Cargando…
Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with heterogeneous clinical presentation, variable severity, and multiple comorbidities. A complex underlying genetic architecture matches the clinical heterogeneity, and evidence indicates that several co-occurring brain disorders shar...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9434349/ https://www.ncbi.nlm.nih.gov/pubmed/36061363 http://dx.doi.org/10.3389/fnmol.2022.932305 |
_version_ | 1784780848759832576 |
---|---|
author | Vilela, Joana Martiniano, Hugo Marques, Ana Rita Santos, João Xavier Rasga, Célia Oliveira, Guiomar Vicente, Astrid Moura |
author_facet | Vilela, Joana Martiniano, Hugo Marques, Ana Rita Santos, João Xavier Rasga, Célia Oliveira, Guiomar Vicente, Astrid Moura |
author_sort | Vilela, Joana |
collection | PubMed |
description | Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with heterogeneous clinical presentation, variable severity, and multiple comorbidities. A complex underlying genetic architecture matches the clinical heterogeneity, and evidence indicates that several co-occurring brain disorders share a genetic component with ASD. In this study, we established a genetic similarity disease network approach to explore the shared genetics between ASD and frequent comorbid brain diseases (and subtypes), namely Intellectual Disability, Attention-Deficit/Hyperactivity Disorder, and Epilepsy, as well as other rarely co-occurring neuropsychiatric conditions in the Schizophrenia and Bipolar Disease spectrum. Using sets of disease-associated genes curated by the DisGeNET database, disease genetic similarity was estimated from the Jaccard coefficient between disease pairs, and the Leiden detection algorithm was used to identify network disease communities and define shared biological pathways. We identified a heterogeneous brain disease community that is genetically more similar to ASD, and that includes Epilepsy, Bipolar Disorder, Attention-Deficit/Hyperactivity Disorder combined type, and some disorders in the Schizophrenia Spectrum. To identify loss-of-function rare de novo variants within shared genes underlying the disease communities, we analyzed a large ASD whole-genome sequencing dataset, showing that ASD shares genes with multiple brain disorders from other, less genetically similar, communities. Some genes (e.g., SHANK3, ASH1L, SCN2A, CHD2, and MECP2) were previously implicated in ASD and these disorders. This approach enabled further clarification of genetic sharing between ASD and brain disorders, with a finer granularity in disease classification and multi-level evidence from DisGeNET. Understanding genetic sharing across disorders has important implications for disease nosology, pathophysiology, and personalized treatment. |
format | Online Article Text |
id | pubmed-9434349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94343492022-09-02 Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders Vilela, Joana Martiniano, Hugo Marques, Ana Rita Santos, João Xavier Rasga, Célia Oliveira, Guiomar Vicente, Astrid Moura Front Mol Neurosci Neuroscience Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with heterogeneous clinical presentation, variable severity, and multiple comorbidities. A complex underlying genetic architecture matches the clinical heterogeneity, and evidence indicates that several co-occurring brain disorders share a genetic component with ASD. In this study, we established a genetic similarity disease network approach to explore the shared genetics between ASD and frequent comorbid brain diseases (and subtypes), namely Intellectual Disability, Attention-Deficit/Hyperactivity Disorder, and Epilepsy, as well as other rarely co-occurring neuropsychiatric conditions in the Schizophrenia and Bipolar Disease spectrum. Using sets of disease-associated genes curated by the DisGeNET database, disease genetic similarity was estimated from the Jaccard coefficient between disease pairs, and the Leiden detection algorithm was used to identify network disease communities and define shared biological pathways. We identified a heterogeneous brain disease community that is genetically more similar to ASD, and that includes Epilepsy, Bipolar Disorder, Attention-Deficit/Hyperactivity Disorder combined type, and some disorders in the Schizophrenia Spectrum. To identify loss-of-function rare de novo variants within shared genes underlying the disease communities, we analyzed a large ASD whole-genome sequencing dataset, showing that ASD shares genes with multiple brain disorders from other, less genetically similar, communities. Some genes (e.g., SHANK3, ASH1L, SCN2A, CHD2, and MECP2) were previously implicated in ASD and these disorders. This approach enabled further clarification of genetic sharing between ASD and brain disorders, with a finer granularity in disease classification and multi-level evidence from DisGeNET. Understanding genetic sharing across disorders has important implications for disease nosology, pathophysiology, and personalized treatment. Frontiers Media S.A. 2022-08-18 /pmc/articles/PMC9434349/ /pubmed/36061363 http://dx.doi.org/10.3389/fnmol.2022.932305 Text en Copyright © 2022 Vilela, Martiniano, Marques, Santos, Rasga, Oliveira and Vicente. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Vilela, Joana Martiniano, Hugo Marques, Ana Rita Santos, João Xavier Rasga, Célia Oliveira, Guiomar Vicente, Astrid Moura Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders |
title | Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders |
title_full | Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders |
title_fullStr | Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders |
title_full_unstemmed | Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders |
title_short | Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders |
title_sort | disease similarity network analysis of autism spectrum disorder and comorbid brain disorders |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9434349/ https://www.ncbi.nlm.nih.gov/pubmed/36061363 http://dx.doi.org/10.3389/fnmol.2022.932305 |
work_keys_str_mv | AT vilelajoana diseasesimilaritynetworkanalysisofautismspectrumdisorderandcomorbidbraindisorders AT martinianohugo diseasesimilaritynetworkanalysisofautismspectrumdisorderandcomorbidbraindisorders AT marquesanarita diseasesimilaritynetworkanalysisofautismspectrumdisorderandcomorbidbraindisorders AT santosjoaoxavier diseasesimilaritynetworkanalysisofautismspectrumdisorderandcomorbidbraindisorders AT rasgacelia diseasesimilaritynetworkanalysisofautismspectrumdisorderandcomorbidbraindisorders AT oliveiraguiomar diseasesimilaritynetworkanalysisofautismspectrumdisorderandcomorbidbraindisorders AT vicenteastridmoura diseasesimilaritynetworkanalysisofautismspectrumdisorderandcomorbidbraindisorders |