Results
| PMID | 22736326 |
| Gene Name | VEGFA |
| Condition | Endometriosis |
| Association |
Associated |
| Population size | 353 |
| Population details | 353 (121 controls without endometriosis at laparoscopy and from 232 women with endometriosis (minimal-mild n = 148; moderate-severe n = 84)) |
| Sex | Female |
| Associated genes | Annexin V, VEGF, CA-125 and sICAM-1, glycodelin |
| Other associated phenotypes |
Endometriosis |
|
Hum Reprod. 2012 Sep;27(9):2698-711. doi: 10.1093/humrep/des234. Epub 2012 Jun Vodolazkaia, A| El-Aalamat, Y| Popovic, D| Mihalyi, A| Bossuyt, X| Kyama, C M| Fassbender, A| Bokor, A| Schols, D| Huskens, D| Meuleman, C| Peeraer, K| Tomassetti, C| Gevaert, O| Waelkens, E| Kasran, A| De Moor, B| D'Hooghe, T M Leuven University Fertility Centre, Department of Obstetrics and Gynaecology, University Hospital Gasthuisberg, Leuven, Belgium. BACKGROUND: At present, the only way to conclusively diagnose endometriosis is laparoscopic inspection, preferably with histological confirmation. This contributes to the delay in the diagnosis of endometriosis which is 6-11 years. So far non-invasive diagnostic approaches such as ultrasound (US), MRI or blood tests do not have sufficient diagnostic power. Our aim was to develop and validate a non-invasive diagnostic test with a high sensitivity (80% or more) for symptomatic endometriosis patients, without US evidence of endometriosis, since this is the group most in need of a non-invasive test. METHODS: A total of 28 inflammatory and non-inflammatory plasma biomarkers were measured in 353 EDTA plasma samples collected at surgery from 121 controls without endometriosis at laparoscopy and from 232 women with endometriosis (minimal-mild n = 148; moderate-severe n = 84), including 175 women without preoperative US evidence of endometriosis. Surgery was done during menstrual (n = 83), follicular (n = 135) and luteal (n = 135) phases of the menstrual cycle. For analysis, the data were randomly divided into an independent training (n = 235) and a test (n = 118) data set. Statistical analysis was done using univariate and multivariate (logistic regression and least squares support vector machines (LS-SVM) approaches in training- and test data set separately to validate our findings. RESULTS: In the training set, two models of four biomarkers (Model 1: annexin V, VEGF, CA-125 and glycodelin; Model 2: annexin V, VEGF, CA-125 and sICAM-1) analysed in plasma, obtained during the menstrual phase, could predict US-negative endometriosis with a high sensitivity (81-90%) and an acceptable specificity (68-81%). The same two models predicted US-negative endometriosis in the independent validation test set with a high sensitivity (82%) and an acceptable specificity (63-75%). CONCLUSIONS: In plasma samples obtained during menstruation, multivariate analysis of four biomarkers (annexin V, VEGF, CA-125 and sICAM-1/or glycodelin) enabled the diagnosis of endometriosis undetectable by US with a sensitivity of 81-90% and a specificity of 63-81% in independent training- and test data set. The next step is to apply these models for preoperative prediction of endometriosis in an independent set of patients with infertility and/or pain without US evidence of endometriosis, scheduled for laparoscopy. Mesh Terms: Adult| Biomarkers/*metabolism| Case-Control Studies| Edetic Acid/metabolism| Endometriosis/*blood/*diagnosis| Female| Humans| Inflammation| Laparoscopy| Least-Squares Analysis| Menstrual Cycle| Middle Aged| Models, Statistical| ROC Curve| Re |
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