Abstract
BACKGROUND: Pregnancy requires precisely timed immune adaptations to maintain foetal tolerance while enabling timely initiation of labour, a process often conceptualised as the 'immune clock' of pregnancy. Disruption of this immune clock contributes to adverse obstetric outcomes. While maternal opioid use disorder (OUD) is a recognised risk factor for poor maternal and neonatal health, its impact on maternal immune landscape at delivery remains poorly understood. METHODS: We analysed peripheral blood collected from pregnant individuals with and without OUD at time of admission for delivery before the onset of active labour. We employed multiparameter flow cytometry, cytokine profiling, and single-cell-RNA sequencing to capture changes in cellular composition, functional responses, and intercellular signalling networks. Given the high prevalence of hepatitis C (HCV) in this population, we stratified our findings by maternal HCV status. FINDINGS: Clinically, maternal OUD was linked to greater use of labour induction and a smaller stature of newborns. Immunophenotyping revealed a shift toward systemic inflammation, with expansion of memory T and B cells, inflammatory monocytes, and NK cells. Cytokine assays demonstrated dysregulated responses to stimulation, consistent with immune tolerance or exhaustion. Single cell transcriptomic mapping identified disrupted communication networks, suggesting impaired cytokine crosstalk as a central mechanism of immune dysregulation. INTERPRETATION: Collectively, our findings demonstrate that maternal OUD, with or without HCV co-infection, is associated with altered circulating maternal immunity at term. This pro-inflammatory, dysregulated immune state may underlie increased obstetric morbidity and highlights potential immunologic pathways that can be targeted for intervention in high-risk pregnancies. FUNDING: This study was supported by grants from the National Institutes of Health: 1R01DA059152-01 (IM and JO), 7R01AI145910-05S1(IM), TL1TR001997 (HT) and pilot funding from the University of Kentucky, including the Clinical and Translational Science Substance Use Disorder pilot grant 3210003238 (IM and JO). This research was indirectly supported by the Kentucky Opioid Response Effort (KORE) via Substance Abuse and Mental Health Services Administration (SAMHSA) Grants, H79TI081704, H79TI083283, as well as the data management system that is hosted by UK with grant support from NIH CTSA UL1TR001998. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the University of Kentucky.