Gut microbiota predicts the diagnosis of ulcerative colitis in Saudi children

M. E. El Mouzan, Ahmed A. Al Sarkhy, Asaad Assiri
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Abstract

BACKGROUND Ulcerative colitis (UC) is an immune-mediated chronic inflammatory condition with a worldwide distribution. Although the etiology of this disease is still unknown, the understanding of the role of the microbiota is becoming increasingly strong. AIM To investigate the predictive power of the gut microbiota for the diagnosis of UC in a cohort of newly diagnosed treatment-naïve Saudi children with UC. METHODS The study population included 20 children with a confirmed diagnosis of UC and 20 healthy controls. Microbial DNA was extracted and sequenced, and shotgun metagenomic analysis was performed for bacteria and bacteriophages. Biostatistics and bioinformatics demonstrated significant dysbiosis in the form of reduced alpha diversity, beta diversity, and significant difference of abundance of taxa between children with UC and control groups. The receiver operating characteristic curve, a probability curve, was used to determine the difference between the UC and control groups. The area under the curve (AUC) represents the degree of separability between the UC group and the control group. The AUC was calculated for all identified bacterial species and for bacterial species identified by the random forest classification algorithm as important potential biomarkers of UC. A similar method of AUC calculation for all bacteriophages and important species was used. RESULTS The median age and range were 14 (0.5-21) and 12.9 (6.8-16.3) years for children with UC and controls, respectively, and 40% and 35% were male for children with UC and controls, respectively. The AUC for all identified bacterial species was 89.5%. However, when using the bacterial species identified as important by random forest classification algorithm analysis, the accuracy increased to 97.6%. Similarly, the AUC for all the identified bacteriophages was 87.4%, but this value increased to 94.5% when the important bacteriophage biomarkers were used. CONCLUSION The very high to excellent AUCs of fecal bacterial and viral species suggest the potential use of noninvasive microbiota-based tests for the diagnosis of unusual cases of UC in children. In addition, the identification of important bacteria and bacteriophages whose abundance is reduced in children with UC suggests the potential of preventive and adjuvant microbial therapy for UC.
肠道微生物群可预测沙特儿童溃疡性结肠炎的诊断结果
背景溃疡性结肠炎(UC)是一种免疫介导的慢性炎症,分布于世界各地。虽然这种疾病的病因尚不清楚,但人们对微生物群的作用的认识却越来越深刻。目的 在一组新诊断的未经治疗的沙特 UC 儿童中,研究肠道微生物群对 UC 诊断的预测能力。方法 研究对象包括 20 名确诊为 UC 的儿童和 20 名健康对照组。对微生物 DNA 进行了提取和测序,并对细菌和噬菌体进行了枪式元基因组分析。生物统计学和生物信息学结果表明,UC 患儿与对照组之间存在明显的菌群失调,表现为α多样性和β多样性降低,类群丰度存在显著差异。接受者操作特征曲线(一种概率曲线)用于确定 UC 组和对照组之间的差异。曲线下面积(AUC)表示 UC 组与对照组之间的可分离性程度。AUC 是针对所有已确定的细菌种类以及通过随机森林分类算法确定为 UC 重要潜在生物标记物的细菌种类计算的。对所有噬菌体和重要菌种也采用了类似的 AUC 计算方法。结果 UC患儿和对照组患儿的中位年龄和范围分别为14(0.5-21)岁和12.9(6.8-16.3)岁,UC患儿和对照组患儿的男性比例分别为40%和35%。所有鉴定出的细菌种类的AUC为89.5%。然而,当使用随机森林分类算法分析确定的重要细菌种类时,准确率提高到了 97.6%。同样,所有鉴定出的噬菌体的 AUC 为 87.4%,但当使用重要的噬菌体生物标记物时,该值增至 94.5%。结论 粪便中细菌和病毒种类的AUC非常高甚至非常好,这表明基于微生物群的无创检验有可能用于儿童UC异常病例的诊断。此外,鉴定出 UC 患儿体内丰度降低的重要细菌和噬菌体表明,有可能对 UC 进行预防性和辅助性微生物治疗。
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