A total of 170 patients with Intellectual Disability and epilepsy and 175 healthy controls were recruited at different hospitals and clinics of Rawalpindi between December 2017 and November 2019. Online calculator was used to calculate the sample size. (http://www.calculator.net/sample-size-calculator.html; World Health Organization (WHO) protocol). All patients were diagnosed and interviewed by neurologic clinicians. Patients were categorised into two categories. Children aged 13 years and less diagnosed with epilepsy and/or intellectual disability and adults aged 18 years above diagnosed with epilepsy and/or intellectual disability were included. Patients without a clear diagnosis of epilepsy and/or intellectual disability were excluded. The exclusion criteria included seizure frequency, hypoxia, prenatal infection, trauma, and accidental diseases. Only an individual without any other nervous system diseases and is with developmental retardation, or family history of intellectual disability and/or epilepsy was eligible for inclusion in the control group. The procedures of this study were approved by the department of Biosciences, Comsats University Islamabad Ethics Committee. Written informed consent was obtained from all guardians of the participants in the study. The clinical information of cases including gender, age, age at onset, disease diagnosis, family history of ID and epilepsy, perinatal and neonatal complications, neurologic and developmental conditions, associated disorders, affected siblings were collected. Participants missing the above-mentioned clinical data were excluded from this study. The participants (n = 170) were further grouped into three categories based on clinical diagnosis: ID only (n = 74), ID with EPI (n = 52), EPI only (n = 44) The neurologic comorbidities included cerebral palsy, microcephaly, Down’s syndrome, anxiety, insomnia, and seizures. Moody or fixed behaviour, interests, and activities stand for impairment in interaction and communication with other individuals. Qualitative assessment of these characteristics was compared to mental age. The developmental comorbidities in this study included speech disorders, dyslexia, delayed development, ADHD, and ASD.
- SNP Selection and Genotyping:
The phenol chloroform technique was used to extract genomic DNA from two millilitres of peripheral blood collected in EDTA tubes (Huang et al., 2015). Two single nucleotide polymorphisms rs147815978 and rs2710102 in CNTNAP2 were targeted and selected by in silico analysis. Primers were designed by the online tool primer3 for tetra primers-amplification refractory mutation system polymerase chain reaction ARMS-PCR. Genotyping of all polymorphisms was conducted using primers of CNTNAP2 rs147815978 and rs2710102 shown in Table 1. The genotyping in 170 individuals with disease as well as their healthy and normal controls was done using the tetra primers-amplification refractory mutation system-PCR method to amplify the targeted SNP regions.
Table 1:
Sequences of primers used for genotyping.
CNTNAP2rs2710102
Forward inner primer (A allele): Melting temperature
476 GCCTTTTTGTTTTTCCTTCTTTCGCA 501 67
Reverse inner primer (G allele):
529 CCGATTGGTTAACATTTACTCTGAGAACC 501 65
Forward outer primer (5' - 3'):
245 GAAAAAAGTGGTAGCCAGTCAGGTTAGC 272 66
Reverse outer primer (5' - 3'):
722 AGGGCACAAAATGGATGAGTGATAGAAT 695 66
Product size for A allele: 248
Product size for G allele: 285
Product size of two outer primers: 478
CNTNAP2rs147815978
Forward inner primer (G allele): Melting temperature
475 GTCTCCTGGTCTTCAGTCACTTTGTGG 501 67
Reverse inner primer (T allele):
526 TCAATCTCCACATTGCCCAAATTGTA 501 67
Forward outer primer (5' - 3'):
345 AGCTTTTCTTGTGTGGAACCCTATACGG 372 67
Reverse outer primer (5' - 3'):
674 CCAAACAAAGCACAACATTAACTCTGGA 647 67
Product size for G allele: 201
Product size for T allele: 182
Product size of two outer primers: 330
Data were expressed for CNTNAP2 rs147815978 and rs2710102 as dominant, heterozygous, and recessive categories for patients and controls based on their comorbidity with intellectual disability and epilepsy. Demographic variables were ethnicity, age group, gender, and other associated diseases. Percentage of variables was calculated for demographic data. (Table 2). Statistical analyses were performed using GraphPad prism software. Odds ratio (OR) was calculated for 95% Cl for CNTNAP2 polymorphisms rs147815978 (alleles GG, GT, and TT) and for rs2710102 (alleles AA, AG, and GG). P-values less than 0.05 were statistically significant. The differences in frequency distributions of genotypes between controls and cases and between patients with and without neurologic and developmental comorbidities were assessed by chi-square test. Association of the targeted SNPs with comorbidity of ID and EPI was calculated and the difference in frequencies of genotypes between patients and control group were analysed by chi-square test for categorical data. The chi-square test was used to assess the deviation from Hardy–Weinberg equilibrium. P-values less than 0.05 were statistically significant. Analysis of variance (ANOVA) was performed to evaluate the significance of difference between the means of both the SNPs in case and control groups for CNTNAP2 gene.