Large-Scale Proteomics Reveals New Candidate Biomarkers for Late-Onset Preeclampsia

子痫前期 胎盘生长因子 内科学 医学 可溶性fms样酪氨酸激酶-1 内分泌学 男科 生物 怀孕 遗传学
作者
Ina Jungersen Andresen,Roberto Romero,Ane C. Westerberg,Nándor Gábor Than,Nardhy Gomez‐Lopez,Gaurav Bhatti,Oladejo Ahmodu,Dereje W. Gudicha,Arun Meyyazhagan,Awoniyi O. Awonuga,Tinnakorn Chaiworapongsa,David R. Bryant,Trond Melbye Michelsen,Adi L. Tarca
出处
期刊:Hypertension [Ovid Technologies (Wolters Kluwer)]
标识
DOI:10.1161/hypertensionaha.125.25189
摘要

BACKGROUND: Preeclampsia is classified as either a more severe early onset or a more prevalent late-onset form. Lower PlGF (placental growth factor) and increased sFlt-1 (fms-like tyrosine kinase-1) in maternal circulation are promising biomarkers, yet they lack specificity for preeclampsia. METHODS: We quantified ≈7000 proteins in 673 samples collected from 89 patients with late-onset preeclampsia and 91 controls at T1 (15–22), T2 (22–30), and T3 (30–42) weeks. Elastic net and random forest models were fitted and evaluated by cross-validation. Differential abundance analysis followed by functional profiling, was used to identify and interpret protein changes. RESULTS: An increase in protein differential abundance in late-onset preeclampsia was observed with advancing gestation, reaching 806 proteins at T3 related to angiogenesis, cell adhesion, and extracellular matrix remodeling. FAAH2 (fatty acid amide hydrolase 2), SIGLEC6 (sialic acid-binding Ig-like lectin-6), IL17RC (interleukin-17 receptor C), HTRA1 (serine protease), sFlt-1, and 47 other proteins dysregulated at T3 were validated in a reanalysis of a ≈5000 protein Norwegian data set. Random forest models with 20 proteins showed high accuracy at T3 (area under the curve [AUC], 0.83 [0.77–0.89], sensitivity 59%) even in cases not yet diagnosed at sampling (n=31, AUC, 0.80 [0.71–0.90], sensitivity 58%), outperforming sFlt-1 and PlGF. Moderate accuracy was obtained at T1 (AUC, 0.63 [0.54–0.72], sensitivity 33%) and T2 (AUC, 0.59 [0.50–0.68], sensitivity 17%). Combining maternal characteristics and obstetric history with proteomics data increased accuracy at T1 (AUC, 0.68 [0.59–0.77], sensitivity 28%), T2 (AUC, 0.68 [0.60–0.77], sensitivity 31%), and T3 (AUC, 0.87 [0.81–0.92], sensitivity 69%). CONCLUSIONS: The findings confirm the involvement of abnormal trophoblast invasion, angiogenesis, and extracellular matrix remodeling in late-onset preeclampsia, while highlighting new protein alterations consistent across diverse cohorts.
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