微生物标志物在预测结直肠癌（CRC）方面具有显著的潜力。本研究旨在评估多模式微生物标志物、多界物种、基因和单核苷酸变异（SNV）在检测癌前腺瘤中的诊断能力。我们通过xMarkerFinder对750个样本的全基因组测序数据进行交叉队列分析，以识别与腺瘤相关的微生物多模式标志物。我们的数据显示，真菌物种在区分腺瘤和对照组方面的曲线下面积（AUC）达到0.71，表现优于其他界的物种。包括具有同义突变的深色SNV在内的微生物SNV显示出最强的诊断能力，AUC值为0.89，灵敏度为0.79，特异度为0.85，马修斯相关系数（MCC）为0.74。SNV生物标志物在三个独立的验证队列中也表现出优异的性能（AUC分别为0.83、0.82、0.76；灵敏度分别为1.0、0.72、0.93；特异度分别为0.67、0.81、0.67，MCC分别为0.69、0.83、0.72），对腺瘤具有较高的疾病特异性。进一步支持上述结果的功能分析显示，细菌与真菌之间的多界关联更为频繁，并在腺瘤中显示出生物量感应、嘌呤和丁酸代谢的异常，这些结果在新招募的队列中通过qRT-PCR进行了验证。因此，这些数据扩展了我们对肠道微生物组与腺瘤相关的多模式变化的认识，并为CRC的早期检测提供了微生物SNV的理论基础。

Microbial signatures show remarkable potentials in predicting colorectal cancer (CRC). This study aimed to evaluate the diagnostic powers of multimodal microbial signatures, multi-kingdom species, genes, and single-nucleotide variants (SNVs) for detecting precancerous adenomas. We performed cross-cohort analyses on whole metagenome sequencing data of 750 samples via xMarkerFinder to identify adenoma-associated microbial multimodal signatures. Our data revealed that fungal species outperformed species from other kingdoms with an area under the ROC curve (AUC) of 0.71 in distinguishing adenomas from controls. The microbial SNVs, including dark SNVs with synonymous mutations, displayed the strongest diagnostic capability with an AUC value of 0.89, sensitivity of 0.79, specificity of 0.85, and Matthews correlation coefficient (MCC) of 0.74. SNV biomarkers also exhibited outstanding performances in three independent validation cohorts (AUCs = 0.83, 0.82, 0.76; sensitivity = 1.0, 0.72, 0.93; specificity = 0.67, 0.81, 0.67, MCCs = 0.69, 0.83, 0.72) with high disease specificity for adenoma. In further support of the above results, functional analyses revealed more frequent inter-kingdom associations between bacteria and fungi, and abnormalities in quorum sensing, purine and butanoate metabolism in adenoma, which were validated in a newly recruited cohort via qRT-PCR. Therefore, these data extend our understanding of adenoma-associated multimodal alterations in the gut microbiome and provide a rationale of microbial SNVs for the early detection of CRC.