Establishing correlates of maternal-fetal cytomegalovirus transmission-one step closer through predictive modeling.

Abstract

Determinants of maternal-fetal cytomegalovirus (CMV) transmission and factors influencing the severity of congenital CMV (cCMV) infection are not well understood. We conducted a descriptive, multi-center study in pregnant women ≥18 years old with primary CMV infection and their newborns (NCT01251744) to explore maternal immune responses to CMV and determine potential immunologic/virologic correlates of cCMV following primary infection during pregnancy. We developed alternative approaches looking into univariate/multivariate factors associated with cCMV, including a participant clustering/stratification approach and an interpretable predictive model-based approach using trained decision trees for risk prediction (post-hoc analyses). Pregnant women were grouped in three distinct clusters with similar baseline characteristics, particularly gestational age at diagnosis. We observed a trend for higher viral loads in urine and saliva samples from mothers of infants with cCMV versus without cCMV. When using a trained predictive-model approach that accounts for interaction effects between variables, anti-pentamer IgG antibody concentration and viral load in saliva were identified as biomarkers jointly associated with the risk of maternal-fetal CMV transmission. We identified biomarkers of CMV maternal-fetal transmission. After validation in larger studies, our findings will guide the management of primary infection during pregnancy and the development of vaccines against cCMV.