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Single-nucleus gene and gene set expression-based similarity network fusion identifies autism molecular subtypes
BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is highly phenotypically and genetically heterogeneous. With the accumulation of biological sequencing data, more and more studies shift to molecular subtype-first approach, from identifying molecular subtypes b...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10091652/ https://www.ncbi.nlm.nih.gov/pubmed/37041460 http://dx.doi.org/10.1186/s12859-023-05278-0 |
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author | Zhang, Junjie Ji, Guoli Gao, Xilin Guan, Jinting |
author_facet | Zhang, Junjie Ji, Guoli Gao, Xilin Guan, Jinting |
author_sort | Zhang, Junjie |
collection | PubMed |
description | BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is highly phenotypically and genetically heterogeneous. With the accumulation of biological sequencing data, more and more studies shift to molecular subtype-first approach, from identifying molecular subtypes based on genetic and molecular data to linking molecular subtypes with clinical manifestation, which can reduce heterogeneity before phenotypic profiling. RESULTS: In this study, we perform similarity network fusion to integrate gene and gene set expression data of multiple human brain cell types for ASD molecular subtype identification. Then we apply subtype-specific differential gene and gene set expression analyses to study expression patterns specific to molecular subtypes in each cell type. To demonstrate the biological and practical significance, we analyze the molecular subtypes, investigate their correlation with ASD clinical phenotype, and construct ASD molecular subtype prediction models. CONCLUSIONS: The identified molecular subtype-specific gene and gene set expression may be used to differentiate ASD molecular subtypes, facilitating the diagnosis and treatment of ASD. Our method provides an analytical pipeline for the identification of molecular subtypes and even disease subtypes of complex disorders. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05278-0. |
format | Online Article Text |
id | pubmed-10091652 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-100916522023-04-13 Single-nucleus gene and gene set expression-based similarity network fusion identifies autism molecular subtypes Zhang, Junjie Ji, Guoli Gao, Xilin Guan, Jinting BMC Bioinformatics Research BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is highly phenotypically and genetically heterogeneous. With the accumulation of biological sequencing data, more and more studies shift to molecular subtype-first approach, from identifying molecular subtypes based on genetic and molecular data to linking molecular subtypes with clinical manifestation, which can reduce heterogeneity before phenotypic profiling. RESULTS: In this study, we perform similarity network fusion to integrate gene and gene set expression data of multiple human brain cell types for ASD molecular subtype identification. Then we apply subtype-specific differential gene and gene set expression analyses to study expression patterns specific to molecular subtypes in each cell type. To demonstrate the biological and practical significance, we analyze the molecular subtypes, investigate their correlation with ASD clinical phenotype, and construct ASD molecular subtype prediction models. CONCLUSIONS: The identified molecular subtype-specific gene and gene set expression may be used to differentiate ASD molecular subtypes, facilitating the diagnosis and treatment of ASD. Our method provides an analytical pipeline for the identification of molecular subtypes and even disease subtypes of complex disorders. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05278-0. BioMed Central 2023-04-11 /pmc/articles/PMC10091652/ /pubmed/37041460 http://dx.doi.org/10.1186/s12859-023-05278-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Zhang, Junjie Ji, Guoli Gao, Xilin Guan, Jinting Single-nucleus gene and gene set expression-based similarity network fusion identifies autism molecular subtypes |
title | Single-nucleus gene and gene set expression-based similarity network fusion identifies autism molecular subtypes |
title_full | Single-nucleus gene and gene set expression-based similarity network fusion identifies autism molecular subtypes |
title_fullStr | Single-nucleus gene and gene set expression-based similarity network fusion identifies autism molecular subtypes |
title_full_unstemmed | Single-nucleus gene and gene set expression-based similarity network fusion identifies autism molecular subtypes |
title_short | Single-nucleus gene and gene set expression-based similarity network fusion identifies autism molecular subtypes |
title_sort | single-nucleus gene and gene set expression-based similarity network fusion identifies autism molecular subtypes |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10091652/ https://www.ncbi.nlm.nih.gov/pubmed/37041460 http://dx.doi.org/10.1186/s12859-023-05278-0 |
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