5. identificacion de genes


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  • 300K SNPs
  • PTPN21 for RA is not correct…..
  • 5. identificacion de genes

    1. 1. ¿Qué sigue después de la identificación de los genes candidatos para las enfermedades autoinmunes?<br />Christopher J. Lessard, B.Sc., PhD<br />Investigador Asociado, Departamento de Artritis e Inmunología Clínica, Fundación para la Investigación Médica de Oklahoma, Oklahoma City, OK, E.U.<br />
    2. 2. What's Next After Candidate Gene and Genome-wide Association Studies in Autoimmunity<br />Christopher J. Lessard, Ph.D., B.Sc.<br />Associate Research Scientist<br />Oklahoma Medical Research Foundation<br />2nd Colombian Autoimmune Symposium<br />3 March 2011<br />
    3. 3. Outline<br />Identification of susceptibility loci<br />systemic lupus erythematosus (SLE)<br />Question of missing heritability<br />Identification of causal variants<br />Functional studies<br />Epistasis<br />Future of genetics<br />
    4. 4. Candidate Gene Studies in SLE<br />History of SLE genetics began in 1970s<br />C2, C4, C1q very rare but potent risk loci<br />Human genome sequence 99.9% complete<br />IRF5 most replicated SLE locus <br />First genome-wide association study 2006<br />
    5. 5. Impact of Genome Wide Association Studies on Gene Discovery<br />Psor<br />SLE<br />MS<br />CD<br />RA<br />T1D<br />1996<br />INS<br />2001<br />Very few confirmed <br />associations prior to 2006<br />IBD5<br />SH2D2A<br />CARD15<br />2003<br />CTLA4<br />2004<br />PAD14<br />PTPN22<br />PTPN22<br />2005<br />IRF5<br />IL2Ra<br />IL7R<br />PTPN22<br />2006<br />IL23R<br />IFIH1<br />ICAM-1<br />FCRL3<br />PHOX2B<br />ATG16L1<br />1st GWAS<br />2007<br />2008<br />2009<br />2010<br />
    6. 6. Impact of Genome Wide Association Studies on Gene Discovery<br />Psor<br />SLE<br />MS<br />CD<br />RA<br />T1D<br />1996<br />INS<br />2001<br />IBD5<br />SH2D2A<br />CARD15<br />2003<br />CTLA4<br />2004<br />PAD14<br />PTPN22<br />PTPN22<br />2005<br />IRF5<br />IL2Ra<br />IL7R<br />PTPN22<br />2006<br />IL23R<br />IFIH1<br />ICAM-1<br />FCRL3<br />PHOX2B<br />ATG16L1<br />1st GWAS<br />2007<br />C12orf30<br />KIAA350<br />Tenr-IL2<br />PTPN2<br />IL12B<br />3p21<br />IRGM<br />5p13<br />ITGAV<br />TNFAIP3<br />CARD8<br />IL7R<br />ADAM33<br />IL23R<br />ERBB3<br />CD226<br />IL7R<br />NKX2-3<br />10q21<br />ATG16L1<br />PTPN2<br />TRAF1<br />STAT4<br />FOXJ1<br />IL2Ra<br />CD58<br />IL12B<br />CD40<br />TNFAIP3<br />SPP1<br />BLK<br />PTPN21<br />CLEC16A<br />PRKCQ<br />NOD2<br />ATG16L1<br />MST1<br />ZNF365<br />ORMDL3<br />5q33.3<br />XKR6<br />2008<br />C12orf30<br />BACH2<br />PTPN11<br />JAK2<br />PTPN2<br />CCR6<br />NKX2-3<br />ITLN1<br />PTPN22<br />STAT4<br />BANK1<br />PHRF1<br />6q21<br />C8orf12<br />PTPN1<br />CTLA4<br />IRGM<br />PTGER4<br />IL12B<br />STAT3<br />CTSH<br />C11orf30<br />TRAF1<br />ITGAM<br />PXK<br />ICA1<br />SCUBE1<br />NMNAT2<br />IFIH1<br />ERBB3<br />K1F1B<br />IL23R<br />CDKAL1<br />TNFSF15<br />MUC19<br />ICOSLG<br />OLIG3<br />TNFSF4<br />UBE2L3<br />8p23.1<br />LYN<br />1q25.1<br />7q11.23<br />DLK1<br />RIO3<br />C10orf59<br />IL2RA<br />HIC2<br />IL2<br />CD69<br />TNFRSF1A<br />REL<br />ETS1<br />CYP27B1<br />PRDM1<br />WDFY4<br />IL23A<br />2009<br />MEG3<br />TYK2<br />SHBB3<br />IL27<br />IL10<br />CTLA4<br />STAT4<br />CD6<br />IKZF1<br />ORMDL3<br />ATG5<br />SLC15A4<br />IL13<br />STAT2<br />IL10<br />LRRC18<br />PTPN2<br />RTL1<br />INS<br />C6orf173<br />GLIS3<br />UBASH3A<br />BLK<br />IRF8<br />JAZF1<br />RASGRP3<br />TNIP1<br />TNFAIP3<br />UHRF1BP1<br />TNIP1<br />2010<br />CCR6<br />AFF3<br />ANKRD55<br />IRF5<br />SPRED2<br />METTL1<br />ETS1<br />DQA1<br />IRF8<br />CD44<br />RBPJ<br />IL2RA<br />IL6ST<br />CCL21<br />STAT3<br />CBLB<br />CD40<br />
