Immune Changes in Pregnancy: Associations with Pre-existing Conditions and Obstetrical Complications at the 20th Gestational Week - A Prospective Cohort Study

Background Pregnancy is a complex biological process and serious complications can arise when the delicate balance between the maternal immune system and the semi-allogeneic fetal immune system is disrupted or challenged. Gestational diabetes mellitus (GDM), pre-eclampsia, preterm birth, and low birth weight, pose serious threats to maternal and fetal health. Identification of early biomarkers through an in-depth understanding of molecular mechanisms is critical for early intervention. Methods We analyzed the associations between 47 proteins involved in inflammation, chemotaxis, angiogenesis, and immune system regulation, maternal and neonatal health outcomes, and the baseline characteristics and pre-existing conditions (diseases and obstetric history) of the mother in a prospective cohort of 1,049 pregnant women around the 20th gestational week. Bayesian linear regression models were used to examine the impact of risk factors on biomarker levels and Bayesian cause-specific parametric proportional hazards models were used to analyze the effect of biomarkers on maternal and neonatal health outcomes. Finally, we evaluated the predictive value of baseline characteristics and the 47 proteins using machine-learning models. Shapley additive explanation (SHAP) scores were used to dissect the machine learning models to identify biomarkers most important for predictions. Results Associations were identified between specific inflammatory markers and existing conditions, including maternal age and pre-pregnancy BMI, chronic diseases, complications from prior pregnancies, and COVID-19 exposure. Smoking during pregnancy significantly affected GM-CSF and 9 other biomarkers. Distinct biomarker patterns were observed for different ethnicities. In obstetric complications, IL-6 inversely correlated with pre-eclampsia risk, while acute cesarean section and birth weight to gestational age ratio were linked to markers such as VEGF or PlGF. GDM was associated with IL-1RA, IL-17D, and Eotaxin-3. Severe PPH correlated with CRP and proteins of the IL-17 family. Predictive modeling using MSD biomarkers yielded ROC-AUC values of 0.708 and 0.672 for GDM and pre-eclampsia, respectively. Significant predictive biomarkers for GDM included IL-1RA and Eotaxin-3, while pre-eclampsia prediction yielded highest predictions when including MIP-1β, IL-1RA, and IL-12p70. Conclusion Our study provides novel insights into the interplay between preexisting conditions and immune dysregulation in pregnancy. These findings contribute to our understanding of the pathophysiology of obstetric complications and the identification of novel biomarkers for early intervention(s) to improve maternal and fetal health. ### Competing Interest Statement SB has ownerships in Hoba Therapeutics Aps, Novo Nordisk A/S, Lundbeck A/S, and managing board memberships in Proscion A/S. HSN received personal payment or honoraria for lectures and presentations from Ferring Pharmaceuticals, Merck, Astra Zeneca, Cook Medical, and Ibsa Nordic. ### Funding Statement The study was supported by funding from the Novo Nordisk Foundation (grant agreements NNF14CC0001 and NNF17OC0027594). The work was also carried out as a part of the BRIDGE Translational Excellence Programme (bridge.ku.dk) at the Faculty of Health and Medical Sciences, University of Copenhagen, funded by the Novo Nordisk Foundation (NNF18SA0034956). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The PREGCO study was approved by the Knowledge Centre for Data Protection and Compliance, The Capital Region of Denmark (P-2020-255), and by the Scientific Ethics Committee of the Capital Region of Denmark (journal number H-20022647). All PREGCO participants provided written informed consent. Danish legislation allows for register-based research to be conducted without the consent of participants and without ethical committee approval. Registry data, i.e. the Danish Medical Birth Registry, was held at Statistics Denmark, which is the Danish national statistical institution. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The participants of this study did not give written consent for their data to be shared publicly, so due to the sensitive nature of the research supporting data is not available.