失调
人口
比例危险模型
肠道菌群
死亡率
死因
队列
医学
疾病
微生物群
生物
内科学
免疫学
生物信息学
环境卫生
作者
J. Casper Swarte,Shuyan Zhang,Lianne M. Nieuwenhuis,Ranko Gaćeša,Tim J. Knobbe,Vincent E. de Meijer,Kevin Damman,Erik A.M. Verschuuren,C. Tji Gan,Jingyuan Fu,Alexandra Zhernakova,Hermie J.M. Harmsen,Hans Blokzijl,Stephan J. L. Bakker,Johannes R. Björk,Rinse K. Weersma
出处
期刊:Cold Spring Harbor Laboratory - medRxiv
日期:2023-10-30
标识
DOI:10.1101/2023.10.28.23297709
摘要
Abstract 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 relation with overall survival in specific diseases has not been extensively studied. In the current study, we present in-depth analyses regarding the relationship between gut dysbiosis and all-cause and cause-specific mortality in the setting of solid organ transplant recipients (SOTR). Design We analyzed 1,337 metagenomes derived from fecal samples of 766 kidney, 334 liver, 170 lung and 67 heart transplant recipients from the TransplantLines Biobank and Cohort; a prospective cohort study including extensive phenotype data with 6.5 years of follow up. To quantify gut dysbiosis, we included additional 8,208 metagenomic samples from a general population from the same geographical location. Multivariable Cox regression and a machine learning algorithm were used to analyze the association of indicators of gut dysbiosis and species abundances, with 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. Gut microbial distance to the average of the general population was associated with all-cause mortality and infection-, malignancy- and cardiovascular disease related mortality. Using multivariable Cox regression, we identified 23 species that were associated with all-cause mortality. By using a machine learning algorithm, we identified a log-ratio of 19 species predictive of all-cause mortality, all of which were also independently associated in the multivariable Cox-regression analysis. Conclusion Gut dysbiosis is consistently associated with mortality in SOTR. Our results support the observations that gut dysbiosis is predictive of long-term survival. Since our data do not provide causative evidence, further research needs to be done to see determine whether gut-microbiome targeting therapies might improve long term outcomes Summary box Significance of this study What is already known on this subject? Current literature suggests that the gut microbiome signature might be associated with mortality risk in the general population. Higher diversity of gut microbiota is associated with lower mortality in allogeneic hematopoietic-cell transplantation recipients. Liver and kidney transplant recipients suffer from gut dysbiosis and an analysis with a relatively low number of events showed that dysbiosis is associated with mortality. What are the new findings? Across kidney, liver, heart and lung transplant recipients, we identified two overall microbial community variation patterns that are associated with all-cause mortality independent of the organ transplant and specifically to death from malignancy and infection. We find that multiple indicators of gut dysbiosis predict all-cause mortality and death by cardiovascular diseases, malignancy and infection. We find multiple microbial species associated with all-cause and cause-specific mortality. Using three different methods, we identify multiple bacterial species (shared between different analytical approaches) that are associated with an increased or decreased risk of mortality following solid organ transplantation. Using a machine learning algorithm, we identify a log-ratio of 19 bacterial species that was associated with all-cause mortality.
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