Login Register Cart 0
Generic placeholder image

Current Indian Science

Editor-in-Chief

ISSN (Print): 2210-299X
ISSN (Online): 2210-3007

Back
Journal Home About Journal Editorial Board Current Issue Volumes/Issues
Subscribe
Review Article

Mechanistic Insight of Innovative Biomarkers for Screening of Type II Diabetes Mellitus

Author(s): Shubh Deep Yadav and Neelam Singh*

Volume 2, 2024

Published on: 20 December, 2023

Article ID: e2210299X257270 Pages: 11

DOI: 10.2174/012210299X257270231127062630

open_access

Open Access Journals Promotions 2
Abstract

Diabetes Mellitus (DM) is a compounded, persistent illness symbolized by an increased range of glucose levels in the blood caused by cellular resistance to insulin action, insufficient insulin production by pancreatic -cells, or both. Type 1 Diabetes Mellitus (T1DM), the extremely widespread form of DM, is recorded for almost 85-90% of worldwide cases. T2DM is mostly common in middle-aged and older people, and its causes are multifaceted. The use of efficient and profitable solutions for DM screening is critical to ensure pre-identification and minimising patients' risk of acquiring the life-compromising illness. Identification of innovative biomarkers with test methods of DM is therefore critical in order to establish vigorous, non-invasive, pain-free, highly sensitive, and precise procedures for screening. The purpose of this review article is to mention and review all the necessary biomarkers that play a vital role in disease diagnosis and to highlight the present-day findings of the latest clinically validated and traditional biomarkers and procedures for determining them, which provide cost-efficient options for T2DM screening with early detection. It is concluded that various biomarkers, both conventional and innovative, go hand in hand to diagnose the DM of any type.

Keywords: Insulin, Screening technique, Diagnosis, Conventional biomarker, Hb1Ac, Diabetes mellitus.

