Incidence of seizures and EEG abnormalities among offspring of epileptic patients

Summary The marriage rate of epileptic patients was 62% in males und 78% in females. Compared with the rates in the general population, the male patients had a 15% lower rate, but there was no difference in females. There were 263 patients with at least one offspring selected for the study. There were 243 sons and 272 daughters (506 total, 1.9 per patient). Distribution by types of seizure was awakening grand mal, absence or myoclonic petit mal in 24%, grand mal with no aura in 21%, grand mal during sleep in 23%, diffuse grand mal in 7%, grand mal with aura in 13%, psychomotor seizure in 9%, and focal seizure in 3%. The probands were composed of 79% idiopathic and 21% symptomatic in pathogenetic classification. An epileptic EEG abnormality was demonstrated in 22% of male and 44% of female probands.The incidence of seizures among offspring was 2.4% (4.2% age-corrected) in a narrow sense (epilepsy) and 9.1% in a broad sense including febrile convulsions. The latter morbidity was 11.0% for the idiopathic and 3.2% for the symptomatic group; 11.0% for female and 6.9% for male probands; 10.2% for sons and 8.1% for daughters. The figure was higher for the probands with the age range at onset of seizure of 0–4 years (20.6%) and 20–29 years (12.6%) than for those with other age ranges; higher for those with awakening grand mal, absence, myoclonic petit mal, or grand mal with no aura than for those with other types of seizure; and higher for those with family history of epilepsy than those without it.Possible correlation of types of seizure between probands and offspring was demonstrated. Thirty-seven percent of offspring exhibited epileptic EEG abnormalities, and the ratio of epileptic EEG abnormalities to clinical manifestation is about 4:1.Possible existence of familial aggregation of EEG abnormalities and of two kinds of families with large or small epileptic predisposition was indicated.The importance of the role of hereditary and environmental factors in epileptic pathogenesis is proved, and the results of an investigation of congenital malformation among offspring of epileptic mothers are presented. These results were considered to be useful for genetic counseling of epileptic patients.     

Genetico-epidemiologic analysis of the role of constitutional factors in the etiology of epilepsy

Using multifactorial and monolocus models interrelations of a number of constitutional factors of probands (sex, child convulsive reactions, character abnormalities, age at the time of illness onset) with genetic factors of epilepsy occurrence among relatives (365 families) and populations from 5 regions of the Khabarovsk krai (2.88 patients per 1000 subjects) were studied. The dependence of epilepsy manifestation probability in mutant homo- and heterozygotes on sex, convulsive reactions and age characteristics of the proband body reactivity was shown. The notions of double threshold determination of convulsive readiness (the T1 threshold "cuts" a part of population with non-paroxysmal abnormality of the brain bioelectric activity, while the T2 threshold "cuts" that with convulsive reactions) were substantiated, the presence of this causing epilepsy development in individuals with a mutant allele of the major dominant gene. The hypothesis of the ecogenetic interaction of epilepsy main etiologic factors (major gene, environmental factors and constitutional readiness) has been described.     

Parental generalized EEG alpha activity predisposes to spike wave discharges in offspring

Familial and twin studies have shown that the individual variability of the normal human electroencephalogram (EEG) is largely genetically determined. In epileptology, these genetic parameters of the EEG background activity are almost totally neglected. The aim of the present study has been to investigate whether a special genetic type of background activity might be related to the pathogenesis of epilepsy. EEG recordings of parents of 257 epileptic children were evaluated retrospectively. Some 156 healthy adults served as controls. Special attention was paid to alpha activity extending to the frontal region, both in bipolar and in referential recordings (Alpha I). Alpha I was found significantly more often in parents of children with primary generalized epilepsy (18%) compared with parents of children with focal epilepsy (8%) or controls (9%). In a second step, parental EEGs of children with different EEG patterns associated with epilepsy were studied. Alpha I was found significantly more often in parents of children with focal sharp waves and generalized spikes and waves (26%) than in parents of probands with focal sharp waves without additional generalized spikes and waves (8%) or in controls (9%). Parents of probands with theta rhythms and spikes and waves had alpha I significantly more often (18%) than parents of probands with theta rhythms without additional spikes and waves (8%) or controls (9%). The findings reveal a clear correlation between the type of EEG background activity in parents and the EEG characteristics in their children, thus pointing to common mechanisms.     

