Objective
The cause of preeclampsia remains unknown and the diagnosis can be uncertain. We used proteomic-based analysis of urine to improve disease classification and extend the pathophysiological understanding of preeclampsia.
Study design
Urine samples from 284 women were analyzed by mass spectrometry-based proteomics (SELDI). In the exploratory phase, 59 samples were used to extract the proteomic fingerprint characteristic of severe preeclampsia requiring mandated delivery and develop a diagnostic algorithm. In the challenge phase we sought to prospectively validate the algorithm in 225 women screened for a variety of high and low-risk conditions, including preeclampsia. Of these, 19 women were followed longitudinally throughout pregnancy. Presence of biomarkers was interpreted relative to clinical classification, need for delivery and other urine laboratory measures (ratios of protein-to-creatinine and soluble fms-like tyrosine kinase-1-to-placental growth factor). In the translational phase biomarker identification by tandem mass spectrometry and validation experiments in urine, serum and placenta were employed to identify, quantify and localize the biomarkers or related proteins.
Results
We report that women with preeclampsia appear to present a unique urine proteomic fingerprint which predicts preeclampsia in need for mandated delivery with highest accuracy. This characteristic proteomic profile also has the ability to distinguish preeclampsia from other hypertensive or proteinuric disorders in pregnancy. Pregnant women followed longitudinally who developed preeclampsia displayed abnormal urinary profiles >10 weeks prior to clinical manifestation. Tandem mass spectrometry followed by de-novo sequencing identified the biomarkers as non-random cleavage products of SERPINA-1 and albumin. Of these, the 21-aminoacid C-terminus fragment of SERPINA-1 was highly associated with severe forms of preeclampsia requiring early delivery. In preeclampsia, increased and aberrant SERPINA-1 immunoreactivity was found in urine, serum and placenta where it localized predominantly to placental villi and placental vascular spaces adherent to the endothelium. In addition, significant perivascular deposits of misfolded SERPINA-1 aggregates were exclusively identified in preeclamptic placentas.
Conclusion
Proteomics-based characterization of urine in preeclampsia identified a proteomic fingerprint composed of SERPINA-1 and albumin fragments which can accurately diagnose preeclampsia and shows promise to discriminate it from other hypertensive proteinuric diseases. These findings provide insight into a novel pathophysiological mechanism of preeclampsia related to SERPINA-1 misfolding which may offer new therapeutic opportunities in the future.