Evaluation of determinants of the serological response to the quadrivalent split‐inactivated influenza vaccine

Abstract

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.

Prevaccination Glycan Markers of Response to an Influenza Vaccine Implicate the Complement Pathway

“…Consistent with this, regrouping the samples using a modified response score that takes into account age, gender, and BMI found the same pattern when comparing the high responders to low/nonresponders (Supporting Information, Figure S4 ). 24 …”

“…We also categorized antibody response using the metric of Wu et al, which takes into account BMI, age, and gender. 24 For our comparison, we ranked participants by the modified response score from high to low. The upper third was considered high responders and the lower third nonresponders.…”

Proteomic signatures of the serological response to flu vaccination in a large human cohort study

“…The upper panel illustrates the distribution of adjusted seroconversion, seroconversion and demographic information for all study participants. Serostatus is defined as in Wu et al [18]. The lower panel shows the normalized protein levels for 273 proteins measured in participant sera.…”

“…the quantitative response to the vaccine as described elsewhere [25]. We then used the computational model we developed [18] to obtain the 'adjusted seroconversion' for each participant which provides a measure of seroconversion that removes the impact of age, BMI, sex, and the other factors mentioned above. Due to this correction, adjusted seroconversion can report vaccine effects independent of known factors such as age and prior vaccination status; it enables discovery of new factors.…”

“…Further, for each sample we obtained information for 'adjusted seroconversion' which reports the seroconversion corrected for the impact of participant age, BMI, sex, race, comorbidities, prior vaccination status, baseline titer levels, month of vaccination, and vaccine dose. We obtained the values from the results published in [18].…”