The emerging picture of host genetic control of susceptibility and outcome in meningococcal disease...

The emerging picture of host genetic control of meningococcal disease: Insights from Genome wide association studies (GWAS)

Michael LevinImperial college LondonMRF Conference November 2013

© Imperial College London

WHY Do some children develop Meningococcal Infection or other forms of meningitis and not others ?

Is it an accident or in the genes?

AIMQuantify the host genetic component of meningococcal disease susceptibility

Method

Calculate the co-efficient of familial clustering: R

Epidemiology and Infection June 2003


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All data > 1 w eek > 1 month > 3 months > 6 months > 9 months > 12 months

Duration between MD onsets in case/affected sibling pairs

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Duration between case/sibling MD onsets

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Why undertake genetic studies of Infectious diseases?• Identify fundamental pathways causing

susceptibility • Identify those susceptible• Identify key components of

pathophysiology• Explain individual differences in clinical

presentation or outcome• Identify targets for therapy


Sites for genetic influence

Nasopharyngeal colonisation

Invasion of bloodstream

Survival in blood

Meningitis Septic Shock

Asymptomatic Bacteraemia Purpura

Fulminans


Susceptibility versus severity genes

Susceptibility

Control colonisation invasion

Survival in blood

Susceptibility genes present with greater frequency in cases vs controls

Severity

Determine inflammatory response

Extent of coagulopathy

Organ failure

Severity genes may have same frequency in cases and controls preferentially in severe/fatal cases


How to identify these genes?

• Candidate gene approach– Biology-based, mice & men– Limited to what you know

• Linkage analysis– Small family studies– Not population based

• Genome-wide association– Can detect ‘novel’ genes– Use SNP arrays

• Next-gen sequencing– Whole exome– Whole genome?

The St Mary's / Imperial College approach 1995+

Detailed clinical phenotype

Immunology, biochemistry, microbiology, haematology

Candidate genes based on pathophysiology

Case control association study

Confirm in second Family study Othercohort cohorts

Protein expression biological studies

Identify gene defects


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Lots of Candidate gene Studies


Problems with candidate gene genetic association studies

• Innumerable candidates?

• Only tests what is known

• Many published studies methodologically flawed

• Few replication studies

• Inadequate correction for multiple hypothesis testing, genetic admixture

•Now possible to type thousands to millions of SNPS across entire genome in each individual

•Cost of genotyping decreasing

The feasibility of Genome-Wide Association Studies


Requires Large patient and control cohorts

High throughput technology and Bioinformatics expertise

HapMapA program to chart genetic variation

within the human genome

• Single neucleotide polymorphisms (SNPs)scattered across genome

10 million sequence variants in each individual

Exponential increase in Validated GWAS findings

Genome wide study of meningococcal disease

• An ESPID collaboration• MRF support for establishment

of St Mary’s/ UK Cohort 1995-2009 and on-going analysis

Meningococcal GWAS

Mike Levin

Victoria Wright

David Inwald

Simon Nadel

Helen Betts

Lachlan Coin

Taco Kuijpers

Willemijn Breunis

Enitan Carrol

Jan Hazelzet

Marieke Emonts

Ronald de Groot

Peter Hermans

Werner Zenz

Alexander Binder

Sonia DavilaMartin HibberdChui Chin Lim

DNA QC:Chang Hua WongDennis TanJie Wen Tay

Computing:Jieming Chen


University of Santiago de Compostela (Spain)Federico Martinon-Torres

Antonio Salas

Discovery study

Replication study

Identification of Key Pathways

UK Caucasian MD cases

Validation in European cohorts (Austria, Holland, Spain ) using Illumina SQNM

Genome-Wide Association Study using Illumina 610 Hap-quad chip

UK Caucasian controls

Bioinformatic Analysis

Top ‘hits’ & selection of candidate genes

Bioinformatic Analysis

Functional Studies Gene Expression/Proteomics

Fine-mapping using Illumina ISelect


Study design of the MRF/ ESPID GWAS

doi:10.1038/ng.640doi:10.1038/ng.640

2010 Sep;42(9):772-6.

UK Meningococcal GWAS

-log

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-log (expected P-values)

How do we detect significance ?

Manhattan plot of significant SNPs in meningococcal disease patients

Martinón-Torres, ESPID 2012Martinón-Torres, ESPID 2012

Factor H & Factor H related protein region on Chr.1

Replication: Austrian/Dutch & Spanish

cohorts

Davila Nature genetics 2010

Factor H/ FH related protein region

• Multiple SNPs spanning FH- FHR protein region

• Highly significant in all 3 cohorts

• Definitive identification of FH and FHR as influencing susceptibility

Inhibits C3b

Reduces killing

Fh on endothelial cells bind meningococci

Complement Factor H binds to Meningococcal protein (FhbP)

What is the role of FH related proteins?

