Comorbid Analysis of Genes Associated with Autism Spectrum Disorders Reveals Differential Evolutionary Constraints

Abstract

The burden of comorbidity in Autism Spectrum Disorder (ASD) is substantial. The symptoms of autism overlap with many other human conditions, reflecting common molecular pathologies suggesting that cross-disorder analysis will help prioritize autism gene candidates. Genes in the intersection between autism and related conditions may represent nonspecific indicators of dysregulation while genes unique to autism may play a more causal role. Thorough literature review allowed us to extract 125 ICD-9 codes comorbid to ASD that we mapped to 30 specific human disorders. In the present work, we performed an automated extraction of genes associated with ASD and its comorbid disorders, and found 1031 genes involved in ASD, among which 262 are involved in ASD only, with the remaining 779 involved in ASD and at least one comorbid disorder. A pathway analysis revealed 13 pathways not involved in any other comorbid disorders and therefore unique to ASD, all associated with basal cellular functions. These pathways differ from the pathways associated with both ASD and its comorbid conditions, with the latter being more specific to neural function. To determine whether the sequence of these genes have been subjected to differential evolutionary constraints, we studied long term constraints by looking into Genomic Evolutionary Rate Profiling, and showed that genes involved in several comorbid disorders seem to have undergone more purifying selection than the genes involved in ASD only. This result was corroborated by a higher dN/dS ratio for genes unique to ASD as compare to those that are shared between ASD and its comorbid disorders. Short-term evolutionary constraints showed the same trend as the pN/pS ratio indicates that genes unique to ASD were under significantly less evolutionary constraint than the genes associated with all other disorders.

Potential identification of vitamin B6 responsiveness in autism spectrum disorder utilizing phenotype variables and machine learning methods

“…Of the five clusters, cluster 1 consisted of all persons who responded to vitamin B6. Although we could not identify meaningful characteristics of the other four clusters (clusters 2 to 5), the AP analysis suggested that persons with ASD may be highly heterogeneous, as previously reported 9 .…”

“…Previous attempts to evaluate the efficacy of vitamin B6 in treating persons with ASD have failed to produce consistent findings 4 – 8 . ASD is highly heterogeneous 9 , and identifying a subgroup of persons who may show responsiveness to vitamin B6, if any, is important.…”

The Relevance of Variants With Unknown Significance for Autism Spectrum Disorder Considering the Genotype–Phenotype Interrelationship

“…As most clinical cases are associated with a broad spectrum of developmental delay and autistic features, it is also critical to apply a comprehensive genetic analysis approach to increase performance and diagnostic yield. One of the main reasons for the unfeasibility of the genetic panels for ASD is because of the variety of genetic profiles and phenotype diversity in the spectrum, contributing to the popularization of WES and WGS (26). WGS is an ideal option to analyze ASD genotypical variety and complexity, not only due to the possibility of investigating the important regulatory intergenic region (27, 28), but also because of improved sequence coverage comparing to WES low coverage regions affecting essential ASD-related genes (16, 29, 30).…”

Colors of Autism Spectrum: A Single Paradigm Explains the Heterogeneity in Autism Spectrum Disorder

“…Importantly, there are many metabolic and regulatory pathways underlying autism, some of which seem unique to this condition (David et al, 2016a). The quest to discover causality relations, including the necessary and sufficient conditions, is difficult.…”