Oxidative dyslipidemia in early pregnancy: integrating atherogenic index of plasma (AIP) and uric acid (UA) to refine preeclampsia risk stratification

Preeclampsia represents an unmasking of underlying vascular and metabolic vulnerability during the physiologic stress of pregnancy. Current first-trimester screening relies heavily on body mass index which incompletely captures qualitative metabolic dysfunction, particularly in non-obese women. In this narrative perspective, we examine the atherogenic index of plasma (AIP; log10[TG/HDL-C]), which reflects triglyceride-rich lipoprotein burden and has emerged as a marker of lipid-driven vascular stress independent of adiposity. This article does not follow systematic review methodology (e.g., PRISMA) and is intended to provide a conceptual synthesis rather than an exhaustive review. Emerging obstetric evidence suggests that first-trimester AIP (≤14 weeks) is associated with an increased risk of subsequent preeclampsia, with uric acid (UA) potentially amplifying this relationship through redox-dependent mechanisms. We propose that elevated AIP and UA define an early, detectable oxidative dyslipidemia phenotype characterized by the convergence of lipotoxic and oxidative pathways, leading to endothelial dysfunction, nitric oxide (NO) depletion, platelet activation, and impaired placental perfusion. We further delineate druggable mechanistic nodes within this axis and outline a precision pharmacology framework for biomarker-enriched prevention trials. These nodes include cyclooxygenase-1 (COX-1)–mediated platelet activation (targeted by low-dose aspirin), NO pathway dysregulation (amenable to NO-supportive strategies), and xanthine oxidase–driven oxidative amplification (a potential target of redox-modulating agents). By explicitly linking early metabolic biomarkers to defined vascular pathways, this framework reframes first-trimester screening as a platform for mechanism-guided pharmacologic investigation rather than risk categorization alone. Before clinical integration, essential steps include independent validation across diverse populations, establishment of pregnancy-specific thresholds, demonstration of incremental predictive value beyond existing screening algorithms, and evidence that biomarker-guided strategies improve maternal and perinatal outcomes. Overall, these observations should be considered hypothesis-generating and require further validation before AIP-based assessment can support biologically informed, phenotype-guided prevention strategies within obstetric pharmacology.