Use of susceptibility scoring in conjunction with the genotypic transmission disequilibrium test

We explored the utility of selecting a genetically predisposed subgroup to increase the finding of a genetic signal in the Genetic Analysis Workshop 14 Collaborative Study on the Genetics of Alcoholism dataset. A subgroup of affected probands with low environmental risk exposures was defined using a susceptibility score calculated from an environmental risk model. Thirty-nine probands with highly positive scores were selected, along with their parents, for use in a genotypic transmission disequilibrium test (TDT) test. We compared the results of the genotypic TDT in this subgroup to the TDT results using all probands and their parents. For some markers, the susceptibility scoring approach resulted in smaller p-values, while for other markers, evidence for a genetic signal weakened. Further explorations into genetic and environmental population characteristics that benefit from this approach are warranted.     

EEG abnormalities, epilepsy and regression in autism: a review

Autism is associated with a high frequency of epileptiform EEG abnormalities (prevalence range 10.3-72.4%) and epilepsy (prevalence range 0-44.5%). A significant subgroup of autistic children (20-49%) experience autistic regression. The relationship among EEG abnormalities, epilepsy, and regression in autistic patients is not yet well understood. In this review, the current knowledge of the relationship is summarized. The evidence from clinical studies does not support the view that EEG abnormalities play a role in autistic regression. The majority of studies also failed to find any significant relationship between epilepsy and autistic regression. However, some results indicated that the higher the prevalence of epilepsy in the sample, the greater the probability of there being a significant association between epilepsy and autistic regression. Further research on the topic is needed.     

Genetico-epidemiologic analysis of schizophrenia with a paroxysmal-progressive course

The results of studying the causes of prevalence and clinical polymorphism of schizophrenia on the basis of epidemiological selection of probands with paroxysmal-progredient form (211 families) have been presented in this paper. The analysis of multifactorial threshold and monolocus diallele models of factors of schizophrenia prevalence among relatives and in a population allowed to ground the hypothesis of the main gene. The characteristic manifestation is paroxysmal course of the process with small progredience and great specific weight of affective disorders. The increase of heterozygous genotype penetrance is linked to constitutional (somatotype, peculiarities of premorbid personality) and environmental (alcohol excesses, psychogenia) factors of probands.     

Heterogeneity and several clinico-genetic correlations in epilepsy under inbred conditions]

The types of inheritance and clinico-genetical correlatins of epilepsy in 291 probands in conditions of inbreeding were studied. The data obtained confirmed the multifactorial (gene-polygene+medium) inheritance of epileptic and convulsive predispositions and contradicted the hypothesis of primarily recessive inheritance of epilepsy. Together with family forms of the disease, which were communicated mainly according to an uncertained and dominant type (rarely recessive type), there were existed forms of eipilepsy with incomplete genetical hereditary predisposition (which were observed in relatives of 2-3 generations only by epileptic features) and phenotypical forms concentrated in sporadic groups. There were found the dependences onthe rate of occurrence of secondary epilepsy (with or without epileptoidness), epileptoid psychopathy and children convulsions in relatives, on the type of inheritance, the age of manifestations, the form, polymorphism of the attacks, the severity of the developement of epilepsy, the expressiveness of epileptoidness in probands and high severity of the disease with distinct epileptoidness inbreeding families. The hereditary heterogeneity of epilepsy, associated, perhaps, with pleiotropy of epileptic (with or without epileptoidness) genes, was assumed. The found clinico-genetical correlaltions mightbe taken into account in medico-genetical prognosis of families burdened by epilspsy in analogous populational-demographic conditions.     

