Ciclo de conferencias y debates en Ciencias. Fundación Ramón Areces-Nature Publishing Group. Jorge R. Oksenberg. Universidad de California, San Francisco, EE. UU. Madrid, 2 de febrero de 2012

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 R. Oksenberg, Ph.D.
jorge.oksenberg@ucsf.edu Professor of Neurology
University of California, San Francisco

2. I Immune response CNS inflammation Neurodegeneration
Processed
Ag T CELL excess
REACTIVATION glutamate
Autoantibodies
TCR MHC Cytokines Complement
and
chemokines ROS
IL-17, IL-12, IL-23, OPN
chemokines
MYELIN
CD28B7-1 Activated Ca2+ Na+
T cell Dendritic IFN-, IL-2
CD11b+ microglia
cell Activation of NA+ channels and
IL-12 reverse Na+Ca2+ exchange
a
T
T DC M
II Immune response Neurodegeneration
CNS inflammation

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
Number of
Population Number of Featured loci /
Study Design screened
origin SNPs genes
samples
Wellcome Trust Cases-shared 1,000 cases 14,436 (non
UK IL7R
CCC (2007) controls 1,500 controls synonymous)
HLA, IL2R, IL7R,
Family and
IMSGC (2007) US, UK 931 family trios 334,923 CLEC16, CD58,
case control
EVI5, TYK2
Comabella et al. Pooled case- 242 cases
Spain 500,000 HLA, 13q31.3
(2008) control 242 controls
US, The
GeneMSA C. 978 cases HLA, GPC5,
Case-control Netherlands, 551,642
(2009) 883 controls PDZRNA4, CSMD1
Switzerland
Case-shared Australia and 1,618 cases HLA, METTL1,
ANZ C. (2009) 303,431
controls New Zealand 3,413 controls CD40
Meta-analysis US, UK, The
De Jager et al. 2,624 case 2,557,248 TNFRSF1A, IRF8,
and case- Netherlands,
(2009) 7,220 controls (imputed) CD6, RGS1
control Switzerland
Jakkula et al. Isolated case- 68 cases
Finland 297,343 STAT3
(2010) control 136 controls
Sanna et al. 882 cases 6,600,000
Case-control Sardinia HLA, CBLB
(2010) 872 controls (imputed)
IMSGC (2011) Case-control US, Europe, 9,772 cases 441,547 HLA, 29 novel
Australia 17,376 controls

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
Nr. % Associated
GOID GOTerm GOLevels GOGroup Genes Genes Term PValue
GO:0007411 axon guidance [4, 5, 7, 8, 9, 10, 11, 12] [None] 23 6.571429 1.84E-08
MyD88-dependent toll-like receptor signaling
Filtered GWAS
GO:0002755 pathway [7, 8, 9, 10, 11, 12] [Group9] 7 9.459459 2.16E-04
nominal
GO:0034142 toll-like receptor 4 signaling pathway [7, 8, 9, 10, 11, 12] [Group9] 7 8.641975 3.79E-04
association P-
MyD88-independent toll-like receptor signaling
GO:0002756 pathway [7, 8, 9, 10, 11, 12] [Group9] 6 9.230769 6.99E-04
values overlap
[Group1,
with a PPI Group24,
GO:0042093 T-helper cell differentiation [9, 10, 11, 12, 13] Group28] 4 16 6.99E-04
network
GO:0034138 toll-like receptor 3 signaling pathway [7, 8, 9, 10, 11, 12] [Group9] 6 8.955224 8.21E-04
GO:0034130 toll-like receptor 1 signaling pathway [7, 8, 9, 10, 11, 12] [Group9] 6 8.695652 9.60E-04
GO:0034134 toll-like receptor 2 signaling pathway [7, 8, 9, 10, 11, 12] [Group9] 6 8.450705 0.001116036
GO:0031290 retinal ganglion cell axon guidance [5, 6, 8, 9, 10, 11, 12, 13] [None] 3 20 0.001749115
inhibition of adenylate cyclase activity by G- [7, 8, 9, 10, 11, 12, 13, 14,
GO:0007193 protein signaling pathway 15] [Group23] 4 9.302325 0.005410457
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)

15. 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

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

17. Full-genome sequencing of a multi-case
MS family
Chr Pos Gene symbol Description
chr1:150727539 CTSS Cathepsin S
chr10:115393929 NRAP Nebulin-related anchoring protein
chr10:88414569 OPN4 Opsin 4
chr11:134128923 ACAD8 Acyl-CoA dehydrogenase family, member 8
chr4:84383735 FAM175A Family with sequence similarity 175, member A
chr5:55206444 IL31RA Interleukin 31 receptor A
Transient receptor potential cation channel, subfamily
chr7:142630534 TRPV5
V5
chr7:149473614 SSPO SCO-spondin homolog
chr7:47851623 PKD1L1 Polycystic kidney disease 1 like 1
chr3:111921116 SLC9A10 Solute carrier family 9, member 10
chr3:111962851 SLC9A10 Solute carrier family 9, member 10
chr3:111996554 SLC9A10 Solute carrier family 9, member 10
chr4:126237567 FAT4 FAT tumor suppressor homolog 4

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

19. Multiple Sclerosis
Treatment of Multiple Sclerosis
Harrison’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

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

21. 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.

22. 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.

23. MS as a genetic disease. The agenda
The convergence of -omics with 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.

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