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Current Diabetes Reviews

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ISSN (Print): 1573-3998
ISSN (Online): 1875-6417

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General Research Article

Growth Differentiation Factor-15 as a Biomarker of Obese Pre-diabetes and Type 2 Diabetes Mellitus in Indian Subjects: A Case-control Study

Author(s): Dipayan Roy*, Purvi Purohit*, Anupama Modi, Manoj Khokhar, Ravindra Kumar Gayaprasad Shukla, Ramkaran Chaudhary, Shrimanjunath Sankanagoudar and Praveen Sharma

Volume 18, Issue 1, 2022

Published on: 04 January, 2021

Article ID: e010321189862 Pages: 13

DOI: 10.2174/1573399817666210104101739

Abstract

Background: Type 2 diabetes mellitus (T2DM) is an ever-growing epidemic in India and poses significant morbidity, mortality, and socioeconomic burden.

Introduction: Growth differentiation factor-15 (GDF15) is a stress-responsive cytokine, increased in T2DM patients compared to control subjects without the disease. We aimed to assess whether serum GDF15 and adipose tissue GDF15 expression can differentiate between obese pre-diabetes and T2DM and control populations.

Methodology: We recruited 156 individuals including 73 type 2 diabetes, 30 pre-diabetes, and 53 healthy controls. Clinical history, anthropometric measurements and biochemical profiling were taken. Insulin resistance indices were calculated following HOMA models. Serum GDF15 was measured by sandwich ELISA. Visceral adipose tissue (VAT) expression of GDF15 was observed in 17 T2DM patients and 29 controls using SYBR Green chemistry in RT-PCR using GAPDH as the housekeeping gene. The data were analyzed on R programming platform using RStudio.

Results: Serum GDF15 was significantly higher (p<0.001) in T2DM subjects (median 1445.47 pg/mL) compared to pre-diabetes (627.85 pg/mL) and healthy controls (609.01 pg/mL). Using the ΔΔCt method, the VAT GDF15 expression was 1.54 fold and 1.57 fold upregulated in T2DM (n=17) compared to control subjects (n=29), and obese (n=12) compared to non-obese (n=34)subjects, respectively. The optimal cut-off point following Youden’s index method was found to be 868.09 pg/mL. ROC curve analysis revealed that serum GDF15 had a sensitivity, specificity, and area under the curve (AUC) of 90.41%, 79.52%, and 0.892 respectively. GDF15 levels were significantly associated with age, BMI, HbA1c, fasting blood sugar, and insulin resistance indices.

Conclusion: Hence, serum GDF15 is a biomarker for T2DM patients in our study population from Western India. However, larger prospective cohorts are necessary to validate this claim.

Keywords: GDF15, MIC-1, biomarker, visceral adipose tissue, cutpointr, type 2 diabetes, obesity.