[1]
Inzucchi, S.E.; Sherwin, R.S. Type 2 diabetes mellitus. Cecil Medicine, 24th ed; Saunders Elsevier: Philadelphia, Pa, 2011.
[2]
Kao, K.T.; Sabin, M.A. Type 2 diabetes mellitus in children and adolescents. Aust. Fam. Physician, 2016, 45(6), 401-406.
[PMID: 27622231]
[3]
Olokoba, A.B.; Obateru, O.A.; Olokoba, L.B. Type 2 diabetes mellitus: a review of current trends. Oman Med. J., 2012, 27(4), 269-273.
[http://dx.doi.org/10.5001/omj.2012.68] [PMID: 23071876]
[4]
American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care, 2013, 36(S1), S67-S74.
[http://dx.doi.org/10.2337/dc13-S067] [PMID: 23264425]
[5]
Mayfield, J. Diagnosis and classification of diabetes mellitus: New criteria. Am. Fam. Physician, 1998, 58(6), 1355-1362, 1369-1370.
[PMID: 9803200]
[6]
Chaturvedi, N. The burden of diabetes and its complications: Trends and implications for intervention. Diabetes Res. Clin. Pract., 2007, 76(3), S3-S12.
[http://dx.doi.org/10.1016/j.diabres.2007.01.019] [PMID: 17343954]
[7]
Vigersky, R.A. An overview of management issues in adult patients with type 2 diabetes mellitus. J. Diabetes Sci. Technol., 2011, 5(2), 245-250.
[http://dx.doi.org/10.1177/193229681100500207] [PMID: 21527089]
[8]
Fong, D.S.; Aiello, L.; Gardner, T.W.; King, G.L.; Blankenship, G.; Cavallerano, J.D.; Ferris, F.L., III; Klein, R. Retinopathy in diabetes. Diabetes Care, 2004, 27(S1), s84-s87.
[http://dx.doi.org/10.2337/diacare.27.2007.S84] [PMID: 14693935]
[9]
Wu, Y.; Ding, Y.; Tanaka, Y.; Zhang, W. Risk factors contributing to type 2 diabetes and recent advances in the treatment and prevention. Int. J. Med. Sci., 2014, 11(11), 1185-1200.
[http://dx.doi.org/10.7150/ijms.10001] [PMID: 25249787]
[10]
Kerner, W.; Brückel, J. Definition, classification and diagnosis of diabetes mellitus. Exp. Clin. Endocrinol. Diabetes, 2014, 122(7), 384-386.
[http://dx.doi.org/10.1055/s-0034-1366278] [PMID: 25014088]
[11]
Sosale, A.; Prasanna Kumar, K.M.; Sadikot, S.M.; Nigam, A.; Bajaj, S.; Zargar, A.H.; Singh, S.K. Chronic complications in newly diagnosed patients with Type 2 diabetes mellitus in India. Indian J. Endocrinol. Metab., 2014, 18(3), 355-360.
[http://dx.doi.org/10.4103/2230-8210.131184] [PMID: 24944931]
[12]
Kumar, P.R.; Bhansali, A.; Ravikiran, M.; Bhansali, S.; Dutta, P.; Thakur, J.S.; Sachdeva, N.; Bhadada, S.K.; Walia, R. Utility of glycated hemoglobin in diagnosing type 2 diabetes mellitus: a community-based study. J. Clin. Endocrinol. Metab., 2010, 95(6), 2832-2835.
[http://dx.doi.org/10.1210/jc.2009-2433] [PMID: 20371663]
[13]
Cox, M.E.; Edelman, D. Tests for screening and diagnosis of type 2 diabetes. Clin. Diabetes, 2009, 27(4), 132-138.
[http://dx.doi.org/10.2337/diaclin.27.4.132]
[14]
Genuth, S.; Alberti, K.G.; Bennett, P.; Buse, J.; Defronzo, R.; Kahn, R.; Kitzmiller, J.; Knowler, W.C.; Lebovitz, H.; Lernmark, A.; Nathan, D.; Palmer, J.; Rizza, R.; Saudek, C.; Shaw, J.; Steffes, M.; Stern, M.; Tuomilehto, J.; Zimmet, P. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care, 2003, 26(11), 3160-3167.
[http://dx.doi.org/10.2337/diacare.26.11.3160] [PMID: 14578255]