Novel PRRT2 mutations in paroxysmal dyskinesia patients with variant inheritance and phenotypes

Paroxysmal dyskinesias (PDs) are a group of episodic movement disorders with marked variability in clinical manifestation and potential association with epilepsy. PRRT2 has been identified as a causative gene for PDs, but the phenotypes and inheritance patterns of PRRT2 mutations need further clarification. In this study, 10 familial and 21 sporadic cases with PDs and PDs‐related phenotypes were collected. Genomic DNA was screened for PRRT2 mutations by direct sequencing. Seven PRRT2 mutations were identified in nine (90.0%) familial cases and in six (28.6%) sporadic cases. Five mutations are novel: two missense mutations (c.647C>G/p.Pro216Arg and c.872C>T/p.Ala291Val) and three truncating mutations (c.117delA/p.Val41TyrfsX49, c.510dupT/p.Leu171SerfsX3 and c.579dupA/p.Glu194ArgfsX6). Autosomal dominant inheritance with incomplete penetrance was observed in most of the familial cases. In the sporadic cases, inheritance was heterogeneous including recessive inheritance with compound heterozygous mutations, inherited mutations with incomplete parental penetrance and de novo mutation. Variant phenotypes associated with PRRT2 mutations, found in 36.0% of the affected cases, included febrile convulsions, epilepsy, infantile non‐convulsive seizures (INCS) and nocturnal convulsions (NC). All patients with INCS or NC, not reported previously, displayed abnormalities on electroencephalogram (EEG). No EEG abnormalities were recorded in patients with classical infantile convulsions and paroxysmal choreoathetosis (ICCA)/paroxysmal kinesigenic dyskinesia (PKD). Our study further confirms that PRRT2 mutations are the most common cause of familial PDs, displaying both dominant and recessive inheritance. Epilepsy may occasionally occur in ICCA/PKD patients with PRRT2 mutations. Variant phenotypes INCS or NC differ from classical ICCA/PKD clinically and electroencephalographically. They have some similarities with, but not identical to epilepsy, possibly represent an overlap between ICCA/PKD and epilepsy .     

Improved Diagnosis in Children with Partial Epilepsy Using a Multivariable Prediction Model Based on EEG Network Characteristics

Background

Electroencephalogram (EEG) acquisition is routinely performed to support an epileptic origin of paroxysmal events in patients referred with a possible diagnosis of epilepsy. However, in children with partial epilepsies the interictal EEGs are often normal. We aimed to develop a multivariable diagnostic prediction model based on electroencephalogram functional network characteristics.

Methodology/Principal Findings

Routinely performed interictal EEG recordings at first presentation of 35 children diagnosed with partial epilepsies, and of 35 children in whom the diagnosis epilepsy was excluded (control group), were used to develop the prediction model. Children with partial epilepsy were individually matched on age and gender with children from the control group. Periods of resting-state EEG, free of abnormal slowing or epileptiform activity, were selected to construct functional networks of correlated activity. We calculated multiple network characteristics previously used in functional network epilepsy studies and used these measures to build a robust, decision tree based, prediction model. Based on epileptiform EEG activity only, EEG results supported the diagnosis of with a sensitivity and specificity of 0.77 and 0.91 respectively. In contrast, the prediction model had a sensitivity of 0.96 [95% confidence interval: 0.78–1.00] and specificity of 0.95 [95% confidence interval: 0.76–1.00] in correctly differentiating patients from controls. The overall discriminative power, quantified as the area under the receiver operating characteristic curve, was 0.89, defined as an excellent model performance. The need of a multivariable network analysis to improve diagnostic accuracy was emphasized by the lack of discriminatory power using single network characteristics or EEG''s power spectral density.

Conclusions/Significance

Diagnostic accuracy in children with partial epilepsy is substantially improved with a model combining functional network characteristics derived from multi-channel electroencephalogram recordings. Early and accurate diagnosis is important to start necessary treatment as soon as possible and inform patients and parents on possible risks and psychosocial aspects in relation to the diagnosis.     

