Unveiling the connection between gut microbiome and metabolic health in individuals with chronic spinal cord injury.

IF 2.5 4区 生物学 Q3 CELL BIOLOGY Physiological genomics Pub Date : 2024-04-01 Epub Date: 2024-02-12 DOI:10.1152/physiolgenomics.00107.2023
Jia Li, Stephen Barnes, Elliot Lefkowitz, Ceren Yarar-Fisher
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Abstract

Accumulating evidence has revealed that alterations in the gut microbiome following spinal cord injury (SCI) exhibit similarities to those observed in metabolic syndrome. Considering the causal role of gut dysbiosis in metabolic syndrome development, SCI-induced gut dysbiosis may be a previously unidentified contributor to the increased risk of cardiometabolic diseases, which has garnered attention. With a cross-sectional design, we evaluated the correlation between gut microbiome composition and functional potential with indicators of metabolic health among 46 individuals with chronic SCI. Gut microbiome communities were profiled using next-generation sequencing techniques. Indices of metabolic health, including fasting lipid profile, glucose tolerance, insulin resistance, and inflammatory markers, were assessed through fasting blood tests and an oral glucose tolerance test. We used multivariate statistical techniques (i.e., regularized canonical correlation analysis) to identify correlations between gut bacterial communities, functional pathways, and metabolic health indicators. Our findings spotlight bacterial species and functional pathways associated with complex carbohydrate degradation and maintenance of gut barrier integrity as potential contributors to improved metabolic health. Conversely, those correlated with detrimental microbial metabolites and gut inflammatory pathways demonstrated associations with poorer metabolic health outcomes. This cross-sectional investigation represents a pivotal initial step toward comprehending the intricate interplay between the gut microbiome and metabolic health in SCI. Furthermore, our results identified potential targets for future research endeavors to elucidate the role of the gut microbiome in metabolic syndrome in this population.NEW & NOTEWORTHY Spinal cord injury (SCI) is accompanied by gut dysbiosis and the impact of this on the development of metabolic syndrome in this population remains to be investigated. Our study used next-generation sequencing and multivariate statistical analyses to explore the correlations between gut microbiome composition, function, and metabolic health indices in individuals with chronic SCI. Our results point to potential gut microbial species and functional pathways that may be implicated in the development of metabolic syndrome.

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揭示慢性脊髓损伤患者肠道微生物群与代谢健康之间的联系。
越来越多的证据表明,脊髓损伤(SCI)后肠道微生物组的改变与代谢紊乱中观察到的改变相似。考虑到肠道菌群失调在代谢紊乱发病中的因果作用,SCI 引起的肠道菌群失调可能是之前未被发现的导致心脏代谢疾病风险增加的因素,这一点已引起人们的关注。通过横断面设计,我们评估了 46 名慢性 SCI 患者的肠道微生物组组成和功能潜力与代谢健康指标之间的相关性。我们使用新一代测序技术分析了肠道微生物群落。通过空腹验血和口服葡萄糖耐量试验评估了代谢健康指标,包括空腹血脂、葡萄糖耐量、胰岛素抵抗和炎症标志物。我们使用多元统计技术(即正则化典型相关分析)来确定肠道细菌群落、功能通路和代谢健康指标之间的相关性。我们的研究结果发现,与复杂碳水化合物降解和维护肠道屏障完整性相关的细菌种类和功能途径是改善代谢健康的潜在因素。相反,那些与有害微生物代谢物和肠道炎症途径相关的细菌则与代谢健康状况较差有关。这项横断面调查为理解 SCI 患者肠道微生物组与代谢健康之间错综复杂的相互作用迈出了关键的第一步。此外,我们的研究结果还确定了未来研究工作的潜在目标,以阐明肠道微生物组在该人群代谢紊乱中的作用。
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来源期刊
Physiological genomics
Physiological genomics 生物-生理学
CiteScore
6.10
自引率
0.00%
发文量
46
审稿时长
4-8 weeks
期刊介绍: The Physiological Genomics publishes original papers, reviews and rapid reports in a wide area of research focused on uncovering the links between genes and physiology at all levels of biological organization. Articles on topics ranging from single genes to the whole genome and their links to the physiology of humans, any model organism, organ, tissue or cell are welcome. Areas of interest include complex polygenic traits preferably of importance to human health and gene-function relationships of disease processes. Specifically, the Journal has dedicated Sections focused on genome-wide association studies (GWAS) to function, cardiovascular, renal, metabolic and neurological systems, exercise physiology, pharmacogenomics, clinical, translational and genomics for precision medicine, comparative and statistical genomics and databases. For further details on research themes covered within these Sections, please refer to the descriptions given under each Section.
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