TY - JOUR
T1 - Review of methods for detecting glycemic disorders
AU - Bergman, Michael
AU - Abdul-Ghani, Muhammad
AU - DeFronzo, Ralph A.
AU - Manco, Melania
AU - Sesti, Giorgio
AU - Fiorentino, Teresa Vanessa
AU - Ceriello, Antonio
AU - Rhee, Mary
AU - Phillips, Lawrence S.
AU - Chung, Stephanie
AU - Cravalho, Celeste
AU - Jagannathan, Ram
AU - Monnier, Louis
AU - Colette, Claude
AU - Owens, David
AU - Bianchi, Cristina
AU - del Prato, Stefano
AU - Monteiro, Mariana P.
AU - Neves, João Sérgio
AU - Medina, Jose Luiz
AU - Macedo, Maria Paula
AU - Ribeiro, Rogério Tavares
AU - Filipe Raposo, João
AU - Dorcely, Brenda
AU - Ibrahim, Nouran
AU - Buysschaert, Martin
N1 - Funding Information:
M.A.G. is a recipient of NIH R01 2R01DK097554-06. R.D. NIH RO1 DK24092, and NIH - R01 DK107680-01A1. M.R. is supported in part by VA awards I01 CX001737 and IK2 RX002928, NIH awards U01 DK098246, P30 DK111024, and R03 AI133172, and Georgia CTSA Pilot grant. M.R. is also supported in part by the Veterans Health Administration (VA). This work is not intended to reflect the official opinion of the VA or the U.S. government. L.P. is supported in part by VA awards I01-CX001025, and I01CX001737, NIH awards R21DK099716, U01 DK091958, U01 DK098246, P30DK111024, and R03AI133172, and a Cystic Fibrosis Foundation award PHILLI12A0. L.P. is supported in part by the Veterans Health Administration (VA). This work is not intended to reflect the official opinion of the VA or the U.S. government. S.T.C. is supported by the Intramural Division of National Institute of Diabetes, Digestive and Kidney Diseases at the National Institutes of Health, Bethesda MD. C.B. and S.D.P. were supported in part by funds from the Italian Ministry of University and Research (MIUR 2015PJ28EP_005. M.P.M. (Mariana P. Monteiro) is funded by public project grants from the Foundation for Science and Technology (FCT) Portugal to UMIB (UID/ Multi/00215/2019). P.M. has received an award from iNOVA4Health – UID/Multi/04462/2013, Marie Skłodowska-Curie Actions H2020 Grant Agreements N° 722619 and N° 734719 from the European Commission, and a grant from Sociedade Portuguesa de Diabetologia. R.T.R. is supported by grant SFRH-BPD-110426-2015 from FCT - Portuguese Science and Technology Foundation. MPM is supported by iNOVA4Health – UID/Multi/04462/2013
Funding Information:
M.A.G. is a recipient of NIH R01 2R01DK097554-06. R.D. NIH RO1 DK24092, and NIH - R01 DK107680-01A1. M.R. is supported in part by VA awards I01 CX001737 and IK2 RX002928, NIH awards U01 DK098246, P30 DK111024, and R03 AI133172, and Georgia CTSA Pilot grant. M.R. is also supported in part by the Veterans Health Administration (VA). This work is not intended to reflect the official opinion of the VA or the U.S. government. L.P. is supported in part by VA awards I01-CX001025, and I01CX001737, NIH awards R21DK099716, U01 DK091958, U01 DK098246, P30DK111024, and R03AI133172, and a Cystic Fibrosis Foundation award PHILLI12A0. L.P. is supported in part by the Veterans Health Administration (VA). This work is not intended to reflect the official opinion of the VA or the U.S. government. S.T.C. is supported by the Intramural Division of National Institute of Diabetes, Digestive and Kidney Diseases at the National Institutes of Health, Bethesda MD. C.B. and S.D.P. were supported in part by funds from the Italian Ministry of University and Research (MIUR 2015PJ28EP_005. M.P.M. (Mariana P. Monteiro) is funded by public project grants from the Foundation for Science and Technology ( FCT ) Portugal to UMIB (UID/ Multi/00215/2019). P.M. has received an award from iNOVA4Health – UID/Multi/04462/2013, Marie Skłodowska-Curie Actions H2020 Grant Agreements N° 722619 and N° 734719 from the European Commission, and a grant from Sociedade Portuguesa de Diabetologia. R.T.R. is supported by grant SFRH-BPD-110426-2015 from FCT - Portuguese Science and Technology Foundation. MPM is supported by iNOVA4Health – UID/Multi/04462/2013
Funding Information:
R.A.D. receives grant support from Astra Zeneca, Merck and Janssen and is a member of the advisory boards of Astra Zeneca, Janssen Pharmaceuticals, Intarcia, Boehringer Ingelheim, and Novo Nordisk; and is a member of the speakers’ bureaus of Novo Nordisk and Astra Zeneca. G.S. has received speaking fees from Novo Nordisk, Merck Sharp & Dohme, Sanofi, Boehringer Ingelheim, Eli Lilly, Astra Zeneca, L-Nutra, Theras, Sanofi, Mundipharma, Omikron, and Novartis, and consultancy fees from Servier, Novo Nordisk, Boehringer Ingelheim, Eli Lilly, Astra Zeneca, Merck Sharp & Dohme, Sanofi, Amgen and GlaxoSmithKline. A.C. has served on Scientific Advisory Boards for Abbott, Astra Zeneca, Boehringer Ingelheim, DOC Generici, Eli Lilly, Janssen, Mundipharma, Novo Nordisk, and OM Pharma. He has been a speaker for Astra Zeneca, Berlin Chemie, Boehringer Ingelheim, Eli Lilly, Mundipharma, Novo Nordisk, Roche Diagnostics and has or had research support from Astra Zeneca, Eli Lilly, Mitsubishi, and Novartis. M.R. has or had research support from Janssen Pharmaceuticals and Boehringer Ingelheim. L.P. has served on Scientific Advisory Boards for Janssen, and has or had research support from Abbvie, 899ck, Amylin, Eli Lilly, Novo Nordisk, Sanofi, PhaseBio, Roche, Abbvie, Vascular Pharmaceuticals, Janssen, Glaxo SmithKline, Pfizer, Kowa, and the Cystic Fibrosis Foundation. L.P. is also a cofounder, Officer and Board member and stockholder of a company, DIASYST, Inc., which is developing software aimed to help improve diabetes management. In the past, he was a speaker for Novartis and Merck, but not within the last five years. J.F.R. has received speaking fees from Eli Lilly and Abbott and consultancy fees from Sanofi, and Novo Nordisk.
Publisher Copyright:
© 2020
PY - 2020/7
Y1 - 2020/7
N2 - 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.
AB - 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.
KW - Biomarkers
KW - Cardiovascular disease
KW - Continuous glucose monitoring
KW - Glycemic variability
KW - HbA1c
KW - Metabolomics
KW - Oral glucose tolerance test
KW - Prediabetes
KW - Type 2 diabetes
UR - http://www.scopus.com/inward/record.url?scp=85086447364&partnerID=8YFLogxK
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U2 - 10.1016/j.diabres.2020.108233
DO - 10.1016/j.diabres.2020.108233
M3 - Review article
C2 - 32497744
AN - SCOPUS:85086447364
SN - 0168-8227
VL - 165
JO - Diabetes Research and Clinical Practice
JF - Diabetes Research and Clinical Practice
M1 - 108233
ER -