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Original Contributions |

Loss of Braking Signals During Inflammation:  A Factor Affecting the Development and Disease Course of Multiple Sclerosis

Francesca Gilli, PhD; Nicole Désirée Navone, MSc; Simona Perga, PhD; Fabiana Marnetto, MSc; Marzia Caldano, PharmD; Marco Capobianco, MD; Annalisa Pulizzi, MD; Simona Malucchi, MD; Antonio Bertolotto, MD
Arch Neurol. 2011;68(7):879-888. doi:10.1001/archneurol.2011.32.
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Background In a recent genome-wide transcriptional analysis, we identified a gene signature for multiple sclerosis (MS), which reverted back to normal during pregnancy. Reversion was particularly evident for 7 genes: SOCS2, TNFAIP3, NR4A2, CXCR4, POLR2J, FAM49B, and STAG3L1, most of which encode negative regulators of inflammation.

Objectives To corroborate dysregulation of genes, to evaluate the prognostic value of genes, and to study modulation of genes during different treatments.

Design Comparison study.

Setting Italian referral center for MS.

Patients Quantitative polymerase chain reaction measurements were performed for 274 patients with MS and 60 healthy controls. Of the 274 patients with MS, 113 were treatment-naive patients in the initial stages of their disorder who were followed up in real-world clinical settings and categorized on the basis of disease course. The remaining 161 patients with MS received disease-modifying therapies (55 patients were treated with interferon beta, 52 with glatiramer acetate, and 54 with natalizumab) for a mean (SD) of 12 (2) months.

Main Outcome Measures Gene expression levels, relapse rate, and change in Expanded Disability Status Scale.

Results We found a dysregulated gene pathway (P ≤ .006), with a downregulation of genes encoding negative regulators. The SOCS2, NR4A2, and TNFAIP3 genes were inversely correlated with both relapse rate (P ≤ .002) and change in Expanded Disability Status Scale (P ≤ .005). SOCS2 was modulated by both interferon beta and glatiramer acetate, TNFAIP3 was modulated by glatiramer acetate, and NR4A2 was not altered at all. No changes were induced by natalizumab.

Conclusions We demonstrate that there is a new molecular pathogenic mechanism that underlies the initiation and progression of MS. Defects in negative-feedback loops of inflammation lead to an overactivation of the immune system so as to predispose the brain to inflammation-sensitive MS.

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Figures

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Figure 1. Patient groups with regard to real-world clinical management at baseline and follow-up. AZA indicates azathioprine sodium; DMT, disease-modifying therapy; GA, glatiramer acetate; IFN-β, interferon beta; METH, methotrexate sodium; MITO, mitoxantrone hydrochloride; MS, multiple sclerosis; and NAT, natalizumab.

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Figure 2. Comparison of mean gene expression levels of (A) CXCR4, (B) SOCS2, (C) TNFAIP3, (D) NR4A2, (E) FAM49B, (F) POLR2J, and (G) STAG3L1 among 60 healthy controls, 113 treatment-naive patients, and 161 patients with multiple sclerosis (MS) who received disease-modifying therapy (55 with interferon beta [IFN-β], 54 with natalizumab [NAT], and 52 with glatiramer acetate [GA]). Such an analysis disclosed dysregulation for the 7 genes in treatment-naive patients compared with healthy controls (P ≤ .007). Treatment with NAT leads to the reversion in expression of 1 of 7 genes (ie, FAM49B). Treatment with GA therapy leads to the reversion in expression of 5 of 7 genes (ie, TNFAIP3, SOCS2, FAM49B, POLR2J, and STAG3L1). Treatment with IFN-β leads to the reversion in expression of 3 of 7 genes (ie, CXCR4, FAM49B, and SOCS2); the latter regulation was observed in patients negative for neutralizing antibodies (NAb) but not in patients positive for NAb (NAb+). * P ≤ .05, † P ≤ .01, and ‡ P ≤ .001. P values are calculated for differences between healthy controls and patients with MS (both untreated patients and patients receiving DMT).

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Figure 3. Comparison of mean gene expression levels of (A) CXCR4, (B) SOCS2, (C) TNFAIP3, (D) NR4A2, (E) FAM49B, (F) POLR2J, and (G) STAG3L1 in healthy controls and in patients with multiple sclerosis who were subdivided into “aggressive” and “nonaggressive” on the basis of their clinical course after providing a blood sample. Horizontal bars indicate median values.

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Figure 4. Relationships between annualized changes in Expanded Disability Status Scale score (ΔEDSS) and baseline messenger RNA levels of SOCS2 (A and B), NR4A2 (C and D), and TNFAIP3 (E and F) in 101 patients with multiple sclerosis. B, D, and F, Correlations between ΔEDSS and gene expression after log transformation of nonnormally distributed variables. P ≤ .005 for all correlations.

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Figure 5. Relationships between relapse rate (RR) and baseline messenger RNA levels of SOCS2 (A and B), NR4A2 (C and D), and TNFAIP3 (E and F) in 101 patients with multiple sclerosis. B, D, and F, Correlations between RR and gene expression after log transformation of nonnormally distributed variables. P ≤ .002 for all correlations.

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