Introduction: Ectopic pregnancy (EP) is a potentially life-threatening condition and early diagnosis still remains a challenge, causing a delay in management leading to tubal rupture. Targeted metabolomics has been shown to identify novel biomarkers for the detection of ectopic pregnancy. Using untargeted metabolomics approach, we sought to identify putative plasma biomarkers for the detection of tubal EP compared to intrauterine pregnancies. Methods: This case-control study included prospective recruitment of 50 tubal EP cases and 50 early intrauterine pregnancy controls. Plasma samples were biochemically profiled using tandem liquid chromatographymass (MS/MS) spectrometry with untargeted metabolomics approach. To avoid over-fitting, datasets were randomly divided into a discovery group (30 cases vs 30 controls) and a test group (20 cases and 20 controls). Logistic regression models were developed in the discovery group and validated in the independent test group. Molecular networking and metabolite identification was employed using Global Natural Products Social Molecular Networking (GNPS) data base. Univariate and multivariate analysis were performed via MetaboAnalyst 5.0. Results: In total 585 molecular features were identified. 46 metabolite concentrations were significantly altered in EP plasma (p<0.05). Metabolomic profiling yielded significant separation between EP and controls (p<0.05) (Figure 1). Independent validation of a two-metabolite model consisting of D-erythro-sphingosine and oleoyl-carnitine, achieved an AUC (95% CI) = 0.962 (0.910-0.1) with a sensitivity of 100% and specificity of 95.9%. Molecular feature networking revealed significant alterations in glycerol phosphocholine pathway and depleted levels of sphingolipids. Conclusion: We report novel untargeted metabolomic biomarkers with a high accuracy for the detection of EP for the first time. Accurate biomarkers could potentially result in improved early diagnosis and better understanding the metabolism of tubal EP cases.
Turkoglu O, Quinn R, Graham SF, Bahado-Singh R. Untargeted metabolomic identification of diagnostic biomarkers in ectopic pregnancy. Reprod Sci. 2022 Mar;29(S1):85-86.