Complex segregation analysis of non-myoclonic idiopathic generalized epilepsy in families ascertained from probands affected with idiopathic epilepsy with tonic-clonic seizures in Antioquia,Colombia

In an attempt to identify the possible role of major genes, multifactorial inheritance, and cohort effects in the susceptibility to idiopathic epilepsy with generalized tonic-clonic seizures of the awakening type (GTCS), complex segregation analysis was performed in 196 nuclear families ascertained through affected probands with idiopathic epilepsy with GTCS belonging to the Paisa community of Antioquia (Colombia). Models postulating no transmission, single major locus (dominant and recessive) only, and multifactorial component only, were rejected. Since the codominant single major locus model could not be rejected and models that assign no major locus to transmission, no polygenic component to transmission, and no transmission of the major effect were rejected, complex segregation analysis suggested that a major autosomal codominant allele together with a multifactorial component (mixed model) best explained clustering of idiopathic epilepsy with GTCS in families of the Paisa community. The deficit of transmission of heterozygotes (0.17) is compatible with the existence of epistasis acting on a major gene whose frequency was estimated to be 0.0211. Its transmission variance accounts for 81% of the susceptibility to idiopathic epilepsy with GTCS. The complementary variance (19%) is due to the polygenic component. Received: 19 January 1996 / Revised: 11 March 1996     

Marfan disease

After reviewing the main features of the Marfan syndrome (musculoskeletal, ocular, cardiovascular, pulmonary abnormalities), its autosomal dominant inheritance with high penetrance but variable phenotype and presence of "soft" conditions preventing an easy diagnosis, the authors report their own data relevant to 73 probands: ratio of each clinical manifestation, state of 34% of familial cases and display of a paternal age effect in the sporadic cases. The pathogenic defect is unknown as like the location of the gene. The difficulties of the genetic counseling are then approached: unpredictability of the severity and of the prognosis in the unborn children of an affected patient, benefit of the echocardiography in the management of people at risk.     

复杂性热性惊厥脑电图特征与癫痫发生的相关性

目的：探讨复杂性热性惊厥脑电图特征与癫痫发生的相关性。方法：2012年3 月到2014 年5 月选择在我院诊治为复杂性热 性惊厥的呼吸道感染患儿86 例作为观察组,同期选择在我院诊治的非热性惊厥的呼吸道感染患儿86 例作为对照组,两组都进 行脑电图监测与认知功能判定,对癫痫发生情况进行判定与分析。结果：观察组的言语智商、行为智商与总智商评分都明显低于 对照组(P<0.05)。观察组的癫痫发生率为9.3 %,脑电图异常率为8.1 %;而对照组的癫痫发生率为1.2 %,脑电图异常率为2.3 %, 对比差异都有统计学意义(P<0.05)。在观察组患儿中,Spearman 相关性分析显示脑电图异常与癫痫发生存在明显正向相关性(r=0. 349,P<0.05)。结论：复杂性热性惊厥伴随有脑电图异常,与癫痫发生存在明显正向相关性,损害患儿的认知功能。     

Bipolar manic-depressive psychoses: Results of a genetic investigation

Summary Ninety-five patients with bipolar manicdepressive disorders were followed from 1959 to 1975, and their first-degree relatives (N=617) were studied. In the search for heterogeneity of bipolar illness the patients were subclassified according to various criteria: sex, age at onset, number of episodes, and longitudinal syndrome subtypes (Dm, MD, Md), and the genetic findings were used as an external criterion.The first-degree relatives of female probands showed a higher morbidity risk for psychiatric disorders than the relatives of male probands, and the highest morbidity risk was found in the female relatives of female probands. Early onset and late-onset patients did not differ from a genetic point of view. Patients with ten episodes or more showed slightly higher family morbidity than those with less than ten episodes.The three subtypes of bipolar disorders preponderantly depressed (Dm), nuclear type (MD), and preponderantly manic (Md), showed significant genetic differences. The families of type Dm had the highest morbidity, and families of type Md, the lowest! The type MD took an intermediate position. The results are surprising and not compatible with current hypotheses of multifactorial heredity assuming a continuum from depression to mania with distinct thresholds for the manifestation of unipolar depression, bipolar psychosis, and pure mania. The findings also do not suggest the existence of a drug-induced hypomania.Father-son transmission was frequent, and this fact excludes a substantial amount of X-chromosomal inheritance.Parents, siblings, and children exhibited roughly the same morbidity risk. If a proband had an affected parent, the morbidity risk for his siblings and children was nearly twice as high as without such a parent (38% vs 21%). The analysis of the intrafamilial distribution of diagnoses supported the assumption that neurotic depression belongs to the true spectrum of affective psychoses.     

