炎症性肠病(IBD)在了解其病因和诊断方面仍然具有挑战性。治疗,监测患者。现代诊断结合了生物标志物,成像,和内窥镜方法。常见的生物标志物,如CRP和粪便钙卫蛋白,虽然宝贵的工具,有局限性,并不完全特定于IBD。现有标记的局限性和内窥镜程序的侵入性凸显了发现和实施新标记的必要性。有了理想的生物标志物,我们可以预测疾病发展的风险,以及对特定疗法的反应的可能性,这对于阐明该疾病的发病机理具有重要意义。机器学习领域的最新研究,蛋白质组学,表观遗传学,和肠道微生物群提供了对疾病发病机制的进一步了解,也揭示了新的生物标志物。新标记,如BAFF,PGE-妈妈,制瘤素M,microRNA面板,αvβ6抗体,和S100A12从大便,越来越多的人被识别,αvβ6抗体和制瘤素M可能接近于临床实践。然而,某些标志物的特异性仍然存在问题。此外,使用昂贵且不易获得的技术来检测新标记,比如microRNA,代表了在临床实践中广泛使用的限制。然而,需要非侵入性,关于IBD治疗的复杂性和整体管理,综合标志物变得越来越重要。
Inflammatory bowel diseases (IBD) remain challenging in terms of understanding their causes and in terms of diagnosing, treating, and monitoring patients. Modern diagnosis combines biomarkers, imaging, and endoscopic methods. Common biomarkers like CRP and fecal calprotectin, while invaluable tools, have limitations and are not entirely specific to IBD. The limitations of existing markers and the invasiveness of endoscopic procedures highlight the need to discover and implement new markers. With an ideal biomarker, we could predict the risk of disease development, as well as the possibility of response to a particular therapy, which would be significant in elucidating the pathogenesis of the disease. Recent research in the fields of machine learning, proteomics, epigenetics, and gut microbiota provides further insight into the pathogenesis of the disease and is also revealing new biomarkers. New markers, such as BAFF, PGE-MUM, oncostatin M, microRNA panels, αvβ6 antibody, and S100A12 from stool, are increasingly being identified, with αvβ6 antibody and oncostatin M being potentially close to being presented into clinical practice. However, the specificity of certain markers still remains problematic. Furthermore, the use of expensive and less accessible technology for detecting new markers, such as microRNAs, represents a limitation for widespread use in clinical practice. Nevertheless, the need for non-invasive, comprehensive markers is becoming increasingly important regarding the complexity of treatment and overall management of IBD.