Fig. 5: Prediction of health status using gut species signatures.

a Receiver operating characteristic (ROC) analysis of the classification of case/control status using the random forest model trained by 277 universal gut species signatures. The classification performance of the model was assessed by the area under the ROC curve (AUC). The AUC values and 95% confidence intervals (CIs) are shown. b The 20 most discriminant species-level signatures in the model classifying diseased and control individuals. The bar lengths indicate the importance of the variables. c Histogram showing the distribution of the GMHI in diseased and control individuals. d ROC analysis of the classification of case/control status in independent public cohorts using the random forest trained by the original cohorts. e ROC analysis of the classification of patients with autoimmune diseases and healthy controls. BD bipolar depression, CRC colorectal cancer, ESRD end-stage renal disease, RA rheumatoid arthritis, SLE systemic lupus erythematosus, SS primary Sjögren’s syndrome.