Genetic biomarkers predict susceptibility to autism spectrum disorder through interactive models of inheritance in a Saudi community

Abstract Objective: To determine whether individual or interactive single nucleotide polymorphisms (SNPs) may influence the development of autism spectrum disorder (ASD). Methods: DNA from buccal cells of 212 participants (110 cases and 102 controls) were subjected to TaqMan genotyping of the HTR2A rs7997012, HTR2C rs6318, SLC6A4 rs3813034, ANKK1 rs1800497, and BDNF rs6265 SNPs. The ASD symptoms and severity were assessed by DSM-IV criteria and CARS scores. The SNPStats software was used to determine the best interactive model of inheritance of genotypic data. Results: We found susceptibility in ASD cases when compared with controls in rs7997012 (log-additive), rs6318, and rs3813034 (overdominant) and in 1800497 and rs6265 (recessive) (P< 0.05). Heterozygosity significantly contributed to the risk of ASD for rs6318 and rs3813034 SNPs (56%, P= 0.03 and 89%, P= 0.005, respectively). The rs6318 and rs6265 SNPs were significantly associated with cases with CARS scores ≥37 (recessive) (P= 0.03 and P= 0.05, respectively). Both the rs7997012 and rs6265A variant alleles were strongly associated with ASD cases with CARS scores ≥37 (P= 0.005 and P= 0.003). Conclusions: Our study provides clear evidence of associations between all five examined biomarkers and risk for ASD. Achieving exome analyses for Saudi patients with ASD could enable to identify more genetic variants and candidate genes.