|Year : 2018 | Volume
| Issue : 3 | Page : 308-312
Prevalence of unrecognized autism spectrum disorders in epilepsy: A clinic-based study
Monica Juneja, Suchit Gupta, Abhinav Thakral
Department of Paediatrics, Maulana Azad Medical College and Associated Lok Nayak Hospital, New Delhi, India
|Date of Web Publication||7-Sep-2018|
Dr. Suchit Gupta
196, Surya Niketan, Delhi 110092
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Objective: To assess prevalence of unrecognized autism spectrum disorders (ASDs) in children with epilepsy using Diagnostic and Statistical Manual IV (DSM-IV) criteria and to evaluate factors affecting it in this population. It was a cross-sectional study conducted at a teaching hospital. It included randomly selected 106 children in the age 4–12 years with epilepsy, and without any structural anomaly identifiable on computed tomography/magnetic resonance imaging. Children already diagnosed with ASD were excluded. Materials and Methods: Detailed clinical evaluation was carried out. Intelligence quotient (IQ) was assessed using Development Profile-II for all and Binet and Kulshrestha test, wherever possible. Participants were screened using Social Communication Questionnaire (SCQ). Those with SCQ score of ≥15 were evaluated for ASD using DSM-IV criteria. Childhood Autism Rating Scale was administered to assess the severity of autism. Data were analyzed with univariate and logistic regression analyses. Results: A total of nine children were screened positive, of them, eight were diagnosed with ASD using DSM-IV criteria. The prevalence of unrecognized ASD was 7.5/100. On univariate analysis, intellectual disability (P < 0.01) and young age of onset of epilepsy (P = 0.03) were significantly associated with ASD. On multivariable analysis, only intellectual disability was significantly associated with ASD (P < 0.01). There was no significant association with gender, seizure type, frequency of seizures, intractability of epilepsy, or the number of antiepileptic drugs used. Conclusion: ASDs are more prevalent in children with epilepsy than in general population. In cases with associated intellectual disability, co-occurrence of ASD is further increased. All children with epilepsy, particularly those with IQ ≤ 50, irrespective of age of onset of epilepsy, seizure type, frequency of seizures, or intractability of epilepsy, should be screened for ASD.
Keywords: Autism, DSM-IV, epilepsy, intellectual disability
|How to cite this article:|
Juneja M, Gupta S, Thakral A. Prevalence of unrecognized autism spectrum disorders in epilepsy: A clinic-based study. J Pediatr Neurosci 2018;13:308-12
| Introduction|| |
Autism spectrum disorders (ASDs) are complex neurodevelopmental disorders with behavioral impairments characterized by deficits in social communication skills and restrictive, repetitive behaviors, and interests. Globally, the prevalence of autism ranges from 1 to 189 per 10,000 children with a median of 62 per 10,000. Data from India are limited to a few clinic-based studies and a recent community-based survey in 1- to 10-year-old children from northwest India, which found prevalence to be 0.9 per 1000.
Autism is a neurodevelopmental disorder with many possible etiologies. Evidence suggests that both epilepsy and ASD arise from abnormal excitability and disrupted synaptic plasticity in the developing brain. This abnormal plasticity can result from genetic conditions. In addition, development of epilepsy and/or seizures during early postnatal development may alter synaptic plasticity and contribute to ASD. High frequency of autism in some of the early-onset developmental encephalopathic epilepsies is frequently cited as an evidence of the relationship between autism and epilepsy. In a prospective study of 95 children with onset of epilepsy in the first year of life, 13.7% developed ASD, particularly those with West syndrome (46%) and those whose seizures were associated with brain insults (69%). Two large prospective studies with respective sample sizes of 453 and 555 have found that approximately 4% and 5% of children with epilepsy had ASD., A retrospective study of a prevalent sample of individuals identified in a pediatric neurology clinic also found that 15% of patients met Diagnostic and Statistical Manual IV (DSM-IV) criteria for ASD. Conversely, there is an increased but variable risk of epilepsy in children with autism, with a prevalence of 5% to 38%.