[15]
Perry, R.C.; Shankar, R.R.; Fineberg, N.; McGill, J.; Baron, A.D. HbA1c measurement improves the detection of type 2 diabetes in high-risk individuals with nondiagnostic levels of fasting plasma glucose: The Early Diabetes Intervention Program (EDIP). Diabetes Care, 2001, 24(3), 465-471.
[http://dx.doi.org/10.2337/diacare.24.3.465] [PMID: 11289469]
[16]
Dedov, I.; Shestakova, M.; Benedetti, M.M.; Simon, D.; Pakhomov, I.; Galstyan, G. Prevalence of type 2 diabetes mellitus (T2DM) in the adult Russian population (NATION study). Diabetes Res. Clin. Pract., 2016, 115, 90-95.
[http://dx.doi.org/10.1016/j.diabres.2016.02.010] [PMID: 27107818]
[17]
Strimbu, K.; Tavel, J.A. What are biomarkers? Curr. Opin. HIV AIDS, 2010, 5(6), 463-466.
[http://dx.doi.org/10.1097/COH.0b013e32833ed177] [PMID: 20978388]
[18]
Mayeux, R. Biomarkers: Potential uses and limitations. NeuroRx, 2004, 1(2), 182-188.
[http://dx.doi.org/10.1602/neurorx.1.2.182] [PMID: 15717018]
[19]
Laakso, M. Biomarkers for type 2 diabetes. Mol. Metab., 2019, 27, S139-S146.
[http://dx.doi.org/10.1016/j.molmet.2019.06.016] [PMID: 31500825]
[20]
Ehtewish, H; Arredouani, A; El-Agnaf, O. Diagnostic, prognostic, and mechanistic biomarkers of diabetes mellitus-associated cognitive decline. Int J Mol Sci., 2022, 23(11), 6144.
[http://dx.doi.org/10.3390/ijms23116144]
[21]
Scirica, B.M. Use of biomarkers in predicting the onset, monitoring the progression, and risk stratification for patients with type 2 diabetes mellitus. Clin. Chem., 2017, 63(1), 186-195.
[http://dx.doi.org/10.1373/clinchem.2016.255539] [PMID: 28062618]
[22]
Luís, C.; Baylina, P.; Soares, R.; Fernandes, R. Metabolic dysfunction biomarkers as predictors of early diabetes. Biomolecules, 2021, 11(11), 1589.
[http://dx.doi.org/10.3390/biom11111589] [PMID: 34827587]
[23]
Pena, M.J.; Heinzel, A.; Heinze, G.; Alkhalaf, A.; Bakker, S.J.L.; Nguyen, T.Q.; Goldschmeding, R.; Bilo, H.J.G.; Perco, P.; Mayer, B.; de Zeeuw, D.; Lambers Heerspink, H.J. A panel of novel biomarkers representing different disease pathways improves prediction of renal function decline in type 2 diabetes. PLoS One, 2015, 10(5), e0120995.
[http://dx.doi.org/10.1371/journal.pone.0120995] [PMID: 25973922]
[24]
Padilla-Martinez, F.; Wojciechowska, G.; Szczerbinski, L.; Kretowski, A. Circulating nucleic acid-based biomarkers of type 2 diabetes. Int. J. Mol. Sci., 2021, 23(1), 295.
[http://dx.doi.org/10.3390/ijms23010295] [PMID: 35008723]
[25]
Jiménez-Lucena, R.; Rangel-Zúñiga, O.A.; Alcalá-Díaz, J.F.; López-Moreno, J.; Roncero-Ramos, I.; Molina-Abril, H.; Yubero-Serrano, E.M.; Caballero-Villarraso, J.; Delgado-Lista, J.; Castaño, J.P.; Ordovás, J.M.; Pérez-Martinez, P.; Camargo, A.; López-Miranda, J. Circulating miRNAs as predictive biomarkers of type 2 diabetes mellitus development in coronary heart disease patients from the CORDIOPREV study. Mol. Ther. Nucleic Acids, 2018, 12, 146-157.
[http://dx.doi.org/10.1016/j.omtn.2018.05.002] [PMID: 30195754]
[26]
