Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna A-1090, Austria.
Exp Biol Med (Maywood). 2020 Mar;245(5):437-447. doi: 10.1177/1535370220903270. Epub 2020 Feb 4.
Endometriosis affects up to 10% of women of childbearing age, causing symptoms that can include chronic pelvic pain and reduced fertility. The symptoms are not specific to the disease and can be confused with other gynecological conditions or normal menstruation. Currently, the disease can be only definitively diagnosed by laparoscopy, as no clinically accepted biomarker exists. Biomarker discovery can either follow a hypothesis-driven approach selecting targets to be tested based on current knowledge of the disease, or take an unbiased high-throughput screening “omics” approach, such as transcriptomics or proteomics, to identify markers that are unique or elevated in accessible bodily fluids of patients with the disease. Numerous studies have been conducted using these approaches to try and identify endometriosis biomarkers, but variabilities in study design, cohort selection, and analysis, together with the fact that most studies were small-scale, have made independent validation of biomarker candidates difficult. Therefore, efforts are underway to standardize cohort selection, patient data, and sample collection to allow better cross-study comparisons. Large scale multi-center studies using this standardized approach are necessary to validate existing endometriosis biomarker candidates and uncover potential new markers. Given the complexity and heterogeneity of the disease, it is likely that a panel of biomarkers will be necessary to diagnose and categorize endometriosis.
Endometriosis is a common disease affecting reproductive age women, which is associated with chronic pain and reduced fertility reducing the quality of life of many women. Definitive diagnosis requires invasive laparoscopic surgery creating a high barrier to diagnosis that can delay the onset of treatment significantly. Clinically approved biomarkers of endometriosis are currently lacking, making the discovery and validation of biomarkers that would lead to earlier diagnosis a priority for improving treatment of the disease.
子宫内膜异位症影响多达 10%的育龄妇女，其症状包括慢性盆腔疼痛和生育能力降低。这些症状并非该疾病所特有，可能与其他妇科疾病或正常月经混淆。目前，由于没有临床上可接受的生物标志物，该疾病只能通过腹腔镜检查来明确诊断。生物标志物的发现可以采用基于疾病现有知识选择目标进行测试的假设驱动方法，也可以采用无偏高通量筛选“组学”方法，如转录组学或蛋白质组学，以识别在疾病患者可及的体液中独特或升高的标志物。已经进行了许多研究来尝试识别子宫内膜异位症的生物标志物，但研究设计、队列选择和分析的变异性，以及大多数研究规模较小，使得独立验证生物标志物候选物变得困难。因此，正在努力标准化队列选择、患者数据和样本采集，以允许更好地进行跨研究比较。使用这种标准化方法的大规模多中心研究对于验证现有的子宫内膜异位症生物标志物候选物和发现潜在的新标志物是必要的。鉴于该疾病的复杂性和异质性，可能需要一组生物标志物来诊断和分类子宫内膜异位症。
子宫内膜异位症是一种常见的疾病，影响育龄妇女，与慢性疼痛和生育能力降低有关，降低了许多妇女的生活质量。明确诊断需要侵入性腹腔镜手术，这大大增加了诊断的难度，可能会导致治疗的延迟。目前缺乏子宫内膜异位症的临床认可生物标志物，因此发现和验证能够更早诊断的生物标志物对于改善疾病的治疗至关重要。
