Omics-based novel strategies in the diagnosis of endometriosis

Mohammad Samare‐Najaf, Seyed Ali Razavinasab, Ali Samareh, Navid Jamali
Critical reviews in clinical laboratory sciences · 2023 · vol. 61(3) , pp. 205–225 · doi:10.1080/10408363.2023.2270736 · PMID:37878077 · W4387931810
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This review examines omics-based biomarkers from 2020 onward, finding that genomics, epigenomics, transcriptomics, proteomics, and metabolomics offer potential noninvasive strategies for endometriosis diagnosis, prognosis, and staging.

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Abstract

Endometriosis, an enigmatic and chronic disorder, is considered a debilitating condition despite being benign. Globally, this gynecologic disorder affects up to 10% of females of reproductive age, impacting almost 190 million individuals. A variety of genetic and environmental factors are involved in endometriosis development, hence the pathophysiology and etiology of endometriosis remain unclear. The uncertainty of the etiology of the disease and its complexity along with nonspecific symptoms have led to misdiagnosis or lack of diagnosis of affected people. Biopsy and laparoscopy are referred to as the gold standard for endometriosis diagnosis. However, the invasiveness of the procedure, the unnecessary operation in disease-free women, and the dependence of the reliability of diagnosis on experience in this area are considered the most significant limitations. Therefore, continuous studies have attempted to offer a noninvasive and reliable approach. The recent advances in modern technologies have led to the generation of large-scale biological data sets, known as -omics data, resulting in the proceeding of the -omics century in biomedical sciences. Thereby, the present study critically reviews novel and noninvasive biomarkers that are based on -omics approaches from 2020 onward. The findings reveal that biomarkers identified based on genomics, epigenomics, transcriptomics, proteomics, and metabolomics are potentially able to diagnose endometriosis, predict prognosis, and stage patients, and potentially, in the near future, a multi-panel of these biomarkers will generate clinical benefits.

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Condition tags

mesh:D004715endometriosis

MeSH descriptors

Biomarkers Biomarkers Biomarkers Biomarkers Biomarkers Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Endometriosis Genomics Genomics Genomics Genomics Genomics Metabolomics Metabolomics Metabolomics

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Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

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