, as biological rhythms with a period of approximately 24 h, are regulated and controlled by an endogenous time-keeping mechanism, i.e., the circadian clock [128,129,130,131]. In mammals, the central clock is situated at the suprachiasmatic nuclei (SCN) of the anterior hypothalamus [132]. The mammalian SCN neurons exhibit higher activity in electrical physiology and metabolism during the daytime [133,134]. External light is received by intrinsically photosensitive retinal ganglion cells (ipRGCs) and transmitted to the SCN via the retinohypothalamic tract (RHT) [135]. The efferent from the SCN projects to the pineal gland and drives the rhythmic release of melatonin, a sleep-promoting hormone. Since light is known to inhibit melatonin synthesis, the daily oscillation of melatonin is similar in both diurnal and nocturnal animals [136,137] and helps to synchronize peripheral organs in the body [138]. Intriguingly, most organs, tissues, and cells display circadian rhythmicity, regulated by the local peripheral clock, as well as neural, hormonal, and metabolic cues from the SCN [139].
Three transcription-translation feedback loops as molecular time-keeping mechanisms are known to generate, regulate, and maintain circadian rhythms [140,141]. In the primary loop, the CLOCK: BMAL1 heterodimer as the positive limb activates the expression of target genes, including Per genes (Per1, Per2, and Per3 ) and Cry genes (Cry1 and Cry2) via binding to E-box (5′-CACGTG-3′) and E’-box (5′-CACGTT-3′) in their promoter regions [142], whereas the PER: CRY heterodimer as the negative limb interferes with the transcriptional activity of the CLOCK-BMAL1 heterodimer and turns off their expression [143]. In the second loop, Rorα/β and Rev-erbα/β are regulated by CLOCK and BMAL1 via E-box, whereas their proteins RORα/β and REV-ERBα/β activate and suppress Bmal1 by competing for binding to the RORE (retinoic-acid-related orphan receptor response element) in the Bmal1 promoter region (Figure 3). In the third loop, D-box-containing proline and acidic amino-acid-rich basic leucine zipper (PAR bZip) genes Dbp (albumin D-box-binding protein), Hlf (hepatic leukemia factor), Tef (thyrotroph embryonic factor), and E4bp4/Nfil3 (E4 promoter-binding protein 4/nuclear factor interleukin-3-regulated protein/nuclear factor, interleukin 3 regulated) are all regulated by CLOCK and BMAL1 via E-box, whereas their proteins DBP, HIF, TEF, and E4BP4/NFIL3 bind to D-box in the promoter regions of their target genes, where DBP, HIF, and TEF activate D-box-containing genes and E4BP4/NFIL3 represses them [144]. Among these three circadian-clock-controlled cis-elements-mediated transcriptional feedback loops, the E/E’-box-mediated loop plays the dominant role in the circadian clock [145]. However, the E/E’-box-mediated loop, combined with the RORE-mediated loop and the D-box-mediated loop, forms the necessary transcriptional repression and delays for oscillating approximately 24 h a day. In particular, E/E’-box, D-box, and RORE act in the morning, evening, and night, respectively [146,147]. In addition, the mechanistic/mammalian target of the rapamycin (mTOR) pathway, implicated in numerous neurological disorders, has been shown to contribute to circadian regulation [148,149] by activating circadian clock genes through the phosphorylation of the translation factor S6K1 [148,150,151]. Specifically, S6K1 phosphorylates GSK3β, which, in turn, phosphorylates CLOCK, BMAL1, and REV-ERB [152].

5. The Roles of Circadian Clock Genes in Epilepsies

Two mechanisms have been proposed to account for the effects of the circadian clock on seizures [4]: one is that canonical clock genes such as BMAL1 and CLOCK contribute directly to epilepsies, and the other is that the circadian clock acts through certain signaling pathways to exert its effect on epilepsy. Loss of the circadian PAR bZip transcription factors DBP, HIF, and TEF resulted in lethal spontaneous epileptic seizures in mice [144]. TEF was shown to regulate the expression of pyridoxal kinase involved in converting B6 vitamers into pyridoxal phosphate (PLP) [144], and downregulation of PLP is associated with the susceptibility of seizures [153]. The CLOCK protein was revealed to be significantly downregulated in the neurons of human focal epilepsy patients, and the seizure threshold was reduced in excitatory pyramidal neuron-specific Clock−/− knockout mice. Similarly, downregulation of BMAL1 was found in hippocampal sclerosis (HS) patients with HS International League Against Epilepsy (ILAE) type I and III [154], and the threshold of seizures was also reduced in Bmal1−/− knockout mice [140]. REV-ERBα was shown to be upregulated in the brain tissues of epileptic human patients and mice, while downregulation of Rev-erbα in mice reduced their seizure susceptibility, and REV-ERBα activated GABA transporters Slc6a1 (Gat1) and Slc6a11 (Gat3) through repressing E4bp4/Nfil3 to downregulate GABA signaling [155]. This study illuminates how circadian clock genes act through GABA signaling to exert their role in epilepsy. Together, these genetic studies have provided strong support for the functional links between the circadian clock and epilepsy.

6. Mutual Effects between Epilepsy and Sleep

Sleep and epilepsy are reciprocally affected. On the one hand, NREM sleep, especially NREM stage 1 (N1) and stage 2 (N2) sleep, facilitates epileptogenesis, while REM sleep inhibits it [156]. Specifically, REM sleep has the most suppressive effect during the EEG desynchronization period [157], whereas NREM sleep facilitates seizures due to the effect of the synchronous discharge of the thalamocortical network [158,159], as evidenced by the fact that 95% of seizures occur in NREM sleep [160]. An interesting study demonstrated that a small lesion in focal cortical dysplasia (FCD) type II patients is highly associated with sleep-related epilepsy [161]. Interictal epileptiform discharges (IEDs) have been used to evaluate seizure exploding [162]. Melatonin, a sleep-promoting hormone, appears to contribute to the nocturnal predominance of IEDs during sleep [163], and reduced melatonin levels with shifted phases were reported in epilepsy patients [126,164,165]. In adult patients, frontal lobe epilepsy is the archetypal sleep-related epilepsy that tends to occur during sleep, whereas juvenile myoclonic epilepsy often occurs in the morning [166]. Furthermore, sleep deprivation has been known to cause seizures in generalized epilepsies and juvenile myoclonic epilepsy [167]. Obstructive sleep apnea (OSA) has been reported to display a high prevalence in epilepsy patients, especially in drug-resistant epilepsy [168]. Conversely, increasing sleep duration by 1.6 h can reduce seizure risk by 27% in focal drug-resistant epilepsy [169].
On the other hand, epileptic activity has been shown to affect sleep continuity, which increases waking time after sleep onset, reduces REM sleep quality, and delays the first REM sleep episode in epilepsy patients [169]. Epilepsy patients often suffer from severe sleep disturbances such as excessive daytime sleepiness, sleep fragmentation, and insomnia [170]. Nocturnal seizures may lead to severe sleep fragmentation and even NREM parasomnia [171], and diurnal seizures also result in the alteration of the sleep architecture [172]. The epileptic activity also alters the sleep oscillations, likely through desynchronizing hippocampal IED and remote cortical spindles [173]. The sleep architecture of JME patients is severely altered with prolonged REM onset latency and decreased REM percentage [174]. Furthermore, most AEDs have been known to result in sleepiness, whereas some AEDs, such as levetiracetam and lamotrigine, have been shown to lead to severe insomnia [175].
Hence, sleep problems are prevalent among epilepsy patients, and reciprocal interactions between epilepsy and sleep should be underscored in epilepsy treatment. Various questionnaire-based instruments, such as the Pittsburgh Sleep Quality Index (PSQI) and the Sleep Condition Indicator, should be employed to evaluate the sleep status of patients, and possible comorbid sleep disorders also must be assessed. In particular, comorbid sleep disorders, once verified, should be treated separately. Generally, after epileptic patients are cured with drug treatment or surgeries, their sleep quality is expected to be improved with normal sleep patterns and melatonin levels [166]. Good quality of sleep helps contain seizures.

7. Animal Models for Epilepsies

Animal models have played important roles in epileptic studies, especially in genetic and molecular mechanistic investigations [176]. In addition to human and some monkey epileptic studies, rodents, primarily mice and rats, are often used, and zebrafish have been increasingly used in recent years (Figure 4). In the following, we focus on pharmacological and genetic models of mice and zebrafish for epilepsies, even though electrical or acoustic stimulation of the brain has been employed to induce rodent models of seizures/epilepsies [177], which are not reviewed here.

7.1. Pharmacological Models

Several drugs have been widely used to evoke seizures in rodents and zebrafish (Table 3). Pentylenetetrazole (PTZ) as a GABAA receptor antagonist is the early convulsant drug [178], while (D, L)-allylglycine (AG) reduces the level of GABA biosynthesis key enzyme glutamic acid decarboxylase (GAD), leading to the depletion of GABA and the accumulation of glutamate [179]. In mice, a 300 mg/kg dose of AG is sufficient to induce 100% recurrent clonic seizures, similar to 20 mM PTZ-induced seizures. Picrotoxin, a chloride-channel blocker, can result in seizures in zebrafish with a 300 μM dose [180] and in mice with a 12 mg/kg dose [181]. Seizures evoked by picrotoxin can be suppressed by methanolic extracts of Hyoscyamus niger L. in mice [181]. Kainic acid (KA) causes excitotoxicity as an agonist of glutamatergic receptors and induces dosage-dependent clonus-like convulsions in zebrafish with an intraperitoneal injection at 1–8 mg/kg [182] and seizures in rats with an intracerebral injection of 0.4–2 ug [183]. Pilocarpine as a cholinergic agonist has been used to induce temporal lobe epilepsy in mice [184] but is rarely used in zebrafish [185]. Ginkgotoxin, purified from Ginkgo biloba, is hypothesized to inhibit GABA synthesis and can induce seizure-like behavior in zebrafish larvae [186,187]. In addition, tetanus toxin (TT) induces severe neurological disease manifested by generalized muscular convulsion in rats [188]. Adult rats displayed seizures 1–2 days after ablating interneurons by TT injection into the Cornu Ammonis 3 (CA3) hippocampal region [189]. Finally, caffeine and strychnine also induce seizures in rodents. An overdose of caffeine (400 mg/kg) as a nonselective antagonist of adenosine receptors induces epilepsy by reducing the threshold of convulsive seizures [190], and a low dose of strychnine as an antagonist of cholinergic and glycinergic receptors also induces epilepsy in mice [191]. These drugs are commonly used to establish pharmacological epilepsy models in rodents and zebrafish.

7.2. Genetic Models

Next-generation sequencing technology has helped uncover many new epilepsy genes [242]. Elucidation of these epilepsy genes is of great importance for the diagnosis and treatment of epilepsy. Well-established animal models for these epilepsy genes provide an efficient way to understand human pathology. Genetic models have been generated with sophisticated genetic manipulations (Table 3). Remarkably, a mutation in SCN1A, voltage-gated sodium channel alpha subunit 1 (VGSC), causes over 80% of Dravet syndrome cases [40,243]. Several knockout rodent models have been generated for Dravet syndrome [244,245], whereas zebrafish homozygous scn1lab−/− mutants have also been used as an epilepsy model [246]. Except for α subunit, β subunit (Scn1b), type 2 (Scn2a), and type 8 (Scn8a) have also been used as genetic models for epilepsy in mice. Scn2a transgenic mice display spontaneous seizures [247]. In addition to epilepsy, Scn2a has also been implicated in other neurological disorders, including schizophrenia and autism spectrum disorder [202]. Intriguingly, one Scn8a mutation leading to hypoexcitation of cortical circuits results in convulsive seizure resistance, whereas the other Scn8a mutation leading to hyperexcitation of thalamocortical circuits causes nonconvulsive absence epilepsy [248]. The members of the KCNQ family, especially KCNQ2 and KCNQ3, encode voltage-gated potassium channels (VGKC), which are associated with epilepsy, such as benign familial neonatal seizures (BFNS) [249]. In zebrafish, kcnq2, kcnq3, and kcnq5 are expressed in early development, and inhibitors of Kv7 channels evoke convulsive behaviors in larvae from 3 dpf (days postfertilization) to 7 dpf [236]. Homozygous Kcnq2−/− and Kcnq3−/− mice also exhibit severe spontaneous generalized seizures concurrent with a disturbed M-current [205]. Moreover, Kcnj10 (potassium inwardly rectifying channel subfamily J10), expressed in glial cells, is an important causative gene for EAST (epilepsy, ataxia, sensorineural deafness, tubulopathy) syndrome [250]. In human patients, KCNJ10 missense or nonsense mutations lead to electrolyte imbalance, seizures, and deafness [251], which are recapitulated in Kcnj10−/− knockout mice [194]. In zebrafish, knocking down orthologs kcnj10a and kcnj10b leads to locomotor defects [235]. Furthermore, models for GABA-receptor-related genes also have been generated [252]. Gabra1−/− knockout mice exhibit brain dysfunction, such as anxiety and seizures, and gabra1−/− zebrafish show generalized seizures in the larval stages [233]. Zebrafish mutants for gabrg2 [212,234] and gabrb3 [239] have been established for epilepsy research. Other genetic models have been established with gene-editing tools such as CRISPR-Cas9 for numerous zebrafish epilepsy genes, including arxa, eef1a2, pnpo, and strada, some of which have been used for drug screens [228,233,234,239] (Table 3).

7.3. Circadian Rhythms of Epileptic Animal Models

These drug-induced and genetic epilepsy models are invaluable for unraveling the specific mechanisms underlying not only epileptic pathogenesis but also how the circadian clock contributes to epilepsy. Pilocarpine-induced temporal lobe epilepsy mice [184] and electrically induced post-limbic status (PLS) rats [127] were shown to display robust rhythmicity of seizures. Interestingly, transcriptome analysis of the ventral hypothalamus of pilocarpine-induced temporal lobe epilepsy mice revealed altered rhythmicity of the genes involved in oxidative phosphorylation and aerobic glycolysis [184], providing novel insights into circadian involvement in epilepsy pathogenesis. Long-term intracranial EEG monitoring with implantable devices (NeuroVista Seizure Advisory System and Summit RC + S) revealed that one human patient and seven epileptic dogs displayed robust rhythmicity of interictal epileptiform spikes (IES), and, intriguingly, thalamic deep brain stimulations (DBS) could alter IES rhythmicity in the human patient and epileptic dogs [253], indicating that the thalamocortical system is involved in regulating the circadian rhythm of epilepsy. Intriguingly, a comparison of the rhythms of chronic TLE rats evoked by chemical drugs or electrical stimuli showed that approximately 78% (7 out of 9) of these epilepsies peak in the light period when these animals sleep [254], whereas most human TLE patients peak in the afternoon, i.e., the light and wakefulness period, indicating that the robust and endogenous circadian rhythm of TLE is independent of the diurnality and nocturnality of animals. Monitoring electrical-stimulation-induced epileptic rats with hippocampal electrodes found that seizures peak at 14:05 under constant dark (DD) conditions but around 14:59 under 12–12 h light/dark (LD) conditions [255], indicating that the circadian clock likely contributes to seizures. Epileptic seizures as abnormal stimuli were shown to induce phase shifts of core body temperature (CBT) rhythms [256]. Furthermore, a comparison of the latency of evoked potentials of the dentate gyrus (DG) of electrically induced epileptic rats found that the latency was significantly reduced in the high-seizure phase (14:00 to 22:00) but not in the low-seizure phase (22:00 to 14:00) [257], indicating that limbic seizures are likely regulated by circadian excitation and inhibition of the DG in chronic epilepsy. These lines of investigation are much needed for a chronomodulated strategy-based epilepsy chronotherapy.

7.4. Advantages and Challenges of Epileptic Animal Models

Mice have played an important role in studies on the mechanisms of epilepsy because their anatomical structures and gene expression patterns are highly similar to those of humans [258,259]. In particular, the development of long-term EEG recordings allows for monitoring of seizures that are usually difficult to measure, including certain age-related spontaneous seizures, infrequent seizures, and nonconvulsive electrographic seizures [177].
However, several limitations of mouse epilepsy models are difficult to circumvent; for instance, some seizure models fail to recapitulate relevant human behaviors [260], and other genetic models result in fatal seizures [261,262]. Mice EEG recordings make long-term seizure monitoring possible, but the procedure also damages the brain due to the insertion of electrodes, and animals are socially isolated during seizure monitoring. Despite these challenges, mice still stand as excellent models for studying epilepsy.
The zebrafish has figured prominently as a model for epileptic studies in recent years, largely due to its large clutch size, transparent embryos, sophisticated genetic manipulation, and utility for high-throughput drug screens [263]. In 2005, Baraban et al. reported the PTZ-induced zebrafish epilepsy model and clearly showed clonus-like convulsion of larval zebrafish as a new powerful system for epileptic studies [228].
As discussed above, several pharmacological and genetic manipulations have successfully been employed to elicit robust seizure-like behavioral and neurophysiological phenotypes in both larval and adult zebrafish. High-throughput drug screens have been developed using zebrafish larvae [264], and a unique scoring system has been established to measure the seizures of adult zebrafish [265]. Light-sheet microscopy and in vivo calcium imaging with genetically encoded indicators allow for directly visualizing almost whole-brain neuronal activities and network connections during epilepsy [266], and pERK (phosphorylated extracellular signal-regulated kinase) [267,268] combined with the Map-Map method as effective biomarkers have been used to characterize neuronal circuits involved in zebrafish epilepsy models. However, the relatively primitive zebrafish behaviors have compromised their predictive power [269]. Zebrafish larvae are thought to be effective only for modeling early-onset epilepsy because of their simple movement and underdeveloped neural system [270], and the small size of zebrafish makes it challenging to use them to perform specific epilepsy interventions such as deep brain stimulation [271]. Nevertheless, as an effective and complementary model, zebrafish epilepsy studies have advanced rapidly [272].

