BAFF

B-cell activating factor polymorphism, auto antibody formation and disease manifestations in patients with systemic inflammatory autoimmune disease.

Introduction
The presence of non-organ specific autoantibodies is a hallmark of the systemic autoimmune inflammatory diseases such as Systemic Lupus Erythematosus (SLE) , Sjøgren’s syndrome (SS) and Rheumatoid Arthritis (RA). Such autoantibodies (fe anti- dsDNA antibodies, anti-SSA or anti-IgG antibodies) are often considered to be specific biomarkers for the various syndromes as reflected by their inclusion in the classification schemes for these diseases(1) (2) (3) . Contrary to recommendations these autoantibodies and classification schemes are often used for diagnostic purposes in daily practice (nosse/Rekv), which cannot do justice to the intrinsic diversity of the process of autoantibody formation (..). More importantly, subsets of such autoantibodies may contribute to the pathogenesis of various disease manifestations, through either direct in-situ binding of tissue antigens(s) or indirectly through deposition of circulating immunecomplexes (4;5). The potential of certain anti-dsDNA antibodies to induce proliferative lupus nephritis and the congenital heart block induced by anti-SSA antibodies exemplify this line of thought (Berden, NY data). During the last decade it has also become abundantly clear that many subsets of autoantibodies in these patient categories are not involved in disease manifestations (nossent/rekv), which results in a rather limited diagnostic and prognostic value of currently available autoantibody assays.
Autoantibody production is the final product of an intricate interplay between immune regulatory mechanisms that involve crosstalk between antigen presenting cells (APC), B-lymphocytes and regulatory T-lymphocytes and result in the differentiation of B-lymphocytes into dedicated plasmacell clones, which function as mere autoantibody producing facilities. The mechanisms, which define the production of pathogenic autoantibodies, are at present unknown, but the class switching and somatic mutations found in nephritogenic anti-dsDNA antibodies in SLE indicate a, antigen-driven, T-cell dependent process , where apoptotic nuclear material may provide the antigenic stimulus (6;7). These autoantibodies are produced by plasmacells, which represent the final and dedicated stage of B-cell maturation. B cells develop from the hematopoietic stem cell lineage in the bone marrow but undergo maturation only after migrating to the periphery. While the B-cell receptor (BCR) plays an essential role in this process, recent findings also suggest a central role for B-lymphocyte activating factor (BAFF), which is a recently described member of the tumor necrosis factor (TNF) ligand superfamily (8). BAFF (also known as BLyS, TALL-1, THANK, zTNF4 or TNFSF13B) is a transmembrane protein, consisting of 285 aminoacids, which can be cleaved from the cell surface by a furin proteinase, which results in the release of a biologically active soluble 17KD-protein (9;10). BAFF is expressed on cells of myeloid origin, including macrophages and dendritic cells and serves as a vital B-cell survival factor through binding to one of three BAFF receptors (BCMA, TACI, BAFFR)(9;11). Signaling through one of the BAFF receptors, BAFF receptor 3 (BR3), controls B-cell numbers in two ways: by varying the proportion of cells that complete transitional B-cell development and by serving as the primary determinant of mature B-cell longevity. The discovery that BCR signaling is selectively coupled to BR3 expression in a developmentally regulated fashion links BCR- and BAFF -mediated events, suggesting that specificity-based selection and survival may be mechanistically similar processes (12). BAFF enhances both T-cell dependent and T-cell independent antibody responses (13) and also elicits Ig class switching and plasmacytoid differentiation that is CD40-independent, thus providing a critical link between the innate and adaptive immune responses(14). Mice genetically deficient in BAFF have few mature B-cells and circulating immunoglobulins(15;16), while BAFF overexpression in transgenic mice leads to B-cell expansion and polyclonal hypergammaglobulinemia (16-18). Such hyper-gammaglobulinemia is a typical feature of many systemic inflammatory autoimmune diseases, and may be explained by the increased serum levels of BAFF described in human SLE, SS and RA (19-24). BAFF transgenic mice, also develop a secondary pathology reminiscent of SS, manifested by severe sialadenitis, decreased saliva production, and destruction of submaxillary glands. Thus, excess BAFF may provide unwarranted survival signals to autoreactive B cells central to SS pathogenesis and autantibody production (19;25)
There are few data on the assumed relation between BAFF expression, autoantibody profiles and disease manifestations in humans with systemic autoimmune inflammatory diseases. In a longitudinal study of SLE patients serum BAFF levels correlated with anti-dsDNA antibody levels, although there was no clear association with overall disease activity (20). In patients with primary SS, serum BAFF levels were higher in patients with anti-SSA antibodies and Rheumatoid Factor, and a dramatic upregulation of BAFF expression was seen in inflamed salivary glands indicating an upregulation of B cell subsets by BAFF (19;26). The gene coding for BAFF (located at 13q32) has been characterized and genome-wide screening has suggested that a linkage may exist between BAFF and autoimmune diseases (moser, proc nat acad sc , 1998). In addition, various BAFF polymorphism have been described that may be involved in the susceptibility to some of the clinical phenotype in the autoimmune diseases, especially mediated through autoantibody selection. Also, establishing the role for BAFF expression in the development of specific autoantibody subsets might have a future therapeutic potential as chimeric antibodies against BAFF have become available and have been introduced in phase I trials (Furie AR 2003 abstr). Reducing BAFF levels and/or activity might thus reduce BAFF mediated autoantibody production and induction of inflammation. The aim of this study is to analyze the frequency and type of BAFF polymorphisms and serum BAFF levels in relation to autoantibody profiles and disease manifestations in patients with pSS and RA.


Patients and Methods
Patients and controls
Patients included in disease groups included will fulfill the revised European criteria for classification of SS (2) and the ACR criteria for classification of RA (3) , while a control group will consist of healthy volunteers.

Clinical data
Demographic data and relevant disease manifestations will be collected and stored in a computerised database.

Autoantibodies
Autoantibody profiles will be determined in sera that are routinely collected at patient visits. Ro/La antibody screening will be performed by counterimmunoelectrophoresis (CIE) and enzyme linked immunosorbent assay (ELISA). Rheumatoid Factor will be determined by laser nephelometry/ELISA.

Serum BAFF-levels
Serum BAFF levels will be determined by enzyme linked immunosorbent assay (ELISA) as described (20).

Genomic DNA
Genomic DNA from patients and controls will be isolated from peripheral blood leukocytes using the QIAamp blood Kit (ref)

BAFF genotyping
The genomic configuration of human BAFF gene is published in the open domain (www.ncbi.nlm.nih.gov/entrez/gene), variation screening and genotyping will be performed using the polymerase chain reaction and sequence specific priming (PCR-SSP).

Data analysis
BAFF polymorphism frequencies will be determined for both disease categories (SS and RA) and associations to demographic variables and specific disease manifestations (exocrine versus non-exocrine manifestations, Ro/La presence in SS) (erosive versus nonerosive, RF positive in RA) will be analyzed by standard statistical techniques (Chi-square for n-tables).
Correlations between BAFF serum levels, BAFF polymorphisms and autoantibody profiles and levels will be analyzed by nonparametric (Mann-Whitney U/Spearman’s rank correlation) test for numeric data.

Reference List
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