Higuchi, C.; Nakatsuka, A.; Eguchi, J.; Teshigawara, S.; Kanzaki, M.; Katayama, A.; Yamaguchi, S.; Takahashi, N.; Murakami, K.; Ogawa, D.; Sasaki, S.; Makino, H.; Wada, J. Identification of Circulating miR-101, miR-375 and miR-802 as Biomarkers for Type 2 Diabetes. Metabolism, 2015, 64(4), 489-497.
[http://dx.doi.org/10.1016/j.metabol.2014.12.003] [PMID: 25726255]
[27]
Sánchez-Ceinos, J.; Rangel-Zuñiga, O.A.; Clemente-Postigo, M.; Podadera-Herreros, A.; Camargo, A.; Alcalá-Diaz, J.F.; Guzmán-Ruiz, R.; López-Miranda, J.; Malagón, M.M. miR-223-3p as a potential biomarker and player for adipose tissue dysfunction preceding type 2 diabetes onset. Mol. Ther. Nucleic Acids, 2021, 23, 1035-1052.
[http://dx.doi.org/10.1016/j.omtn.2021.01.014] [PMID: 33614249]
[28]
Vasu, S.; Kumano, K.; Darden, C.M.; Rahman, I.; Lawrence, M.C.; Naziruddin, B. MicroRNA signatures as future biomarkers for diagnosis of diabetes states. Cells, 2019, 8(12), 1533.
[http://dx.doi.org/10.3390/cells8121533] [PMID: 31795194]
[29]
Guay, C.; Regazzi, R. Circulating microRNAs as novel biomarkers for diabetes mellitus. Nat. Rev. Endocrinol., 2013, 9(9), 513-521.
[http://dx.doi.org/10.1038/nrendo.2013.86] [PMID: 23629540]
[30]
Chi, T.; Lin, J.; Wang, M.; Zhao, Y.; Liao, Z.; Wei, P. Non-coding RNA as biomarkers for Type 2 diabetes development and clinical management. Front. Endocrinol., 2021, 12, 630032.
[http://dx.doi.org/10.3389/fendo.2021.630032] [PMID: 34603195]
[31]
Ciobanu, D.M.; Bogdan, F.; Pătruț, C.I.; Roman, G. Glycated albumin is correlated with glycated hemoglobin in type 2 diabetes. Med. Pharm. Rep., 2019, 92(2), 134-138.
[http://dx.doi.org/10.15386/mpr-1247] [PMID: 31086840]
[32]
Yoshiuchi, K.; Matsuhisa, M.; Katakami, N.; Nakatani, Y.; Sakamoto, K.; Matsuoka, T.; Umayahara, Y.; Kosugi, K.; Kaneto, H.; Yamasaki, Y.; Hori, M. Glycated albumin is a better indicator for glucose excursion than glycated hemoglobin in type 1 and type 2 diabetes. Endocr. J., 2008, 55(3), 503-507.
[http://dx.doi.org/10.1507/endocrj.K07E-089] [PMID: 18445997]
[33]
Rescalli, A.; Varoni, E.M.; Cellesi, F.; Cerveri, P. Analytical challenges in diabetes management: Towards glycated albumin point-of-care detection. Biosensors, 2022, 12(9), 687.
[http://dx.doi.org/10.3390/bios12090687] [PMID: 36140073]
[34]
Toft, J.H.; Dalen, I.; Skadberg, Ø.; Gøransson, L.G.; Økland, I.; Bleskestad, I.H. Glycated albumin and continuous glucose monitoring metrics across pregnancy in women with pre‐gestational diabetes. Endocrinol. Diabetes Metab., 2022, 5(6), e376.
[http://dx.doi.org/10.1002/edm2.376] [PMID: 36121204]
[35]
Sierawska, O.; Niedźwiedzka-Rystwej, P. Adipokines as potential biomarkers for type 2 diabetes mellitus in cats. Front. Immunol., 2022, 13, 950049.
[http://dx.doi.org/10.3389/fimmu.2022.950049] [PMID: 36248900]
[36]
Bowker, N.; Shah, R.L.; Sharp, S.J.; Luan, J.; Stewart, I.D.; Wheeler, E.; Ferreira, M.A.R.; Baras, A.; Wareham, N.J.; Langenberg, C.; Lotta, L.A. Meta-analysis investigating the role of interleukin-6 mediated inflammation in type 2 diabetes. EBioMedicine, 2020, 61, 103062.
[http://dx.doi.org/10.1016/j.ebiom.2020.103062] [PMID: 33096487]
[37]