8. A Chronomodulated Strategy for Epilepsy Therapy

8.1. Circadian Mechanisms Underlying Epileptogenesis

Although our understanding of the mechanisms underlying epilepsy remains limited, mounting evidence indicates circadian involvement in epilepsy pathogenesis, as numerous types of human epilepsies display robust daily rhythmicity [111]. Future efforts will aim to identify circadian biomarkers by elucidating molecular genetic mechanisms underlying how the circadian clock regulates the robust rhythmicity of these epilepsies. In doing so, the circadian clock system and possible circadian-clock-regulated epilepsy processes such as the hypothalamus–pituitary–adrenal (HPA) axis and the hypothalamus–pituitary–gonadal (HPG) axis should be investigated. The circadian clock regulates the HPA axis [273,274] and the HPG axis [275,276], which are known to contribute to epilepsy pathogenesis [277,278,279]. In some epilepsies, it would be worthwhile to investigate how the circadian clock acts through the HPA axis or the HPG axis to regulate epilepsy pathogenesis. Furthermore, it would be intriguing to determine whether the core circadian clock genes and circadian-clock-controlled epilepsy genes harbor mutations or whether the normal rhythmic expression patterns of these circadian clock genes and circadian-clock-controlled epilepsy genes are altered in individual patients. This line of investigation should provide insights into the circadian regulation of the dynamics of the pathogenesis of a particular epilepsy, which should provide cues for the time-of-day delivery of AEDs (Figure 5). It is important to investigate the mechanisms underlying why epilepsy displays robust rhythmicity. We have reanalyzed the circadian rhythms of epilepsy-related genes in TLE mice [184] and observed that the circadian rhythmicity of approximately 50 epileptic driver genes is altered in TLE mice, with some losing their rhythmicity, some gaining rhythmicity, and some maintaining rhythmicity [280]. For instance, APEH (acylaminoacyl-peptide hydrolase) was shown to be associated with valproic acid metabolism in Chinese epileptic patients [281], and its expression amplitude increased with the lengthened period in TLE mice. The specific alteration of the rhythmicity of circadian clock genes and epilepsy genes in epilepsy patients and animal models must be emphasized when developing a chronomodulated chronotherapy.

8.2. Pharmacokinetic and Pharmacodynamic Studies of AEDs

The circadian clock has been known to contribute to pharmacokinetics and pharmacodynamics [282]. Chronopharmacokinetics investigates how the circadian clock regulates drug absorption, distribution, metabolism, and excretion (ADME), each of which plays a critical role in regulating drug levels in the body [283,284]. In particular, peripheral molecular clocks in several vital organs, such as the intestine, liver, and drug target tissues, play a direct role in regulating blood drug levels. The absorption of oral drugs depends on the intestinal tract’s physiological parameters [285]. Considerable evidence has shown the importance of circadian clocks in intestinal physiology [286]. Recently, a study reported intestinal dysbiosis associated with a particular form of epilepsy and short-bowel syndrome in an epilepsy patient who was successfully treated with valproic acid (VPA) and levetiracetam (LEV) [287]. Further, intractable epilepsy in children is comorbid with intestinal bacterial dysbiosis [288]. In addition to the lipophilicity of drugs, the distribution of drugs is also determined by plasma protein characteristics and the transport capabilities of membrane channels [282]. Daily variations of the free fraction of valproic acid (VPA) are affected by the collective actions of albumin concentration, free fatty acid (FFA) levels, and valproate concentration [289], and both free and total plasma levels of carbamazepine (CBZ) exhibit diurnal fluctuations, which should be monitored to help adjust the dosing schedule to minimize its intermittent adverse effects [290]. Numerous transporters regulated by the circadian clock are critical for drug distribution [291,292]. Metabolism and excretion are affected by liver and kidney functions, respectively. Drug efficacy duration depends on the metabolizing speed regulated by the liver clock [293]. Both aerobic glycolysis and oxidative phosphorylation are altered in TLE mice [184], indicating that AED metabolism is also altered in epilepsy. Finally, the circadian clock also regulates the expression of renal epithelial sodium transporters, directly affecting drug excretion in mice [294,295].
Furthermore, chronopharmacodynamics focuses on how the circadian clock regulates the factors that affect drug efficacy [282]. The circadian clock acts through the genes encoding drug targets, transporters, and enzymes, as well as those involved in intracellular signaling pathways, to exert effects on drug efficacy [296]. Together, chronopharmacokinetic and chronopharmacodynamic studies of an AED should help develop a chronomodulated schedule for time-of-day-specific drug delivery to maximize its efficacy and minimize its toxicities/side effects (Figure 5).

8.3. Epileptic Chronotherapy

In a study with a small cohort of 17 children with nocturnal or early-morning seizures, instead of conventional administration of equal doses of AEDs in the morning and evening each day, two times the morning AED dose was delivered in the evening with the equivalent total dosage. After the 5-month differential dosing treatment, 64.7% (11/17) of patients became seizure-free, and 88.2% (15/17) experienced a ≥50% reduction in seizures [24]. AED therapy with CBZ treatment was shown to significantly reduce urinary melatonin metabolite levels of epileptic patients during 06:00–14:00 and 22:00–06:00 [126]. Further, a 5–10 mg evening melatonin delivery can effectively reduce the frequency of epileptic attacks [297]. These studies have demonstrated clear efficacies of time-of-day-specific dosing of AEDs [284,298]. Indeed, the robust rhythmicity of epilepsy/seizures allows for timing the dosing of higher levels of AEDs to be around the time when seizures peak to control seizures effectively. Chronomodulation-based chronotherapy aims at enhancing efficacy and reducing side effects through the proper timing and dosing of AEDs [298,299,300,301] (Figure 5). In addition, as numerous factors are involved, mathematical/computational modeling is also needed to help develop an optimal chronotherapy plan for a specific epilepsy (Figure 5).

9. Discussion

We interrogated 2 major disease gene databases, PHGKB and OMIM, as well as relevant published studies, compiled 661 epilepsy-related genes (Supplementary Table S1), and classified 192 as epilepsy causative/driver genes (Table 1). These epilepsy driver genes included those involved in GABAergic, cholinergic, glutamatergic, and dopaminergic synapses; mTOR signaling, MAPK signaling, and numerous metabolic pathways; and lysosomes, as well as those encoding various ligand-gated and voltage-gated ion channels and transcription factors (Figure 1B, Table 1), indicating the complex, polygenic, and heterogeneous nature of epilepsy. A great majority of these 192 driver genes were identified with the ever-increasing power of DNA/RNA sequencing technologies [45] but have yet to be investigated in animal models. A future endeavor will be to generate mouse and/or zebrafish models for these epilepsy driver genes, particularly employing CRISPR-Cas9-mediated base-editing tools to generate mutated animals that precisely model relevant human variants [302]. The animal models of these epilepsy driver genes will help elucidate their roles in epileptic pathogenesis and provide novel targets for AED development. In the latter case, zebrafish models should be employed to conduct large-scale high-throughput epileptic drug screens [269]. In addition, whether the remaining 469 passenger and undetermined genes contribute to epilepsy also needs to be genetically ascertained using animal models in the future. However, even though OMIM and PHGKB are widely accepted disease databases, we may have missed some epileptic genes that were not yet collected in the two disease databases. This list of 661 epilepsy-related genes will need to be revised and updated because some passenger or undetermined genes may have new experimental verification. The subjective classification may result in an inaccurate grouping. In addition, limited references likely result in data omission for the pharmacological and genetic animal models. Nevertheless, we have made efforts to avoid these situations.
Many types of human epilepsies display robust rhythmicity (Table 2) [20], which is also observed in some epileptic animal models [127,184,253]. Epileptic rhythmicity supports the notion of circadian involvement in epileptogenesis and provides a unique opportunity for developing a chronomodulated strategy-based epileptic chronotherapy. We postulate three lines of experiments for developing epileptic chronotherapy (Figure 4). First, to investigate circadian mechanisms underlying time-of-day-specific dynamics of rhythmic epilepsies, particularly to determine how the peak occurrences of epilepsies are regulated by the circadian clock genes and/or by the circadian-clock-controlled epileptic genes. The findings of this line of experiments are useful for developing new AEDs per se and for helping to determine time-of-day-specific timing for dosing AEDs. Second, to investigate the chronopharmacokinetics of specific AEDs, i.e., to determine how the circadian clock regulates the ADME of the AEDs. Third, to investigate the chronopharmacodynamics of specific AEDs, i.e., to determine how the circadian clock regulates the factors affecting the efficacy and toxicity of the AEDs. The findings from chronopharmacokinetic and chronopharmacodynamic studies, combined with the circadian investigation of rhythmic epilepsies, should help select time-of-day-specific timing for the AED delivery to maximize its efficacy but minimize its toxicity [298,299,300,301] (Figure 5).
The sleep–wake cycle is the most overt circadian rhythm [303] and also affects epilepsy [304]. The sleep status of epileptic patients cannot be ignored. Sleep disorders are commonly comorbid with epilepsy and should be separately diagnosed and treated, if verified, as a part of the epilepsy treatment. Sleep problems can wreak havoc on epilepsy treatment, but ensuring that patients have good-quality sleep helps contain epilepsy.
Even though sophisticated medical management with numerous AEDs has been well carried out in clinics, more than 30% of epilepsy patients cannot be cured. Unfortunately, they must live with unpredictable seizures, pains, and fears [305]. With approximately 1% of the population worldwide suffering from epilepsies [1], the enormous number of drug-resistant epilepsy (DRE) patients makes it necessary and urgent to develop effective therapeutics. Targeting the circadian clock and circadian-clock-regulated epileptic processes will shed light on novel aspects of epilepsy pathogenesis, provide novel targets for AED development, and promise to develop effective chronomodulated strategy-based chronotherapy for the large proportion of rhythmic epilepsy patients.

10. Methods

Epilepsy-related genes in PHGKB [306] and OMIM were searched for with the keyword “epilepsy and genes” and with the keyword “epilepsy” in 2022, respectively. In addition to the papers listed on PHGKB and OMIM, relevant papers in PubMed of NCBI were also searched for with the keyword “epilepsy and gene name.” If one gene had fewer than three references, all were included. Only the latest articles were included for those genes with more than three references. A total of 543 articles were cited. Those genes without a reference are still shown in Supplementary Table S1, marked with an asterisk. Two authors selected papers independently, and only English papers were selected. According to the conclusions of these relevant articles, epilepsy-related genes were classified into driver genes, passenger genes, or undetermined genes, respectively. Because this is a narrative review, no sensitivity analysis was performed. The KEGG enrichment analysis was conducted with the KOBAS database (http://kobas.cbi.pku.edu.cn/kobas3/, accessed on 8 August 2022) [307], and a Q-value less than 0.05 was selected; the top 20 ranked KEGG pathways of the 192 driver genes are shown in Supplementary Table S3. GO enrichment analysis was performed with ClueGO in Cytoscape, and those with a kappa score higher than 0.4 were selected.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms24044223/s1.

Author Contributions

H.W. and S.S.: the conceptualization and design of this study. S.S.: the investigation and methodology of this study. H.W. and S.S.: the formal analysis. H.W.: the funding acquisition and project administration of this study. S.S.: writing—original draft. H.W. and S.S.: writing—reviewing and editing the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by grants from the National Key R&D Program of China (2019YFA0802400), the National Natural Science Foundation of China (NSFC) (#31961133026, #31871187, #31030062, #81570171, and #81070455), and the Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions (#YX13400214).

Institutional Review Board Statement

Not applicable.

