Literature DB >> 32497744

Review of methods for detecting glycemic disorders.

Michael Bergman1, Muhammad Abdul-Ghani2, Ralph A DeFronzo3, Melania Manco4, Giorgio Sesti5, Teresa Vanessa Fiorentino6, Antonio Ceriello7, Mary Rhee8, Lawrence S Phillips9, Stephanie Chung10, Celeste Cravalho11, Ram Jagannathan12, Louis Monnier13, Claude Colette14, David Owens15, Cristina Bianchi16, Stefano Del Prato17, Mariana P Monteiro18, João Sérgio Neves19, Jose Luiz Medina20, Maria Paula Macedo21, Rogério Tavares Ribeiro22, João Filipe Raposo23, Brenda Dorcely24, Nouran Ibrahim25, Martin Buysschaert26.   

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. Published by Elsevier B.V.

Entities:  

Keywords:  Biomarkers; Cardiovascular disease; Continuous glucose monitoring; Glycemic variability; HbA1c; Metabolomics; Oral glucose tolerance test; Prediabetes; Type 2 diabetes

Mesh:

Substances:

Year:  2020        PMID: 32497744      PMCID: PMC7977482          DOI: 10.1016/j.diabres.2020.108233

Source DB:  PubMed          Journal:  Diabetes Res Clin Pract        ISSN: 0168-8227            Impact factor:   5.602


  349 in total

1.  Glucose tolerance, insulin secretion, and insulin sensitivity in nonobese and obese Japanese subjects.

Authors:  K Matsumoto; S Miyake; M Yano; Y Ueki; Y Yamaguchi; S Akazawa; Y Tominaga
Journal:  Diabetes Care       Date:  1997-10       Impact factor: 19.112

2.  Enhanced Predictive Capability of a 1-Hour Oral Glucose Tolerance Test: A Prospective Population-Based Cohort Study.

Authors:  Manan Pareek; Deepak L Bhatt; Mette L Nielsen; Ram Jagannathan; Karl-Fredrik Eriksson; Peter M Nilsson; Michael Bergman; Michael H Olsen
Journal:  Diabetes Care       Date:  2017-11-14       Impact factor: 19.112

3.  Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity.

Authors:  E Bonora; G Targher; M Alberiche; R C Bonadonna; F Saggiani; M B Zenere; T Monauni; M Muggeo
Journal:  Diabetes Care       Date:  2000-01       Impact factor: 19.112

4.  Continuous Glucose Monitoring Profiles in Healthy Nondiabetic Participants: A Multicenter Prospective Study.

Authors:  Viral N Shah; Stephanie N DuBose; Zoey Li; Roy W Beck; Anne L Peters; Ruth S Weinstock; Davida Kruger; Michael Tansey; David Sparling; Stephanie Woerner; Francesco Vendrame; Richard Bergenstal; William V Tamborlane; Sara E Watson; Jennifer Sherr
Journal:  J Clin Endocrinol Metab       Date:  2019-10-01       Impact factor: 5.958

5.  The Contribution of Unrecognized Factors to the Diabetes Epidemic.

Authors:  Michael Bergman; Ram Jagannathan; Giorgio Sesti
Journal:  Diabetes Metab Res Rev       Date:  2020-03-29       Impact factor: 4.876

6.  One-hour post-load plasma glucose levels associated with decreased insulin sensitivity and secretion and early makers of cardiometabolic risk.

Authors:  M L Marcovecchio; M Bagordo; E Marisi; T de Giorgis; V Chiavaroli; F Chiarelli; A Mohn
Journal:  J Endocrinol Invest       Date:  2017-03-01       Impact factor: 4.256

7.  Early Prediction of Developing Type 2 Diabetes by Plasma Acylcarnitines: A Population-Based Study.

Authors:  Liang Sun; Liming Liang; Xianfu Gao; Huiping Zhang; Pang Yao; Yao Hu; Yiwei Ma; Feijie Wang; Qianlu Jin; Huaixing Li; Rongxia Li; Yong Liu; Frank B Hu; Rong Zeng; Xu Lin; Jiarui Wu
Journal:  Diabetes Care       Date:  2016-07-07       Impact factor: 19.112

8.  Plasma metabolomic profiles reflective of glucose homeostasis in non-diabetic and type 2 diabetic obese African-American women.

Authors:  Oliver Fiehn; W Timothy Garvey; John W Newman; Kerry H Lok; Charles L Hoppel; Sean H Adams
Journal:  PLoS One       Date:  2010-12-10       Impact factor: 3.240

9.  Genome-Wide Association Study of Serum Fructosamine and Glycated Albumin in Adults Without Diagnosed Diabetes: Results From the Atherosclerosis Risk in Communities Study.

