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期刊来源：Nat Med

原文链接：https://doi.org/10.1038/s41591-024-02963-2

摘要内容如下：

尽管癌症微生物组研究取得了实质性进展，但公认的混杂因素和绝对微生物组量化方面的进展仍未得到充分利用。这引起了对潜在虚假关联的担忧。在此，我们研究了589名处于不同结直肠癌（CRC）阶段的患者的粪便微生物群，并将观察结果与多达15项已发表的研究（共4，439名患者和对照）进行比较。使用基于16S核糖体RNA扩增子测序的定量微生物组分析，结合严格的混杂因素控制，我们将转运时间、粪便钙卫蛋白（肠道炎症）和身体质量指数确定为主要的微生物协变量，取代了CRC诊断组解释的差异。当控制这些协变量时，公认的微生物组CRC靶标，如具核梭杆菌，与CRC诊断组（健康、腺瘤和癌）没有显著关联。相反，阴道厌氧球菌、肺炎阿利斯特菌、微小小单胞菌、厌氧消化链球菌、解糖卟啉单胞菌和中间普氏菌的相关性仍然很强，突出了它们未来的靶标潜力。最后，对照个体（年龄22-80岁，平均57.7岁，标准差11.3）符合结肠镜检查的标准（例如，通过阳性粪便免疫化学试验），但没有结肠病变，这些个体富集了菌群失调的类杆菌2肠型，强调了在癌症微生物组研究中定义健康对照的不确定性。总之，这些结果表明，在CRC微生物组研究中，定量微生物组分析和协变量控制对于生物标志物鉴定的重要性。

英文原文如下：

Abstracts

Despite substantial progress in cancer microbiome research, recognized confounders and advances in absolute microbiome quantification remain underused; this raises concerns regarding potential spurious associations. Here we study the fecal microbiota of 589 patients at different colorectal cancer (CRC) stages and compare observations with up to 15 published studies (4,439 patients and controls total). Using quantitative microbiome profiling based on 16S ribosomal RNA amplicon sequencing, combined with rigorous confounder control, we identified transit time, fecal calprotectin (intestinal inflammation) and body mass index as primary microbial covariates, superseding variance explained by CRC diagnostic groups. Well-established microbiome CRC targets, such as Fusobacterium nucleatum, did not significantly associate with CRC diagnostic groups (healthy, adenoma and carcinoma) when controlling for these covariates. In contrast, the associations of Anaerococcus vaginalis, Dialister pneumosintes, Parvimonas micra, Peptostreptococcus anaerobius, Porphyromonas asaccharolytica and Prevotella intermedia remained robust, highlighting their future target potential. Finally, control individuals (age 22-80 years, mean 57.7 years, standard deviation 11.3) meeting criteria for colonoscopy (for example, through a positive fecal immunochemical test) but without colonic lesions are enriched for the dysbiotic Bacteroides2 enterotype, emphasizing uncertainties in defining healthy controls in cancer microbiome research. Together, these results indicate the importance of quantitative microbiome profiling and covariate control for biomarker identification in CRC microbiome studies.

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