Acknowledgments

We wish to thank the members of the Han Wang laboratory and Manxiu Ma for their helpful discussions on the early versions of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Leonardi, M.; Ustun, T.B. The global burden of epilepsy. Epilepsia 2002, 43, 21–25. [Google Scholar] [CrossRef] [PubMed]
  2. Kwan, P.; Brodie, M.J. Effectiveness of First Antiepileptic Drug. Epilepsia 2001, 42, 1255–1260. [Google Scholar] [CrossRef] [PubMed]
  3. Schmidt, D.; Löscher, W. Drug Resistance in Epilepsy: Putative Neurobiologic and Clinical Mechanisms. Epilepsia 2005, 46, 858–877. [Google Scholar] [CrossRef] [PubMed]
  4. Semah, F.; Picot, M.C.; Adam, C.; Broglin, D.; Arzimanoglou, A.; Bazin, B.; Cavalcanti, D.; Baulac, M. Is the underlying cause of epilepsy a major prognostic factor for recurrence? Neurology 1998, 51, 1256–1262. [Google Scholar] [CrossRef] [PubMed]
  5. Vogel, F. Moderne Probleme der Humangenetik; Springer: Berlin/Heidelberg, Germany, 1959; pp. 52–125. [Google Scholar]
  6. Tate, S.K.; Sisodiya, S.M. Multidrug resistance in epilepsy: A pharmacogenomic update. Expert Opin. Pharmacother. 2007, 8, 1441–1449. [Google Scholar] [CrossRef]
  7. Ott, J. Association of genetic loci: Replication or not, that is the question. Neurology 2004, 63, 955–958. [Google Scholar] [CrossRef]
  8. Löscher, W.; Klotz, U.; Zimprich, F.; Schmidt, D. The clinical impact of pharmacogenetics on the treatment of epilepsy. Epilepsia 2009, 50, 1–23. [Google Scholar] [CrossRef]
  9. Chouchi, M.; Klaa, H.; Ben-Youssef Turki, I.; Hila, L. ABCB1 Polymorphisms and Drug-Resistant Epilepsy in a Tunisian Population. Dis. Markers 2019, 2019, 1343650. [Google Scholar] [CrossRef]
  10. Ihtisham, K.; Ramanujam, B.; Srivastava, S.; Mehra, N.K.; Kaur, G.; Khanna, N.; Jain, S.; Kumar, S.; Kaul, B.; Samudrala, R.; et al. Association of cutaneous adverse drug reactions due to antiepileptic drugs with HLA alleles in a North Indian population. Seizure 2019, 66, 99–103. [Google Scholar] [CrossRef]
  11. Langdon-Down, M.; Brain, W.R. Time of day in relation to convulsions in epilepsy. Lancet 1929, 213, 1029–1032. [Google Scholar] [CrossRef]
  12. Gowers, W.R. Epilepsy and Other Chronic Convulsive Diseases: Their Causes, Symptoms & Treatment; William Wood & Company: West Chester, PA, USA, 1885. [Google Scholar]
  13. Fisher, R.S.; Boas, W.V.E.; Blume, W.; Elger, C.; Genton, P.; Lee, P.; Engel, J., Jr. Epileptic seizures and epilepsy: Definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE). Epilepsia 2005, 46, 470–472. [Google Scholar] [CrossRef] [PubMed]
  14. Horne, J.A.; Östberg, O. A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. Int. J. Chronobiol. 1976, 4, 97–110. [Google Scholar] [PubMed]
  15. Quigg, M. Circadian rhythms: Interactions with seizures and epilepsy. Epilepsy Res. 2000, 42, 43–55. [Google Scholar] [CrossRef] [PubMed]
  16. Pavlova, M.K.; Shea, S.A.; Scheer, F.A.; Bromfield, E.B. Is there a circadian variation of epileptiform abnormalities in idiopathic generalized epilepsy? Epilepsy Behav. 2009, 16, 461–467. [Google Scholar] [CrossRef]
  17. Hofstra, W.A. The circadian rhythm and its interaction with human epilepsy: A review of literature. Sleep Med. Rev. 2009, 13, 413–420. [Google Scholar] [CrossRef]
  18. Pavlova, M.K.; Shea, S.A.; Bromfield, E.B. Day/night patterns of focal seizures. Epilepsy Behav. 2004, 5, 44–49. [Google Scholar] [CrossRef]
  19. Pung, T.; Schmitz, B. Circadian rhythm and personality profile in juvenile myoclonic epilepsy. Epilepsia 2006, 47, 111–114. [Google Scholar] [CrossRef]
  20. Durazzo, T.; Spencer, S.; Duckrow, R.; Novotny, E.; Spencer, D.; Zaveri, H. Temporal distributions of seizure occurrence from various epileptogenic regions. Neurology 2008, 70, 1265–1271. [Google Scholar] [CrossRef]
  21. Lemmer, B.; Labrecque, G. Chronopharmacology and chronotherapeutics: Definitions and concepts. Chronobiol. Int. 1987, 4, 319–329. [Google Scholar] [CrossRef]
  22. Manganaro, S.; Loddenkemper, T.; Rotenberg, A. The Need for Antiepileptic Drug Chronotherapy to Treat Selected Childhood Epilepsy Syndromes and Avert the Harmful Consequences of Drug Resistance. J. Cent. Nerv. Syst. Dis. 2017, 9, 1179573516685883. [Google Scholar] [CrossRef]
  23. Loddenkemper, T.; Vendrame, M.; Zarowski, M.; Gregas, M.; Alexopoulos, A.V.; Wyllie, E.; Kothare, S.V. Circadian patterns of pediatric seizures. Neurology 2011, 76, 145–153. [Google Scholar] [CrossRef] [PubMed]
  24. Guilhoto, L.M.; Loddenkemper, T.; Vendrame, M.; Bergin, A.; Bourgeois, B.F.; Kothare, S.V. Higher evening antiepileptic drug dose for nocturnal and early-morning seizures. Epilepsy Behav. 2011, 20, 334–337. [Google Scholar] [CrossRef] [PubMed]
  25. Kalilani, L.; Sun, X.; Pelgrims, B.; Noack-Rink, M.; Villanueva, V. The epidemiology of drug-resistant epilepsy: A systematic review and meta-analysis. Epilepsia 2018, 59, 2179–2193. [Google Scholar] [CrossRef]
  26. Kwan, P.; Brodie, M.J. Early identification of refractory epilepsy. N. Engl. J. Med. 2000, 342, 314–319. [Google Scholar] [CrossRef]
  27. Sillanpää, M.; Schmidt, D. Natural history of treated childhood-onset epilepsy: Prospective, long-term population-based study. Brain 2006, 129, 617–624. [Google Scholar] [CrossRef]
  28. Wolking, S.; Moreau, C.; McCormack, M.; Krause, R.; Krenn, M.; Berkovic, S.; Cavalleri, G.L.; Delanty, N.; Depondt, C.; Johnson, M.R.; et al. Assessing the role of rare genetic variants in drug-resistant, non-lesional focal epilepsy. Ann. Clin. Transl. Neurol. 2021, 8, 1376–1387. [Google Scholar] [CrossRef] [PubMed]
  29. Cui, L.; Tao, H.; Wang, Y.; Liu, Z.; Xu, Z.; Zhou, H.; Cai, Y.; Yao, L.; Chen, B.; Liang, W.; et al. A functional polymorphism of the microRNA-146a gene is associated with susceptibility to drug-resistant epilepsy and seizures frequency. Seizure 2015, 27, 60–65. [Google Scholar] [CrossRef] [PubMed]
  30. Balestrini, S.; Sisodiya, S.M. Pharmacogenomics in epilepsy. Neurosci. Lett. 2018, 667, 27–39. [Google Scholar] [CrossRef]
  31. Božina, N.; Sporiš, I.; Božina, T.; Klarica-Domjanović, I.; Tvrdeić, A.; Sporiš, D. Pharmacogenetics and the treatment of epilepsy: What do we know? Pharmacogenomics 2019, 20, 1093–1101. [Google Scholar] [CrossRef]
  32. Vadlamudi, L.; Milne, R.L.; Lawrence, K.; Heron, S.E.; Eckhaus, J.; Keay, D.; Connellan, M.; Torn-Broers, Y.; Howell, R.A.; Mulley, J.C.; et al. Genetics of epilepsy: The testimony of twins in the molecular era. Neurology 2014, 83, 1042–1048. [Google Scholar] [CrossRef]
  33. Berkovic, S.F.; Howell, R.A.; Hay, D.A.; Hopper, J.L. Epilepsies in twins: Genetics of the major epilepsy syndromes. Ann. Neurol. 1998, 43, 435–445. [Google Scholar] [CrossRef] [PubMed]
  34. Steinlein, O.K.; Mulley, J.C.; Propping, P.; Wallace, R.H.; Phillips, H.A.; Sutherland, G.R.; Scheffer, I.E.; Berkovic, S.F. A missense mutation in the neuronal nicotinic acetylcholine receptor alpha 4 subunit is associated with autosomal dominant nocturnal frontal lobe epilepsy. Nat. Genet. 1995, 11, 201–203. [Google Scholar] [CrossRef] [PubMed]
  35. Anand, R.; Lindstrom, J. Chromosomal localization of seven neuronal nicotinic acetylcholine receptor subunit genes in humans. Genomics 1992, 13, 962–967. [Google Scholar] [CrossRef] [PubMed]
  36. Conti, V.; Aracri, P.; Chiti, L.; Brusco, S.; Mari, F.; Marini, C.; Albanese, M.; Marchi, A.; Liguori, C.; Placidi, F.; et al. Nocturnal frontal lobe epilepsy with paroxysmal arousals due to CHRNA2 loss of function. Neurology 2015, 84, 1520–1528. [Google Scholar] [CrossRef] [PubMed]
  37. Ellis, C.A.; Petrovski, S.; Berkovic, S.F. Epilepsy genetics: Clinical impacts and biological insights. Lancet Neurol. 2020, 19, 93–100. [Google Scholar] [CrossRef] [PubMed]
  38. Dunn, P.; Albury, C.L.; Maksemous, N.; Benton, M.C.; Sutherland, H.G.; Smith, R.A.; Haupt, L.M.; Griffiths, L.R. Next Generation Sequencing Methods for Diagnosis of Epilepsy Syndromes. Front. Genet. 2018, 9, 20. [Google Scholar] [CrossRef] [PubMed]
  39. Epilepsy Genetics Initiative. The Epilepsy Genetics Initiative: Systematic reanalysis of diagnostic exomes increases yield. Epilepsia 2019, 60, 797–806. [Google Scholar] [CrossRef] [PubMed]
  40. Mei, D.; Cetica, V.; Marini, C.; Guerrini, R. Dravet syndrome as part of the clinical and genetic spectrum of sodium channel epilepsies and encephalopathies. Epilepsia 2019, 60 (Suppl. 3), S2–S7. [Google Scholar] [CrossRef]
  41. Costain, G.; Cordeiro, D.; Matviychuk, D.; Mercimek-Andrews, S. Clinical Application of Targeted Next-Generation Sequencing Panels and Whole Exome Sequencing in Childhood Epilepsy. Neuroscience 2019, 418, 291–310. [Google Scholar] [CrossRef]
  42. Heinzen, E.L.; Yoon, W.; Tate, S.K.; Sen, A.; Wood, N.W.; Sisodiya, S.M.; Goldstein, D.B. Nova2 interacts with a cis-acting polymorphism to influence the proportions of drug-responsive splice variants of SCN1A. Am. J. Hum. Genet. 2007, 80, 876–883. [Google Scholar] [CrossRef]
  43. Fricke-Galindo, I.; Jung-Cook, H.; Llerena, A.; López-López, M. Pharmacogenetics of adverse reactions to antiepileptic drugs. Neurologia 2018, 33, 165–176. [Google Scholar] [CrossRef] [PubMed]
  44. Zaccara, G.; Franciotta, D.; Perucca, E. Idiosyncratic Adverse Reactions to Antiepileptic Drugs. Epilepsia 2007, 48, 1223–1244. [Google Scholar] [CrossRef] [PubMed]
  45. Perucca, P.; Bahlo, M.; Berkovic, S.F. The Genetics of Epilepsy. Annu. Rev. Genom. Hum. Genet. 2020, 21, 205–230. [Google Scholar] [CrossRef] [PubMed]
  46. Wang, J.; Lin, Z.J.; Liu, L.; Xu, H.Q.; Shi, Y.W.; Yi, Y.H.; He, N.; Liao, W.P. Epilepsy-associated genes. Seizure 2017, 44, 11–20. [Google Scholar] [CrossRef]
  47. Peng, M.; Yin, N.; Li, M.O. SZT2 dictates GATOR control of mTORC1 signalling. Nature 2017, 543, 433–437. [Google Scholar] [CrossRef]
  48. Naseer, M.I.; Alwasiyah, M.K.; Abdulkareem, A.A.; Bajammal, R.A.; Trujillo, C.; Abu-Elmagd, M.; Jafri, M.A.; Chaudhary, A.G.; Al-Qahtani, M.H. A novel homozygous mutation in SZT2 gene in Saudi family with developmental delay, macrocephaly and epilepsy. Genes Genom. 2018, 40, 1149–1155. [Google Scholar] [CrossRef]
  49. Feng, H.; Sjögren, B.; Karaj, B.; Shaw, V.; Gezer, A.; Neubig, R.R. Movement disorder in GNAO1 encephalopathy associated with gain-of-function mutations. Neurology 2017, 89, 762–770. [Google Scholar] [CrossRef]
  50. Mazzola, L.; Oliver, K.L.; Labalme, A.; Baykan, B.; Muona, M.; Joensuu, T.H.; Courage, C.; Chatron, N.; Borsani, G.; Alix, E.; et al. Progressive Myoclonus Epilepsy Caused by a Homozygous Splicing Variant of SLC7A6OS. Ann. Neurol. 2021, 89, 402–407. [Google Scholar] [CrossRef]
  51. Jonker, J.W.; Schinkel, A.H. Pharmacological and physiological functions of the polyspecific organic cation transporters: OCT1, 2, and 3 (SLC22A1-3). J. Pharmacol. Exp. Ther. 2004, 308, 2–9. [Google Scholar] [CrossRef]
  52. Ortega-Vázquez, A.; Fricke-Galindo, I.; Dorado, P.; Jung-Cook, H.; Martínez-Juárez, I.E.; Monroy-Jaramillo, N.; Rojas-Tomé, I.S.; Peñas-Lledó, E.; Llerena, A.; López-López, M. Influence of genetic variants and antiepileptic drug co-treatment on lamotrigine plasma concentration in Mexican Mestizo patients with epilepsy. Pharm. J. 2020, 20, 845–856. [Google Scholar] [CrossRef]
  53. De Fusco, M.; Becchetti, A.; Patrignani, A.; Annesi, G.; Gambardella, A.; Quattrone, A.; Ballabio, A.; Wanke, E.; Casari, G. The nicotinic receptor beta 2 subunit is mutant in nocturnal frontal lobe epilepsy. Nat. Genet. 2000, 26, 275–276. [Google Scholar] [CrossRef] [PubMed]
  54. Phillips, H.A.; Favre, I.; Kirkpatrick, M.; Zuberi, S.M.; Goudie, D.; Heron, S.E.; Scheffer, I.E.; Sutherland, G.R.; Berkovic, S.F.; Bertrand, D.; et al. CHRNB2 is the second acetylcholine receptor subunit associated with autosomal dominant nocturnal frontal lobe epilepsy. Am. J. Hum. Genet. 2001, 68, 225–231. [Google Scholar] [CrossRef] [PubMed]
  55. Aridon, P.; Marini, C.; Di Resta, C.; Brilli, E.; De Fusco, M.; Politi, F.; Parrini, E.; Manfredi, I.; Pisano, T.; Pruna, D.; et al. Increased sensitivity of the neuronal nicotinic receptor alpha 2 subunit causes familial epilepsy with nocturnal wandering and ictal fear. Am. J. Hum. Genet. 2006, 79, 342–350. [Google Scholar] [CrossRef]
  56. Steinlein, O.K. Genetics and epilepsy. Dialogues Clin. Neurosci. 2008, 10, 29–38. [Google Scholar] [CrossRef]
  57. Quik, M.; Polonskaya, Y.; Gillespie, A.; Jakowec, M.; Lloyd, G.K.; Langston, J.W. Localization of nicotinic receptor subunit mRNAs in monkey brain by in situ hybridization. J. Comp. Neurol. 2000, 425, 58–69. [Google Scholar] [CrossRef] [PubMed]
  58. Zoli, M.; Pistillo, F.; Gotti, C. Diversity of native nicotinic receptor subtypes in mammalian brain. Neuropharmacology 2015, 96, 302–311. [Google Scholar] [CrossRef] [PubMed]
  59. Hilscher, M.M.; Leão, R.N.; Edwards, S.J.; Leão, K.E.; Kullander, K. Chrna2-Martinotti Cells Synchronize Layer 5 Type A Pyramidal Cells via Rebound Excitation. PLoS Biol. 2017, 15, e2001392. [Google Scholar] [CrossRef]
  60. Son, J.H.; Winzer-Serhan, U.H. Postnatal expression of alpha2 nicotinic acetylcholine receptor subunit mRNA in developing cortex and hippocampus. J. Chem. Neuroanat. 2006, 32, 179–190. [Google Scholar] [CrossRef]
  61. Becchetti, A.; Grandi, L.C.; Colombo, G.; Meneghini, S.; Amadeo, A. Nicotinic Receptors in Sleep-Related Hypermotor Epilepsy: Pathophysiology and Pharmacology. Brain Sci. 2020, 10, 907. [Google Scholar] [CrossRef] [PubMed]
  62. Olsen, R.W.; Avoli, M. GABA and epileptogenesis. Epilepsia 1997, 38, 399–407. [Google Scholar] [CrossRef]
  63. Riban, V.; Fitzsimons, H.L.; During, M.J. Gene therapy in epilepsy. Epilepsia 2009, 50, 24–32. [Google Scholar] [CrossRef]
  64. Gernert, M.; Thompson, K.W.; Löscher, W.; Tobin, A.J. Genetically engineered GABA-producing cells demonstrate anticonvulsant effects and long-term transgene expression when transplanted into the central piriform cortex of rats. Exp. Neurol. 2002, 176, 183–192. [Google Scholar] [CrossRef] [PubMed]
  65. Asada, H.; Kawamura, Y.; Maruyama, K.; Kume, H.; Ding, R.G.; Kanbara, N.; Kuzume, H.; Sanbo, M.; Yagi, T.; Obata, K. Cleft palate and decreased brain gamma-aminobutyric acid in mice lacking the 67-kDa isoform of glutamic acid decarboxylase. Proc. Natl. Acad. Sci. USA 1997, 94, 6496–6499. [Google Scholar] [CrossRef] [PubMed]
  66. Kaufman, D.L.; Houser, C.R.; Tobin, A.J. Two forms of the gamma-aminobutyric acid synthetic enzyme glutamate decarboxylase have distinct intraneuronal distributions and cofactor interactions. J. Neurochem. 1991, 56, 720–723. [Google Scholar] [CrossRef] [PubMed]