Malmström, H.; Walldius, G.; Grill, V.; Jungner, I.; Gudbjörnsdottir, S.; Hammar, N. Fructosamine is a useful indicator of hyperglycaemia and glucose control in clinical and epidemiological studies--cross-sectional and longitudinal experience from the AMORIS cohort. PLoS One, 2014, 9(10), e111463.
[http://dx.doi.org/10.1371/journal.pone.0111463] [PMID: 25353659]
[38]
Bergman, M.; Abdul-Ghani, M.; DeFronzo, R.A.; Manco, M.; Sesti, G.; Fiorentino, T.V.; Ceriello, A.; Rhee, M.; Phillips, L.S.; Chung, S.; Cravalho, C.; Jagannathan, R.; Monnier, L.; Colette, C.; Owens, D.; Bianchi, C.; del Prato, S.; Monteiro, M.P.; Neves, J.S.; Medina, J.L.; Macedo, M.P.; Ribeiro, R.T.; Filipe Raposo, J.; Dorcely, B.; Ibrahim, N.; Buysschaert, M. Review of methods for detecting glycemic disorders. Diabetes Res. Clin. Pract., 2020, 165, 108233.
[http://dx.doi.org/10.1016/j.diabres.2020.108233] [PMID: 32497744]
[39]
Amita, D.; Dhiraj, K.; Vivek, S.; Satya, P.M. The novel biomarkers in diabetes. J Assoc Physicians India, 2019, 67(7), 65-69.
[40]
Pramodkumar, T.A.; Jayashri, R.; Gokulakrishnan, K.; Velmurugan, K.; Pradeepa, R.; Venkatesan, U.; Saravanan, P.; Uma, R.; Anjana, R.M.; Mohan, V. 1,5 Anhydroglucitol in gestational diabetes mellitus. J. Diabetes Complications, 2019, 33(3), 231-235.
[http://dx.doi.org/10.1016/j.jdiacomp.2018.11.010] [PMID: 30594413]
[41]
Ortiz-Martínez, M.; González-González, M.; Martagón, A.J.; Hlavinka, V.; Willson, R.C.; Rito-Palomares, M. Recent developments in biomarkers for diagnosis and screening of type 2 diabetes mellitus. Curr. Diab. Rep., 2022, 22(3), 95-115.
[http://dx.doi.org/10.1007/s11892-022-01453-4] [PMID: 35267140]
[42]
Chon, S.; Lee, Y.J.; Fraterrigo, G.; Pozzilli, P.; Choi, M.C.; Kwon, M.K.; Chin, S.O.; Rhee, S.Y.; Oh, S.; Kim, Y.S.; Woo, J.T. Evaluation of glycemic variability in well-controlled type 2 diabetes mellitus. Diabetes Technol. Ther., 2013, 15(6), 455-460.
[http://dx.doi.org/10.1089/dia.2012.0315] [PMID: 23617251]
[43]
Chan, C.L.; Pyle, L.; Kelsey, M.; Newnes, L.; Zeitler, P.S.; Nadeau, K.J. Screening for type 2 diabetes and prediabetes in obese youth: evaluating alternate markers of glycemia - 1,5-anhydroglucitol, fructosamine, and glycated albumin. Pediatr. Diabetes, 2016, 17(3), 206-211.
[http://dx.doi.org/10.1111/pedi.12258] [PMID: 25652226]
[44]
Ueda, S.; Nagai, K.; Yokota, N.; Hirose, D.; Mori, H.; Noma, Y.; Doi, T.; Minakuchi, J. Influence of albumin leakage on glycated albumin in patients with type 2 diabetes undergoing hemodialysis. J. Artif. Organs, 2019, 22(3), 264-267.
[http://dx.doi.org/10.1007/s10047-019-01097-4] [PMID: 30805746]
[45]
Liu, L.; Wan, X.; Liu, J.; Huang, Z.; Cao, X.; Li, Y. Increased 1,5-anhydroglucitol predicts glycemic remission in patients with newly diagnosed type 2 diabetes treated with short-term intensive insulin therapy. Diabetes Technol. Ther., 2012, 14(9), 756-761.
[http://dx.doi.org/10.1089/dia.2012.0055] [PMID: 22731793]
[46]
Dorcely, B.; Katz, K.; Jagannathan, R.; Chiang, S.S.; Oluwadare, B.; Goldberg, I.J.; Bergman, M. Novel biomarkers for prediabetes, diabetes, and associated complications. Diabetes Metab. Syndr. Obes., 2017, 10, 345-361.
