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Browsing by Author "Wiegand, Ryan E."
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Item Innate immune activation restricts priming and protective efficacy of the radiation-attenuated PfSPZ malaria vaccine(American Society for Clinical Investigation, 2024-04-30) Senkpeil, Leetah; Bhardwaj, Jyoti; Little, Morgan R.; Holla, Prasida; Upadhye, Aditi; Fusco, Elizabeth M.; Swanson, Phillip A., II; Wiegand, Ryan E.; Macklin, Michael D.; Bi, Kevin; Flynn, Barbara J.; Yamamoto, Ayako; Gaskin, Erik L.; Sather, D. Noah; Oblak, Adrian L.; Simpson, Edward; Gao, Hongyu; Haining, W. Nicholas; Yates, Kathleen B.; Liu, Xiaowen; Murshedkar, Tooba; Richie, Thomas L.; Sim, B. Kim Lee; Otieno, Kephas; Kariuki, Simon; Xuei, Xiaoling; Liu, Yunlong; Polidoro, Rafael B.; Hoffman, Stephen L.; Oneko, Martina; Steinhardt, Laura C.; Schmidt, Nathan W.; Seder, Robert A.; Tran, Tuan M.; Medicine, School of MedicineA systems analysis was conducted to determine the potential molecular mechanisms underlying differential immunogenicity and protective efficacy results of a clinical trial of the radiation-attenuated whole-sporozoite PfSPZ vaccine in African infants. Innate immune activation and myeloid signatures at prevaccination baseline correlated with protection from P. falciparum parasitemia in placebo controls. These same signatures were associated with susceptibility to parasitemia among infants who received the highest and most protective PfSPZ vaccine dose. Machine learning identified spliceosome, proteosome, and resting DC signatures as prevaccination features predictive of protection after highest-dose PfSPZ vaccination, whereas baseline circumsporozoite protein-specific (CSP-specific) IgG predicted nonprotection. Prevaccination innate inflammatory and myeloid signatures were associated with higher sporozoite-specific IgG Ab response but undetectable PfSPZ-specific CD8+ T cell responses after vaccination. Consistent with these human data, innate stimulation in vivo conferred protection against infection by sporozoite injection in malaria-naive mice while diminishing the CD8+ T cell response to radiation-attenuated sporozoites. These data suggest a dichotomous role of innate stimulation for malaria protection and induction of protective immunity by whole-sporozoite malaria vaccines. The uncoupling of vaccine-induced protective immunity achieved by Abs from more protective CD8+ T cell responses suggests that PfSPZ vaccine efficacy in malaria-endemic settings may be constrained by opposing antigen presentation pathways.Item Methods to Adjust for Confounding in Test-Negative Design COVID-19 Effectiveness Studies: Simulation Study(JMIR, 2025-01-27) Rowley, Elizabeth A. K.; Mitchell, Patrick K.; Yang, Duck-Hye; Lewis, Ned; Dixon, Brian E.; Vazquez-Benitez, Gabriela; Fadel, William F.; Essien, Inih J.; Naleway, Allison L.; Stenehjem, Edward; Ong, Toan C.; Gaglani, Manjusha; Natarajan, Karthik; Embi, Peter; Wiegand, Ryan E.; Link-Gelles, Ruth; Tenforde, Mark W.; Fireman, Bruce; Health Policy and Management, Richard M. Fairbanks School of Public HealthBackground: Real-world COVID-19 vaccine effectiveness (VE) studies are investigating exposures of increasing complexity accounting for time since vaccination. These studies require methods that adjust for the confounding that arises when morbidities and demographics are associated with vaccination and the risk of outcome events. Methods based on propensity scores (PS) are well-suited to this when the exposure is dichotomous, but present challenges when the exposure is multinomial. Objective: This simulation study aimed to investigate alternative methods to adjust for confounding in VE studies that have a test-negative design. Methods: Adjustment for a disease risk score (DRS) is compared with multivariable logistic regression. Both stratification on the DRS and direct covariate adjustment of the DRS are examined. Multivariable logistic regression with all the covariates and with a limited subset of key covariates is considered. The performance of VE estimators is evaluated across a multinomial vaccination exposure in simulated datasets. Results: Bias in VE estimates from multivariable models ranged from -5.3% to 6.1% across 4 levels of vaccination. Standard errors of VE estimates were unbiased, and 95% coverage probabilities were attained in most scenarios. The lowest coverage in the multivariable scenarios was 93.7% (95% CI 92.2%-95.2%) and occurred in the multivariable model with key covariates, while the highest coverage in the multivariable scenarios was 95.3% (95% CI 94.0%-96.6%) and occurred in the multivariable model with all covariates. Bias in VE estimates from DRS-adjusted models was low, ranging from -2.2% to 4.2%. However, the DRS-adjusted models underestimated the standard errors of VE estimates, with coverage sometimes below the 95% level. The lowest coverage in the DRS scenarios was 87.8% (95% CI 85.8%-89.8%) and occurred in the direct adjustment for the DRS model. The highest coverage in the DRS scenarios was 94.8% (95% CI 93.4%-96.2%) and occurred in the model that stratified on DRS. Although variation in the performance of VE estimates occurred across modeling strategies, variation in performance was also present across exposure groups. Conclusions: Overall, models using a DRS to adjust for confounding performed adequately but not as well as the multivariable models that adjusted for covariates individually.