  67. Lynex, C.N.; Carr, I.M.; Leek, J.P.; Achuthan, R.; Mitchell, S.; Maher, E.R.; Woods, C.G.; Bonthon, D.T.; Markham, A.F. Homozygosity for a missense mutation in the 67 kDa isoform of glutamate decarboxylase in a family with autosomal recessive spastic cerebral palsy: Parallels with Stiff-Person Syndrome and other movement disorders. BMC Neurol. 2004, 4, 20. [Google Scholar] [CrossRef]
  68. Ruzicka, W.B.; Subburaju, S.; Benes, F.M. Circuit- and Diagnosis-Specific DNA Methylation Changes at γ-Aminobutyric Acid-Related Genes in Postmortem Human Hippocampus in Schizophrenia and Bipolar Disorder. JAMA Psychiatry 2015, 72, 541–551. [Google Scholar] [CrossRef]
  69. Neuray, C.; Maroofian, R.; Scala, M.; Sultan, T.; Pai, G.S.; Mojarrad, M.; Khashab, H.E.; Deholl, L.; Yue, W.; Alsaif, H.S.; et al. Early-infantile onset epilepsy and developmental delay caused by bi-allelic GAD1 variants. Brain 2020, 143, 2388–2397. [Google Scholar] [CrossRef]
  70. Wang, Y.; Zhan, L.; Zeng, W.; Li, K.; Sun, W.; Xu, Z.C.; Xu, E. Downregulation of hippocampal GABA after hypoxia-induced seizures in neonatal rats. Neurochem. Res. 2011, 36, 2409–2416. [Google Scholar] [CrossRef]
  71. Jacob, T.C.; Moss, S.J.; Jurd, R. GABA(A) receptor trafficking and its role in the dynamic modulation of neuronal inhibition. Nat. Reviews. Neurosci. 2008, 9, 331–343. [Google Scholar] [CrossRef]
  72. Sieghart, W.; Sperk, G. Subunit composition, distribution and function of GABA(A) receptor subtypes. Curr. Top. Med. Chem. 2002, 2, 795–816. [Google Scholar] [CrossRef]
  73. Cossette, P.; Liu, L.; Brisebois, K.; Dong, H.; Lortie, A.; Vanasse, M.; Saint-Hilaire, J.M.; Carmant, L.; Verner, A.; Lu, W.Y.; et al. Mutation of GABRA1 in an autosomal dominant form of juvenile myoclonic epilepsy. Nat. Genet. 2002, 31, 184–189. [Google Scholar] [CrossRef] [PubMed]
  74. Naylor, D.E.; Liu, H.; Wasterlain, C.G. Trafficking of GABA(A) receptors, loss of inhibition, and a mechanism for pharmacoresistance in status epilepticus. J. Neurosci. 2005, 25, 7724–7733. [Google Scholar] [CrossRef] [PubMed]
  75. Terunuma, M.; Xu, J.; Vithlani, M.; Sieghart, W.; Kittler, J.; Pangalos, M.; Haydon, P.G.; Coulter, D.A.; Moss, S.J. Deficits in phosphorylation of GABA(A) receptors by intimately associated protein kinase C activity underlie compromised synaptic inhibition during status epilepticus. J. Neurosci. 2008, 28, 376–384. [Google Scholar] [CrossRef] [PubMed]
  76. Bouilleret, V.; Loup, F.; Kiener, T.; Marescaux, C.; Fritschy, J.M. Early loss of interneurons and delayed subunit-specific changes in GABA(A)-receptor expression in a mouse model of mesial temporal lobe epilepsy. Hippocampus 2000, 10, 305–324. [Google Scholar] [CrossRef] [PubMed]
  77. Oyrer, J.; Maljevic, S.; Scheffer, I.E.; Berkovic, S.F.; Petrou, S.; Reid, C.A. Ion Channels in Genetic Epilepsy: From Genes and Mechanisms to Disease-Targeted Therapies. Pharmacol. Rev. 2018, 70, 142–173. [Google Scholar] [CrossRef] [PubMed]
  78. Brunklaus, A.; Du, J.; Steckler, F.; Ghanty, I.I.; Johannesen, K.M.; Fenger, C.D.; Schorge, S.; Baez-Nieto, D.; Wang, H.R.; Allen, A.; et al. Biological concepts in human sodium channel epilepsies and their relevance in clinical practice. Epilepsia 2020, 61, 387–399. [Google Scholar] [CrossRef] [PubMed]
  79. Zuberi, S.M.; Brunklaus, A.; Birch, R.; Reavey, E.; Duncan, J.; Forbes, G.H. Genotype-phenotype associations in SCN1A-related epilepsies. Neurology 2011, 76, 594–600. [Google Scholar] [CrossRef] [PubMed]
  80. Nabbout, R.; Gennaro, E.; Dalla Bernardina, B.; Dulac, O.; Madia, F.; Bertini, E.; Capovilla, G.; Chiron, C.; Cristofori, G.; Elia, M.; et al. Spectrum of SCN1A mutations in severe myoclonic epilepsy of infancy. Neurology 2003, 60, 1961–1967. [Google Scholar] [CrossRef]
  81. Begemann, A.; Acuña, M.A.; Zweier, M.; Vincent, M.; Steindl, K.; Bachmann-Gagescu, R.; Hackenberg, A.; Abela, L.; Plecko, B.; Kroell-Seger, J.; et al. Further corroboration of distinct functional features in SCN2A variants causing intellectual disability or epileptic phenotypes. Mol. Med. 2019, 25, 6. [Google Scholar] [CrossRef]
  82. Wallace, R.H.; Wang, D.W.; Singh, R.; Scheffer, I.E.; George, A.L., Jr.; Phillips, H.A.; Saar, K.; Reis, A.; Johnson, E.W.; Sutherland, G.R.; et al. Febrile seizures and generalized epilepsy associated with a mutation in the Na+-channel beta1 subunit gene SCN1B. Nat. Genet. 1998, 19, 366–370. [Google Scholar] [CrossRef]
  83. Wimmer, V.C.; Reid, C.A.; Mitchell, S.; Richards, K.L.; Scaf, B.B.; Leaw, B.T.; Hill, E.L.; Royeck, M.; Horstmann, M.T.; Cromer, B.A.; et al. Axon initial segment dysfunction in a mouse model of genetic epilepsy with febrile seizures plus. J. Clin. Investig. 2010, 120, 2661–2671. [Google Scholar] [CrossRef] [PubMed]
  84. Maljevic, S.; Lerche, H. Potassium channel genes and benign familial neonatal epilepsy. Prog. Brain Res. 2014, 213, 17–53. [Google Scholar] [CrossRef] [PubMed]
  85. Wang, H.S.; Pan, Z.; Shi, W.; Brown, B.S.; Wymore, R.S.; Cohen, I.S.; Dixon, J.E.; McKinnon, D. KCNQ2 and KCNQ3 potassium channel subunits: Molecular correlates of the M-channel. Science 1998, 282, 1890–1893. [Google Scholar] [CrossRef] [PubMed]
  86. Watanabe, H.; Nagata, E.; Kosakai, A.; Nakamura, M.; Yokoyama, M.; Tanaka, K.; Sasai, H. Disruption of the epilepsy KCNQ2 gene results in neural hyperexcitability. J. Neurochem. 2000, 75, 28–33. [Google Scholar] [CrossRef]
  87. Zamponi, G.W.; Lory, P.; Perez-Reyes, E. Role of voltage-gated calcium channels in epilepsy. Pflug. Arch. Eur. J. Physiol. 2010, 460, 395–403. [Google Scholar] [CrossRef]
  88. Sánchez-Carpintero Abad, R.; Sanmartí Vilaplana, F.X.; Serratosa Fernández, J.M. Genetic causes of epilepsy. Neurologist 2007, 13, S47–S51. [Google Scholar] [CrossRef]
  89. Citraro, R.; Leo, A.; Constanti, A.; Russo, E.; De Sarro, G. mTOR pathway inhibition as a new therapeutic strategy in epilepsy and epileptogenesis. Pharmacol. Res. 2016, 107, 333–343. [Google Scholar] [CrossRef]
  90. Hodges, S.L.; Lugo, J.N. Therapeutic role of targeting mTOR signaling and neuroinflammation in epilepsy. Epilepsy Res. 2020, 161, 106282. [Google Scholar] [CrossRef]
  91. Crino, P.B. mTOR: A pathogenic signaling pathway in developmental brain malformations. Trends Mol. Med. 2011, 17, 734–742. [Google Scholar] [CrossRef]
  92. Baulac, S.; Ishida, S.; Marsan, E.; Miquel, C.; Biraben, A.; Nguyen, D.K.; Nordli, D.; Cossette, P.; Nguyen, S.; Lambrecq, V.; et al. Familial focal epilepsy with focal cortical dysplasia due to DEPDC5 mutations. Ann. Neurol. 2015, 77, 675–683. [Google Scholar] [CrossRef]
  93. Sim, J.C.; Scerri, T.; Fanjul-Fernández, M.; Riseley, J.R.; Gillies, G.; Pope, K.; van Roozendaal, H.; Heng, J.I.; Mandelstam, S.A.; McGillivray, G.; et al. Familial cortical dysplasia caused by mutation in the mammalian target of rapamycin regulator NPRL3. Ann. Neurol. 2016, 79, 132–137. [Google Scholar] [CrossRef]
  94. Baldassari, S.; Picard, F.; Verbeek, N.E.; Van Kempen, M.; Brilstra, E.H.; Lesca, G.; Conti, V.; Guerrini, R.; Bisulli, F.; Licchetta, L.; et al. The landscape of epilepsy-related GATOR1 variants. Genet. Med. 2019, 21, 398–408. [Google Scholar] [CrossRef]
  95. Weckhuysen, S.; Marsan, E.; Lambrecq, V.; Marchal, C.; Morin-Brureau, M.; An-Gourfinkel, I.; Baulac, M.; Fohlen, M.; Kallay Zetchi, C.; Seeck, M.; et al. Involvement of GATOR complex genes in familial focal epilepsies and focal cortical dysplasia. Epilepsia 2016, 57, 994–1003. [Google Scholar] [CrossRef]
  96. Ferguson, S.M.; De Camilli, P. Dynamin, a membrane-remodelling GTPase. Nat. Rev. Mol. Cell Biol. 2012, 13, 75–88. [Google Scholar] [CrossRef]
  97. Von Spiczak, S.; Helbig, K.L.; Shinde, D.N.; Huether, R.; Pendziwiat, M.; Lourenço, C.; Nunes, M.E.; Sarco, D.P.; Kaplan, R.A.; Dlugos, D.J.; et al. DNM1 encephalopathy: A new disease of vesicle fission. Neurology 2017, 89, 385–394. [Google Scholar] [CrossRef]
  98. Cali, E.; Rocca, C.; Salpietro, V.; Houlden, H. Epileptic Phenotypes Associated with SNAREs and Related Synaptic Vesicle Exocytosis Machinery. Front. Neurol. 2021, 12, 806506. [Google Scholar] [CrossRef] [PubMed]
  99. Wolking, S.; May, P.; Mei, D.; Møller, R.S.; Balestrini, S.; Helbig, K.L.; Altuzarra, C.D.; Chatron, N.; Kaiwar, C.; Stöhr, K.; et al. Clinical spectrum of STX1B-related epileptic disorders. Neurology 2019, 92, e1238–e1249. [Google Scholar] [CrossRef]
  100. Strømme, P.; Mangelsdorf, M.E.; Shaw, M.A.; Lower, K.M.; Lewis, S.M.; Bruyere, H.; Lütcherath, V.; Gedeon, A.K.; Wallace, R.H.; Scheffer, I.E.; et al. Mutations in the human ortholog of Aristaless cause X-linked mental retardation and epilepsy. Nat. Genet. 2002, 30, 441–445. [Google Scholar] [CrossRef] [PubMed]
  101. Poeta, L.; Fusco, F.; Drongitis, D.; Shoubridge, C.; Manganelli, G.; Filosa, S.; Paciolla, M.; Courtney, M.; Collombat, P.; Lioi, M.B.; et al. A regulatory path associated with X-linked intellectual disability and epilepsy links KDM5C to the polyalanine expansions in ARX. Am. J. Hum. Genet. 2013, 92, 114–125. [Google Scholar] [CrossRef]
  102. Kato, M.; Saitoh, S.; Kamei, A.; Shiraishi, H.; Ueda, Y.; Akasaka, M.; Tohyama, J.; Akasaka, N.; Hayasaka, K. A longer polyalanine expansion mutation in the ARX gene causes early infantile epileptic encephalopathy with suppression-burst pattern (Ohtahara syndrome). Am. J. Hum. Genet. 2007, 81, 361–366. [Google Scholar] [CrossRef] [PubMed]
  103. Van Esch, H. MECP2 Duplication Syndrome. Mol. Syndromol. 2012, 2, 128–136. [Google Scholar] [CrossRef] [PubMed]
  104. Vignoli, A.; Borgatti, R.; Peron, A.; Zucca, C.; Ballarati, L.; Bonaglia, C.; Bellini, M.; Giordano, L.; Romaniello, R.; Bedeschi, M.F.; et al. Electroclinical pattern in MECP2 duplication syndrome: Eight new reported cases and review of literature. Epilepsia 2012, 53, 1146–1155. [Google Scholar] [CrossRef] [PubMed]
  105. Sanchez, R.E.A.; Bussi, I.L.; Ben-Hamo, M.; Caldart, C.S.; Catterall, W.A.; De La Iglesia, H.O. Circadian regulation of sleep in a pre-clinical model of Dravet syndrome: Dynamics of sleep stage and siesta re-entrainment. Sleep 2019, 42, zsz173. [Google Scholar] [CrossRef] [PubMed]
  106. Ma, Z.; Eaton, M.; Liu, Y.; Zhang, J.; Chen, X.; Tu, X.; Shi, Y.; Que, Z.; Wettschurack, K.; Zhang, Z.; et al. Deficiency of autism-related Scn2a gene in mice disrupts sleep patterns and circadian rhythms. Neurobiol. Dis. 2022, 168, 105690. [Google Scholar] [CrossRef]
  107. Wallace, E.; Wright, S.; Schoenike, B.; Roopra, A.; Rho, J.M.; Maganti, R.K. Altered circadian rhythms and oscillation of clock genes and sirtuin 1 in a model of sudden unexpected death in epilepsy. Epilepsia 2018, 59, 1527–1539. [Google Scholar] [CrossRef]
  108. Hidalgo, S.; Campusano, J.M.; Hodge, J.J.L. The Drosophila ortholog of the schizophrenia-associated CACNA1A and CACNA1B voltage-gated calcium channels regulate memory, sleep and circadian rhythms. Neurobiol. Dis. 2021, 155, 105394. [Google Scholar] [CrossRef]
  109. Martínez de Paz, A.; Sanchez-Mut, J.V.; Samitier-Martí, M.; Petazzi, P.; Sáez, M.; Szczesna, K.; Huertas, D.; Esteller, M.; Ausió, J. Circadian cycle-dependent MeCP2 and brain chromatin changes. PLoS ONE 2015, 10, e0123693. [Google Scholar] [CrossRef]
  110. Autret, A.; Lucas, B.; Laffont, F.; Bertrand, P.; Degiovanni, E.; De Toffol, B. Two distinct classifications of adult epilepsies: By time of seizures and by sensitivity of the interictal paroxysmal activities to sleep and waking. Electroencephalogr. Clin. Neurophysiol. 1987, 66, 211–218. [Google Scholar] [CrossRef]
  111. Karoly, P.; Goldenholz, D.; Freestone, D.; Moss, R.; Grayden, D.; Theodore, W.; Cook, M. Circadian and circaseptan rhythms in human epilepsy: A retrospective cohort study. Lancet Neurol. 2018, 17, 977–985. [Google Scholar] [CrossRef]
  112. Berg, A.T.; Berkovic, S.F.; Brodie, M.J.; Buchhalter, J.; Cross, J.H.; Van Emde Boas, W.; Engel, J.; French, J.; Glauser, T.A.; Mathern, G.W. Revised terminology and concepts for organization of seizures and epilepsies: Report of the ILAE Commission on Classification and Terminology, 2005–2009. Epilepsia 2010, 51, 676–685. [Google Scholar] [CrossRef]
  113. Mirzoev, A.; Bercovici, E.; Stewart, L.S.; Cortez, M.A.; Snead, O.C., 3rd; Desrocher, M. Circadian profiles of focal epileptic seizures: A need for reappraisal. Seizure 2012, 21, 412–416. [Google Scholar] [CrossRef] [PubMed]
  114. Scheffer, I.E.; Berkovic, S.; Capovilla, G.; Connolly, M.B.; French, J.; Guilhoto, L.; Hirsch, E.; Jain, S.; Mathern, G.W.; Moshé, S.L.; et al. ILAE classification of the epilepsies: Position paper of the ILAE Commission for Classification and Terminology. Epilepsia 2017, 58, 512–521. [Google Scholar] [CrossRef] [PubMed]
  115. Fisher, R.S.; Cross, J.H.; French, J.A.; Higurashi, N.; Hirsch, E.; Jansen, F.E.; Lagae, L.; Moshé, S.L.; Peltola, J.; Roulet Perez, E.; et al. Operational classification of seizure types by the International League Against Epilepsy: Position Paper of the ILAE Commission for Classification and Terminology. Epilepsia 2017, 58, 522–530. [Google Scholar] [CrossRef] [PubMed]
  116. Labate, A.; Ambrosio, R.; Gambardella, A.; Sturniolo, M.; Pucci, F.; Quattrone, A. Usefulness of a morning routine EEG recording in patients with juvenile myoclonic epilepsy. Epilepsy Res. 2007, 77, 17–21. [Google Scholar] [CrossRef] [PubMed]
  117. Hofstra, W.A.; Spetgens, W.P.; Leijten, F.S.; Van Rijen, P.C.; Gosselaar, P.; Van Der Palen, J.; De Weerd, A.W. Diurnal rhythms in seizures detected by intracranial electrocorticographic monitoring: An observational study. Epilepsy Behav. 2009, 14, 617–621. [Google Scholar] [CrossRef]
  118. Hofstra, W.A.; Grootemarsink, B.E.; Dieker, R.; Van Der Palen, J.; De Weerd, A.W. Temporal distribution of clinical seizures over the 24-h day: A retrospective observational study in a tertiary epilepsy clinic. Epilepsia 2009, 50, 2019–2026. [Google Scholar] [CrossRef]
  119. Karafin, M.; St Louis, E.K.; Zimmerman, M.B.; Sparks, J.D.; Granner, M.A. Bimodal ultradian seizure periodicity in human mesial temporal lobe epilepsy. Seizure 2010, 19, 347–351. [Google Scholar] [CrossRef]
  120. Spencer, D.C.; Sun, F.T.; Brown, S.N.; Jobst, B.C.; Fountain, N.B.; Wong, V.S.; Mirro, E.A.; Quigg, M. Circadian and ultradian patterns of epileptiform discharges differ by seizure-onset location during long-term ambulatory intracranial monitoring. Epilepsia 2016, 57, 1495–1502. [Google Scholar] [CrossRef]
  121. Daley, J.T.; DeWolfe, J.L. Sleep, Circadian Rhythms, and Epilepsy. Curr. Treat. Options Neurol. 2018, 20, 47. [Google Scholar] [CrossRef]