Though there are many studies from developed world on the prevalence of ASD in children with epilepsy, there is no such published literature from India; hence, this study was conducted to assess the prevalence of unrecognized ASDs in children with epilepsy using DSM-IV criteria and to evaluate the factors affecting the prevalence of ASD in this population.
| Materialsand Methods|| |
This study was a cross-sectional study conducted in children in the age group of 4–12 years, attending the neurology clinic of a tertiary care hospital between 2008 and 2009. A sample of 100 children was needed to get a prevalence of 30% with an error of ±10% with 95% confidence interval (CI) level; the study enrolled 106 children. A prevalence of 30% was presumed on the basis that certain studies, reported prevalence up to 32%–37%. The children with epilepsy (defined as two or more epileptic seizures unprovoked by any immediate identifiable cause) and without any structural anomaly identifiable on computed-tomography/magnetic resonance imaging were randomly selected using the standard random number tables. The children who already had a diagnosis of ASD were not included in the study.
The study was approved by the institutional ethics committee and consent was obtained from the parents.
Materials and methods
A detailed history was taken, and the children were clinically examined. Development Profile-II test was administered in all children, and Binet and Kulshrestha test was administered, wherever possible, to assess the intelligence quotient (IQ). The children were screened using Social Communication Questionnaire (SCQ). The children who had SCQ score of ≥15 were taken as screen positive for the purpose of study, and they underwent detailed evaluation in Child Development Clinic comprising a semi-structured interview regarding child’s development and behavior, focusing on socialization, communication, restricted interest, and presence of stereotyped behaviors and activities for making diagnosis of ASD using the DSM-IV criteria. Apart from this, a detailed medical, perinatal, family, and treatment history was also obtained, and Childhood Autism Rating Scale (CARS)  was administered to assess the severity of autistic features.
Statistical analysis was carried out using Statistical Package for the Social Science (SPSS) software, IBM. Nonparametric data were analyzed using the Mann–Whitney U test. Proportions were analyzed using the chi-square test and Fisher’s exact test. Multivariable analysis was carried out using a forward conditional multiple logistic regression model. All variables, irrespective of statistical significance on univariate analysis, were included in the model.
| Results|| |
The baseline population characteristics are summarized in [Table 1]. Age distribution was almost equal in different groups (4–6, 7–9, and 10–12 years) with a median of 108 months. History of developmental delay was present in 26.4% and speech delay in 1.8%. Most of the children (60.4%) were from the upper-lower socioeconomic status, and none of them were from the upper socioeconomic status, as per modified Kuppuswamy classification. A total of 21.7% of the children had normal IQ, whereas 36.8% had borderline intelligence. Mild intellectual disability (ID) was present in 18.9% of the cases, and 22.6% had an IQ of ≤50. There were no children with developmental regression. A total of 47 children had abnormal electroencephalography records. One case had fragile X syndrome and two had Lennox–Gastaut syndrome.
Of 106 children, 9 (8.4%) were screen positive by the SCQ. Of the screen positive children, eight were diagnosed with ASD, based on DSM-IV criteria [Figure 1]. The prevalence of unrecognized ASD was 7.5 per 100 cases of epilepsy in this study. Three cases had severe autism and three had mild-to-moderate autism on the basis of CARS score. Two children had Pervasive Developmental Disorder Not Otherwise Specified (PDD-NOS). The comparison of characteristics of the children with and without ASD, along with univariate analysis, has been presented in [Table 2].,
On multivariable analysis, only ID was found to be significantly associated with ASD (odds ratio [OR], 33.3; 95% CI, 3.8–289.0; P < 0.01).
| Discussion|| |
In this clinic-based study, the prevalence of unrecognized autism in epilepsy was found to be 7.5 per 100, which was significantly higher than that in the general population of 0.9 per 1000 from India.
The results of this study are similar to those of a study conducted in 573 subjects with refractory epilepsy admitted in a residential rehabilitation and epilepsy unit in which behavioral and neuropsychological profiles documented ASD in 8% of the study population. Another retrospective clinic-based study from Japan reported a prevalence of 15% in a population of 519 children with epilepsy, whereas a study of ASD from a tertiary care center in Toronto found the prevalence to be 32%. In this study, autism was diagnosed using only SCQ, which is a screening tool only, and no further evaluation was carried out for making the diagnosis. Also, clinic-based studies in general tend to report a higher prevalence because of referral bias.
Community-based studies report a varying prevalence of autism in epilepsy, but in general, the reported prevalence is lower than that of the clinic-based studies. A prospective study from Connecticut reported a prevalence of 5% in a population of 555 children with epilepsy. A community-based study from Iceland found that of 95 children with unprovoked seizures in the first year of life, 13.7% had ASD. A possible explanation for the higher prevalence in this study could be that the onset of seizures was in the first year of life in the study population, thereby contributing to a higher representation of early-onset epileptic encephalopathies, which in turn are known to have a higher association with ASD. Another population-based survey of mental health problems of children with epilepsy from the United Kingdom reported that of the 67 children with epilepsy, 4 were diagnosed with ASD on the basis of DSM-IV criteria, giving a prevalence of 5.9%. The prevalence, however, was found to be 37% in a similar study from Sweden, the higher prevalence of ASD in this Swedish study could be due to all the children that had ID along with epilepsy, which itself is associated with increased risk of ASD.
