Molecular diagnosis of autism spectrum disorder through whole exome sequencing - Almeida, Tatiana Ferreira de (2018)
Autism spectrum disorder (ASD) is a neurodevelopment disorder characterized by impairment in communication skills, behavior and social interactions that affects around 1-2% worldwide. To date the etiology of ASD has not yet been fully understood, but in the last 18 years many advances have been made to understand the genetic component related to the development of the clinical phenotype. With the advent of genomic scan analysis such as chromosome analysis by microarray and whole exome sequencing (WHE) many advances have been made to understand the pathophysiology of the disease. About 10-15% of the cases can be explained by large losses or gains (deletions or duplications greater than 1000 base pairs) of the genetic material, which generally involve the disruption of one or more genes. Next generation sequencing methodologies were fundamental in the description of point mutations and small insertions and deletions associated with ASD. The WES has allowed many discoveries to be made about new candidate genes and mechanisms for the development of the disease. It is now claimed that de novo (non-inherited) and likely gene disruptive mutations, such as loss-of-function and non-synonymous changes with high prediction of damage by computational tools, in genes related to neurodevelopment are a major contributor to the disease mechanism. However, these mutations, in addition to not explaining the majority of cases, are rarely recurrent in the population, which makes it difficult to establish a definitive molecular diagnosis for most patients. WES is already a practice in clinical genetics laboratories and demonstrates high effectiveness for diseases that follow a Mendelian pattern of inheritance, and have an established genetic cause. In clinical practice WES is requested for cases of ASD, despite having different modes of inheritance and having more than 1,000 genes associated with the disease. Due to these characteristics the analysis of WES for ASD is a major challenge for the clinical laboratory. This study proposes the construction of a computerized WES analysis routine that can test different candidate genes for their sensitivity and specificity for the detection of affected individuals. The proposed approach consists in the counting of variants separated by their possible protein damage and population frequency for each individual from affected and control groups, this study analyzed 168 WES, being 49 with ASD and 119 controls. After counting formulation, these values are subjected to a sequence of statistical tests, seeking a significant difference in the amount of mutations of all the variants alone, loss-of-function or damaging missense mutations, and the application of models of multivariate analysis such as: logistic regression, decision tree, neural network, vector support machine and principal component analysis for the elaboration of more complex models for disease development. A total of 21 lists of genes were tested, of which 19 presented at least one significant result, and the analysis of variants alone was the one that obtained the largest number of significant events. From apparently protective variants (higher number in the control group), such as the missense variants in RAS/MAPK pathway as variants of stopgain with population frequency above 0.05 in chromatin genes in greater number in individuals with ASD. None of the multivariate analysis models had significant discrimination results between the two groups. Due to the small sample size, the results of this study should be interpreted with limitations, and it is necessary to replicate these scenarios in other databases. However, these findings suggest that different types and frequencies of variants may have distinct contributions to disease development depending on the genes analyzed, rather than complex relationships between variants of the same gene list