Diagnostic accuracy of plasma microRNA as a potential biomarker for detection of endometriosis

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This case-control study evaluated plasma microRNA expression in 50 women, finding that specific miRNAs exhibit moderate to acceptable diagnostic accuracy for endometriosis detection.

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This case-control study evaluated the diagnostic potential of plasma microRNAs for endometriosis by analyzing expression levels in 25 affected women compared to 25 healthy controls. Using quantitative reverse transcription polymerase chain reaction, researchers identified significant differential expression patterns among 16 specific miRNAs, with sensitivity ranging from 64.0% to 88.0% and specificity between 56.0% and 88.0%. The area under the curve values varied from 0.619 to 0.846, indicating that these molecular markers offer moderate to acceptable accuracy for detecting the disease without invasive surgery. This paper is centrally about endometriosis — specifically investigating non-invasive plasma biomarkers as an alternative or adjunct to laparoscopic diagnosis.

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Abstract

Endometriosis is a complex condition with a wide range of clinical manifestations, presenting significant challenges, particularly for young women. Its diverse and often perplexing presentations pose difficulties within the medical community. Laparoscopy remains the gold-standard diagnostic tool for endometriosis. However, alternative diagnostic methods are valuable for monitoring disease progression, assessing the likelihood of recurrence, reducing the need for surgical procedures, and facilitating timely decisions regarding fertility concerns. Recent research highlights the potential of microRNAs (miRNAs) as an alternative diagnostic test for endometriosis. A case-control study was conducted at the infertility unit of Arash Women's Hospital, involving 50 female participants, 25 with endometriosis and 25 without it. Plasma samples were collected and analyzed for the expression levels of 16 miRNAs using quantitative reverse transcription polymerase chain reaction (qRT-PCR). Diagnostic accuracy measures were evaluated to establish a reliable and comparable diagnostic framework. Compared to the control group, downregulation of 11 miRNAs and upregulation of 5 miRNAs were observed in the case group. Regarding expression patterns, evidence from this study indicates that half of the evaluated miRNAs fall into the high-agreement category with similar studies. Sensitivity (SN) of the evaluated miRNAs ranged from 64.0% to 88.0%, while specificity (SP) ranged from 56.0% to 88.0%. The area under the curve (AUC) was reported between 0.619 (miR-135a) and 0.846 (miR-340). These findings suggest that the evaluated miRNAs demonstrate moderate to acceptable diagnostic accuracy for endometriosis.
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Abstract Endometriosis is a complex condition with a wide range of clinical manifestations, presenting significant challenges, particularly for young women. Its diverse and often perplexing presentations pose difficulties within the medical community. Laparoscopy remains the gold-standard diagnostic tool for endometriosis. However, alternative diagnostic methods are valuable for monitoring disease progression, assessing the likelihood of recurrence, reducing the need for surgical procedures, and facilitating timely decisions regarding fertility concerns. Recent research highlights the potential of microRNAs (miRNAs) as an alternative diagnostic test for endometriosis. A case-control study was conducted at the infertility unit of Arash Women’s Hospital, involving 50 female participants, 25 with endometriosis and 25 without it. Plasma samples were collected and analyzed for the expression levels of 16 miRNAs using quantitative reverse transcription polymerase chain reaction (qRT-PCR). Diagnostic accuracy measures were evaluated to establish a reliable and comparable diagnostic framework. Compared to the control group, downregulation of 11 miRNAs and upregulation of 5 miRNAs were observed in the case group. Regarding expression patterns, evidence from this study indicates that half of the evaluated miRNAs fall into the high-agreement category with similar studies. Sensitivity (SN) of the evaluated miRNAs ranged from 64.0% to 88.0%, while specificity (SP) ranged from 56.0% to 88.0%. The area under the curve (AUC) was reported between 0.619 (miR-135a) and 0.846 (miR-340). These findings suggest that the evaluated miRNAs demonstrate moderate to acceptable diagnostic accuracy for endometriosis. Acknowledgments We extend our gratitude to all those who have dedicated their time and energy to this study, with special mention to the esteemed colleagues at Arash Hospital, the professors of Tehran University of Medical Sciences, and the respected Professor Abbasali Keshtkar, whose exceptional contributions to the methodology and statistical aspects were invaluable. Ethics approval The present study was designed as a predetermined investigation and was approved by the institutional review board (IRB) of Tehran University of Medical Sciences under reference number 46868. Approval was granted by the ethics committee of this university with the assigned code IR.TUMS.MEDICINE.REC.1399.009. The article was written in accordance with the standards for reporting diagnostic accuracy studies (STARD) guidelines (Mitchell et al. Citation2008). Disclosure statement The authors of this study have no affiliations or financial interests with any companies mentioned in the test methods or elsewhere in the paper. Furthermore, there are no conflicts of interest to report. Authors’ contributions Project administration: NT; Conceptualization, methodology: FA; Validation: AM; Supervision, writing – review & editing: TR; Methodology, formal Analysis: MS; Investigation, data curation: FH; Investigation, software, writing – original draft, resources: SDM. Investigation, resources: ShZh; Validation and supervision; SA. Data availability statement All data pertaining to this study, including information gathering and analysis, may be disclosed and made accessible for review at any time, provided that doing so does not violate any university regulations.

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Condition tags

endometriosisinfertility

MeSH descriptors

Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis

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pubmed
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