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肠道微生物群和专项运动员的炎症模式:不同类型运动的多队列研究。

Gut microbiota and inflammation patterns for specialized athletes: a multi-cohort study across different types of sports.

机构信息

Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center of Artificial Intelligence Biology, College of Life Science and Technology, Huazhong University of Science and Technology , Wuhan, China.

Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology , Wuhan, China.

出版信息

mSystems. 2023 Aug 31;8(4):e0025923. doi: 10.1128/msystems.00259-23. Epub 2023 Jul 27.

DOI:10.1128/msystems.00259-23
PMID:37498086
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10470055/
Abstract

Regular high-intensity exercise can cause changes in athletes' gut microbiota, and the extent and nature of these changes may be affected by the athletes' exercise patterns. However, it is still unclear to what extent different types of athletes have distinct gut microbiome profiles and whether we can effectively monitor an athlete's inflammatory risk based on their microbiota. To address these questions, we conducted a multi-cohort study of 543 fecal samples from athletes in three different sports: aerobics ( = 316), wrestling ( = 53), and rowing ( = 174). We sought to investigate how athletes' gut microbiota was specialized for different types of sports, and its associations with inflammation, diet, anthropometrics, and anaerobic measurements. We established a microbiota catalog of multi-cohort athletes and found that athletes have specialized gut microbiota specific to the type of sport they engaged in. Using latent Dirichlet allocation, we identified 10 microbial subgroups of athletes' gut microbiota, each of which had specific correlations with inflammation, diet, and anaerobic performance in different types of athletes. Notably, most inflammation indicators were associated with -driven subgroup 7. Finally, we found that the effects of sport types and exercise intensity on the gut microbiota were sex-dependent. These findings shed light on the complex associations between physical factors, gut microbiota, and inflammation in athletes of different sports types and could have significant implications for monitoring potential inflammation risk and developing personalized exercise programs. IMPORTANCE This study is the first multi-cohort investigation of athletes across a range of sports, including aerobics, wrestling, and rowing, with the goal of establishing a multi-sport microbiota catalog. Our findings highlight that athletes' gut microbiota is sport-specific, indicating that exercise patterns may play a significant role in shaping the microbiome. Additionally, we observed distinct associations between gut microbiota and markers of inflammation, diet, and anaerobic performance in athletes of different sports. Moreover, we expanded our analysis to include a non-athlete cohort and found that exercise intensity had varying effects on the gut microbiota of participants, depending on sex.

摘要

定期进行高强度运动可以改变运动员的肠道微生物群,而这些变化的程度和性质可能受到运动员运动模式的影响。然而,不同类型的运动员的肠道微生物组图谱有何不同,以及我们是否可以基于他们的微生物组有效地监测运动员的炎症风险,目前仍不清楚。为了解决这些问题,我们对来自三种不同运动的 543 份粪便样本进行了多队列研究:有氧运动(=316)、摔跤(=53)和划船(=174)。我们试图研究运动员的肠道微生物群如何针对不同类型的运动进行专业化,以及它与炎症、饮食、人体测量学和无氧测量的关联。我们建立了多队列运动员的微生物组目录,并发现运动员的肠道微生物群具有针对他们从事的运动类型的专业化特征。使用潜在狄利克雷分配(LDA),我们确定了运动员肠道微生物群的 10 个微生物亚群,每个亚群与不同类型运动员的炎症、饮食和无氧表现都有特定的相关性。值得注意的是,大多数炎症指标都与驱动亚群 7 相关。最后,我们发现运动类型和运动强度对肠道微生物群的影响具有性别依赖性。这些发现揭示了不同运动类型的运动员的身体因素、肠道微生物群和炎症之间的复杂关联,并可能对监测潜在的炎症风险和制定个性化的运动计划具有重要意义。

重要性

本研究是首次对包括有氧运动、摔跤和划船在内的一系列运动的运动员进行的多队列研究,旨在建立多运动微生物组目录。我们的研究结果表明,运动员的肠道微生物群是具有运动特异性的,这表明运动模式可能在塑造微生物组方面发挥重要作用。此外,我们观察到运动员的肠道微生物群与不同运动的炎症标志物、饮食和无氧表现之间存在不同的关联。此外,我们将分析扩展到包括非运动员队列,并发现运动强度对参与者的肠道微生物群的影响因性别而异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5871/10470055/dc018b2c3be0/msystems.00259-23.f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5871/10470055/93497e95dcca/msystems.00259-23.f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5871/10470055/49a0c649739b/msystems.00259-23.f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5871/10470055/3ccd41becaa3/msystems.00259-23.f003.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5871/10470055/dc018b2c3be0/msystems.00259-23.f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5871/10470055/93497e95dcca/msystems.00259-23.f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5871/10470055/49a0c649739b/msystems.00259-23.f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5871/10470055/3ccd41becaa3/msystems.00259-23.f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5871/10470055/1e1be8293ae6/msystems.00259-23.f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5871/10470055/dc018b2c3be0/msystems.00259-23.f005.jpg

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