Troy D. Querec

Yellow fever vaccine YF-17D activates multiple dendritic cell subsets via TLR2, 7, 8, and 9 to stimulate polyvalent immunity

The live attenuated yellow fever vaccine 17D (YF-17D) is one of the most effective vaccines available, with a 65-yr history of use in >400 million people globally. Despite this efficacy, there is presently no information about the immunological mechanisms by which YF-17D acts. Here, we present data that suggest that YF-17D activates multiple Toll-like receptors (TLRs) on dendritic cells (DCs) to elicit a broad spectrum of innate and adaptive immune responses. Specifically, YF-17D activates multiple DC subsets via TLRs 2, 7, 8, and 9 to elicit the proinflammatory cytokines interleukin (IL)-12p40, IL-6, and interferon-α. Interestingly, the resulting adaptive immune responses are characterized by a mixed T helper cell (Th)1/Th2 cytokine profile and antigen-specific CD8+ T cells. Furthermore, distinct TLRs appear to differentially control the Th1/Th2 balance; thus, whilst MyD88-deficient mice show a profound impairment of Th1 cytokines, TLR2-deficient mice show greatly enhanced Th1 and Tc1 responses to YF-17D. Together, these data enhance our understanding of the molecular mechanism of action of YF-17D, and highlight the potential of vaccination strategies that use combinations of different TLR ligands to stimulate polyvalent immune responses.

Case of Yellow Fever Vaccine-associated Viscerotropic Disease with Prolonged Viremia, Robust Adaptive Immune Responses, and Polymorphisms in CCR5 and RANTES Genes

BACKGROUND The live attenuated yellow fever vaccine 17D (YF-17D) is one of the most effective vaccines. Despite its excellent safety record, some cases of viscerotropic adverse events develop, which are sometimes fatal. The mechanisms underlying such events remain a mystery. Here, we present an analysis of the immunologic and genetic factors driving disease in a 64-year-old male who developed viscerotropic symptoms. METHODS We obtained clinical, serologic, virologic, immunologic and genetic data on this case patient. RESULTS Viral RNA was detected in the blood 33 days after vaccination, in contrast to the expected clearance of virus by day 7 after vaccination in healthy vaccinees. Vaccination induced robust antigen-specific T and B cell responses, which suggested that persistent virus was not due to adaptive immunity of suboptimal magnitude. The genes encoding OAS1, OAS2, TLR3, and DC-SIGN, which mediate antiviral innate immunity, were wild type. However, there were heterozygous genetic polymorphisms in chemokine receptor CCR5, and its ligand RANTES, which influence the migration of effector T cells and CD14+CD16bright monocytes to tissues. Consistent with this, there was a 200-fold increase in the number of CD14+CD16bright monocytes in the blood during viremia and even several months after virus clearance. CONCLUSION In this patient, viscerotropic disease was not due to the impaired magnitude of adaptive immunity but instead to anomalies in the innate immune system and a possible disruption of the CCR5-RANTES axis.

Fatal multiorgan failure due to yellow fever vaccine-associated viscerotropic disease

Abstract Yellow fever vaccine-associated viscerotropic disease (YEL-AVD) is a rare complication of yellow fever (YF) vaccination. A previously healthy 22-year-old female died following YF vaccination despite aggressive measures. Serial viral load titers, cytokine levels and host genetic factors were evaluated in an attempt to understand this unusual and lethal outcome. The patients high-titer vaccine viremia and possibly related minor genetic anomalies provide clues to exploring the etiology of YEL-AVD.

Understanding the role of innate immunity in the mechanism of action of the live attenuated Yellow Fever Vaccine 17D.

The live attenuated Yellow Fever Vaccine 17D [YF-17D] is one of the most effective vaccines available. During the 70 years since its development, the vaccine has been administered to more than 400 million people worldwide with minimal incident of severe side effects. Despite its efficacy, the immunological mechanisms that mediate its efficacy are poorly understood. Here we review the development of YF-17D in a historical context, and then present some emerging evidence which suggests that YF-17D activates multiple Toll-like receptors (TLRs) on dendritic cells (DCs) to elicit a broad spectrum of innate and adaptive immune responses. Interestingly, the resulting adaptive immune responses are characterized by a mixed T helper cell (Th)1/Th2 cytokine profile and antigenspecific CD8(+) T cells, and distinct TLRs appear to differentially control the Th1/Th2 balance. These data offer some new insights into the molecular mechanism of action of YF-17D, and highlight the potential of vaccination strategies that use combinations of different TLR ligands to stimulate polyvalent immune responses.

A Randomized, Double-Blind, Controlled Trial of the 17D Yellow Fever Virus Vaccine Given in Combination with Immune Globulin or Placebo: Comparative Viremia and Immunogenicity

We evaluated whether coadministration of the yellow fever (YF) virus vaccine with human immunoglobulin (Ig) that contained YF virus-neutralizing antibodies would reduce post-vaccination viremia without compromising immunogenicity and thus, potentially mitigate YF vaccine-associated adverse events. We randomized 80 participants to receive either YF vaccine and Ig or YF vaccine and saline placebo. Participants were followed for 91 days for safety and assessments of viremia and immunogenicity. There were no differences found between the two groups in the proportion of vaccinated participants who developed viremia, seroconversion, cluster of differentiation (CD)-8(+) and CD4(+) T-cell responses, and cytokine responses. These results argue against one putative explanation for the increased reporting of YF vaccine side effects in recent years (i.e., a change in travel clinic practice after 1996 when hepatitis A prophylaxis with vaccine replaced routine use of pre-travel Ig, thus potentially removing an incidental YF vaccine-attenuating effect of anti-YF virus antibodies present in Ig).

