Genetic Influences on Autism Spectrum Disorders
New technologies and methodological approaches are starting to elucidate the relationship between DNA and complex human behavior.
ATLANTA, Georgia – Rapid technological development is perhaps the single most powerful force in modern brain research with the potential to greatly affect people's lives. One novel approach for examining brain functional network connectivity is optogenetic functional magnetic resonance imaging (ofMRI).1 More specifically, traditional ”optogenetic” tools, a revolutionary invention in its own right,2 enable light-based modulation of genetically defined neurons and temporally precise stimulation of neural circuit activity. On the other hand, traditional fMRI allows visualization of functional connectivity patterns of the brain. And consider the CRISPR/Cas systems,3 to date the most precise and efficient way of editing or engineering the genome of any organism that shows promise in transforming the field of biology.
Autism is a heritable disorder, but genetic causes remain largely unknown. Matthew State, MD, PhD, a child psychiatrist and human geneticist at the University of California, San Francisco, started conducting genetics and genomics research in the late 1990s in order to understand the underlying molecular and circuit-level mechanisms and causes of autism, a neurodevelopmental disorder that affects approximately 1 in 100 children worldwide and is 4 times more prevalent in males than females. Aside from behavioral therapies, medications including atypical antipsychotics are used to address the behavioral disturbances; however, medical professionals currently do not have any available measures to rely on to treat the core social deficits seen in patients diagnosed with autism.4
The high-throughput next-generation genome and exome sequencing technology is rapidly advancing and is becoming increasingly affordable. Importantly, it enables systematic examination of the entire genome, which has led to an unprecedented discovery of variation between individual genomes. Consequently, these technological advances are shaping the evidence for the genetic basis of disease risk in various neuropsychiatric disorders, including autism.5
The human genome contains roughly 3 billion DNA base pairs, and the great majority of these bases is the same in all people. “When trying to understand how genetics contribute to neuropsychiatric disorders, what's relevant is not the 99% of the genome that's identical between people, but it's how the genomes vary,” said Dr State in his lecture titled “From Genes to Neurobiology in Autism Spectrum Disorders,” presented at the 2016 Annual Meeting of the American Psychiatric Association (APA) in Atlanta, Georgia.
Genome-wide association studies (GWAS)—an established method used to identify multiple common genetic variants, or single nucleotide polymorphisms (SNPs), that influence the risk for disease—have been successful in research on schizophrenia, for example. The relative success of these genome-wide experiments in detecting causal genes in complex disorders, including schizophrenia and autism, relies on a sufficiently large sample size. This method has been successful in schizophrenia but not autism research because more than 40,000 cases are included in statistical analysis for the former and less than 5000 for the latter, Dr State explained during his lecture. Although most of the variation in the human genome is common variation, we now know that individual SNPs exert a relatively small effect on overall disease risk (between 10% and 20%). Therefore, it is assumed that multiple SNPs work together to influence risk of neuropsychiatric disorders. To complicate matters further, the SNPs that are associated with substantial risk for autism are not restricted to this disorder; they are shared among many conditions and may, for example, also confer risk for attention deficit hyperactivity disorder (ADHD), bipolar disorder, or schizophrenia.
The contribution of rare genetic variants, such as copy number variations (CNVs), however, appears to be much larger, with estimates for increased risk of autism ranging from 20 to 60 fold, Dr State said in his lecture. (The structural variants that are considered to be rare are those that are observed in less than 1% of the population.) In fact, initial successes in identifying genes that are associated with the risk for autism came from studies of extremely rare de novo variations arising from spontaneous mutations in either sperm or egg that lead to new gene variants in the offspring. Notably, anything that increases the rate of de novo mutations in the population, such as advanced parental age, has the potential to increase the risk for autism in the offspring.4,6 This hypothesis is in line with recently reported epidemiological findings based on a population-based cohort study.7
When examining the relative contribution of rare de novo CNVs and single nucleotide variants (SNVs) to the risk for autism, the ultimate goal is to compare parent's DNA to child's DNA and to also compare DNA from a child on the autism spectrum with DNA of at least one unaffected sibling. This invaluable research approach designed to help identify de novo mutations became increasingly possible following the establishment of The Simons Simplex Collection, a repository of genetic samples from more than 2500 families with a single affected child and no other evidence of autism in that same family.
