Zinc-ion binding and cytokine activity regulation pathways predicts outcome in relapsing–remitting multiple sclerosis
http://www.ncbi.nlm.nih.gov/pmc/article ... 9-0235.pdf
Multiple sclerosis (MS) is a demyelinating disease characterized by an unpredictable clinical course with intermittent relapses that lead over time to significant neurological disability. Clinical and radiological variables are limited in the ability to predict disease course. Peripheral blood genome scale analyses were used to characterize MS patients with different disease types, but not for prediction of outcome. Using complementary-DNA microarrays we studied peripheral-blood gene expression patterns in 53 relapsing–remitting MS patients. Patients were classified into good, intermediate and poor clinical outcome established after 2-year follow-up. A training set of 26 samples was used to identify clinical outcome differentiating gene-expression signature. Supervised learning and feature selection algorithms were applied to identify a predictive signature that was validated in an independent group of 27 patients. Key genes within the predictive signature were confirmed by quantitative reverse transcription–polymerase chain reaction in an additional 10 patients. The analysis identified 431 differentiating genes between patients with good and poor clinical outcome (change in neurological disability by the expanded disability status scale was-0•33±0•24 and 1•6±0•35,P=0•0002, total number of relapses were 0 and 1•80±0•35,P=0•00009, respectively). An optimal set of 29 genes was depicted as a clinical outcome predictive gene expression signature and classified appropriately 88•9% of patients. This predictive signature was enriched by genes related biologically to zinc-ion binding and cytokine activity regulation pathways involved in inflammation and apoptosis. Our findings provide a basis for monitoring patients by prediction of disease outcome and can be incorporated into clinical decision-making in relapsing–remitting MS.
The clinical outcome predictive gene expression signature was enriched by zinc-ion binding and cytokine activity pathways. Activation of mononuclear cells in MS involves proinflammatory cytokines such as IFN-g and tumour necrosis factor (TNF)-a that promote disease activity. Conversely, anti-inflammatory cytokines such as TGF-b, interleukin (IL)-4 and IL-10 decrease proinflammatory activation. The molecular transcripts we identified regulate the balance of these opposing effectors and are thus associated with clinical outcome prediction. The zinc-ion binding genes in the predictive signature include KLF4, known to be activated by (signal transducers and activators of transcription (STAT1), which is activated by S100B , and increases IFN-g expression , a well-known proinflammatory cytokine involved in MS disease activity.
KLF4 is markedly induced in response to IFN-g, lipolpolysaccharide (LPS) or TNF-a. Over-expression of KLF4 is associated with macrophage activation marker inducible nitric-oxide synthase and with TGF-b1 inhibition. KLF4 interacts with the NF-kB family member p65 (RelA), and has an important role as a regulator of key signalling pathways that control macrophage activation .
The S100B gene protein is known to be involved in intracellular and extracellular regulatory events within the central nervous system. S100B was found to be elevated in acute brain lesions of RRMS patients , and its plasma levels were reported elevated in RRMS patients responding to IFN-b treatment . This is in accordance with our findings, demonstrating decreased S100B expression in patients with poor outcome. Additionally, a novel association of the zinc-ion binding gene CA11 was identified in the network reconstruction.
The balance between T helper 1 (Th1) and Th2 immune responses plays an important role in the pathogenesis of MS. In addition to the recognition of encephalitogenic epitopes, the ability to produce Th1 cytokines is an important functional requirement by which myelin-reactive T cells mediate the disease, while Th2 cells secreting IL-10 suppress the ongoing inflammation. The cytokine activity-enriched gene family identified in the prediction signature included CCL17, MUC4, PTN and VEGFB. CCL17 displays chemotactic activity for Th2 lymphocytes , and its activity is well known to be enhanced by the Th2-related cytokines IL-4 and IL-13, leading to inhibition of inflammation. MUC4 expression is dependent upon IL-4 and IL-13 levels [31–33]. PTN is involved in regulation of cell-mediated immunity , and negatively regulates VEGF activity . These findings demonstrate that the poor clinical outcome predictive signature in RRMS is affected mainly by decreased Th2 cytokine activity and aberrant regulation of inflammation.
In conclusion, the predictive outcome gene expression signature is sensitive to RRMS evolution and as such provides a new perspective on disease progression. Moreover, our findings suggest that the co-stimulatory regulatory pathways of zinc-ion binding and cytokine activity-related genes within the predictive signature may serve as new targets for therapeutic interventions. Finally, the predictive signature may enable planning of tailored therapeutic strategies, and allow delineation of patients at high risk who may benefit from early therapy.