A deep transcriptome meta-analysis reveals sex differences in multiple sclerosis.


Journal

Neurobiology of disease
ISSN: 1095-953X
Titre abrégé: Neurobiol Dis
Pays: United States
ID NLM: 9500169

Informations de publication

Date de publication:
01 06 2023
Historique:
received: 07 12 2022
revised: 17 03 2023
accepted: 30 03 2023
medline: 17 5 2023
pubmed: 7 4 2023
entrez: 6 4 2023
Statut: ppublish

Résumé

Multiple sclerosis (MS), a chronic auto-immune, inflammatory, and degenerative disease of the central nervous system, affects both males and females; however, females suffer from a higher risk of developing MS (2-3:1 ratio relative to males). The precise sex-based factors influencing risk of MS are currently unknown. Here, we explore the role of sex in MS to identify molecular mechanisms underlying observed MS sex differences that may guide novel therapeutic approaches tailored for males or females. We performed a rigorous and systematic review of genome-wide transcriptome studies of MS that included patient sex data in the Gene Expression Omnibus and ArrayExpress databases following PRISMA statement guidelines. For each selected study, we analyzed differential gene expression to explore the impact of the disease in females (IDF), in males (IDM) and our main goal: the sex differential impact of the disease (SDID). Then, for each scenario (IDF, IDM and SDID) we performed 2 meta-analyses in the main tissues involved in the disease (brain and blood). Finally, we performed a gene set analysis in brain tissue, in which a higher number of genes were dysregulated, to characterize sex differences in biological pathways. After screening 122 publications, the systematic review provided a selection of 9 studies (5 in blood and 4 in brain tissue) with a total of 474 samples (189 females with MS and 109 control females; 82 males with MS and 94 control males). Blood and brain tissue meta-analyses identified, respectively, 1 (KIR2DL3) and 13 (ARL17B, CECR7, CEP78, IFFO2, LOC401127, NUDT18, RNF10, SLC17A5, STMP1, TRAF3IP2-AS1, UBXN2B, ZNF117, ZNF488) MS-associated genes that differed between males and females (SDID comparison). Functional analyses in the brain revealed different altered immune patterns in females and males (IDF and IDM comparisons). The pro-inflammatory environment and innate immune responses related to myeloid lineage appear to be more affected in females, while adaptive responses associated with the lymphocyte lineage in males. Additionally, females with MS displayed alterations in mitochondrial respiratory chain complexes, purine, and glutamate metabolism, while MS males displayed alterations in stress response to metal ion, amine, and amino acid transport. We found transcriptomic and functional differences between MS males and MS females (especially in the immune system), which may support the development of new sex-based research of this disease. Our study highlights the importance of understanding the role of biological sex in MS to guide a more personalized medicine.

Sections du résumé

BACKGROUND
Multiple sclerosis (MS), a chronic auto-immune, inflammatory, and degenerative disease of the central nervous system, affects both males and females; however, females suffer from a higher risk of developing MS (2-3:1 ratio relative to males). The precise sex-based factors influencing risk of MS are currently unknown. Here, we explore the role of sex in MS to identify molecular mechanisms underlying observed MS sex differences that may guide novel therapeutic approaches tailored for males or females.
METHODS
We performed a rigorous and systematic review of genome-wide transcriptome studies of MS that included patient sex data in the Gene Expression Omnibus and ArrayExpress databases following PRISMA statement guidelines. For each selected study, we analyzed differential gene expression to explore the impact of the disease in females (IDF), in males (IDM) and our main goal: the sex differential impact of the disease (SDID). Then, for each scenario (IDF, IDM and SDID) we performed 2 meta-analyses in the main tissues involved in the disease (brain and blood). Finally, we performed a gene set analysis in brain tissue, in which a higher number of genes were dysregulated, to characterize sex differences in biological pathways.
RESULTS
After screening 122 publications, the systematic review provided a selection of 9 studies (5 in blood and 4 in brain tissue) with a total of 474 samples (189 females with MS and 109 control females; 82 males with MS and 94 control males). Blood and brain tissue meta-analyses identified, respectively, 1 (KIR2DL3) and 13 (ARL17B, CECR7, CEP78, IFFO2, LOC401127, NUDT18, RNF10, SLC17A5, STMP1, TRAF3IP2-AS1, UBXN2B, ZNF117, ZNF488) MS-associated genes that differed between males and females (SDID comparison). Functional analyses in the brain revealed different altered immune patterns in females and males (IDF and IDM comparisons). The pro-inflammatory environment and innate immune responses related to myeloid lineage appear to be more affected in females, while adaptive responses associated with the lymphocyte lineage in males. Additionally, females with MS displayed alterations in mitochondrial respiratory chain complexes, purine, and glutamate metabolism, while MS males displayed alterations in stress response to metal ion, amine, and amino acid transport.
CONCLUSION
We found transcriptomic and functional differences between MS males and MS females (especially in the immune system), which may support the development of new sex-based research of this disease. Our study highlights the importance of understanding the role of biological sex in MS to guide a more personalized medicine.

Identifiants

pubmed: 37023829
pii: S0969-9961(23)00127-4
doi: 10.1016/j.nbd.2023.106113
pii:
doi:

Substances chimiques

RNF10 protein, human 0
Carrier Proteins 0
CEP78 protein, human 0
Cell Cycle Proteins 0

Types de publication

Meta-Analysis Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

106113

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

Auteurs

José Francisco Català-Senent (JF)

Bioinformatics and Biostatistics Unit, Principe Felipe Research Center (CIPF), 46012 Valencia, Spain.

Zoraida Andreu (Z)

Foundation Valencian Institute of Oncology (FIVO), 46009 Valencia, Spain.

Marta R Hidalgo (MR)

Bioinformatics and Biostatistics Unit, Principe Felipe Research Center (CIPF), 46012 Valencia, Spain.

Irene Soler-Sáez (I)

Bioinformatics and Biostatistics Unit, Principe Felipe Research Center (CIPF), 46012 Valencia, Spain.

Francisco José Roig (FJ)

Bioinformatics and Biostatistics Unit, Principe Felipe Research Center (CIPF), 46012 Valencia, Spain; Faculty of Health Sciences, San Jorge University, 50830 Zaragoza, Spain.

Natalia Yanguas-Casás (N)

Instituto de Investigación Sanitaria Puerta de Hierro-Segovia de Arana (IDIPHISA), Grupo de Investigación en Linfomas, C/Joaquín Rodrigo 2, Majadahonda, 28222 Madrid, Spain.

Almudena Neva-Alejo (A)

Bioinformatics and Biostatistics Unit, Principe Felipe Research Center (CIPF), 46012 Valencia, Spain.

Adolfo López-Cerdán (A)

Biomedical Imaging Unit FISABIO-CIPF, Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunidad Valenciana, 46012 Valencia, Spain.

María de la Iglesia-Vayá (M)

Biomedical Imaging Unit FISABIO-CIPF, Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunidad Valenciana, 46012 Valencia, Spain.

Barbara E Stranger (BE)

Department of Pharmacology, Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

Francisco García-García (F)

Bioinformatics and Biostatistics Unit, Principe Felipe Research Center (CIPF), 46012 Valencia, Spain. Electronic address: fgarcia@cipf.es.

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Classifications MeSH