Authors:  Stephanie J Loomis; Man Li; Nisa M Maruthur; Abigail S Baldridge; Kari E North; Hao Mei; Alanna Morrison; April P Carson; James S Pankow; Eric Boerwinkle; Robert Scharpf; Laura J Rasmussen-Torvik; Josef Coresh; Priya Duggal; Anna Köttgen; Elizabeth Selvin
Journal:  Diabetes       Date:  2018-05-29       Impact factor: 9.337

10.  Combining information from common type 2 diabetes risk polymorphisms improves disease prediction.

Authors:  Michael N Weedon; Mark I McCarthy; Graham Hitman; Mark Walker; Christopher J Groves; Eleftheria Zeggini; N William Rayner; Beverley Shields; Katharine R Owen; Andrew T Hattersley; Timothy M Frayling
Journal:  PLoS Med       Date:  2006-10       Impact factor: 11.069

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  29 in total

1.  Comprehensive profiling and kinetic studies of glycated lysine residues in human serum albumin.

Authors:  Aleks Shin; Yahor Vazmitsel; Shawn Connolly; Kuanysh Kabytaev
Journal:  Anal Bioanal Chem       Date:  2022-05-11       Impact factor: 4.142

Review 2.  Screening for Diabetes and Prediabetes.

Authors:  Daisy Duan; Andre P Kengne; Justin B Echouffo-Tcheugui
Journal:  Endocrinol Metab Clin North Am       Date:  2021-07-12       Impact factor: 4.748

Review 3.  Progression from prediabetes to type 2 diabetes mellitus induced by overnutrition.

Authors:  Yuli Zhang; Tuming Shen; Songtao Wang
Journal:  Hormones (Athens)       Date:  2022-10-05       Impact factor: 3.419

4.  Differential contribution of alpha and beta cell dysfunction to impaired fasting glucose and impaired glucose tolerance.

Authors:  Jacob D Kohlenberg; Marcello C Laurenti; Aoife M Egan; Daniel Schembri Wismayer; Kent R Bailey; Claudio Cobelli; Chiara Dalla Man; Adrian Vella
Journal:  Diabetologia       Date:  2022-09-16       Impact factor: 10.460

5.  Oral glucose tolerance testing at 1 h and 2 h: relationship with glucose and cardiometabolic parameters and agreement for pre-diabetes diagnosis in patients with morbid obesity.

Authors:  Vanessa Guerreiro; Isabel Maia; João Sérgio Neves; Daniela Salazar; Maria João Ferreira; Fernando Mendonça; Maria Manuel Silva; Marta Borges-Canha; Sara Viana; Cláudia Costa; Jorge Pedro; Ana Varela; Eva Lau; Paula Freitas; Davide Carvalho
Journal:  Diabetol Metab Syndr       Date:  2022-07-06       Impact factor: 5.395

6.  The bad rainbow of COVID-19 time: effects on glucose metabolism in children and adolescents with obesity and overweight.

Authors:  Cosimo Giannini; Nella Polidori; Francesco Chiarelli; Angelika Mohn
Journal:  Int J Obes (Lond)       Date:  2022-07-01       Impact factor: 5.551

Review 7.  Lifestyle Interventions for Diabetes Prevention in South Asians: Current Evidence and Opportunities.

Authors:  Mary Beth Weber; Unjali P Gujral; Ram Jagannathan; Megha Shah
Journal:  Curr Diab Rep       Date:  2021-06-07       Impact factor: 4.810

8.  Prevalence of prediabetes in children and adolescents by class of obesity.

Authors:  Stefania Pedicelli; Danilo Fintini; Lucilla Ravà; Elena Inzaghi; Annalisa Deodati; Maria Rita Spreghini; Carla Bizzarri; Michela Mariani; Stefano Cianfarani; Marco Cappa; Melania Manco
Journal:  Pediatr Obes       Date:  2022-02-10       Impact factor: 3.910

Review 9.  Hyperglycemia at 1h-OGTT in Pregnancy: A Reliable Predictor of Metabolic Outcomes?

Authors:  Elena Succurro; Federica Fraticelli; Marica Franzago; Teresa Vanessa Fiorentino; Francesco Andreozzi; Ester Vitacolonna; Giorgio Sesti
Journal:  Front Endocrinol (Lausanne)       Date:  2021-05-24       Impact factor: 5.555

10.  Adipose Tissue Epigenetic Profile in Obesity-Related Dysglycemia - A Systematic Review.

Authors:  Sara Andrade; Tiago Morais; Ionel Sandovici; Alexandre L Seabra; Miguel Constância; Mariana P Monteiro
Journal:  Front Endocrinol (Lausanne)       Date:  2021-06-29       Impact factor: 5.555

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