A novel computational biostatistics approach implies impaired dephosphorylation of growth factor receptors as associated with severity of autism

作者：Wittkowski K M^*; Sonakya V; Bigio B; Tonn M K; Shic F; Ascano M Jr; Nasca C; Gold Von Simson G

来源：Translational Psychiatry, 2014, 4(1): e354.

DOI：10.1038/tp.2013.124

• genetics
• autism
• epilepsy
• computational biostatistics
• genome-wide significance
• genome-wide association studies
• minor allele frequency

The prevalence of autism spectrum disorders (ASDs) has increased 20-fold over the past 50 years to >1% of US children. Although twin studies attest to a high degree of heritability, the genetic risk factors are still poorly understood. We analyzed data from two independent populations using u-statistics for genetically structured wide-locus data and added data from unrelated controls to explore epistasis. To account for systematic, but disease-unrelated differences in (non-randomized) genome-wide association studies (GWAS), a correlation between P-values and minor allele frequency with low granularity data and for conducting multiple tests in overlapping genetic regions, we present a novel study-specific criterion for 'genome-wide significance'. From recent results in a comorbid disease, childhood absence epilepsy, we had hypothesized that axonal guidance and calcium signaling are involved in autism as well. Enrichment of the results in both studies with related genes confirms this hypothesis. Additional ASD-specific variations identified in this study suggest protracted growth factor signaling as causing more severe forms of ASD. Another cluster of related genes suggests chloride and potassium ion channels as additional ASD-specific drug targets. The involvement of growth factors suggests the time of accelerated neuronal growth and pruning at 9-24 months of age as the period during which treatment with ion channel modulators would be most effective in preventing progression to more severe forms of autism. By extension, the same computational biostatistics approach could yield profound insights into the etiology of many common diseases from the genetic data collected over the last decade.

• 出版日期2014-1