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Byun, Jinyoung

https://orcid.org/0000-0001-8579-1435

Mayo Clinic

UNM Comprehensive Cancer Center

Citations 13

Identification of Functional and Expression Polymorphisms Associated With Risk for Antineutrophil Cytoplasmic Autoantibody–Associated Vasculitis
Ji, Xuemei , Ciavatta, Dominic J. , Pinder, Benjamin D. , Zhao, Ai, Zhang, Jinyi , Tadesse, Yohannes, Qian, David C. , Nair, Rajan P. , Tsoi, Lam C. , Carette, Simon , Cuthbertson, David , Davis, John C. , Dellaripa, Paul F., Forbess, Lindsy, Gewurz‐Singer, Ora, Hoffman, Gary S., Koening, Curry L. , Langford, Carol A. , Mahr, Alfred , McAlear, Carol A. , Moreland, Larry W. , Seo, Philip , Sreih, Antoine G. , Clair, E. William St. , Stone, John H., Ytterberg, Steven R. , Elder, James T. , Qu, Jia , Ochi, Toshiki , Hirano, Naoto , Edberg, Jeffrey C., Falk, Ronald J. , Siminovitch, Katherine A. , Merkel, Peter A. , Xie, Gang , Monach, Paul A. , Byun, Jinyoung , Weirauch, Matthew T. , Pagnoux, Christian , Chung, Sharon A. , Dellaripa, Paul F. , Khalidi, Nader , Specks, Ulrich , Spiera, Robert , Amos, Christopher I. , Mahr, Alfred , Moreland, Larry W , Tsoi, Lam C

Arthritis & Rheumatology | December 28, 2016 | Volume: 69 | Issue: 5 | Pages: 1054-1066

10.1002/art.40034 Get It

Objective To identify risk alleles relevant to the causal and biologic mechanisms of antineutrophil cytoplasmic antibody (ANCA)–associated vasculitis (AAV). Methods A genome‐wide association study and subsequent replication study were conducted in a total cohort of 1,986 cases of AAV (patients with granulomatosis with polyangiitis [Wegener's] [GPA] or microscopic polyangiitis [MPA]) and 4,723 healthy controls. Meta‐analysis of these data sets and functional annotation of identified risk loci were performed, and candidate disease variants with unknown functional effects were investigated for their impact on gene expression and/or protein function. Results Among the genome‐wide significant associations identified, the largest effect on risk of AAV came from the single‐nucleotide polymorphism variants rs141530233 and rs1042169 at the HLA–DPB1 locus (odds ratio [OR] 2.99 and OR 2.82, respectively) which, together with a third variant, rs386699872, constitute a triallelic risk haplotype associated with reduced expression of the HLA–DPB1 gene and HLA–DP protein in B cells and monocytes and with increased frequency of complementary proteinase 3 (PR3)–reactive T cells relative to that in carriers of the protective haplotype. Significant associations were also observed at the SERPINA1 and PTPN22 loci, the peak signals arising from functionally relevant missense variants, and at PRTN3 , in which the top‐scoring variant correlated with increased PRTN3 expression in neutrophils. Effects of individual loci on AAV risk differed between patients with GPA and those with MPA or between patients with PR3‐ANCAs and those with myeloperoxidase‐ANCAs, but the collective population attributable fraction for these variants was substantive, at 77%. Conclusion This study reveals the association of susceptibility to GPA and MPA with functional gene variants that explain much of the genetic etiology of AAV, could influence and possibly be predictors of the clinical presentation, and appear to alter immune cell proteins and responses likely to be key factors in the pathogenesis of AAV.
The OncoArray Consortium: A Network for Understanding the Genetic Architecture of Common Cancers
Wang, Zhaoming , Schumacher, Fredrick R. , Gayther, Simon A. , Casey, Graham , Sellers, Thomas A. , Gruber, Stephen B., Dunning, Alison M. , Michailidou, Kyriaki , Fachal, Laura , Doheny, Kimberly F. , Li, Yafang , Xiao, Xiangjun , Romm, Jane, Pugh, Elizabeth, Coetzee, Gerhard A. , Hazelett, Dennis J. , Bojesen, Stig E. , Caga-Anan, Charlisse , Haiman, Christopher A. , Kamal, Ahsan , Luccarini, Craig , Tessier, Daniel C., Vincent, Daniel , Bacot, François, Berg, David Van Den , Nelson, Stefanie A. , Demetriades, Stephen, Goldgar, David E., Forman, Judith L., Conti, David V. , Bickeböller, Heike , Risch, Angela , Waldenberger, Mélanie , Brüske‐Hohlfeld, Irene, Hicks, Belynda , McGuffog, Lesley, Kuchenbaecker, Karoline , Soucy, Penny, Manz, Judith, Cunningham, Julie M. , Butterbach, Katja, Kote‐Jarai, Zsofia , Kraft, Peter , Lindström, Sara , Adams, Marcia, McKay, James , Phelan, Catherine M., Benlloch, Sara, Kelemen, Linda E., Brennan, Paul , Riggan, Marjorie J. , O’Mara, Tracy A. , Shen, Hongbing , Shi, Yongyong , Thompson, Deborah J. , Goodman, Marc T. , Nielsen, Sune F. , LaBoissière, Sylvie, Schmit, Stephanie L. , Shelford, Tameka, Edlund, Christopher K., Taylor, Jack A. , Field, John K. , Park, Sue K. , Offit, Kenneth , Thomassen, Mads , Schmutzler, Rita K., Ottini, Laura , Hung, Rayjean J., Olama, Ali Amin Al , Peters, Ulrike , Eeles, Rosalind A. , Seldin, Michael F., Gillanders, Elizabeth M. , Seminara, Daniela, Antoniou, Antonis C. , Chenevix‐Trench, Georgia , Simard, Jacques , Easton, Douglas F. , Durocher, Francine , Hung, Rayjean J. , Amos, Christopher I. , Dennis, Joe , Byun, Jinyoung , Hunter, David J. , Spurdle, Amanda B. , Couch, Fergus J. , Giles, Graham G. , Ling, Hua , Lee, Andrew , FitzGerald, Liesel M. , Berchuck, Andrew , Marchini, Jonathan , Pharoah, Paul D.P. , Chanock, Stephen Jacob , Hazelett, Dennis J , Eeles, Rosalind A , Van Den Berg, David J , Hung, Rayjean J , Wang, Zhaoming , O'Mara, Tracy A , Field, John K , Dunning, Alison M , Michailidou, Kyriaki , Taylor, Jack A , Kraft, Peter , Simard, Jacques , Chenevix-Trench, Georgia , Ottini, Laura , Conti, David V , Bojesen, Stig E , Risch, Angela , Bickeböller, Heike , Shen, Hongbing , Goodman, Marc T , Fachal, Laura

Cancer Epidemiology, Biomarkers & Prevention | October 3, 2016 | Volume: 26 | Issue: 1 | Pages: 126-135

10.1158/1055-9965.epi-16-0106 Get It

Abstract Background: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. Methods: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. Results: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. Conclusions: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. Impact: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126–35. ©2016 AACR.