Aspectos genòmicos y factores de protecctiònAspectos genòmicos y factores de protecctiònAmalio Telenti, University of Lausanne

The next frontierThe next frontier

#1 Exploiting differences among pathogens#1 Exploiting differences among pathogens

#2 Exploiting extreme phenotypes#2 Exploiting extreme phenotypes

#3 Exploiting technological breakthroughs#3 Exploiting technological breakthroughs

#1 - Exploiting differences amongpathogens

• A 32 year-old person is found at the time of a blood donation to be HIV+/HCV+.

• His HIV viremia is 4.9 log copies/ml, CD4 T cells are 168 cell/ul.

• His HCV viremia is undetectable, liver tests are normal.

Genome analyses: How do we do it?

• DNA from a large number of individuals

• Large scale genotyping of common human variation (500’000 – 1 moi polymorphisms).

• Association analysis with correction for the large number of tests (significative p-values should be <10-7 to 10-8

Homozygous 1

Heterozygous

Homozygous 2

Genome-wide genotypingGenome-wide genotyping

500.000 to 1.000.000 SNPs/individual

Chromosomal location of locus of susceptibility Chromosomal location of locus of susceptibility to HIV-1 and to Hepatitis Cto HIV-1 and to Hepatitis C

Fellay et al Science 2007Fellay et al Science 2007Rauch el al. SubmittedRauch el al. Submitted

HIV Chr. 6HIV Chr. 6

HCV Chr. 19HCV Chr. 19

N=478 HIV+N=478 HIV+

N=1350 HepC+N=1350 HepC+

rs2395029 (HLA-B*5701)rs9264942 (HLA-C -35)rs9261174 (ZNRD1)rs333 (CCR5Δ32)

Years

Su

rviv

al/P

rog

ress

ion

Fellay et al,

Genetic score and progressionGenetic score and progression

Chromosomal location of locus of susceptibility Chromosomal location of locus of susceptibility to HIV-1 and to Hepatitis Cto HIV-1 and to Hepatitis C

Fellay et al Science 2007Fellay et al Science 2007Rauch el al. SubmittedRauch el al. Submitted

HIV Chr. 6HIV Chr. 6

HCV Chr. 19HCV Chr. 19

N=478 HIV+N=478 HIV+

N=1350 HepC+N=1350 HepC+

HCV - Genetic determinants of spontaneous HCV - Genetic determinants of spontaneous clearance and treatment successclearance and treatment success

HCV - Viral and genetic determinants HCV - Viral and genetic determinants of treatment successof treatment success

GWAS Results

• We have reached experimental power conditions to identify most common human (Caucasian) variation influencing susceptibility to HIV-1

• We can know explain 22% of population variance by genetics, population effects, gender and age.

• Clear and profoundly different signals for various pathogens (n=2).

#2 - Exploiting extreme phenotypes

HIV-HIV- HIV+HIV+

A rapid progressor

Rapid progression – a genetic extreme Rapid progression – a genetic extreme

ECLTNP

CNP P RP

0.0

0.5

1.0

CCR2 V64ICCR5 32

HLA-C

ZNRD1HLA-A+

HLA-B+

CCR5_HHE/HHE

HLA-B-

CCR5_H+/H+

CCR5_P1/P1

Alle

lic f

req

uen

cy o

r p

rop

ort

ion

Integrating host and viral parametersIntegrating host and viral parameters

Casado et al.

