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Cited by 158Autism Spectrum Disorder ResearchGenetics and Neurodevelopmental DisordersGenomics and Rare Diseases

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Inherited and multiple de novo mutations in autism/developmental delay risk genes suggest a multifactorial model

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Guo, Hui, Wang, Tianyun, Wu, Huidan, Long, Min, Coe, Bradley P., Li, Honghui, Xun, Guanglei, Ou, Jianjun, Chen, Biyuan, Duan, Guiqin, Bai, Ting, Zhao, Ningxia, Shen, Yidong, Li, Yun, Wang, Yazhe, Zhang, Yu, Baker, Carl, Liu, Yanling, Pang, Nan, Huang, Lian, Han, Lin, Jia, Xiangbin, Liu, Cenying, Ni, Hailun, Yang, Xinyi, Xia, Lu, Chen, Jingjing, Shen, Lu, Li, Ying, Zhao, Rongjuan, Zhao, Wenjing, Peng, Jing, Pan, Qian, Long, Zhigao, Su, Wei, Tan, Jieqiong, Du, Xiaogang, Ke, Xiaoyan, Yao, Meiling, Hu, Zhengmao, Zou, Xiaobing, Zhao, Jingping, Bernier, Raphael A., Eichler, Evan E., Xia, Kun·2018·Molecular Autism
DOI 10.1186/s13229-018-0247-zPMC PMC6293633
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Abstract

Background: We previously performed targeted sequencing of autism risk genes in probands from the Autism Clinical and Genetic Resources in China (ACGC) (phase I). Here, we expand this analysis to a larger cohort of patients (ACGC phase II) to better understand the prevalence, inheritance, and genotype-phenotype correlations of likely gene-disrupting (LGD) mutations for autism candidate genes originally identified in cohorts of European descent. Methods: We sequenced 187 autism candidate genes in an additional 784 probands and 85 genes in 599 probands using single-molecule molecular inversion probes. We tested the inheritance of potentially pathogenic mutations, performed a meta-analysis of phase I and phase II data and combined our results with existing exome sequence data to investigate the phenotypes of carrier parents and patients with multiple hits in different autism risk genes. Results: ). We identified the transmission of private LGD mutations in genes predominantly associated with DNMs and showed that parental carriers tended to share milder autism-related phenotypes. Patients that carried DNMs in two or more candidate genes show more severe phenotypes. Conclusions: We identify new risk genes and transmission of deleterious mutations in genes primarily associated with DNMs. The fact that parental carriers show milder phenotypes and patients with multiple hits are more severe supports a multifactorial model of risk.

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Fig. 1 Distribution of DNMs in two potential novel autism risk genes (ZNF292, RALGAPB) and CTTNBP2. Dagger symbol indicates the DNMs reported in this study. ZNF292: p.R89* was reported in an ASC patient, p.L943Qfs*5 was reported in an ID patient, p. N1741Lfs*25 was reported in DDD study. RALGAPB: p.M289Vfs*3 was reported in an ASC patient, p.S1287* was reported in an EPI4K patient. CTTNBP2: p.V706Efs*14 was reported in an SSC patient
Fig. 1 Distribution of DNMs in two potential novel autism risk genes (ZNF292, RALGAPB) and CTTNBP2. Dagger symbol indicates the DNMs reported in this study. ZNF292: p.R89* was reported in an ASC patient, p.L943Qfs*5 was reported in an ID patient, p. N1741Lfs*25 was reported in DDD study. RALGAPB: p.M289Vfs*3 was reported in an ASC patient, p.S1287* was reported in an EPI4K patient. CTTNBP2: p.V706Efs*14 was reported in an SSC patientCC BY · PubMed Central
Fig. 2 Multiple-hit model for ASD. a Ten families and corresponding double-hit DNMs in the ACGC, SSC and ASC cohorts are shown. Dagger symbol indicates the genes listed as autism risk genes in SFARI; number sign indicates the variants presented in ExAC database. b The logistic histogram plot shows that both males and females have a higher probability of being affected with an increase in the number of DNMs even after correcting for paternal age effect. Females show a higher odds ratio (OR) than males for this additional DNM effect. c The plot shows the distribution of OR and the corresponding 95% CI of regression models, which predict affected status and different phenotype severity by DNM numbers
Fig. 2 Multiple-hit model for ASD. a Ten families and corresponding double-hit DNMs in the ACGC, SSC and ASC cohorts are shown. Dagger symbol indicates the genes listed as autism risk genes in SFARI; number sign indicates the variants presented in ExAC database. b The logistic histogram plot shows that both males and females have a higher probability of being affected with an increase in the number of DNMs even after correcting for paternal age effect. Females show a higher odds ratio (OR) than males for this additional DNM effect. c The plot shows the distribution of OR and the corresponding 95% CI of regression models, which predict affected status and different phenotype severity by DNM numbersCC BY · PubMed Central
Fig. 3 Inheritance of high-risk ASD genes. a The number of inherited and DNMs by autism risk gene within the ACGC. b Families with inherited LGD mutations or gene-disrupting CNVs in ASD high-risk genes, including CHD8 (5), KMT5B (2), DSCAM (2), FOXP1 (2), SCN2A (1), ADNP (1), and WDFY3 (1). c Genomic location of inherited CNV-disrupting CHD8 within an ASD family from the ACGC cohort. LGD, likely gene-disrupting
Fig. 3 Inheritance of high-risk ASD genes. a The number of inherited and DNMs by autism risk gene within the ACGC. b Families with inherited LGD mutations or gene-disrupting CNVs in ASD high-risk genes, including CHD8 (5), KMT5B (2), DSCAM (2), FOXP1 (2), SCN2A (1), ADNP (1), and WDFY3 (1). c Genomic location of inherited CNV-disrupting CHD8 within an ASD family from the ACGC cohort. LGD, likely gene-disruptingCC BY · PubMed Central