  122. Leguia, M.G.; Andrzejak, R.G.; Rummel, C.; Fan, J.M.; Mirro, E.A.; Tcheng, T.K.; Rao, V.R.; Baud, M.O. Seizure Cycles in Focal Epilepsy. JAMA Neurol. 2021, 78, 454–463. [Google Scholar] [CrossRef]
  123. Baud, M.O.; Kleen, J.K.; Mirro, E.A.; Andrechak, J.C.; King-Stephens, D.; Chang, E.F.; Rao, V.R. Multi-day rhythms modulate seizure risk in epilepsy. Nat. Commun. 2018, 9, 88. [Google Scholar] [CrossRef] [PubMed]
  124. Gregg, N.M.; Nasseri, M.; Kremen, V.; Patterson, E.E.; Sturges, B.K.; Denison, T.J.; Brinkmann, B.H.; Worrell, G.A. Circadian and multiday seizure periodicities, and seizure clusters in canine epilepsy. Brain Commun. 2020, 2, fcaa008. [Google Scholar] [CrossRef] [PubMed]
  125. Ronkainen, E.; Ansakorpi, H.; Huikuri, H.V.; Myllylä, V.V.; Isojärvi, J.I.; Korpelainen, J.T. Suppressed circadian heart rate dynamics in temporal lobe epilepsy. J. Neurol. Neurosurg. Psychiatry 2005, 76, 1382–1386. [Google Scholar] [CrossRef] [PubMed]
  126. Schapel, G.J.; Beran, R.G.; Kennaway, D.L.; McLoughney, J.; Matthews, C.D. Melatonin response in active epilepsy. Epilepsia 1995, 36, 75–78. [Google Scholar] [CrossRef] [PubMed]
  127. Quigg, M.; Straume, M.; Menaker, M.; Bertram, E.H., 3rd. Temporal distribution of partial seizures: Comparison of an animal model with human partial epilepsy. Ann. Neurol. 1998, 43, 748–755. [Google Scholar] [CrossRef]
  128. Crnko, S.; Du Pré, B.C.; Sluijter, J.P.G.; Van Laake, L.W. Circadian rhythms and the molecular clock in cardiovascular biology and disease. Nat. Rev. Cardiol. 2019, 16, 437–447. [Google Scholar] [CrossRef]
  129. Wang, H. Perfect timing: A Nobel Prize in Physiology or Medicine for circadian clocks. Sci. Bull. 2018, 63, 398–401. [Google Scholar] [CrossRef]
  130. Fagiani, F.; Di Marino, D.; Romagnoli, A.; Travelli, C.; Voltan, D.; Di Cesare Mannelli, L.; Racchi, M.; Govoni, S.; Lanni, C. Molecular regulations of circadian rhythm and implications for physiology and diseases. Signal Transduct. Target. Ther. 2022, 7, 41. [Google Scholar] [CrossRef]
  131. Lee, Y.; Field, J.M.; Sehgal, A. Circadian Rhythms, Disease and Chronotherapy. J. Biol. Rhythm. 2021, 36, 503–531. [Google Scholar] [CrossRef]
  132. Buijs, F.N.; León-Mercado, L.; Guzmán-Ruiz, M.; Guerrero-Vargas, N.N.; Romo-Nava, F.; Buijs, R.M. The Circadian System: A Regulatory Feedback Network of Periphery and Brain. Physiology 2016, 31, 170–181. [Google Scholar] [CrossRef]
  133. Shin-ichi, T.I.; Kawamura, H. Characteristics of a circadian pacemaker in the suprachiasmatic nucleus. J. Comp. Physiol. 1982, 146, 153–160. [Google Scholar]
  134. Schwartz, W.J.; Reppert, S.M.; Eagan, S.M.; Moore-Ede, M.C. In vivo metabolic activity of the suprachiasmatic nuclei: A comparative study. Brain Res. 1983, 274, 184–187. [Google Scholar] [CrossRef] [PubMed]
  135. Lucas, R.J.; Peirson, S.N.; Berson, D.M.; Brown, T.M.; Cooper, H.M.; Czeisler, C.A.; Figueiro, M.G.; Gamlin, P.D.; Lockley, S.W.; O’Hagan, J.B.; et al. Measuring and using light in the melanopsin age. Trends Neurosci. 2014, 37, 1–9. [Google Scholar] [CrossRef] [PubMed]
  136. Bilu, C.; Kronfeld-Schor, N. Effects of circadian phase and melatonin injection on anxiety-like behavior in nocturnal and diurnal rodents. Chronobiol. Int. 2013, 30, 828–836. [Google Scholar] [CrossRef]
  137. Vivanco, P.; Ortiz, V.; Rol, M.A.; Madrid, J.A. Looking for the keys to diurnality downstream from the circadian clock: Role of melatonin in a dual-phasing rodent, Octodon degus. J. Pineal Res. 2007, 42, 280–290. [Google Scholar] [CrossRef]
  138. Partch, C.L.; Green, C.B.; Takahashi, J.S. Molecular architecture of the mammalian circadian clock. Trends Cell Biol. 2014, 24, 90–99. [Google Scholar] [CrossRef]
  139. Brown, S.A.; Azzi, A. Peripheral circadian oscillators in mammals. Handb. Exp. Pharmacol. 2013, 217, 45–66. [Google Scholar] [CrossRef]
  140. Gerstner, J.R.; Smith, G.G.; Lenz, O.; Perron, I.J.; Buono, R.J.; Ferraro, T.N. BMAL1 controls the diurnal rhythm and set point for electrical seizure threshold in mice. Front. Syst. Neurosci. 2014, 8, 121. [Google Scholar] [CrossRef]
  141. Li, P.; Fu, X.; Smith, N.A.; Ziobro, J.; Curiel, J.; Tenga, M.J.; Martin, B.; Freedman, S.; Cea-Del Rio, C.A.; Oboti, L.; et al. Loss of CLOCK Results in Dysfunction of Brain Circuits Underlying Focal Epilepsy. Neuron 2017, 96, 387–401. [Google Scholar] [CrossRef]
  142. Gekakis, N.; Staknis, D.; Nguyen, H.B.; Davis, F.C.; Wilsbacher, L.D.; King, D.P.; Takahashi, J.S.; Weitz, C.J. Role of the CLOCK protein in the mammalian circadian mechanism. Science 1998, 280, 1564–1569. [Google Scholar] [CrossRef]
  143. Sato, T.K.; Yamada, R.G.; Ukai, H.; Baggs, J.E.; Miraglia, L.J.; Kobayashi, T.J.; Welsh, D.K.; Kay, S.A.; Ueda, H.R.; Hogenesch, J.B. Feedback repression is required for mammalian circadian clock function. Nat. Genet. 2006, 38, 312–319. [Google Scholar] [CrossRef] [PubMed]
  144. Gachon, F.; Fonjallaz, P.; Damiola, F.; Gos, P.; Kodama, T.; Zakany, J.; Duboule, D.; Petit, B.; Tafti, M.; Schibler, U. The loss of circadian PAR bZip transcription factors results in epilepsy. Genes Dev. 2004, 18, 1397–1412. [Google Scholar] [CrossRef] [PubMed]
  145. Ueda, H.R.; Hayashi, S.; Chen, W.; Sano, M.; Machida, M.; Shigeyoshi, Y.; Iino, M.; Hashimoto, S. System-level identification of transcriptional circuits underlying mammalian circadian clocks. Nat. Genet. 2005, 37, 187–192. [Google Scholar] [CrossRef] [PubMed]
  146. Ukai-Tadenuma, M.; Yamada, R.G.; Xu, H.; Ripperger, J.A.; Liu, A.C.; Ueda, H.R. Delay in feedback repression by cryptochrome 1 is required for circadian clock function. Cell 2011, 144, 268–281. [Google Scholar] [CrossRef]
  147. Minami, Y.; Ode, K.L.; Ueda, H.R. Mammalian circadian clock: The roles of transcriptional repression and delay. Handb. Exp. Pharmacol. 2013, 217, 359–377. [Google Scholar] [CrossRef]
  148. Lipton, J.O.; Yuan, E.D.; Boyle, L.M.; Ebrahimi-Fakhari, D.; Kwiatkowski, E.; Nathan, A.; Guttler, T.; Davis, F.; Asara, J.M.; Sahin, M. The Circadian Protein BMAL1 Regulates Translation in Response to S6K1-Mediated Phosphorylation. Cell 2015, 161, 1138–1151. [Google Scholar] [CrossRef]
  149. Ramanathan, C.; Kathale, N.D.; Liu, D.; Lee, C.; Freeman, D.A.; Hogenesch, J.B.; Cao, R. mTOR signaling regulates central and peripheral circadian clock function. PLoS Genet. 2018, 14, e1007369. [Google Scholar] [CrossRef]
  150. Liu, D.; Stowie, A.; De Zavalia, N.; Leise, T.; Pathak, S.S.; Drewes, L.R.; Davidson, A.J.; Amir, S.; Sonenberg, N.; Cao, R. mTOR signaling in VIP neurons regulates circadian clock synchrony and olfaction. Proc. Natl. Acad. Sci. USA 2018, 115, E3296–E3304. [Google Scholar] [CrossRef]
  151. Khan, S.; Nobili, L.; Khatami, R.; Loddenkemper, T.; Cajochen, C.; Dijk, D.J.; Eriksson, S.H. Circadian rhythm and epilepsy. Lancet Neurol. 2018, 17, 1098–1108. [Google Scholar] [CrossRef]
  152. Sahar, S.; Zocchi, L.; Kinoshita, C.; Borrelli, E.; Sassone-Corsi, P. Regulation of BMAL1 protein stability and circadian function by GSK3beta-mediated phosphorylation. PLoS ONE 2010, 5, e8561. [Google Scholar] [CrossRef]
  153. Sharma, S.K.; Dakshinamurti, K. Seizure activity in pyridoxine-deficient adult rats. Epilepsia 1992, 33, 235–247. [Google Scholar] [CrossRef] [PubMed]
  154. Wu, H.; Liu, Y.; Liu, L.; Meng, Q.; Du, C.; Li, K.; Dong, S.; Zhang, Y.; Li, H.; Zhang, H. Decreased expression of the clock gene Bmal1 is involved in the pathogenesis of temporal lobe epilepsy. Mol Brain 2021, 14, 113. [Google Scholar] [CrossRef] [PubMed]
  155. Zhang, T.; Yu, F.; Xu, H.; Chen, M.; Chen, X.; Guo, L.; Zhou, C.; Xu, Y.; Wang, F.; Yu, J.; et al. Dysregulation of REV-ERBα impairs GABAergic function and promotes epileptic seizures in preclinical models. Nat. Commun. 2021, 12, 1216. [Google Scholar] [CrossRef]
  156. Ng, M.; Pavlova, M. Why are seizures rare in rapid eye movement sleep? Review of the frequency of seizures in different sleep stages. Epilepsy Res. Treat. 2013, 2013, 932790. [Google Scholar] [CrossRef] [PubMed]
  157. Frauscher, B.; Von Ellenrieder, N.; Dubeau, F.; Gotman, J. EEG desynchronization during phasic REM sleep suppresses interictal epileptic activity in humans. Epilepsia 2016, 57, 879–888. [Google Scholar] [CrossRef] [PubMed]
  158. Saper, C.B.; Scammell, T.E.; Lu, J. Hypothalamic regulation of sleep and circadian rhythms. Nature 2005, 437, 1257–1263. [Google Scholar] [CrossRef] [PubMed]
  159. Bazhenov, M.; Timofeev, I.; Steriade, M.; Sejnowski, T. Spiking-bursting activity in the thalamic reticular nucleus initiates sequences of spindle oscillations in thalamic networks. J. Neurophysiol. 2000, 84, 1076–1087. [Google Scholar] [CrossRef] [PubMed]
  160. Minecan, D.; Natarajan, A.; Marzec, M.; Malow, B. Relationship of epileptic seizures to sleep stage and sleep depth. Sleep 2002, 25, 899–904. [Google Scholar] [CrossRef] [PubMed]
  161. Jin, B.; Hu, W.; Ye, L.; Krishnan, B.; Aung, T.; Jones, S.E.; Najm, I.M.; Alexopoulos, A.V.; Zhang, K.; Zhu, J.; et al. Small Lesion Size Is Associated with Sleep-Related Epilepsy in Focal Cortical Dysplasia Type II. Front. Neurol. 2018, 9, 106. [Google Scholar] [CrossRef] [PubMed]
  162. Da Silva Lourenço, C.; Tjepkema-Cloostermans, M.C.; Van Putten, M. Machine learning for detection of interictal epileptiform discharges. Clin. Neurophysiol. Off. J. Int. Fed. Clin. Neurophysiol. 2021, 132, 1433–1443. [Google Scholar] [CrossRef] [PubMed]
  163. De Berardis, D.; Orsolini, L.; Serroni, N.; Girinelli, G.; Iasevoli, F.; Tomasetti, C.; Mazza, M.; Valchera, A.; Fornaro, M.; Perna, G. The role of melatonin in mood disorders. ChronoPhysiology Ther. 2015, 5, 65. [Google Scholar] [CrossRef]
  164. Bazil, C.W.; Short, D.; Crispin, D.; Zheng, W. Patients with intractable epilepsy have low melatonin, which increases following seizures. Neurology 2000, 55, 1746–1748. [Google Scholar] [CrossRef] [PubMed]
  165. Molina-Carballo, A.; Acuna-Castroviejo, D.; Rodriguez-Cabezas, T.; Munoz-Hoyos, A. Effects of febrile and epileptic convulsions on daily variations in plasma melatonin concentration in children. J. Pineal Res. 1994, 16, 1–9. [Google Scholar] [CrossRef] [PubMed]
  166. Kothare, S.V.; Kaleyias, J. Sleep and epilepsy in children and adolescents. Sleep Med. 2010, 11, 674–685. [Google Scholar] [CrossRef] [PubMed]
  167. Xu, L.; Guo, D.; Liu, Y.Y.; Qiao, D.D.; Ye, J.Y.; Xue, R. Juvenile myoclonic epilepsy and sleep. Epilepsy Behav. 2018, 80, 326–330. [Google Scholar] [CrossRef] [PubMed]
  168. Malow, B.A.; Levy, K.; Maturen, K.; Bowes, R. Obstructive sleep apnea is common in medically refractory epilepsy patients. Neurology 2000, 55, 1002–1007. [Google Scholar] [CrossRef] [PubMed]
  169. Dell, K.L.; Payne, D.E.; Kremen, V.; Maturana, M.I.; Gerla, V.; Nejedly, P.; Worrell, G.A.; Lenka, L.; Mivalt, F.; Boston, R.C.; et al. Seizure likelihood varies with day-to-day variations in sleep duration in patients with refractory focal epilepsy: A longitudinal electroencephalography investigation. EClinicalMedicine 2021, 37, 100934. [Google Scholar] [CrossRef]
  170. Staniszewska, A.; Maka, A.; Religioni, U.; Olejniczak, D. Sleep disturbances among patients with epilepsy. Neuropsychiatr. Dis. Treat. 2017, 13, 1797–1803. [Google Scholar] [CrossRef]
  171. Leschziner, G. Seizures and Sleep: Not such strange bedfellows. Adv. Clin. Neurosci. Rehabil. 2022, 21, 19–21. [Google Scholar] [CrossRef]
  172. Bazil, C.W.; Castro, L.H.; Walczak, T.S. Reduction of rapid eye movement sleep by diurnal and nocturnal seizures in temporal lobe epilepsy. Arch. Neurol. 2000, 57, 363–368. [Google Scholar] [CrossRef]
  173. Gelinas, J.N.; Khodagholy, D.; Thesen, T.; Devinsky, O.; Buzsáki, G. Interictal epileptiform discharges induce hippocampal-cortical coupling in temporal lobe epilepsy. Nat. Med. 2016, 22, 641–648. [Google Scholar] [CrossRef] [PubMed]
  174. Mekky, J.F.; Elbhrawy, S.M.; Boraey, M.F.; Omar, H.M. Sleep architecture in patients with Juvenile Myoclonic Epilepsy. Sleep Med. 2017, 38, 116–121. [Google Scholar] [CrossRef] [PubMed]
  175. Shvarts, V.; Chung, S. Epilepsy, antiseizure therapy, and sleep cycle parameters. Epilepsy Res. Treat. 2013, 2013, 670682. [Google Scholar] [CrossRef] [PubMed]
  176. Löscher, W. Animal Models of Seizures and Epilepsy: Past, Present, and Future Role for the Discovery of Antiseizure Drugs. Neurochem. Res. 2017, 42, 1873–1888. [Google Scholar] [CrossRef]
  177. Marshall, G.F.; Gonzalez-Sulser, A.; Abbott, C.M. Modelling epilepsy in the mouse: Challenges and solutions. Dis. Model. Mech. 2021, 14, dmm047449. [Google Scholar] [CrossRef]
  178. Porter, R.J.; Cereghino, J.J.; Gladding, G.D.; Hessie, B.; Kupferberg, H.J.; Scoville, B.; White, B.G. Antiepileptic Drug Development Program. Clevel. Clin. J. Med. 1984, 51, 293–305. [Google Scholar] [CrossRef]
  179. Leclercq, K.; Afrikanova, T.; Langlois, M.; De Prins, A.; Buenafe, O.E.; Rospo, C.C.; Van Eeckhaut, A.; de Witte, P.A.; Crawford, A.D.; Smolders, I.; et al. Cross-species pharmacological characterization of the allylglycine seizure model in mice and larval zebrafish. Epilepsy Behav. 2015, 45, 53–63. [Google Scholar] [CrossRef]
  180. Baxendale, S.; Holdsworth, C.J.; Meza Santoscoy, P.L.; Harrison, M.R.M.; Fox, J.; Parkin, C.A.; Ingham, P.W.; Cunliffe, V.T. Identification of compounds with anti-convulsant properties in a zebrafish model of epileptic seizures. Dis. Model. Mech. 2012, 5, 773–784. [Google Scholar] [CrossRef]
  181. Reza, H.M.; Mohammad, H.; Golnaz, E.; Gholamreza, S. Effect of methanolic extract of Hyoscymus niger L. on the seizure induced by picritoxin in mice. Pak. J. Pharm. Sci. 2009, 22, 308–312. [Google Scholar]
  182. Alfaro, J.M.; Ripoll-Gómez, J.; Burgos, J.S. Kainate administered to adult zebrafish causes seizures similar to those in rodent models. Eur. J. Neurosci. 2011, 33, 1252–1255. [Google Scholar] [CrossRef]
  183. Lévesque, M.; Avoli, M. The kainic acid model of temporal lobe epilepsy. Neurosci. Biobehav. Rev. 2013, 37, 2887–2899. [Google Scholar] [CrossRef] [PubMed]
  184. Debski, K.J.; Ceglia, N.; Ghestem, A.; Ivanov, A.I.; Brancati, G.E.; Broer, S.; Bot, A.M.; Muller, J.A.; Schoch, S.; Becker, A.; et al. The circadian dynamics of the hippocampal transcriptome and proteome is altered in experimental temporal lobe epilepsy. Sci. Adv. 2020, 6, eaat5979. [Google Scholar] [CrossRef] [PubMed]
  185. Hong, S.; Lee, P.; Baraban, S.C.; Lee, L.P. A Novel Long-term, Multi-Channel and Non-invasive Electrophysiology Platform for Zebrafish. Sci. Rep. 2016, 6, 28248. [Google Scholar] [CrossRef] [PubMed]
