A cross-sectional examination of immune adaptations during pregnancy in the ECHO Cohort
Banker, S. M.; Shapiro-Thompson, R.; Sinsel, S.; Ghassabian, A.; Douglas, C.; Nelson, M. E.; Peterson, L. A.; Thyagarajan, B.; Morales, S.; Hockett, C. W.; Elliot, A. J.; Giamberardino, S. N.; Shuffrey, L. C.; The ECHO Cohort Consortium,
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BackgroundPregnancy requires finely tuned immune changes that support implantation, placental development, maternal-fetal tolerance, and preparation for labor, yet the normative trajectories of circulating inflammatory proteins across gestation remain poorly defined. This cross-sectional study investigates how circulating inflammatory proteins vary with gestational age in pregnancy and examines the impacts of fundamental biological characteristics, such as gravidity and fetal sex. MethodsData were drawn from 1154 pregnant individuals from six study sites of the National Institutes of Health Environmental influences on Child Health Outcomes (ECHO) Cohort. We used Olink high-throughput proteomic profiling to map cross-sectional associations between protein expression levels and gestational age at blood draw using linear, spline-based, and generalized additive modeling approaches. ResultsGeneralized additive models provided the best fit, revealing that immune changes across pregnancy were predominantly nonlinear. Sixty-one proteins showed significant associations with gestational age, with many exhibiting shared inflection points that aligned with major physiological transitions. A small subset of proteins also showed evidence of modification by fetal and maternal characteristics. CD244 displayed different gestational patterns by fetal sex, while CST5 and SIRT2 showed varied gestational associations by maternal gravidity. ConclusionThe findings highlight pregnancy as a sequence of coordinated immune transitions rather than a simple linear shift and provide one of the most detailed characterizations to date of circulating inflammatory protein dynamics across human gestation. Establishing these normative trajectories offers a crucial reference for detecting early deviations that may signal risk for pregnancy complications and for identifying biomarkers in maternal and fetal health research.
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