Altered levels of acylcarnitines, phosphatidylcholines, and sphingomyelins in peritoneal fluid from ovarian endometriosis patients

Endometriosis is a complex, polygenic, and estrogen-dependent disease that affects 6% to 10% of women of reproductive age, and 30% to 50% of women with infertility and/or pelvic pain. Surgical diagnosis of endometriosis is still the gold standard, as there are currently no diagnostic biomarkers available. Due to the invasive diagnostics, it can take up to 11 years before affected women are diagnosed and receive the appropriate treatment. We performed a targeted metabolomics study to search for potential semi-invasive biomarkers in peritoneal fluid from endometriosis patients. Our case-control study comprised 29 ovarian endometriosis patients and 36 healthy control women. The 148 metabolites included acylcarnitines, glycerophospholipids, and sphingolipids, which were quantified by electrospray ionization tandem mass spectrometry. The strength of association between the metabolites and the metabolite ratios and disease was assessed using crude and adjusted odds ratios. The best combination of biomarkers was then selected by performing step-wise logistic regression. Our analysis reveals significantly decreased concentrations of 10 metabolites, of carnitine and acylcarnitines (C0, C8:1, C6C4:1 DC, C10:1), phosphatidylcholines (PC aa C38:3, PC aa C38:4, PC aa C40:4, PC aa C40:5), and sphingomyelins (SM C16:1, SM C18:1), and 125 significantly altered metabolite ratios in patients versus control women. The best model includes two ratios: a carnitine to a phosphatidylcholine (C0/PC ae C36:0); and between two phosphatidylcholines (PC aa C30:0/PC ae C32:2). When adjusted for age, this provides sensitivity of 82.8% and specificity of 94.4%, with AUC of 0.944. Our study supports the importance of carnitine, phosphatidylcholine, and sphingomyelin metabolites in the pathophysiology of endometriosis, and confirms the potential for the combination of individual metabolite ratios to provide biomarkers for semi-invasive diagnostics.