TY - JOUR
T1 - Cladribine and ocrelizumab induce differential miRNA profiles in peripheral blood mononucleated cells from relapsing–remitting multiple sclerosis patients
AU - Arisi, Ivan
AU - Malimpensa, Leonardo
AU - Manzini, Valeria
AU - Brandi, Rossella
AU - Gosetti di Sturmeck, Tommaso
AU - D’Amelio, Chiara
AU - Crisafulli, Sebastiano
AU - Ferrazzano, Gina
AU - Belvisi, Daniele
AU - Malerba, Francesca
AU - Florio, Rita
AU - Pascale, Esterina
AU - Soreq, Hermona
AU - Salvetti, Marco
AU - Cattaneo, Antonino
AU - D’Onofrio, Mara
AU - Conte, Antonella
N1 - Publisher Copyright:
Copyright © 2023 Arisi, Malimpensa, Manzini, Brandi, Gosetti di Sturmeck, D’Amelio, Crisafulli, Ferrazzano, Belvisi, Malerba, Florio, Pascale, Soreq, Salvetti, Cattaneo, D’Onofrio and Conte.
PY - 2023
Y1 - 2023
N2 - Background and objectives: Multiple sclerosis (MS) is a chronic, progressive neurological disease characterized by early-stage neuroinflammation, neurodegeneration, and demyelination that involves a spectrum of heterogeneous clinical manifestations in terms of disease course and response to therapy. Even though several disease-modifying therapies (DMTs) are available to prevent MS-related brain damage—acting on the peripheral immune system with an indirect effect on MS lesions—individualizing therapy according to disease characteristics and prognostic factors is still an unmet need. Given that deregulated miRNAs have been proposed as diagnostic tools in neurodegenerative/neuroinflammatory diseases such as MS, we aimed to explore miRNA profiles as potential classifiers of the relapsing–remitting MS (RRMS) patients’ prospects to gain a more effective DMT choice and achieve a preferential drug response. Methods: A total of 25 adult patients with RRMS were enrolled in a cohort study, according to the latest McDonald criteria before (pre-cladribine, pre-CLA; pre-ocrelizumab, pre-OCRE, time T0) and after high-efficacy DMTs, time T1, 6 months post-CLA (n = 10, 7 F and 3 M, age 39.0 ± 7.5) or post-OCRE (n = 15, 10 F and 5 M, age 40.5 ± 10.4) treatment. A total of 15 age- and sex-matched healthy control subjects (9 F and 6 M, age 36.3 ± 3.0) were also selected. By using Agilent microarrays, we analyzed miRNA profiles from peripheral blood mononuclear cells (PBMC). miRNA–target networks were obtained by miRTargetLink, and Pearson’s correlation served to estimate the association between miRNAs and outcome clinical features. Results: First, the miRNA profiles of pre-CLA or pre-OCRE RRMS patients compared to healthy controls identified modulated miRNA patterns (40 and seven miRNAs, respectively). A direct comparison of the two pre-treatment groups at T0 and T1 revealed more pro-inflammatory patterns in the pre-CLA miRNA profiles. Moreover, both DMTs emerged as being capable of reverting some dysregulated miRNAs toward a protective phenotype. Both drug-dependent miRNA profiles and specific miRNAs, such as miR-199a-3p, miR-29b-3p, and miR-151a-3p, emerged as potentially involved in these drug-induced mechanisms. This enabled the selection of miRNAs correlated to clinical features and the related miRNA–mRNA network. Discussion: These data support the hypothesis of specific deregulated miRNAs as putative biomarkers in RRMS patients’ stratification and DMT drug response.
AB - Background and objectives: Multiple sclerosis (MS) is a chronic, progressive neurological disease characterized by early-stage neuroinflammation, neurodegeneration, and demyelination that involves a spectrum of heterogeneous clinical manifestations in terms of disease course and response to therapy. Even though several disease-modifying therapies (DMTs) are available to prevent MS-related brain damage—acting on the peripheral immune system with an indirect effect on MS lesions—individualizing therapy according to disease characteristics and prognostic factors is still an unmet need. Given that deregulated miRNAs have been proposed as diagnostic tools in neurodegenerative/neuroinflammatory diseases such as MS, we aimed to explore miRNA profiles as potential classifiers of the relapsing–remitting MS (RRMS) patients’ prospects to gain a more effective DMT choice and achieve a preferential drug response. Methods: A total of 25 adult patients with RRMS were enrolled in a cohort study, according to the latest McDonald criteria before (pre-cladribine, pre-CLA; pre-ocrelizumab, pre-OCRE, time T0) and after high-efficacy DMTs, time T1, 6 months post-CLA (n = 10, 7 F and 3 M, age 39.0 ± 7.5) or post-OCRE (n = 15, 10 F and 5 M, age 40.5 ± 10.4) treatment. A total of 15 age- and sex-matched healthy control subjects (9 F and 6 M, age 36.3 ± 3.0) were also selected. By using Agilent microarrays, we analyzed miRNA profiles from peripheral blood mononuclear cells (PBMC). miRNA–target networks were obtained by miRTargetLink, and Pearson’s correlation served to estimate the association between miRNAs and outcome clinical features. Results: First, the miRNA profiles of pre-CLA or pre-OCRE RRMS patients compared to healthy controls identified modulated miRNA patterns (40 and seven miRNAs, respectively). A direct comparison of the two pre-treatment groups at T0 and T1 revealed more pro-inflammatory patterns in the pre-CLA miRNA profiles. Moreover, both DMTs emerged as being capable of reverting some dysregulated miRNAs toward a protective phenotype. Both drug-dependent miRNA profiles and specific miRNAs, such as miR-199a-3p, miR-29b-3p, and miR-151a-3p, emerged as potentially involved in these drug-induced mechanisms. This enabled the selection of miRNAs correlated to clinical features and the related miRNA–mRNA network. Discussion: These data support the hypothesis of specific deregulated miRNAs as putative biomarkers in RRMS patients’ stratification and DMT drug response.
KW - DMT
KW - PBMC
KW - biomarker
KW - cladribine
KW - miRNA
KW - multiple sclerosis
KW - ocrelizumab
UR - http://www.scopus.com/inward/record.url?scp=85180659550&partnerID=8YFLogxK
U2 - 10.3389/fimmu.2023.1234869
DO - 10.3389/fimmu.2023.1234869
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C2 - 38152407
AN - SCOPUS:85180659550
SN - 1664-3224
VL - 14
JO - Frontiers in Immunology
JF - Frontiers in Immunology
M1 - 1234869
ER -