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腹泻型肠易激综合征的转录组模块发现:一种因果网络推断方法。

Transcriptomic Module Discovery of Diarrhea-Predominant Irritable Bowel Syndrome: A Causal Network Inference Approach.

机构信息

Data Science Unit, National Institute of Gastroenterology-IRCCS "Saverio de Bellis", 70013 Castellana Grotte, Bari, Italy.

Functional Gastrointestinal Disorders Research Group, National Institute of Gastroenterology-IRCCS "Saverio de Bellis", 70013 Castellana Grotte, Bari, Italy.

出版信息

Int J Mol Sci. 2024 Aug 28;25(17):9322. doi: 10.3390/ijms25179322.

Abstract

Irritable bowel syndrome with diarrhea (IBS-D) is the most prevalent subtype of IBS, characterized by chronic gastrointestinal symptoms in the absence of identifiable pathological findings. This study aims to investigate the molecular mechanisms underlying IBS-D using transcriptomic data. By employing causal network inference methods, we identify key transcriptomic modules associated with IBS-D. Utilizing data from public databases and applying advanced computational techniques, we uncover potential biomarkers and therapeutic targets. Our analysis reveals significant molecular alterations that affect cellular functions, offering new insights into the complex pathophysiology of IBS-D. These findings enhance our understanding of the disease and may foster the development of more effective treatments.

摘要

腹泻型肠易激综合征(IBS-D)是最常见的 IBS 亚型,其特征是慢性胃肠道症状,但不存在可识别的病理发现。本研究旨在使用转录组学数据来探究 IBS-D 的分子机制。通过采用因果网络推断方法,我们确定了与 IBS-D 相关的关键转录组模块。利用公共数据库中的数据并应用先进的计算技术,我们发现了潜在的生物标志物和治疗靶点。我们的分析揭示了影响细胞功能的显著分子变化,为 IBS-D 的复杂病理生理学提供了新的见解。这些发现增进了我们对该疾病的理解,并可能促进更有效的治疗方法的发展。

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