Abstract
Background:
Growth differentiation factor-15 (GDF-15), a stress responsive cytokine, is a promising biomarker of renal functional decline in diabetic kidney disease (DKD). This study aimed primarily to establish normative data and secondarily to evaluate the potential utility of GDF-15 in DKD using Roche Diagnostics electrochemiluminescence immunoassay (ECLIA) in an Irish Caucasian population.
Methods:
Following informed consent, 188 healthy volunteers and 128 participants with diabetes (72 with and 56 without DKD) were recruited to a cross-sectional study. Baseline demographics, anthropometric measurements and laboratory measurements were recorded. Blood for GDF-15 measurement was collected into plain specimen tubes kept at room temperature and processed (centrifugation, separation of serum, freezing at −80 °C) within 1 h of phlebotomy pending batch analyses. Reference intervals were determined using the 2.5th and 97.5th percentiles for serum GDF-15 concentration.
Results:
Of 188 healthy participants, 63 failed to meet study inclusion criteria. The reference interval for serum GDF-15 was 399 ng/L (90% confidence interval [CI]: 399–399) – 1335 ng/L (90% CI: 1152–1445). Receiver operator characteristics (ROC) curve analysis for DKD determined the area under the ROC curve to be 0.931 (95% CI: 0.893–0.959; p<0.001). The optimum GDF-15 cutoff for predicting DKD was >1136 ng/L providing a diagnostic sensitivity and specificity of 94.4% and 79%, respectively, and positive likelihood ratio of 4.5:1 (95% CI: 3.4–6.0).
Conclusions:
The reference interval for serum GDF-15 in a healthy Irish Caucasian population using Roche Diagnostics ECLIA was established and a preliminary determination of the potential of GDF-15 as a screening test for DKD was made. Further prospective validation with a larger DKD cohort will be required before the cutoff presented here is recommended for clinical use.
Acknowledgments
We wish to express our gratitude to all volunteers and patients who made this study possible. Special thanks to the scientific, nursing and medical staff at the Centre for Endocrinology, Diabetes and Metabolism, and the Department of Clinical Biochemistry at Saolta University Health Care Group (SUHCG), Galway University Hospitals.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Guarantor: PMOS.
Research funding: TPG is supported by a Hardiman Scholarship from the College of Medicine, Nursing and Health Science, National University of Ireland, Galway and a bursary from the Irish Endocrine Society/Royal College of Physicians of Ireland. The authors are supported by grants from the European Commission [Horizon 2020 Collaborative Health Project NEPHSTROM (Funder Id: 10.13039/100010661, grant number 634086; TPG, NI, MDG) and FP7 Collaborative Health Project VISICORT (grant number 602470; MDG)] and from Science Foundation Ireland [REMEDI Strategic Research Cluster (Funder Id: 10.13039/501100001602, grant number 09/SRC-B1794; MDG) and CÚRAM Research Centre (grant number 13/RC/2073; MDG)] and by the European Regional Development Fund. The materials presented and views expressed here are the responsibility of the author(s) only. The EU Commission takes no responsibility for any use made of the information set out.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
References
1. Berezin AE. Growth-differentiation factor-15 at risk stratification in diabetes patients: usefulness, discrepancies, and hype. Int Arch Endocrinol Clin Res 2015;1:002.10.23937/2572-407X.1510002Search in Google Scholar
2. Hromas R, Hufford M, Sutton J, Xu D, Li Y, Lu L. PLAB, a novel placental bone morphogenetic protein. Biochim Biophys Acta 1997;1354:40–4.10.1016/S0167-4781(97)00122-XSearch in Google Scholar
3. Moore AG, Brown DA, Fairlie WD, Bauskin AR, Brown PK, Munier ML, et al. The transforming growth factor-ss superfamily cytokine macrophage inhibitory cytokine-1 is present in high concentrations in the serum of pregnant women. J Clin Endocrinol Metab 2000;85:4781–8.Search in Google Scholar
4. Bermudez B, Lopez S, Pacheco YM, Villar J, Muriana FJ, Hoheisel JD, et al. Influence of postprandial triglyceride-rich lipoproteins on lipid-mediated gene expression in smooth muscle cells of the human coronary artery. Cardiovasc Res 2008;79:294–303.10.1093/cvr/cvn082Search in Google Scholar PubMed
5. Schlittenhardt D, Schober A, Strelau J, Bonaterra GA, Schmiedt W, Unsicker K, et al. Involvement of growth differentiation factor-15/macrophage inhibitory cytokine-1 (GDF-15/MIC-1) in oxLDL-induced apoptosis of human macrophages in vitro and in arteriosclerotic lesions. Cell Tissue Res 2004;318:325–33.10.1007/s00441-004-0986-3Search in Google Scholar PubMed
6. Ding Q, Mracek T, Gonzalez-Muniesa P, Kos K, Wilding J, Trayhurn P, et al. Identification of macrophage inhibitory cytokine-1 in adipose tissue and its secretion as an adipokine by human adipocytes. Endocrinology 2009;150:1688–96.10.1210/en.2008-0952Search in Google Scholar PubMed
7. Ferrari N, Pfeffer U, Dell’Eva R, Ambrosini C, Noonan DM, Albini A. The transforming growth factor-beta family members bone morphogenetic protein-2 and macrophage inhibitory cytokine-1 as mediators of the antiangiogenic activity of N-(4-hydroxyphenyl)retinamide. Clin Cancer Res 2005;11:4610–9.10.1158/1078-0432.CCR-04-2210Search in Google Scholar PubMed
8. Corre J, Hébraud B, Bourin P. Concise review: growth differentiation factor 15 in pathology: a clinical role? Stem Cells Transl Med 2013;2:946–52.10.5966/sctm.2013-0055Search in Google Scholar PubMed PubMed Central
9. Adela R, Banerjee SK. GDF-15 as a target and biomarker for diabetes and cardiovascular diseases: a translational prospective. J Diabetes Res 2015;2015:490842.10.1155/2015/490842Search in Google Scholar PubMed PubMed Central
10. Wollert KC, Kempf T, Giannitsis E, Bertsch T, Braun SL, Maier H, et al. An automated assay for growth differentiation factor 15. J Appl Lab Med AACC Pub 2017;1:510–21.10.1373/jalm.2016.022376Search in Google Scholar PubMed
11. International Diabetes Federation. IDF Diabetes Atlas, 8th ed. Brussels, Belgium: International Diabetes Federation, 2017.Search in Google Scholar
12. Tuttle KR, Bakris GL, Bilous RW, Chiang JL, de Boer IH, Goldstein-Fuchs J, et al. Diabetic kidney disease: a report from an ADA Consensus Conference. Am J Kidney Dis 2014;64: 510–33.10.1053/j.ajkd.2014.08.001Search in Google Scholar PubMed
13. Inker LA, Astor BC, Fox CH, Isakova T, Lash JP, Peralta CA, et al. KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD. Am J Kidney Dis 2014;63:713–35.10.1053/j.ajkd.2014.01.416Search in Google Scholar PubMed
14. Levey AS, Eckardt KU, Tsukamoto Y, Levin A, Coresh J, Rossert J, et al. Definition and classification of chronic kidney disease: a position statement from kidney disease: improving global outcomes (KDIGO). Kidney Int 2005;67:2089–100.10.1111/j.1523-1755.2005.00365.xSearch in Google Scholar PubMed
15. Griffin TP, Martin WP, Islam N, O’Brien T, Griffin MD. The promise of mesenchymal stem cell therapy for diabetic kidney disease. Curr Diab Rep 2016;16:42.10.1007/s11892-016-0734-6Search in Google Scholar PubMed
