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

Abstract

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.

Disruption of MET Receptor Tyrosine Kinase, an Autism Risk Factor, Impairs Developmental Synaptic Plasticity in the Hippocampus

“…The highly selective regional expression of MET in developing limbic structures is consistent with its role in wiring circuits involved in higher cognitive, social, and emotional function. The role of MET in ASD is further supported by the findings that a large number of ASD risk genes are related to growth factor signaling (Wittkowski et al ., ), converge to regulate brain growth trajectories (Levitt and Campbell, ; Berg and Geschwind, ), and coalesce with other functional ASD gene networks involving cortical glutamatergic projection neurons (Voineagu et al ., ; Parikshak et al ., ).…”

“…This risk allele also correlates with atypical patterns of human brain activity in response to social stimuli, as fMRI measurement indicates reduced structural and functional connectivity in temporoparietal lobes (Rudie et al, 2012), areas express high levels of MET protein (Judson et al, 2011a). The human MET gene transcription is also regulated by FOXP2 and MeCP2 (Mukamel et al, 2011;Plummer et al, 2013), factor known to affect ASD-related circuits development in humans (Konopka et al, 2009;Wood et al, 2009). These findings suggest that MET signaling engages biological processes highly relevant to the ASD pathogenesis.…”

Auditory Processing Enhancements in the TS2-Neo Mouse Model of Timothy Syndrome, a Rare Genetic Disorder Associated with Autism Spectrum Disorders

“…Disruption of synapses and signal transmission that alters neuronal connectivity in the brain could in turn mediate functional changes associated with ASD (Auerbach, Osterweil & Bear, 2011; Hahamy, Behrmann, & Malach, 2015). Recent pathway network analyses, coupled with genome-wide association studies of autism, reveal the calcium signaling pathway to be the most affected, suggesting that it is highly involved in the molecular basis of ASD (Skafidas et al, 2014; Wen, Alshikho & Herbert, 2016; Wittkoski et al, 2014). Genes associated with calcium channels modulate neuronal function by mediating influx of calcium into neurons (and thus neurotransmitter release), intracellular signaling, and gene transcription.…”

Complex polymorphisms in endocytosis genes suggest alpha-cyclodextrin as a treatment for breast cancer

“…In this analysis, conventional single-SNP GWAS (ssGWAS) are complemented with a computational biostatistics approach (muGWAS, GWAS using muStat (Wittkowski 2012) ) that incorporates knowledge about genetics into the method (Wittkowski 2010, Sections 4.3.4 and 4.4.2;Wittkowski 2013) and knowledge about the nature of GWAS into the decision strategy. (Wittkowski 2014) Statistical methods tend to have higher power if they are based on more realistic assumptions, which, in biology, tend to be weak. In contrast, methods based on stronger assumptions, such as additivity of allelic effects and independence of SNPs within an linkage disequilibrium (LD) block (LDB), may generate more significant results when errors happen to fulfill these assumptions than for true effects.…”

“…Here, we replace a fixed cut-off for GWS with an empirical (Aslibekyan 2013a) adaptive (study-specific) cut-off (aGWS) that automatically accounts for the specifics of the population studied, the chip used, differences in minor allele frequency (MAF,) and GWAS being non-randomized. (Wittkowski 2014) As previously discussed, (Wittkowski 2014) the expected distribution in a ssGWAS QR plot is a mixture of univariate distributions whose carriers vary by MAF, because the most significant result possible depends on MAF when outcomes are bounded (allele counts 0, 1, 2). Hence, it is a convex curve, rather than a straight line; (Wittkowski 2014) see, for instance, CGEM chromosomes 14-17, 19, and 22 (S1 Fig 2).…”