Classification of individuals based on ex-vivo glatiramer acetate-induced interferon-γ and interleukin-4 response.

BACKGROUND: Glatiramer acetate (GA) in multiple sclerosis acts through the induction of GA-specific T-helper 2 cells. Nevertheless, the phenomenon is not universal in patients, explaining individual differences in clinical response. OBJECTIVE: The objective of this article was to categorize GA-treated patients. METHOD: An enhanced quantitative PCR assay was used for measuring ex-vivo GA-induced IFNγ and IL4 mRNA responses in mononuclear cells from 23 healthy donors, 27 untreated patients, 33 short-term (≤6 months) and 77 long-term (>6 months) GA-treated patients. Thresholds for IFNγ and IL4 transcriptional response were calculated by ROC analysis and long-term treated patients were compared in terms of prognostic stratification. RESULTS: Thresholds for IFNγ and IL4 transcriptional response were calculated at 5.36 and 1.41 relative expression (RE). Finally, 67% of long-term treated patients scored above both response thresholds. These patients had a higher proportion of relapse-free subjects (74% vs 40% when compare to patients who scored below both thresholds) and a significantly better relapse-free survival rate (p=0.006; CI 0.29-0.75). The negative predictive value to predict adverse clinical outcome was 79% (CI 0.63-0.90), meaning that by a positive response, there is a 79% chance that the patient will not experience a negative outcome at 3 years. CONCLUSIONS: Our enhanced quantitative PCR assay produced clinically significant results for GA-treated patients. As such, if patients have a positive response, it means they have less chance of a relapse, while patients with a negative response have a greater probability of a worse outcome.

A20 in Multiple Sclerosis and Parkinson's Disease: Clue to a Common Dysregulation of Anti-Inflammatory Pathways?

Chronic inflammation significantly contributes to the pathogenesis of several neurodegenerative disorders. In physiological conditions, a chronic inflammatory state is prevented through the termination of the acute inflammatory response once the triggering insult is eliminated. Several mechanisms regulate the resolution of inflammation. Among these, a potent inhibitor of the pro-inflammatory NF-kB signaling known as A20 has emerged as a key player. Recent studies have shown reduced blood levels of A20 in the patients of diverse chronic inflammatory diseases. Similar results have also been demonstrated in patients of multiple sclerosis (MS), a neurodegenerative disease characterized by persisting inflammation. In the present study, we investigate whether other similar neurodegenerative disorders such as Parkinson's disease (PD), Alzheimer's disease (AD), and amyotrophic lateral sclerosis (ALS) also demonstrate deregulated levels of A20 expression as compared to healthy controls (HC) and treatment-naive MS patients. Our results confirm previous data that the A20 expression is reduced in whole blood of MS patients as compared to HC. Additionally, we demonstrate that significantly diminished A20 expression is also evident in PD patients. The dysregulation of the A20 pathway could then contribute to the persistence of inflammation in these disorders. It would thus be interesting to investigate further whether such commonly deregulated pathways between different inflammatory diseases could represent novel targets for therapy.

A gene expression study denies the ability of 25 candidate biomarkers to predict the interferon-beta treatment response in multiple sclerosis patients.

We studied the baseline expression level of 25 interferon-regulated genes (MxA, GPR3, IL17RC, ISG15, TRAIL, OASL, IFIT1, IFIT2, RSAD2, OAS3, IFI44L, TRIM22, IL10, CXCL10, STAT1, OAS1, OAS2, IFNAR1, IFNAR2, IFNß, ISG20, IFI6, PKR, IRF7, USP18), recurrently proposed in the literature as predictive biomarkers of interferon-beta treatment response, in whole blood of 10 "responders" and 10 "non-responders" multiple sclerosis relapsing-remitting patients, retrospectively selected on the basis of stringent clinical criteria after a five years follow-up. However, we cannot confirm the predictive value of these candidate biomarkers.