[http://dx.doi.org/10.2147/DMSO.S100074] [PMID: 28860833]
[47]
Aghaei Zarch, S.M.; Dehghan Tezerjani, M.; Talebi, M.; Vahidi Mehrjardi, M.Y. Molecular biomarkers in diabetes mellitus (DM). Med. J. Islam. Repub. Iran, 2020, 34, 28.
[http://dx.doi.org/10.34171/mjiri.34.28] [PMID: 32617267]
[48]
Hilvo, M.; Vasile, V.C.; Donato, L.J.; Hurme, R.; Laaksonen, R. Ceramides and ceramide scores: Clinical applications for cardiometabolic risk stratification. Front. Endocrinol., 2020, 11, 570628.
[http://dx.doi.org/10.3389/fendo.2020.570628] [PMID: 33133018]
[49]
Gall, W.E.; Beebe, K.; Lawton, K.A.; Adam, K.P.; Mitchell, M.W.; Nakhle, P.J.; Ryals, J.A.; Milburn, M.V.; Nannipieri, M.; Camastra, S.; Natali, A.; Ferrannini, E. alpha-hydroxybutyrate is an early biomarker of insulin resistance and glucose intolerance in a nondiabetic population. PLoS One, 2010, 5(5), e10883.
[http://dx.doi.org/10.1371/journal.pone.0010883] [PMID: 20526369]
[50]
Landaas, S. The formation of 2-hydroxybutyric acid in experimental animals. Clin. Chim. Acta, 1975, 58(1), 23-32.
[http://dx.doi.org/10.1016/0009-8981(75)90481-7]
[51]
Gar, C.; Rottenkolber, M.; Prehn, C.; Adamski, J.; Seissler, J.; Lechner, A. Serum and plasma amino acids as markers of prediabetes, insulin resistance, and incident diabetes. Crit. Rev. Clin. Lab. Sci., 2018, 55(1), 21-32.
[http://dx.doi.org/10.1080/10408363.2017.1414143] [PMID: 29239245]
[52]
Saltevo, J.; Kautiainen, H.; Vanhala, M. Gender differences in adiponectin and low-grade inflammation among individuals with normal glucose tolerance, prediabetes, and type 2 diabetes. Gend. Med., 2009, 6(3), 463-470.
[http://dx.doi.org/10.1016/j.genm.2009.09.006] [PMID: 19850242]
[53]
Zhang, X.; Zhang, C.; Chen, L.; Han, X.; Ji, L. Human serum acylcarnitine profiles in different glucose tolerance states. Diabetes Res. Clin. Pract., 2014, 104(3), 376-382.
[http://dx.doi.org/10.1016/j.diabres.2014.04.013] [PMID: 24837145]
[54]
Sun, L.; Liang, L.; Gao, X.; Zhang, H.; Yao, P.; Hu, Y.; Ma, Y.; Wang, F.; Jin, Q.; Li, H.; Li, R.; Liu, Y.; Hu, F.B.; Zeng, R.; Lin, X.; Wu, J. Early prediction of developing type 2 diabetes by plasma acylcarnitines: A population-based study. Diabetes Care, 2016, 39(9), 1563-1570.
[http://dx.doi.org/10.2337/dc16-0232] [PMID: 27388475]
[55]
Ruiz-Canela, M.; Guasch-Ferré, M.; Toledo, E.; Clish, C.B.; Razquin, C.; Liang, L.; Wang, D.D.; Corella, D.; Estruch, R.; Hernáez, Á.; Yu, E.; Gómez-Gracia, E.; Zheng, Y.; Arós, F.; Romaguera, D.; Dennis, C.; Ros, E.; Lapetra, J.; Serra-Majem, L.; Papandreou, C.; Portoles, O.; Fitó, M.; Salas-Salvadó, J.; Hu, F.B.; Martínez-González, M.A. Plasma branched chain/aromatic amino acids, enriched Mediterranean diet and risk of type 2 diabetes: case-cohort study within the PREDIMED Trial. Diabetologia, 2018, 61(7), 1560-1571.
[http://dx.doi.org/10.1007/s00125-018-4611-5] [PMID: 29663011]
[56]
Chen, X.; Yang, W. Branched‐chain amino acids and the association with type 2 diabetes. J. Diabetes Investig., 2015, 6(4), 369-370.
