In Silico Analysis Highlights Potential Predictive Indicators Associated with Secondary Progressive Multiple Sclerosis
Multiple sclerosis (MS) is a complex inflammatory disease affecting the central nervous system. Most commonly, it begins with recurrent symptoms followed by partial or complete recovery, known as relapsing–remitting MS (RRMS). Over time, many RRMS patients progress to secondary progressive MS (SPMS)...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-03-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/25/6/3374 |
| _version_ | 1797240705860501504 |
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| author | Marco Calabrò Maria Lui Emanuela Mazzon Simone D’Angiolini |
| author_facet | Marco Calabrò Maria Lui Emanuela Mazzon Simone D’Angiolini |
| author_sort | Marco Calabrò |
| collection | DOAJ |
| description | Multiple sclerosis (MS) is a complex inflammatory disease affecting the central nervous system. Most commonly, it begins with recurrent symptoms followed by partial or complete recovery, known as relapsing–remitting MS (RRMS). Over time, many RRMS patients progress to secondary progressive MS (SPMS), marked by gradual symptom deterioration. The factors triggering this transition remain unknown, lacking predictive biomarkers. This study aims to identify blood biomarkers specific to SPMS. We analyzed six datasets of SPMS and RRMS patients’ blood and brain tissues, and compared the differential expressed genes (DEGs) obtained to highlight DEGs reflecting alterations occurring in both brain and blood tissues and the potential biological processes involved. We observed a total of 38 DEGs up-regulated in both blood and brain tissues, and their interaction network was evaluated through network analysis. Among the aforementioned DEGs, 21 may be directly involved with SPMS transition. Further, we highlighted three biological processes, including the calcineurin–NFAT pathway, related to this transition. The investigated DEGs may serve as a promising means to monitor the transition from RRMS to SPMS, which is still elusive. Given that they can also be sourced from blood samples, this approach could offer a relatively rapid and convenient method for monitoring MS and facilitating expedited assessments. |
| first_indexed | 2024-04-24T18:11:41Z |
| format | Article |
| id | doaj.art-ba3332c5bafb44fda7eb0e7016c86b6c |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-04-24T18:11:41Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-ba3332c5bafb44fda7eb0e7016c86b6c2024-03-27T13:45:53ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672024-03-01256337410.3390/ijms25063374In Silico Analysis Highlights Potential Predictive Indicators Associated with Secondary Progressive Multiple SclerosisMarco Calabrò0Maria Lui1Emanuela Mazzon2Simone D’Angiolini3IRCCS Centro Neurolesi “Bonino-Pulejo”, Via Provinciale Palermo, Contrada Casazza, 98124 Messina, ItalyIRCCS Centro Neurolesi “Bonino-Pulejo”, Via Provinciale Palermo, Contrada Casazza, 98124 Messina, ItalyIRCCS Centro Neurolesi “Bonino-Pulejo”, Via Provinciale Palermo, Contrada Casazza, 98124 Messina, ItalyIRCCS Centro Neurolesi “Bonino-Pulejo”, Via Provinciale Palermo, Contrada Casazza, 98124 Messina, ItalyMultiple sclerosis (MS) is a complex inflammatory disease affecting the central nervous system. Most commonly, it begins with recurrent symptoms followed by partial or complete recovery, known as relapsing–remitting MS (RRMS). Over time, many RRMS patients progress to secondary progressive MS (SPMS), marked by gradual symptom deterioration. The factors triggering this transition remain unknown, lacking predictive biomarkers. This study aims to identify blood biomarkers specific to SPMS. We analyzed six datasets of SPMS and RRMS patients’ blood and brain tissues, and compared the differential expressed genes (DEGs) obtained to highlight DEGs reflecting alterations occurring in both brain and blood tissues and the potential biological processes involved. We observed a total of 38 DEGs up-regulated in both blood and brain tissues, and their interaction network was evaluated through network analysis. Among the aforementioned DEGs, 21 may be directly involved with SPMS transition. Further, we highlighted three biological processes, including the calcineurin–NFAT pathway, related to this transition. The investigated DEGs may serve as a promising means to monitor the transition from RRMS to SPMS, which is still elusive. Given that they can also be sourced from blood samples, this approach could offer a relatively rapid and convenient method for monitoring MS and facilitating expedited assessments.https://www.mdpi.com/1422-0067/25/6/3374secondary progressive multiple sclerosistranscriptomic analysisblood samplesbrain samplesbiomarkers |
| spellingShingle | Marco Calabrò Maria Lui Emanuela Mazzon Simone D’Angiolini In Silico Analysis Highlights Potential Predictive Indicators Associated with Secondary Progressive Multiple Sclerosis International Journal of Molecular Sciences secondary progressive multiple sclerosis transcriptomic analysis blood samples brain samples biomarkers |
| title | In Silico Analysis Highlights Potential Predictive Indicators Associated with Secondary Progressive Multiple Sclerosis |
| title_full | In Silico Analysis Highlights Potential Predictive Indicators Associated with Secondary Progressive Multiple Sclerosis |
| title_fullStr | In Silico Analysis Highlights Potential Predictive Indicators Associated with Secondary Progressive Multiple Sclerosis |
| title_full_unstemmed | In Silico Analysis Highlights Potential Predictive Indicators Associated with Secondary Progressive Multiple Sclerosis |
| title_short | In Silico Analysis Highlights Potential Predictive Indicators Associated with Secondary Progressive Multiple Sclerosis |
| title_sort | in silico analysis highlights potential predictive indicators associated with secondary progressive multiple sclerosis |
| topic | secondary progressive multiple sclerosis transcriptomic analysis blood samples brain samples biomarkers |
| url | https://www.mdpi.com/1422-0067/25/6/3374 |
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