Development and evaluation of multiplexed immunoassay for detection of antibodies to HPV vaccine types

Reliable antibody based-assays are needed to evaluate the immunogenicity of current vaccines, impact of altered dosing schemes or of new vaccine formulations. An ideal assay platform would allow multiplex type-specific detection with minimal sample requirement. We used the Meso Scale Discovery (MSD) electrochemiluminescence based detection platform to develop a multiplex direct virus-like particle (VLP) ELISA to detect antibodies to HPV 6, 11, 16, and 18 with a protocol developed for detection using the SI 6000 imager (M4ELISA). MSD prepared the plates in the 7-spot/well format, using the purified VLPs (4 spots) and PBS+BSA pH7.4 (3 blank spots). Three-point titrations and the parallel line method were used to calculate antibody levels. Dynamic range, precision, and stability of pre-printed plates were determined using a panel of previously characterized sera. Cut-off values using childrens sera were established using 99% RLU limits based on the 4-parameter Johnson Su best fit curve. Results of the M4ELISA were compared to competitive Luminex Immunoassay (cLIA) on n = 4454 sera from a predominantly unvaccinated cohort. Using a VLP coating concentration of 80 μg/ml with BSA provided the most robust RLU signal for all types. The dynamic range of the assay was about 1000 fold, with assay variability under 25% for each of the four vaccine types. Long-term stability of the plates extended to about 7 months from the time plates was received in the laboratory after printing. There was moderate agreement (κ = 0.38-0.54) between M4ELISA and cLIA, with antibody detection for each of the 4 types more frequent with M4ELISA. Quantitative analysis however showed a good correlation between concordant samples by both assays (ρ ≥ 0.6). The MSD platform shows promise for simultaneous quantitation of the antibody responses to four HPV vaccine types in a high-throughput manner.

Randomization modeling to ascertain clustering patterns of human papillomavirus types detected in cervicovaginal samples in the United States.

Detection of multiple human papillomavirus (HPV) types in the genital tract is common. Associations among HPV types may impact HPV vaccination modeling and type replacement. The objectives were to determine the distribution of concurrent HPV type infections in cervicovaginal samples and examine type-specific associations. We analyzed HPV genotyping results from 32,245 cervicovaginal specimens collected from women aged 11 to 83 years in the United States from 2001 through 2011. Statistical power was enhanced by combining 6 separate studies. Expected concurrent infection frequencies from a series of permutation models, each with increasing fidelity to the real data, were compared with the observed data. Statistics were computed based on the distributional properties of the randomized data. Concurrent detection occurred more than expected with 0 or ≥3 HPV types and less than expected with 1 and 2 types. Some women bear a disproportionate burden of the HPV type prevalence. Type associations were observed that exceeded multiple hypothesis corrected significance. Multiple HPV types were detected more frequently than expected by chance and associations among particular HPV types were detected. However vaccine-targeted types were not specifically affected, supporting the expectation that current bivalent/quadrivalent HPV vaccination will not result in type replacement with other high-risk types.

Machine Learning for Predicting Vaccine Immunogenicity

The ability to predict how different individuals will respond to vaccination and to understand what best protects individuals from infection greatly facilitates developing next-generation vaccines. It facilitates both the rapid design and evaluation of new and emerging vaccines and identifies individuals unlikely to be protected by vaccine. We describe a general-purpose machine-learning framework, DAMIP, for discovering gene signatures that can predict vaccine immunity and efficacy. DAMIP is a multiple-group, concurrent classifier that offers unique features not present in other models: a nonlinear data transformation to manage the curse of dimensionality and noise; a reserved-judgment region that handles fuzzy entities; and constraints on the allowed percentage of misclassifications.Using DAMIP, implemented results for yellow fever demonstrated that, for the first time, a vaccine’s ability to immunize a patient could be successfully predicted (with accuracy of greater than 90 percent) within one week after vaccination. A gene identified by DAMIP, EIF2AK4, decrypted a seven-decade-old mystery of vaccination. Results for flu vaccine demonstrated DAMIP’s applicability to both live-attenuated and inactivated vaccines. Results in a malaria study enabled targeted delivery to individual patients.Our project’s methods and findings permit highlighting and probabilistically prioritizing hypothesis design to enhance biological discovery. Moreover, they guide the rapid development of better vaccines to fight emerging infections, and improve monitoring for poor responses in the elderly, infants, or others with weakened immune systems. In addition, the project’s work should help with universal flu-vaccine design.

Controlling for population variances in health and exposure risk using randomized matrix based mathematical modeling

In a previous work, we analyzed the co-occurrence of HPV types in 6 large studies with cervicovaginal samples, representing >32,000 women, to ascertain if associations exist among HPV types and to guide policies on HPV vaccination and vaccine development. The data showed that more women either were uninfected by HPV or had multiple concurrent infections than could be explained by independent assortment, which could result from variance in health and exposure risk factors. Modeling exposure and immune competence proved unstable, so we used a randomized matrix based approach that obviated the need to understand the underlying risk factors. We randomized our source data while preserving increasing levels of fidelity to the original data structures to discover the type associations for HPV infection. We offer that this could be a generally useful technique for studying any type of association in biosocial science, e.g. between demographic, socioeconomic, or other variables.