[1]
Bootcov MR, Bauskin AR, Valenzuela SM, et al. MIC-1, a novel macrophage inhibitory cytokine, is a divergent member of the TGF-beta superfamily. Proc Natl Acad Sci USA 1997; 94(21): 11514-9.
[http://dx.doi.org/10.1073/pnas.94.21.11514] [PMID: 9326641]
[2]
Ding Q, Mracek T, Gonzalez-Muniesa P, et al. Identification of macrophage inhibitory cytokine-1 in adipose tissue and its secretion as an adipokine by human adipocytes. Endocrinology 2009; 150(4): 1688-96.
[http://dx.doi.org/10.1210/en.2008-0952] [PMID: 19074584]
[3]
Patel S, Alvarez-Guaita A, Melvin A, et al. GDF15 provides an endocrine signal of nutritional stress in mice and humans. Cell Metab 2019; 29(3): 707-718.e8.
[http://dx.doi.org/10.1016/j.cmet.2018.12.016] [PMID: 30639358]
[4]
Macia L, Tsai VW, Nguyen AD, et al. Macrophage inhibitory cytokine 1 (MIC-1/GDF15) decreases food intake, body weight and improves glucose tolerance in mice on normal & obesogenic diets. PLoS One 2012; 7(4)
[http://dx.doi.org/10.1371/journal.pone.0034868] [PMID: 22514681]
[5]
Chrysovergis K, Wang X, Kosak J, et al. NAG-1/GDF-15 prevents obesity by increasing thermogenesis, lipolysis and oxidative metabolism. Int J Obes 2014; 38(12): 1555-64.
[http://dx.doi.org/10.1038/ijo.2014.27] [PMID: 24531647]
[6]
Adela R, Banerjee SK. GDF-15 as a target and biomarker for diabetes and cardiovascular diseases:a translational prospective. J Diabetes Res 2015; 2015:490842.
[http://dx.doi.org/10.1155/2015/490842] [PMID: 26273671]
[7]
Dostálová I, Roubícek T, Bártlová M, et al. Increased serum concentrations of macrophage inhibitory cytokine-1 in patients with obesity and type 2 diabetes mellitus: the influence of very low calorie diet. Eur J Endocrinol 2009; 161(3): 397-404.
[http://dx.doi.org/10.1530/EJE-09-0417] [PMID: 19515791]
[8]
Vila G, Riedl M, Anderwald C, et al. The relationship between insulin resistance and the cardiovascular biomarker growth differentiation factor-15 in obese patients. Clin Chem 2011; 57(2): 309-16.
[http://dx.doi.org/10.1373/clinchem.2010.153726] [PMID: 21164037]
[9]
Kempf T, Guba-Quint A, Torgerson J, et al. Growth differentiation factor 15 predicts future insulin resistance and impaired glucose control in obese nondiabetic individuals: results from the XENDOS trial. Eur J Endocrinol 2012; 167(5): 671-8.
[http://dx.doi.org/10.1530/EJE-12-0466] [PMID: 22918303]
[10]
Bao X, Borné Y, Muhammad IF, et al. Growth differentiation factor 15 is positively associated with incidence of diabetes mellitus: the Malmö Diet and Cancer-Cardiovascular Cohort. Diabetologia 2019; 62(1): 78-86.
[http://dx.doi.org/10.1007/s00125-018-4751-7] [PMID: 30350239]
[11]
Carstensen M, Herder C, Brunner EJ, et al. Macrophage inhibitory cytokine-1 is increased in individuals before type 2 diabetes diagnosis but is not an independent predictor of type 2 diabetes: the Whitehall II study. Eur J Endocrinol 2010; 162(5): 913-7.
[http://dx.doi.org/10.1530/EJE-09-1066] [PMID: 20167682]
[12]
Hong JH, Chung HK, Park HY, et al. GDF15 Is a Novel Biomarker for Impaired Fasting Glucose. Diabetes Metab J 2014; 38(6): 472-9.
[http://dx.doi.org/10.4093/dmj.2014.38.6.472] [PMID: 25541611]
[13]
Pradeepa R, Mohan V. Prevalence of type 2 diabetes and its complications in India and economic costs to the nation. Eur J Clin Nutr 2017; 71(7): 816-24.
[http://dx.doi.org/10.1038/ejcn.2017.40] [PMID: 28422124]
[14]
Hruby A, Frank B. The epidemiology of obesity: A big picture. Pharmacoeconomics 2015. Jul;33(7):673-89.
[http://dx.doi.org/10.1007/s40273-014-0243-x] [PMID: 25471927]
[15]
American Diabetes Association. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes-2020. Diabetes Care 2020; 43(Suppl. 1): S14-31.
[http://dx.doi.org/10.2337/dc20-S002] [PMID: 31862745]
[16]
World Health Organization. (‎2011)‎. Waist circumference and waist-hip ratio : report of a WHO expert consultation, Geneva, 8-11 December 2008. World Health Organization. https://apps.who.int/iris/handle/10665/44583
[17]
Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28(7): 412-9.
[http://dx.doi.org/10.1007/BF00280883] [PMID: 3899825]
[18]
Jeppesen J, Facchini FS, Reaven GM. Individuals with high total cholesterol/HDL cholesterol ratios are insulin resistant. J Intern Med 1998; 243(4): 293-8.
[http://dx.doi.org/10.1046/j.1365-2796.1998.00301.x] [PMID: 9627143]
[19]
Zhang L, Chen S, Deng A, et al. Association between lipid ratios and insulin resistance in a Chinese population. PLoS One 2015; 10(1): e0116110.
[http://dx.doi.org/10.1371/journal.pone.0116110] [PMID: 25635876]
[20]