[http://dx.doi.org/10.1111/jdi.12345] [PMID: 26221513]
[57]
Sabanayagam, C.; Shankar, A.; Lim, S.C.; Lee, J.; Tai, E.S.; Wong, T.Y. Serum C-reactive protein level and prediabetes in two Asian populations. Diabetologia, 2011, 54(4), 767-775.
[http://dx.doi.org/10.1007/s00125-011-2052-5] [PMID: 21267537]
[58]
Grossmann, V.; Schmitt, V.H.; Zeller, T.; Panova-Noeva, M.; Schulz, A.; Laubert-Reh, D.; Juenger, C.; Schnabel, R.B.; Abt, T.G.J.; Laskowski, R.; Wiltink, J.; Schulz, E.; Blankenberg, S.; Lackner, K.J.; Münzel, T.; Wild, P.S. Profile of the immune and inflammatory response in individuals with prediabetes and type 2 diabetes. Diabetes Care, 2015, 38(7), 1356-1364.
[http://dx.doi.org/10.2337/dc14-3008] [PMID: 25877811]
[59]
Kunutsor, S.K.; Apekey, T.A.; Walley, J.; Kain, K. Ferritin levels and risk of type 2 diabetes mellitus: An updated systematic review and meta-analysis of prospective evidence. Diabetes Metab. Res. Rev., 2013, 29(4), 308-318.
[http://dx.doi.org/10.1002/dmrr.2394] [PMID: 23381919]
[60]
Forouhi, N.G.; Harding, A.H.; Allison, M.; Sandhu, M.S.; Welch, A.; Luben, R.; Bingham, S.; Khaw, K.T.; Wareham, N.J. Elevated serum ferritin levels predict new-onset type 2 diabetes: Results from the EPIC-Norfolk prospective study. Diabetologia, 2007, 50(5), 949-956.
[http://dx.doi.org/10.1007/s00125-007-0604-5] [PMID: 17333112]
[61]
Lee, J.E. Alternative biomarkers for assessing glycemic control in diabetes: Fructosamine, glycated albumin, and 1,5-anhydroglucitol. Ann. Pediatr. Endocrinol. Metab., 2015, 20(2), 74-78.
[http://dx.doi.org/10.6065/apem.2015.20.2.74] [PMID: 26191510]
[62]
Danese, E.; Montagnana, M.; Nouvenne, A.; Lippi, G. Advantages and pitfalls of fructosamine and glycated albumin in the diagnosis and treatment of diabetes. J. Diabetes Sci. Technol., 2015, 9(2), 169-176.
[http://dx.doi.org/10.1177/1932296814567227] [PMID: 25591856]
[63]
Long, J.; Yang, Z.; Wang, L.; Han, Y.; Peng, C.; Yan, C.; Yan, D. Metabolite biomarkers of type 2 diabetes mellitus and pre-diabetes: A systematic review and meta-analysis. BMC Endocr. Disord., 2020, 20(1), 174.
[http://dx.doi.org/10.1186/s12902-020-00653-x] [PMID: 33228610]
[64]
Wang-Sattler, R.; Yu, Z.; Herder, C.; Messias, A.C.; Floegel, A.; He, Y.; Heim, K.; Campillos, M.; Holzapfel, C.; Thorand, B.; Grallert, H.; Xu, T.; Bader, E.; Huth, C.; Mittelstrass, K.; Döring, A.; Meisinger, C.; Gieger, C.; Prehn, C.; Roemisch-Margl, W.; Carstensen, M.; Xie, L.; Yamanaka-Okumura, H.; Xing, G.; Ceglarek, U.; Thiery, J.; Giani, G.; Lickert, H.; Lin, X.; Li, Y.; Boeing, H.; Joost, H.G.; de Angelis, M.H.; Rathmann, W.; Suhre, K.; Prokisch, H.; Peters, A.; Meitinger, T.; Roden, M.; Wichmann, H.E.; Pischon, T.; Adamski, J.; Illig, T. Novel biomarkers for pre‐diabetes identified by metabolomics. Mol. Syst. Biol., 2012, 8(1), 615.
[http://dx.doi.org/10.1038/msb.2012.43] [PMID: 23010998]
[65]
Pérez-Matos, M.C.; Morales-Álvarez, M.C.; Toloza, F.J.K.; Ricardo-Silgado, M.L.; Mantilla-Rivas, J.O.; Pinzón-Cortes, J.A.; Perez-Mayorga, M.; Jiménez, E.; Guevara, E.; Mendivil, C.O. The phospholipid linoleoylglycerophosphocholine as a biomarker of directly measured insulin resistance. Diabetes Metab. J., 2017, 41(6), 466-473.
