Title
Machine Learning Identifies Specific Habitats Associated With Genetic Connectivity In Hyla Squirella
Keywords
Alpha-Glucosidase; Antibody; Immune response; Pompe; T cell
Abstract
Pompe disease is a neuromuscular disease caused by an inherited deficiency of the lysosomal enzyme acid α-glucosidase (GAA). The resulting accumulation of glycogen causes muscle weakness with the severe form of the disease resulting in death by cardiorespiratory failure in the first year of life. The only available treatment, enzyme replacement therapy (ERT) with recombinant GAA (rhGAA), is severely hampered by antibody responses that reduce efficacy and cause immunotoxicities. Currently, Pompe mice represent the only pre-clinical model for development of new treatments and for immunological studies. While antibody formation following ERT in this model has been described, the underlying T cell response has not been studied. In order to define the T helper response to rhGAA in Pompe mice, immunodominant CD4 + T cell epitopes were mapped in GAA -/- 129SVE mice using ELISpot. Additionally, cytokine responses and antibody formation against rhGAA during ERT were measured. Among the three CD4 + T cell epitopes identified, only epitope IFLGPEPKSVVQ, predicted to be the strongest MHC II binder, consistently contributed to IL-4 production. Frequencies of IL-4 producing T cells were considerably higher than those of IL-17 or IFN-γ producing cells, suggesting a predominantly Th2 cell mediated response. This is further supported by IgG1 being the prevalent antibody subclass against rhGAA during ERT and consistent with prior reports on IgE formation and anaphylaxis in this model. These results will facilitate mechanistic studies of the immune response to rhGAA in Pompe mice during development of new therapies and tolerance protocols. © 2012 Elsevier Inc.
Publication Date
6-1-2012
Publication Title
Journal of Evolutionary Biology
Volume
25
Issue
2
Number of Pages
1039-1052
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1111/j.1420-9101.2012.02497.x
Copyright Status
Unknown
Socpus ID
84861193656 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84861193656
STARS Citation
Hether, T. D. and Hoffman, E. A., "Machine Learning Identifies Specific Habitats Associated With Genetic Connectivity In Hyla Squirella" (2012). Scopus Export 2010-2014. 5384.
https://stars.library.ucf.edu/scopus2010/5384