All different and yet the same: searching for biological similarities between individuals with autism
/“If you know one child with autism,” the saying goes, “you know one child with autism.” Though an estimated 1 in 68 children in the United States will be diagnosed with Autism Spectrum Disorder (ASD), their diverse personalities seem to defy categorization. One child’s sensitivity to loud sound will be another’s hatred of scratchy cotton tee shirts; one might talk at lengths on the minutia of the electrical fan industry, while another cannot speak at all.
This diversity is seen in biology as well as behavior. Some estimates put the number of genetic abnormalities associated with ASD at 1,000 – a substantial fraction of all the proteins made in the human body. Although some rare versions of genes confer a serious risk for ASD, many patients harbor an unlucky combination of common but low-impact genetic mutations seen in otherwise typically developing individuals.
Yet, dating back to the first report on ASD by Austrian-American psychiatrist Leo Kanner, clinicians have identified clear themes in the children’s behavior. Diagnoses are based on difficulty with social communication – which includes a range of subtle behaviors, like playing with others and noticing where conversation partners direct their attention – and the presence of restricted interests or repetitive behaviors. Researchers have long struggled to pinpoint the common biological pathway underlying these behavioral commonalities seen in ASD. A study published last year by Silvia De Rubeis and her colleagues took advantage of rare risk variants to find molecular commonalities that underlie the behavioral traits that link autism spectrum disorders together.
Her data drew from a set of previous studies that sequenced its participants’ exomes – that is, the 2% of the genome that encodes a potentially disease-linked gene. The study was special because she compared ASD patients both to their unaffected parents and to typically developing unrelated individuals. In that way, she was able to ask which alleles (“genes had been exactly copied from parent to child”) had been transmitted from parents and which genes had mutations that appeared spontaneously (de novo, in scientific parlance) in order to determine how individuals with ASD are different genetically from the rest of the population.
Her work is particularly exciting because it leverages new techniques to increase the statistical power of the study – that is, the mathematical likelihood that the study is truly detecting a real effect. First of all, the number of subjects in the study was extremely large, including over two thousand patients with autism. Second, the two mathematical steps implemented by the authors carefully used many pieces of information when deciding that a gene conferred autism risk. The first step, called Transmission And De Novo Association (TADA), looked for a variety of different mutations, rather than just one type of mutation, in genes that were associated with autism risk. The second step, DAWN, found even more potential risk genes by looking at what other genes were associated with the known, TADA risk genes. Altogether, they found that the proteins affected by these gene mutations clustered into four main groups: transcription-controlling proteins, synaptic communication proteins, synapse adhesion proteins, and neurodegeneration proteins.
In many ways, this paper inspires more questions than it answers. Do all autism risk genes cluster into these groups, or only these rare variants? What behaviors and pathways are these mutations affecting? What the heck are neurodegeneration proteins doing in autism? Nevertheless, her findings provide a major step forward in finding the missing link between all individuals with ASD.