A Physiology-Based Seizure Detection System for Multichannel EEG

Background

Epilepsy is a common chronic neurological disorder characterized by recurrent unprovoked seizures. Electroencephalogram (EEG) signals play a critical role in the diagnosis of epilepsy. Multichannel EEGs contain more information than do single-channel EEGs. Automatic detection algorithms for spikes or seizures have traditionally been implemented on single-channel EEG, and algorithms for multichannel EEG are unavailable.

Methodology

This study proposes a physiology-based detection system for epileptic seizures that uses multichannel EEG signals. The proposed technique was tested on two EEG data sets acquired from 18 patients. Both unipolar and bipolar EEG signals were analyzed. We employed sample entropy (SampEn), statistical values, and concepts used in clinical neurophysiology (e.g., phase reversals and potential fields of a bipolar EEG) to extract the features. We further tested the performance of a genetic algorithm cascaded with a support vector machine and post-classification spike matching.

Principal Findings

We obtained 86.69% spike detection and 99.77% seizure detection for Data Set I. The detection system was further validated using the model trained by Data Set I on Data Set II. The system again showed high performance, with 91.18% detection of spikes and 99.22% seizure detection.

Conclusion

We report a de novo EEG classification system for seizure and spike detection on multichannel EEG that includes physiology-based knowledge to enhance the performance of this type of system.     

An avian model of genetic reflex epilepsy

The Fayoumi strain of chickens (Fepi) carries a recessive autosomal gene mutation in which homozygotes are afflicted with a photogenic and audiogenic reflex epilepsy. Seizures consist of stimulus-locked motor symptoms followed by generalized self sustained convulsions. EEG recordings show spikes and spike and waves patterns at rest which are suppressed during seizures and replaced by a desynchronized pattern of activity. Neurones of the prosencephalon discharge in bursts at rest, while neurones of the mesencephalon are bursting during seizures. Living neural chimeras were obtained by replacing specific embryonic brain vesicles in a normal chicken embryo with equivalent vesicles from a Fepi donor. These chimeras show that the epileptic phenotype can be totally or partially transferred from the Fepi to the normal chickens. Total transfer of photogenic and audiogenic seizures was obtained by substitution of both the prosencephalon and mesencephalon, while substitution of the prosencephalon alone resulted in transfer of interictal paroxysmal activity and substitution of the mesencephalon alone resulted principally in transfer of ictal motor symptoms. Increased expression of the c-fos protooncogene, as revealed by the western blot technique, confirmed the distinct encephalic localizations of the symptoms of the photogenic and audiogenic reflex epilepsy of the Fepi shown with the methods of electrophysiology and brain chimeras. We conclude that the Fepi is a good model of brain stem reflex epilepsy and suggest that the brain stem is a generator of some other animal and human genetic reflex "epileptic syndromes".     

A clinical and molecular genetic analysis of the fragile X syndrome

Results of phenotypical, patho-psychological and molecular-genetic analysis of the 53 probands with clinical features of the fragile X syndrome and 10 female carriers are presented. The clinical heterogeneity, diagnostic criteria, methods of genetic risk estimation, perspectives of prevention of this disease are discussed.     

Genetic relationship of catalepsy to penduliform movements and audiogenic epilepsy in rats

Within outbred Wistar stock, the pendulum movements are found to be inherited in what may be considered as a dominant mono- or oligogenic mode of inheritance with incomplete penetrance. This indicates that the albinism only permits the manifestation of the pendulum movements, which are also controlled by some other gene or genes. The pendulum movements show a positive genetic relation to catalepsy, although this relation is not strong: the proportion of animals with pendulum movements is 23% in the control population and 32% in F12-F16 bred for catalepsy (p less than 0.05). Within the latter, the proportion of animals with pendulum movements was 43% in the progeny of parents with phenotypically expressed catalepsy, and 29% in the progeny of phenotypically "normal" animals (p less than 0.01). The frequency of audiogenic seizures was 32% in the control population and 17% in F8-F16 bred for catalepsy (p less than 0.001). A genetic model is proposed to account for the paradoxical situation, where pendulum movements have a positive genetic relation both to catalepsy and audiogenic epilepsy, the catalepsy being at the same time negatively related to epilepsy.     

