Summary of Advances
In Autism Spectrum Disorder Research
The idiosyncratic brain: distortion of spontaneous connectivity patterns in autism spectrum disorder
Hahamy A, Behrmann M, Malach R. Nat Neurosci. 2015 Feb;18(2):302-9. [PMID: 25599222]
Research that helps scientists understand differences in how the brain is structured and how it functions in people on the autism spectrum compared with neurotypical individuals not only increases scientific knowledge about autism but also provides a way to potentially characterize the severity of ASD symptoms and ultimately helps to provide a path for developing effective interventions. Scientists can measure areas in the brain that are associated with the processing of various tasks in thinking and reasoning (cognitive tasks) to identify abnormalities in brain activity, or connectivity, by using functional magnetic resonance imaging (fMRI). fMRI is a noninvasive imaging procedure that measures brain activity by assessing changes in blood flow in the brain that are associated with the activity of neurons. By using fMRI to measure brain function connectivity in adults at rest, scientists have developed a substantial body of research that has identified irregular patterns of brain connectivity in people with ASD. Although these findings, which include a reduction in certain brain connections, support the idea that the ASD brain is “under-connected,” some more recent studies have reported results suggesting that the brain in ASD is “over-connected.” To try to find an explanation for the differences between these varying reports, scientists accessed a large collection of fMRI scan data sets (the Autism Brain Imaging Data Exchange [ABIDE]).
The researchers analyzed the resting state fMRIs of 68 adults with high-functioning ASD (adults with relatively mild symptoms of ASD) and 73 control participants (participants without ASD) from the ABIDE data set. The scientists found that while the brain activity patterns in the control participants were relatively consistent, ASD participants showed significant and individually distinct (idiosyncratic) distortions of the pattern of functional connectivity. This greater variability of patterns among individuals may explain conflicting findings from previous studies, and the authors caution that brain regional connectivity differences between ASD and control groups should be examined carefully as high variability among ASD subjects may be contributing to those apparent differences. The researchers who conducted this study propose that the variations in the connectivity patterns of the ASD participants may reveal a previously unrecognized core characteristic of high-functioning adults with ASD and could potentially be used to distinguish subtypes and severity of symptoms in ASD populations. While they did discover that there was a correlation between some measures of symptom severity and the degree of distortion from the control group, given the small sample size they were not able to distinguish any subtypes of ASD. In addition, some of the study findings indicate that the differences in the connectivity patterns among individuals, including those with ASD, may be in part a result of each person’s unique interaction with his or her environment. Future studies may help explain how these distinct functional connectivity patterns arise in ASD and influence symptoms, as well as if these results can be replicated in additional populations with other disorders affecting the interaction between the brain and the environment.
Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci
Sanders SJ, He X, Willsey AJ, Ercan-Sencicek AG, Samocha KE, Cicek AE, Murtha MT, Bal VH, Bishop SL, Dong S, Goldberg AP, Jinlu C, Keaney JF 3rd, Klei L, Mandell JD, Moreno-De-Luca D, Poultney CS, Robinson EB, Smith L, Solli-Nowlan T, Su MY, Teran NA, Walker MF, Werling DM, Beaudet AL, Cantor RM, Fombonne E, Geschwind DH, Grice DE, Lord C, Lowe JK, Mane SM, Martin DM, Morrow EM, Talkowski ME, Sutcliffe JS, Walsh CA, Yu TW; Autism Sequencing Consortium, Ledbetter DH, Martin CL, Cook EH, Buxbaum JD, Daly MJ, Devlin B, Roeder K, State MW. Neuron. 2015 Sep 23;87(6):1215-33. [PMID: 26402605]
Autism is known to have a strong genetic component—which is why, for example, siblings of children with autism have a higher risk of developing autism. Finding the genes and the areas of the human genome that are involved in autism can help provide a deeper understanding of how the brain works in autism and potentially lead to the development of new, more effective interventions. In this study, an international research team analyzed genomic information from 2,591 families that include at least one child with ASD. They found six large regions of the genome that contain de novo copy number variants (dnCNVs; widespread structural variations in the human genome that are not inherited) contributing to autism risk. In addition, the team found 65 specific genes that contribute to ASD risk, 27 of which were newly identified. Notably, 28 of the 65 identified genes are believed to be highly likely to play a role in the risk of developing ASD.
The team’s analysis revealed a total of 71 locations in the genome where DNA mutation is associated with ASD (risk loci), including the six dnCNV regions and the 65 specific high-risk genes noted above. The researchers also determined that some of the ASD-associated genes are related to the development and function of synapses (the small junctures separating neurons), while others are related to chromatin (part of a cell that packages DNA and determines whether genes are “turned on” or “turned off”). Through this study, it was also found that small dnCNV regions are more likely to include a single gene with a strong effect on ASD risk, while large dnCNV regions, in contrast, are more likely to contain a number of genes each of which exert a more modest effect on autism risk. The study also considered how the sex of the individual and the type of mutation relate to non-verbal IQ (NVIQ; or thinking and problem-solving skills that do not require the use of language). It was concluded that although lower NVIQ is found in both males and females with autism, having a low NVIQ does not necessarily mean that the ASD-associated mutations are present, and having a high NVIQ does not mean that the ASD-associated mutations are missing. In other words, de novo mutations were found in ASD-associated genes of individuals across the entire range of intellectual levels seen in ASD, including in high-IQ individuals with ASD, suggesting these mutations confer ASD risk separately from intellectual disability. In addition, the team found data to support what is called the “female protective effect” (FPE) hypothesis as an explanation for the fact that females are far less likely than males to be diagnosed with ASD. Although the genetic mutations associated with ASD are found in the same set of genes in both sexes, more genetic mutations occur in females than in males with ASD, suggesting that in girls the number of mutations present in these genes must reach a high threshold in order to result in ASD. All of this information can help guide researchers as they continue their work to discover which genes and genomic regions need to be studied more intensively among the hundreds that are likely to be involved in ASD—and as even more studies on these genes go forward, we can move closer to understanding the disorder and translating these basic research discoveries into treatments.