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Edward K. Wakeland, PhD

Professor

UT Southwestern Medical Center

Immunology

https://profiles.utsouthwestern.edu/profile/36900/edward-wakeland.html

Identifying functional variants that underlie SLE susceptibility

We propose to utilize a targeted resequencing strategy to characterize the precise DNA sequences of all SLE risk loci identified by previous GWAS and the Immunochip Consortium in a cohort of 2500 SLE patients and controls. In preliminary studies, we have produced a panel of genomic sequencing libraries and performed taregeted resequencing on 56 autoimmune risk loci in 1500 genomes. In addition, we have performed genotypic analysis of a cohort of more than 4000 patients and controls using the Immunochip SNP typing panel and identified more than 20 new loci associated with the transition to severe SLE. We are requesting funds to develop a new target enrichment panel and resequence these newly identified common and rare disease risk loci in a panel of 2500 patients and controls. This analysis will be combined with eQTL databases, the ENCODE database, and disease status to identify all of the causative functional variations that are strongly linked with disease-associated tagging SNPs. These proposed studies will be strongly leveraged by our preliminary studies, during which we have produced the genomic libraries for sequencing of more than 1500 well characterized cases and controls. This analysis will also include comparisons of the disease alleles found in ANA negative, ANA positive, incomplete lupus, and clinical SLE cohorts. This will allow an accurate assessment of the impact of rare alleles on disease susceptibility. All of the patients in these cohorts have also been typed with the Immunochip, thus providing an opportunity to significantly extend the fine mapping results for >10,000 genotyped cases and controls from the Immunochip studies. A major product of the proposed research will be the creation of a technical protocol and analytic strategy with which to comprehensively characterize genetic risk for SLE. The results of this analysis will be developed into a web-accessible database and all qualified investigators will be provided access to support the development of hypothesis-driven research into the causes of SLE at the population level by the biomedical research community.

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