Objective Gut microbiome composition is associated with multiple diseases, but relatively little is known about its relationship with long-term outcome measures. While gut dysbiosis has been linked to mortality risk in the general population, the relationship with overall survival in specific diseases has not been extensively studied. In the current study, we present results from an in-depth analysis of the relationship between gut dysbiosis and all-cause and cause-specific mortality in the setting of solid organ transplant recipients (SOTR). Design We analysed 1337 metagenomes derived from faecal samples of 766 kidney, 334 liver, 170 lung and 67 heart transplant recipients part of the TransplantLines Biobank and Cohort—a prospective cohort study including extensive phenotype data with 6.5 years of follow-up. To analyze gut dysbiosis, we included an additional 8208 metagenomes from the general population of the same geographical area (northern Netherlands). Multivariable Cox regression and a machine learning algorithm were used to analyse the association between multiple indicators of gut dysbiosis, including individual species abundances, and all-cause and cause-specific mortality. Results We identified two patterns representing overall microbiome community variation that were associated with both all-cause and cause-specific mortality. The gut microbiome distance between each transplantation recipient to the average of the general population was associated with all-cause mortality and death from infection, malignancy and cardiovascular disease. A multivariable Cox regression on individual species abundances identified 23 bacterial species that were associated with all-cause mortality, and by applying a machine learning algorithm, we identified a balance (a type of log-ratio) consisting of 19 out of the 23 species that were associated with all-cause mortality. Conclusion Gut dysbiosis is consistently associated with mortality in SOTR. Our results support the observations that gut dysbiosis is associated with long-term survival. Since our data do not allow us to infer causality, more preclinical research is needed to understand mechanisms before we can determine whether gut microbiome-directed therapies may be designed to improve long-term outcomes. Data are available on reasonable request. The raw microbiome sequencing data and basic phenotypes used in this study are available at the European Genome-Phenome Archive under accession numbers EGAD00001008907 (), EGAS00001006257 () and EGAS00001006258 (). Due to patient confidentiality, the clinical datasets associated with the metagenomic datasets are available on request to the University Medical Centre Groningen. Access to this clinical dataset requires a minimal access procedure consisting of a request per email (datarequest.transplantlines@umcg.nl) for a data access form. A response will be provided within two working weeks. This access procedure is to ensure that the data are being requested for research/scientific purposes only and thus comply with the informed consent signed by TransplantLines participants, which specifies that the collected data will not be used for commercial purposes.

中文翻译：

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肠道菌群失调的多项指标可预测实体器官移植受者的全因和特定原因死亡率


目的 肠道微生物组组成与多种疾病相关，但对其与长期结果指标的关系知之甚少。虽然肠道菌群失调与普通人群的死亡风险有关，但其与特定疾病总生存率的关系尚未得到广泛研究。在当前的研究中，我们提出了对实体器官移植受者（SOTR）肠道菌群失调与全因和特定原因死亡率之间关系的深入分析结果。设计 我们分析了 1337 个宏基因组，这些样本来自 TransplantLines 生物库和队列中的 766 个肾脏、334 个肝脏、170 个肺和 67 个心脏移植受者的粪便样本，这是一项前瞻性队列研究，包括广泛的表型数据和 6.5 年的随访。为了分析肠道菌群失调，我们纳入了来自同一地理区域（荷兰北部）一般人群的额外 8208 个宏基因组。使用多变量 Cox 回归和机器学习算法来分析肠道菌群失调的多个指标之间的关联，包括个体物种丰度以及全因和特定原因死亡率。结果我们确定了代表总体微生物群落变异的两种模式，它们与全因死亡率和特定原因死亡率相关。每个移植接受者的肠道微生物组与一般人群平均水平之间的距离与全因死亡率以及感染、恶性肿瘤和心血管疾病导致的死亡相关。 对单个物种丰度的多变量 Cox 回归确定了与全因死亡率相关的 23 种细菌物种，并通过应用机器学习算法，我们确定了由 23 种细菌中的 19 种组成的平衡（一种对数比）与全因死亡率相关。结论 肠道菌群失调与 SOTR 患者的死亡率始终相关。我们的结果支持肠道菌群失调与长期生存相关的观察结果。由于我们的数据不允许我们推断因果关系，因此需要进行更多的临床前研究来了解机制，然后才能确定肠道微生物组导向的疗法是否可以改善长期结果。可根据合理要求提供数据。本研究中使用的原始微生物组测序数据和基本表型可在欧洲基因组-表型档案馆获取，登录号为 EGAD00001008907 ()、EGAS00001006257 () 和 EGAS00001006258 ()。由于患者的机密性，与宏基因组数据集相关的临床数据集可根据要求向格罗宁根大学医学中心提供。访问此临床数据集需要一个最小的访问程序，其中包括每封电子邮件 (datarequest.transplantlines@umcg.nl) 的数据访问表格请求。我们将在两个工作周内提供答复。此访问程序是为了确保所请求的数据仅用于研究/科学目的，从而遵守 TransplantLines 参与者签署的知情同意书，该同意书规定收集的数据不会用于商业目的。