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  1. Constantino JN, Gruber CP. Social responsiveness scale (SRS). Los Angeles: Western Psychological Services; 2005.

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Metadata

Authors
Guo, H., Wang, T., Wu, H., Long, M., Coe, B. P., Li, H., Xun, G., Ou, J., Chen, B., Duan, G., Bai, T., Zhao, N., Shen, Y., Li, Y., Wang, Y., Zhang, Y., Baker, C., Liu, Y., Pang, N., Huang, L., Han, L., Jia, X., Liu, C., Ni, H., Yang, X., Xia, L., Chen, J., Shen, L., Li, Y., Zhao, R., Zhao, W., Peng, J., Pan, Q., Long, Z., Su, W., Tan, J., Du, X., Ke, X., Yao, M., Hu, Z., Zou, X., Zhao, J., Bernier, R. A., Eichler, E. E., & Xia, K.
Affiliations
  • Central South University (CN)
  • University of Washington (US)
  • Liuzhou Maternal and Child Health Hospital (CN)
  • Shandong Mental Health Center (CN)
  • Third Affiliated Hospital of Sun Yat-sen University (CN)
  • Third Affiliated Hospital of Zhengzhou University (CN)
  • Nanjing Brain Hospital (CN)
  • Howard Hughes Medical Institute (US)
Corresponding author
  • Guo, Hui
  • Eichler, Evan E.
  • Xia, Kun
ORCID
Venue
Molecular Autism
Publisher
Springer Science and Business Media LLC
Published
2018-12
Volume
9
Issue
1
Pages
64-64
ISSN
2040-2392 (ISSN-L)
DOI
10.1186/s13229-018-0247-z
PMC
PMC6293633
OpenAlex
W2904691870
Cited by
154
References
40
Citations by year
2026: 8 · 2025: 7 · 2024: 22 · 2023: 21 · 2022: 31 · 2021: 26 · 2020: 27 · 2019: 12
FWCI
9.66
Type
journal article
Language
en
Open access
Licence
Locations
  • Molecular Autism (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • National Natural Science Foundation of China (81330027, 81525007, 31671114, 31400919, 81601197, 81460500)
  • Simons Foundation (SFARI 303241)
  • National Institutes of Health (R01MH101221, R01MH100047)
  • Howard Hughes Medical Institute (N/A)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
Keywords
autism spectrum disorder, developmental delay, autism risk genes, de novo mutations, inherited mutations, multi-factor models, genotype-phenotype correlation, autism candidate genes
MeSH terms
Autism Spectrum Disorder, Adult, Child, Female, Humans, Male, Models, Genetic, Mutation, Pedigree, Multifactorial Inheritance, Quantitative Trait Loci

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