1
|
Moreira FD, Reis CEG, Gallassi AD, Moreira DC, Welker AF. Suppression of the postprandial hyperglycemia in patients with type 2 diabetes by a raw medicinal herb powder is weakened when consumed in ordinary hard gelatin capsules: A randomized crossover clinical trial. PLoS One 2024; 19:e0311501. [PMID: 39383145 PMCID: PMC11463819 DOI: 10.1371/journal.pone.0311501] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 09/16/2024] [Indexed: 10/11/2024] Open
Abstract
INTRODUCTION Contradictory claims about the efficacy of several medicinal plants to promote glycemic control in patients with type 2 diabetes mellitus (T2DM) have been explained by divergences in the administration form and by extrapolation of data obtained from healthy individuals. It is not known whether the antidiabetic effects of traditional herbal medicines are influenced by gelatin capsules. This randomized crossover trial aimed to evaluate the acute effect of a single dose of raw cinnamon consumed orally either dissolved in water as a beverage or as ordinary hard gelatin capsules on postprandial hyperglycemia (>140 mg/dL; >7.8 mmol/L) in T2DM patients elicited by a nutritionally-balanced meal providing 50 g of complex carbohydrates. METHODS Fasting T2DM patients (n = 19) randomly ingested a standardized meal in five experimental sessions, one alone (Control) and the other after prior intake of 3 or 6 g of crude cinnamon in the form of hard gelatin capsules or powder dissolved in water. Blood glucose was measured at fasting and at 0.25, 0.5, 0.75, 1, 1.5 and 2 hours postprandially. After each breakfast, its palatability scores for visual appeal, smell and pleasantness of taste were assessed, as well as the taste intensity sweetness, saltiness, bitterness, sourness and creaminess. RESULTS The intake of raw cinnamon dissolved in water, independently of the dose, decreased the meal-induced large glucose spike (peak-rise of +87 mg/dL and Δ1-hour glycemia of +79 mg/dL) and the hyperglycemic blood glucose peak. When cinnamon was taken as capsules, these anti-hyperglycemic effects were lost or significantly diminished. Raw cinnamon intake did not change time-to-peak or the 2-h post-meal glycaemia, but flattened the glycemic curve (lower iAUC) without changing the shape that is typical of T2DM patients. CONCLUSIONS This cinnamon's antihyperglycemic action confirms its acarbose-like property to inhibit the activities of the carbohydrate-digesting enzymes α-amylases/α-glucosidases, which is in accordance with its exceptionally high content of raw insoluble fiber. The efficacy of using raw cinnamon as a diabetes treatment strategy seems to require its intake at a specific time before/concomitantly the main hyperglycemic daily meals. Trial registration: Registro Brasileiro de Ensaios Clínicos (ReBEC), number RBR-98tx28b.
Collapse
Affiliation(s)
- Fernanda Duarte Moreira
- Ministério da Saúde, Brasília, Brazil
- Secretaria de Estado de Saúde do Distrito Federal, Brasília, Brazil
- Programa de Pós-Graduação em Ciências e Tecnologias em Saúde, Universidade de Brasília, Brasília, Brazil
| | | | - Andrea Donatti Gallassi
- Programa de Pós-Graduação em Ciências e Tecnologias em Saúde, Universidade de Brasília, Brasília, Brazil
| | | | - Alexis Fonseca Welker
- Programa de Pós-Graduação em Ciências e Tecnologias em Saúde, Universidade de Brasília, Brasília, Brazil
| |
Collapse
|
2
|
Jagannathan R, Stefanovski D, Smiley DD, Oladejo O, Cotten LF, Umpierrez G, Vellanki P. 1-h Glucose During Oral Glucose Tolerance Test Predicts Hyperglycemia Relapse-Free Survival in Obese Black Patients With Hyperglycemic Crises. Front Endocrinol (Lausanne) 2022; 13:871965. [PMID: 35721763 PMCID: PMC9202609 DOI: 10.3389/fendo.2022.871965] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE Approximately 50% of obese Black patients with unprovoked diabetic ketoacidosis (DKA) or severe hyperglycemia (SH) at new-onset diabetes achieve near-normoglycemia remission with intensive insulin treatment. Despite the initial near-normoglycemia remission, most DKA/SH individuals develop hyperglycemia relapse after insulin discontinuation. Traditional biomarkers such as normal glucose tolerance at the time of remission were not predictive of hyperglycemia relapse. We tested whether 1-h plasma glucose (1-h PG) at remission predicts hyperglycemia relapse in Black patients with DKA/SH. METHODS Secondary analysis was performed of two prospective randomized controlled trials in 73 patients with DKA/SH at the safety net hospital with a median follow-up of 408 days. Patients with DKA/SH underwent a 5-point, 2-h 75-g oral glucose tolerance test after hyperglycemia remission. Hyperglycemia relapse is defined by fasting blood glucose (FBG) > 130 mg/dl, random blood glucose (BG) >180 mg/dl, or HbA1c > 7%. RESULTS During the median 408 (interquartile range: 110-602) days of follow-up, hyperglycemia relapse occurred in 28 (38.4%) participants. One-hour PG value ≥199 mg/dl discriminates hyperglycemia relapse (sensitivity: 64%; specificity: 71%). Elevated levels of 1-h PG (≥199 mg/dl) were independently associated with hyperglycemia relapse (adjusted hazard ratio: 2.40 [95% CI: 1.04, 5.56]). In a multivariable model with FBG, adding 1-h PG level enhanced the prediction of hyperglycemia relapse, with significant improvements in C-index (Δ: +0.05; p = 0.04), net reclassification improvement (NRI: 48.7%; p = 0.04), and integrated discrimination improvement (IDI: 7.8%; p = 0.02) as compared with the addition of 2-h PG (NRI: 20.2%; p = 0.42; IDI: 1.32%; p = 0.41) or HbA1c (NRI: 35.2%; p = 0.143; IDI: 5.8%; p = 0.04). CONCLUSION One-hour PG at the time of remission is a better predictor of hyperglycemia relapse than traditional glycemic markers among obese Black patients presenting with DKA/SH. Testing 1-h PG at insulin discontinuation identifies individuals at high risk of developing hyperglycemia relapse.
Collapse
Affiliation(s)
- Ram Jagannathan
- Division of Hospital Medicine, Emory University School of Medicine, Atlanta GA, United States
| | - Darko Stefanovski
- Department of Biostatistics, University of Pennsylvania School of Veterinary Medicine, Kennett Square, PA, United States
| | - Dawn D. Smiley
- Division of Endocrinology, Metabolism and Lipids, Emory University School of Medicine, Atlanta, GA, United States
| | - Omolade Oladejo
- Division of Endocrinology, Metabolism and Lipids, Emory University School of Medicine, Atlanta, GA, United States
| | - Lucia F. Cotten
- Division of Endocrinology, Metabolism and Lipids, Emory University School of Medicine, Atlanta, GA, United States
| | - Guillermo Umpierrez
- Division of Endocrinology, Metabolism and Lipids, Emory University School of Medicine, Atlanta, GA, United States
| | - Priyathama Vellanki
- Division of Endocrinology, Metabolism and Lipids, Emory University School of Medicine, Atlanta, GA, United States
- *Correspondence: Priyathama Vellanki,
| |
Collapse
|
3
|
Farmer BC, Williams HC, Devanney NA, Piron MA, Nation GK, Carter DJ, Walsh AE, Khanal R, Young LEA, Kluemper JC, Hernandez G, Allenger EJ, Mooney R, Golden LR, Smith CT, Brandon JA, Gupta VA, Kern PA, Gentry MS, Morganti JM, Sun RC, Johnson LA. APOΕ4 lowers energy expenditure in females and impairs glucose oxidation by increasing flux through aerobic glycolysis. Mol Neurodegener 2021; 16:62. [PMID: 34488832 PMCID: PMC8420022 DOI: 10.1186/s13024-021-00483-y] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 08/15/2021] [Indexed: 01/21/2023] Open
Abstract
Background Cerebral glucose hypometabolism is consistently observed in individuals with Alzheimer’s disease (AD), as well as in young cognitively normal carriers of the Ε4 allele of Apolipoprotein E (APOE), the strongest genetic predictor of late-onset AD. While this clinical feature has been described for over two decades, the mechanism underlying these changes in cerebral glucose metabolism remains a critical knowledge gap in the field. Methods Here, we undertook a multi-omic approach by combining single-cell RNA sequencing (scRNAseq) and stable isotope resolved metabolomics (SIRM) to define a metabolic rewiring across astrocytes, brain tissue, mice, and human subjects expressing APOE4. Results Single-cell analysis of brain tissue from mice expressing human APOE revealed E4-associated decreases in genes related to oxidative phosphorylation, particularly in astrocytes. This shift was confirmed on a metabolic level with isotopic tracing of 13C-glucose in E4 mice and astrocytes, which showed decreased pyruvate entry into the TCA cycle and increased lactate synthesis. Metabolic phenotyping of E4 astrocytes showed elevated glycolytic activity, decreased oxygen consumption, blunted oxidative flexibility, and a lower rate of glucose oxidation in the presence of lactate. Together, these cellular findings suggest an E4-associated increase in aerobic glycolysis (i.e. the Warburg effect). To test whether this phenomenon translated to APOE4 humans, we analyzed the plasma metabolome of young and middle-aged human participants with and without the Ε4 allele, and used indirect calorimetry to measure whole body oxygen consumption and energy expenditure. In line with data from E4-expressing female mice, a subgroup analysis revealed that young female E4 carriers showed a striking decrease in energy expenditure compared to non-carriers. This decrease in energy expenditure was primarily driven by a lower rate of oxygen consumption, and was exaggerated following a dietary glucose challenge. Further, the stunted oxygen consumption was accompanied by markedly increased lactate in the plasma of E4 carriers, and a pathway analysis of the plasma metabolome suggested an increase in aerobic glycolysis. Conclusions Together, these results suggest astrocyte, brain and system-level metabolic reprogramming in the presence of APOE4, a ‘Warburg like’ endophenotype that is observable in young females decades prior to clinically manifest AD. Supplementary Information The online version contains supplementary material available at 10.1186/s13024-021-00483-y.
Collapse
Affiliation(s)
- Brandon C Farmer
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - Holden C Williams
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA.,Sanders Brown Center on Aging, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Nicholas A Devanney
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA.,Sanders Brown Center on Aging, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Margaret A Piron
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - Grant K Nation
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - David J Carter
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - Adeline E Walsh
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - Rebika Khanal
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - Lyndsay E A Young
- Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, USA
| | - Jude C Kluemper
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - Gabriela Hernandez
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - Elizabeth J Allenger
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - Rachel Mooney
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - Lesley R Golden
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - Cathryn T Smith
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - J Anthony Brandon
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA
| | - Vedant A Gupta
- Gill Heart and Vascular Institute, University of Kentucky, Lexington, KY, USA
| | - Philip A Kern
- Center for Clinical and Translational Science, University of Kentucky College of Medicine, Lexington, KY, USA.,Department of Internal Medicine, Division of Endocrinology, University of Kentucky, Lexington, KY, USA
| | - Matthew S Gentry
- Department of Molecular and Cellular Biochemistry, University of Kentucky, Lexington, KY, USA
| | - Josh M Morganti
- Sanders Brown Center on Aging, University of Kentucky College of Medicine, Lexington, KY, USA.,Department of Neuroscience, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Ramon C Sun
- Department of Neuroscience, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Lance A Johnson
- Department of Physiology, University of Kentucky College of Medicine, UKMC/MS 609, 800 Rose Street, Lexington, KY, 40536, USA. .,Sanders Brown Center on Aging, University of Kentucky College of Medicine, Lexington, KY, USA.
| |
Collapse
|
4
|
Mussa J, Meltzer S, Bond R, Garfield N, Dasgupta K. Trends in National Canadian Guideline Recommendations for the Screening and Diagnosis of Gestational Diabetes Mellitus over the Years: A Scoping Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:1454. [PMID: 33557155 PMCID: PMC7913952 DOI: 10.3390/ijerph18041454] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Revised: 01/29/2021] [Accepted: 02/01/2021] [Indexed: 11/16/2022]
Abstract
Canada's largest national obstetric and diabetology organizations have recommended various algorithms for the screening of gestational diabetes mellitus (GDM) over the years. Though uniformity across recommendations from clinical practice guidelines (CPGs) is desirable, historically, national guidelines from Diabetes Canada (DC) and the Society of Obstetricians and Gynaecologists of Canada (SOGC) have differed. Lack of consensus has led to variation in screening approaches, rendering precise ascertainment of GDM prevalence challenging. To highlight the reason and level of disparity in Canada, we conducted a scoping review of CPGs released by DC and the SOGC over the last thirty years and distributed a survey on screening practices among Canadian physicians. Earlier CPGs were based on expert opinion, leading to different recommendations from these organizations. However, as a result of the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study, disparities between DC and the SOGC no longer exist and many Canadian physicians have adopted their recent recommendations. Given that Canadian guidelines now recommend two different screening programs (one step vs. two step), lack of consensus on a single diagnostic threshold continues to exist, resulting in differing estimates of GDM prevalence. Our scoping review highlights these disparities and provides a step forward towards reaching a consensus on one unified threshold.
Collapse
Affiliation(s)
- Joseph Mussa
- Department of Medicine, McGill University, Montreal, QC H4A 3J1, Canada; (J.M.); (S.M.); (R.B.); (N.G.)
- Centre for Outcomes Research and Evaluation of the RI-MUHC, 5252 boul de Maisonneuve Ouest, Office 3E.09, Montreal, QC H4A 3S5, Canada
| | - Sara Meltzer
- Department of Medicine, McGill University, Montreal, QC H4A 3J1, Canada; (J.M.); (S.M.); (R.B.); (N.G.)
- Department of Obstetrics and Gynecology, McGill University, Montreal, QC H4A 3J1, Canada
| | - Rachel Bond
- Department of Medicine, McGill University, Montreal, QC H4A 3J1, Canada; (J.M.); (S.M.); (R.B.); (N.G.)
| | - Natasha Garfield
- Department of Medicine, McGill University, Montreal, QC H4A 3J1, Canada; (J.M.); (S.M.); (R.B.); (N.G.)
| | - Kaberi Dasgupta
- Department of Medicine, McGill University, Montreal, QC H4A 3J1, Canada; (J.M.); (S.M.); (R.B.); (N.G.)
- Centre for Outcomes Research and Evaluation of the RI-MUHC, 5252 boul de Maisonneuve Ouest, Office 3E.09, Montreal, QC H4A 3S5, Canada
| |
Collapse
|
5
|
Fishbein HA, Birch RJ, Mathew SM, Sawyer HL, Pulver G, Poling J, Kaelber D, Mardon R, Johnson MC, Pace W, Umbel KD, Zhang X, Siegel KR, Imperatore G, Shrestha S, Proia K, Cheng Y, McKeever Bullard K, Gregg EW, Rolka D, Pavkov ME. The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR): Unique 1.4 M patient Electronic Health Record cohort. HEALTHCARE (AMSTERDAM, NETHERLANDS) 2020; 8:100458. [PMID: 33011645 PMCID: PMC11008431 DOI: 10.1016/j.hjdsi.2020.100458] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 06/17/2020] [Accepted: 07/27/2020] [Indexed: 01/22/2023]
Abstract
BACKGROUND The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR) study uses a novel Electronic Health Record (EHR) data approach as a tool to assess the epidemiology of known and new risk factors for type 2 diabetes mellitus (T2DM) and study how prevention interventions affect progression to and onset of T2DM. We created an electronic cohort of 1.4 million patients having had at least 4 encounters with a healthcare organization for at least 24-months; were aged ≥18 years in 2010; and had no diabetes (i.e., T1DM or T2DM) at cohort entry or in the 12 months following entry. EHR data came from patients at nine healthcare organizations across the U.S. between January 1, 2010-December 31, 2016. RESULTS Approximately 5.9% of the LEADR cohort (82,922 patients) developed T2DM, providing opportunities to explore longitudinal clinical care, medication use, risk factor trajectories, and diagnoses for these patients, compared with patients similarly matched prior to disease onset. CONCLUSIONS LEADR represents one of the largest EHR databases to have repurposed EHR data to examine patients' T2DM risk. This paper is first in a series demonstrating this novel approach to studying T2DM. IMPLICATIONS Chronic conditions that often take years to develop can be studied efficiently using EHR data in a retrospective design. LEVEL OF EVIDENCE While much is already known about T2DM risk, this EHR's cohort's 160 M data points for 1.4 M people over six years, provides opportunities to investigate new unique risk factors and evaluate research hypotheses where results could modify public health practice for preventing T2DM.
Collapse
Affiliation(s)
| | | | | | | | - Gerald Pulver
- University of Colorado Anschutz Medical Campus, Denver, CO, USA
| | | | - David Kaelber
- The MetroHealth System and Case Western Reserve University, Cleveland, OH, USA
| | | | | | | | | | - Xuanping Zhang
- Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, GA, USA
| | - Karen R Siegel
- Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, GA, USA
| | - Giuseppina Imperatore
- Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, GA, USA
| | - Sundar Shrestha
- Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, GA, USA
| | - Krista Proia
- Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, GA, USA
| | - Yiling Cheng
- Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, GA, USA
| | - Kai McKeever Bullard
- Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, GA, USA
| | - Edward W Gregg
- Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, GA, USA
| | - Deborah Rolka
- Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, GA, USA
| | - Meda E Pavkov
- Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, GA, USA
| |
Collapse
|
6
|
Dadwani RS, Skandari MR, GoodSmith MS, Phillips LS, Rhee MK, Laiteerapong N. Alternative type 2 diabetes screening tests may reduce the number of U.S. adults with undiagnosed diabetes. Diabet Med 2020; 37:1935-1943. [PMID: 32449198 PMCID: PMC7572743 DOI: 10.1111/dme.14330] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/18/2020] [Indexed: 12/12/2022]
Abstract
AIM To evaluate the U.S. population-level impact of two alternatives for initial type 2 diabetes screening [opportunistic random plasma glucose (RPG) > 6.7 mmol/l and a 1-h 50-g glucose challenge test (GCT) > 8.9 mmol/l] compared with American Diabetes Association (ADA)-recommended tests. METHODS Using a sample (n = 1471) from the National Health and Nutrition Examination Survey (NHANES) 2013-2014 that represented 145 million U.S. adults at high risk for developing type 2 diabetes, we simulated a two-test screening process. We compared ADA-recommended screening tests [fasting plasma glucose (FPG), 2-h 75-g oral glucose tolerance test (OGTT), HbA1c ] vs. initial screening with opportunistic RPG or GCT (followed by FPG, OGTT or HbA1c ). After simulation, participants were entered into an individual-level Monte Carlo-based Markov lifetime outcomes model. Primary outcomes were representative number of U.S. adults correctly identified with type 2 diabetes, societal lifetime costs and quality-adjusted life years (QALYs). RESULTS In NHANES 2013-2014, 100 individuals had undiagnosed diabetes [weighted estimate: 8.4 million, standard error (se): 1.1 million]. Among ADA-recommended screening tests, FPG followed by OGTT (FPG-OGTT) was most sensitive, identifying 35 individuals with undiagnosed diabetes (weighted estimate: 3.2 million, se: 0.9 million). Four alternative screening strategies performed superior to FPG-OGTT, with RPG followed by OGTT being the most sensitive overall, identifying 72 individuals with undiagnosed diabetes (weighted estimate: 6.1 million, se: 1.0 million). There was no increase in average lifetime costs and comparable QALYs. CONCLUSIONS Initial screening using opportunistic RPG or a GCT may identify more U.S. adults with type 2 diabetes without increasing societal costs.
Collapse
Affiliation(s)
- R S Dadwani
- Pritzker School of Medicine, Chicago, IL, USA
| | - M R Skandari
- Imperial College Business School, Imperial College London, London, UK
| | | | - L S Phillips
- Division of Endocrinology and Metabolism, Department of Medicine, Emory School of Medicine, Atlanta, GA, USA
- Atlanta VA Medical Center, Decatur, GA, USA
| | - M K Rhee
- Division of Endocrinology and Metabolism, Department of Medicine, Emory School of Medicine, Atlanta, GA, USA
- Atlanta VA Medical Center, Decatur, GA, USA
| | - N Laiteerapong
- Section of General Internal Medicine, University of Chicago, Chicago, IL, USA
| |
Collapse
|
7
|
Jagannathan R, Neves JS, Dorcely B, Chung ST, Tamura K, Rhee M, Bergman M. The Oral Glucose Tolerance Test: 100 Years Later. Diabetes Metab Syndr Obes 2020; 13:3787-3805. [PMID: 33116727 PMCID: PMC7585270 DOI: 10.2147/dmso.s246062] [Citation(s) in RCA: 91] [Impact Index Per Article: 18.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 09/24/2020] [Indexed: 12/15/2022] Open
Abstract
For over 100 years, the oral glucose tolerance test (OGTT) has been the cornerstone for detecting prediabetes and type 2 diabetes (T2DM). In recent decades, controversies have arisen identifying internationally acceptable cut points using fasting plasma glucose (FPG), 2-h post-load glucose (2-h PG), and/or HbA1c for defining intermediate hyperglycemia (prediabetes). Despite this, there has been a steadfast global consensus of the 2-h PG for defining dysglycemic states during the OGTT. This article reviews the history of the OGTT and recent advances in its application, including the glucose challenge test and mathematical modeling for determining the shape of the glucose curve. Pitfalls of the FPG, 2-h PG during the OGTT, and HbA1c are considered as well. Finally, the associations between the 30-minute and 1-hour plasma glucose (1-h PG) levels derived from the OGTT and incidence of diabetes and its complications will be reviewed. The considerable evidence base supports modifying current screening and diagnostic recommendations with the use of the 1-h PG. Measurement of the 1-h PG level could increase the likelihood of identifying high-risk individuals when the pancreatic ß-cell function is substantially more intact with the added practical advantage of potentially replacing the conventional 2-h OGTT making it more acceptable in the clinical setting.
Collapse
Affiliation(s)
- Ram Jagannathan
- Division of Hospital Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - João Sérgio Neves
- Department of Surgery and Physiology, Cardiovascular Research and Development Center, Faculty of Medicine, University of Porto, Porto, Portugal
- Department of Endocrinology, Diabetes and Metabolism, Sa˜o Joa˜ o University Hospital Center, Porto, Portugal
| | - Brenda Dorcely
- NYU Grossman School of Medicine, Division of Endocrinology, Diabetes, Metabolism, New York, NY10016, USA
| | - Stephanie T Chung
- Diabetes, Obesity, and Endocrinology Branch, National Institute of Diabetes & Digestive & Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Kosuke Tamura
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD20892, USA
| | - Mary Rhee
- Emory University School of Medicine, Department of Medicine, Division of Endocrinology, Metabolism, and Lipids, Atlanta VA Health Care System, Atlanta, GA30322, USA
| | - Michael Bergman
- NYU Grossman School of Medicine, NYU Diabetes Prevention Program, Endocrinology, Diabetes, Metabolism, VA New York Harbor Healthcare System, Manhattan Campus, New York, NY10010, USA
| |
Collapse
|
8
|
Cao Z, Yao F, Lang Y, Feng X. Elevated Circulating LINC-P21 Serves as a Diagnostic Biomarker of Type 2 Diabetes Mellitus and Regulates Pancreatic β-cell Function by Sponging miR-766-3p to Upregulate NR3C2. Exp Clin Endocrinol Diabetes 2020; 130:156-164. [PMID: 33007789 DOI: 10.1055/a-1247-4978] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
OBJECTIVE The purpose of this study was to evaluate the clinical value and biological function of long non-coding RNA (lncRNA) LINC-P21 in type 2 diabetes mellitus (T2DM), and explore the underlying mechanisms. METHODS The expression of LINC-P21 was estimated using quantitative real-time PCR. The functional role of LINC-P21 was explored by gain- and loss-of-function experiments. INS-1 cell proliferation was analyzed using a cell counting kit-8 (CCK-8)assay, and the glucose-stimulated insulin secretion was measured using an ELISA kit. The miRNAs that might be sponged by LINC-P21 were analyzed, and the subsequent target genes were predicted and assessed in INS-1 cells. RESULTS Serum expression of LINC-P21 was elevated in T2DM patients, which was correlated with fasting blood glucose levels and disease diagnosis. The glucose-stimulated insulin secretion and the proliferation of INS-1 cells were enhanced by LINC-P21 knockdown, but the overexpression of LINC-P21 led to opposite effects. miR-766-3p could be directly inhibited by LINC-P21 in INS-1 cells and reverse the effects of LINC-P21 on β-cell function. Additionally, NR3C2 was determined as a target of miR-766-3p, which could be positively regulated by LINC-P21 and had same effects with LINC-P21 on INS-1 cell proliferation and insulin secretion. CONCLUSION All the data demonstrated that serum elevated LINC-P21 and decreased miR-766-3p serve as candidate diagnostic biomarkers in T2DM patients. LINC-P21 acts as a potential regulator in insulin secretion and proliferation of pancreatic β-cells through targeting miR-766-3p to upregulate NR3C2.
Collapse
Affiliation(s)
- Zhibin Cao
- Department of Endocrinology, Affiliated Hospital of Weifang Medical University, Weifang, Shandong
| | - Fuwang Yao
- Department of Anesthesiology, Affiliated Hospital of Weifang Medical University, Weifang, Shandong
| | - Yuqin Lang
- Department of Endoscopic Outpatient Operating Room, Affiliated Hospital of Weifang Medical University, Weifang, Shandong
| | - Xueqiang Feng
- Vascular Intervention Department, Affiliated Hospital of Weifang Medical University, Weifang, Shandong
| |
Collapse
|
9
|
Tucker LA. Limited Agreement between Classifications of Diabetes and Prediabetes Resulting from the OGTT, Hemoglobin A1c, and Fasting Glucose Tests in 7412 U.S. Adults. J Clin Med 2020; 9:jcm9072207. [PMID: 32668564 PMCID: PMC7408667 DOI: 10.3390/jcm9072207] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2020] [Revised: 07/04/2020] [Accepted: 07/10/2020] [Indexed: 12/22/2022] Open
Abstract
This investigation was designed to determine the degree of concordance resulting from tests of fasting plasma glucose (FPG) and hemoglobin A1c (A1c) compared to the oral glucose tolerance test (OGTT) for detecting prediabetes and diabetes in undiagnosed adults. Another objective was to measure concordance within subsamples of women and men, and within three age groups. Lastly, the value of combining the FPG and A1c for detecting diabetes was compared to the OGTT. A total of 7412 randomly selected adults from the National Health and Nutrition Examination Survey (NHANES) were included. With outcomes classified as normal, prediabetes, or diabetes, according to standard guidelines, overall test agreements were low. With an OGTT diagnosis of diabetes, concordance was only 34% for the A1c assessment and 44% for the FPG assay. Delimited to older adults, agreement between the OGTT and A1c was only 25%, and between the OGTT and FPG, concordance was only 33.5%. Given the large percentage of discordant results associated with the FPG and A1c, clinicians should be cautious about employing these tests as lone assessments. Using both the FPG and A1c helped with accurately diagnosing diabetes and normal glycemia, but not prediabetes. The OGTT is a good choice to reduce misdiagnosis.
Collapse
Affiliation(s)
- Larry A Tucker
- College of Life Sciences, Brigham Young University, Provo, UT 84602, USA
| |
Collapse
|
10
|
Limited Agreement between Classifications of Diabetes and Prediabetes Resulting from the OGTT, Hemoglobin A1c, and Fasting Glucose Tests in 7412 U.S. Adults. J Clin Med 2020. [DOI: 10.3390/jcm9072207 [doi]] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
This investigation was designed to determine the degree of concordance resulting from tests of fasting plasma glucose (FPG) and hemoglobin A1c (A1c) compared to the oral glucose tolerance test (OGTT) for detecting prediabetes and diabetes in undiagnosed adults. Another objective was to measure concordance within subsamples of women and men, and within three age groups. Lastly, the value of combining the FPG and A1c for detecting diabetes was compared to the OGTT. A total of 7412 randomly selected adults from the National Health and Nutrition Examination Survey (NHANES) were included. With outcomes classified as normal, prediabetes, or diabetes, according to standard guidelines, overall test agreements were low. With an OGTT diagnosis of diabetes, concordance was only 34% for the A1c assessment and 44% for the FPG assay. Delimited to older adults, agreement between the OGTT and A1c was only 25%, and between the OGTT and FPG, concordance was only 33.5%. Given the large percentage of discordant results associated with the FPG and A1c, clinicians should be cautious about employing these tests as lone assessments. Using both the FPG and A1c helped with accurately diagnosing diabetes and normal glycemia, but not prediabetes. The OGTT is a good choice to reduce misdiagnosis.
Collapse
|
11
|
Limited Agreement between Classifications of Diabetes and Prediabetes Resulting from the OGTT, Hemoglobin A1c, and Fasting Glucose Tests in 7412 U.S. Adults. J Clin Med 2020. [PMID: 32668564 DOI: 10.3390/jcm9072207+[doi]] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
This investigation was designed to determine the degree of concordance resulting from tests of fasting plasma glucose (FPG) and hemoglobin A1c (A1c) compared to the oral glucose tolerance test (OGTT) for detecting prediabetes and diabetes in undiagnosed adults. Another objective was to measure concordance within subsamples of women and men, and within three age groups. Lastly, the value of combining the FPG and A1c for detecting diabetes was compared to the OGTT. A total of 7412 randomly selected adults from the National Health and Nutrition Examination Survey (NHANES) were included. With outcomes classified as normal, prediabetes, or diabetes, according to standard guidelines, overall test agreements were low. With an OGTT diagnosis of diabetes, concordance was only 34% for the A1c assessment and 44% for the FPG assay. Delimited to older adults, agreement between the OGTT and A1c was only 25%, and between the OGTT and FPG, concordance was only 33.5%. Given the large percentage of discordant results associated with the FPG and A1c, clinicians should be cautious about employing these tests as lone assessments. Using both the FPG and A1c helped with accurately diagnosing diabetes and normal glycemia, but not prediabetes. The OGTT is a good choice to reduce misdiagnosis.
Collapse
|
12
|
Bergman M, Abdul-Ghani M, DeFronzo RA, Manco M, Sesti G, Fiorentino TV, Ceriello A, Rhee M, Phillips LS, Chung S, Cravalho C, Jagannathan R, Monnier L, Colette C, Owens D, Bianchi C, Del Prato S, Monteiro MP, Neves JS, Medina JL, Macedo MP, Ribeiro RT, Filipe Raposo J, Dorcely B, Ibrahim N, Buysschaert M. Review of methods for detecting glycemic disorders. Diabetes Res Clin Pract 2020; 165:108233. [PMID: 32497744 PMCID: PMC7977482 DOI: 10.1016/j.diabres.2020.108233] [Citation(s) in RCA: 116] [Impact Index Per Article: 23.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 05/19/2020] [Indexed: 02/07/2023]
Abstract
Prediabetes (intermediate hyperglycemia) consists of two abnormalities, impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) detected by a standardized 75-gram oral glucose tolerance test (OGTT). Individuals with isolated IGT or combined IFG and IGT have increased risk for developing type 2 diabetes (T2D) and cardiovascular disease (CVD). Diagnosing prediabetes early and accurately is critical in order to refer high-risk individuals for intensive lifestyle modification. However, there is currently no international consensus for diagnosing prediabetes with HbA1c or glucose measurements based upon American Diabetes Association (ADA) and the World Health Organization (WHO) criteria that identify different populations at risk for progressing to diabetes. Various caveats affecting the accuracy of interpreting the HbA1c including genetics complicate this further. This review describes established methods for detecting glucose disorders based upon glucose and HbA1c parameters as well as novel approaches including the 1-hour plasma glucose (1-h PG), glucose challenge test (GCT), shape of the glucose curve, genetics, continuous glucose monitoring (CGM), measures of insulin secretion and sensitivity, metabolomics, and ancillary tools such as fructosamine, glycated albumin (GA), 1,5- anhydroglucitol (1,5-AG). Of the approaches considered, the 1-h PG has considerable potential as a biomarker for detecting glucose disorders if confirmed by additional data including health economic analysis. Whether the 1-h OGTT is superior to genetics and omics in providing greater precision for individualized treatment requires further investigation. These methods will need to demonstrate substantially superiority to simpler tools for detecting glucose disorders to justify their cost and complexity.
Collapse
Affiliation(s)
- Michael Bergman
- NYU School of Medicine, NYU Diabetes Prevention Program, Endocrinology, Diabetes, Metabolism, VA New York Harbor Healthcare System, Manhattan Campus, 423 East 23rd Street, Room 16049C, NY, NY 10010, USA.
| | - Muhammad Abdul-Ghani
- Division of Diabetes, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA.
| | - Ralph A DeFronzo
- Division of Diabetes, University of Texas Health Science Center at San Antonio, San Antonio, TX 78229, USA.
| | - Melania Manco
- Research Area for Multifactorial Diseases, Bambino Gesù Children Hospital, Rome, Italy.
| | - Giorgio Sesti
- Department of Clinical and Molecular Medicine, University of Rome Sapienza, Rome 00161, Italy
| | - Teresa Vanessa Fiorentino
- Department of Medical and Surgical Sciences, University Magna Græcia of Catanzaro, Catanzaro 88100, Italy.
| | - Antonio Ceriello
- Department of Cardiovascular and Metabolic Diseases, Istituto Ricerca Cura Carattere Scientifico Multimedica, Sesto, San Giovanni (MI), Italy.
| | - Mary Rhee
- Emory University School of Medicine, Department of Medicine, Division of Endocrinology, Metabolism, and Lipids, Atlanta VA Health Care System, Atlanta, GA 30322, USA.
| | - Lawrence S Phillips
- Emory University School of Medicine, Department of Medicine, Division of Endocrinology, Metabolism, and Lipids, Atlanta VA Health Care System, Atlanta, GA 30322, USA.
| | - Stephanie Chung
- Diabetes Endocrinology and Obesity Branch, National Institutes of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Celeste Cravalho
- Diabetes Endocrinology and Obesity Branch, National Institutes of Diabetes, Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Ram Jagannathan
- Emory University School of Medicine, Department of Medicine, Division of Endocrinology, Metabolism, and Lipids, Atlanta VA Health Care System, Atlanta, GA 30322, USA.
| | - Louis Monnier
- Institute of Clinical Research, University of Montpellier, Montpellier, France.
| | - Claude Colette
- Institute of Clinical Research, University of Montpellier, Montpellier, France.
| | - David Owens
- Diabetes Research Group, Institute of Life Science, Swansea University, Wales, UK.
| | - Cristina Bianchi
- University Hospital of Pisa, Section of Metabolic Diseases and Diabetes, University Hospital, University of Pisa, Pisa, Italy.
| | - Stefano Del Prato
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.
| | - Mariana P Monteiro
- Endocrine, Cardiovascular & Metabolic Research, Unit for Multidisciplinary Research in Biomedicine (UMIB), University of Porto, Porto, Portugal; Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal.
| | - João Sérgio Neves
- Department of Surgery and Physiology, Cardiovascular Research and Development Center, Faculty of Medicine, University of Porto, Porto, Portugal; Department of Endocrinology, Diabetes and Metabolism, São João University Hospital Center, Porto, Portugal.
| | | | - Maria Paula Macedo
- CEDOC-Centro de Estudos de Doenças Crónicas, NOVA Medical School, Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Lisboa, Portugal; APDP-Diabetes Portugal, Education and Research Center (APDP-ERC), Lisboa, Portugal.
| | - Rogério Tavares Ribeiro
- Institute for Biomedicine, Department of Medical Sciences, University of Aveiro, APDP Diabetes Portugal, Education and Research Center (APDP-ERC), Aveiro, Portugal.
| | - João Filipe Raposo
- CEDOC-Centro de Estudos de Doenças Crónicas, NOVA Medical School, Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Lisboa, Portugal; APDP-Diabetes Portugal, Education and Research Center (APDP-ERC), Lisboa, Portugal.
| | - Brenda Dorcely
- NYU School of Medicine, Division of Endocrinology, Diabetes, Metabolism, NY, NY 10016, USA.
| | - Nouran Ibrahim
- NYU School of Medicine, Division of Endocrinology, Diabetes, Metabolism, NY, NY 10016, USA.
| | - Martin Buysschaert
- Department of Endocrinology and Diabetology, Université Catholique de Louvain, University Clinic Saint-Luc, Brussels, Belgium.
| |
Collapse
|
13
|
Gonzalez A, Deng Y, Lane AN, Benkeser D, Cui X, Staimez LR, Ford CN, Khan FN, Markley Webster SC, Leong A, Wilson PWF, Phillips LS, Rhee MK. Impact of mismatches in HbA 1c vs glucose values on the diagnostic classification of diabetes and prediabetes. Diabet Med 2020; 37:689-696. [PMID: 31721287 DOI: 10.1111/dme.14181] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/11/2019] [Indexed: 12/18/2022]
Abstract
AIMS To determine whether HbA1c mismatches (HbA1c levels that are higher or lower than expected for the average glucose levels in different individuals) could lead to errors if diagnostic classification is based only on HbA1c levels. METHODS In a cross-sectional study, 3106 participants without known diabetes underwent a 75-g oral glucose tolerance test (fasting glucose and 2-h glucose) and a 50-g glucose challenge test (1-h glucose) on separate days. They were classified by oral glucose tolerance test results as having: normal glucose metabolism; prediabetes; or diabetes. Predicted HbA1c was determined from the linear regression modelling the relationship between observed HbA1c and average glucose (mean of fasting glucose and 2-h glucose from the oral glucose tolerance test, and 1-h glucose from the glucose challenge test) within oral glucose tolerance test groups. The haemoglobin glycation index was calculated as [observed - predicted HbA1c ], and divided into low, intermediate and high haemoglobin glycation index mismatch tertiles. RESULTS Those participants with higher mismatches were more likely to be black, to be men, to be older, and to have higher BMI (all P<0.001). Using oral glucose tolerance test criteria, the distribution of normal glucose metabolism, prediabetes and diabetes was similar across mismatch tertiles; however, using HbA1c criteria, the participants with low mismatches were classified as 97% normal glucose metabolism, 3% prediabetes and 0% diabetes, i.e. mostly normal, while those with high mismatches were classified as 13% normal glucose metabolism, 77% prediabetes and 10% diabetes, i.e. mostly abnormal (P<0.001). CONCLUSIONS Measuring only HbA1c could lead to under-diagnosis in people with low mismatches and over-diagnosis in those with high mismatches. Additional oral glucose tolerance tests and/or fasting glucose testing to complement HbA1c in diagnostic classification should be performed in most individuals.
Collapse
Affiliation(s)
- A Gonzalez
- Atlanta VA Health Care System, Decatur, GA, USA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Y Deng
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA
| | - A N Lane
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA
| | - D Benkeser
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA
| | - X Cui
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA
| | - L R Staimez
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - C N Ford
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - F N Khan
- Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, University of Washington, Seattle, WA, USA
| | - S C Markley Webster
- Atlanta VA Health Care System, Decatur, GA, USA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - A Leong
- Endocrine Unit, Diabetes Unit, Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - P W F Wilson
- Atlanta VA Health Care System, Decatur, GA, USA
- Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - L S Phillips
- Atlanta VA Health Care System, Decatur, GA, USA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - M K Rhee
- Atlanta VA Health Care System, Decatur, GA, USA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| |
Collapse
|
14
|
Iskandar S, Migahid A, Kamal D, Megahed O, DeFronzo RA, Zirie M, Jayyousi A, Al Jaidah M, Abdul-Ghani M. Glycated hemoglobin versus oral glucose tolerance test in the identification of subjects with prediabetes in Qatari population. BMC Endocr Disord 2019; 19:87. [PMID: 31438915 PMCID: PMC6704621 DOI: 10.1186/s12902-019-0412-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Accepted: 07/19/2019] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Subjects with prediabetes are at increased risk of future T2DM and cardiovascular disease (CVD) compared to NGT individuals. The OGTT (FPG = 100-125 and 2 h-PG = 140-199 mg/dl) and HbA1c 5.7-6.4% have been used to diagnose subjects with prediabetes. In the present study, we compared the ability of the OGTT and HbA1c to identify Qatari subjects with prediabetes. METHODS Four hundred forty six subjects without a history of T2DM received 75-g OGTT and measurement of HbA1c. The incidence of prediabetes in this cohort according to OGTT criteria was compared to that of HbA1c criteria. RESULTS The agreement between the OGTT and HbA1c in identifying subjects with prediabetes in Qatari subjects was poor, though significant (k = 015, p < 0.0001). Only 56% of participants had prediabetes or NGT according to OGTT and HbA1c. The disagreement between OGTT and HbA1c in diagnosing prediabetes was primarily due to low sensitivity of HbA1c. Moreover, subjects with prediabetes diagnosed with the OGTT have more severe metabolic profile than prediabetic subjects diagnosed with HbA1c. Lastly, more subjects with the metabolic syndrome were identified with OGTT (60%) criteria than with the HbA1c (49%), p < 0.0001. CONCLUSION These results demonstrate subjects with prediabetes diagnosed with OGTT have more severe metabolic risk than those diagnosed with HbA1c, and more likely to have greater risk of progression to T2DM.
Collapse
Affiliation(s)
| | - Ayman Migahid
- Academic Health System, Hamad General Hospital, PO Box 3050, Doha, Qatar
| | - Dalia Kamal
- Academic Health System, Hamad General Hospital, PO Box 3050, Doha, Qatar
| | - Osama Megahed
- Academic Health System, Hamad General Hospital, PO Box 3050, Doha, Qatar
| | - Ralph A. DeFronzo
- Diabetes Division, University of Texas Health Science Center, San Antonio, TX USA
| | - Mahmoud Zirie
- Academic Health System, Hamad General Hospital, PO Box 3050, Doha, Qatar
| | - Amin Jayyousi
- Academic Health System, Hamad General Hospital, PO Box 3050, Doha, Qatar
| | | | - Muhammad Abdul-Ghani
- Academic Health System, Hamad General Hospital, PO Box 3050, Doha, Qatar
- Diabetes Division, University of Texas Health Science Center, San Antonio, TX USA
| |
Collapse
|
15
|
Rhee MK, Ho YL, Raghavan S, Vassy JL, Cho K, Gagnon D, Staimez LR, Ford CN, Wilson PWF, Phillips LS. Random plasma glucose predicts the diagnosis of diabetes. PLoS One 2019; 14:e0219964. [PMID: 31323063 PMCID: PMC6641200 DOI: 10.1371/journal.pone.0219964] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 07/06/2019] [Indexed: 11/19/2022] Open
Abstract
Aims/Hypothesis Early recognition of those at high risk for diabetes as well as diabetes itself can permit preventive management, but many Americans with diabetes are undiagnosed. We sought to determine whether routinely available outpatient random plasma glucose (RPG) would be useful to facilitate the diagnosis of diabetes. Methods Retrospective cohort study of 942,446 U.S. Veterans without diagnosed diabetes, ≥3 RPG in a baseline year, and ≥1 primary care visit/year during 5-year follow-up. The primary outcome was incident diabetes (defined by diagnostic codes and outpatient prescription of a diabetes drug). Results Over 5 years, 94,599 were diagnosed with diabetes [DIAB] while 847,847 were not [NONDIAB]. Baseline demographics of DIAB and NONDIAB were clinically similar, except DIAB had higher BMI (32 vs. 28 kg/m2) and RPG (150 vs. 107 mg/dl), and were more likely to have Black race (18% vs. 15%), all p<0.001. ROC area for prediction of DIAB diagnosis within 1 year by demographic factors was 0.701, and 0.708 with addition of SBP, non-HDL cholesterol, and smoking. These were significantly less than that for prediction by baseline RPG alone (≥2 RPGs at/above a given level, ROC 0.878, p<0.001), which improved slightly when other factors were added (ROC 0.900, p<0.001). Having ≥2 RPGs ≥115 mg/dl had specificity 77% and sensitivity 87%, and ≥2 RPGs ≥130 mg/dl had specificity 93% and sensitivity 59%. For predicting diagnosis within 3 and 5 years by RPG alone, ROC was reduced but remained substantial (ROC 0.839 and 0.803, respectively). Conclusions RPG levels below the diabetes “diagnostic” range (≥200 mg/dl) provide good discrimination for follow-up diagnosis. Use of such levels–obtained opportunistically, during outpatient visits–could signal the need for further testing, allow preventive intervention in high risk individuals before onset of disease, and lead to earlier identification of diabetes.
