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A polygenic risk score analysis of ASD and ADHD across emotion recognition subtypes
This study investigated the genetic components of ADHD and ASD by examining the cross‐disorder trait of emotion recognition problems. The genetic burden for ADHD and ASD on previously identified emotion recognition factors (speed and accuracy of visual and auditory emotion recognition) and classes (...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9290011/ https://www.ncbi.nlm.nih.gov/pubmed/32815639 http://dx.doi.org/10.1002/ajmg.b.32818 |
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author | Waddington, Francesca Franke, Barbara Hartman, Catharina Buitelaar, Jan K. Rommelse, Nanda Mota, Nina Roth |
author_facet | Waddington, Francesca Franke, Barbara Hartman, Catharina Buitelaar, Jan K. Rommelse, Nanda Mota, Nina Roth |
author_sort | Waddington, Francesca |
collection | PubMed |
description | This study investigated the genetic components of ADHD and ASD by examining the cross‐disorder trait of emotion recognition problems. The genetic burden for ADHD and ASD on previously identified emotion recognition factors (speed and accuracy of visual and auditory emotion recognition) and classes (Class 1: Average visual, impulsive auditory; Class 2: Average‐strong visual & auditory; Class 3: Impulsive & imprecise visual, average auditory; Class 4: Weak visual & auditory) was assessed using ASD and ADHD polygenic risk scores (PRS). Our sample contained 552 participants: 74 with ADHD, 85 with ASD, 60 with ASD + ADHD, 177 unaffected siblings of ADHD or ASD probands, and 156 controls. ADHD‐ and ASD‐PRS, calculated from the latest ADHD and ASD GWAS meta‐analyses, were analyzed across these emotion recognition factors and classes using linear mixed models. Unexpectedly, the analysis of emotion recognition factors showed higher ASD‐PRS to be associated with faster visual emotion recognition. The categorical analysis of emotion recognition classes showed ASD‐PRS to be reduced in Class 3 compared to the other classes (p value threshold [pT] = 1, p = .021). A dimensional analysis identified a high ADHD‐PRS reduced the probability of being assigned to the Class 1 or Class 3 (pT = .05, p = .028 and p = .044, respectively). Though these nominally significant results did not pass FDR correction, they potentially indicate different indirect causative chains from genetics via emotion recognition to ADHD and ASD, which need to be verified in future research. |
format | Online Article Text |
id | pubmed-9290011 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92900112022-07-20 A polygenic risk score analysis of ASD and ADHD across emotion recognition subtypes Waddington, Francesca Franke, Barbara Hartman, Catharina Buitelaar, Jan K. Rommelse, Nanda Mota, Nina Roth Am J Med Genet B Neuropsychiatr Genet Research Articles This study investigated the genetic components of ADHD and ASD by examining the cross‐disorder trait of emotion recognition problems. The genetic burden for ADHD and ASD on previously identified emotion recognition factors (speed and accuracy of visual and auditory emotion recognition) and classes (Class 1: Average visual, impulsive auditory; Class 2: Average‐strong visual & auditory; Class 3: Impulsive & imprecise visual, average auditory; Class 4: Weak visual & auditory) was assessed using ASD and ADHD polygenic risk scores (PRS). Our sample contained 552 participants: 74 with ADHD, 85 with ASD, 60 with ASD + ADHD, 177 unaffected siblings of ADHD or ASD probands, and 156 controls. ADHD‐ and ASD‐PRS, calculated from the latest ADHD and ASD GWAS meta‐analyses, were analyzed across these emotion recognition factors and classes using linear mixed models. Unexpectedly, the analysis of emotion recognition factors showed higher ASD‐PRS to be associated with faster visual emotion recognition. The categorical analysis of emotion recognition classes showed ASD‐PRS to be reduced in Class 3 compared to the other classes (p value threshold [pT] = 1, p = .021). A dimensional analysis identified a high ADHD‐PRS reduced the probability of being assigned to the Class 1 or Class 3 (pT = .05, p = .028 and p = .044, respectively). Though these nominally significant results did not pass FDR correction, they potentially indicate different indirect causative chains from genetics via emotion recognition to ADHD and ASD, which need to be verified in future research. John Wiley & Sons, Inc. 2020-08-20 2021-10 /pmc/articles/PMC9290011/ /pubmed/32815639 http://dx.doi.org/10.1002/ajmg.b.32818 Text en © 2020 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Articles Waddington, Francesca Franke, Barbara Hartman, Catharina Buitelaar, Jan K. Rommelse, Nanda Mota, Nina Roth A polygenic risk score analysis of ASD and ADHD across emotion recognition subtypes |
title | A polygenic risk score analysis of ASD and ADHD across emotion recognition subtypes |
title_full | A polygenic risk score analysis of ASD and ADHD across emotion recognition subtypes |
title_fullStr | A polygenic risk score analysis of ASD and ADHD across emotion recognition subtypes |
title_full_unstemmed | A polygenic risk score analysis of ASD and ADHD across emotion recognition subtypes |
title_short | A polygenic risk score analysis of ASD and ADHD across emotion recognition subtypes |
title_sort | polygenic risk score analysis of asd and adhd across emotion recognition subtypes |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9290011/ https://www.ncbi.nlm.nih.gov/pubmed/32815639 http://dx.doi.org/10.1002/ajmg.b.32818 |
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