• Sequence homology to FH• Individual variation in ratio of FH/FHR

proteins 1-4 ?• Competition between FH and FHR for binding

to Meningococcal FHBP ?• Further work to define mechanisms at a

functional and protein level

Further exploration of meningococcal genenticsEU Childhood Life-threatening Infectious Disease Study

Staged programme to identify genetic basis of Meningococcal disease

UK GWAS

Spanish GWAS Central Europe GWAS

Fine mapping & sequencing of candidate

regions

Genotype/RNA/Protein studies [Functional studies]

Evaluation of variants in animal models

Vaccine GWAS

Predictive biomarkers of susceptibility & severity & clinical translation

Identify top Hits

Cross-validation between European cohorts

Meta-analysis of combined UK, Spanish, CE European GWAS

Severity analysis / Pathway analysis

Replicate in 2nd vaccine cohort

Genomic analysis of Extreme Phenotype cohorts

Validation in prospective MD & other bacterial infection cohorts [EU & Africa]

Prospective recruitment of MD &

other bacterial infection

Meningococcal disease and age-related macular degeneration share genetic susceptibility loci


Meningococcal disease and age-related macular degeneration share genetic susceptibility loci

ESIGEM network and EUCLIDS consortium

• ABCA4 encodes a protein expressed in retinal photoreceptors.

• Mutations in ABCA4 are associated with degenerative macular diseases.

ABCA4 top hit after CFH region

http://ghr.nlm.nih.gov/dynamicImages/chromomap/ABCA4.jpeg

AMD Leading cause of blindness

in western societies

MDLeading bacterial threat

In children


CFH

ABCA4

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Complement mediated

pathogenesis

EUCLIDS

• Large sample size enables meta analysis of the European cohort to identify genes controlling severity and outcome

• Pathway based analysis

Multiple sites for genetic regulation of Inflammatory response to a

pathogen


Pathway Based analysis of Genome wide studies

• Can the combined effect of mutiple variants in a biological pathway be used for analysis of GWAS and gene expression data ?

Test for pathway association

MAX x=(0,1,2) x=(0,1,1) x=(0,0,1) x=(0,1,0)CA = max (CA| , CA| , CA| , CA| )

aa aA AA Total

Cases r0 r1 r2 R

Controls s0 s1 s2 S

Total n0 n1 n2 N

Contigency table of case-control genotype SNP data

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Dominant 0 1 1

Recessive 0 0 1

Heterozygote 0 1 0

4 genetic models1

1. Select pathway

• Create a gene list• Map all SNPs to genes within 10K

2. Max single-SNP trend test statistic of the 4 genetic models (for every SNP in the pathway)

Max statistic

0 : , 0,1, 2i iH p q i Null hypothesis

1. Sasieni, Biometrics, 19972. Freidlin et al, Hum Hered, 2002

Genes with consistent association

Variable selection and cross validation identifies

Visualization of genomic riskIndividual genomic fingerprint Type 1

diabetes1

0.5

0 Predicted probability of disease

Real disease status

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SEVERITY AND PATHWAY ANALYSIS OF EUCLIDS

MENINGOCOCCAL COHORTS

• UK GWAS 475 cases/ 4703 controls• SPANISH GWAS 417 cases/882 controls• AUSTRIAN/DUTCH GWAS 344 cases/2557 controls

End Points : Death; amputations :skin grafting; mechanical ventilation;severity scores

Intermediate phenotypes

Death associated with second messenger signaling

Second messengersignaling

Death and severity controlled by second messenger signalling

The second messenger signalling systems are used by all cells to switch on and off multiple processes

Genetic variation in the second messanger on/off switch may control intensity of inflammation in MD

Processes controlled by SMSEnvironment

Amputations and skin loss

Severity and pathway analysis of EUCLIDS GWAS is revealing complex control of phenotypes by genes within each individual

• Further validation of initial findings planned in new EUCLIDS cohort

• New Pathways as therapeutic targets

AcknowledgementsMD patients and families

Control familiesVictoria Wright

David Inwald

Simon Nadel

Helen Betts

Lachlan Coin

Harieta Eleftherohorinou

Taco Kuijpers

Willemijn Breunis

Enitan Carrol

Jan Hazelzet

Marieke Emonts

Ronald de Groot

Peter Hermans

Werner Zenz

Alexander Binder

Sonia DavilaMartin HibberdChui Chin Lim

DNA QC:Chang Hua WongDennis TanJie Wen Tay

Genotyping:Wee Yang MeahKhai Koon Heng

Sigeeta RajaramComputing:Kar Seng SimJieming Chen


University of Santiago de Compostela (Spain)Federico Martinon-TorresAntonio Salas

Thank You!

The emerging picture of host genetic control of susceptibility and outcome in meningococcal disease...

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