  186. Gawel, K.; Turski, W.A.; Van Der Ent, W.; Mathai, B.J.; Kirstein-Smardzewska, K.J.; Simonsen, A.; Esguerra, C.V. Phenotypic Characterization of Larval Zebrafish (Danio rerio) with Partial Knockdown of the cacna1a Gene. Mol. Neurobiol. 2020, 57, 1904–1916. [Google Scholar] [CrossRef]
  187. Lee, G.-H.; Sung, S.-Y.; Chang, W.-N.; Kao, T.-T.; Du, H.-C.; Hsiao, T.-H.; Safo, M.K.; Fu, T.-F. Zebrafish larvae exposed to ginkgotoxin exhibit seizure-like behavior that is relieved by pyridoxal-5′-phosphate, GABA and anti-epileptic drugs. Dis. Model. Mech. 2012, 5, 785–795. [Google Scholar] [CrossRef]
  188. Benke, T.A.; Swann, J. The tetanus toxin model of chronic epilepsy. Adv. Exp. Med. Biol. 2004, 548, 226–238. [Google Scholar] [CrossRef]
  189. Mitchell, J.; Gatherer, M.; Sundstrom, L.E. Loss of hilar somatostatin neurons following tetanus toxin-induced seizures. Acta Neuropathol. 1995, 89, 425–430. [Google Scholar] [CrossRef]
  190. Chrościńska-Krawczyk, M.; Jargiełło-Baszak, M.; Wałek, M.; Tylus, B.; Czuczwar, S.J. Caffeine and the anticonvulsant potency of antiepileptic drugs: Experimental and clinical data. Pharmacol. Rep. 2011, 63, 12–18. [Google Scholar] [CrossRef]
  191. Garba, K.; Yaro, A.H.; Ya’u, J. Anticonvulsant effects of ethanol stem bark extract of Lannea barteri (Anacardiaceae) in mice and chicks. J. Ethnopharmacol. 2015, 172, 227–231. [Google Scholar] [CrossRef]
  192. White, H.S. Clinical Significance of Animal Seizure Models and Mechanism of Action Studies of Potential Antiepileptic Drugs. Epilepsia 1997, 38, S9–S17. [Google Scholar] [CrossRef]
  193. Stöhr, T.; Kupferberg, H.J.; Stables, J.P.; Choi, D.; Harris, R.H.; Kohn, H.; Walton, N.; White, H.S. Lacosamide, a novel anti-convulsant drug, shows efficacy with a wide safety margin in rodent models for epilepsy. Epilepsy Res. 2007, 74, 147–154. [Google Scholar] [CrossRef] [PubMed]
  194. Scholl, U.I.; Choi, M.; Liu, T.; Ramaekers, V.T.; Häusler, M.G.; Grimmer, J.; Tobe, S.W.; Farhi, A.; Nelson-Williams, C.; Lifton, R.P. Seizures, sensorineural deafness, ataxia, mental retardation, and electrolyte imbalance (SeSAME syndrome) caused by mutations in KCNJ10. Proc. Natl. Acad. Sci. USA 2009, 106, 5842–5847. [Google Scholar] [CrossRef] [PubMed]
  195. Al-Shekaili, H.H.; Petkau, T.L.; Pena, I.; Lengyell, T.C.; Verhoeven-Duif, N.M.; Ciapaite, J.; Bosma, M.; van Faassen, M.; Kema, I.P.; Horvath, G.; et al. A novel mouse model for pyridoxine-dependent epilepsy due to antiquitin deficiency. Hum. Mol. Genet. 2020, 29, 3266–3284. [Google Scholar] [CrossRef] [PubMed]
  196. Wither, R.G.; Colic, S.; Bardakjian, B.L.; Snead, O.C., 3rd; Zhang, L.; Eubanks, J.H. Electrographic and pharmacological characterization of a progressive epilepsy phenotype in female MeCP2-deficient mice. Epilepsy Res. 2018, 140, 177–183. [Google Scholar] [CrossRef] [PubMed]
  197. Yu, F.H.; Mantegazza, M.; Westenbroek, R.E.; Robbins, C.A.; Kalume, F.; Burton, K.A.; Spain, W.J.; McKnight, G.S.; Scheuer, T.; Catterall, W.A. Reduced sodium current in GABAergic interneurons in a mouse model of severe myoclonic epilepsy in infancy. Nat. Neurosci. 2006, 9, 1142–1149. [Google Scholar] [CrossRef]
  198. Okuda, K.; Kobayashi, S.; Fukaya, M.; Watanabe, A.; Murakami, T.; Hagiwara, M.; Sato, T.; Ueno, H.; Ogonuki, N.; Komano-Inoue, S.; et al. CDKL5 controls postsynaptic localization of GluN2B-containing NMDA receptors in the hippocampus and regulates seizure susceptibility. Neurobiol. Dis. 2017, 106, 158–170. [Google Scholar] [CrossRef]
  199. Gonzalez-Sulser, A. Rodent genetic models of neurodevelopmental disorders and epilepsy. Eur. J. Paediatr. Neurol. 2020, 24, 66–69. [Google Scholar] [CrossRef]
  200. Chabrol, E.; Navarro, V.; Provenzano, G.; Cohen, I.; Dinocourt, C.; Rivaud-Péchoux, S.; Fricker, D.; Baulac, M.; Miles, R.; LeGuern, E.; et al. Electroclinical characterization of epileptic seizures in leucine-rich, glioma-inactivated 1-deficient mice. Brain 2010, 133, 2749–2762. [Google Scholar] [CrossRef]
  201. Miura, K.; Kishino, T.; Li, E.; Webber, H.; Dikkes, P.; Holmes, G.L.; Wagstaff, J. Neurobehavioral and Electroencephalographic Abnormalities in Ube3aMaternal-Deficient Mice. Neurobiol. Dis. 2002, 9, 149–159. [Google Scholar] [CrossRef]
  202. Shin, W.; Kweon, H.; Kang, R.; Kim, D.; Kim, K.; Kang, M.; Kim, S.Y.; Hwang, S.N.; Kim, J.Y.; Yang, E.; et al. Scn2a Haploinsufficiency in Mice Suppresses Hippocampal Neuronal Excitability, Excitatory Synaptic Drive, and Long-Term Potentiation, and Spatial Learning and Memory. Front. Mol. Neurosci. 2019, 12, 145. [Google Scholar] [CrossRef]
  203. Wagnon, J.L.; Korn, M.J.; Parent, R.; Tarpey, T.A.; Jones, J.M.; Hammer, M.F.; Murphy, G.G.; Parent, J.M.; Meisler, M.H. Convulsive seizures and SUDEP in a mouse model of SCN8A epileptic encephalopathy. Hum. Mol. Genet. 2015, 24, 506–515. [Google Scholar] [CrossRef] [PubMed]
  204. O’Malley, H.A.; Hull, J.M.; Clawson, B.C.; Chen, C.; Owens-Fiestan, G.; Jameson, M.B.; Aton, S.J.; Parent, J.M.; Isom, L.L. Scn1b deletion in adult mice results in seizures and SUDEP. Ann. Clin. Transl. Neurol. 2019, 6, 1121–1126. [Google Scholar] [CrossRef] [PubMed]
  205. Singh, N.A.; Otto, J.F.; Dahle, E.J.; Pappas, C.; Leslie, J.D.; Vilaythong, A.; Noebels, J.L.; White, H.S.; Wilcox, K.S.; Leppert, M.F. Mouse models of human KCNQ2 and KCNQ3 mutations for benign familial neonatal convulsions show seizures and neuronal plasticity without synaptic reorganization. J. Physiol. 2008, 586, 3405–3423. [Google Scholar] [CrossRef] [PubMed]
  206. Simeone, K.A.; Hallgren, J.; Bockman, C.S.; Aggarwal, A.; Kansal, V.; Netzel, L.; Iyer, S.H.; Matthews, S.A.; Deodhar, M.; Oldenburg, P.J.; et al. Respiratory dysfunction progresses with age in Kcna1-null mice, a model of sudden unexpected death in epilepsy. Epilepsia 2018, 59, 345–357. [Google Scholar] [CrossRef]
  207. Robbins, C.A.; Tempel, B.L. Kv1.1 and Kv1.2: Similar channels, different seizure models. Epilepsia 2012, 53 (Suppl. 1), 134–141. [Google Scholar] [CrossRef]
  208. Whitmire, L.E.; Ling, L.; Bugay, V.; Carver, C.M.; Timilsina, S.; Chuang, H.H.; Jaffe, D.B.; Shapiro, M.S.; Cavazos, J.E.; Brenner, R. Downregulation of KCNMB4 expression and changes in BK channel subtype in hippocampal granule neurons following seizure activity. PLoS ONE 2017, 12, e0188064. [Google Scholar] [CrossRef]
  209. Mark, M.D.; Maejima, T.; Kuckelsberg, D.; Yoo, J.W.; Hyde, R.A.; Shah, V.; Gutierrez, D.; Moreno, R.L.; Kruse, W.; Noebels, J.L.; et al. Delayed postnatal loss of P/Q-type calcium channels recapitulates the absence epilepsy, dyskinesia, and ataxia phenotypes of genomic Cacna1a mutations. J. Neurosci. 2011, 31, 4311–4326. [Google Scholar] [CrossRef]
  210. Machnes, Z.M.; Huang, T.C.; Chang, P.K.; Gill, R.; Reist, N.; Dezsi, G.; Ozturk, E.; Charron, F.; O’Brien, T.J.; Jones, N.C.; et al. DNA methylation mediates persistent epileptiform activity in vitro and in vivo. PLoS ONE 2013, 8, e76299. [Google Scholar] [CrossRef]
  211. Zhu, G.; Okada, M.; Yoshida, S.; Ueno, S.; Mori, F.; Takahara, T.; Saito, R.; Miura, Y.; Kishi, A.; Tomiyama, M.; et al. Rats harboring S284L Chrna4 mutation show attenuation of synaptic and extrasynaptic GABAergic transmission and exhibit the nocturnal frontal lobe epilepsy phenotype. J. Neurosci. 2008, 28, 12465–12476. [Google Scholar] [CrossRef]
  212. Warner, T.A.; Liu, Z.; Macdonald, R.L.; Kang, J.Q. Heat induced temperature dysregulation and seizures in Dravet Syndrome/GEFS+ Gabrg2(+/Q390X) mice. Epilepsy Res. 2017, 134, 1–8. [Google Scholar] [CrossRef]
  213. Puranam, R.S.; He, X.P.; Yao, L.; Le, T.; Jang, W.; Rehder, C.W.; Lewis, D.V.; McNamara, J.O. Disruption of Fgf13 causes synaptic excitatory-inhibitory imbalance and genetic epilepsy and febrile seizures plus. J. Neurosci. 2015, 35, 8866–8881. [Google Scholar] [CrossRef] [PubMed]
  214. Vogt, D.L.; Thomas, D.; Galvan, V.; Bredesen, D.E.; Lamb, B.T.; Pimplikar, S.W. Abnormal neuronal networks and seizure susceptibility in mice overexpressing the APP intracellular domain. Neurobiol. Aging 2011, 32, 1725–1729. [Google Scholar] [CrossRef] [PubMed]
  215. Grier, M.D.; Carson, R.P.; Lagrange, A.H. Toward a Broader View of Ube3a in a Mouse Model of Angelman Syndrome: Expression in Brain, Spinal Cord, Sciatic Nerve and Glial Cells. PLoS ONE 2015, 10, e0124649. [Google Scholar] [CrossRef] [PubMed]
  216. Jin, C.; Zhang, Y.; Kim, S.; Kim, Y.; Lee, Y.; Han, K. Spontaneous seizure and partial lethality of juvenile Shank3-overexpressing mice in C57BL/6 J background. Mol. Brain 2018, 11, 57. [Google Scholar] [CrossRef] [PubMed]
  217. Peñagarikano, O.; Abrahams, B.S.; Herman, E.I.; Winden, K.D.; Gdalyahu, A.; Dong, H.; Sonnenblick, L.I.; Gruver, R.; Almajano, J.; Bragin, A.; et al. Absence of CNTNAP2 leads to epilepsy, neuronal migration abnormalities, and core autism-related deficits. Cell 2011, 147, 235–246. [Google Scholar] [CrossRef] [PubMed]
  218. Ganesh, S.; Delgado-Escueta, A.V.; Sakamoto, T.; Avila, M.R.; Machado-Salas, J.; Hoshii, Y.; Akagi, T.; Gomi, H.; Suzuki, T.; Amano, K.; et al. Targeted disruption of the Epm2a gene causes formation of Lafora inclusion bodies, neurodegeneration, ataxia, myoclonus epilepsy and impaired behavioral response in mice. Hum. Mol. Genet. 2002, 11, 1251–1262. [Google Scholar] [CrossRef]
  219. Wagnon, J.L.; Mahaffey, C.L.; Sun, W.; Yang, Y.; Chao, H.T.; Frankel, W.N. Etiology of a genetically complex seizure disorder in Celf4 mutant mice. Genes Brain Behav. 2011, 10, 765–777. [Google Scholar] [CrossRef]
  220. Acampora, D.; Mazan, S.; Avantaggiato, V.; Barone, P.; Tuorto, F.; Lallemand, Y.; Brûlet, P.; Simeone, A. Epilepsy and brain abnormalities in mice lacking the Otx1 gene. Nat. Genet. 1996, 14, 218–222. [Google Scholar] [CrossRef]
  221. Menten-Dedoyart, C.; Serrano Navacerrada, M.E.; Bartholome, O.; Sánchez Gil, J.; Neirinckx, V.; Wislet, S.; Becker, G.; Plenevaux, A.; Van den Ackerveken, P.; Rogister, B. Development and Validation of a New Mouse Model to Investigate the Role of SV2A in Epilepsy. PLoS ONE 2016, 11, e0166525. [Google Scholar] [CrossRef]
  222. Hu, H.; Zhu, T.; Gong, L.; Zhao, Y.; Shao, Y.; Li, S.; Sun, Z.; Ling, Y.; Tao, Y.; Ying, Y.; et al. Transient receptor potential melastatin 2 contributes to neuroinflammation and negatively regulates cognitive outcomes in a pilocarpine-induced mouse model of epilepsy. Int. Immunopharmacol. 2020, 87, 106824. [Google Scholar] [CrossRef]
  223. Zhang, D.; Yuan, C.; Liu, M.; Zhou, X.; Ge, S.; Wang, X.; Luo, G.; Hou, M.; Liu, Z.; Wang, Q.K.; et al. Deficiency of SCAMP5 leads to pediatric epilepsy and dysregulation of neurotransmitter release in the brain. Hum. Genet. 2020, 139, 545–555. [Google Scholar] [CrossRef]
  224. Mota Vieira, M.; Nguyen, T.A.; Wu, K.; Badger, J.D., 2nd; Collins, B.M.; Anggono, V.; Lu, W.; Roche, K.W. An Epilepsy-Associated GRIN2A Rare Variant Disrupts CaMKIIα Phosphorylation of GluN2A and NMDA Receptor Trafficking. Cell Rep. 2020, 32, 108104. [Google Scholar] [CrossRef] [PubMed]
  225. Klofas, L.K.; Short, B.P.; Zhou, C.; Carson, R.P. Prevention of premature death and seizures in a Depdc5 mouse epilepsy model through inhibition of mTORC1. Hum. Mol. Genet. 2020, 29, 1365–1377. [Google Scholar] [CrossRef] [PubMed]
  226. Huo, J.; Ren, S.; Gao, P.; Wan, D.; Rong, S.; Li, X.; Liu, S.; Xu, S.; Sun, K.; Guo, B.; et al. ALG13 participates in epileptogenesis via regulation of GABA(A) receptors in mouse models. Cell Death Discov. 2020, 6, 87. [Google Scholar] [CrossRef] [PubMed]
  227. Nishitani, A.; Kunisawa, N.; Sugimura, T.; Sato, K.; Yoshida, Y.; Suzuki, T.; Sakuma, T.; Yamamoto, T.; Asano, M.; Saito, Y.; et al. Loss of HCN1 subunits causes absence epilepsy in rats. Brain Res. 2019, 1706, 209–217. [Google Scholar] [CrossRef]
  228. Baraban, S.; Taylor, M.; Castro, P.; Baier, H. Pentylenetetrazole induced changes in zebrafish behavior, neural activity and c-fos expression. Neuroscience 2005, 131, 759–768. [Google Scholar] [CrossRef]
  229. Lopes, M.W.; Sapio, M.R.; Leal, R.B.; Fricker, L.D. Knockdown of Carboxypeptidase A6 in Zebrafish Larvae Reduces Response to Seizure-Inducing Drugs and Causes Changes in the Level of mRNAs Encoding Signaling Molecules. PLoS ONE 2016, 11, e0152905. [Google Scholar] [CrossRef]
  230. Vermoesen, K.; Serruys, A.-S.K.; Loyens, E.; Afrikanova, T.; Massie, A.; Schallier, A.; Michotte, Y.; Crawford, A.D.; Esguerra, C.V.; de Witte, P.A.M.; et al. Assessment of the convulsant liability of antidepressants using zebrafish and mouse seizure models. Epilepsy Behav. 2011, 22, 450–460. [Google Scholar] [CrossRef]
  231. Gawel, K.; Langlois, M.; Martins, T.; van der Ent, W.; Tiraboschi, E.; Jacmin, M.; Crawford, A.D.; Esguerra, C.V. Seizing the moment: Zebrafish epilepsy models. Neurosci. Biobehav. Rev. 2020, 116, 1–20. [Google Scholar] [CrossRef]
  232. Baraban, S.C.; Dinday, M.T.; Hortopan, G.A. Drug screening in Scn1a zebrafish mutant identifies clemizole as a potential Dravet syndrome treatment. Nat. Commun. 2013, 4, 2410. [Google Scholar] [CrossRef]
  233. Samarut, E.; Swaminathan, A.; Riche, R.; Liao, M.; Hassan-Abdi, R.; Renault, S.; Allard, M.; Dufour, L.; Cossette, P.; Soussi-Yanicostas, N.; et al. gamma-Aminobutyric acid receptor alpha 1 subunit loss of function causes genetic generalized epilepsy by impairing inhibitory network neurodevelopment. Epilepsia 2018, 59, 2061–2074. [Google Scholar] [CrossRef] [PubMed]
  234. Liao, M.; Kundap, U.; Rosch, R.E.; Burrows, D.R.W.; Meyer, M.P.; Bencheikh, B.O.A.; Cossette, P.; Samarut, É. Targeted knockout of GABA receptor gamma 2 subunit provokes transient light-induced reflex seizures in zebrafish larvae. Dis. Model. Mech. 2019, 12, dmm.040782. [Google Scholar] [CrossRef] [PubMed]
  235. Mahmood, F.; Mozere, M.; Zdebik, A.A.; Stanescu, H.C.; Tobin, J.; Beales, P.L.; Kleta, R.; Bockenhauer, D.; Russell, C. Generation and validation of a zebrafish model of EAST (epilepsy, ataxia, sensorineural deafness and tubulopathy) syndrome. Dis. Model. Mech. 2013, 6, 652–660. [Google Scholar] [CrossRef] [PubMed]
  236. Chege, S.W.; Hortopan, G.A.; Dinday, M.T.; Baraban, S.C. Expression and function of KCNQ channels in larval zebrafish. Dev. Neurobiol. 2012, 72, 186–198. [Google Scholar] [CrossRef]
  237. Schubert, J.; Siekierska, A.; Langlois, M.; May, P.; Huneau, C.; Becker, F.; Muhle, H.; Suls, A.; Lemke, J.R.; de Kovel, C.G.F.; et al. Mutations in STX1B, encoding a presynaptic protein, cause fever-associated epilepsy syndromes. Nat. Genet. 2014, 46, 1327–1332. [Google Scholar] [CrossRef]
