Omouma: a prospective mother and child cohort aiming to identify early biomarkers of pregnancy complications in women living in Qatar.

Background: Pregnancy is governed by multiple molecular and cellular processes, which might influence pregnancy health and outcomes. Failure to predict and understand the cause of pregnancy complications, adverse pregnancy outcomes, infant's morbidity and mortality, have limited effective interventions. Integrative multi-omics technologies provide an unbiased platform to explore the complex molecular interactions with an unprecedented depth. The objective of the present protocol is to build a longitudinal mother-baby cohort and use multi-omics technologies to help identify predictive biomarkers of adverse pregnancy outcomes, early life determinants and their effect on child health.

Methods/design: One thousand pregnant women with a viable pregnancy in the first trimester (6-14 weeks of gestation) will be recruited from Sidra Medicine hospital. All the study participants will be monitored every trimester, at delivery, and one-year post-partum. Serial high-frequency sampling, including blood, stool, urine, saliva, skin, and vaginal swabs (mother only) from the pregnant women and their babies, will be collected. Maternal and neonatal health, including mental health and perinatal growth, will be recorded using a combination of questionnaires, interviews, and medical records. Downstream sample processing including microbial profiling, vaginal immune response, blood transcriptomics, epigenomics, and metabolomics will be performed.

Discussion: It is expected that the present study will provide valuable insights into predicting pregnancy complications and neonatal health outcomes. Those include whether specific microbial and/or epigenomics signatures, immune profiles are associated with a healthy pregnancy and/or complicated pregnancy and poor neonatal health outcome. Moreover, this non-interventional cohort will also serve as a baseline dataset to understand how familial, socioeconomic, environmental and lifestyle factors interact with genetic determinants to influence health outcomes later in life. These findings will hold promise for the diagnosis and precision-medicine interventions.