Genetic Association and Functional Prediction of PTEN and TSC1 3'UTR Variants in Autism Spectrum Disorder Among...

ASD etiology may be influenced by non-coding single-nucleotide polymorphisms (SNPs) in 3' untranslated regions (3'UTRs). These variations can affect post-transcriptional regulation by altering RNA structure and miRNA binding patterns. PTEN and TSC1, two key regulators of the PI3K/AKT/mTOR signaling pathway, are promising candidate genes for ASD. We performed a case-control study involving 108 individuals diagnosed with ASD and 184 healthy matched controls from the Tunisian population. Four specific 3'UTR SNPs (PTEN: rs701848, rs34140758; TSC1: rs739442, rs2809244) were analyzed through genotyping. Statistical associations were assessed using various genetic inheritance models, with multivariate logistic regression adjusting for gender, family psychiatric history, and parental age. A thorough bioinformatics approach was applied, which included miRNASNP-v3 for predicting altered miRNA binding sites, RNAhybrid for calculating the minimum free energy (MFE) of miRNA-mRNA duplexes, PhyloP and phastCons for evolutionary conservation analysis, and mfold for modeling RNA secondary structures. PTEN rs701848 showed a significant statistical association with ASD risk that remained significant after correction for multiple testing (corrected p < .0004), while TSC1 rs739442 showed a suggestive association (p = .009, corrected p = .036). Systematic functional assessment using multi-criteria evaluation identified rs701848 as having high predicted functional impact (extensive miRNA binding changes, including loss of neurodevelopmental miR-129 sites, high conservation (PhyloP = 2.24), and altered RNA stability), while rs739442 showed moderate impact, and rs2809244 minimal predicted functional significance. For mutant alleles, RNA structure modeling showed slight decreases in mRNA stability, which might affect transcript accessibility to regulatory factors. Evolutionary conservation analysis demonstrated that rs701848 and rs34140758 reside in highly conserved areas, whereas rs739442 and rs2809244 are in less evolutionarily conserved regions. By integrating population-genetics data with bioinformatics predictions, this study supports the relevance of non-coding SNPs as biological risk factors for ASD. It emphasizes their functional significance in modulating post-transcriptional gene regulation mechanisms.