HLA alleles associated with the adaptive immune response to smallpox vaccine: a replication study

Ovsyannikova, Inna G.; Pankratz, V. Shane; Salk, Hannah M.; Kennedy, Richard B.

doi:10.1007/s00439-014-1449-x

Cited by 27 publications

(34 citation statements)

References 41 publications

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“…The phenotype of interest is vaccinia virus-induced IFN-a production detected in peripheral blood mononuclear cells (PBMCs) from first-time recipients of smallpox vaccine. More details about the study cohorts can be found in Ovsyannikova et al (2011Ovsyannikova et al ( , 2012Ovsyannikova et al ( , 2014 and Kennedy et al (2012) gender, time from immunization to blood draw, vaccination date, immune assay batch, and the first principal component to adjust for potential population stratification. For the San Diego cohort, the phenotype was regressed on the following covariates: date of IFN-a assay, date of blood draw, shipping temperature of the sample, site the sample was drawn from, and the second principal component (the first is not included because it is not significant).…”

Section: Application Of Methodsmentioning

confidence: 99%

Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics

et al. 2015

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Two recently developed fine-mapping methods, CAVIAR and PAINTOR, demonstrate better performance over other finemapping methods. They also have the advantage of using only the marginal test statistics and the correlation among SNPs. Both methods leverage the fact that the marginal test statistics asymptotically follow a multivariate normal distribution and are likelihood based. However, their relationship with Bayesian fine mapping, such as BIMBAM, is not clear. In this study, we first show that CAVIAR and BIMBAM are actually approximately equivalent to each other. This leads to a fine-mapping method using marginal test statistics in the Bayesian framework, which we call CAVIAR Bayes factor (CAVIARBF). Another advantage of the Bayesian framework is that it can answer both association and fine-mapping questions. We also used simulations to compare CAVIARBF with other methods under different numbers of causal variants. The results showed that both CAVIARBF and BIMBAM have better performance than PAINTOR and other methods. Compared to BIMBAM, CAVIARBF has the advantage of using only marginal test statistics and takes about one-quarter to onefifth of the running time. We applied different methods on two independent cohorts of the same phenotype. Results showed that CAVIARBF, BIMBAM, and PAINTOR selected the same top 3 SNPs; however, CAVIARBF and BIMBAM had better consistency in selecting the top 10 ranked SNPs between the two cohorts. Software is available at https://bitbucket.org/Wenan/caviarbf. KEYWORDS Bayesian fine mapping; marginal test statistics; causal variants U NTIL recently, there have been .2000 genome-wide association studies (GWAS) published with different traits or disease status (Hindorff et al. 2014). Most of them reported only regions of association, represented by SNPs with the lowest P-values in each region. Only a few provide further information of likely underlying causal variants. A noted exception is refinement based on Bayesian methods (Maller et al. 2012). Fine mapping the causal variants from the verified association regions is an important step toward understanding the complex biological mechanisms linking the genetic code to various traits or phenotypes.Fine-mapping methods can be roughly divided into two groups. The first group was developed before the availability of high-density genotype data. These fine-mapping methods assume the causal variants are not genotyped in the data and aim to identify a region as close as possible to the causal variants (Morris et al. 2002; Durrant et al. 2004;Liang and Chiu 2005;Zollner and Pritchard 2005;Minichiello and Durbin 2006;Waldron et al. 2006). Because the causal variants are not observed in the data, these methods usually rely on various strong assumptions to model the relationship of the causal and the observed variants. Examples include models based on the coalescent theory (Morris et al. 2002;Zollner and Pritchard 2005;Minichiello and Durbin 2006) or statistical assumptions about the patterns of linkage disequilibrium (LD) (Liang and ...

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Section: Application Of Methodsmentioning

confidence: 99%

Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics

et al. 2015

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“…Increasing evidence indicating that specific risk factors exist have been provided in the literature, including the role of age, sex, and SNPs [3,5,16,39,44,45,47].…”

Section: Discussionmentioning

confidence: 98%

“…A number of studies have been reported on this topic, including significant evidence about the role of several SNPs in cytokines production following vaccinations [44][45][46][47][48][49][50].…”

Section: The Molecular Mechanismmentioning

confidence: 98%

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Vaccine–Drug Interactions: Cytokines, Cytochromes, and Molecular Mechanisms

et al. 2015

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Vaccinations are recommended throughout life to reduce the risk of vaccine-preventable diseases and their sequelae. Vaccines are often administered in patients with chronic diseases who are likely to be treated with several drugs. A growing number of clinical observations have indicated the possibility of interactions between vaccines and drugs, leading to changes in drug metabolism after vaccination. These interactions represent a significant concern because of the increasing use of vaccines in older patients who are likely to be treated with several drugs. Because of the possible implications of adverse reactions in terms of public health, several studies were performed to verify the risk posed by these interactions and to clarify the biologic mechanisms that drive these events. Of the several mechanisms proposed to be at the basis of vaccine-drug interactions, the most convincing evidence suggests a role of inflammatory cytokines on the regulation of specific cytochrome P450 enzymes in the liver. Differences in the cytochrome P450 enzymes involved in the metabolism of these drugs could explain these contrasting results and provide important insights to fully understand the clinical importance of these events. Further studies are required to verify whether vaccine-drug interactions may occur in other clinical settings, especially the ones for which patients are required to be vaccinated against specific diseases.

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“…Two independent cohorts of study subjects, previously described in detail [10, 11], were used in this study. In total, 1,796 healthy individuals (with proven measles vaccine-induced immunity), ranging in age from 18 to 41 years, from two cohorts (San Diego cohort, n=844; US cohort, n=952) were included in this study (Table 1).…”

Section: Methodsmentioning

confidence: 99%

Immunoglobulin GM and KM genes and measles vaccine-induced humoral immunity

Ovsyannikova

Larrabee

Schaid

2017

Vaccine

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Identifying genetic polymorphisms that explain variations in humoral immunity to live measles virus vaccine is of great interest. Immunoglobulin GM (heavy chain) and KM (light chain) allotypes are genetic markers known to be associated with susceptibility to several infectious diseases. We assessed associations between GM and KM genotypes and measles vaccine humoral immunity (neutralizing antibody titers) in a combined cohort (n=1,796) of racially diverse healthy individuals (age 18–41 years). We did not discover any significant associations between GM and/or KM genotypes and measles vaccine-induced neutralizing antibody titers. African-American subjects had higher neutralizing antibody titers than Caucasians (1,260 mIU/mL vs. 740 mIU/mL, p=7.10 × 10−13), and those titers remained statistically significant (p=1.68 × 10−09) after adjusting for age at enrollment and time since last vaccination. There were no statistically significant sex-specific differences in measles-induced neutralizing antibody titers in our study (p=0.375). Our data indicate a surprising lack of evidence for an association between GM and KM genotypes and measles-specific neutralizing antibody titers, despite the importance of these immune response genes.

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HLA alleles associated with the adaptive immune response to smallpox vaccine: a replication study

Cited by 27 publications

References 41 publications

Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics

Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics

Vaccine–Drug Interactions: Cytokines, Cytochromes, and Molecular Mechanisms

Immunoglobulin GM and KM genes and measles vaccine-induced humoral immunity

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