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On the Nature of Monozygotic Twin Concordance and Discordance for Autistic Trait Severity: A Quantitative Analysis
The characterizing features of autism spectrum disorder (ASD) are continuously distributed in nature; however, prior twin studies have not systematically incorporated this knowledge into estimations of concordance and discordance. We conducted a quantitative analysis of twin–twin similarity for auti...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355281/ https://www.ncbi.nlm.nih.gov/pubmed/31853901 http://dx.doi.org/10.1007/s10519-019-09987-2 |
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author | Castelbaum, Lauren Sylvester, Chad M. Zhang, Yi Yu, Qiongru Constantino, John N. |
author_facet | Castelbaum, Lauren Sylvester, Chad M. Zhang, Yi Yu, Qiongru Constantino, John N. |
author_sort | Castelbaum, Lauren |
collection | PubMed |
description | The characterizing features of autism spectrum disorder (ASD) are continuously distributed in nature; however, prior twin studies have not systematically incorporated this knowledge into estimations of concordance and discordance. We conducted a quantitative analysis of twin–twin similarity for autistic trait severity in three existing data sets involving 366 pairs of uniformly-phenotyped monozygotic (MZ) twins with and without ASD. Probandwise concordance for ASD was 96%; however, MZ trait correlations differed markedly for pairs with ASD trait burden below versus above the threshold for clinical diagnosis, with R(2)s on the order of 0.6 versus 0.1, respectively. Categorical MZ twin discordance for ASD diagnosis is rare and more appropriately operationalized by standardized quantification of twin–twin differences. Here we provide new evidence that although ASD itself is highly heritable, variation-in-severity of symptomatology above the diagnostic threshold is substantially influenced, in contrast, by non-shared environmental factors which may identify novel targets of early ASD amelioration. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10519-019-09987-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7355281 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-73552812020-07-16 On the Nature of Monozygotic Twin Concordance and Discordance for Autistic Trait Severity: A Quantitative Analysis Castelbaum, Lauren Sylvester, Chad M. Zhang, Yi Yu, Qiongru Constantino, John N. Behav Genet Original Research The characterizing features of autism spectrum disorder (ASD) are continuously distributed in nature; however, prior twin studies have not systematically incorporated this knowledge into estimations of concordance and discordance. We conducted a quantitative analysis of twin–twin similarity for autistic trait severity in three existing data sets involving 366 pairs of uniformly-phenotyped monozygotic (MZ) twins with and without ASD. Probandwise concordance for ASD was 96%; however, MZ trait correlations differed markedly for pairs with ASD trait burden below versus above the threshold for clinical diagnosis, with R(2)s on the order of 0.6 versus 0.1, respectively. Categorical MZ twin discordance for ASD diagnosis is rare and more appropriately operationalized by standardized quantification of twin–twin differences. Here we provide new evidence that although ASD itself is highly heritable, variation-in-severity of symptomatology above the diagnostic threshold is substantially influenced, in contrast, by non-shared environmental factors which may identify novel targets of early ASD amelioration. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10519-019-09987-2) contains supplementary material, which is available to authorized users. Springer US 2019-12-18 2020 /pmc/articles/PMC7355281/ /pubmed/31853901 http://dx.doi.org/10.1007/s10519-019-09987-2 Text en © The Author(s) 2019 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 https://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Original Research Castelbaum, Lauren Sylvester, Chad M. Zhang, Yi Yu, Qiongru Constantino, John N. On the Nature of Monozygotic Twin Concordance and Discordance for Autistic Trait Severity: A Quantitative Analysis |
title | On the Nature of Monozygotic Twin Concordance and Discordance for Autistic Trait Severity: A Quantitative Analysis |
title_full | On the Nature of Monozygotic Twin Concordance and Discordance for Autistic Trait Severity: A Quantitative Analysis |
title_fullStr | On the Nature of Monozygotic Twin Concordance and Discordance for Autistic Trait Severity: A Quantitative Analysis |
title_full_unstemmed | On the Nature of Monozygotic Twin Concordance and Discordance for Autistic Trait Severity: A Quantitative Analysis |
title_short | On the Nature of Monozygotic Twin Concordance and Discordance for Autistic Trait Severity: A Quantitative Analysis |
title_sort | on the nature of monozygotic twin concordance and discordance for autistic trait severity: a quantitative analysis |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355281/ https://www.ncbi.nlm.nih.gov/pubmed/31853901 http://dx.doi.org/10.1007/s10519-019-09987-2 |
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