In Silico and In Vivo Analysis of IL37 in Multiple Sclerosis Reveals Its Probable Homeostatic Role on the Clinical Activity, Disability, and Treatment with Fingolimod

Abstract

We evaluated the in silico expression and circulating levels of interleukin (IL)37 in patients with different forms of multiple sclerosis (MS) and also upon treatment with different disease-modifying drugs. The combined interpretation of the resulting data strengthens and extends the current emerging concept that endogenous IL37 plays an important role in determining onset and progression of MS. The in silico analysis revealed that production of IL37 from cluster of differentiation (CD)4+ T cells from MS patients was reduced in vitro as compared to healthy controls. The analysis of the datasets also demonstrated that "higher" levels of IL37 production from PBMC entailed significant protection from MS relapses. In addition, the in vivo part of the study showed that IL37 was selectively augmented in the sera of MS patients during a relapse and that treatment with the high potency disease-modifying drug fingolimod significantly increased the frequency of patients with circulating blood levels of IL37 (6/9, 66%) as compared to patients receiving no treatment (n = 48) or platform therapy (n = 59) who had levels of IL37 below the limit of the sensitivity of the assay. This finding therefore anticipates that fingolimod may at least partially exert its beneficial effects in MS by upregulating the production of IL37.

Impaired Expression of Tetraspanin 32 (TSPAN32) in Memory T Cells of Patients with Multiple Sclerosis

“…We also studied the possible diagnostic and prognostic value of TSPAN32 expression in PBMC of MS patients, on the course of the disease. The use of whole-genome expression databases has been largely exploited [25][26][27][28] for the characterization of pathogenic pathways and to identify therapeutic targets for a variety of disorders, including immunoinflammatory and autoimmune diseases [29][30][31][32][33][34][35][36], cancer [37][38][39], and has allowed dismantling pathogenetic pathways [40][41][42], along with the identification of novel tailored therapeutic targets [43][44][45][46].…”

Exploratory Analysis of iPSCS-Derived Neuronal Cells as Predictors of Diagnosis and Treatment of Alzheimer Disease

“…To this aim, gene expression signatures obtained from -omics data [28] are used to discover novel mechanisms of disease and searches inverse drug-disease relationships by matching gene expression profiles. We and others have used whole-genome expression databases for the better understanding of pathogenic pathways and the prediction of diagnostic and therapeutic strategies for a series of disorders-e.g., immunoinflammatory and autoimmune diseases [29][30][31][32][33][34][35][36][37], and cancer [38,39]-which has led to the identification of potential novel therapeutic targets [40][41][42][43][44][45][46][47][48][49][50][51]. However, gene perturbation alone cannot accurately predict treatment options due to variability related to disease genetics and epigenetics, as well as, experimental settings.…”

<p>Rituximab Prevents the Development of Experimental Autoimmune Encephalomyelitis (EAE): Comparison with Prophylactic, Therapeutic or Combinational Regimens</p>

“…31 Similar method was used to investigate the role of IL-37 in MS patients, and how this cytokine might influence the disease before or after therapy. 32 Also, the role of Tetraspanin-32 in MS was explored utilizing ex vivo and in silico analysis. 33 Based on in silico analysis we performed immunohistochemical studies to corroborate the effects of RTX in ameliorating the EAE clinical scores with histological examination of brain tissues.…”