Division of Gastroenterology, University of Washington, Seattle, Washington, USA.
Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Hepatology. 2023 Dec 1;78(6):1843-1857. doi: 10.1097/HEP.0000000000000474. Epub 2023 May 25.
There is great interest in identifying microbiome features as reliable noninvasive diagnostic and/or prognostic biomarkers for non-cirrhotic NASH fibrosis. Several cross-sectional studies have reported gut microbiome features associated with advanced NASH fibrosis and cirrhosis, where the most prominent features are associated with cirrhosis. However, no large, prospectively collected data exist establishing microbiome features that discern non-cirrhotic NASH fibrosis, integrate the fecal metabolome as disease biomarkers, and are unconfounded by BMI and age.
Results from shotgun metagenomic sequencing performed on fecal samples prospectively collected from 279 US patients with biopsy-proven NASH (F1-F3 fibrosis) enrolled in the REGENERATE I303 study were compared to those from 3 healthy control cohorts and integrated with the absolute quantification of fecal bile acids. Microbiota beta-diversity was different, and BMI- and age-adjusted logistic regression identified 12 NASH-associated species. Random forest prediction models resulted in an AUC of 0.75-0.81 in a receiver operator characteristic analysis. In addition, specific fecal bile acids were significantly lower in NASH and correlated with plasma C4 levels. Microbial gene abundance analysis revealed 127 genes increased in controls, many involving protein synthesis, whereas 362 genes were increased in NASH many involving bacterial environmental responses (false discovery rate < 0.01). Finally, we provide evidence that fecal bile acid levels may be a better discriminator of non-cirrhotic NASH versus health than either plasma bile acids or gut microbiome features.
These results may have value as a set of baseline characteristics of non-cirrhotic NASH against which therapeutic interventions to prevent cirrhosis can be compared and microbiome-based diagnostic biomarkers identified.
人们对识别微生物组特征作为非肝硬化 NASH 纤维化的可靠非侵入性诊断和/或预后生物标志物非常感兴趣。几项横断面研究报告了与进展性 NASH 纤维化和肝硬化相关的肠道微生物组特征，其中最突出的特征与肝硬化有关。然而，尚无大型前瞻性收集的数据来确定可区分非肝硬化 NASH 纤维化的微生物组特征，将粪便代谢组整合为疾病生物标志物，并且不受 BMI 和年龄的影响。
对前瞻性收集的 279 名美国 NASH 患者（F1-F3 纤维化）粪便样本进行的 shotgun 宏基因组测序结果与 3 名健康对照组进行了比较，并与粪便胆汁酸的绝对定量相结合。微生物组β多样性不同，BMI 和年龄调整的逻辑回归确定了 12 种与 NASH 相关的物种。随机森林预测模型在接受者操作特征分析中产生了 0.75-0.81 的 AUC。此外，特定的粪便胆汁酸在 NASH 中显著降低，并与血浆 C4 水平相关。微生物基因丰度分析显示，对照中 127 个基因增加，许多涉及蛋白质合成，而 NASH 中增加了 362 个基因，许多涉及细菌环境反应（错误发现率 < 0.01）。最后，我们提供的证据表明，粪便胆汁酸水平可能是区分非肝硬化 NASH 与健康的更好指标，优于血浆胆汁酸或肠道微生物组特征。
这些结果可能具有作为非肝硬化 NASH 的基线特征的价值，可用于比较预防肝硬化的治疗干预措施，并确定基于微生物组的诊断生物标志物。
