Serum Protein Profile in Women With Pregnancy Morbidity Associated With Antiphospholipid Syndrome.

CONTEXT: Antiphospholipid antibodies (aPL) are related with a high risk of pregnancy morbidity (PM) and also of vascular thrombosis. On the basis of recent studies, we expect that in women with PM associated with antiphospholipid syndrome (APS), further factors may be deregulated and involved in pathophysiology of the disease. Such factors may have the potential to become novel biomarkers for APS and its stages. SETTINGS AND DESIGN: Descriptive study from a recurrent pregnancy loss program. AIMS: To study the protein expression in sera from women with PM with or without aPL. MATERIALS AND METHODS: Protein profiles were determined by surface enhanced laser desorption and ionization - time of flight mass spectrometry (SELDI-TOF MS) in the serum samples from women with PM, 10 of them with aPL and 12 without aPL. On the basis of the mass-to-charge ratio (m/z) of the protein, signals differentially expressed between the two groups were compared with data banks to approach candidate proteins. STATISTICAL ANALYSIS USED: To determine the differential expression of each protein, a no paired t-test was performed using Ciphergen Express Client 3.1 software. RESULTS: SELDI-TOF analysis makes it possible to discriminate between several proteins in women with PM with and without aPL, although it does not allow protein identification. Nine proteins were found in significantly higher levels in aPL-positive women. CONCLUSION: The results underline that further factors beyond autoantibodies are involved in PM associated with APS and might lead to the development of new biomarkers.

Transthyretin is dysregulated in preeclampsia, and its native form prevents the onset of disease in a preclinical mouse model.

Preeclampsia is a major pregnancy complication with potential short- and long-term consequences for both mother and fetus. Understanding its pathogenesis and causative biomarkers is likely to yield insights for prediction and treatment. Herein, we provide evidence that transthyretin, a transporter of thyroxine and retinol, is aggregated in preeclampsia and is present at reduced levels in sera of preeclamptic women, as detected by proteomic screen. We demonstrate that transthyretin aggregates form deposits in preeclampsia placental tissue and cause apoptosis. By using in vitro approaches and a humanized mouse model, we provide evidence for a causal link between dysregulated transthyretin and preeclampsia. Native transthyretin inhibits all preeclampsia-like features in the humanized mouse model, including new-onset proteinuria, increased blood pressure, glomerular endotheliosis, and production of anti-angiogenic factors. Our findings suggest that a focus on transthyretin structure and function is a novel strategy to understand and combat preeclampsia.

Novel approaches for mechanistic understanding and predicting preeclampsia.

Despite intense investigation, preeclampsia (PE) remains largely enigmatic. Relatively late onset of diagnostic signs and heterogeneous nature of the disease further contribute to poor understanding of its etiology and clinical management. There exist no concrete animal models that can provide mechanistic underpinnings for evaluating targeted therapeutic intervention. Poor cross-sectional findings with potential biochemical markers reported so far have proved counterintuitive and suggest a need for novel approaches to predict the early onset of disease. Because of the co-onset of local placental anomalies and systemic manifestation of symptoms, it is highly likely that serum from PE patients can provide a "blueprint" of causative factors. Proteomic and/or functional analysis of maternal serum are expected to predict the onset of disease ahead of manifestation of clinical symptoms. A serum-based predictive assay should overcome complexities resulting from the heterogeneous etiology of PE. This review attempts to address some of these issues and discuss the signature biochemical serum factors and propose new and better ways to predict PE.