« Sooty-like » patterns of evolution

CD4 evolution of Rapid Progressors (n=73) CD4 evolution of Rapid Progressors (n=73) during 3 years after seroconversion during 3 years after seroconversion

Red: associated with an AIDS event/death

<350 CD4 T cells

0 365 730 10950

100

200

300

400

500

600

700

800

900

1000

Days post SC

CD

4 T

cel

l co

un

t

A genomic, tanscriptomic and immunogenetic A genomic, tanscriptomic and immunogenetic study of rapid progressionstudy of rapid progression

CD4 T cell analysis

Interferon-Interferon-stimulated genesstimulated genes

CD4 T cell analysis

Interferon stimulated genes Rapid Interferon stimulated genes Rapid progressors versus Sooty-like profilesprogressors versus Sooty-like profiles

CD4 T cell analysis

More expressed More expressed in Sooty-likein Sooty-like

More expressed More expressed in Rapid in Rapid progressorsprogressors

Gene expression changes in African green monkeys (natural host model) and Asian pigtailedmacaques (pathogenic model) between day 10 and day 45 post infection.

AGM PM

Lederer et al. PLoS Pathogens 2009

Interferon-Interferon-stimulated genesstimulated genes

CD4 T cell analysis

T cell receptor T cell receptor signallingsignalling

T cell receptor T cell receptor signallingsignalling

Kaufmann DE, Walker BD. PD-1 and CTLA-4 inhibitory cosignaling pathways in HIV infection and the potential for therapeutic intervention. J Immunol. 2009

Transcriptome Results

• The analysis of extreme phenotypes (beyond elite controllers) remains of major interest.

• New profiles, such as the rare “sooty-like” can be very informative and directly link to some of the non-pathogenic primate models.

• However….what to do with the long lists of candidate genes??

#3 - Exploiting technological breakthroughs

• A severe hemophilia patient received multiple blood transfusions through the early 1980’ies.

• Today this patient remains HIV negative, while HCV positive

Characterization of high-risk HIV-1 seronegative Characterization of high-risk HIV-1 seronegative hemophiliacs. Salkowitz et al. hemophiliacs. Salkowitz et al.

Among hemophiliacs from the MACS who remained HIV-1 seronegative despite a high (94%) risk for acquisition of HIV-1 infection, 7/43 (16%) were homozygous for the 7/43 (16%) were homozygous for the protective CCR5 Delta32 polymorphismprotective CCR5 Delta32 polymorphism. Among the remainder, neither CCR5 density nor beta-chemokine production, nor in vitro susceptibility to infection with the HIV-1 isolate JR-FL could distinguish HRSN hemophiliacs from healthy controls.

Clin Immunol. 2001 Feb;98(2):200-11.

>5%1%<<<<<<1%

Severe ????? Mild

Primary immuno-deficiencies

?????????Common trait disease

Genetic frequency in a populationGenetic frequency in a population

Disease manifestation / riskDisease manifestation / risk

>5%1%<<<<<<1%

Severe ????? Mild

Primary immuno-deficiencies

Common trait disease

Genetic frequency in a populationGenetic frequency in a population

Disease manifestation / riskDisease manifestation / risk

>5%1%<<<<<<1%

Severe ????? Mild

Primary immuno-deficiencies

RARE AND RARE AND PRIVATE PRIVATE

MUTATIONSMUTATIONS

Common trait disease

Genetic frequency in a populationGenetic frequency in a population

Disease manifestation / riskDisease manifestation / risk

“…some 11,000 of Watson’s SNPs (15% novel) are predicted to change the amino-acid sequence — and so, perhaps, the function — of a protein.”

Whole Genome SequencingWhole Genome Sequencing

James WATSON

Where could be the Where could be the genes of interest?genes of interest?

Homo sapiens

Pan paniscus

Pan troglodytes verus

Pan troglodytes schweinfurthi

Pan troglodytes vellerosus

Gorilla gorilla

Pongo pygmaeus

hylobates lar

hylobates syndactylus

hylobates leucogenys

Mandrillus sphinx

Mandrillus leucophaeus

Cercocebus torquatus

Cercocebus atys

Macaca nemestrina

Macaca mulatta

Macaca arctoides

Cercopithecus aethiops

Cercopithecus albogularis

Cercopithecus solatus

Cercopithecus cephus

Cercopithecus lhoesti

Cercopithecus mona

Cercopithecus denti

Cercopithecus neglectus

Cercopithecus tantalus

Guereza colobus

Callithrix jacchus

Lemurs

Cercopithecus sabaeus

Cercopithecus niticans

SIV Human jumpSIV Simian jump?

