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Background and objectives: The neurodevelopment of the offspring is suggested to be influenced by the maternal immune system's responses throughout pregnancy, which in turn is also vulnerable to maternal psychosocial stress conditions. Therefore, our main goal was to investigate whether maternal peripheral immunological biomarkers (IB) during two stages of gestation are associated with distinct neurodevelopmental trajectories in the first two years of life. As a second goal, we also explored the association between maternal distal (childhood) and proximal (gestation) stressful experiences and the immunological markers assessed during pregnancy. Methods: Maternal childhood trauma, depressive and anxiety symptoms, and peripheral IB (IFNγ, IL-10, IL1ß, IL6, IL8, TNFα, EGF, IL13, IL17, IL1Ra and IL4) were measured at baseline (8-16 weeks of pregnancy) and at 30 weeks of pregnancy in 160 women. The participants had the blood samples collected from two randomized clinical trials conducted by the same team and methods in the same community. A Principal Component Analysis (PCA) was implemented to create meaningful composite variables that describe the cytokines joint variation. Finally, linear mixed-effects modeling was used to investigate the influence of inflammatory biomarkers, maternal childhood trauma, anxiety, and depressive symptoms on Bayley's III scores trajectories. Results: The IB profile during the 3rd trimester of pregnancy predicted the offspring's neurodevelopmental trajectories in the first two years of life. The components derived from PCA were important predictors and captured different immune responses, reflecting both pro- and anti-inflammatory states. Maternal stressful experiences did not correlate with the immunological markers. Although not a reliable predictor alone, maternal psychosocial stress at the 1st trimester of pregnancy interacted with the mother's immune response while predicting the neurodevelopmental scores during the first two years of life. Conclusions: Our results underscore the importance of the maternal immune response during pregnancy in shaping the neurodevelopmental trajectory of the offspring. Additionally, we observed that the maternal distress at the early stages of pregnancy has an incremental effect on the neurodevelopmental outcome but depends upon the immune response.
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BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease 2019; COVID-19) is associated with adverse outcomes in patients with cardiovascular disease (CVD). The aim of the study was to characterize the interaction between SARS-CoV-2 and Angiotensin-Converting Enzyme 2 (ACE2) functional networks with a focus on CVD. METHODS: Using the network medicine approach and publicly available datasets, we investigated ACE2 tissue expression and described ACE2 interaction networks that could be affected by SARS-CoV-2 infection in the heart, lungs and nervous system. We compared them with changes in ACE-2 networks following SARS-CoV-2 infection by analyzing public data of human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). This analysis was performed using the Network by Relative Importance (NERI) algorithm, which integrates protein-protein interaction with co-expression networks. We also performed miRNA-target predictions to identify which miRNAs regulate ACE2-related networks and could play a role in the COVID19 outcome. Finally, we performed enrichment analysis for identifying the main COVID-19 risk groups. RESULTS: We found similar ACE2 expression confidence levels in respiratory and cardiovascular systems, supporting that heart tissue is a potential target of SARS-CoV-2. Analysis of ACE2 interaction networks in infected hiPSC-CMs identified multiple hub genes with corrupted signaling which can be responsible for cardiovascular symptoms. The most affected genes were EGFR (Epidermal Growth Factor Receptor), FN1 (Fibronectin 1), TP53, HSP90AA1, and APP (Amyloid Beta Precursor Protein), while the most affected interactions were associated with MAST2 and CALM1 (Calmodulin 1). Enrichment analysis revealed multiple diseases associated with the interaction networks of ACE2, especially cancerous diseases, obesity, hypertensive disease, Alzheimer's disease, non-insulin-dependent diabetes mellitus, and congestive heart failure. Among affected ACE2-network components connected with the SARS-Cov-2 interactome, we identified AGT (Angiotensinogen), CAT (Catalase), DPP4 (Dipeptidyl Peptidase 4), CCL2 (C-C Motif Chemokine Ligand 2), TFRC (Transferrin Receptor) and CAV1 (Caveolin-1), associated with cardiovascular risk factors. We described for the first time miRNAs which were common regulators of ACE2 networks and virus-related proteins in all analyzed datasets. The top miRNAs regulating ACE2 networks were miR-27a-3p, miR-26b-5p, miR-10b-5p, miR-302c-5p, hsa-miR-587, hsa-miR-1305, hsa-miR-200b-3p, hsa-miR-124-3p, and hsa-miR-16-5p. CONCLUSION: Our study provides a complete mechanistic framework for investigating the ACE2 network which was validated by expression data. This framework predicted risk groups, including the established ones, thus providing reliable novel information regarding the complexity of signaling pathways affected by SARS-CoV-2. It also identified miRNAs that could be used in personalized diagnosis in COVID-19.