Contributions
Abstract: P953
Type: Poster
Abstract Category: Pathology and pathogenesis of MS - Genetics /Epigenetics and Pharmacogenetics
Background: fingolimod (FTY) is an oral treatment recently approved for relapsing-remitting (RR) multiple sclerosis (MS). No gene expression experiments have been performed at whole genome level to assess the transcriptional changes induced by the treatment.
Aim: to investigate the molecular mechanisms underlying FTY action, by looking at transcriptional alterations induced by the treatment.
Methods: whole blood samples were collected at baseline (BL) and after 6 months of FTY treatment in RRMS patients. We excluded subjects with a clinical relapse or steroid treatment in the month before FTY, treated with interferon or cyclophosphamide in the 3 months before or previsouly treated with Natalizumab. The gene expression profiling was assessed using the Illumina® HumanHT-12v4.0 Expression BeadChips. Differentially expressed genes (DEGs) were identified using Limma software, including white blood cell and lymphocyte counts as covariates. As additional tool, we used the CellMix R package to deconvolute the expression data according to cell types. We then analyzed the obtained gene lists in terms of Gene Ontology enrichment.
Results: we enrolled 24 RRMS patients (F:M ratio 2.5), with a mean age at BL of 39.9±8.4 years, median EDSS 2.0 (range 1.0-4.5) and mean disease duration at BL of 10±7 years. At the primary analysis, we found 478 DEGs with FDR< 15%; the top ten were all downregulated, with the CTLA4 being the more significantly modulated (log Fold-Change -2.399, p-value=0.00026). We than moved on to the deconvoluted data and selected 316 DEGs with a log Fold Change >1 and P-value< 0.01; out of them, 135 were up-regulated and 181 were down-regulated genes. When comparing DEGs list using the two tools, we observed a significant overlap for 51 down-regulated genes. Moreover, there was a substantial overlap between the pathways selected from both experimental and deconvoluted data, confirming an enrichment in genes involved in lymphocyte activation (p-value=5.4E-10), lymphocyte differentiation (p-value=3.2E-05) and regulation of immune system process (p-value=4.1E-08).
Conclusions: FTY treatment appears to induce a significant downregulation of genes involved in lymphocyte activation and immune response. These data could be driven by FTY mechanism of action, although we took into account the effect on lymphocyte count at the analytical level. Additional experiments on sorted cells are ongoing, in order to better assess FTY effect at the cellular level.
Disclosure:
F. Esposito received honoraria from TEVA and Merck.
L. Moiola received honoraria for speaking at meetings or for attending to advisory board from Sanofi-Genzyme, Biogen-Idec, Novartis and TEVA.
B. Colombo received travel grant from Biogen-Idec, Merck, Bayer, Genzyme.
V. Martinelli has received honoraria for consulting and speaking activities from Biogen-Idec, Merck, Bayer, TEVA, Novartis and Genzyme.
G. Comi has received compensation for consulting services with the following companies: Novartis, Teva, Sanofi, Genzyme, Merck, Biogen, Excemed, Roche, Almirall, Chugai, Receptos, Forward Pharma and compensation for speaking activities from Novartis, Teva, Sanofi, Genzyme, Merk, Biogen, Excemed, Roche.
F. Martinelli Boneschi has received compensation for activities with Teva Neuroscienze as speaker and/or advisor.
E. Mascia: nothing to disclose.
P. Provero: nothing to disclose.
L. Ferrè: nothing to disclose.
F. Clarelli: nothing to disclose.
G. Sferruzza: nothing to disclose.
C. Guaschino: nothing to disclose.
M. Radaelli: nothing to disclose.
This study is supported by the “Fondazione Italiana Sclerosi Multipla”, project 2013/R/13
Abstract: P953
Type: Poster
Abstract Category: Pathology and pathogenesis of MS - Genetics /Epigenetics and Pharmacogenetics
Background: fingolimod (FTY) is an oral treatment recently approved for relapsing-remitting (RR) multiple sclerosis (MS). No gene expression experiments have been performed at whole genome level to assess the transcriptional changes induced by the treatment.
Aim: to investigate the molecular mechanisms underlying FTY action, by looking at transcriptional alterations induced by the treatment.
Methods: whole blood samples were collected at baseline (BL) and after 6 months of FTY treatment in RRMS patients. We excluded subjects with a clinical relapse or steroid treatment in the month before FTY, treated with interferon or cyclophosphamide in the 3 months before or previsouly treated with Natalizumab. The gene expression profiling was assessed using the Illumina® HumanHT-12v4.0 Expression BeadChips. Differentially expressed genes (DEGs) were identified using Limma software, including white blood cell and lymphocyte counts as covariates. As additional tool, we used the CellMix R package to deconvolute the expression data according to cell types. We then analyzed the obtained gene lists in terms of Gene Ontology enrichment.
Results: we enrolled 24 RRMS patients (F:M ratio 2.5), with a mean age at BL of 39.9±8.4 years, median EDSS 2.0 (range 1.0-4.5) and mean disease duration at BL of 10±7 years. At the primary analysis, we found 478 DEGs with FDR< 15%; the top ten were all downregulated, with the CTLA4 being the more significantly modulated (log Fold-Change -2.399, p-value=0.00026). We than moved on to the deconvoluted data and selected 316 DEGs with a log Fold Change >1 and P-value< 0.01; out of them, 135 were up-regulated and 181 were down-regulated genes. When comparing DEGs list using the two tools, we observed a significant overlap for 51 down-regulated genes. Moreover, there was a substantial overlap between the pathways selected from both experimental and deconvoluted data, confirming an enrichment in genes involved in lymphocyte activation (p-value=5.4E-10), lymphocyte differentiation (p-value=3.2E-05) and regulation of immune system process (p-value=4.1E-08).
Conclusions: FTY treatment appears to induce a significant downregulation of genes involved in lymphocyte activation and immune response. These data could be driven by FTY mechanism of action, although we took into account the effect on lymphocyte count at the analytical level. Additional experiments on sorted cells are ongoing, in order to better assess FTY effect at the cellular level.
Disclosure:
F. Esposito received honoraria from TEVA and Merck.
L. Moiola received honoraria for speaking at meetings or for attending to advisory board from Sanofi-Genzyme, Biogen-Idec, Novartis and TEVA.
B. Colombo received travel grant from Biogen-Idec, Merck, Bayer, Genzyme.
V. Martinelli has received honoraria for consulting and speaking activities from Biogen-Idec, Merck, Bayer, TEVA, Novartis and Genzyme.
G. Comi has received compensation for consulting services with the following companies: Novartis, Teva, Sanofi, Genzyme, Merck, Biogen, Excemed, Roche, Almirall, Chugai, Receptos, Forward Pharma and compensation for speaking activities from Novartis, Teva, Sanofi, Genzyme, Merk, Biogen, Excemed, Roche.
F. Martinelli Boneschi has received compensation for activities with Teva Neuroscienze as speaker and/or advisor.
E. Mascia: nothing to disclose.
P. Provero: nothing to disclose.
L. Ferrè: nothing to disclose.
F. Clarelli: nothing to disclose.
G. Sferruzza: nothing to disclose.
C. Guaschino: nothing to disclose.
M. Radaelli: nothing to disclose.
This study is supported by the “Fondazione Italiana Sclerosi Multipla”, project 2013/R/13