    7. 7. 2008: New SLE Genes Revealed by GWAS<br />
    8. 8. Association between a SNP and disease status<br />For “D” = disease risk allele:<br />Affecteds<br />Controls<br />DD 10/20 = .50 <br />Dd 6/20 = .30 <br />dd 4/20 = .20<br />DD 2/20 = .10 <br />Dd 4/20 = .20 <br />dd 14/20 = .70<br />Test <br />distributions for <br />a statistically significant difference<br />
    9. 9. MN GWAS Results Summary<br />431 SLE cases; 2155 controls<br />MHC<br />IRF5<br />TNFAIP3<br />P=5x10-8 (genome-wide significant)<br />Significance level<br />P=9x10-7 (suggestive)<br />SNP Location (by chromosome then base pair)<br />Genome-wide - P=5x10-8<br />Suggestive - P=9x10-7<br />Graham et al. Nat Genet 2008<br />
    10. 10. STAT4<br />IRAK1<br />IRF5<br />TNFAIP3<br />HLA-DR<br />PTPN22<br />BLK<br />BANK1<br />FcγR3A<br />FcγR2B<br />C4A<br />C2<br />FcγR3B<br />C4B<br />IRAK1<br />TNFSF4<br />PXK<br />XKR6<br />ICA1<br />ATG5<br />NMNAT2 <br />MECP2<br />ITGAM<br />PDCD1<br />SCUBE1<br />UBE2L3<br />KIAA1542<br />CRP<br />STAT4<br />C1q<br />TNFAIP3<br />SPP1<br />HLA-DR<br />ITGAM<br />STAT4<br />LYN<br />TREX1<br />CD44<br />T Cell signaling<br />DNA methylation<br />TLR/IFN signaling<br />TNF/NFκB signaling<br />B Cell signaling<br />Phagocytosis <br />Complement <br />Apoptosis<br />Ubiquitination<br />Unknown<br />Cellular adhesion<br />Many Genes, Fewer Genetic Pathways in SLE<br />Association of ~35 genes robustly confirmed, more on the way <br />b((Modified from Moser et al, Gene & Immunity SLE Genetics Special Issue, 2009)<br />Pathways<br />Cells<br />Genes<br />Innate Immune Response<br />Dendritic cells<br />Macrophages <br />Autoreactive T cells<br />Autoreactive B cells<br />Lymphocyte Activation/Function<br />Immune Complex Clearance <br />Macrophages<br />Neutrophils<br />Other<br />
    11. 11. More Loci Identified in 2009-present<br />Continued replication in European cohorts<br />GWAS replication limited to top few hits<br />CD44 ranked ~2000<br />Ranking of SNPs by p-value not optimal<br />Common or rare variants hard to detect in small sample sizes <br />
    12. 12. Asian GWAS completed in 2009<br />First SLE GWAS in non-European population<br />Evidence for susceptibility loci unique to Asians<br />Some regions not evaluated in Europeans<br />
    13. 13. Question of Missing Heritability<br />Many risk loci, but marginal risk <br />odds ratios (OR) typically < 2.0<br />HLA and TNFAIP3 OR ≈ 2.5<br />HLA and IRF5 account for ~1% of heritable risk for Europeans<br />With all loci identified (~35), it is estimated that only 8-12% of heritable risk for Europeans has been identified<br />Why? <br />
    14. 14. GWAS to Date Limited<br />Many of the causal variants yet to be identified<br />Functional consequences remain elusive<br />No subphenotype GWAS<br />Limited resequencing to find rare variants<br />Methylation not comprehensively studied <br />No whole transcriptome sequencing <br />No Amerindian and African-American GWAS <br />
    15. 15. Causal Variants Bottleneck<br />Linkage Disequilibrium (LD)<br />Correlation between variants<br />Aids identification of association during GWAS(lowers cost)<br />Makes causal variant localization difficult<br />
    16. 16. CD44 Replication Dataset and Association Analysis<br />Analysis: Logistic regression (PLINK)<br /><ul><li>Compare distribution (frequencies) of SNP genotypes (DD, Dd, dd) between cases and controls to identify a statistically significant difference
