Multiple indicators of gut dysbiosis predict all-cause and cause-specific mortality in solid organ transplant recipients

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
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.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
三清小爷完成签到,获得积分10
1秒前
复杂的海发布了新的文献求助10
3秒前
打打应助草木采纳,获得10
3秒前
3秒前
4秒前
胡慧婷完成签到 ,获得积分10
5秒前
如常完成签到,获得积分10
6秒前
偏偏海完成签到,获得积分10
6秒前
yuki完成签到 ,获得积分10
6秒前
6秒前
踏实幻竹发布了新的文献求助10
7秒前
海德堡完成签到,获得积分10
7秒前
7秒前
lqy完成签到,获得积分10
7秒前
7秒前
shuoye发布了新的文献求助30
7秒前
7秒前
田様应助gsit采纳,获得10
7秒前
8秒前
希望天下0贩的0应助水123采纳,获得10
9秒前
10秒前
10秒前
leey发布了新的文献求助10
11秒前
lqy发布了新的文献求助10
12秒前
wang发布了新的文献求助10
12秒前
洪豆豆完成签到,获得积分10
12秒前
13秒前
13秒前
14秒前
SciGPT应助aaa采纳,获得30
16秒前
豆子发布了新的文献求助10
17秒前
Bonaventure完成签到,获得积分10
18秒前
leey完成签到,获得积分10
18秒前
调皮帆布鞋完成签到,获得积分10
20秒前
你都至少信我八分吧完成签到 ,获得积分10
21秒前
Luffa完成签到,获得积分10
23秒前
24秒前
24秒前
rsimap360完成签到,获得积分10
24秒前
量子星尘发布了新的文献求助10
25秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 临床微生物学程序手册,多卷,第5版 2000
人脑智能与人工智能 1000
King Tyrant 720
Silicon in Organic, Organometallic, and Polymer Chemistry 500
Peptide Synthesis_Methods and Protocols 400
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5603799
求助须知:如何正确求助?哪些是违规求助? 4688754
关于积分的说明 14855835
捐赠科研通 4695101
什么是DOI,文献DOI怎么找? 2540987
邀请新用户注册赠送积分活动 1507143
关于科研通互助平台的介绍 1471814