Jiang Puzi, Wu Sicheng, Luo Qibin, Zhao Xing-Ming, Chen Wei-Hua
Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, Freising, Germany.
mSystems. 2021 May 4;6(3):e00112-21. doi: 10.1128/mSystems.00112-21.
Common intestinal diseases such as Crohn's disease (CD), ulcerative colitis (UC), and colorectal cancer (CRC) share clinical symptoms and altered gut microbes, necessitating cross-disease comparisons and the use of multidisease models. Here, we performed meta-analyses on 13 fecal metagenome data sets of the three diseases. We identified 87 species and 65 pathway markers that were consistently changed in multiple data sets of the same diseases. According to their overall trends, we grouped the disease-enriched marker species into disease-specific and disease-common clusters and revealed their distinct phylogenetic relationships; species in the CD-specific cluster were phylogenetically related, while those in the CRC-specific cluster were more distant. Strikingly, UC-specific species were phylogenetically closer to CRC, likely because UC patients have higher risk of CRC. Consistent with their phylogenetic relationships, marker species had similar within-cluster and different between-cluster metabolic preferences. A portion of marker species and pathways correlated with an indicator of leaky gut, suggesting a link between gut dysbiosis and human-derived contents. Marker species showed more coordinated changes and tighter inner-connections in cases than the controls, suggesting that the diseased gut may represent a stressed environment and pose stronger selection on gut microbes. With the marker species and pathways, we constructed four high-performance (including multidisease) models with an area under the receiver operating characteristic curve (AUROC) of 0.87 and true-positive rates up to 90%, and explained their putative clinical applications. We identified consistent microbial alterations in common intestinal diseases, revealed metabolic capacities and the relationships among marker bacteria in distinct states, and supported the feasibility of metagenome-derived multidisease diagnosis. Gut microbes have been identified as potential markers in distinguishing patients from controls in colorectal cancer, ulcerative colitis, and Crohn's disease individually, whereas there lacks a systematic analysis to investigate the exclusive microbial shifts of these enteropathies with similar clinical symptoms. Our meta-analysis and cross-disease comparisons identified consistent microbial alterations in each enteropathy, revealed microbial ecosystems among marker bacteria in distinct states, and demonstrated the necessity and feasibility of metagenome-based multidisease classifications. To the best of our knowledge, this is the first study to construct multiclass models for these common intestinal diseases.
常见的肠道疾病，如克罗恩病（CD）、溃疡性结肠炎（UC）和结直肠癌（CRC），具有共同的临床症状且肠道微生物群发生改变，因此需要进行跨疾病比较并使用多疾病模型。在此，我们对这三种疾病的13个粪便宏基因组数据集进行了荟萃分析。我们鉴定出87个物种和65条通路标志物，它们在同一疾病的多个数据集中持续发生变化。根据其总体趋势，我们将疾病富集的标志物物种分为疾病特异性和疾病共同性簇，并揭示了它们不同的系统发育关系；CD特异性簇中的物种在系统发育上相关，而CRC特异性簇中的物种关系更为疏远。引人注目的是，UC特异性物种在系统发育上更接近CRC，可能是因为UC患者患CRC的风险更高。与它们的系统发育关系一致，标志物物种在簇内具有相似的代谢偏好，而在簇间则不同。一部分标志物物种和通路与肠道渗漏指标相关，表明肠道微生物失调与人体来源物质之间存在联系。与对照组相比，标志物物种在病例中表现出更协调的变化和更紧密的内部联系，这表明患病肠道可能代表一个应激环境，对肠道微生物构成更强的选择。利用标志物物种和通路，我们构建了四个高性能（包括多疾病）模型，其受试者工作特征曲线下面积（AUROC）为0.87，真阳性率高达90%，并解释了它们可能的临床应用。我们在常见肠道疾病中鉴定出一致的微生物改变，揭示了不同状态下标志物细菌的代谢能力及其相互关系，并支持基于宏基因组的多疾病诊断的可行性。肠道微生物已被确定为在结直肠癌、溃疡性结肠炎和克罗恩病中区分患者与对照的潜在标志物，然而缺乏系统分析来研究这些具有相似临床症状的肠道疾病的独特微生物变化。我们的荟萃分析和跨疾病比较确定了每种肠道疾病中一致的微生物改变，揭示了不同状态下标志物细菌之间的微生物生态系统，并证明了基于宏基因组的多疾病分类的必要性和可行性。据我们所知，这是第一项为这些常见肠道疾病构建多类模型的研究。
