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Identification of molecular signatures and pathways involved in Rett syndrome using a multi-omics approach
BACKGROUND: Rett syndrome (RTT) is a neurodevelopmental disorder mainly caused by mutations in the methyl-CpG-binding protein 2 gene (MECP2). MeCP2 is a multi-functional protein involved in many cellular processes, but the mechanisms by which its dysfunction causes disease are not fully understood....
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/PMC10503149/ https://www.ncbi.nlm.nih.gov/pubmed/37710353 http://dx.doi.org/10.1186/s40246-023-00532-1 |
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author | Pascual-Alonso, Ainhoa Xiol, Clara Smirnov, Dmitrii Kopajtich, Robert Prokisch, Holger Armstrong, Judith |
author_facet | Pascual-Alonso, Ainhoa Xiol, Clara Smirnov, Dmitrii Kopajtich, Robert Prokisch, Holger Armstrong, Judith |
author_sort | Pascual-Alonso, Ainhoa |
collection | PubMed |
description | BACKGROUND: Rett syndrome (RTT) is a neurodevelopmental disorder mainly caused by mutations in the methyl-CpG-binding protein 2 gene (MECP2). MeCP2 is a multi-functional protein involved in many cellular processes, but the mechanisms by which its dysfunction causes disease are not fully understood. The duplication of the MECP2 gene causes a distinct disorder called MECP2 duplication syndrome (MDS), highlighting the importance of tightly regulating its dosage for proper cellular function. Additionally, some patients with mutations in genes other than MECP2 exhibit phenotypic similarities with RTT, indicating that these genes may also play a role in similar cellular functions. The purpose of this study was to characterise the molecular alterations in patients with RTT in order to identify potential biomarkers or therapeutic targets for this disorder. METHODS: We used a combination of transcriptomics (RNAseq) and proteomics (TMT mass spectrometry) to characterise the expression patterns in fibroblast cell lines from 22 patients with RTT and detected mutation in MECP2, 15 patients with MDS, 12 patients with RTT-like phenotypes and 13 healthy controls. Transcriptomics and proteomics data were used to identify differentially expressed genes at both RNA and protein levels, which were further inspected via enrichment and upstream regulator analyses and compared to find shared features in patients with RTT. RESULTS: We identified molecular alterations in cellular functions and pathways that may contribute to the disease phenotype in patients with RTT, such as deregulated cytoskeletal components, vesicular transport elements, ribosomal subunits and mRNA processing machinery. We also compared RTT expression profiles with those of MDS seeking changes in opposite directions that could lead to the identification of MeCP2 direct targets. Some of the deregulated transcripts and proteins were consistently affected in patients with RTT-like phenotypes, revealing potentially relevant molecular processes in patients with overlapping traits and different genetic aetiology. CONCLUSIONS: The integration of data in a multi-omics analysis has helped to interpret the molecular consequences of MECP2 dysfunction, contributing to the characterisation of the molecular landscape in patients with RTT. The comparison with MDS provides knowledge of MeCP2 direct targets, whilst the correlation with RTT-like phenotypes highlights processes potentially contributing to the pathomechanism leading these disorders. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40246-023-00532-1. |
format | Online Article Text |
id | pubmed-10503149 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-105031492023-09-16 Identification of molecular signatures and pathways involved in Rett syndrome using a multi-omics approach Pascual-Alonso, Ainhoa Xiol, Clara Smirnov, Dmitrii Kopajtich, Robert Prokisch, Holger Armstrong, Judith Hum Genomics Research BACKGROUND: Rett syndrome (RTT) is a neurodevelopmental disorder mainly caused by mutations in the methyl-CpG-binding protein 2 gene (MECP2). MeCP2 is a multi-functional protein involved in many cellular processes, but the mechanisms by which its dysfunction causes disease are not fully understood. The duplication of the MECP2 gene causes a distinct disorder called MECP2 duplication syndrome (MDS), highlighting the importance of tightly regulating its dosage for proper cellular function. Additionally, some patients with mutations in genes other than MECP2 exhibit phenotypic similarities with RTT, indicating that these genes may also play a role in similar cellular functions. The purpose of this study was to characterise the molecular alterations in patients with RTT in order to identify potential biomarkers or therapeutic targets for this disorder. METHODS: We used a combination of transcriptomics (RNAseq) and proteomics (TMT mass spectrometry) to characterise the expression patterns in fibroblast cell lines from 22 patients with RTT and detected mutation in MECP2, 15 patients with MDS, 12 patients with RTT-like phenotypes and 13 healthy controls. Transcriptomics and proteomics data were used to identify differentially expressed genes at both RNA and protein levels, which were further inspected via enrichment and upstream regulator analyses and compared to find shared features in patients with RTT. RESULTS: We identified molecular alterations in cellular functions and pathways that may contribute to the disease phenotype in patients with RTT, such as deregulated cytoskeletal components, vesicular transport elements, ribosomal subunits and mRNA processing machinery. We also compared RTT expression profiles with those of MDS seeking changes in opposite directions that could lead to the identification of MeCP2 direct targets. Some of the deregulated transcripts and proteins were consistently affected in patients with RTT-like phenotypes, revealing potentially relevant molecular processes in patients with overlapping traits and different genetic aetiology. CONCLUSIONS: The integration of data in a multi-omics analysis has helped to interpret the molecular consequences of MECP2 dysfunction, contributing to the characterisation of the molecular landscape in patients with RTT. The comparison with MDS provides knowledge of MeCP2 direct targets, whilst the correlation with RTT-like phenotypes highlights processes potentially contributing to the pathomechanism leading these disorders. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40246-023-00532-1. BioMed Central 2023-09-15 /pmc/articles/PMC10503149/ /pubmed/37710353 http://dx.doi.org/10.1186/s40246-023-00532-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Pascual-Alonso, Ainhoa Xiol, Clara Smirnov, Dmitrii Kopajtich, Robert Prokisch, Holger Armstrong, Judith Identification of molecular signatures and pathways involved in Rett syndrome using a multi-omics approach |
title | Identification of molecular signatures and pathways involved in Rett syndrome using a multi-omics approach |
title_full | Identification of molecular signatures and pathways involved in Rett syndrome using a multi-omics approach |
title_fullStr | Identification of molecular signatures and pathways involved in Rett syndrome using a multi-omics approach |
title_full_unstemmed | Identification of molecular signatures and pathways involved in Rett syndrome using a multi-omics approach |
title_short | Identification of molecular signatures and pathways involved in Rett syndrome using a multi-omics approach |
title_sort | identification of molecular signatures and pathways involved in rett syndrome using a multi-omics approach |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503149/ https://www.ncbi.nlm.nih.gov/pubmed/37710353 http://dx.doi.org/10.1186/s40246-023-00532-1 |
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