The astonishingly high costs (around $100 million in 2001) associated with sequencing of a human-size genome thwarted the scientific progress for a decade. In 2016, the cost of DNA sequencing fell to around $1,000. This crucial economic development paved the path forward and it enabled efficient sequencing of every nucleotide of DNA for the 1% of the genome that codes for proteins. In 2012, by using the whole-exome sequencing method and this family-based design, Dr State and colleagues reported that de novo SNVs that are associated with autism are 5 times as likely to increase the risk. In other words, the identified de novo mutations in brain-expressed genes have very large effects. The researchers also identified previously unknown genes, such as SCN2A, that are associated with autism, and they estimate that more than 1000 genes play a role in increasing the risk for autism when gene function is disrupted by de novo mutations.8
Another point of great interest for Dr State and his team was to identify specific time periods of brain development and particular brain cell types, regions, or circuits that may be more vulnerable to perturbations caused by rare de novo mutations. They again used exome-wide sequencing to examine genetic data from The Simons Simplex Collection repository and found a significant overrepresentation of genes that increase the risk for autism in the prefrontal cortex during midfetal development. Notably, 2 out of previous 6 well-established syndromic autism genes (NRXN1 and NLGN4X, but not FMR1, TSC1, TSC2, or PTEN) were identified in this study for this time period in brain development and in this particular brain region. The study authors noted, “Additional time points and brain regions are likely to be identified as both the number of bona fide risk genes grows and the depth of data on the molecular landscape of human brain development increases.”9
The anatomic and cellular complexity and diversity of the brain, as well as the dynamic nature of brain development (a particular genotype can lead to multiple different phenotypes), creates many challenges in the field of translational neuroscience. In addition, the genetic overlap in disease involvement presents another great challenge when thinking about potential approaches to therapy. As is the case with individual SNPs, rare de novo SNVs that increase the risk for autism have pleiotropic biological effects and are involved in illnesses such as congenital heart disease, but there is no evidence of increased rates of autism in this population. However, the importance of systematic gene discovery, and the significance of genetics and genomics research on single-point mutations and CNVs that specifically influence the risk of developmental neuropsychiatric disorders, is undeniable. Taken together, Dr State concluded that “the importance of gene discovery in diagnosis and understanding of treatment responses is certainly not realized at this moment, but there has been a profound change in autism genetics and a reliable gene discovery establishes a firm foundation to explore the underlying neurobiology.”
Click here for more research from the 2016 Annual Meeting of the American Psychiatric Association.
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Tsai HC, Zhang F, Adamantidis A, et al. Phasic firing in dopaminergic neurons is sufficient for behavioral conditioning. Science. 2009;324:1080-1084.
Cong L, Ran FA, Cox D, et al. Multiplex genome engineering using CRISPR/Cas systems. Science. 2013;339:819-823.
Geschwind DH, State MW. Gene hunting in autism spectrum disorder: on the path to precision medicine. Lancet Neurol. 2015;14:1109-1120.
De Rubeis S, Buxbaum JD. Recent advances in the genetics of autism spectrum disorder. Curr Neurol Neurosci Rep. 2015;15:36.
Cirulli ET, Goldstein DB. Uncovering the role of rare variants in common disease through whole-genome sequencing. Nat Rev Genet. 2010;11:415-425.
Sandin S, Schendel D, Magnusson P, et al. Autism risk associated with parental age and with increasing difference in age between the parents. Mol Psychiatry. 2016;21:693-700.
Sanders SJ, Murtha MT, Gupta AR, et al. De novo mutations revealed by whole exome sequencing are strongly associated with autism. Nature. 2012;485:237-241.
Willsey AJ, Sanders SJ, Mingfeng L, et al. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism. Cell. 2013;155:997-1007.