The diagnosis of autism spectrum disorders (ASD) continues to be challenging and depends on neurological and psychological analyses. A number of risk factors and genetic associations with the disorder have been identified. However, work is ongoing to better characterize the genetic basis of ASD, to determine how to identify the risk for ASD, and to design the best therapies for those diagnosed with ASD. Given the high heritability, the genetic etiology of ASD is known. Therefore, genome-wide studies to make associations with ASD are providing new data that, in the future, may help address the current diagnostic and treatment limitations.
Understanding Autism Spectrum Disorders (ASD)
Autism Spectrum Disorders refers to a group of heritable neurodevelopmental disorders that can cause variable symptoms and different degrees of learning and other disabilities. About 1.5% of children (with prevalence in males) in the U.S. have been diagnosed with ASD (1). Each child with ASD has distinct manifestations of the disorder; however, the primary areas of life that can affect children with ASD include behavior, social interaction, and communication.
The primary way ASD is diagnosed is by a medical examination of a child’s development and behavior. Parents and caregivers often notice differences in socialization, and interactions with other children. Adults may also be diagnosed with ASD by observations of the social interaction, behaviors, and other psychological parameters. The diagnosis of ASD is not straightforward, and observed symptoms may be similar to other neurological disorders.
The genetic etiology of ASD is evidenced by its high heritability (80–90 %) (2). Several genetic syndromes are described in ASD including fragile X and Retts syndromes (3). Epigenetic studies indicate an important environmental influence on ASD. Ladd-Acosta et al. conducted genome-wide DNA methylation studies in post-mortem brain specimen and observed two hypomethylation regions located at PRRT1 and C11orf21/TSPAN32 genes (4). Genome-wide association studies (GWAS) have suggested the region between CDH9 and CDH10 on chromosome 5p14.1 (5).
Searching the link between Autism Spectrum Disorders and Genetics
Massively parallel sequencing (or next-generation sequencing) techniques such and whole-exome (WES) and whole-genome sequencing (WGS) have been successfully used to identify a number of Mendelian genetic disorders. These techniques have been applied to identify genetic variants associated with a risk for ASD. For example, Lossifov et al used WES on blood samples from parents and children with and without ASD (6). They found that that 13% of de novo missense mutations contribute to 12% of ASD diagnoses, while 43% of de novo mutations contribute 9% of diagnoses.
The use of NGS has revolutionized the study of genetic etiology of medical disorders and conditions. The unprecedented speed and lower cost allows the collection of data that can be analyzed and archived. The information obtained has the potential to improve early diagnosis and provide clues to creating personalized therapy for those with ASD.
Whole genome sequencing in ASD research is an approach to identify coding and noncoding variants. Given the phenotypic heterogeneity of ASD, the development of a more inclusive data resource may help in the efforts to determine the genetic basis of the phenotypic differences among individuals with ASD. In an Autism Speaks-supported study by Yuen et al., WGS of 85 quartet families was performed to address the need for a comprehensive data resource for ASD. Their results show that a significant percentage (69.4%) of affected siblings carried different ASD-related mutations. This correlated to differential phenotypic presentation in these siblings. The investigators concluded that WGS is crucial to better identify all variants associated with ASD risk.
Both common and rare variants are associated with overall population risk of ASD (7); however, the strongest contribution is from common variants (8). Inherited rare variants have been identified by searching consanguineous and/or multiplex families using WES analysis (9). The analyses identified AMT, PEX7, and SYNE1 genes as affected by rare variations associated with ASD. Klei et al. performed genotyping on families affected by ASD. When analyzing genome-wide common variation, they found that common genetic polymorphism has strong additive genetic effects on ASD risk (10).
Advances in Genomic Prediction
D’Gama et al. conducted a deep sequencing study of postmortem ASD brains for single nucleotide variants in ASD candidate genes (11). They identified more deleterious and loss-of-function mutations in the ASD brains when compared to controls. This data suggest that multiple mechanisms may contribute to ASD risk.
With the data generated from sequencing studies, one goal is to be able to use the information to predict the risk of ASD in offspring. Krishnan et al. developed a network-based machine-learning method to identify link gene associations with functional characteristics. Their results show that a large set of ASD-related genes corresponds to a smaller number of important pathways and stages of brain development. For instance, genes associated with ASD that involve enteric nervous system development may be associated with gastrointestinal symptoms common in children with ASD (12).
Genetic testing before conception can provide valuable information for potential parents. Those who are planning a family often want to know if they carry genetics for conditions that can be passed to their children. Applying the current and emerging knowledge regarding the genetic basis of ASD to noninvasive parental testing (NIPT) may be possible in the near future. With this come the ethical considerations with this ability as it is with current NIPT applications. However, if parents could know the potential that a baby will have autism, early interventions can allow them to begin early therapeutic and social skills interventions that can benefit the child’s development.
The heterogeneity of ASD that can occur even within the same family requires comprehensive genetic research approaches to link the numerous genetic variants to functional pathways. When conducting genomic assessment at the individual level, the information obtained and compared to genetic data resources can contribute to the design and application of personalized therapeutic approaches. Molecular and bioinformatic strategies can help make targeted therapies possible to provide a higher quality of life and social functionality for people with ASD.
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