RESEARCH - Autoantibody profiling in MS reveals novel antigenic candidates

[Guest guest]

J Immunol. 2008 Mar 15;180(6):3957-63.

Autoantibody profiling in multiple sclerosis reveals novel antigenic candidates.

Somers V, Govarts C, Somers K, Hupperts R, Medaer R, Stinissen P.

Hasselt University, Biomedical Research Institute and Transnationale

Universiteit Limburg, School of Life Sciences, Diepenbeek, Belgium.

An important contribution of B cells and autoantibodies has been

demonstrated in the pathogenesis of multiple sclerosis (MS), leading

to interest in the use of such autoantibodies as diagnostic or

prognostic biomarkers. The objective of this study was to identify

novel Ab biomarkers for MS using " serological Ag selection " . Using a

phage display library derived from MS brain plaques, we applied

serological Ag selection to identify antigenic targets specifically

interacting with Abs present in the cerebrospinal fluid (CSF) of 10

relapsing-remitting MS patients. These antigenic targets were further

evaluated on a large panel of CSF from 63 other MS patients, 30

patients with other inflammatory disorders, and 64 patients with

noninflammatory neurological disorders. A panel of eight antigenic

targets was identified that showed a 86% specificity and 45%

sensitivity in discriminating MS patients and controls. Four of the

antigenic targets showed exclusive reactivity (100% specificity; 23%

sensitivity) in the MS group as compared with the control group.

Detailed bio-informatic analyses revealed a novel Ag, SPAG16. Among

the novel phage peptides identified, novel epitopes were generated

from untranslated sequences and out-of-frame sequences. Of 10

relapsing-remitting patients used for serological Ag selection, Ab

reactivity toward one of the eight antigenic targets was also

demonstrated in serum of 38% CSF-positive patients. Autoantibody

profiles against epitopes derived from MS brain tissue could serve as

diagnostic markers or form the basis for the identification of a

subgroup of MS patients.

PMID: 18322204

http://www.ncbi.nlm.nih.gov/pubmed/18322204

--

Not an MD