Immunological patterns identifying disease course and evolution in multiple sclerosis patients

Roberto Furlan; Marco Rovaris; Filippo Martinelli Boneschi; Mohsen Khademi; Alessandra Bergami; Maira Gironi; Michela Deleidi; Federica Agosta; Diego Franciotta; Elio Scarpini; Antonio Uccelli; Mauro Zaffaroni; Asli Kurne; Giancarlo Comi; Tomas Olsson; Massimo Filippi; Gianvito Martino

doi:10.1016/j.jneuroim.2005.04.012

Immunological patterns identifying disease course and evolution in multiple sclerosis patients

J Neuroimmunol. 2005 Aug;165(1-2):192-200. doi: 10.1016/j.jneuroim.2005.04.012.

Authors

Roberto Furlan¹, Marco Rovaris, Filippo Martinelli Boneschi, Mohsen Khademi, Alessandra Bergami, Maira Gironi, Michela Deleidi, Federica Agosta, Diego Franciotta, Elio Scarpini, Antonio Uccelli, Mauro Zaffaroni, Asli Kurne, Giancarlo Comi, Tomas Olsson, Massimo Filippi, Gianvito Martino

Affiliation

¹ Neuroimmunology Unit, San Raffaele, Scientific Institute, Via Olgettina 58, 20132 Milan, Italy. [email protected]

PMID: 15949850
DOI: 10.1016/j.jneuroim.2005.04.012

Abstract

Reliable, and easy to measure, immunological markers able to denote disease characteristics in multiple sclerosis (MS) patients are still lacking. We applied a multivariate statistical analysis on results obtained by measuring-by real-time RT-PCR-mRNA levels of 25 immunological relevant molecules in PBMCs from 198 MS patients. The combined measurement of mRNA levels of IL-1beta, TNF-alpha, TGF-beta, CCL20 and CCR3 was able to distinguish MS patients from healthy individuals. CXCR5, CCL5, and CCR3 combined mRNA levels identify primary progressive MS patients while TNF-alpha, IL-10, CXCL10 and CCR3 differentiate relapsing MS patients. Our results indicate that multi-parametric analysis of mRNA levels of immunological relevant molecules in PBMCs may represent a successful strategy for the identification of putative peripheral markers of disease state and disease activity in MS patients.

Publication types

Comparative Study
Research Support, Non-U.S. Gov't

MeSH terms

Adult
Biomarkers
Chemokine CCL20
Chemokine CCL5
Chemokines, CC / genetics
Chemokines, CC / metabolism
Disease Progression
Female
Humans
Interleukin-1 / biosynthesis
Linear Models
Macrophage Inflammatory Proteins / genetics
Macrophage Inflammatory Proteins / metabolism
Magnetic Resonance Imaging / statistics & numerical data
Male
Middle Aged
Models, Immunological
Multiple Sclerosis / diagnosis*
Multiple Sclerosis / immunology*
Multiple Sclerosis, Chronic Progressive / diagnosis
Multiple Sclerosis, Chronic Progressive / immunology
Multivariate Analysis
RNA, Messenger / metabolism
Receptors, CCR3
Receptors, CXCR5
Receptors, Chemokine / genetics
Receptors, Chemokine / metabolism
Receptors, Cytokine / genetics
Receptors, Cytokine / metabolism
Transforming Growth Factor beta / genetics
Transforming Growth Factor beta / metabolism
Tumor Necrosis Factor-alpha / genetics
Tumor Necrosis Factor-alpha / metabolism

Substances

Biomarkers
CCL20 protein, human
CCL5 protein, human
CCR3 protein, human
CXCR5 protein, human
Chemokine CCL20
Chemokine CCL5
Chemokines, CC
Interleukin-1
Macrophage Inflammatory Proteins
RNA, Messenger
Receptors, CCR3
Receptors, CXCR5
Receptors, Chemokine
Receptors, Cytokine
Transforming Growth Factor beta
Tumor Necrosis Factor-alpha