  238. Carvill, G.L.; Heavin, S.B.; Yendle, S.C.; McMahon, J.M.; O’Roak, B.J.; Cook, J.; Khan, A.; Dorschner, M.O.; Weaver, M.; Calvert, S.; et al. Targeted resequencing in epileptic encephalopathies identifies de novo mutations in CHD2 and SYNGAP1. Nat. Genet. 2013, 45, 825–830. [Google Scholar] [CrossRef]
  239. Griffin, A.; Carpenter, C.; Liu, J.; Paterno, R.; Grone, B.; Hamling, K.; Moog, M.; Dinday, M.T.; Figueroa, F.; Anvar, M.; et al. Phenotypic analysis of catastrophic childhood epilepsy genes. Commun. Biol. 2021, 4, 680. [Google Scholar] [CrossRef]
  240. Teng, Y.; Xie, X.; Walker, S.; Rempala, G.; Kozlowski, D.J.; Mumm, J.S.; Cowell, J.K. Knockdown of zebrafish Lgi1a results in abnormal development, brain defects and a seizure-like behavioral phenotype. Hum. Mol. Genet. 2010, 19, 4409–4420. [Google Scholar] [CrossRef]
  241. Swaminathan, A.; Hassan-Abdi, R.; Renault, S.; Siekierska, A.; Riché, R.; Liao, M.; de Witte, P.A.M.; Yanicostas, C.; Soussi-Yanicostas, N.; Drapeau, P.; et al. Non-canonical mTOR-Independent Role of DEPDC5 in Regulating GABAergic Network Development. Curr. Biol. 2018, 28, 1924–1937. [Google Scholar] [CrossRef]
  242. Weckhuysen, S.; Korff, C.M. Epilepsy: Old syndromes, new genes. Curr. Neurol. Neurosci. Rep. 2014, 14, 447. [Google Scholar] [CrossRef]
  243. Harkin, L.A.; McMahon, J.M.; Iona, X.; Dibbens, L.; Pelekanos, J.T.; Zuberi, S.M.; Sadleir, L.G.; Andermann, E.; Gill, D.; Farrell, K.; et al. The spectrum of SCN1A-related infantile epileptic encephalopathies. Brain 2007, 130, 843–852. [Google Scholar] [CrossRef] [PubMed]
  244. Yamakawa, K. Molecular and cellular basis: Insights from experimental models of Dravet syndrome. Epilepsia 2011, 52 (Suppl. 2), 70–71. [Google Scholar] [CrossRef] [PubMed]
  245. Jansen, N.A.; Dehghani, A.; Breukel, C.; Tolner, E.A.; Van Den Maagdenberg, A. Focal and generalized seizure activity after local hippocampal or cortical ablation of Na(V) 1.1 channels in mice. Epilepsia 2020, 61, e30–e36. [Google Scholar] [CrossRef] [PubMed]
  246. Grone, B.P.; Qu, T.; Baraban, S.C. Behavioral Comorbidities and Drug Treatments in a Zebrafish scn1lab Model of Dravet Syndrome. eNeuro 2017, 4, eneuro.0066. [Google Scholar] [CrossRef]
  247. Calhoun, J.D.; Hawkins, N.A.; Zachwieja, N.J.; Kearney, J.A. Cacna1g is a genetic modifier of epilepsy caused by mutation of voltage-gated sodium channel Scn2a. Epilepsia 2016, 57, e103–e107. [Google Scholar] [CrossRef]
  248. Makinson, C.D.; Tanaka, B.S.; Sorokin, J.M.; Wong, J.C.; Christian, C.A.; Goldin, A.L.; Escayg, A.; Huguenard, J.R. Regulation of Thalamic and Cortical Network Synchrony by Scn8a. Neuron 2017, 93, 1165–1179. [Google Scholar] [CrossRef]
  249. Allen, N.M.; Mannion, M.; Conroy, J.; Lynch, S.A.; Shahwan, A.; Lynch, B.; King, M.D. The variable phenotypes of KCNQ-related epilepsy. Epilepsia 2014, 55, e99–e105. [Google Scholar] [CrossRef]
  250. Olsen, M.L.; Sontheimer, H. Functional implications for Kir4.1 channels in glial biology: From K+ buffering to cell differentiation. J. Neurochem. 2008, 107, 589–601. [Google Scholar] [CrossRef]
  251. Reichold, M.; Zdebik, A.A.; Lieberer, E.; Rapedius, M.; Schmidt, K.; Bandulik, S.; Sterner, C.; Tegtmeier, I.; Penton, D.; Baukrowitz, T.; et al. KCNJ10 gene mutations causing EAST syndrome (epilepsy, ataxia, sensorineural deafness, and tubulopathy) disrupt channel function. Proc. Natl. Acad. Sci. USA 2010, 107, 14490–14495. [Google Scholar] [CrossRef]
  252. Raol, Y.H.; Lund, I.V.; Bandyopadhyay, S.; Zhang, G.; Roberts, D.S.; Wolfe, J.H.; Russek, S.J.; Brooks-Kayal, A.R. Enhancing GABA(A) receptor alpha 1 subunit levels in hippocampal dentate gyrus inhibits epilepsy development in an animal model of temporal lobe epilepsy. J. Neurosci. 2006, 26, 11342–11346. [Google Scholar] [CrossRef]
  253. Gregg, N.M.; Sladky, V.; Nejedly, P.; Mivalt, F.; Kim, I.; Balzekas, I.; Sturges, B.K.; Crowe, C.; Patterson, E.E.; Van Gompel, J.J.; et al. Thalamic deep brain stimulation modulates cycles of seizure risk in epilepsy. Sci. Rep. 2021, 11, 24250. [Google Scholar] [CrossRef] [PubMed]
  254. Bajorat, R.; Wilde, M.; Sellmann, T.; Kirschstein, T.; Köhling, R. Seizure frequency in pilocarpine-treated rats is independent of circadian rhythm. Epilepsia 2011, 52, e118–e122. [Google Scholar] [CrossRef]
  255. Quigg, M.; Clayburn, H.; Straume, M.; Menaker, M.; Bertram, E.H., 3rd. Effects of circadian regulation and rest-activity state on spontaneous seizures in a rat model of limbic epilepsy. Epilepsia 2000, 41, 502–509. [Google Scholar] [CrossRef] [PubMed]
  256. Quigg, M.; Straume, M.; Smith, T.; Menaker, M.; Bertram, E.H. Seizures induce phase shifts of rat circadian rhythms. Brain Res. 2001, 913, 165–169. [Google Scholar] [CrossRef] [PubMed]
  257. Matzen, J.; Buchheim, K.; Holtkamp, M. Circadian dentate gyrus excitability in a rat model of temporal lobe epilepsy. Exp. Neurol. 2012, 234, 105–111. [Google Scholar] [CrossRef] [PubMed]
  258. Strand, A.; Aragaki, A.; Baquet, Z.; Hodges, A.; Cunningham, P.; Holmans, P.; Jones, K.; Kooperberg, C.; Olson, J. Conservation of Regional Gene Expression in Mouse and Human Brain. PLoS Genet. 2007, 3, e59. [Google Scholar] [CrossRef]
  259. Waterston, R.; Lindblad-Toh, K.; Birney, E.; Rogers, J.; Abril, J.; Agarwal, P.; Agarwala, R.; Ainscough, R.; Alexandersson, M.; An, P.; et al. Initial sequencing and comparative analysis of the mouse genome. Nature 2003, 420, 520–562. [Google Scholar] [CrossRef]
  260. Amendola, E.; Zhan, Y.; Mattucci, C.; Castroflorio, E.; Calcagno, E.; Fuchs, C.; Lonetti, G.; Silingardi, D.; Vyssotski, A.; Farley, D.; et al. Mapping Pathological Phenotypes in a Mouse Model of CDKL5 Disorder. PLoS ONE 2014, 9, e91613. [Google Scholar] [CrossRef]
  261. Bunton-Stasyshyn, R.K.A.; Wagnon, J.L.; Wengert, E.R.; Barker, B.S.; Faulkner, A.; Wagley, P.K.; Bhatia, K.; Jones, J.M.; Maniaci, M.R.; Parent, J.M.; et al. Prominent role of forebrain excitatory neurons in SCN8A encephalopathy. Brain 2019, 142, 362–375. [Google Scholar] [CrossRef]
  262. Kerjan, G.; Koizumi, H.; Han, E.B.; Dubé, C.M.; Djakovic, S.N.; Patrick, G.N.; Baram, T.Z.; Heinemann, S.F.; Gleeson, J.G. Mice lacking doublecortin and doublecortin-like kinase 2 display altered hippocampal neuronal maturation and spontaneous seizures. Proc. Natl. Acad. Sci. USA 2009, 106, 6766–6771. [Google Scholar] [CrossRef]
  263. MacRae, C.A.; Peterson, R.T. Zebrafish as tools for drug discovery. Nat. Reviews. Drug Discov. 2015, 14, 721–731. [Google Scholar] [CrossRef] [PubMed]
  264. Hortopan, G.A.; Dinday, M.T.; Baraban, S.C. Zebrafish as a model for studying genetic aspects of epilepsy. Dis. Model. Mech. 2010, 3, 144–148. [Google Scholar] [CrossRef] [PubMed]
  265. Wong, K.; Stewart, A.; Gilder, T.; Wu, N.; Frank, K.; Gaikwad, S.; Suciu, C.; Dileo, J.; Utterback, E.; Chang, K.; et al. Modeling seizure-related behavioral and endocrine phenotypes in adult zebrafish. Brain Res. 2010, 1348, 209–215. [Google Scholar] [CrossRef] [PubMed]
  266. Rosch, R.E.; Hunter, P.R.; Baldeweg, T.; Friston, K.J.; Meyer, M.P. Calcium imaging and dynamic causal modelling reveal brain-wide changes in effective connectivity and synaptic dynamics during epileptic seizures. PLoS Comput. Biol. 2018, 14, e1006375. [Google Scholar] [CrossRef]
  267. Randlett, O.; Wee, C.L.; Naumann, E.A.; Nnaemeka, O.; Schoppik, D.; Fitzgerald, J.E.; Portugues, R.; Lacoste, A.M.; Riegler, C.; Engert, F.; et al. Whole-brain activity mapping onto a zebrafish brain atlas. Nat. Methods 2015, 12, 1039–1046. [Google Scholar] [CrossRef]
  268. Brunal, A.A.; Clark, K.C.; Ma, M.; Woods, I.G.; Pan, Y.A. Effects of Constitutive and Acute Connexin 36 Deficiency on Brain-Wide Susceptibility to PTZ-Induced Neuronal Hyperactivity. Front. Mol. Neurosci. 2020, 13, 587978. [Google Scholar] [CrossRef]
  269. Stewart, A.M.; Desmond, D.; Kyzar, E.; Gaikwad, S.; Roth, A.; Riehl, R.; Collins, C.; Monnig, L.; Green, J.; Kalueff, A.V. Perspectives of zebrafish models of epilepsy: What, how and where next? Brain Res. Bull. 2012, 87, 135–143. [Google Scholar] [CrossRef]
  270. Baraban, S. Modeling Epilepsy and Seizures in Developing Zebrafish Larvae. In Models of Seizures and Epilepsy, 1st ed.; Asla Pitkänen, A., Schwartzkroin, P., Moshé, S., Eds.; Elsevier: Amsterdam, The Netherlands, 2006; pp. 189–198. [Google Scholar] [CrossRef]
  271. Zhong, X.L.; Yu, J.T.; Zhang, Q.; Wang, N.D.; Tan, L. Deep brain stimulation for epilepsy in clinical practice and in animal models. Brain Res. Bull. 2011, 85, 81–88. [Google Scholar] [CrossRef]
  272. Yaksi, E.; Jamali, A.; Diaz Verdugo, C.; Jurisch-Yaksi, N. Past, present and future of zebrafish in epilepsy research. FEBS J. 2021, 288, 7243–7255. [Google Scholar] [CrossRef]
  273. Kalsbeek, A.; Van Der Spek, R.; Lei, J.; Endert, E.; Buijs, R.M.; Fliers, E. Circadian rhythms in the hypothalamo-pituitary-adrenal (HPA) axis. Mol. Cell. Endocrinol. 2012, 349, 20–29. [Google Scholar] [CrossRef]
  274. Androulakis, I.P. Circadian rhythms and the HPA axis: A systems view. WIREs Mech. Dis. 2021, 13, e1518. [Google Scholar] [CrossRef]
  275. Sen, A.; Sellix, M.T. The Circadian Timing System and Environmental Circadian Disruption: From Follicles to Fertility. Endocrinology 2016, 157, 3366–3373. [Google Scholar] [CrossRef] [PubMed]
  276. Shao, S.; Zhao, H.; Lu, Z.; Lei, X.; Zhang, Y. Circadian Rhythms Within the Female HPG Axis: From Physiology to Etiology. Endocrinology 2021, 162, bqab117. [Google Scholar] [CrossRef] [PubMed]
  277. Fawley, J.A.; Pouliot, W.A.; Dudek, F.E. Epilepsy and reproductive disorders: The role of the gonadotropin-releasing hormone network. Epilepsy Behav. 2006, 8, 477–482. [Google Scholar] [CrossRef]
  278. Peng, B.W.; Li, X.J.; Wu, W.X.; Zeng, Y.R.; Liao, Y.T.; Hou, C.; Liang, H.C.; Zhang, W.; Wang, X.Y.; Chen, W.X. The Possible Role of Hypothalamus-Pituitary-Adrenal Dysfunction in Epileptic Spasms. Seizure 2020, 81, 145–150. [Google Scholar] [CrossRef] [PubMed]
  279. Basu, T.; Maguire, J.; Salpekar, J.A. Hypothalamic-pituitary-adrenal axis targets for the treatment of epilepsy. Neurosci. Lett. 2021, 746, 135618. [Google Scholar] [CrossRef]
  280. Sun, S.; Wang, H. Disrupting the circadian dynamics of epileptic genes in mouse temporal lobe epilepsy. Front. Mol. Neurosci. 2022, 11, 751. [Google Scholar]
  281. Wen, Z.P.; Fan, S.S.; Du, C.; Yin, T.; Zhou, B.T.; Peng, Z.F.; Xie, Y.Y.; Zhang, W.; Chen, Y.; Tang, J.; et al. Influence of acylpeptide hydrolase polymorphisms on valproic acid level in Chinese epilepsy patients. Pharmacogenomics 2016, 17, 1219–1225. [Google Scholar] [CrossRef]
  282. Musiek, E.S.; Fitzgerald, G.A. Molecular clocks in pharmacology. Handb. Exp. Pharmacol. 2013, 217, 243–260. [Google Scholar] [CrossRef] [PubMed]
  283. Lu, D.; Wang, Z.; Wu, B. Pharmacokinetics-based Chronotherapy. Curr. Drug. Metab. 2022, 23, 2–7. [Google Scholar] [CrossRef]
  284. Ruben, M.D.; Smith, D.F.; FitzGerald, G.A.; Hogenesch, J.B. Dosing time matters. Science 2019, 365, 547–549. [Google Scholar] [CrossRef] [PubMed]
  285. Nicolas, J.M.; Bouzom, F.; Hugues, C.; Ungell, A.L. Oral drug absorption in pediatrics: The intestinal wall, its developmental changes and current tools for predictions. Biopharm. Drug Dispos. 2017, 38, 209–230. [Google Scholar] [CrossRef] [PubMed]
  286. Konturek, P.C.; Brzozowski, T.; Konturek, S.J. Gut clock: Implication of circadian rhythms in the gastrointestinal tract. J. Physiol. Pharmacol. 2011, 62, 139–150. [Google Scholar]
  287. Kurishima, A.; Hayashi, M.; Shimozato, R.; Isozaki, R.; Shioda, T.; Iijima, A. Successful Treatment of Symptomatic Epilepsy with Oral Valproic Acid and Levetiracetam in a Patient with Short-bowel Syndrome: A Case Report. Intern. Med. 2021, 61, 1457–1461. [Google Scholar] [CrossRef]
  288. Lee, K.; Kim, N.; Shim, J.O.; Kim, G.H. Gut Bacterial Dysbiosis in Children with Intractable Epilepsy. J. Clin. Med. 2020, 10, 5. [Google Scholar] [CrossRef]
  289. Patel, I.H.; Venkataramanan, R.; Levy, R.H.; Viswanathan, C.T.; Ojemann, L.M. Diurnal oscillations in plasma protein binding of valproic acid. Epilepsia 1982, 23, 283–290. [Google Scholar] [CrossRef]
  290. Riva, R.; Albani, F.; Ambrosetto, G.; Contin, M.; Cortelli, P.; Perucca, E.; Baruzzi, A. Diurnal fluctuations in free and total steady-state plasma levels of carbamazepine and correlation with intermittent side effects. Epilepsia 1984, 25, 476–481. [Google Scholar] [CrossRef]
  291. Ando, H.; Yanagihara, H.; Sugimoto, K.; Hayashi, Y.; Tsuruoka, S.; Takamura, T.; Kaneko, S.; Fujimura, A. Daily rhythms of P-glycoprotein expression in mice. Chronobiol. Int. 2005, 22, 655–665. [Google Scholar] [CrossRef]
  292. Pácha, J.; Balounová, K.; Soták, M. Circadian regulation of transporter expression and implications for drug disposition. Expert Opin. Drug Metab. Toxicol. 2021, 17, 425–439. [Google Scholar] [CrossRef]
  293. Zhao, M.; Xing, H.; Chen, M.; Dong, D.; Wu, B. Circadian clock-controlled drug metabolism and transport. Xenobiotica Fate Foreign Compd. Biol. Syst. 2020, 50, 495–505. [Google Scholar] [CrossRef]
  294. Gumz, M.L.; Stow, L.R.; Lynch, I.J.; Greenlee, M.M.; Rudin, A.; Cain, B.D.; Weaver, D.R.; Wingo, C.S. The circadian clock protein Period 1 regulates expression of the renal epithelial sodium channel in mice. J. Clin. Investig. 2009, 119, 2423–2434. [Google Scholar] [CrossRef] [PubMed]
  295. Zuber, A.M.; Centeno, G.; Pradervand, S.; Nikolaeva, S.; Maquelin, L.; Cardinaux, L.; Bonny, O.; Firsov, D. Molecular clock is involved in predictive circadian adjustment of renal function. Proc. Natl. Acad. Sci. USA 2009, 106, 16523–16528. [Google Scholar] [CrossRef] [PubMed]
  296. Henriksson, E.; Huber, A.L.; Soto, E.K.; Kriebs, A.; Vaughan, M.E.; Duglan, D.; Chan, A.B.; Papp, S.J.; Nguyen, M.; Afetian, M.E.; et al. The Liver Circadian Clock Modulates Biochemical and Physiological Responses to Metformin. J. Biol. Rhythm. 2017, 32, 345–358. [Google Scholar] [CrossRef]
  297. Fauteck, J.; Schmidt, H.; Lerchl, A.; Kurlemann, G.; Wittkowski, W. Melatonin in epilepsy: First results of replacement therapy and first clinical results. Biol. Signals Recept. 1999, 8, 105–110. [Google Scholar] [CrossRef] [PubMed]
  298. Cederroth, C.R.; Albrecht, U.; Bass, J.; Brown, S.A.; Dyhrfjeld-Johnsen, J.; Gachon, F.; Green, C.B.; Hastings, M.H.; Helfrich-Forster, C.; Hogenesch, J.B.; et al. Medicine in the Fourth Dimension. Cell. Metab. 2019, 30, 238–250. [Google Scholar] [CrossRef]
  299. Allada, R.; Bass, J. Circadian Mechanisms in Medicine. N. Engl. J. Med. 2021, 384, 550–561. [Google Scholar] [CrossRef]
  300. Kramer, A.; Lange, T.; Spies, C.; Finger, A.M.; Berg, D.; Oster, H. Foundations of circadian medicine. PLoS Biol. 2022, 20, e3001567. [Google Scholar] [CrossRef]
