Proteomics Analysis of Plasma for Early Diagnosis of Endometriosis

Fassbender, Amelie PhD; Waelkens, Etienne MD, PhD; Verbeeck, Nico MSc; Kyama, Cleophas M. PhD; Bokor, Attila MD, PhD; Vodolazkaia, Alexandra MD; Van de Plas, Raf PhD; Meuleman, Christel MD, PhD; Peeraer, Karen MD; Tomassetti, Carla MD; Gevaert, Olivier PhD; Ojeda, Fabian PhD; De Moor, Bart PhD; D'Hooghe, Thomas MD, PhD

Obstetrics & Gynecology:
doi: 10.1097/AOG.0b013e31823fda8d
Original Research
Abstract

OBJECTIVE: To test the hypothesis that differential surface-enhanced laser desorption/ionization time-of-flight mass spectrometry protein or peptide expression in plasma can be used in infertile women with or without pelvic pain to predict the presence of laparoscopically and histologically confirmed endometriosis, especially in the subpopulation with a normal preoperative gynecologic ultrasound examination.

METHODS: Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry analysis was performed on 254 plasma samples obtained from 89 women without endometriosis and 165 women with endometriosis (histologically confirmed) undergoing laparoscopies for infertility with or without pelvic pain. Data were analyzed using least squares support vector machines and were divided randomly (100 times) into a training data set (70%) and a test data set (30%).

RESULTS: Minimal-to-mild endometriosis was best predicted (sensitivity 75%, 95% confidence interval [CI] 63–89; specificity 86%, 95% CI 71–94; positive predictive value 83.6%, negative predictive value 78.3%) using a model based on five peptide and protein peaks (range 4.898–14.698 m/z) in menstrual phase samples. Moderate-to-severe endometriosis was best predicted (sensitivity 98%, 95% CI 84–100; specificity 81%, 95% CI 67–92; positive predictive value 74.4%, negative predictive value 98.6%) using a model based on five other peptide and protein peaks (range 2.189–7.457 m/z) in luteal phase samples. The peak with the highest intensity (2.189 m/z) was identified as a fibrinogen β-chain peptide. Ultrasonography-negative endometriosis was best predicted (sensitivity 88%, 95% CI 73–100; specificity 84%, 95% CI 71–96) using a model based on five peptide peaks (range 2.058–42.065 m/z) in menstrual phase samples.

CONCLUSION: A noninvasive test using proteomic analysis of plasma samples obtained during the menstrual phase enabled the diagnosis of endometriosis undetectable by ultrasonography with high sensitivity and specificity.

LEVEL OF EVIDENCE: II

In Brief

A noninvasive test using plasma proteomics allowed the diagnosis of endometriosis undetectable by ultrasonography with high sensitivity and specificity.

Author Information

From the Department of Obstetrics and Gynaecology, Leuven University Fertility Centre, University Hospital Gasthuisberg, the Department of Molecular Cell Biology, Campus Gasthuisberg, ProMeta, Interfaculty Centre for Proteomics and Metabolomics, O&N2, and the IBBT-KU Leuven Future Health Department, Leuven, Belgium; the Division of Reproductive Biology, Institute of Primate Research, Karen, Nairobi, Kenya; the Department of Obstetrics and Gynecology, Semmelweis University, Budapest, Hungary; and the Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium.

Supported by grants from the Leuven University Council (Dienst Onderzoekscoordinatie, KU Leuven, Leuven, Belgium), the Flemish Fund for Scientific Research (FWO), Leuven–Belgium, and KU Leuven Interfaculty Council for Development Cooperation, Leuven, Belgium. Research funded by a PhD grant of the Agency for Innovation by Science and Technology (IWT). Research supported by 1) the Research Council KUL (ProMeta, GOA Ambiorics, GOA MaNet, CoE EF/05/007 SymBioSys en KUL PFV/10/016 SymBioSys, START 1, several PhD, postdoctoral, and fellow grants); 2) the Flemish government; the FWO: PhD/postdoctoral grants, projects, G.0318.05 (subfunctionalization), G.0553.06 (VitamineD), G.0302.07 (SVM/Kernel), research communities (ICCoS, ANMMM, MLDM), G.0733.09 (3UTR), G.082409 (EGFR); 3) the IWT: PhD grants, Silicos; SBO-BioFrame, SBO-MoKa, TBM-IOTA3; 4) FOD: cancer plans; 5) IBBT; and 6) the Belgian Federal Science Policy Office (IUAP P6/25 [BioMaGNet, Bioinformatics and Modeling: from Genomes to Networks, 2007–2011]); and EU-RTD (ERNSI: European Research Network on System Identification; FP7-HEALTH CHeartED).

The authors thank Katrien Drijkoningen, Katrien Luyten, Rieta Van Bree, Dr. Veronika Beck, Dr. Sabine Jourdain and Dr. Goedele Paternot for technical assistance in the experiment.

Corresponding author: Thomas D'Hooghe, MD, PhD, Leuven University Fertility Center, Department of Obstetrics and Gynecology, UZ Gasthuisberg, 3000 Leuven, Belgium; e-mail: thomas.dhooghe@uz.kuleuven.ac.be.

Financial Disclosure The authors did not report any potential conflicts of interest.

© 2012 by The American College of Obstetricians and Gynecologists.