HIV-1 group M

SIVcpz2

SIVcpz5

HIV-1 group N

SIVcpz1

SIVcpz4

HIV-1 group O

SIVcpzANT

SIVcpzTAN1

SIVmnd3

SIVmnd1

SIVdrll

SIVrcm2

SIVrcm1

SIVsm3

HIV-2 B

HIV-2 A

SIVstm

SIVsm4

SIVsm1

SIVsm2

SIVmne

SIVmac1

SIVmac3

SIVmac2

SIVagmSab

SIVagmTan

SIVagmGri

SIVagmVer1

SIVagmVer2

SIVdeb

SIVden

SIVsyk1

SIVsyk2

SIVmon

SIVmus

SIVgsn1

SIVgsn2

SIVmnd4

SIVhoest

SIVsun

SIVcol

100

100

100

100

100

97

100

100

100

100

100

100

100

92

100

100

100

84

85

100

100

92

100

100

100

95

79

46

100

100

100

100

100

86

100

100

96

97

100

Ortiz et al Mol Biol Evol 2009

siRNA/shRNA screens for genes needed for siRNA/shRNA screens for genes needed for HIV replication in human cellsHIV replication in human cells

Brass et al. Science 2008.Konig et al. Cell 2008.Zhou et al. Cell Host Microbe 2008Jeung et al. J Biol Chem 2009.

• >1000 gene candidates• Only 3 genes common to at least three studies.• 38 genes common to 2 or more studies.• No restriction factors identified

Nuclear poreNuclear pore

Mediator Mediator complexcomplex

NF-NF-kappa-Bkappa-B

Protein kinasesProtein kinases

Predicted interaction networks of genes identified as Predicted interaction networks of genes identified as HIV dependency factors in silencing screens and HIV dependency factors in silencing screens and

differentially expressed during HIV-1 infection.differentially expressed during HIV-1 infection.

ProteasomeProteasome

Putting it to work

LawLaw

EthicsEthics

MaterialsMaterials

EquipmentEquipment

AnalysisAnalysis

Haas

Transcriptomics ProteomicsImaging

Genotyping

Mathematics, statistics and computer sciences

"Scientists have learned to expect everything from mathematicians short of actual help"John HAMMERSLEY, Bull Inst Math Appl 10, 235, 1974

The role of the physician

• Identification of study phenotyes• Avoiding low-power, limited scope studies.• Bringing the best predictors to clinical use.

<Stronger in seroprevalent<Stronger in seroprevalent Stronger in seroconverters>Stronger in seroconverters>

VIRAL LOAD GENETICSVIRAL LOAD GENETICS- Effect estimates in - Effect estimates in Genome-wide studies:Genome-wide studies:

Recruiting seroprevalent versus seroconverter individuals

Final Conclusions

• The genetic basis of human susceptibility to HIV-1 susceptibility to infection includes common variants (probably known by now), and a undefined number of rare variants.

• Technological breakthroughs are not adequately supported by clinical cohorts.

Will I ever use this knowledge?

1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

HIV amplicorPCR

HBV vaccine

ErytrhopoeitinInsulineRecombinant technology

Rituximab

18 commercial MoAbs

First FDA approval

MoAB

Monoclonal Antibodies

Human genomics

University of LausanneA Ciuffi M. Rotger M. OrtizS. ColomboUniversity Hospital BernA. RauchGenomics Platf. GenevaP. Descombes

Ragon InstituteP. McLarenP. De BakkerB. Walker

Duke UniversityJ. FellayK. Dang D. Goldstein

Pasteur InstituteL. Quintana-Murci

Carlos IIIC. Lopez GalindezC. Casado

IrsiCaixaJ. DalmauJ. Martinez-Picado