Associations between SNPs in candidate immune-relevant genes and rubella antibody levels: a multigenic assessment
1 Mayo Clinic Division of Biomedical Statistics and Informatics, Harwick 7 200 1st Street SW Rochester, MN 55905 USA
2 Mayo Clinic Division of Biomedical Statistics and Informatics, Charlton 6 200 1st Street SW Rochester, MN 55905 USA
3 Mayo Clinic Vaccine Research Group Program in Translational Immunovirology and Biodefense 200 1st Street SW Rochester, MN 55905 USA
BMC Immunology 2010, 11:48 doi:10.1186/1471-2172-11-48Published: 5 October 2010
The mechanisms of immune response are structured within a highly complex regulatory system. Genetic associations with variation in the immune response to rubella vaccine have typically been assessed one locus at a time. We simultaneously assessed the associations between 726 SNPs tagging 84 candidate immune response genes and rubella-specific antibody levels. Blood samples were obtained from 714 school-aged children who had received two doses of MMR vaccine. Associations between rubella-specific antibody levels and 726 candidate tagSNPs were assessed both one SNP at a time and in a variety of multigenic analyses.
Single-SNP assessments identified 4 SNPs that appeared to be univariately associated with rubella antibody levels: rs2844482 (p = 0.0002) and rs2857708 (p = 0.001) in the 5'UTR of the LTA gene, rs7801617 in the 5'UTR of the IL6 gene (p = 0.0005), and rs4787947 in the 5'UTR of the IL4R gene (p = 0.002). While there was not significant evidence in favor of epistatic genetic associations among the candidate SNPs, multigenic analyses identified 29 SNPs significantly associated with rubella antibody levels when selected as a group (p = 0.017). This collection of SNPs included not only those that were significant univariately, but others that would not have been identified if only considered in isolation from the other SNPs.
For the first time, multigenic assessment of associations between candidate SNPs and rubella antibody levels identified a broad number of genetic associations that would not have been deemed important univariately. It is important to consider approaches like those applied here in order to better understand the full genetic complexity of response to vaccination.