Abstract
Maternal and neonatal health (women during pregnancy, childbirth, and the postnatal period) presents a spectrum of healthcare challenges, including preterm birth, preeclampsia, intrauterine growth restriction, polycystic ovarian syndrome, and gestational diabetes mellitus. While genomic investigations have shed light on many of these topics, protein biomarker discovery, a pivotal aspect of such research, holds promise in offering insights into disease diagnosis, progression, and prognosis. This review paper aims to explore the landscape of proteomics research pertaining to the aforementioned disorders. In the search for viable biomarkers, existing ones are either outdated or lack specificity and new ones being investigated do not commonly make it to the validation stage. In this review, the reasons for the gap between the biomarker discovery stage and the clinical validation stage are evaluated, in addition to what steps are being taken to mitigate the unexpectedly slow scientific and clinical progress. Notably, this paper also delves into the ethnic disparities found in maternal and neonatal health research, as well as how AI is currently being used to alleviate socioeconomic and ethnic disparities, as well as its advantages for the analysis of large "omics" datasets. We anticipate this investigation will provide critical, invaluable information for researchers, medical professionals, and policy decision-makers in this field to improve overall maternal and neonatal health outcomes.