| Autor: |
Jacob A. S. Vorstman, Evdokia Anagnostou, Daniele Merico, Jeffrey R. MacDonald, Jennifer L. Howe, Zhuozhi Wang, Ryan K. C. Yuen, Thomas Nalpathamkalam, Judith H. Miles, Carol Negrijn, Miriam S. Reuter, Neal Sondheimer, Bridget A. Fernandez, Stephen W. Scherer, Wilson W L Sung, Kristiina Tammimies, Rohan V. Patel, Worrawat Engchuan, Giovanna Pellecchia, Nicole Takahashi, Mehdi Zarrei, Ada J.S. Chan, Dimitri J. Stavropoulos, Bhooma Thiruvahindrapuram, Sylvia Lamoureux, Brett Trost |
| Rok vydání: |
2021 |
| Předmět: |
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| DOI: |
10.1101/2021.10.20.21264950 |
| Popis: |
Defining different genetic subtypes of autism spectrum disorder (ASD) can enable the prediction of developmental outcomes. Based on minor physical and major congenital anomalies, we categorized 325 Canadian children with ASD into dysmorphic and nondysmorphic subgroups. We developed a method for calculating a patient-level, genome-wide rare variant score (GRVS) from whole-genome sequencing (WGS) data. GRVS is a sum of the number of variants in morphology-associated coding and non-coding regions, weighted by their effect sizes. Probands with dysmorphic ASD had a significantly higher GRVS compared to those with nondysmorphic ASD (P= 0.027). Using the polygenic transmission disequilibrium test, we observed an over-transmission of ASD-associated common variants in nondysmorphic ASD probands (P= 2.9×10−3). These findings replicated using WGS data from 442 ASD probands with accompanying morphology data from the Simons Simplex Collection. Our results provide support for an alternative genomic classification of ASD subgroups using morphology data, which may inform intervention protocols. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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