SUSCEPTIBILITY GENES AND BIOMARKERS FOR RHEUMATOID ARTHRITIS (NARAC 2)

点击翻译按钮获取中文摘要

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Rheumatoid arthritis (RA) is a genetically complex and clinically heterogeneous chronic disease of unknown etiology that affects 0.5-1% of the population. The North American RA Consortium (NARAC) has previously identified several genomic regions containing susceptibility genes, and this proposal represents the continuation and expansion of that work, in addition to the identification of new biomarkers to predict outcome and clinical response. On specific aim 1, the NARAC will identify 1,000 "trio" families, where the proband has seropositive and erosive RA and the parents not affected. Trios will be recruited from several sites around the country and will be critical for the fine mapping of the regions containing susceptibility genes. On specific aim 2, high-density single nucleotide polymorphism (SNP) mapping will be done using terminal deoxynucleotidyl transferase (TDT) in ten candidate chromosomal regions of interest recently identified in the NARAC linkage studies. After narrowing down the regions of interest, candidate genes will be re-sequenced. Specific aim 3 will identify biomarkers predictive for response to therapy with antinecrosis factor agents in a large cohort of RA patients. Patients will be followed for one year and several parameters will be tested, including genetic markers, the pattern of gene expression using Affymetric microarrays in peripheral blood leucocytes (PBL), cell surface markers in PBL, and serum/plasma levels of several proteins. These parameters will be used to compare responders and non-responders in order to identify the best predictors.