1. ¿Qué sigue después de la identificación de los genes candidatos para las enfermedades autoinmunes? Christopher J. Lessard, B.Sc., PhD Investigador Asociado, Departamento de Artritis e Inmunología Clínica, Fundación para la Investigación Médica de Oklahoma, Oklahoma City, OK, E.U.

2. What's Next After Candidate Gene and Genome-wide Association Studies in Autoimmunity Christopher J. Lessard, Ph.D., B.Sc. Associate Research Scientist Oklahoma Medical Research Foundation 2nd Colombian Autoimmune Symposium 3 March 2011

3. Outline Identification of susceptibility loci systemic lupus erythematosus (SLE) Question of missing heritability Identification of causal variants Functional studies Epistasis Future of genetics

4. Candidate Gene Studies in SLE History of SLE genetics began in 1970s C2, C4, C1q very rare but potent risk loci Human genome sequence 99.9% complete IRF5 most replicated SLE locus First genome-wide association study 2006

5. Impact of Genome Wide Association Studies on Gene Discovery Psor SLE MS CD RA T1D 1996 INS 2001 Very few confirmed associations prior to 2006 IBD5 SH2D2A CARD15 2003 CTLA4 2004 PAD14 PTPN22 PTPN22 2005 IRF5 IL2Ra IL7R PTPN22 2006 IL23R IFIH1 ICAM-1 FCRL3 PHOX2B ATG16L1 1st GWAS 2007 2008 2009 2010

6. Impact of Genome Wide Association Studies on Gene Discovery Psor SLE MS CD RA T1D 1996 INS 2001 IBD5 SH2D2A CARD15 2003 CTLA4 2004 PAD14 PTPN22 PTPN22 2005 IRF5 IL2Ra IL7R PTPN22 2006 IL23R IFIH1 ICAM-1 FCRL3 PHOX2B ATG16L1 1st GWAS 2007 C12orf30 KIAA350 Tenr-IL2 PTPN2 IL12B 3p21 IRGM 5p13 ITGAV TNFAIP3 CARD8 IL7R ADAM33 IL23R ERBB3 CD226 IL7R NKX2-3 10q21 ATG16L1 PTPN2 TRAF1 STAT4 FOXJ1 IL2Ra CD58 IL12B CD40 TNFAIP3 SPP1 BLK PTPN21 CLEC16A PRKCQ NOD2 ATG16L1 MST1 ZNF365 ORMDL3 5q33.3 XKR6 2008 C12orf30 BACH2 PTPN11 JAK2 PTPN2 CCR6 NKX2-3 ITLN1 PTPN22 STAT4 BANK1 PHRF1 6q21 C8orf12 PTPN1 CTLA4 IRGM PTGER4 IL12B STAT3 CTSH C11orf30 TRAF1 ITGAM PXK ICA1 SCUBE1 NMNAT2 IFIH1 ERBB3 K1F1B IL23R CDKAL1 TNFSF15 MUC19 ICOSLG OLIG3 TNFSF4 UBE2L3 8p23.1 LYN 1q25.1 7q11.23 DLK1 RIO3 C10orf59 IL2RA HIC2 IL2 CD69 TNFRSF1A REL ETS1 CYP27B1 PRDM1 WDFY4 IL23A 2009 MEG3 TYK2 SHBB3 IL27 IL10 CTLA4 STAT4 CD6 IKZF1 ORMDL3 ATG5 SLC15A4 IL13 STAT2 IL10 LRRC18 PTPN2 RTL1 INS C6orf173 GLIS3 UBASH3A BLK IRF8 JAZF1 RASGRP3 TNIP1 TNFAIP3 UHRF1BP1 TNIP1 2010 CCR6 AFF3 ANKRD55 IRF5 SPRED2 METTL1 ETS1 DQA1 IRF8 CD44 RBPJ IL2RA IL6ST CCL21 STAT3 CBLB CD40

7. 2008: New SLE Genes Revealed by GWAS

8. Association between a SNP and disease status For “D” = disease risk allele: Affecteds Controls DD 10/20 = .50 Dd 6/20 = .30 dd 4/20 = .20 DD 2/20 = .10 Dd 4/20 = .20 dd 14/20 = .70 Test distributions for a statistically significant difference

