Direct Measure of the De Novo Mutation Rate in Autism and Schizophrenia Cohorts
journal contribution
posted on 2023-06-08, 10:03authored byPhilip Awadalla, Julie Gauthier, Rachel A Myers, Ferran Casals, Fadi F Hamdan, Alexander R Griffing, Mélanie Côté, Edouard Henrion, Dan Spiegelman, Julien Tarabeux, Amélie Piton, Yan Yang, Adam Boyko, Carlos Bustamante, Lan Xiong, Judith L Rapoport, Anjené M Addington, J Lynn E DeLisi, Marie-Odile Krebs, Ridha Joober, Bruno Millet, Éric Fombonne, Laurent Mottron, Martine Zilversmit, Jon Keebler, Hussein Daoud, Claude Marineau, Marie-Hélène Roy-Gagnon, Marie-Pierre Dubé, Adam Eyre-WalkerAdam Eyre-Walker, Pierre Drapeau, Eric A Stone, Ronald G Lafrenière, Guy A Rouleau
The role of de novo mutations (DNMs) in common diseases remains largely unknown. Nonetheless, the rate of de novo deleterious mutations and the strength of selection against de novo mutations are critical to understanding the genetic architecture of a disease. Discovery of high-impact DNMs requires substantial high-resolution interrogation of partial or complete genomes of families via resequencing. We hypothesized that deleterious DNMs may play a role in cases of autism spectrum disorders (ASD) and schizophrenia (SCZ), two etiologically heterogeneous disorders with significantly reduced reproductive fitness. We present a direct measure of the de novo mutation rate (mu) and selective constraints from DNMs estimated from a deep resequencing data set generated from a large cohort of ASD and SCZ cases (n = 285) and population control individuals (n = 285) with available parental DNA. A survey of -430 Mb of DNA from 401 synapse-expressed genes across all cases and 25 Mb of DNA in controls found 28 candidate DNMs, 13 of which were cell line artifacts. Our calculated direct neutral mutation rate (1.36 x 10(-8)) is similar to previous indirect estimates, but we observed a significant excess of potentially deleterious DNMs in ASD and SCZ individuals. Our results emphasize the importance of DNMs as genetic mechanisms in ASD and SCZ and the limitations of using DNA from archived cell lines to identify functional variants.