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Jorge R. Oksenberg, Ph.D. Professor of Neurology University of California, San Francisco

Mapping genetic susceptibility and modeling pathogenesis in multiple sclerosis. Fundación Ramón Areces. Madrid, 2 de Febrero de 2012. Jorge Oksenberg UCSF School of Medicine Department of Neurology jorge.oksenberg@ucsf.edu. Jorge R. Oksenberg, Ph.D. Professor of Neurology

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Jorge R. Oksenberg, Ph.D. Professor of Neurology University of California, San Francisco

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  1. Mapping genetic susceptibility and modeling pathogenesis in multiple sclerosis Fundación Ramón Areces. Madrid, 2 de Febrero de 2012 Jorge Oksenberg UCSF School of Medicine Department of Neurology jorge.oksenberg@ucsf.edu Jorge R. Oksenberg, Ph.D. Professor of Neurology University of California, San Francisco

  2. I excess glutamate Autoantibodies Immune response CNS inflammation Neurodegeneration Neurodegeneration CNS inflammation Immune response Complement Processed Ag T CELL REACTIVATION ROS Cytokines and chemokines TCR MHC M Y E L I N Ca2+ Na+ IL-17, IL-12, IL-23, OPN chemokines Activation of NA+ channels and reverse Na+Ca2+ exchange Activated CD11b+ microglia CD28 B7-1 IFN-, IL-2 Dendritic cell IL-12 T cell II a T DC T M

  3. Multiple Sclerosis • 1:1000 in North Americans and Europeans • Incidence increased steadily during the        20th century • F:M ratio = 2-3:1 • Age of onset = 20-40 • Influence of latitude on risk • Influence of ancestry on risk • Disease family history in ~20% of cases

  4. MS is a complex genetic disease

  5. Genome-wide association screens MS

  6. The MS Genome 2012 IMSGC & WTCCC2 Nature (2011) 476; 214-9

  7. MS susceptibility genes in the T helper cell differentiation pathway Genome-wide significant Discovery P < 10-4.5 and consistent replication Discovery P < 10-3 IMSGC & WTCCC2 Nature (2011) 476; 214-9

  8. The autoimmunity web Baranzini S. Curr Opin Immunol 21:596, 2009

  9. Pathways and networks in MS Filtered GWAS nominal association P-values overlap with a PPI network Baranzini et al. Hum Molec Genet 18:2078, 2009

  10. Cumulative genetic risk MSGB gradient in multi- and single-case families

  11. Cumulative genetic risk MSGB gradient among siblings

  12. Cumulative genetic risk MSGB gradient among siblings No direct use in diagnostic No predictive power

  13. Sir Augustus d’Este (1794-1848) from the collection of the Victoria and Albert Museum, London. MS makes its first clear appearance in 1822 in the diaries of Augustus D’Este, the illegitimate grandson of King George III (Firth D, 1948)

  14. Full-genome sequencing of a multi-case MS family DRB1*15:01 I DRB1*15:01 DRB1*15:01 II III DRB1*15:01 DRB1*15:01 DRB1*15:01

  15. Full-genome sequencing of a multi-case MS family Input: 4.5 million variants (SNVs and indels) / genome L. Madireddy, P. Khankhanian & S. Baranzini

  16. Full-genome sequencing of a multi-case MS family

  17. Gene discovery in MS Second generation GWAS (10,000 patients) Second generation genome-wide linkage study (5000 markers) Whole genome sequencing of MS twins First generation genome-wide linkage studies (400 markers) First reported association between MS and HLA A/A First generation GWAS (1000 patients) Meta-analysis of GWAS G/G STUDIES A/G 1996 2010 1972 2011 2009 2005 2007 2011 GENES HLA IL2RA IL7R CD58 CLEC16A EVI5 CD226 CD6 IRF8 TNFRSF1A TYK2 MMEL1 RGS1 KIF21B CBLB TMEM39A IL12A PTGER OLIG3 IL7 ZMIZ1 MPHOSPH9 STAT3 CD40 CLECL1 ZFP36L1 BATF GALC MALT1 TNFSF14 MPV17L2 DKKL1 MAPK1 SCO2 NFKB2 CXCR5 SOX8 RPS6KB1 TNFRSF6 CYP27B1 CYP24A1 VCAM PLEK MERT SP140 EOMES CD86 IL12B BACH2 THEMIS MYB IL22RA2 TAGAP ZNF767 MYC PVT1 HHEX

  18. Multiple Sclerosis Treatment of Multiple SclerosisHarrison’s Principles of Internal Medicine 3rd Ed, 1958 The most that can be done is to reassure and encourage the patient through moderate exercise and supportive measures…during an acute episode it is surely preferable to assure the patient that he will recover and to preserve silence on the subject of relapse. John N. Walton

  19. Multiple Sclerosis therapeutics 2012 Phase I Lymphocyte trafficking AJM-300 Interferons Phase II ATL-1102 Fc- IFb TBC4746 Phase III Firategrast IFN omega IFNTau R1295 Marketed Fingolimod MLN-0002 sc IFN β-1b Peg IFNb (BIIB017) Natalizumab im IFN β-1a sc IFN β-1a Laquinimod Azathioprine Riluzole Novantrone Anti-proliferation agents Cladribine Teriflunomide Daclizumab Glatiramer acetate BG12 Pixantrone MM-093 Anti-T cell vaccine Delta-9-THC 683699 (T-0047) Targeted Immune regulation ATX-MS-1467 Fampridine SR Rituximab Alemtuzumab Vaccine, tolerization PI2301 Nerispirdine Ocrelizumab Symptomatic Tx LY-2127399 Atacicept Ofatumumab oral administration injectable Targeted mAbs/Fc-Ab Courtesy of Gavin Giovannoni

  20. MS as a genetic disease. The agenda • In the last 10 years, sequencing technologies have improved by many orders of magnitude. • In the last 5 years, tissue and organ imaging technologies permit the (non-invasive) deconstruction of the phenotype to the metabolite level.

  21. MS as a genetic disease. The agenda • Advances in microscopy now make it possible to observe how individual cells, including neurons behave when genes are turned on and off. • Cell- and molecular- resolution models of the nervous system is looking more and more doable. • Major improvements in the development of systems and network-based approaches for the interpretation of high-dimensional biological data.

  22. MS as a genetic disease. The agenda The convergence of -omicswith next generation imaging, informatics, and effective Electronic Medical Record systems will: • Allow the deployment of this information in a point-of-care decision support environment. • Generate a genetic road map to guide us in the discovery of new drugs at an unprecedented pace. • Allow to implement the promise of personalized medicine.

  23. Front-end tablet Application Database Gateway & Computations Imaging User data Reference groups of patients Individual data

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