OBJECTIVE: We tested the hypothesis that first-trimester metabolic biomarkers offered a unique profile in women with preeclampsia (PE) in the second half of pregnancy, compared with controls. METHOD: We conducted a nested case-control study within a prospective cohort of pregnant women followed from the first-trimester to delivery. Cases were those who developed PE at any gestational age, and these were compared with a control group without adverse pregnancy outcome, matched for gestational age within 3 days. We analyzed maternal blood obtained at 11-14 weeks' gestation for 40 acylcarnitine species (C2-C18 saturated, unsaturated, and hydroxylated) and 32 amino acids by liquid chromatography tandem mass spectrometry. Logistic regression modeling estimated the association of each metabolite with development of PE. RESULTS: We compared 41 cases with PE with 41 controls and found four metabolites (hydroxyhexanoylcarnitine, alanine, phenylalanine, and glutamate) that were significantly higher in the cases with PE. The area under the curve (AUC) using these metabolites individually to predict PE varied from 0.77 to 0.80, and when combined, the AUC improved to 0.82 [95% confidence interval (95% CI): 0.80-0.85] for all cases of PE and 0.85 (95% CI: 0.76-0.91) for early onset PE. CONCLUSION: Our findings suggest a potential role for first-trimester metabolomics in screening for PE.
OBJECTIVE: We tested the hypothesis that first-trimester metabolic biomarkers offered a unique profile in women with preeclampsia (PE) in the second half of pregnancy, compared with controls. METHOD: We conducted a nested case-control study within a prospective cohort of pregnant women followed from the first-trimester to delivery. Cases were those who developed PE at any gestational age, and these were compared with a control group without adverse pregnancy outcome, matched for gestational age within 3 days. We analyzed maternal blood obtained at 11-14 weeks' gestation for 40 acylcarnitine species (C2-C18 saturated, unsaturated, and hydroxylated) and 32 amino acids by liquid chromatography tandem mass spectrometry. Logistic regression modeling estimated the association of each metabolite with development of PE. RESULTS: We compared 41 cases with PE with 41 controls and found four metabolites (hydroxyhexanoylcarnitine, alanine, phenylalanine, and glutamate) that were significantly higher in the cases with PE. The area under the curve (AUC) using these metabolites individually to predict PE varied from 0.77 to 0.80, and when combined, the AUC improved to 0.82 [95% confidence interval (95% CI): 0.80-0.85] for all cases of PE and 0.85 (95% CI: 0.76-0.91) for early onset PE. CONCLUSION: Our findings suggest a potential role for first-trimester metabolomics in screening for PE.
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