Microbiome Program, Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA.
Division of Surgery Research, Department of Surgery, Mayo Clinic, Rochester, MN, 55905, USA.
Nat Commun. 2020 Sep 15;11(1):4635. doi: 10.1038/s41467-020-18476-8.
Providing insight into one's health status from a gut microbiome sample is an important clinical goal in current human microbiome research. Herein, we introduce the Gut Microbiome Health Index (GMHI), a biologically-interpretable mathematical formula for predicting the likelihood of disease independent of the clinical diagnosis. GMHI is formulated upon 50 microbial species associated with healthy gut ecosystems. These species are identified through a multi-study, integrative analysis on 4347 human stool metagenomes from 34 published studies across healthy and 12 different nonhealthy conditions, i.e., disease or abnormal bodyweight. When demonstrated on our population-scale meta-dataset, GMHI is the most robust and consistent predictor of disease presence (or absence) compared to α-diversity indices. Validation on 679 samples from 9 additional studies results in a balanced accuracy of 73.7% in distinguishing healthy from non-healthy groups. Our findings suggest that gut taxonomic signatures can predict health status, and highlight how data sharing efforts can provide broadly applicable discoveries.
从肠道微生物组样本中洞察一个人的健康状况是当前人类微生物组研究的一个重要临床目标。在此，我们引入了肠道微生物组健康指数（GMHI），这是一种具有生物学解释的数学公式，可以在不依赖临床诊断的情况下预测疾病的可能性。GMHI 是基于与健康肠道生态系统相关的 50 种微生物物种制定的。这些物种是通过对来自 34 项已发表研究的 4347 个人类粪便宏基因组进行多研究、综合分析确定的，这些研究涵盖了健康和 12 种不同的非健康状态，即疾病或异常体重。当在我们的人群规模元数据集上进行演示时，GMHI 是疾病存在（或不存在）的最稳健和一致的预测因子，与 α 多样性指数相比。在来自 9 项额外研究的 679 个样本上进行验证，结果表明 GMHI 在区分健康组和非健康组方面的平衡准确性为 73.7%。我们的研究结果表明，肠道分类特征可以预测健康状况，并强调了数据共享工作如何能够提供广泛适用的发现。
