biostudies-literatureWu SNCATS NIH HHSNIAID NIH HHSOffice of Extramural Research, National Institutes of HealthNational Medical Research CouncilNIGMS NIH HHSe10724https://www.ebi.ac.uk/biostudies/studies/S-EPMC9073386biostudies-literatureUnknown18(5)The seasonal influenza vaccine is only effective in half of the vaccinated population. To identify determinants of vaccine efficacy, we used data from > 1,300 vaccination events to predict the response to vaccination measured as seroconversion as well as hemagglutination inhibition (HAI) titer levels one year after. We evaluated the predictive capabilities of age, body mass index (BMI), sex, race, comorbidities, vaccination history, and baseline HAI titers, as well as vaccination month and vaccine dose in multiple linear regression models. The models predicted the categorical response for > 75% of the cases in all subsets with one exception. Prior vaccination, baseline titer level, and age were the major determinants of seroconversion, all of which had negative effects. Further, we identified a gender effect in older participants and an effect of vaccination month. BMI had a surprisingly small effect, likely due to its correlation with age. Comorbidities, vaccine dose, and race had negligible effects. Our models can generate a new seroconversion score that is corrected for the impact of these factors which can facilitate future biomarker identification.Molecular systems biologyEvaluation of determinants of the serological response to the quadrivalent split-inactivated influenza vaccine.PMC9073386UL1 TR002378UL1TR00237875N93019C00052R35GM127089NMRC/CG/M009/2017R35 GM127089Vogel CChoi HWu SGhedin ERoss TMCarlock MAfalseEvaluation of determinants of the serological response to the quadrivalent split-inactivated influenza vaccine.The seasonal influenza vaccine is only effective in half of the vaccinated population. To identify determinants of vaccine efficacy, we used data from > 1,300 vaccination events to predict the response to vaccination measured as seroconversion as well as hemagglutination inhibition (HAI) titer levels one year after. We evaluated the predictive capabilities of age, body mass index (BMI), sex, race, comorbidities, vaccination history, and baseline HAI titers, as well as vaccination month and vaccine dose in multiple linear regression models. The models predicted the categorical response for > 75% of the cases in all subsets with one exception. Prior vaccination, baseline titer level, and age were the major determinants of seroconversion, all of which had negative effects. Further, we identified a gender effect in older participants and an effect of vaccination month. BMI had a surprisingly small effect, likely due to its correlation with age. Comorbidities, vaccine dose, and race had negligible effects. Our models can generate a new seroconversion score that is corrected for the impact of these factors which can facilitate future biomarker identification.2022-01-01T00:00:00Z2022 May2025-04-18T23:02:58.378Z2025-02-19T03:58:36.693ZS-EPMC90733863551420710.15252/msb.202110724