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      Low aspartate aminotransferase/alanine aminotransferase (DeRitis) ratio assists in predicting diabetes in Chinese population

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          Abstract

          Background

          Few studies discussed the predictive ability of aspartate aminotransferase/alanine aminotransferase (AST/ALT, DeRitis) ratio for diabetes risk. The aim of this study was to characterize the role of AST/ALT ratio in the prediction of Chinese diabetes.

          Methods

          This retrospective cohort study analyzed a Chinese population comprising 87,883 participants without diabetes at baseline between 2010 and 2016. Cox proportional hazards regression was used to identify independent risk factors. Restricted cubic spline (RCS) was performed to investigate the non-linear correlation between AST/ALT ratio and diabetes risk.

          Results

          During a median follow-up period of 3.01 years, 1,877 participants developed diabetes. Comparing the baseline characteristics, diabetes group exhibited lower AST/ALT ratio. The Kaplan-Meier curve showed that participants with low AST/ALT ratio had higher cumulative incidence, and Cox regression also demonstrated that the lower AST/ALT ratio, the higher diabetes risk (HR: 0.56, 95% CI: 0.37–0.85, P = 0.006). The RCS model revealed a non-linear correlation between AST/ALT ratio and diabetes risk. In the condition of AST/ALT ratio ≤1.18, diabetes risk increased as it decreased (HR: 0.42, 95% CI: 0.19–0.91, P = 0.028). In contrast, AST/ALT ratio did not independently affect diabetes when beyond 1.18.

          Conclusion

          AST/ALT ratio is a valuable predictor of diabetes. Diabetes risk increases rapidly in the condition of AST/ALT ratio ≤1.18.

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          Most cited references35

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          Global aetiology and epidemiology of type 2 diabetes mellitus and its complications

          Globally, the number of people with diabetes mellitus has quadrupled in the past three decades, and diabetes mellitus is the ninth major cause of death. About 1 in 11 adults worldwide now have diabetes mellitus, 90% of whom have type 2 diabetes mellitus (T2DM). Asia is a major area of the rapidly emerging T2DM global epidemic, with China and India the top two epicentres. Although genetic predisposition partly determines individual susceptibility to T2DM, an unhealthy diet and a sedentary lifestyle are important drivers of the current global epidemic; early developmental factors (such as intrauterine exposures) also have a role in susceptibility to T2DM later in life. Many cases of T2DM could be prevented with lifestyle changes, including maintaining a healthy body weight, consuming a healthy diet, staying physically active, not smoking and drinking alcohol in moderation. Most patients with T2DM have at least one complication, and cardiovascular complications are the leading cause of morbidity and mortality in these patients. This Review provides an updated view of the global epidemiology of T2DM, as well as dietary, lifestyle and other risk factors for T2DM and its complications.
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            The Global Epidemiology of NAFLD and NASH in Patients with type 2 diabetes: A Systematic Review and Meta-analysis

            Although non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH) and NASH with advanced fibrosis are closely associated with type 2 diabetes mellitus (T2DM), their global prevalence rates have not been well described. Our aim was to estimate the prevalence of NAFLD, NASH, and advanced fibrosis among patients with T2DM, by regions of the world.
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              Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis

              OBJECTIVE To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on prediabetes and type 2 diabetes. RESEARCH DESIGN AND METHODS We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review of cross-sectional and prospective studies. Additionally, meta-analyses of metabolite markers, with data estimates from at least three prospective studies, and type 2 diabetes risk were conducted, and multivariable-adjusted relative risks of type 2 diabetes were calculated per study-specific SD difference in a given metabolite. RESULTS We identified 27 cross-sectional and 19 prospective publications reporting associations of metabolites and prediabetes and/or type 2 diabetes. Carbohydrate (glucose and fructose), lipid (phospholipids, sphingomyelins, and triglycerides), and amino acid (branched-chain amino acids, aromatic amino acids, glycine, and glutamine) metabolites were higher in individuals with type 2 diabetes compared with control subjects. Prospective studies provided evidence that blood concentrations of several metabolites, including hexoses, branched-chain amino acids, aromatic amino acids, phospholipids, and triglycerides, were associated with the incidence of prediabetes and type 2 diabetes. We meta-analyzed results from eight prospective studies that reported risk estimates for metabolites and type 2 diabetes, including 8,000 individuals of whom 1,940 had type 2 diabetes. We found 36% higher risk of type 2 diabetes per study-specific SD difference for isoleucine (pooled relative risk 1.36 [1.24–1.48]; I 2 = 9.5%), 36% for leucine (1.36 [1.17–1.58]; I 2 = 37.4%), 35% for valine (1.35 [1.19–1.53]; I 2 = 45.8%), 36% for tyrosine (1.36 [1.19–1.55]; I 2 = 51.6%), and 26% for phenylalanine (1.26 [1.10–1.44]; I 2 = 56%). Glycine and glutamine were inversely associated with type 2 diabetes risk (0.89 [0.81–0.96] and 0.85 [0.82–0.89], respectively; both I 2 = 0.0%). CONCLUSIONS In studies using high-throughput metabolomics, several blood amino acids appear to be consistently associated with the risk of developing type 2 diabetes.
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                Author and article information

                Contributors
                Journal
                Front Public Health
                Front Public Health
                Front. Public Health
                Frontiers in Public Health
                Frontiers Media S.A.
                2296-2565
                02 November 2022
                2022
                : 10
                : 1049804
                Affiliations
                [1] 1Department of General Surgery, Shanghai Tenth People's Hospital, Tongji University School of Medicine , Shanghai, China
                [2] 2College of Traditional Chinese Medicine, Southern Medical University , Guangzhou, China
                [3] 3Department of Pancreatic Surgery, Fudan University Shanghai Cancer Center , Shanghai, China
                Author notes

                Edited by: Sathish Thirunavukkarasu, Emory University, United States

                Reviewed by: Nirmala Devi Chandrasekaran, SRM University, India; Mary Chandrika Anton, Sree Balaji Medical College and Hospital, India

                *Correspondence: Zhenshun Song zs_song@ 123456tongji.edu.cn

                This article was submitted to Clinical Diabetes, a section of the journal Frontiers in Public Health

                †These authors have contributed equally to this work and share first authorship

                Article
                10.3389/fpubh.2022.1049804
                9666731
                36408044
                3d780d68-b235-42c7-91d5-6e7b17ae8a5d
                Copyright © 2022 Xie, Yu, Chen, Ma, Yang and Song.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 21 September 2022
                : 17 October 2022
                Page count
                Figures: 3, Tables: 3, Equations: 0, References: 36, Pages: 8, Words: 5121
                Categories
                Public Health
                Original Research

                alanine aminotransferase,aspartate aminotransferase,chinese,diabetes,non-linearity

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