    17. 17. P-value thresholds for two levels of significance:
    18. 18. “Genome-wide” = p < 5 x 10-8
    19. 19. “Suggestive” = p-value < 1 x 10-4
    20. 20. GWAS identified 2 SNPs p=3x10-3</li></li></ul><li>Replication of Association at 11p13 near CD44<br />meta-analysis<br />
    21. 21. Results After Imputation<br />
    22. 22. Association with Other Ethnic Groups<br /><ul><li>Both AA and Asians associated with rs2732552:
    23. 23. AA: P=5.0x10-3
    24. 24. Asian: P=4.3x10-4
    25. 25. Combined all Europeans, Asians and African-Americans: Pmeta=3.0x10-13
    26. 26. rs387619 was associated with Asians, but not AA
    27. 27. No evidence of association with Hispanics, Gullah or Amerindians</li></ul>European<br />Asian<br />African-<br />American<br />
    28. 28. Regulatory Region<br /><ul><li>Haplotype contains several regulatory elements:
    29. 29. ~74 Kb telomeric of CD44 and ~61 Kb centromeric of PDHX
    30. 30. Several regulatory sites identified by mining ENCODE ChIP-Seq data</li></li></ul><li>CD44<br /><ul><li>Widely expressed in immunological cells
    31. 31. Numerous splice variants
    32. 32. Tissue specificity
    33. 33. Variable exonic region
    34. 34. Cell-surface glyoprotein involved in cell-cell interactions, cell adhesion and migration
    35. 35. Receptor for:
    36. 36. Hyaluronic acid (HA), osteopontin, collagens, matrix metalloproteinases (MMPs)
    37. 37. Accessory molecule in the synapse between APC-T cell complex</li></ul>~93Kb<br />
    38. 38. CD44 and SLE<br /><ul><li>Expression of protein widely studied</li></li></ul><li>TNFAIP3 Putative Causal Variant<br />
    39. 39. NF-B Signaling<br />TNFAIP3 encodes the protein A20<br />
    40. 40. Attenuates TNF signaling<br />Vigo Heissmeyer & Anjana Rao, Nature Immunology 9, 227 - 229 (2008)<br />
    41. 41. Association of TNFAIP3 <br />Europeans<br />Identified a broad region of association<br />No association in African-Americans<br />Imputation and resequencing reveal putative causal variant<br />Asians<br />Koreans<br />
    42. 42. Imputation and Resequencing<br />Imputation found a novel SNP in the 1000 Genomes dataset<br />Resequencing identified a deletion/insertion polymorphism<br />Together form TT>A putative causal polymorphism<br />Conditional analysis <br />
    43. 43. Transcription Factors Sites Identified<br />Chromatin immunopreciptitation followed by sequencing by ENCODE project<br />Used this data to begin functional studies<br />
    44. 44. Risk Variants Affect Biology<br />Found difference in binding using electrophoretic mobility shift assays<br />mRNA expression altered<br />Protein expression altered<br />
    45. 45. Epistasis<br />Gene-gene interactions<br />Usually done statistically<br />No evidence for epistasis in regions found in SLE work<br />TNFAIP3 and TNIP1 both associated with SLE and do interact biologically<br />
    46. 46. Future of Autoimmune Genetics <br />Essential to recruit more subjects<br />Much larger GWAS: <br />>50,000 subjects<br />More variants (>5 million)<br />Makes subphenotype studies possible<br />Whole genome sequencing<br />Whole transcriptome sequencing<br />eQTL analysis with GWAS data<br />Epigenetic studies<br />
    47. 47. Power to Detect Association<br />Power influenced by:<br />Allele freqency<br />Odds ratio<br />Sample size<br />Need large sample size for rare variants and recessive effects<br />