  301. Selfridge, J.M.; Gotoh, T.; Schiffhauer, S.; Liu, J.; Stauffer, P.E.; Li, A.; Capelluto, D.G.; Finkielstein, C.V. Chronotherapy: Intuitive, Sound, Founded... But Not Broadly Applied. Drugs 2016, 76, 1507–1521. [Google Scholar] [CrossRef]
  302. Torres-Ruiz, R.; Rodriguez-Perales, S. CRISPR-Cas9 technology: Applications and human disease modelling. Brief. Funct. Genom. 2017, 16, 4–12. [Google Scholar] [CrossRef]
  303. Fuller, P.M.; Gooley, J.J.; Saper, C.B. Neurobiology of the sleep-wake cycle: Sleep architecture, circadian regulation, and regulatory feedback. J. Biol. Rhythm. 2006, 21, 482–493. [Google Scholar] [CrossRef]
  304. Fountain, N.B.; Kim, J.S.; Lee, S.I. Sleep deprivation activates epileptiform discharges independent of the activating effects of sleep. J. Clin. Neurophysiol. 1998, 15, 69–75. [Google Scholar] [CrossRef] [PubMed]
  305. Thijs, R.D.; Surges, R.; O’Brien, T.J.; Sander, J.W. Epilepsy in adults. Lancet 2019, 393, 689–701. [Google Scholar] [CrossRef]
  306. Yu, W.; Gwinn, M.; Dotson, W.D.; Green, R.F.; Clyne, M.; Wulf, A.; Bowen, S.; Kolor, K.; Khoury, M.J. A knowledge base for tracking the impact of genomics on population health. Genet. Med. 2016, 18, 1312–1314. [Google Scholar] [CrossRef] [PubMed]
  307. Bu, D.; Luo, H.; Huo, P.; Wang, Z.; Zhang, S.; He, Z.; Wu, Y.; Zhao, L.; Liu, J.; Guo, J.; et al. KOBAS-i: Intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis. Nucleic Acids Res. 2021, 49, W317–W325. [Google Scholar] [CrossRef] [PubMed]
Ijms 24 04223 g001
Figure 1. GO and KEGG analyses of human epilepsy-related genes. (A) The circadian rhythm pathway is enriched in the GO analysis of human epilepsy-related genes. These 661 epilepsy-related genes were classified into biological processes with ClueGO in Cytoscape. Those with Kappa scores higher than 0.4 are presented. Those with the circadian term are shown. The node size indicates the number of genes in each pathway, the lines between the nodes indicate the correlations between the terms, and dotted lines possible correlations between the terms. The same color in different nodes indicates the same sets of genes enriched in different pathways. The arrows indicate the affiliation between pathways. (B) The top 20 ranked KEGG pathways of the 192 driver genes are shown. Pathways with the same category were sorted and merged.
Figure 1. GO and KEGG analyses of human epilepsy-related genes. (A) The circadian rhythm pathway is enriched in the GO analysis of human epilepsy-related genes. These 661 epilepsy-related genes were classified into biological processes with ClueGO in Cytoscape. Those with Kappa scores higher than 0.4 are presented. Those with the circadian term are shown. The node size indicates the number of genes in each pathway, the lines between the nodes indicate the correlations between the terms, and dotted lines possible correlations between the terms. The same color in different nodes indicates the same sets of genes enriched in different pathways. The arrows indicate the affiliation between pathways. (B) The top 20 ranked KEGG pathways of the 192 driver genes are shown. Pathways with the same category were sorted and merged.
Ijms 24 04223 g001
Ijms 24 04223 g002
Figure 2. The classification of seizure types proposed by the International League Against Epilepsy 2017. Focal seizures occur within one hemisphere, whereas generalized seizures occur in the bilateral hemisphere. The onset of some seizures is unknown, which may not be classified as focal or generalized seizures. A further classification of seizures highlights features of seizure onset, including awareness level, motor onset, or nonmotor onset symptoms. Drawn from Fisher et al., 2017 [115].
Figure 2. The classification of seizure types proposed by the International League Against Epilepsy 2017. Focal seizures occur within one hemisphere, whereas generalized seizures occur in the bilateral hemisphere. The onset of some seizures is unknown, which may not be classified as focal or generalized seizures. A further classification of seizures highlights features of seizure onset, including awareness level, motor onset, or nonmotor onset symptoms. Drawn from Fisher et al., 2017 [115].
Ijms 24 04223 g002
Ijms 24 04223 g003
Figure 3. Mammalian circadian clockwork model. Three transcription-translation feedback loops are known to operate in the mammalian circadian clock. In the first loop, the CLOCK: BMAL1 heterodimer activates the expression of target genes, including Per genes (Per1, Per2, and Per3) and Cry genes (Cry1 and Cry2) via binding to E-box (5′-CACGTG-3′) in their promoter regions, whereas the PER: CRY heterodimer interferes with the transcriptional activity of the CLOCK-BMAL1 heterodimer and turns off their own expression. In the second loop, Rorα/β and Rev-erbα/β are regulated by CLOCK and BMAL1 via E-box, whereas their proteins RORα/β and REV-ERBα/β activate and suppress Bmal1 by competing for binding to the RORE (retinoic-acid-related orphan receptor response element). In the third loop, Dbp, Hlf, Tef, and E4bp4/Nfil3 are all regulated by CLOCK and BMAL1 via E-box, whereas their proteins DBP, HIF, TEF, and E4BP4/NFIL3 bind to D-box in the promoter regions of their target genes, where DBP, HIF, and TEF activate D-box-containing genes and E4BP4/NFIL3 represses them. Among these three circadian clock-controlled cis-elements-mediated transcriptional feedback loops, the E/E’-box-mediated loop plays the dominant role in the circadian clock. In addition, the mTOR pathway has been shown to contribute to circadian regulation. Color arrows indicate transcription or translation, black arrows transcription activation, and turnstile symbol suppression.
Figure 3. Mammalian circadian clockwork model. Three transcription-translation feedback loops are known to operate in the mammalian circadian clock. In the first loop, the CLOCK: BMAL1 heterodimer activates the expression of target genes, including Per genes (Per1, Per2, and Per3) and Cry genes (Cry1 and Cry2) via binding to E-box (5′-CACGTG-3′) in their promoter regions, whereas the PER: CRY heterodimer interferes with the transcriptional activity of the CLOCK-BMAL1 heterodimer and turns off their own expression. In the second loop, Rorα/β and Rev-erbα/β are regulated by CLOCK and BMAL1 via E-box, whereas their proteins RORα/β and REV-ERBα/β activate and suppress Bmal1 by competing for binding to the RORE (retinoic-acid-related orphan receptor response element). In the third loop, Dbp, Hlf, Tef, and E4bp4/Nfil3 are all regulated by CLOCK and BMAL1 via E-box, whereas their proteins DBP, HIF, TEF, and E4BP4/NFIL3 bind to D-box in the promoter regions of their target genes, where DBP, HIF, and TEF activate D-box-containing genes and E4BP4/NFIL3 represses them. Among these three circadian clock-controlled cis-elements-mediated transcriptional feedback loops, the E/E’-box-mediated loop plays the dominant role in the circadian clock. In addition, the mTOR pathway has been shown to contribute to circadian regulation. Color arrows indicate transcription or translation, black arrows transcription activation, and turnstile symbol suppression.
Ijms 24 04223 g003
Ijms 24 04223 g004
Figure 4. Summary of epileptic publications using different animals. (A) Number of epileptic publications using animal models, compiled by the Web of Science™ (https://clarivate.com/webofsciencegroup/solutions/web-of-science/, accessed on 23 February 2022) during the past 5 years. (B) Tendency of using different animal models for epileptic studies. Percentages of the number of published articles annually in total literature for each animal model are shown.
Figure 4. Summary of epileptic publications using different animals. (A) Number of epileptic publications using animal models, compiled by the Web of Science™ (https://clarivate.com/webofsciencegroup/solutions/web-of-science/, accessed on 23 February 2022) during the past 5 years. (B) Tendency of using different animal models for epileptic studies. Percentages of the number of published articles annually in total literature for each animal model are shown.
Ijms 24 04223 g004
Ijms 24 04223 g005
Figure 5. A chronomodulated strategy for epilepsy chronotherapy. Three lines of experiments are required for developing chronomodulated strategy-based epilepsy chronotherapy: (1) to investigate circadian mechanisms underlying time-of-day-specific dynamics of rhythmic epilepsies (red), (2) to investigate chronopharmacokinetics of specific AEDs (blue), and (3) to investigate chronopharmacodynamics of specific AEDs (green). The findings from these three lines of experiments should help develop chronomodulated strategy-based chronotherapy for specific rhythmic epilepsy. Mathematical/computational modeling is also needed to help select an optimal chronotherapy plan.
Figure 5. A chronomodulated strategy for epilepsy chronotherapy. Three lines of experiments are required for developing chronomodulated strategy-based epilepsy chronotherapy: (1) to investigate circadian mechanisms underlying time-of-day-specific dynamics of rhythmic epilepsies (red), (2) to investigate chronopharmacokinetics of specific AEDs (blue), and (3) to investigate chronopharmacodynamics of specific AEDs (green). The findings from these three lines of experiments should help develop chronomodulated strategy-based chronotherapy for specific rhythmic epilepsy. Mathematical/computational modeling is also needed to help select an optimal chronotherapy plan.
Ijms 24 04223 g005
Table 1. KEGG groups of epilepsy driver genes.
Table 1. KEGG groups of epilepsy driver genes.
TermsInput Genes
Taste transductionCACNA1A, HCN4, GABRA5, SCN2A, GEFSP7, GABBR2, GABRA6, GABRA1, GABRA2
GABAergic synapseSLC6A1, GABRA6, SLC38A3, GABRG2, GAD1, SLC12A5, ABAT, CACNA1A, GABRA5, GABBR2, GABRB3, GABRA1, GABRB2, GABRA2
Synaptic vesicle cycleATP6V0C, SLC6A1, STX1B, ATP6V1A, CACNA1A, STXBP1, CPLX1, DNM1, ATP6V0A1, SLC1A2
Retrograde endocannabinoid signalingPLCB1, GABRA6, GRIA2, GABRG2, CACNA1A, GABRA5, GABRB2, GABRB3, GABRA1, GABRA2
Glutamatergic synapsePLCB1, SLC38A3, GRIA2, CACNA1A, GRIK2, GRIN2A, PPP3CA, GRIN1, SLC1A2
Cholinergic synapsePLCB1, CACNA1A, CHRNB2, KCNQ2, KCNQ3, CHRNA4
Long-term potentiationGRIA2, PPP3CA, GRIN1, GRIN2A, PLCB1
Dopaminergic synapsePLCB1, GRIA2, CACNA1A, GRIN2A, SCN1A, PPP3CA
Thyroid hormone signaling pathwayPDPK1, NOTCH3, MTOR, SLC2A1, PLCB1
β-Alanine metabolismABAT, GAD1, ALDH2, ALDH7A1
Glycosylphosphatidylinositol (GPI)-anchor biosynthesisPIGP, PIGQ, PIGS, PIGA
Metabolic pathwaysST3GAL3, PIGA, ATP6V0C, ATP6V1A, ASAH1, PNPO,
PLCB1, ATP6V0C, ACP1, ALDH2, PIGP, PIGQ, PIGS, SYNJ1, MDH2, ABAT, ALDH7A1, CAD, ALG14, GAD1, UGP2
Amyotrophic lateral sclerosis (ALS)GRIA2, PPP3CA, GRIN2A, SLC1A2, GRIN1
Nicotine addictionGABRA6, GRIA2, GABRG2, CHRNB2, CHRNA4, GRIN2A, CACNA1A, GABRA5, GRIN1, GABRB3, GABRA1, GABRB2, GABRA2
Morphine addictionGABRA6, GABRG2, CACNA1A, GABRA5, GABBR2, GABRB3, GABRA1, GABRB2, GABRA2
Neuroactive ligand–receptor interactionGABRA6, GRIA2, GABRG2, GRIK2, CHRNB2, GABRB2, GLUD1, LEPR, CHRNA4, GRIN2A, CHRNA2, GABRA5, GRIN1, GABRB3, GABRA1, GABBR2, GABRA2
mTOR signaling pathwayATP6V1A, MTOR, DEPDC5, PDPK1, STRADA, NPRL3, NPRL2
cAMP signaling pathwayGRIA2, HCN2, HCN4, GLI3, GRIN2A, GRIN1, GABBR2
MAPK signaling pathwayRAPGEF2, CACNA1A, CACNA1E, NTRK2, CACNB4, MEF2C, EJM4, PPP3CA
LysosomeMFSD8, AP3B2, ASAH1, ATP6V0C, SCARB2, ATP6V0A1, TPP1
OthersSZT2, DOCK7, HNRNPU, GEFSP4, GEFSP8, GEFSP6, SLC25A12, SLC25A22, LNPK, EJM9, EJM3, ETL6, ETL3, TRAK1, P4HTM, DALRD3, UBA5, YEATS2, TNRC6A, MARCH6, EPPS, HWE1, HWE2, SPATA5, CYFIP2, PHACTR1, CNPY3, ICK, ACTL6B, RHOBTB2, PLPBP, OXR1, EIG1, EIG2, EIG3, EIG4, EIG5, EIG7, ETL4, ETL2, FRRS1L, KCNC1, DENND5A, TRAPPC4, PACS2, DMXL2, AARS1, SEMA6B, SYN1, SIK1, EEF1A2, SCN8A, LGI1, ARHGEF9, HCN1, NHLRC1, ADAM22, ADAM10, KIF3C, SMS, PDPK1(PDK1), CDYL, KCNV2, MECP2, NIPA1, SYNGAP1, EJM1, EJM2, CYFIP1, PCDH19, TRAPPC6B, SAMD12, LGI4, TBC1D24, SETD1A, CDKL5, EFHC1, POLG, NRXN1, CNTNAP2, EPM2A, ARX, KCNA2, FOXG1, CSTB, CHRNA7, SLC9A6, KCNAB1, ZEB2, SMC1A, REST, NR2F1, MYH1, KCNT2, ARV1, CASR, GUF1, PRDM8, YWHAG, NECAP1, SLC13A5, GOSR2, LMNB2, KCNB1, CLN8, FGF12, SATB2, KCNMA1, SCN1B, KCNE1, KCNMB3, FGF12, NCDN, FBXO28, YIPF5, MED23, CELF2, KCNC2
Table 3. Pharmacological and genetic epileptic models in rodents and zebrafish.
Table 3. Pharmacological and genetic epileptic models in rodents and zebrafish.
RodentsZebrafish
Pharmacological ModelsGenetic ModelsPharmacological ModelsGenetic Models
Pentylenetetrazol (PTZ) [192],
(D,L)-Allylglycine (AG) [179],
Kainic acid (KA) [176,183],
Picrotoxin [193],
Bicuculline [193],
Pilocarpine [184],
Tetanus toxin [188],
Caffeine [190],
Strychnine [191]		Kcnj10 [194], Aldh7a1 [195], Mecp2 [196], Scn1a [197], Cdkl5 [198], Syngap1 [199], Lgi1 [200], Ube3a [201], Scn2a [202], Scn8a [203], Scn1b [204], Kcnq2/3 [205], Kcna1 [206], Kcna2 [207], Kcnmb4 [208], Cacna1a [209], Gria2 [210], Chma4 [211], Gabrg2 [212], Fgf13 [213], App [214], Ube3a [215], Shank3 [216], Cntnap2 [217], Epm2a [218], Celf4 [219], Otx1 [220], Sv2a [221], Trpm2 [222], Scamp5 [223], Grin2a [224], Depdc5 [225], Alg13 [226], Hcn1 [227]Pentylenetetrazol (PTZ) [228],
(D,L)-Allylglycine (AG) [179],
Kainic acid (KA) [182],
Picrotoxin [180],
Pilocarpine [229,230],
Ginkgotoxin [187,231]		scn1lab [232], gabra1 [233], gabrg2 [234], kcnj10 [235], kcnq2/3 [236], stx1b [237],
chd2 [238], arxa [239], eef1a2 [239], gabrb3 [239], pnpo [239], strada [239], lgi1a [240], cacna1a/b [186],
depdc5 [241]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Sun, S.; Wang, H. Clocking Epilepsies: A Chronomodulated Strategy-Based Therapy for Rhythmic Seizures. Int. J. Mol. Sci. 2023, 24, 4223. https://doi.org/10.3390/ijms24044223

AMA Style

Sun S, Wang H. Clocking Epilepsies: A Chronomodulated Strategy-Based Therapy for Rhythmic Seizures. International Journal of Molecular Sciences. 2023; 24(4):4223. https://doi.org/10.3390/ijms24044223

Chicago/Turabian Style

Sun, Sha, and Han Wang. 2023. "Clocking Epilepsies: A Chronomodulated Strategy-Based Therapy for Rhythmic Seizures" International Journal of Molecular Sciences 24, no. 4: 4223. https://doi.org/10.3390/ijms24044223

APA Style

Sun, S., & Wang, H. (2023). Clocking Epilepsies: A Chronomodulated Strategy-Based Therapy for Rhythmic Seizures. International Journal of Molecular Sciences, 24(4), 4223. https://doi.org/10.3390/ijms24044223

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop