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      Hemoglobin glycation index as a useful predictor of therapeutic responses to dipeptidyl peptidase-4 inhibitors in patients with type 2 diabetes

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          Abstract

          Introduction

          A high hemoglobin glycation index (HGI) and glycated hemoglobin (HbA1c) level are associated with greater inflammatory status, and dipeptidyl peptidase-4 (DPP-4) inhibitors can suppress inflammation. We aimed to evaluate the relationship between HGI and the therapeutic effect of DPP-4 inhibitors.

          Methods

          This retrospective cohort study followed 468 patients with type 2 diabetes receiving DPP-4 inhibitor treatment for 1 year. Estimated HbA1c was calculated using a linear regression equation derived from another 2969 randomly extracted patients with type 2 diabetes based on fasting plasma glucose (FPG) level. The subjects were divided into two groups based on HGI (HGI = observed HbA1c - estimated HbA1c). Mixed model repeated measures were used to compare the treatment efficacy after 1 year in patients with a low (HGI<0, n = 199) and high HGI (HGI≧0, n = 269).

          Results

          There were no significant group differences in mean changes of FPG after 1 year (-12.8 and -13.4 mg/dL in the low and high HGI groups, respectively). However, the patients with a high HGI had a significantly greater reduction in HbA1c from baseline compared to those with a low HGI (-1.9 versus -0.3% [-20.8 versus -3.3 mmol/mol]). Improvements in glycemic control were statistically significantly associated with the tested DPP-4 inhibitors in the high HGI group (-2.4, -1.4, -1.2 and -2.2% [-26.2, -15.3, -13.1 and -24.0 mmol/mol] for vildagliptin, linagliptin, saxagliptin and sitagliptin, respectively) but not in the low HGI group.

          Conclusions

          The HGI index derived from FPG and HbA1c may be able to identify who will have a better response to DPP-4 inhibitors.

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          Most cited references28

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          Contributions of fasting and postprandial plasma glucose increments to the overall diurnal hyperglycemia of type 2 diabetic patients: variations with increasing levels of HbA(1c).

          Louis Monnier, Hélène Lapinski, Claude Colette (2003)
          The exact contributions of postprandial and fasting glucose increments to overall hyperglycemia remain controversial. The discrepancies between the data published previously might be caused by the interference of several factors. To test the effect of overall glycemic control itself, we analyzed the diurnal glycemic profiles of type 2 diabetic patients investigated at different levels of HbA(1c). In 290 non-insulin- and non-acarbose-using patients with type 2 diabetes, plasma glucose (PG) concentrations were determined at fasting (8:00 A.M.) and during postprandial and postabsorptive periods (at 11:00 A.M., 2:00 P.M., and 5:00 P.M.). The areas under the curve above fasting PG concentrations (AUC(1)) and >6.1 mmol/l (AUC(2)) were calculated for further evaluation of the relative contributions of postprandial (AUC(1)/AUC(2), %) and fasting [(AUC(2) - AUC(1))/AUC(2), %] PG increments to the overall diurnal hyperglycemia. The data were compared over quintiles of HbA(1c). The relative contribution of postprandial glucose decreased progressively from the lowest (69.7%) to the highest quintile of HbA(1c) (30.5%, P < 0.001), whereas the relative contribution of fasting glucose increased gradually with increasing levels of HbA(1c): 30.3% in the lowest vs. 69.5% in the highest quintile (P < 0.001). The relative contribution of postprandial glucose excursions is predominant in fairly controlled patients, whereas the contribution of fasting hyperglycemia increases gradually with diabetes worsening. These results could therefore provide a unifying explanation for the discrepancies as observed in previous studies.
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            Reduction of Oxidative Stress and Inflammation by Blunting Daily Acute Glucose Fluctuations in Patients With Type 2 Diabetes