Simental-Mendía LE, Rodríguez-Morán M, Guerrero-Romero F. The product of fasting glucose and triglycerides as surrogate for identifying insulin resistance in apparently healthy subjects. Metab Syndr Relat Disord 2008; 6(4): 299-304.
[http://dx.doi.org/10.1089/met.2008.0034] [PMID: 19067533]
[21]
Roy D, Tomo S, Modi A, Purohit P, Sharma P. Optimising total RNA quality and quantity by phenol-chloroform extraction method from human visceral adipose tissue: a standardisation study. MethodsX 2020; 101113
[http://dx.doi.org/10.1016/j.mex.2020.101113]
[22]
Chomczynski P, Sacchi N. The single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction: twenty-something years on. Nat Protoc 2006; 1(2): 581-5.
[http://dx.doi.org/10.1038/nprot.2006.83] [PMID: 17406285]
[23]
RStudio Team. RStudio: Integrated Development for R RStudio, Inc 2015.http://www.rstudio.com/
[24]
Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Δ Δ C(T)) Method. Methods 2001; 25(4): 402-8.
[http://dx.doi.org/10.1006/meth.2001.1262] [PMID: 11846609]
[25]
Tan CK, Chong HC, Tan EHP, Tan NS. Getting ‘Smad’ about obesity and diabetes. Nutr Diabetes 2012; 2(3)
[http://dx.doi.org/10.1038/nutd.2012.1] [PMID: 23449528]
[26]
Herder C, Zierer A, Koenig W, Roden M, Meisinger C, Thorand B. Transforming growth factor-beta1 and incident type 2 diabetes: results from the MONICA/KORA case-cohort study, 1984-2002. Diabetes Care 2009; 32(10): 1921-3.
[http://dx.doi.org/10.2337/dc09-0476] [PMID: 19592635]
[27]
Germain RN. Maintaining system homeostasis: the third law of Newtonian immunology. Nat Immunol 2012; 13(10): 902-6.
[http://dx.doi.org/10.1038/ni.2404] [PMID: 22990887]
[28]
Kolb H, Mandrup-Poulsen T. The global diabetes epidemic as a consequence of lifestyle-induced low-grade inflammation. Diabetologia 2010; 53(1): 10-20.
[http://dx.doi.org/10.1007/s00125-009-1573-7] [PMID: 19890624]
[29]
Minamino T, Orimo M, Shimizu I, et al. A crucial role for adipose tissue p53 in the regulation of insulin resistance. Nat Med 2009; 15(9): 1082-7.
[http://dx.doi.org/10.1038/nm.2014] [PMID: 19718037]
[30]
Berezin AE. Diabetes mellitus related biomarker: The predictive role of growth-differentiation factor-15. Diabetes Metab Syndr 2016; 10(1)(Suppl. 1): S154-7.
[http://dx.doi.org/10.1016/j.dsx.2015.09.016] [PMID: 26482961]
[31]
Mullican SE, Lin-Schmidt X, Chin CN, et al. GFRAL is the receptor for GDF15 and the ligand promotes weight loss in mice and nonhuman primates. Nat Med 2017; 23(10): 1150-7.
[http://dx.doi.org/10.1038/nm.4392] [PMID: 28846097]
[32]
Karczewska-Kupczewska M, Kowalska I, Nikolajuk A, et al. Hyperinsulinemia acutely increases serum macrophage inhibitory cytokine-1 concentration in anorexia nervosa and obesity. Clin Endocrinol (Oxf) 2012; 76(1): 46-50.
[http://dx.doi.org/10.1111/j.1365-2265.2011.04139.x] [PMID: 21645023]
[33]
Schernthaner-Reiter MH, Itariu BK, Krebs M, et al. GDF15 reflects beta cell function in obese patients independently of the grade of impairment of glucose metabolism. Nutr Metab Cardiovasc Dis 2019; 29(4): 334-42.
[http://dx.doi.org/10.1016/j.numecd.2018.12.008] [PMID: 30718144]
[34]
Lu J, Zhang Y, Dong X, et al. Association between MIC-1 and Type 2 Diabetes: A Combined Analysis. Dis Markers 2019; 2019:7284691.
[http://dx.doi.org/10.1155/2019/7284691] [PMID: 31827641]
[35]
Kempf T, Horn-Wichmann R, Brabant G, et al. Circulating concentrations of growth-differentiation factor 15 in apparently healthy elderly individuals and patients with chronic heart failure as assessed by a new immunoradiometric sandwich assay. Clin Chem 2007; 53(2): 284-91.
[http://dx.doi.org/10.1373/clinchem.2006.076828] [PMID: 17185363]
[36]
Modi A, Dwivedi S, Roy D, et al. Growth differentiation factor 15 and its role in carcinogenesis: an update. Growth Factors 2019; 37(3-4): 190-207.
[http://dx.doi.org/10.1080/08977194.2019.1685988] [PMID: 31693861]
[37]
Gerstein HC, Pare G, Hess S, et al. ORIGIN Investigators. Growth Differentiation Factor 15 as a Novel Biomarker for Metformin. Diabetes Care 2017; 40(2): 280-3.
[http://dx.doi.org/10.2337/dc16-1682] [PMID: 27974345]
[38]
Day EA, Ford RJ, Smith BK, et al. Metformin-induced increases in GDF15 are important for suppressing appetite and promoting weight loss. Nature Metabolism 2019; 1: pp. 1202-8.
[http://dx.doi.org/10.1038/s42255-019-0146-4]
[39]
Coll AP, Chen M, Taskar P, et al. GDF15 mediates the effects of metformin on body weight and energy balance. Nature 2019; 578: 444-8.
[http://dx.doi.org/10.1038/s41586-019-1911-y] [PMID: 31875646]

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