Collapse
Affiliation(s)
- Mary K. Rhee
- Atlanta VA Health Care System, Decatur, Georgia, United States of America
- Department of Medicine, Division of Endocrinology and Metabolism, Emory University School of Medicine, Atlanta, Georgia, United States of America
- * E-mail:
| | - Yuk-Lam Ho
- MAVERIC VA Boston Healthcare System, Boston, Massachusetts, United States of America
| | - Sridharan Raghavan
- VA Eastern Colorado Healthcare System, Aurora, Colorado, United States of America
- Department of Medicine, Division of Hospital Medicine, University of Colorado School of Medicine, Aurora, Colorado, United States of America
| | - Jason L. Vassy
- MAVERIC VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Medicine, Division of General Internal Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Kelly Cho
- MAVERIC VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Medicine, Department of General Aging, Brigham and Women’s Hospital, Boston, Massachusetts, United States of America
| | - David Gagnon
- MAVERIC VA Boston Healthcare System, Boston, Massachusetts, United States of America
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, United States of America
| | - Lisa R. Staimez
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Christopher N. Ford
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Peter W. F. Wilson
- Atlanta VA Health Care System, Decatur, Georgia, United States of America
- Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Lawrence S. Phillips
- Atlanta VA Health Care System, Decatur, Georgia, United States of America
- Department of Medicine, Division of Endocrinology and Metabolism, Emory University School of Medicine, Atlanta, Georgia, United States of America
| |
Collapse
|
16
|
Beksac MS, Tanacan A, Hakli DA, Ozyuncu O. Use of the 50-g glucose challenge test to predict excess delivery weight. Int J Gynaecol Obstet 2018; 142:61-65. [PMID: 29637552 DOI: 10.1002/ijgo.12504] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2017] [Revised: 01/19/2018] [Accepted: 04/05/2018] [Indexed: 02/05/2023]
Abstract
OBJECTIVE To identify a cut-off value for the 50-g glucose challenge test (GCT) that predicts excess delivery weight. METHODS A retrospective study was conducted among pregnant women who undertook a 50-g GCT at Hacettepe University Hospital, Ankara, Turkey, between January 1, 2000, and December 31, 2016. Patients with singleton pregnancies who delivered live neonates after 28 weeks of pregnancy were included. Patients were classified according to their 50-g GCT values into group 1 (<7.770 mmol/L); group 2 (7.770 to <8.880 mmol/L, group 3 (8.880-9.990 mmol/L); or group 4 (>9.990 mmol/L). Classification and regression tree data mining was performed to identify the 50-g GCT cut-off value corresponding to a substantial increase in delivery weight. , RESULTS Median delivery weight were 3100 g in group 1 (n=352), 3200 g in group 2 (n=165), 3720 g in group 3 (n=47), and 3865 g in group 4 (n=20). Gravidity, 50-g GCT value, and pregnancy duration at delivery explained 30.6% of the observed variance in delivery weight. The cut-off required for maternal blood glucose level to predict excessive delivery weight was 8.741 mmol/L. CONCLUSION The 50-g GCT can be used to identify women at risk of delivering offspring with excessive delivery weight.
Collapse
Affiliation(s)
- M Sinan Beksac
- Division of Perinatology, Department of Obstetrics and Gynecology, Hacettepe University Medical Faculty, Ankara, Turkey
| | - Atakan Tanacan
- Division of Perinatology, Department of Obstetrics and Gynecology, Hacettepe University Medical Faculty, Ankara, Turkey
| | - Duygu A Hakli
- Department of Biostatistics, Hacettepe University Medical Faculty, Ankara, Turkey
| | - Ozgur Ozyuncu
- Division of Perinatology, Department of Obstetrics and Gynecology, Hacettepe University Medical Faculty, Ankara, Turkey
| |
Collapse
|
17
|
Velazquez R, Tran A, Ishimwe E, Denner L, Dave N, Oddo S, Dineley KT. Central insulin dysregulation and energy dyshomeostasis in two mouse models of Alzheimer's disease. Neurobiol Aging 2017; 58:1-13. [PMID: 28688899 PMCID: PMC5819888 DOI: 10.1016/j.neurobiolaging.2017.06.003] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Revised: 05/23/2017] [Accepted: 06/09/2017] [Indexed: 12/14/2022]
Abstract
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder worldwide. While the causes of AD are not known, several risk factors have been identified. Among these, type two diabetes (T2D), a chronic metabolic disease, is one of the most prevalent risk factors for AD. Insulin resistance, which is associated with T2D, is defined as diminished or absent insulin signaling and is reflected by peripheral blood hyperglycemia and impaired glucose clearance. In this study, we used complementary approaches to probe for peripheral insulin resistance, central nervous system (CNS) insulin sensitivity and energy homeostasis in Tg2576 and 3xTg-AD mice, two widely used animal models of AD. We report that CNS insulin signaling abnormalities are evident months before peripheral insulin resistance. In addition, we find that brain energy metabolism is differentially altered in both mouse models, with 3xTg-AD mice showing more extensive changes. Collectively, our data suggest that early AD may reflect engagement of different signaling networks that influence CNS metabolism, which in turn may alter peripheral insulin signaling.
Collapse
Affiliation(s)
- Ramon Velazquez
- Arizona State University-Banner Neurodegenerative Disease Research Center at the Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - An Tran
- Arizona State University-Banner Neurodegenerative Disease Research Center at the Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Egide Ishimwe
- Department of Neurology, Mitchell Center for Neurodegenerative Diseases, University of Texas Medical Branch at Galveston (UTMB), Galveston, TX, USA
| | - Larry Denner
- Internal Medicine, Mitchell Center for Neurodegenerative Diseases, University of Texas Medical Branch at Galveston (UTMB), Galveston, TX, USA
| | - Nikhil Dave
- Arizona State University-Banner Neurodegenerative Disease Research Center at the Biodesign Institute, Arizona State University, Tempe, AZ, USA
| | - Salvatore Oddo
- Arizona State University-Banner Neurodegenerative Disease Research Center at the Biodesign Institute, Arizona State University, Tempe, AZ, USA; School of Life Sciences, Arizona State University, Tempe, AZ, USA.
| | - Kelly T Dineley
- Department of Neurology, Mitchell Center for Neurodegenerative Diseases, University of Texas Medical Branch at Galveston (UTMB), Galveston, TX, USA.
| |
Collapse
|