Recent advances in genome-wide approaches for gene discovery in autism spectrum disorders (ASDs) have identified a large list of strongly associated ASD risk genes, as well as an even larger list of potential ASD risk genes. In total, these comprise approximately 250 genes. In order to further distinguish the true ASD risk genes from false-positive associations, additional sequencing data is required. Molecular inversion probe (MIP) sequencing is an efficient approach because of the low cost, potential for parallelization and high-throughput capacity.

Gene discovery in autism spectrum disorders (ASDs) has accelerated in the past several years. However, current efforts have mainly focused on the coding portion of the genome, which reflects approximately 1 percent of the total genome. This focus is partly due to the expense of characterizing the entire genome, as well as difficulties in interpreting the significance of variations in noncoding DNA information.

Autism, intellectual disability, developmental delay and related phenotypes affect more than 1 percent of children worldwide. These conditions can reduce the length and quality of life of affected individuals, and contribute to emotional distress, financial challenges and lifestyle restrictions for affected families. Because these conditions are diverse and sometimes severe, many affected children undergo years of interactions with clinicians and costly testing procedures without ever receiving a precise medical diagnosis.

Autism spectrum disorder (ASD) affects at least 1 child in 68, and imposes a huge psychological and economic burden on affected individuals, their families and society. While significant progress has been made in determining genetic risk factors for ASD, there remains a substantial amount of unidentified genetic change contributing to risk.

Exome sequencing and copy number variant (CNV) analyses have contributed significantly to our understanding of the genetic etiology of autism spectrum disorder (ASD). In particular, de novo and private likely-gene-disruptive (LGD) mutations are major risk factors, contributing to 30 percent and 7 percent of simplex autism, respectively. Despite these successes, roughly 60 percent of the genetic etiology of ASD remains unexplained.

Despite the existence of a core set of features and affected biological networks, autism spectrum disorders (ASDs) are genetically heterogeneous. While variants in hundreds of genes have been implicated as causal or risk-conferring for ASD, a large percentage of the heritability of ASDs remains unaccounted for. This suggests that a number of inherited causal or risk mutations linked to autism have gone undiagnosed.

Half a century ago, the introduction of karyotyping transformed human genetics and clinical diagnostics by opening access to gross changes in chromosomes, revealing an entire class of previously undetectable genetic lesions. More recently, new technologies have refined our ability to search for genetic variants that cause disease. Yet in autism spectrum disorders (ASDs), a large proportion of genetic contribution still remains unexplained. Classes of chromosomal alterations that can cause loss-of-function mutations, namely balanced and complex structural variation (SVs), and copy number variants (CNVs), below the threshold of microarray —  collectively referred to as cryptic SVs — remain to be fully considered for their potential contribution to ASD.

Human genetic studies have identified hundreds of genes with variants associated with autism. However, the significance of most of these variants is unknown. At least half of the genes are present in all animals and thus can be studied in genetic model organisms that allow rapid, rigorous genetic analysis.

Ivan Iossifov studies the genetics of autism using the large datasets produced with comparative genomic hybridization, whole-exome and whole-genome sequencing of the extensively phenotyped Simons Simplex Collection.