Gut microbiota‐based translational biomarkers to prevent metabolic syndrome via nutritional modulation. Issue 2 (12th December 2013)

• Record Type: Journal Article
• Authors: Xiao, Shuiming; Zhao, Liping
• Is Part Of: FEMS microbiology ecology. Volume 87:Issue 2(2014)
• Page Start: 303
• Page End: 314
• Publication Date: 2013-12-12
• Subjects: Microbial ecology -- Periodicals; Microbiology -- Periodicals; 579.17
• DOI: 10.1111/1574-6941.12250
• Languages: English
• ISSNs: 0168-6496

Abstract

<abstract abstract-type="main" id="fem12250-abs-0001"> <title>Abstract</title> <p>In the face of the global epidemic of metabolic syndrome (MetS) and its strong association with the increasing rate of cardiovascular morbidity and mortality, it is critical to detect MetS at an early stage in the clinical setting to implement preventive intervention long before the complications arise. Lipopolysaccharide, the cell wall component of Gram‐negative bacteria produced from diet‐disrupted gut microbiota, has been shown to induce metabolic endotoxemia, chronic low‐grade inflammation, and ultimately insulin resistance. Therefore, ameliorating the inflammation and insulin resistance underlying MetS by gut microbiota‐targeted, dietary intervention has gained increasing attention. In this review, we propose using dynamic monitoring of a set of translational biomarkers related with the etiological role of gut microbiota, including lipopolysaccharide binding protein (LBP), C‐reactive protein (CRP), fasting insulin, and homeostasis model assessment of insulin resistance (HOMA‐IR), for early detection and prevention of MetS via nutritional modulation. LBP initiates the recognition and monomerization of lipopolysaccharide and amplifies host immune responses, linking the gut‐derived antigen load and inflammation indicated by the plasma levels of CRP. Fasting plasma insulin and HOMA‐IR are measured to evaluate insulin sensitivity that is damaged by pro‐inflammatory cytokines. The dynamic monitoring of these biomarkers in high‐risk populations may provide translational methods for the quantitative and dynamic evaluation of dysbiosis‐induced insulin resistance and the effectiveness of dietary treatment for MetS.</p> </abstract>