Sieving treatment biomarkers from blood gene-expression profiles: a pharmacogenomic update on two types of multiple sclerosis therapy.

Interferon-ß (IFN-ß) and glatiramer acetate are routinely used to inhibit disease activity in multiple sclerosis, but their mechanisms of action are incompletely understood. Individual treatment responses vary and candidate molecular markers that predict them have yet to be established. Why some patients respond poorly to a certain treatment while others respond well is addressed by the pharmacogenomic approach, which postulates that the molecular response to treatment correlates with the clinical effects, and thus seeks biological markers to estimate prognosis, guide therapy, comprehend the drugs' mechanisms of action and offer insights into disease pathogenesis. A poor clinical response can be owing to genetic variants in drug receptors or signaling components, or the appearance of neutralizing antibodies that interfere with the drug's binding efficacy. Independently, such mechanisms could lead to inadequate, that is to say unchanged, molecular responses, or exceedingly increased or decreased changes. By means of DNA microarray studies, various research groups endeavour to establish a clinically relevant relationship between the biological response to these drugs and treatment effects. Molecular profiles obtained in this way differ in the pattern and number of modulated genes, suggesting the existence of an individual 'drug-response fingerprint'. To further unravel the underlying regulatory interaction structure of the genes responsive to these immunotherapies represents a daunting but inevitable task. In this article, we focus on longitudinal ex vivo transcriptomic studies in multiple sclerosis and its therapy. We will discuss recurrently reported biomarker candidates, emphasizing those of immunologically meaning, and review studies with network module outputs.

Tyrosine kinase 2 variant influences T lymphocyte polarization and multiple sclerosis susceptibility.

The tyrosine kinase 2 variant rs34536443 has been established as a genetic risk factor for multiple sclerosis in a variety of populations. However, the functional effect of this variant on disease pathogenesis remains unclear. This study replicated the genetic association of tyrosine kinase 2 with multiple sclerosis in a cohort of 1366 French patients and 1802 controls. Furthermore, we assessed the functional consequences of this polymorphism on human T lymphocytes by comparing the reactivity and cytokine profile of T lymphocytes isolated from individuals expressing the protective TYK2(GC) genotype with the disease-associated TYK2(GG) genotype. Our results demonstrate that the protective C allele infers decreased tyrosine kinase 2 activity, and this reduction of activity is associated with a shift in the cytokine profile favouring the secretion of Th2 cytokines. These findings suggest that the rs34536443 variant effect on multiple sclerosis susceptibility might be mediated by deviating T lymphocyte differentiation toward a Th2 phenotype. This impact of tyrosine kinase 2 on effector differentiation is likely to be of wider importance because other autoimmune diseases also have been associated with polymorphisms within tyrosine kinase 2. The modulation of tyrosine kinase 2 activity might therefore represent a new therapeutic approach for the treatment of autoimmune diseases.

Long-term genome-wide blood RNA expression profiles yield novel molecular response candidates for IFN-beta-1b treatment in relapsing remitting MS.

AIMS: In multiple sclerosis patients, treatment with recombinant IFN-beta (rIFN-beta) is partially efficient in reducing clinical exacerbations. However, its molecular mechanism of action is still under scrutiny. MATERIALS & METHODS: We used DNA microarrays (Affymetrix, CA, USA) and peripheral mononuclear blood cells from 25 relapsing remitting multiple sclerosis patients to analyze the longitudinal transcriptional profile within 2 years of rIFN-beta administration. Sets of differentially expressed genes were attained by applying a combination of independent criteria, thereby providing efficient data curation and gene filtering that accounted for technical and biological noise. Gene ontology term-association analysis and scientific literature text mining were used to explore evidence of gene interaction. RESULTS: Post-therapy initiation, we identified 42 (day 2), 175 (month 1), 103 (month 12) and 108 (month 24) differentially expressed genes. Increased expression of established IFN-beta marker genes, as well as differential expression of circulating IFN-beta-responsive candidate genes, were observed. MS4A1 (CD20), a known target of B-cell depletion therapy, was significantly downregulated after one month. CMPK2, FCER1A, and FFAR2 appeared as hitherto unrecognized multiple sclerosis treatment-related differentially expressed genes that were consistently modulated over time. Overall, 84 interactions between 54 genes were attained, of which two major gene networks were identified at an earlier stage of therapy: the first (n = 15 genes) consisted of mostly known IFN-beta-activated genes, whereas the second (n = 12) mainly contained downregulated genes that to date have not been associated with IFN-beta effects in multiple sclerosis array research. CONCLUSION: We achieved both a broadening of the knowledge of IFN-beta mechanism-of-action-related constituents and the identification of time-dependent interactions between IFN-beta regulated genes.

Monitoring of multiple sclerosis immunotherapy: from single candidates to biomarker networks.

Applying microarray technology to identify new diagnostic and prognostic markers in peripheral blood cells (PBC) after therapeutic intervention opens great perspectives regarding patient subclassification. Three recombinant products of the pleiotropic agent interferon beta (rIFN-beta) are available for disease modifying therapy of relapsing remitting multiple sclerosis (RRMS), a complex inflammatory autoimmune disease that targets the central nervous system. They differ according to formulation, route of administration and dosage regimens. The currently, only partially understood mechanism of action of injected rIFN-beta into human organisms needs provision with accessory key molecules; in addition, the significance of established clinical IFN-beta response criteria that distinguish responding from non-responding patients remain unclear.With respect to these major questions, we discuss promising candidates on the gene transcription level, attained from scientific MS literature that included a longitudinal aspect. Reviewed studies were in part carried out with distinct gene interrogating platforms (GeneArrays; RT-PCR), settings (in vitro; ex vivo), and study designs (drug formulations and regimen; inclusion criteria and clinical endpoints), hampering meaningful meta-analysis. Nevertheless, PBC from therapy-naïve MS patients, rIFN-beta treated MS patients, and healthy controls served to characterize facets of both the disease and its treatment. Hence, the field of MS transcriptomics in immunomodulatory therapy is (by far) not adequately understood and should be embedded into systems biology disciplines, yielding multi-layer analyses that deliver timely identification of MS subjects who will profit from applied rIFN-beta therapy.