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Dear Colleagues,

The Special Issue "Metabolic Biomarkers and Gut Microbiota in Adults with Prediabetes" focuses on the interplay between metabolic biomarkers and gut microbiota in individuals with prediabetes. The development of prediabetes is associated with changes in the gut microbiota, which in turn, affect metabolism and increase the risk of developing type 2 diabetes.

This Special Issue explores the latest research in identifying metabolic biomarkers and their association with gut microbiota in adults with prediabetes. It aims to provide a comprehensive understanding of the complex relationship between metabolic health, gut microbiota, and prediabetes.

The scope of this Special Issue includes the identification and validation of biomarkers associated with prediabetes and the gut microbiota, the elucidation of underlying mechanisms, and the development of interventions that target the gut microbiota to improve metabolic health.

Overall, this Special Issue will contribute to a better understanding of the role of gut microbiota and metabolic biomarkers in prediabetes. The articles will provide valuable insights for clinicians, researchers, and policymakers in developing effective strategies for the prevention and treatment of prediabetes and type 2 diabetes.

Dr. Xuhuiqun Zhang
Dr. Yen Chin Koay
Guest Editors

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Keywords

metabolic biomarkers
gut microbiota
prediabetes
next-generation sequencing
data analysis

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16 pages, 2227 KiB

Open AccessArticle

Metabolomics and Lipidomics Analyses Aid Model Classification of Type 2 Diabetes in Non-Human Primates

by Peining Tao, Stacey Conarello, Thomas P. Wyche, Nanyan Rena Zhang, Keefe Chng, John Kang and Theodore R. Sana

Metabolites 2024, 14(3), 159; https://doi.org/10.3390/metabo14030159 - 09 Mar 2024

Viewed by 1115

Abstract

Type 2 diabetes (T2D) is a global public health issue characterized by excess weight, abdominal obesity, dyslipidemia, hyperglycemia, and a progressive increase in insulin resistance. Human population studies of T2D development and its effects on systemic metabolism are confounded by many factors that cannot be controlled, complicating the interpretation of results and the identification of early biomarkers. Aged, sedentary, and overweight/obese non-human primates (NHPs) are one of the best animal models to mimic spontaneous T2D development in humans. We sought to identify and distinguish a set of plasma and/or fecal metabolite biomarkers, that have earlier disease onset predictability, and that could be evaluated for their predictability in subsequent T2D studies in human cohorts. In this study, a single plasma and fecal sample was collected from each animal in a colony of 57 healthy and dysmetabolic NHPs and analyzed for metabolomics and lipidomics. The samples were comprehensively analyzed using untargeted and targeted LC/MS/MS. The changes in each animal’s disease phenotype were monitored using IVGTT, HbA1c, and other clinical metrics, and correlated with their metabolic profile. The plasma and fecal lipids, as well as bile acid profiles, from Healthy, Dysmetabolic (Dys), and Diabetic (Dia) animals were compared. Following univariate and multivariate analyses, including adjustments for weight, age, and sex, several plasma lipid species were identified to be significantly different between these animal groups. Medium and long-chain plasma phosphatidylcholines (PCs) ranked highest at distinguishing Healthy from Dys animals, whereas plasma triglycerides (TG) primarily distinguished Dia from Dys animals. Random Forest (RF) analysis of fecal bile acids showed a reduction in the secondary bile acid glycoconjugate, GCDCA, in diseased animals (AUC 0.76[0.64, 0.89]). Moreover, metagenomics results revealed several bacterial species, belonging to the genera Roseburia, Ruminococcus, Clostridium, and Streptococcus, to be both significantly enriched in non-healthy animals and associated with secondary bile acid levels. In summary, our results highlight the detection of several elevated circulating plasma PCs and microbial species associated with fecal secondary bile acids in NHP dysmetabolic states. The lipids and metabolites we have identified may help researchers to differentiate individual NHPs more precisely between dysmetabolic and overtly diabetic states. This could help assign animals to study groups that are more likely to respond to potential therapies where a difference in efficacy might be anticipated between early vs. advanced disease. Full article

(This article belongs to the Special Issue Metabolic Biomarkers and Gut Microbiota in Adults with Prediabetes)

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