The impact of maternal vulnerability on stress biomarkers and first-trimester growth: the Rotterdam Periconceptional Cohort (Predict Study)

Is the degree of maternal vulnerability positively associated with stress biomarkers (stress hormones, C-reactive protein, tryptophan metabolites, and one-carbon metabolites), and does long-term exposure to stress hormones reduce first-trimester growth? The maternal vulnerability risk score is positively associated with concentrations of hair cortisol and cortisone and negatively with tryptophan, while higher hair cortisol concentrations are associated with reduced first-trimester growth without mediation of tryptophan. A high degree of maternal vulnerability during the periconception period is associated with impaired first-trimester growth and pregnancy complications, with consequences for long-term health of the child and future life course. However, due to the challenges of early identification of vulnerable women, the uptake of periconception care is low in this target group. Between June 2022 and June 2023, this study was conducted in a sub-cohort of 160 pregnant women participating in the Rotterdam Periconceptional Cohort (Predict Study), an ongoing prospective tertiary hospital-based cohort. One hundred and thirty-two women with ongoing pregnancies and available stress biomarker data were included in the analysis. Data on periconceptional social, lifestyle, and medical risk factors were collected via self-administered questionnaires, and these factors were used for the development of a composite maternal vulnerability risk score. Stress biomarkers, including stress hormones (hair cortisol and cortisone) and inflammatory and oxidative stress biomarkers (C-reactive protein, total homocysteine, and tryptophan metabolites) were determined in the first trimester of pregnancy. First-trimester growth was assessed by crown-rump length (CRL) and embryonic volume (EV) measurements at 7, 9, and 11 weeks gestation by making use of an artificial intelligence algorithm and virtual reality techniques using 3D ultrasound data sets. The associations between the maternal vulnerability risk score and stress biomarkers were identified using linear regression models, and between stress hormones and CRL- and EV-trajectories using mixed models. A mediation analysis was performed to assess the contribution of tryptophan. All associations were adjusted for potential confounders, which were identified using a data-driven approach. Several sensitivity analyses were performed to check the robustness of the findings. The maternal vulnerability risk score was positively associa