The link between intestinal inflammation and spondyloarthritis (SpA) has long been recognized. Likewise, the role for intestinal microbiota in inflammatory bowel disease (IBD) is well appreciated, and a similar role in SpA is emerging. It is unknown, however, whether the contents of the flora are abnormal in SpA patients (dysbiosis), or whether the immunologic response to an otherwise normal flora mediates intestinal inflammation. Data in both IBD and SpA suggest a role for dysregulated adaptive immunity in the pathogenesis of both diseases, and there is also evidence supporting dysbiosis in the pathogenesis of IBD. Therefore, we predict that SpA patients will have an abnormal adaptive (B and T cell) immune response to a limited set of bacterial antigens and will additionally demonstrate abnormal fecal flora contents. Both of these hypotheses will be tested in this proposal.
In Aim 1, we will identify humoral immunologic targets to enteric antigens using a novel antigen microarray followed by targeted screening of select bacteria.
In Aim 2, we will evaluate for abnormal floral content through 16S ribosomal DNA sequencing followed by metagenome sequencing of the enteric microflora of children and adults with SpA.
In Aim 3, we will perform T cell functional studies and analysis of T cell receptor (TCR) oligoclonality before and after exposure to potential target antigens. All of these aims are inter-connected, as bacterial antigens identified in Aim 2 will be studied in Aims 1 and 3, and B cell targets identified in Aim 1 will also be studied in Aim 3. These studies will help to establish a role for an altered adaptive lymphocyte response to intestinal bacteria in SpA patients (compared to control subjects), as well as explore a potential role for an altered gut microbiota in the pathogenesis of SpA. The outcome of these studies will be the identification of a limited set of bacterial antigens associated with and potentially causative of the disease, as well as identifying a role for the adaptive immune response in SpA. Thus, this research will provide novel insights into the pathogenesis of SpA as well as suggest potential new biomarkers useful for diagnosis and monitoring of the disease, and even targets of therapy as we learn to manipulate the microbiota and/or the adaptive immune response to the microbiota.
This study will integrate cutting-edge technologies of antigen identification with microbiome/metagenome analysis to provide novel information on the microbial contributions to spondyloarthritis. The data will result in new insights into the pathogenesis of SpA, suggest potential new biomarkers for diagnosis and monitoring, and lead to new approaches to therapy by manipulating the microbiota and adaptive immune responses to it.
|Stoll, M L; Kumar, R; Lefkowitz, E J et al. (2016) Fecal metabolomics in pediatric spondyloarthritis implicate decreased metabolic diversity and altered tryptophan metabolism as pathogenic factors. Genes Immun 17:400-405|
|Stoll, Matthew L; Cron, Randy Q (2016) The microbiota in pediatric rheumatic disease: epiphenomenon or therapeutic target? Curr Opin Rheumatol 28:537-43|
|Yang, Celeste; Bartolucci, Alfred A; Cui, Xiangqin (2015) Multigroup Equivalence Analysis for High-Dimensional Expression Data. Cancer Inform 14:253-63|
|Curtis, J R; Yang, S; Chen, L et al. (2015) Determining the Minimally Important Difference in the Clinical Disease Activity Index for Improvement and Worsening in Early Rheumatoid Arthritis Patients. Arthritis Care Res (Hoboken) 67:1345-53|
|Li, Peng; Redden, David T (2015) Small sample performance of bias-corrected sandwich estimators for cluster-randomized trials with binary outcomes. Stat Med 34:281-96|
|Yan, Qi; Weeks, Daniel E; CeledÃ³n, Juan C et al. (2015) Associating Multivariate Quantitative Phenotypes with Genetic Variants in Family Samples with a Novel Kernel Machine Regression Method. Genetics 201:1329-39|
|Li, Peng; Redden, David T (2015) Comparing denominator degrees of freedom approximations for the generalized linear mixed model in analyzing binary outcome in small sample cluster-randomized trials. BMC Med Res Methodol 15:38|
|Liu, Nianjun (2015) QTL mapping - Current status and challenges: Comment on "Mapping complex traits as a dynamic system" by L. Sun and R. Wu. Phys Life Rev 13:194-5|
|Cui, Xiangqin; Yu, Shaohua; Tamhane, Ashutosh et al. (2015) Simple regression for correcting Î”Ct bias in RT-qPCR low-density array data normalization. BMC Genomics 16:82|
|Yan, Qi; Weeks, Daniel E; Tiwari, Hemant K et al. (2015) Rare-Variant Kernel Machine Test for Longitudinal Data from Population and Family Samples. Hum Hered 80:126-38|
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