            Maria Rizzo, Michelangela Barbieri, Raffaele Marfella … (2012)
            OBJECTIVE Evaluate the effects of two dipeptidyl peptidase-IV (DPP-4) inhibitors, sitagliptin and vildagliptin, known to have different efficacy on mean amplitude of glycemic excursions (MAGE), on oxidative stress, and on systemic inflammatory markers in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS A prospective, randomized, open-label PROBE design (parallel group with a blinded end point) study was performed in 90 patients with type 2 diabetes inadequately controlled by metformin. The study assigned 45 patients to receive sitagliptin (100 mg once daily; sitagliptin group) and 45 patients to receive vildagliptin (50 mg twice daily; vildagliptin group) for 12 weeks. MAGE, evaluated during 48 h of continuous subcutaneous glucose monitoring, allowed an assessment of daily glucose fluctuations at baseline and after 12 weeks in all patients. Assessment of oxidative stress (nitrotyrosine) and systemic levels of inflammatory markers interleukin (IL)-6 and IL-18 was performed at baseline and after 12 weeks in all patients. RESULTS HbA1c, fasting and postprandial glucose, MAGE, and inflammatory and oxidative stress markers were similar between the groups at baseline. After 12 weeks, MAGE (P < 0.01) was lower in the vildagliptin group than in the sitagliptin group. After treatment, HbA1c and postprandial glucose evidenced similar changes between the groups (P = NS). Vildagliptin treatment was associated with a stronger decrease in nitrotyrosine (P < 0.01), IL-6 (P < 0.05), and IL-18 (P < 0.05) than sitagliptin treatment. Nitrotyrosine and IL-6 changes significantly correlated with changes in MAGE but not in fasting glucose and HbA1c. CONCLUSIONS MAGE reduction is associated with reduction of oxidative stress and markers of systemic inflammation in type 2 diabetic patients. These effects were greater in the vildagliptin group than in the sitagliptin group.
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              Correlation of fasting and postprandial plasma glucose with HbA1c in assessing glycemic control; systematic review and meta-analysis

              Ezra Belay Ketema, Kelemu Kibret (2015)
              Background Glycemic control in diabetes mellitus is a cornerstone in reducing morbidity and mortality of the disease. Achieving glycemic control or reducing hyperglycemia significantly decreases the microvascular and macrovascular complications of diabetes. Even though measurement of glycated hemoglobin (HbA1c) remains the gold standard for assessment of glycemic control, there is no consensus whether fasting or postprandial plasma glucose (PPG) is a better predictor of glycemic control in resource-poor settings when HbA1c is not available. The aim of this systematic review and meta-analysis was to summarize evidences on the significance of fasting and postprandial plasma glucose, and their correlation with HbA1c. Methods Relevant studies were identified through systematic search of online databases (e.g. EMBASE, MEDLINE/PubMed and Cochrane library) and manual search of bibliographies of the included studies. Original research papers describing the correlations or associations of fasting and postprandial plasma glucose with HbA1c were included. The MedCalc software was used for data entry and analysis. We used the random effect model to estimate the pooled correlations of fasting and postprandial plasma glucose with HbA1c. Heterogeneity assessment and robustness analysis was also performed. Result From total 126 articles identified, 14 articles were eligible for systemic review. Eleven of these eligible studies evaluated the correlations of fasting and postprandial plasma glucose to the standard HbA1c values and used in meta-analysis. Seven of these studies (63.5 %) found better or stronger correlations between PPG and HbA1c than fasting plasma glucose (FPG). In all the studies that estimated the relative contribution FPG and PPG to the overall hyperglycemia, decreases in PPG was accounted for greater decrease in HbA1c compared with decreases in FPG value. PPG also showed a better sensitivity, specificity and positive predictive value than FPG. The pooled correlation coefficient (r) between PPG and HbA1c was 0.68 (P < 0.001, 95 % CI; 0.56–0.75) slightly higher than pooled correlation coefficient of FPG (r = 0.61(P < 0.001, 95 % CI; 0.48–0.72)). Conclusion PPG has a closer association with HbA1c than FPG. Hence, PPG is better in predicting overall glycemic control in the absence of HbA1c. Electronic supplementary material The online version of this article (doi:10.1186/s13690-015-0088-6) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Stephen L. Atkin: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS ONE
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 9 February 2017
                Publication date Collection: 2017
                Volume: 12
                Issue: 2
                Electronic Location Identifier: e0171753
                Affiliations
                [1 ]Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
                [2 ]School of Medicine, National Yang Ming University, Taipei, Taiwan
                [3 ]College of Medicine, National Defense Medical Center, Taipei, Taiwan
                [4 ]Center for Geriatrics and Gerontology, Taichung Veterans General Hospital, Taichung, Taiwan
                [5 ]Graduate Institute of Biomedical Electronics and Bioinformatics, College of Electrical Engineering and Computer Science, National Taiwan University, Taipei, Taiwan
                [6 ]Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan
                [7 ]Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan
                Weill Cornell Medical College Qatar, QATAR
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: Y-WC J-SW C-LL.