    48. 48. Connecticut<br />Mark Mamula<br />Yale University<br />New York<br />Michigan<br />Andras Perl<br />SUNY<br />Jane Salmon<br />Hospital for Special Surgery<br />Nicholas Chiarazzi<br />Charles Chu<br />Peter Gregerson<br />North Shore University Hospital<br />Joseph McCune<br />University of Michigan<br />Ohio<br />Illinois<br />John B. Harley<br />Cincinnati Children’s Hospital MC<br />Jane Olson<br />Case Western University<br />Washington<br />Michael Schneider<br />Southern Illinois U<br />Timothy Niewold<br />Tammy Utset<br />UChicago<br />J. Lee Nelson<br />F. Hutchinson Cancer Res Ctr<br />Gerald Nopom<br />Virginia Mason Research Ctr<br />Oklahoma<br />Morris Foster<br />OU<br />Kathleen O’Neil<br />OUHSC<br />Pennsylvania<br />Mark Shriver<br />Penn State U<br />Kathleen Sullivan<br />Children’s Hospital of Philadelphia<br />North Carolina<br />Missouri<br />Bart Haynes<br />Duke University<br />Andrey Shaw<br />WashingtonU<br />California<br />OMRF<br />Marta E. Alarcón-Riquelme<br />Darise Farris<br />Bart Frank<br />Judith James<br />Ken Kaufman<br />Biji Kurien<br />Joan Merrill<br />Courtney Montgomery<br />Kathy Moser<br />Patrick Gaffney<br />Swapan Nath<br />Amr Sawalha<br />Hal Scofield<br />Minnesota<br />Steve Bindor<br />Bio-Rad Labs<br />Lisa Barcellos<br />UC Berkeley<br />Evan Hermel<br />Touro University<br />Lindsey Criswell<br />UCSF<br />Betty Tsao<br />UCLA<br />Anshu Agrawal<br />Univ California<br />Mariana Israeli<br />Dan Wallace<br />Michael Weisman<br />CSMC<br />Chaim Jacob<br />USC<br />South Carolina<br />Timothy Behrens<br />University of Minnesota<br />Gary Gilkeson<br />Diane Kamen<br />MUSC<br />Kentucky<br />Jonathan Chaires<br />James Brown Cancer Center<br />Bart Haynes<br />Dukes University<br />Dama Laxminarayana<br />Wake Forest University<br />Alabama<br />Robert Kimberley<br />UAB<br />Massachusetts<br />Harold Chapman<br />Harvard Medical School<br />Brigette Huber<br />Tufts University<br />Patricia Fraser<br />Brigham & Women’s Hospital<br />Texas<br />Edward Wakeland<br />David Karp<br />UT Southwestern MC<br />USA LFRR Collaborators & Approved Users<br />
    49. 49. Sweden<br />Marta Alarcon<br />Uppsala University<br />Rose Goldstein<br />University of Ottawa<br />Andrew Paterson<br />University of Toronto<br />United Kingdom<br />Timothy Vyse<br />Imperial College of Science, Technology & Medicine<br />Grant Gallagher<br />University of Glasgow<br />Norway<br />Finland<br />Roland Jonsson<br />University of Bergen<br />Markus Perola<br />National Public Health Institute<br />Ana Quintero<br />OMRF<br />Denmark<br />Runa Nolsoe<br />Steno Diabetes Center<br />Juan-Manuel Anaya<br />Adriana Rojas<br />University del Rosario<br />Japan<br />Sachiko Hirosa<br />Juntonda U School of Medicine<br />Sumida Takayuki<br />University of Tsukuba<br />Ontario<br />Manual Ramos-Casals<br />Barcelona Hospital<br />South Korea<br />Colombia<br />Spain<br />Bao Sang-Cheol<br />University of Seoul<br />Australia<br />Puerto Rico<br />Carola Vinuesa<br />Australian National University<br />International LFRR Collaborators & Approved Users<br />
    50. 50. SGENE: The Sjogren’sGenetics Network<br /> International group interested in contributing DNA samples and clinical data for genetic studies<br /> Currently:<br />15 contributing sites (plus subsites) <br />>2000 SS cases (AECG criteria), 2000 controls<br />Developing consistent clinical dataset<br /> Goal:<br /> Continue to expand sites <br /> Overall: 15,000+ cases<br /> Primary cohort for Replication Studies<br />
    51. 51.
    52. 52. The Lupus Family Registry & Repository<br />The LFRR always needs more participants<br />lupus-recruiters@lupus.omrf.org<br />lupus.omrf.org<br />More Sjögren’s syndrome Patients Needed<br />lessardc@omrf.org<br />