9. MN GWAS Results Summary 431 SLE cases; 2155 controls MHC IRF5 TNFAIP3 P=5x10-8 (genome-wide significant) Significance level P=9x10-7 (suggestive) SNP Location (by chromosome then base pair) Genome-wide - P=5x10-8 Suggestive - P=9x10-7 Graham et al. Nat Genet 2008

10. STAT4 IRAK1 IRF5 TNFAIP3 HLA-DR PTPN22 BLK BANK1 FcγR3A FcγR2B C4A C2 FcγR3B C4B IRAK1 TNFSF4 PXK XKR6 ICA1 ATG5 NMNAT2 MECP2 ITGAM PDCD1 SCUBE1 UBE2L3 KIAA1542 CRP STAT4 C1q TNFAIP3 SPP1 HLA-DR ITGAM STAT4 LYN TREX1 CD44 T Cell signaling DNA methylation TLR/IFN signaling TNF/NFκB signaling B Cell signaling Phagocytosis Complement Apoptosis Ubiquitination Unknown Cellular adhesion Many Genes, Fewer Genetic Pathways in SLE Association of ~35 genes robustly confirmed, more on the way b((Modified from Moser et al, Gene & Immunity SLE Genetics Special Issue, 2009) Pathways Cells Genes Innate Immune Response Dendritic cells Macrophages Autoreactive T cells Autoreactive B cells Lymphocyte Activation/Function Immune Complex Clearance Macrophages Neutrophils Other

11. More Loci Identified in 2009-present Continued replication in European cohorts GWAS replication limited to top few hits CD44 ranked ~2000 Ranking of SNPs by p-value not optimal Common or rare variants hard to detect in small sample sizes

12. Asian GWAS completed in 2009 First SLE GWAS in non-European population Evidence for susceptibility loci unique to Asians Some regions not evaluated in Europeans

13. Question of Missing Heritability Many risk loci, but marginal risk odds ratios (OR) typically < 2.0 HLA and TNFAIP3 OR ≈ 2.5 HLA and IRF5 account for ~1% of heritable risk for Europeans With all loci identified (~35), it is estimated that only 8-12% of heritable risk for Europeans has been identified Why?

14. GWAS to Date Limited Many of the causal variants yet to be identified Functional consequences remain elusive No subphenotype GWAS Limited resequencing to find rare variants Methylation not comprehensively studied No whole transcriptome sequencing No Amerindian and African-American GWAS

15. Causal Variants Bottleneck Linkage Disequilibrium (LD) Correlation between variants Aids identification of association during GWAS(lowers cost) Makes causal variant localization difficult

17. P-value thresholds for two levels of significance:

18. “Genome-wide” = p < 5 x 10-8

19. “Suggestive” = p-value < 1 x 10-4

21. Results After Imputation

23. AA: P=5.0x10-3

24. Asian: P=4.3x10-4

25. Combined all Europeans, Asians and African-Americans: Pmeta=3.0x10-13

26. rs387619 was associated with Asians, but not AA

27. No evidence of association with Hispanics, Gullah or AmerindiansEuropean Asian African- American

29. ~74 Kb telomeric of CD44 and ~61 Kb centromeric of PDHX

31. Numerous splice variants

32. Tissue specificity

33. Variable exonic region

34. Cell-surface glyoprotein involved in cell-cell interactions, cell adhesion and migration

35. Receptor for:

36. Hyaluronic acid (HA), osteopontin, collagens, matrix metalloproteinases (MMPs)

37. Accessory molecule in the synapse between APC-T cell complex~93Kb

39. NF-B Signaling TNFAIP3 encodes the protein A20

40. Attenuates TNF signaling Vigo Heissmeyer & Anjana Rao, Nature Immunology 9, 227 - 229 (2008)

41. Association of TNFAIP3 Europeans Identified a broad region of association No association in African-Americans Imputation and resequencing reveal putative causal variant Asians Koreans

42. Imputation and Resequencing Imputation found a novel SNP in the 1000 Genomes dataset Resequencing identified a deletion/insertion polymorphism Together form TT>A putative causal polymorphism Conditional analysis