16. Rich SS, Cefalu WT. The impact of precision medicine in diabetes: a multidimensional perspective. Diabetes Care 2016;39:1854–7.10.2337/dc16-1833Search in Google Scholar PubMed PubMed Central
17. Griffin TP, Wall D, Browne GA, Dennedy MC, O’Shea PM. Associations between glycaemic control and activation of the renin-angiotensin-aldosterone system in participants with type 2 diabetes mellitus and hypertension. Ann Clin Biochem 2018;55:373–84.10.1177/0004563217728964Search in Google Scholar PubMed
18. Florez JC. Precision medicine in diabetes: is it time? Diabetes Care 2016;39:1085–8.10.2337/dc16-0586Search in Google Scholar PubMed
19. Martin WP, Griffin TP, Lappin DW, Griffin DG, Ferguson JP, O’Brien T, et al. Influence of referral to a combined diabetology and nephrology clinic on renal functional trends and metabolic parameters in adults with diabetic kidney disease. Mayo Clin Proc Innov Qual Outcomes 2017;1:150–60.10.1016/j.mayocpiqo.2017.07.003Search in Google Scholar PubMed PubMed Central
20. Parving HH, Lehnert H, Brochner-Mortensen J, Gomis R, Andersen S, Arner P, et al. The effect of irbesartan on the development of diabetic nephropathy in patients with type 2 diabetes. N Engl J Med 2001;345:870–8.10.1056/NEJMoa011489Search in Google Scholar PubMed
21. Ruggenenti P, Fassi A, Ilieva AP, Bruno S, Iliev IP, Brusegan V, et al. Preventing microalbuminuria in type 2 diabetes. N Engl J Med 2004;351:1941–51.10.1056/NEJMoa042167Search in Google Scholar PubMed
22. De Muro P, Lepedda AJ, Nieddu G, Idini M, Tram Nguyen HQ, Lobina O, et al. Evaluation of early markers of nephropathy in patients with type 2 diabetes mellitus. Biochem Res Int 2016;2016:1–6.10.1155/2016/7497614Search in Google Scholar PubMed PubMed Central
23. Lajer M, Jorsal A, Tarnow L, Parving HH, Rossing P. Plasma growth differentiation factor-15 independently predicts all-cause and cardiovascular mortality as well as deterioration of kidney function in type 1 diabetic patients with nephropathy. Diabetes Care 2010;33:1567–72.10.2337/dc09-2174Search in Google Scholar PubMed PubMed Central
24. Frimodt-Moller M, von Scholten BJ, Reinhard H, Jacobsen PK, Hansen TW, Persson FI, et al. Growth differentiation factor-15 and fibroblast growth factor-23 are associated with mortality in type 2 diabetes – an observational follow-up study. PLoS One 2018;13:e0196634.10.1371/journal.pone.0196634Search in Google Scholar PubMed PubMed Central
25. Hellemons ME, Mazagova M, Gansevoort RT, Henning RH, de Zeeuw D, Bakker SJ, et al. Growth-differentiation factor 15 predicts worsening of albuminuria in patients with type 2 diabetes. Diabetes Care 2012;35:2340–6.10.2337/dc12-0180Search in Google Scholar PubMed PubMed Central
26. Bidadkosh A, Lambooy SP, Heerspink HJ, Pena MJ, Henning RH, Buikema H, et al. Predictive properties of biomarkers GDF-15, NTproBNP, and hs-TnT for morbidity and mortality in patients with type 2 diabetes with nephropathy. Diabetes Care 2017;40:784–92.10.2337/dc16-2175Search in Google Scholar PubMed
27. Mazagova M, Buikema H, van Buiten A, Duin M, Goris M, Sandovici M, et al. Genetic deletion of growth differentiation factor 15 augments renal damage in both type 1 and type 2 models of diabetes. Am J Physiol Renal Physiol 2013;305:F1249–64.10.1152/ajprenal.00387.2013Search in Google Scholar PubMed
28. Nair V, Robinson-Cohen C, Smith MR, Bellovich KA, Bhat ZY, Bobadilla M, et al. Growth differentiation factor-15 and risk of CKD progression. J Am Soc Nephrol 2017;28:2233–40.10.1681/ASN.2016080919Search in Google Scholar PubMed PubMed Central
29. National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification and stratification. Am J Kidney Dis 2002;39(Suppl 1):S1–266.Search in Google Scholar
30. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, 3rd, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604–12.10.7326/0003-4819-150-9-200905050-00006Search in Google Scholar PubMed PubMed Central
31. Roche Diagnostics. Elecsys GDF-15. Available at: https://pim-eservices.roche.com/eLD_SF/ie/en/Documents/GetDocument?documentId=7a3c5678-76b1-e611-c58c-00215a9b3428. Accessed: 15 April 2017.Search in Google Scholar
32. CLSI. Evaluation of precision of quantitative measurement procedures; approved guideline, 3rd ed. CLSI document EP05-A3. Wayne, PA: Clinical and Laboratory Standards Institute, 2014.Search in Google Scholar
33. Dixon W. Processing data for outliers. Biometrics 1953;9:74–89.10.2307/3001634Search in Google Scholar
34. Reed AH, Henry RJ, Mason WB. Influence of statistical method used on the resulting estimate of normal range. Clin Chem 1971;17:275–84.10.1093/clinchem/17.4.275Search in Google Scholar
35. CLSI. Defining, establishing, and verifying reference intervals in the clinical laboratory; approved guideline, 3rd ed. CLSI document EP28-A3c. Wayne, PA: Clinical and Laboratory Standards Institute, 2008.Search in Google Scholar
36. Soreide K. Receiver-operating characteristic curve analysis in diagnostic, prognostic and predictive biomarker research. J Clin Pathol 2009;62:1–5.10.1136/jcp.2008.061010Search in Google Scholar PubMed
37. Tripepi G, Jager KJ, Dekker FW, Zoccali C. Diagnostic methods 2: receiver operating characteristic (ROC) curves. Kidney Int 2009;76:252–6.10.1038/ki.2009.171Search in Google Scholar PubMed
38. Jones G, Barker A. Reference intervals. Clin Biochem Rev 2008;29(Suppl 1):S93–7.Search in Google Scholar
39. Ho JE, Mahajan A, Chen MH, Larson MG, McCabe EL, Ghorbani A, et al. Clinical and genetic correlates of growth differentiation factor 15 in the community. Clin Chem 2012;58:1582–91.10.1373/clinchem.2012.190322Search in Google Scholar PubMed PubMed Central
40. Kempf T, Horn-Wichmann R, Brabant G, Peter T, Allhoff T, Klein 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;53:284–91.10.1373/clinchem.2006.076828Search in Google Scholar PubMed
41. Vila G, Riedl M, Anderwald C, Resl M, Handisurya A, Clodi M, et al. The relationship between insulin resistance and the cardiovascular biomarker growth differentiation factor-15 in obese patients. Clin Chem 2011;57:309–16.10.1373/clinchem.2010.153726Search in Google Scholar PubMed
42. Daniels LB, Clopton P, Laughlin GA, Maisel AS, Barrett-Connor E. Growth-differentiation factor-15 is a robust, independent predictor of 11-year mortality risk in community-dwelling older adults: the Rancho Bernardo Study. Circulation 2011;123:2101–10.10.1161/CIRCULATIONAHA.110.979740Search in Google Scholar PubMed PubMed Central
43. Li H, Gao F, Xue Y, Qian Y. Value of plasma growth differentiation factor-15 in diagnosis and evaluation of type 2 diabetic nephropathy. Nan Fang Yi Ke Da Xue Xue Bao 2014;34:387–90.Search in Google Scholar
44. Wollert KC, Kempf T, Wallentin L. Growth differentiation factor 15 as a biomarker in cardiovascular disease. Clin Chem 2017;63:140–51.10.1373/clinchem.2016.255174Search in Google Scholar PubMed
45. Biesenbach G, Bodlaj G, Pieringer H, Sedlak M. Clinical versus histological diagnosis of diabetic nephropathy – is renal biopsy required in type 2 diabetic patients with renal disease? Q J Med 2011;104:771–4.10.1093/qjmed/hcr059Search in Google Scholar PubMed
Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2018-0534).
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