Epilepsy and ID commonly coexist, and it has been suggested that the prevalence of epilepsy in individuals with ASD and of ASD in epilepsy is accounted for by the degree of ID. In a meta-analysis of studies from 1963 to 2006, the pooled prevalence of epilepsy was 21.5% in ASD individuals with ID, whereas it was 8% in those having ASD without ID. Conversely, in children with epilepsy, ID is a significant predictor of ASD. The findings of this study are in agreement with these observations, wherein ID was found to be strongly associated with ASD. The prevalence of autism in the group with IQ ≤ 50 (29.7%) was much higher than that in the group with IQ > 50 (1.2%), and this difference was statistically significant (P = 0.0004). Also, all children with ASD had ID, and the overall prevalence of ASD in those with ID was 17.3%.
Another factor that has been found to be significantly associated with the risk of ASD is the mean age of onset of seizures. This study also found that the mean age of onset of seizure in the ASD group (36.3 months) was lower as compared to that of the non-ASD group (63.6 months), and the mean ranks were significantly different on univariate analysis (P = 0.03); however, in the multivariable model, ID was found to be the only significant risk factor for ASD, and there was no significant association with age of onset of seizures. In other words, younger age at onset of epilepsy had no independent association with ASD, and the results on univariate analysis may be explained by the association of young age of onset of epilepsy with ID. Similar results have been reported in a prospective community-based study, which did not find young age of onset of epilepsy to be a significant independent risk factor for ASD. This was in contrast to the Swedish study that found a higher age of onset of seizures in the ASD vs. non-ASD group (2.2 vs. 0.9 years). This may be explained by the overrepresentation of children with cerebral palsy and ID in the non-ASD group in this particular study.
Similar to the results of other studies,,, this study found no statistically significant difference in the predominant seizure type, seizure frequency, and the number of antiepileptic drugs prescribed. The difference in sex distribution between the ASD and non-ASD groups in this study was also not statistically significant. Though one study has found male gender to be associated with ASD in epilepsy, another has not found gender to be a significant factor.
The present study, to the best of our knowledge, is the first of its kind in India. Extensive review of published literature could not find any work related to prevalence of ASD in epilepsy from India. However, this study has certain limitations. Potential concerns include the use of SCQ, which being a questionnaire, is based on respondent judgments and not on investigator concepts. The sensitivity and specificity of SCQ in Indian population is not known. This study found that all the children with ASD had ID, none had normal cognitive abilities. In contrast, a community-based study of autism in epilepsy has found that 2.2% of its participants with normal cognitive abilities had autism. There could be several possible explanations for why this study found no child with ASD and normal cognitive ability. The SCQ may have missed children with high functioning autism in the Indian context. Moreover, being a clinic-based study, the sample size may not have been sufficient to pick up the children with ASD and normal IQ in contrast to the community-based study. Future studies with larger sample size would be needed to address this issue. Another weakness was that although, the mean age of the population (8 years and 7 months) was somewhat younger than that of the other studies (10 to 12.7 years,,,), this study could not enroll children below 4 years of age, as the SCQ can be applied only to subjects of age 4 years and above, provided that the mental age exceeds 2 years. Thus, the study had a lower representation of subjects with early-onset developmental encephalopathic epilepsies, which have higher association with ASD. Finally, being conducted in a tertiary care center, the study may have referral bias. The sex distribution of our study group showed a male-to-female ratio of 3:1, whereas epidemiologic studies of epilepsy report that the incidence and prevalence are only slightly higher in boys than girls. The difference could be explained by a referral bias in favor of boys.
| Conclusion|| |
In conclusion, ASDs are more prevalent in children with epilepsy as compared to general population. In cases of epilepsy and associated ID, the chances of co-occurrence of ASD are further increased. This risk is not related to the age of onset of epilepsy, seizure type, frequency of seizures, or intractability of epilepsy. So, all children with epilepsy and particularly those with IQ ≤ 50 should be screened for the presence of ASD. Further, our findings add to the growing body of evidence that epilepsy, autism, and ID are different clinical manifestations of neurological damage that disrupts the normal neuronal pathways in the developing brain.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Arlington, VA: American Psychiatric Publishing; 2013.