43. Transcription Factors Sites Identified Chromatin immunopreciptitation followed by sequencing by ENCODE project Used this data to begin functional studies

44. Risk Variants Affect Biology Found difference in binding using electrophoretic mobility shift assays mRNA expression altered Protein expression altered

45. Epistasis Gene-gene interactions Usually done statistically No evidence for epistasis in regions found in SLE work TNFAIP3 and TNIP1 both associated with SLE and do interact biologically

46. Future of Autoimmune Genetics Essential to recruit more subjects Much larger GWAS: >50,000 subjects More variants (>5 million) Makes subphenotype studies possible Whole genome sequencing Whole transcriptome sequencing eQTL analysis with GWAS data Epigenetic studies

47. Power to Detect Association Power influenced by: Allele freqency Odds ratio Sample size Need large sample size for rare variants and recessive effects

48. Connecticut Mark Mamula Yale University New York Michigan Andras Perl SUNY Jane Salmon Hospital for Special Surgery Nicholas Chiarazzi Charles Chu Peter Gregerson North Shore University Hospital Joseph McCune University of Michigan Ohio Illinois John B. Harley Cincinnati Children’s Hospital MC Jane Olson Case Western University Washington Michael Schneider Southern Illinois U Timothy Niewold Tammy Utset UChicago J. Lee Nelson F. Hutchinson Cancer Res Ctr Gerald Nopom Virginia Mason Research Ctr Oklahoma Morris Foster OU Kathleen O’Neil OUHSC Pennsylvania Mark Shriver Penn State U Kathleen Sullivan Children’s Hospital of Philadelphia North Carolina Missouri Bart Haynes Duke University Andrey Shaw WashingtonU California OMRF Marta E. Alarcón-Riquelme Darise Farris Bart Frank Judith James Ken Kaufman Biji Kurien Joan Merrill Courtney Montgomery Kathy Moser Patrick Gaffney Swapan Nath Amr Sawalha Hal Scofield Minnesota Steve Bindor Bio-Rad Labs Lisa Barcellos UC Berkeley Evan Hermel Touro University Lindsey Criswell UCSF Betty Tsao UCLA Anshu Agrawal Univ California Mariana Israeli Dan Wallace Michael Weisman CSMC Chaim Jacob USC South Carolina Timothy Behrens University of Minnesota Gary Gilkeson Diane Kamen MUSC Kentucky Jonathan Chaires James Brown Cancer Center Bart Haynes Dukes University Dama Laxminarayana Wake Forest University Alabama Robert Kimberley UAB Massachusetts Harold Chapman Harvard Medical School Brigette Huber Tufts University Patricia Fraser Brigham & Women’s Hospital Texas Edward Wakeland David Karp UT Southwestern MC USA LFRR Collaborators & Approved Users

49. Sweden Marta Alarcon Uppsala University Rose Goldstein University of Ottawa Andrew Paterson University of Toronto United Kingdom Timothy Vyse Imperial College of Science, Technology & Medicine Grant Gallagher University of Glasgow Norway Finland Roland Jonsson University of Bergen Markus Perola National Public Health Institute Ana Quintero OMRF Denmark Runa Nolsoe Steno Diabetes Center Juan-Manuel Anaya Adriana Rojas University del Rosario Japan Sachiko Hirosa Juntonda U School of Medicine Sumida Takayuki University of Tsukuba Ontario Manual Ramos-Casals Barcelona Hospital South Korea Colombia Spain Bao Sang-Cheol University of Seoul Australia Puerto Rico Carola Vinuesa Australian National University International LFRR Collaborators & Approved Users

50. SGENE: The Sjogren’sGenetics Network International group interested in contributing DNA samples and clinical data for genetic studies Currently: 15 contributing sites (plus subsites) >2000 SS cases (AECG criteria), 2000 controls Developing consistent clinical dataset Goal: Continue to expand sites Overall: 15,000+ cases Primary cohort for Replication Studies

52. The Lupus Family Registry & Repository The LFRR always needs more participants lupus-recruiters@lupus.omrf.org lupus.omrf.org More Sjögren’s syndrome Patients Needed lessardc@omrf.org