Identification of Key Genes and Regulatory Pathways in Multiple Sclerosis Brain Samples: A Meta-Analysis of Micro-Array Datasets.

Jansen, MI; Castorina, A

Identification of Key Genes and Regulatory Pathways in Multiple Sclerosis Brain Samples: A Meta-Analysis of Micro-Array Datasets.

Jansen, MI Castorina, A

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Publisher:: MDPI
Publication Type:: Journal Article
Citation:: Int J Mol Sci, 2023, 24, (11), pp. 9361
Issue Date:: 2023-05-27

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Field	Value	Language
dc.contributor.author	Jansen, MI
dc.contributor.author	Castorina, A https://orcid.org/0000-0001-7037-759X
dc.date.accessioned	2024-01-08T05:30:21Z
dc.date.available	2023-05-25
dc.date.available	2024-01-08T05:30:21Z
dc.date.issued	2023-05-27
dc.identifier.citation	Int J Mol Sci, 2023, 24, (11), pp. 9361
dc.identifier.issn	1422-0067
dc.identifier.issn	1422-0067
dc.identifier.uri	http://hdl.handle.net/10453/174098
dc.description.abstract	Multiple sclerosis (MS) is an autoimmune disorder of the central nervous system (CNS) whose aetiology is only partly understood. Investigating the intricate transcriptional changes occurring in MS brains is critical to unravel novel pathogenic mechanisms and therapeutic targets. Unfortunately, this process is often hindered by the difficulty in retrieving an adequate number of samples. However, by merging data from publicly available datasets, it is possible to identify alterations in gene expression profiles and regulatory pathways that were previously overlooked. Here, we merged microarray gene expression profiles obtained from CNS white matter samples taken from MS donors to identify novel differentially expressed genes (DEGs) linked with MS. Data from three independent datasets (GSE38010, GSE32915, and GSE108000) were combined and used to detect novel DEGs using the Stouffer's Z-score method. Corresponding regulatory pathways were analysed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases. Finally, top up- and down-regulated transcripts were validated by real-time quantitative PCR (qPCR) using an independent set of white matter tissue samples obtained from MS donors with different disease subtypes. There were a total of 1446 DEGs, of which 742 were up-regulated and 704 genes were down-regulated. DEGs were associated with several myelin-related pathways and protein metabolism pathways. Validation studies of selected top up- or down-regulated genes highlighted MS subtype-specific differences in the expression of some of the identified genes, underlining a more complex scenario of white matter pathology amongst people afflicted by this devastating disease.
dc.format	Electronic
dc.language	eng
dc.publisher	MDPI
dc.relation.ispartof	Int J Mol Sci
dc.relation.isbasedon	10.3390/ijms24119361
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	0399 Other Chemical Sciences, 0604 Genetics, 0699 Other Biological Sciences
dc.subject.classification	Chemical Physics
dc.subject.classification	3101 Biochemistry and cell biology
dc.subject.classification	3107 Microbiology
dc.subject.classification	3404 Medicinal and biomolecular chemistry
dc.subject.mesh	Humans
dc.subject.mesh	Multiple Sclerosis
dc.subject.mesh	Gene Expression Profiling
dc.subject.mesh	Brain
dc.subject.mesh	Microarray Analysis
dc.subject.mesh	Central Nervous System
dc.subject.mesh	Computational Biology
dc.subject.mesh	Gene Regulatory Networks
dc.subject.mesh	Central Nervous System
dc.subject.mesh	Brain
dc.subject.mesh	Humans
dc.subject.mesh	Multiple Sclerosis
dc.subject.mesh	Microarray Analysis
dc.subject.mesh	Gene Expression Profiling
dc.subject.mesh	Computational Biology
dc.subject.mesh	Gene Regulatory Networks
dc.subject.mesh	Humans
dc.subject.mesh	Multiple Sclerosis
dc.subject.mesh	Gene Expression Profiling
dc.subject.mesh	Brain
dc.subject.mesh	Microarray Analysis
dc.subject.mesh	Central Nervous System
dc.subject.mesh	Computational Biology
dc.subject.mesh	Gene Regulatory Networks
dc.title	Identification of Key Genes and Regulatory Pathways in Multiple Sclerosis Brain Samples: A Meta-Analysis of Micro-Array Datasets.
dc.type	Journal Article
utslib.citation.volume	24
utslib.location.activity	Switzerland
utslib.for	0399 Other Chemical Sciences
utslib.for	0604 Genetics
utslib.for	0699 Other Biological Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Centre for Health Technologies (CHT)
utslib.copyright.status	open_access	*
dc.date.updated	2024-01-08T05:30:15Z
pubs.issue	11
pubs.publication-status	Published online
pubs.volume	24
utslib.citation.issue	11

Abstract:

Multiple sclerosis (MS) is an autoimmune disorder of the central nervous system (CNS) whose aetiology is only partly understood. Investigating the intricate transcriptional changes occurring in MS brains is critical to unravel novel pathogenic mechanisms and therapeutic targets. Unfortunately, this process is often hindered by the difficulty in retrieving an adequate number of samples. However, by merging data from publicly available datasets, it is possible to identify alterations in gene expression profiles and regulatory pathways that were previously overlooked. Here, we merged microarray gene expression profiles obtained from CNS white matter samples taken from MS donors to identify novel differentially expressed genes (DEGs) linked with MS. Data from three independent datasets (GSE38010, GSE32915, and GSE108000) were combined and used to detect novel DEGs using the Stouffer's Z-score method. Corresponding regulatory pathways were analysed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases. Finally, top up- and down-regulated transcripts were validated by real-time quantitative PCR (qPCR) using an independent set of white matter tissue samples obtained from MS donors with different disease subtypes. There were a total of 1446 DEGs, of which 742 were up-regulated and 704 genes were down-regulated. DEGs were associated with several myelin-related pathways and protein metabolism pathways. Validation studies of selected top up- or down-regulated genes highlighted MS subtype-specific differences in the expression of some of the identified genes, underlining a more complex scenario of white matter pathology amongst people afflicted by this devastating disease.

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http://hdl.handle.net/10453/174098