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Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank
BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition whose biological basis is yet to be elucidated. The Australian Autism Biobank (AAB) is an initiative of the Cooperative Research Centre for Living with Autism (Autism CRC) to establish an Australian resource of bios...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7874616/ https://www.ncbi.nlm.nih.gov/pubmed/33568206 http://dx.doi.org/10.1186/s13229-020-00407-5 |
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author | Yap, Chloe X. Alvares, Gail A. Henders, Anjali K. Lin, Tian Wallace, Leanne Farrelly, Alaina McLaren, Tiana Berry, Jolene Vinkhuyzen, Anna A. E. Trzaskowski, Maciej Zeng, Jian Yang, Yuanhao Cleary, Dominique Grove, Rachel Hafekost, Claire Harun, Alexis Holdsworth, Helen Jellett, Rachel Khan, Feroza Lawson, Lauren Leslie, Jodie Levis Frenk, Mira Masi, Anne Mathew, Nisha E. Muniandy, Melanie Nothard, Michaela Visscher, Peter M. Dawson, Paul A. Dissanayake, Cheryl Eapen, Valsamma Heussler, Helen S. Whitehouse, Andrew J. O. Wray, Naomi R. Gratten, Jacob |
author_facet | Yap, Chloe X. Alvares, Gail A. Henders, Anjali K. Lin, Tian Wallace, Leanne Farrelly, Alaina McLaren, Tiana Berry, Jolene Vinkhuyzen, Anna A. E. Trzaskowski, Maciej Zeng, Jian Yang, Yuanhao Cleary, Dominique Grove, Rachel Hafekost, Claire Harun, Alexis Holdsworth, Helen Jellett, Rachel Khan, Feroza Lawson, Lauren Leslie, Jodie Levis Frenk, Mira Masi, Anne Mathew, Nisha E. Muniandy, Melanie Nothard, Michaela Visscher, Peter M. Dawson, Paul A. Dissanayake, Cheryl Eapen, Valsamma Heussler, Helen S. Whitehouse, Andrew J. O. Wray, Naomi R. Gratten, Jacob |
author_sort | Yap, Chloe X. |
collection | PubMed |
description | BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition whose biological basis is yet to be elucidated. The Australian Autism Biobank (AAB) is an initiative of the Cooperative Research Centre for Living with Autism (Autism CRC) to establish an Australian resource of biospecimens, phenotypes and genomic data for research on autism. METHODS: Genome-wide single-nucleotide polymorphism genotypes were available for 2,477 individuals (after quality control) from 546 families (436 complete), including 886 participants aged 2 to 17 years with diagnosed (n = 871) or suspected (n = 15) ASD, 218 siblings without ASD, 1,256 parents, and 117 unrelated children without an ASD diagnosis. The genetic data were used to confirm familial relationships and assign ancestry, which was majority European (n = 1,964 European individuals). We generated polygenic scores (PGS) for ASD, IQ, chronotype and height in the subset of Europeans, and in 3,490 unrelated ancestry-matched participants from the UK Biobank. We tested for group differences for each PGS, and performed prediction analyses for related phenotypes in the AAB. We called copy-number variants (CNVs) in all participants, and intersected these with high-confidence ASD- and intellectual disability (ID)-associated CNVs and genes from the public domain. RESULTS: The ASD (p = 6.1e−13), sibling (p = 4.9e−3) and unrelated (p = 3.0e−3) groups had significantly higher ASD PGS than UK Biobank controls, whereas this was not the case for height—a control trait. The IQ PGS was a significant predictor of measured IQ in undiagnosed children (r = 0.24, p = 2.1e−3) and parents (r = 0.17, p = 8.0e−7; 4.0% of variance), but not the ASD group. Chronotype PGS predicted sleep disturbances within the ASD group (r = 0.13, p = 1.9e−3; 1.3% of variance). In the CNV analysis, we identified 13 individuals with CNVs overlapping ASD/ID-associated CNVs, and 12 with CNVs overlapping ASD/ID/developmental delay-associated genes identified on the basis of de novo variants. LIMITATIONS: This dataset is modest in size, and the publicly-available genome-wide-association-study (GWAS) summary statistics used to calculate PGS for ASD and other traits are relatively underpowered. CONCLUSIONS: We report on common genetic variation and rare CNVs within the AAB. Prediction analyses using currently available GWAS summary statistics are largely consistent with expected relationships based on published studies. As the size of publicly-available GWAS summary statistics grows, the phenotypic depth of the AAB dataset will provide many opportunities for analyses of autism profiles and co-occurring conditions, including when integrated with other omics datasets generated from AAB biospecimens (blood, urine, stool, hair). |
format | Online Article Text |