                • Data curation: WH-HS J-SW C-LL.

                • Formal analysis: Y-WC J-SW S-YL C-LL.

                • Investigation: Y-WC J-SW C-LL.

                • Methodology: Y-WC J-SW C-LL.

                • Project administration: Y-WC C-LL.

                • Resources: WH-HS S-YL I-TL Y-MS.

                • Software: J-SW C-LL.

                • Supervision: WH-HS S-YL.

                • Validation: Y-WC J-SW C-LL.

                • Visualization: Y-WC C-PF.

                • Writing – original draft: Y-WC J-SW C-LL.

                • Writing – review & editing: S-YL I-TL Y-MS C-PF.

                Article
                Publisher ID: PONE-D-16-37167
                DOI: 10.1371/journal.pone.0171753
                PMC ID: 5300176
                PubMed ID: 28182722
                SO-VID: c01483a7-e6c3-4685-9608-434083127358
                Copyright © © 2017 Chen et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 16 September 2016
                Date accepted : 25 January 2017
                Page count
                Figures: 2, Tables: 1, Pages: 10
                Funding
                The authors received no specific funding for this work.
                Categories
                Subject: Research Article
                Subject: Medicine and health sciences
                Subject: Diagnostic medicine
                Subject: Diabetes diagnosis and management
                Subject: HbA1c
                Subject: Biology and life sciences
                Subject: Biochemistry
                Subject: Proteins
                Subject: Hemoglobin
                Subject: HbA1c
                Subject: Medicine and Health Sciences
                Subject: Endocrinology
                Subject: Endocrine Disorders
                Subject: Diabetes Mellitus
                Subject: Medicine and Health Sciences
                Subject: Metabolic Disorders
                Subject: Diabetes Mellitus
                Subject: Physical Sciences
                Subject: Chemistry
                Subject: Chemical Compounds
                Subject: Organic Compounds
                Subject: Carbohydrates
                Subject: Monosaccharides
                Subject: Glucose
                Subject: Physical Sciences
                Subject: Chemistry
                Subject: Organic Chemistry
                Subject: Organic Compounds
                Subject: Carbohydrates
                Subject: Monosaccharides
                Subject: Glucose
                Subject: Medicine and Health Sciences
                Subject: Endocrinology
                Subject: Endocrine Disorders
                Subject: Diabetes Mellitus
                Subject: Type 2 Diabetes
                Subject: Medicine and Health Sciences
                Subject: Metabolic Disorders
                Subject: Diabetes Mellitus
                Subject: Type 2 Diabetes
                Subject: Biology and Life Sciences
                Subject: Immunology
                Subject: Immune Response
                Subject: Inflammation
                Subject: Medicine and Health Sciences
                Subject: Immunology
                Subject: Immune Response
                Subject: Inflammation
                Subject: Medicine and Health Sciences
                Subject: Diagnostic Medicine
                Subject: Signs and Symptoms
                Subject: Inflammation
                Subject: Medicine and Health Sciences
                Subject: Pathology and Laboratory Medicine
                Subject: Signs and Symptoms
                Subject: Inflammation
                Subject: Biology and Life Sciences
                Subject: Biochemistry
                Subject: Proteins
                Subject: Hemoglobin
                Subject: Biology and Life Sciences
                Subject: Biochemistry
                Subject: Proteins
                Subject: Post-Translational Modification
                Subject: Glycation
                Subject: Biology and Life Sciences
                Subject: Anatomy
                Subject: Body Fluids
                Subject: Blood
                Subject: Blood Sugar
                Subject: Medicine and Health Sciences
                Subject: Anatomy
                Subject: Body Fluids
                Subject: Blood
                Subject: Blood Sugar
                Subject: Biology and Life Sciences
                Subject: Physiology
                Subject: Body Fluids
                Subject: Blood
                Subject: Blood Sugar
                Subject: Medicine and Health Sciences
                Subject: Physiology
                Subject: Body Fluids
                Subject: Blood
                Subject: Blood Sugar
                Subject: Medicine and Health Sciences
                Subject: Hematology
                Subject: Blood
                Subject: Blood Sugar
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