# Presentation: 449465

## Genetic Risk Factors for Smallpox Vaccine Associated Myopericarditis?

**Presentation Outline**
- Study Goals and Team
- Background, Rationale, Hypotheses, Design
- Preliminary Genome-wide Association Findings and Forecast

## Study Goals

- Identify genetic variation(s) that confers risk for the development of myopericarditis following smallpox vaccine, the most common serious adverse event identified in the US since smallpox vaccination was resumed in Dec 2002
- Determine the biological plausibility of these associations by assessment of their functional consequences

## Study Team

- DoD Vaccine Health Care Centers
- Walter Reed - Brooke Army – Ft.Bragg-Womack
- Renata Engler, Michael Nelson and colleagues
- _Clinical Training and Clinical Data Coordination_
- KPNC Vaccine Center
- Steve Black, Joanie Johnson, Robert Davis

- Project Coordination - Chris Wilson, Mercedes Pérez-Melgosa
- Data Management/Information Technology - Jeffrey Furlong
- Genotyping - Debbie Nickerson, Josh Smith
- HLA – Richard Kaslow and Jianming Tang, UAB
- Association Analysis - Chris Carlson, Gail Jarvik
- DNase HS Site Mapping – John Stammatoyanopoulos, Michael Dorschner
- Vaccinia Epitopes Presented by HLA Risk Allele(s) – David Koelle

**Study Team**

## Mechanistic Hypothesis

- Based on the findings that clinically overt smallpox vaccine-associated myopericarditis is 1) characterized by a lymphocytic inflammatory infiltrate with a CD4 T cell predominance, 2) the absence of vaccinia virus by PCR/culture in cardiac tissue, 3) and at the time of diagnosis the inoculation site is healing and blood is negative for vaccinia by PCR/culture
- We hypothesize that this disorder is caused by CD4 T cell-dependent self injury triggered by vaccinia

## Model of Vaccinia-Induced Myocarditis(adapted from Eriksson et al, MacLellan et al Nat Med Dec 2003)

## Genetic Hypothesis

- Based on the finding that clinically overt smallpox vaccine-associated myopericarditis is rare (~1:5-10,000) and predominantly affects individuals of European ancestry (RR3.4, p=0.001), we hypothesize that
- The risk allele(s) is of relatively recent, European origin
- One or two alleles/extended haplotypes, are associated with ≥80% of the attributable risk

## Study Design

- Primary cohort: 48 cases and 144 unaffected controls (matched for race, gender, primary vs. secondary vaccination)
- >80% power to detect allelic/haplotype odds ratio >2.9

##     Genotyping

- Candidate gene approach:** ****	****	****	****	****	**Number of biologically plausible genes is large (>200)
*A priori* list of 17 high priority candidate genes: *PDCD1, RUNX1, FOXP3, CTLA4, TGFB1, TGFBR1, TGF-****RII, TGFBR2, IL2, IL2RA,* *IL2RB, HAVCR1, HAVCR2, IL10, IL10RA*, *IL10RB, CCR5, CCR2,* HLA
**However, should/must we be limited to ‘looking under the lamppost’?**

**    ****Genotyping**
**	**

##     Genotyping

- Foundation for whole genome studies provided by dbSNP and HapMap Projects
- More than 10x106 SNPs have been identified in the human genome and 4x106 have been typed in reference human populations; copy number variations (CNVs) have also been shown to account for ~15% of human genetic variation
- High throughput, high quality platforms are available to interrogate SNPs in an unbiased, genome-wide manner
- We have chosen to use Illumina platform to interrogate 550K SNPs (~1 SNP every 500bp) in cases vs. controls, also providing an initial screen for CNVs

**    ****Genotyping**
**	**

**Modified from C Carlson**

## Preliminary Analysis

- 	Samples from 24 cases and 22 controls using 317K Illumina chips performed in July 2006

**Modified from C Carlson**

## Analytic Assumptions

- Adverse reaction: ~1 in 10,000
- Assume 100% penetrance
- Dominant: 0.005% allele frequency
- Recessive: 1% allele frequency
- There are 317k common (i.e., minor allele frequency/         MAF >5%) European SNPs on this Illumina chip
- Since the causal allele is rare, it is probably not on the chip
- BUT, the causal allele (i.e., SNP) will be in complete (D’=1) but imperfect (r2<1) linkage disequilibrium (LD) with SNPs that are on this chip
- The haplotype(s) containing the risk conferring SNP (and the other SNPs linked to it) is of relatively recent origin and consequently spans hundreds of kilobases

**Modified from C Carlson**

## Predictions

- Dominant Risk Model
- Cluster of SNPs with significant MAF Cases vs. Controls at risk loci
- HWE in Controls
- Excess Heterozygosity in Cases

- Recessive Risk Model
- Cluster of SNPs with significant MAF Cases vs. Controls at risk loci
- HWE in Controls
- Excess Homozygosity in Cases or Cases plus Controls

**Modified from C Carlson**

- *HWE = Hardy Weinberg Equilibrium: Allele frequencies in a general population will be found in "genetic equilibrium" - the basic principle of population genetics.

##    Summary

- Four loci preliminarily linked on recessive analysis – including IL2RA direct hit and IL2 near miss
- One locus preliminary signal on dominant analysis - HLA
*A priori* high priority candidate list of 17 genes **             ***PDCD1, RUNX1, FOXP3, CTLA4, TGFB1, TGFBR1,TGF-****RII, TGFBR2, **IL2**, **IL2RA**,* *IL2RB, HAVCR1, HAVCR2, IL10, IL10RA*, *IL10RB, CCR5, CCR2,* HLA** **
**These associations are forecast to be significant in final sample size, if current trends continue**

**   ****Summary**
**Preliminary Genotyping Hits**
**	**

## Plans

- Enrollment sufficient to provide >80% power to detect allelic/haplotype odds ratio >2.9 expected by this summer  complete genotyping  perform adequately powered analysis
- Enroll/identify validation cohort
- Seek to identify causal SNP/CNV and causal mechanism
- HLA – Identification of vaccinia epitopes, determine if any are capable of molecular mimicry of heart antigens
- Other loci
- DNase array profiling to identify regulatory elements that govern gene expression in immune cell subsets in a comprehensive, unbiased, genomewide manner and map SNPs to these regulatory elements
- Other approaches based on gene and nature of apparently causal SNP