中老年人肠道微生物组组成与肌肉骨骼特征的关系:一项双队列联合研究。

Ruolin Li, Paul C Okoro, M Carola Zillikens, Ramachandran S Vasan, Shivani Sahni, Fernando Rivadeneira, Douglas P Kiel, Carolina Medina-Gomez
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引用次数: 0

摘要

背景:骨骼和肌肉在解剖学和功能上是相互联系的。初步证据表明,在动物研究中,肠道微生物组影响骨骼和肌肉的衰老过程。然而,在人类中这样的证据仍然很少。本研究旨在评估两组社区老年人中微生物组-骨骼和微生物组-肌肉的关联。方法:我们利用了两个基于人群的大型队列的信息,即鹿特丹研究(平均年龄62.7±5.6岁;n=1,249)和Framingham心脏研究(平均年龄55.2±9.1岁;n = 1227)。对于本研究中包括的个体,可获得肠道微生物组16S rRNA测序,DXA图像衍生的肌肉骨骼表型,生活方式和社会经济数据以及药物记录。每个队列中,来自粪便的16S rRNA测序数据使用DADA2管道进行处理,并使用SILVA参考数据库分配分类。此外,利用PICRUSt2获得了微生物组功能电位。此外,我们研究了人类肠道微生物组(α多样性,属和预测的功能途径)与阑尾瘦质量(ALM),股骨颈骨矿物质密度(FN-BMD)和小梁骨评分(TBS)之间的关系,使用控制多个混杂因素的多线性回归模型,并对两个队列进行了联合分析。还进行了性别分层分析。结果:考虑多重测试后,肠道微生物组α多样性与任一测试表型均无相关性(P>1.67e-02)。在联合分析中,Oscillibacter (β = -)丰度较低。51, 95%CI[-0.74, - 0.29])、无氧树干(β =-0.41, 95%CI[-0.61, - 0.21])、艾森伯格菌(β =-0.39, 95%CI[-0.59, - 0.19])和较高丰度的Agathobacter (β =0.40, 95%CI[-0.45, - 0.19])与较高的ALM相关(PAnaerotruncus (β =-0.32, 95%CI[-0.45, - 0.19])、Hungatella (β =-0.26, 95%CI[-0.38, - 0.15])和Clostridiales细菌DTU089 (β =-0.37, 95%CI[-0.55, - 0.19])仅在女性中与较高的ALM相关(P< 2.0e-04)。此外,生物素生物合成II途径与ALM呈正相关(β =0.44, 95% CI[0.24, 0.64])。(结论:我们的研究结果表明,特定的属与中老年人ALM相关,并且这些关联可能以性别特异性的方式存在。总的来说,我们的研究表明,肠道微生物群与中老年人的肌肉衰老有关。然而,仍然需要更大的样本量来支持所涉及的特定微生物组特征。
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The association of gut microbiome composition with musculoskeletal features in middle-aged and older adults: a two-cohort joint study.

Background: Bones and muscles are connected anatomically, and functionally. Preliminary evidence has shown the gut microbiome influences the aging process of bone and muscle in animal studies. However, such evidence in humans is still scarce. This study aimed to assess the microbiome-bone and microbiome-muscle associations in two cohorts of community-dwelling older adults.

Methods: We leveraged information from two large population-based cohorts, i.e., the Rotterdam Study (mean age 62.7 ± 5.6 years; n=1,249) and the Framingham Heart Study (mean age 55.2 ± 9.1 years; n=1,227). For individuals included in this study, gut microbiome 16S rRNA sequencing, musculoskeletal phenotyping derived from DXA images, lifestyle and socioeconomic data, and medication records were available. Per cohort, the 16S rRNA sequencing data, derived from stool, were processed with the DADA2 pipeline and taxonomies were assigned using the SILVA reference database. In addition, the microbiome functional potential was obtained with PICRUSt2. Further, we investigated the association between the human gut microbiome (alpha diversity, genera and predicted functional pathways) and appendicular lean mass (ALM), femoral neck bone mineral density (FN-BMD) and trabecular bone score (TBS) using multilinear regression models controlling for multiple confounders, and performed a joint analysis from both cohorts. Sex-stratified analyses were also conducted.

Results: The gut microbiome alpha diversity was not associated with either tested phenotype after accounting for multiple-testing (P>1.67e-02). In the joint analysis, lower abundance of Oscillibacter (beta= -.51, 95%CI [-0.74, -.29]), Anaerotruncus (beta=-0.41, 95%CI [-0.61, - 0.21]), Eisenbergiella (beta=-0.39, 95%CI [-0.59, -.19]) and higher abundance of Agathobacter (beta=0.40, 95%CI [0.20, 0.60]) were associated with higher ALM (P<2.0e-04). Lower abundance of Anaerotruncus (beta=-0.32, 95%CI [-0.45, -.19]), Hungatella (beta=-0.26, 95%CI [-0.38, -.15]) and Clostridiales bacterium DTU089 (beta=-0.37, 95%CI [-0.55, -.19]) was associated with higher ALM only in females (P< 2.0e-04). Moreover, the biotin biosynthesis II pathway was positively associated with ALM (beta=0.44, 95% CI [0.24, 0.64]) (P<1.90e-04) in females while no associations were observed in males. We did not observe any robust association of bone traits with gut microbiome features.

Conclusion: Our results indicate that specific genera are associated with ALM in middle-aged and older adults and these associations can present in a sex-specific manner. Overall, our study suggests that the gut microbiome is linked to muscle aging in middle-aged and older adults. However, larger sample sizes are still needed to underpin the specific microbiome features involved.

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