[http://dx.doi.org/10.4093/dmj.2017.41.6.466] [PMID: 29199411]
[66]
Ahn, N.; Baumeister, S.E.; Amann, U.; Rathmann, W.; Peters, A.; Huth, C.; Thorand, B.; Meisinger, C. Visceral adiposity index (VAI), lipid accumulation product (LAP), and product of triglycerides and glucose (TyG) to discriminate prediabetes and diabetes. Sci. Rep., 2019, 9(1), 9693.
[http://dx.doi.org/10.1038/s41598-019-46187-8] [PMID: 31273286]
[67]
Hamasaki, H.; Noda, M.; Moriyama, S.; Yoshikawa, R.; Katsuyama, H.; Sako, A.; Mishima, S.; Kakei, M.; Ezaki, O.; Yanai, H. Daily physical activity assessed by a triaxial accelerometer is beneficially associated with waist circumference, serum triglycerides, and insulin resistance in japanese patients with prediabetes or untreated early type 2 diabetes. J. Diabetes Res., 2015, 2015, 1-6.
[http://dx.doi.org/10.1155/2015/526201] [PMID: 26064983]
[68]
Barr, R.G.; Nathan, D.M.; Meigs, J.B.; Singer, D.E. Tests of glycemia for the diagnosis of type 2 diabetes mellitus. Ann. Intern. Med., 2002, 137(4), 263-272.
[http://dx.doi.org/10.7326/0003-4819-137-4-200208200-00011] [PMID: 12186517]
[69]
Jiang, Y.; Owei, I.; Wan, J.; Ebenibo, S.; Dagogo-Jack, S. Adiponectin levels predict prediabetes risk: The pathobiology of prediabetes in a biracial cohort (POP-ABC) study. BMJ Open Diabetes Res. Care, 2016, 4(1), e000194.
[http://dx.doi.org/10.1136/bmjdrc-2016-000194] [PMID: 27026810]
[70]
Pescador, N.; Pérez-Barba, M.; Ibarra, J.M.; Corbatón, A.; Martínez-Larrad, M.T.; Serrano-Ríos, M. Serum circulating microRNA profiling for identification of potential type 2 diabetes and obesity biomarkers. PLoS One, 2013, 8(10), e77251.
[http://dx.doi.org/10.1371/journal.pone.0077251] [PMID: 24204780]
[71]
Belgardt, B.F.; Ahmed, K.; Spranger, M.; Latreille, M.; Denzler, R.; Kondratiuk, N.; von Meyenn, F.; Villena, F.N.; Herrmanns, K.; Bosco, D.; Kerr-Conte, J.; Pattou, F.; Rülicke, T.; Stoffel, M. The microRNA-200 family regulates pancreatic beta cell survival in type 2 diabetes. Nat. Med., 2015, 21(6), 619-627.
[http://dx.doi.org/10.1038/nm.3862] [PMID: 25985365]
[72]
He, A.; Zhu, L.; Gupta, N.; Chang, Y.; Fang, F. Overexpression of micro ribonucleic acid 29, highly up-regulated in diabetic rats, leads to insulin resistance in 3T3-L1 adipocytes. Mol. Endocrinol., 2007, 21(11), 2785-2794.
[http://dx.doi.org/10.1210/me.2007-0167] [PMID: 17652184]
[73]
Stefan, N.; Sun, Q.; Fritsche, A.; Machann, J.; Schick, F.; Gerst, F.; Jeppesen, C.; Joost, H.G.; Hu, F.B.; Boeing, H.; Ullrich, S.; Häring, H.U.; Schulze, M.B. Impact of the adipokine adiponectin and the hepatokine fetuin-A on the development of type 2 diabetes: Prospective cohort- and cross-sectional phenotyping studies. PLoS One, 2014, 9(3), e92238.
[http://dx.doi.org/10.1371/journal.pone.0092238] [PMID: 24643166]

Rights & Permissions Print Cite
Article Metrics
13
1
Wayfinder Image
Open Access Journals Promotions
© 2024 Bentham Science Publishers | Privacy Policy