Lineage tree analysis of immunoglobulin variable-region gene mutations in autoimmune diseases: chronic activation, normal selection.
Autoimmune diseases show high diversity in the affected organs, clinical manifestations and disease dynamics. Yet they all share common features, such as the ectopic germinal centers found in many affected tissues. Lineage trees depict the diversification, via somatic hypermutation (SHM), of immunoglobulin variable-region (IGV) genes. We previously developed an algorithm for quantifying the graphical properties of IGV gene lineage trees, allowing evaluation of the dynamical interplay between SHM and antigen-driven selection in different lymphoid tissues, species, and disease situations. Here, we apply this method to ectopic GC B cell clones from patients with Myasthenia Gravis, Rheumatoid Arthritis, and Sjögren's Syndrome, using data scaling to minimize the effects of the large variability due to methodological differences between groups. Autoimmune trees were found to be significantly larger relative to normal controls. In contrast, comparison of the measurements for tree branching indicated that similar selection pressure operates on autoimmune and normal control clones.
Steiman-Shimony
Avital
A
The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Building 212, Box 61, Ramat-Gan 52900, Israel.
Edelman
Hanna
H
Hutzler
Anat
A
Barak
Michal
M
Zuckerman
Neta S
NS
Shahaf
Gitit
G
Dunn-Walters
Deborah
D
Stott
David I
DI
Abraham
Roshini S
RS
Mehr
Ramit
R
D000465:Algorithms; D001327:Autoimmune Diseases / Q000235:genetics* / Q000276:immunology*; D001402:B-Lymphocytes / Q000276:immunology; D016000:Cluster Analysis; D014644:Genetic Variation; D018858:Germinal Center / Q000276:immunology*; D006801:Humans; D007135:Immunoglobulin Variable Region / Q000235:genetics* / Q000276:immunology; D009154:Mutation; D027041:Somatic Hypermutation, Immunoglobulin / Q000276:immunology; D018709:Statistics, Nonparametric
D007135:Immunoglobulin Variable Region