Serum microRNAs as diagnostic markers of endometriosis: a comprehensive array-based analysis
To investigate serum microRNAs (miRNAs) in women with endometriosis. Case-control study. University hospital. Women with (n = 24) and without (n = 24) endometriosis. Serum samples were obtained from surgically diagnosed subjects. miRNA from women with without endometriosis were used for microarray p...
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| Published in: | Fertility and sterility Vol. 106; no. 2; pp. 402 - 409 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
United States
01.08.2016
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| Subjects: | |
| ISSN: | 1556-5653 |
| Online Access: | Get more information |
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| Summary: | To investigate serum microRNAs (miRNAs) in women with endometriosis.
Case-control study.
University hospital.
Women with (n = 24) and without (n = 24) endometriosis.
Serum samples were obtained from surgically diagnosed subjects.
miRNA from women with without endometriosis were used for microarray profiling and confirmed by means of quantitative real-time polymerase chain reaction (qRT-PCR). Receiver operating characteristic (ROC) analysis was performed on differentially expressed miRNAs.
miR-3613-5p, miR-6755-3p were down-regulated and miR-125b-5p, miR-150-5p, miR-342-3p, miR-143-3p, miR-145-5p, miR-500a-3p, miR-451a, miR-18a-5p were up-regulated more than 10-fold in the microarray. These results were confirmed with the use of qRT-PCR. Among the differentially expressed miRNAs, miR-125b-5p expression levels had the highest area under the ROC curve (AUC). The maximum AUC score of 1.000 was achieved when combining miR-125b-5p, miR-451a, and miR-3613-5p with the use of a logistic regression model.
We identified several miRNAs in serum that distinguished subjects with endometriosis from those without. miR-125b-5p had the greatest potential as a single diagnostic biomarker. A combination of that miRNA with miR-451a and miR-3613-5p further improved diagnostic performance. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1556-5653 |
| DOI: | 10.1016/j.fertnstert.2016.04.013 |