id | pubmed-7874616 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78746162021-02-11 Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank Yap, Chloe X. Alvares, Gail A. Henders, Anjali K. Lin, Tian Wallace, Leanne Farrelly, Alaina McLaren, Tiana Berry, Jolene Vinkhuyzen, Anna A. E. Trzaskowski, Maciej Zeng, Jian Yang, Yuanhao Cleary, Dominique Grove, Rachel Hafekost, Claire Harun, Alexis Holdsworth, Helen Jellett, Rachel Khan, Feroza Lawson, Lauren Leslie, Jodie Levis Frenk, Mira Masi, Anne Mathew, Nisha E. Muniandy, Melanie Nothard, Michaela Visscher, Peter M. Dawson, Paul A. Dissanayake, Cheryl Eapen, Valsamma Heussler, Helen S. Whitehouse, Andrew J. O. Wray, Naomi R. Gratten, Jacob Mol Autism Research BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition whose biological basis is yet to be elucidated. The Australian Autism Biobank (AAB) is an initiative of the Cooperative Research Centre for Living with Autism (Autism CRC) to establish an Australian resource of biospecimens, phenotypes and genomic data for research on autism. METHODS: Genome-wide single-nucleotide polymorphism genotypes were available for 2,477 individuals (after quality control) from 546 families (436 complete), including 886 participants aged 2 to 17 years with diagnosed (n = 871) or suspected (n = 15) ASD, 218 siblings without ASD, 1,256 parents, and 117 unrelated children without an ASD diagnosis. The genetic data were used to confirm familial relationships and assign ancestry, which was majority European (n = 1,964 European individuals). We generated polygenic scores (PGS) for ASD, IQ, chronotype and height in the subset of Europeans, and in 3,490 unrelated ancestry-matched participants from the UK Biobank. We tested for group differences for each PGS, and performed prediction analyses for related phenotypes in the AAB. We called copy-number variants (CNVs) in all participants, and intersected these with high-confidence ASD- and intellectual disability (ID)-associated CNVs and genes from the public domain. RESULTS: The ASD (p = 6.1e−13), sibling (p = 4.9e−3) and unrelated (p = 3.0e−3) groups had significantly higher ASD PGS than UK Biobank controls, whereas this was not the case for height—a control trait. The IQ PGS was a significant predictor of measured IQ in undiagnosed children (r = 0.24, p = 2.1e−3) and parents (r = 0.17, p = 8.0e−7; 4.0% of variance), but not the ASD group. Chronotype PGS predicted sleep disturbances within the ASD group (r = 0.13, p = 1.9e−3; 1.3% of variance). In the CNV analysis, we identified 13 individuals with CNVs overlapping ASD/ID-associated CNVs, and 12 with CNVs overlapping ASD/ID/developmental delay-associated genes identified on the basis of de novo variants. LIMITATIONS: This dataset is modest in size, and the publicly-available genome-wide-association-study (GWAS) summary statistics used to calculate PGS for ASD and other traits are relatively underpowered. CONCLUSIONS: We report on common genetic variation and rare CNVs within the AAB. Prediction analyses using currently available GWAS summary statistics are largely consistent with expected relationships based on published studies. As the size of publicly-available GWAS summary statistics grows, the phenotypic depth of the AAB dataset will provide many opportunities for analyses of autism profiles and co-occurring conditions, including when integrated with other omics datasets generated from AAB biospecimens (blood, urine, stool, hair). BioMed Central 2021-02-10 /pmc/articles/PMC7874616/ /pubmed/33568206 http://dx.doi.org/10.1186/s13229-020-00407-5 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Yap, Chloe X. Alvares, Gail A. Henders, Anjali K. Lin, Tian Wallace, Leanne Farrelly, Alaina McLaren, Tiana Berry, Jolene Vinkhuyzen, Anna A. E. Trzaskowski, Maciej Zeng, Jian Yang, Yuanhao Cleary, Dominique Grove, Rachel Hafekost, Claire Harun, Alexis Holdsworth, Helen Jellett, Rachel Khan, Feroza Lawson, Lauren Leslie, Jodie Levis Frenk, Mira Masi, Anne Mathew, Nisha E. Muniandy, Melanie Nothard, Michaela Visscher, Peter M. Dawson, Paul A. Dissanayake, Cheryl Eapen, Valsamma Heussler, Helen S. Whitehouse, Andrew J. O. Wray, Naomi R. Gratten, Jacob Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank |
title | Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank |
title_full | Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank |
title_fullStr | Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank |
title_full_unstemmed | Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank |
title_short | Analysis of common genetic variation and rare CNVs in the Australian Autism Biobank |
title_sort | analysis of common genetic variation and rare cnvs in the australian autism biobank |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7874616/ https://www.ncbi.nlm.nih.gov/pubmed/33568206 http://dx.doi.org/10.1186/s13229-020-00407-5 |
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