Elsabbagh M, Divan G, Koh YJ, Kim YS, Kauchali S, Marcín C, et al
. Global prevalence of autism and other pervasive developmental disorders. Autism Res 2012;13:160-79.
Juneja M, Mukherjee S, Sharma S. A descriptive hospital based study of children with autism. Indian Pediatr 2005;13: 453-8.
Raina SK, Kashyap V, Bhardwaj AK, Kumar D, Chander V. Prevalence of autism spectrum disorders among children (1-10 years of age)—findings of a mid-term report from northwest India. J Postgrad Med 2015;13:243-6.
Brooks-Kayal A. Epilepsy and autism spectrum disorders: are there common developmental mechanisms? Brain Dev 2010;13:731-8.
Berg AT, Plioplys S. Epilepsy and autism: is there a special relationship? Epilepsy Behav 2012;13:193-8.
Saemundsen E, Ludvigsson P, Rafnsson V. Risk of autism spectrum disorders after infantile spasms: a population-based study nested in a cohort with seizures in the first year of life. Epilepsia 2008;13:1865-70.
Geerts A, Brouwer O, van Donselaar C, Stroink H, Peters B, Peeters E, et al
. Health perception and socioeconomic status following childhood-onset epilepsy: the Dutch study of epilepsy in childhood. Epilepsia 2011;13:2192-202.
Berg AT, Plioplys S, Tuchman R. Risk and correlates of autism spectrum disorder in children with epilepsy: a community-based study. J Child Neurol 2011;13:540-7.
Matsuo M, Maeda T, Sasaki K, Ishii K, Hamasaki Y. Frequent association of autism spectrum disorder in patients with childhood onset epilepsy. Brain Dev 2010;13:759-63.
Tuchman R, Rapin I. Epilepsy in autism. Lancet Neurol 2002;13:352-8.
American Psychiatric Association. Diagnostic and statistical manual of mental disorders: DSM-IV-TR. Washington, DC: American Psychiatric Association; 2000.
Clarke DF, Roberts W, Daraksan M, Dupuis A, McCabe J, Wood H, et al
. The prevalence of autistic spectrum disorder in children surveyed in a tertiary care epilepsy clinic. Epilepsia 2005;13:1970-7.
Davies S, Heyman I, Goodman R. A population survey of mental health problems in children with epilepsy. Dev Med Child Neurol 2003;13:292-5.
Commission on epidemiology and prognosis, international league against epilepsy. Guidelines for epidemiologic studies on epilepsy. Epilepsia 1993;13:592-6.
Alpern G, Boll T, Shearer M. Developmental profile II. Los Angeles, CA: Western Psychological Services; 1986.
Kulshrestha S. Stanford Binet intelligence scale, Hindi adaptation of 3rd revision. Allahabad, India: Manas Seva Sansthan; 1971. pp. 17-185.
Rutter M, Bailey A, Lord C. Social communications questionnaire. Los Angeles, CA: Western Psychological Services; 2003.
Schopler E, Reichlers R, Rochen R. The childhood autism rating scale. Los Angeles, CA: Western Psychological Services; 1998.
Mishra D, Singh HP. Kuppuswamy’s socioeconomic status scale—a revision. Indian J Pediatr 2003;13:273-4.
Boel MJ. Behavioural and neuropsychological problems in refractory paediatric epilepsies. Eur J Paediatr Neurol 2004;13:291-7.
Steffenburg S, Gillberg C, Steffenburg U. Psychiatric disorders in children and adolescents with mental retardation and active epilepsy. Arch Neurol 1996;13:904-12.
Amiet C, Gourfinkel-An I, Bouzamondo A, Tordjman S, Baulac M, Lechat P, et al
. Epilepsy in autism is associated with intellectual disability and gender: evidence from a meta-analysis. Biol Psychiatry 2008;13:577-82.
Vasconcellos E, Wyllie E, Sullivan S, Stanford L, Bulacio J, Kotagal P, et al
. Mental retardation in pediatric candidates for epilepsy surgery: the role of early seizure onset. Epilepsia 2001;13:268-74.
Koul R, Razdan S, Motta A. Prevalence and pattern of epilepsy (lath/mirgi/laran) in rural Kashmir, India. Epilepsia 1988;13:116-22.
[Table 1], [Table 2]
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