Persistence of Cortical Sensory Processing during Absence Seizures in Human and an Animal Model: Evidence from EEG and Intracellular Recordings

Absence seizures are caused by brief periods of abnormal synchronized oscillations in the thalamocortical loops, resulting in widespread spike-and-wave discharges (SWDs) in the electroencephalogram (EEG). SWDs are concomitant with a complete or partial impairment of consciousness, notably expressed by an interruption of ongoing behaviour together with a lack of conscious perception of external stimuli. It is largely considered that the paroxysmal synchronizations during the epileptic episode transiently render the thalamocortical system incapable of transmitting primary sensory information to the cortex. Here, we examined in young patients and in the Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a well-established genetic model of absence epilepsy, how sensory inputs are processed in the related cortical areas during SWDs. In epileptic patients, visual event-related potentials (ERPs) were still present in the occipital EEG when the stimuli were delivered during seizures, with a significant increase in amplitude compared to interictal periods and a decrease in latency compared to that measured from non-epileptic subjects. Using simultaneous in vivo EEG and intracellular recordings from the primary somatosensory cortex of GAERS and non-epileptic rats, we found that ERPs and firing responses of related pyramidal neurons to whisker deflection were not significantly modified during SWDs. However, the intracellular subthreshold synaptic responses in somatosensory cortical neurons during seizures had larger amplitude compared to quiescent situations. These convergent findings from human patients and a rodent genetic model show the persistence of cortical responses to sensory stimulations during SWDs, indicating that the brain can still process external stimuli during absence seizures. They also demonstrate that the disruption of conscious perception during absences is not due to an obliteration of information transfer in the thalamocortical system. The possible mechanisms rendering the cortical operation ineffective for conscious perception are discussed, but their definite elucidation will require further investigations.     

Segregation analysis of cryptogenic epilepsy and an empirical test of the validity of the results.

We used POINTER to perform segregation analysis of cryptogenic epilepsy in 1,557 three-generation families (probands and their parents, siblings, and offspring) ascertained from voluntary organizations. Analysis of the full data set indicated that the data were most consistent with an autosomal dominant (AD) model with 61% penetrance of the susceptibility gene. However, subsequent analyses revealed that the patterns of familial aggregation differed markedly between siblings and offspring of the probands. Risks in siblings were consistent with an autosomal recessive (AR) model and inconsistent with an AD model, whereas risks in offspring were inconsistent with an AR model and more consistent with an AD model. As a further test of the validity of the AD model, we used sequential ascertainment to extend the family history information in the subset of families judged likely to carry the putative susceptibility gene because they contained at least three affected individuals. Prevalence of idiopathic/cryptogenic epilepsy was only 3.7% in newly identified relatives expected to have a 50% probability of carrying the susceptibility gene under an AD model. Approximately 30% (i.e., 50% x 61%) were expected to be affected under the AD model resulting from the segregation analysis. These results suggest that the familial distribution of cryptogenic epilepsy is inconsistent with any conventional genetic model. The differences between siblings and offspring in the patterns of familial risk are intriguing and should be investigated further.     

A multi-context learning approach for EEG epileptic seizure detection

Background

Epilepsy is a neurological disease characterized by unprovoked seizures in the brain. The recent advances in sensor technologies allow researchers to analyze the collected biological records to improve the treatment of epilepsy. Electroencephalogram (EEG) is the most commonly used biological measurement to effectively capture the abnormalities of different brain areas during the EEG seizures. To avoid manual visual inspection from long-term EEG readings, automatic epileptic EEG seizure detection has become an important research issue in bioinformatics.

Results

We present a multi-context learning approach to automatically detect EEG seizures by incorporating a feature fusion strategy. We generate EEG scalogram sequences from the EEG records by utilizing waveform transform to describe the frequency content over time. We propose a multi-stage unsupervised model that integrates the features extracted from the global handcrafted engineering, channel-wise deep learning, and EEG embeddings, respectively. The learned multi-context features are subsequently merged to train a seizure detector.

Conclusions

To validate the effectiveness of the proposed approach, extensive experiments against several baseline methods are carried out on two benchmark biological datasets. The experimental results demonstrate that the representative context features from multiple perspectives can be learned by the proposed model, and further improve the performance for the task of EEG seizure detection.