Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine

Protein glycation provides a biomarker in widespread clinical use, glycated hemoglobin HbA1c (A1C). It is a biomarker for diagnosis of diabetes and prediabetes and of medium-term glycemic control in patients with established diabetes. A1C is an early-stage glycation adduct of hemoglobin with glucose...

Full description

Saved in:
Bibliographic Details
Main Author: Naila, Rabbani (author)
Other Authors: Thornalley, Paul J. (author)
Format: article
Published: 2021
Subjects:
Online Access:http://dx.doi.org/10.1016/j.redox.2021.101920
https://www.sciencedirect.com/science/article/pii/S2213231721000689
http://hdl.handle.net/10576/44665
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1857415086715437056
author Naila, Rabbani
author2 Thornalley, Paul J.
author2_role author
author_facet Naila, Rabbani
Thornalley, Paul J.
author_role author
dc.creator.none.fl_str_mv Naila, Rabbani
Thornalley, Paul J.
dc.date.none.fl_str_mv 2021-06-30
2023-06-22T04:35:04Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://dx.doi.org/10.1016/j.redox.2021.101920
22132317
https://www.sciencedirect.com/science/article/pii/S2213231721000689
http://hdl.handle.net/10576/44665
42
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Elsevier
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Glycated hemoglobin
Fructosamine
Methylglyoxal
Diabetes
Chronic kidney disease
Machine learning
dc.title.none.fl_str_mv Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine
dc.type.none.fl_str_mv Article
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Protein glycation provides a biomarker in widespread clinical use, glycated hemoglobin HbA1c (A1C). It is a biomarker for diagnosis of diabetes and prediabetes and of medium-term glycemic control in patients with established diabetes. A1C is an early-stage glycation adduct of hemoglobin with glucose; a fructosamine derivative. Glucose is an amino group-directed glycating agent, modifying N-terminal and lysine sidechain amino groups. A similar fructosamine derivative of serum albumin, glycated albumin (GA), finds use as a biomarker of glycemic control, particularly where there is interference in use of A1C. Later stage adducts, advanced glycation endproducts (AGEs), are formed by the degradation of fructosamines and by the reaction of reactive dicarbonyl metabolites, such as methylglyoxal. Dicarbonyls are arginine-directed glycating agents forming mainly hydroimidazolone AGEs. Glucosepane and pentosidine, an intense fluorophore, are AGE covalent crosslinks. Cellular proteolysis of glycated proteins forms glycated amino acids, which are released into plasma and excreted in urine. Development of diagnostic algorithms by artificial intelligence machine learning is enhancing the applications of glycation biomarkers. Investigational glycation biomarkers are in development for: (i) healthy aging; (ii) risk prediction of vascular complications of diabetes; (iii) diagnosis of autism; and (iv) diagnosis and classification of early-stage arthritis. Protein glycation biomarkers are influenced by heritability, aging, decline in metabolic, vascular, renal and skeletal health, and other factors. They are applicable to populations of differing ethnicities, bridging the gap between genotype and phenotype. They are thereby likely to find continued and expanding clinical use, including in the current era of developing precision medicine, reporting on multiple pathogenic processes and supporting a precision medicine approach.
eu_rights_str_mv openAccess
format article
id qu_ca3470588933c8d58eea6c819bc62af0
identifier_str_mv 22132317
42
language_invalid_str_mv en
network_acronym_str qu
network_name_str Qatar University repository
oai_identifier_str oai:qspace.qu.edu.qa:10576/44665
publishDate 2021
publisher.none.fl_str_mv Elsevier
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
spelling Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicineNaila, RabbaniThornalley, Paul J.Glycated hemoglobinFructosamineMethylglyoxalDiabetesChronic kidney diseaseMachine learningProtein glycation provides a biomarker in widespread clinical use, glycated hemoglobin HbA1c (A1C). It is a biomarker for diagnosis of diabetes and prediabetes and of medium-term glycemic control in patients with established diabetes. A1C is an early-stage glycation adduct of hemoglobin with glucose; a fructosamine derivative. Glucose is an amino group-directed glycating agent, modifying N-terminal and lysine sidechain amino groups. A similar fructosamine derivative of serum albumin, glycated albumin (GA), finds use as a biomarker of glycemic control, particularly where there is interference in use of A1C. Later stage adducts, advanced glycation endproducts (AGEs), are formed by the degradation of fructosamines and by the reaction of reactive dicarbonyl metabolites, such as methylglyoxal. Dicarbonyls are arginine-directed glycating agents forming mainly hydroimidazolone AGEs. Glucosepane and pentosidine, an intense fluorophore, are AGE covalent crosslinks. Cellular proteolysis of glycated proteins forms glycated amino acids, which are released into plasma and excreted in urine. Development of diagnostic algorithms by artificial intelligence machine learning is enhancing the applications of glycation biomarkers. Investigational glycation biomarkers are in development for: (i) healthy aging; (ii) risk prediction of vascular complications of diabetes; (iii) diagnosis of autism; and (iv) diagnosis and classification of early-stage arthritis. Protein glycation biomarkers are influenced by heritability, aging, decline in metabolic, vascular, renal and skeletal health, and other factors. They are applicable to populations of differing ethnicities, bridging the gap between genotype and phenotype. They are thereby likely to find continued and expanding clinical use, including in the current era of developing precision medicine, reporting on multiple pathogenic processes and supporting a precision medicine approach.Elsevier2023-06-22T04:35:04Z2021-06-30Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://dx.doi.org/10.1016/j.redox.2021.10192022132317https://www.sciencedirect.com/science/article/pii/S2213231721000689http://hdl.handle.net/10576/4466542enhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:qspace.qu.edu.qa:10576/446652024-07-23T13:53:42Z
spellingShingle Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine
Naila, Rabbani
Glycated hemoglobin
Fructosamine
Methylglyoxal
Diabetes
Chronic kidney disease
Machine learning
status_str publishedVersion
title Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine
title_full Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine
title_fullStr Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine
title_full_unstemmed Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine
title_short Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine
title_sort Protein glycation – biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine
topic Glycated hemoglobin
Fructosamine
Methylglyoxal
Diabetes
Chronic kidney disease
Machine learning
url http://dx.doi.org/10.1016/j.redox.2021.101920
https://www.sciencedirect.com/science/article/pii/S2213231721000689
http://hdl.handle.net/10576/44665