Xia Z, Secor E, Chibnik LB, et al. Modeling disease severity in multiple sclerosis using electronic health records. PLoS One. 2013;8(11):e78927. doi:10.1371/journal.pone.0078927
Patsopoulos NA, Barcellos LF, Hintzen RQ, et al. Fine-mapping the genetic association of the major histocompatibility complex in multiple sclerosis: HLA and non-HLA effects. PLoS Genet. 2013;9(11):e1003926. doi:10.1371/journal.pgen.1003926
Gusev A, Bhatia G, Zaitlen N, et al. Quantifying missing heritability at known GWAS loci. PLoS Genet. 2013;9(12):e1003993. doi:10.1371/journal.pgen.1003993
Damotte V, Guillot-Noel L, Patsopoulos NA, et al. A gene pathway analysis highlights the role of cellular adhesion molecules in multiple sclerosis susceptibility. Genes Immun. 2014;15(2):126-32. doi:10.1038/gene.2013.70
Yang J, Zaitlen NA, Goddard ME, Visscher PM, Price AL. Advantages and pitfalls in the application of mixed-model association methods. Nat Genet. 2014;46(2):100-6. doi:10.1038/ng.2876
Kleinewietfeld M, Hafler DA. Regulatory T cells in autoimmune neuroinflammation. Immunol Rev. 2014;259(1):231-44. doi:10.1111/imr.12169
Xiao S, Yosef N, Yang J, et al. Small-molecule RORγt antagonists inhibit T helper 17 cell transcriptional network by divergent mechanisms. Immunity. 2014;40(4):477-89. doi:10.1016/j.immuni.2014.04.004
Paraboschi EM, Rimoldi V, Soldà G, et al. Functional variations modulating PRKCA expression and alternative splicing predispose to multiple sclerosis. Hum Mol Genet. 2014;23(25):6746-61. doi:10.1093/hmg/ddu392
Hayeck TJ, Zaitlen NA, Loh PR, et al. Mixed model with correction for case-control ascertainment increases association power. Am J Hum Genet. 2015;96(5):720-30. doi:10.1016/j.ajhg.2015.03.004
Cao Y, Goods BA, Raddassi K, et al. Functional inflammatory profiles distinguish myelin-reactive T cells from patients with multiple sclerosis. Sci Transl Med. 2015;7(287):287ra74. doi:10.1126/scitranslmed.aaa8038