Genomic Patterns of De Novo Mutation in Simplex Autism

Abstract

SUMMARY To further our understanding of the genetic etiology of autism, we generated and analyzed genome sequence data from 516 idiopathic autism families (2,064 individuals). This resource includes >59 million single-nucleotide variants (SNVs) and 9,212 private copy number variants (CNVs), of which 133,992 and 88 are de novo mutations (DNMs), respectively. We estimate a mutation rate of ~1.5×10−8 SNVs per site per generation with a significantly higher mutation rate in repetitive DNA. Comparing probands and unaffected siblings, we observe several DNM trends. Probands carry more gene-disruptive CNVs and SNVs resulting in severe missense mutations and mapping to predicted fetal brain promoters and embryonic stem cell enhancers. These differences become more pronounced for autism genes (p=1.8×10−3, OR=2.2). Patients are more likely to carry multiple coding and noncoding DNMs in different genes, which are enriched for expression in striatal neurons (p=3×10−3), suggesting a path forward for characterizing genetically more complex cases of autism.

An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder

“…Collectively, this catalogue of de novo SVs achieved high specificity, almost certainly at the cost of sensitivity for SV detection from short-read WGS, though there are few gold-standard datasets to estimate accurate SV mutation rates at present. Notably, a study from Turner et al published during revision of this manuscript identified 88 de novo SVs from 476 of these quartets with an estimated 87.5% confirmation rate using microarray validation 31 .…”

“…Continuing the analogy, instead of candidate genes, the field would be substituting “candidate annotations” with all likelihood of poor outcomes, due to myriad combinations of annotations, cell types, brain regions, and developmental stages. Several ASD studies have selected different regions of the noncoding genome on which to focus 16,31,36,43,44 , and associations from initial small studies have failed to replicate in larger datasets (Supplementary Fig. 15), a trend likely to persist if nominal significance is the threshold chosen for exploring genomes.…”

Estimating contribution of rare non‐coding variants to neuropsychiatric disorders

“…More recently, results of two WGS studies analyzing the same dataset of the Simons Simplex Collection (>500 quads: a father, a mother, a proband with autism, and an unaffected sibling; probands carrying likely causal variants were excluded from the Pilot and Phase 1 batches) with an emphasis on non‐coding DNM were reported. One study (Turner et al …”

“…However, nominal significance was indeed observed in the control group, further suggesting need of a comprehensive, unbiased, and appropriately stringent approach, such as CWAS. Key findings and the points of difference in these two studies are summarized in Table …”

“…Considering possible sources of many differences between the two studies, first, each study used a different statistical procedure to calculate P ‐values: one‐tailed Fisher's exact tests without covariation for possible confounding factors, such as paternal age, were used in Turner et al significance was calculated by case/control label‐swapping permutations (at least 10 000 times) that took paternal age and sequencing quality metrics into account.…”