International journal of molecular sciences
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Hypertensive disorders of pregnancy, including preeclampsia, are major contributors to maternal morbidity. The goal of this study was to evaluate the potential of metabolomics to predict preeclampsia and gestational hypertension from urine and serum samples in early pregnancy, and elucidate the metabolic changes related to the diseases. Metabolic profiles were obtained by nuclear magnetic resonance spectroscopy of serum and urine samples from 599 women at medium to high risk of preeclampsia (nulliparous or previous preeclampsia/gestational hypertension). ⋯ Serum metabolomic profiles predicted preeclampsia and gestational hypertension at 15% and 33% sensitivity, respectively, with increased lipid levels and an atherogenic lipid profile as most important for the prediction. Combining maternal characteristics with the urinary hippurate/creatinine level improved the prediction rates of preeclampsia in a logistic regression model. The study indicates a potential future role of clinical importance for metabolomic analysis of urine in prediction of preeclampsia.
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Cytokines are the most important soluble mediators of inflammation. Rare pediatric diseases provided exemplar conditions to study the anti-inflammatory efficacy of new generation therapies (biologics/biopharmaceuticals) selectively targeting single cytokines. Monoclonal antibodies and recombinant proteins have revolutionized anti-inflammatory therapies in the last two decades, allowing the specific targeting of single cytokines. ⋯ They are orally-administrable drugs whose dosage can be easily adjusted to obtain the desired anti-inflammatory effect. This could make these drugs more suitable for a wide range of diseases as stroke, gout, or neurological impairment, where inflammatory activation plays a pivotal role as trigger. Autoinflammatory diseases, which have previously put anti-cytokine proteins in the limelight, can again provide a valuable model to measure the real potential of small inhibitors as anti-inflammatory agents.