Advertisement

Diabetologia

, Volume 62, Issue 1, pp 58–69 | Cite as

Non-traditional biomarkers and incident diabetes in the Diabetes Prevention Program: comparative effects of lifestyle and metformin interventions

  • Ronald B. Goldberg
  • George A. Bray
  • Santica M. Marcovina
  • Kieren J. Mather
  • Trevor J. Orchard
  • Leigh Perreault
  • Marinella Temprosa
  • Diabetes Prevention Program Research Group
Article

Abstract

Aims/hypothesis

We compared the associations of circulating biomarkers of inflammation, endothelial and adipocyte dysfunction and coagulation with incident diabetes in the placebo, lifestyle and metformin intervention arms of the Diabetes Prevention Program, a randomised clinical trial, to determine whether reported associations in general populations are reproduced in individuals with impaired glucose tolerance, and whether these associations are independent of traditional diabetes risk factors. We further investigated whether biomarker–incident diabetes associations are influenced by interventions that alter pathophysiology, biomarker concentrations and rates of incident diabetes.

Methods

The Diabetes Prevention Program randomised 3234 individuals with impaired glucose tolerance into placebo, metformin (850 mg twice daily) and intensive lifestyle groups and showed that metformin and lifestyle reduced incident diabetes by 31% and 58%, respectively compared with placebo over an average follow-up period of 3.2 years. For this study, we measured adiponectin, leptin, tissue plasminogen activator (as a surrogate for plasminogen activator inhibitor 1), high-sensitivity C-reactive protein, IL-6, monocyte chemotactic protein 1, fibrinogen, E-selectin and intercellular adhesion molecule 1 at baseline and at 1 year by specific immunoassays. Traditional diabetes risk factors were defined as family history, HDL-cholesterol, triacylglycerol, BMI, fasting and 2 h glucose, HbA1c, systolic blood pressure, inverse of fasting insulin and insulinogenic index. Cox proportional hazard models were used to assess the effects of each biomarker on the development of diabetes assessed semi-annually and the effects of covariates on these.

Results

E-selectin, (HR 1.19 [95% CI 1.06, 1.34]), adiponectin (0.84 [0.71, 0.99]) and tissue plasminogen activator (1.13 [1.03, 1.24]) were associated with incident diabetes in the placebo group, independent of diabetes risk factors. Only the association between adiponectin and diabetes was maintained in the lifestyle (0.69 [0.52, 0.92]) and metformin groups (0.79 [0.66, 0.94]). E-selectin was not related to diabetes development in either lifestyle or metformin groups. A novel association appeared for change in IL-6 in the metformin group (1.09 [1.021, 1.173]) and for baseline leptin in the lifestyle groups (1.31 [1.06, 1.63]).

Conclusions/interpretation

These findings clarify associations between an extensive group of biomarkers and incident diabetes in a multi-ethnic cohort with impaired glucose tolerance, the effects of diabetes risk factors on these, and demonstrate differential modification of associations by interventions. They strengthen evidence linking adiponectin to diabetes development, and argue against a central role for endothelial dysfunction. The findings have implications for the pathophysiology of diabetes development and its prevention.

Keywords

Adiponectin Biomarkers C-reactive protein Diabetes prevention E-selectin Interleukin 6 Leptin Lifestyle change Metformin Tissue plasminogen activator 

Abbreviations

CRP

C-reactive protein

DRF

Diabetes risk factor

DPP

Diabetes Prevention Program

IFI

Inverse of fasting insulin

IGI

Insulinogenic index

ILS

Intensive lifestyle modification

MCP-1

Monocyte chemoattractive protein 1

PAI-1

Plasminogen activator inhibitor 1

SBP

Systolic BP

sE-selectin

Soluble E-selectin

sICAM-1

Soluble intercellular adhesion molecule 1

tPA

Tissue plasminogen activator

Notes

Acknowledgements

This manuscript is dedicated to the late Abbas Kitabchi MD, in recognition of his many contributions to the field of diabetes.

The Research Group gratefully acknowledges the commitment and dedication of the participants of the DPP and Diabetes Prevention Program Outcomes Study (DPPOS). A complete list of centres, investigators and staff can be found in the ESM.

Contribution statement

MT and RG wrote the manuscript, SM performed the assays, MT did the major analyses and RG, MT, GB, SM, TO, LP and KM, who comprised the Writing Group, all made substantial contributions to study design, analysis and interpretation of data, and revised the manuscript critically for intellectual content and gave final approval of the version to be published. MT is the guarantor of the work.

Funding

During the DPP and DPPOS, the NIDDK of the National Institutes of Health provided funding to the clinical centres and the coordinating centre for the design and conduct of the study and collection, management, analysis and interpretation of the data (U01 DK048489). Funding for measurement of biomarkers was provided by an NIDDK grant (1R01DK078907-01A1). The Southwestern American Indian centres were supported directly by the NIDDK, including its intramural research programme, and the Indian Health Service. The General Clinical Research Center Program, National Center for Research Resources and the Department of Veterans Affairs supported data collection at many of the clinical centres. Funding was also provided by the National Institute of Child Health and Human Development, the National Institute on Aging, the National Eye Institute, the National Heart Lung and Blood Institute, the National Cancer Institute, the Office of Research on Women’s Health, the National Institute on Minority Health and Health Disparities, the Centers for Disease Control and Prevention and the American Diabetes Association. Bristol-Myers Squibb and Parke-Davis provided additional funding and material support during the DPP, Lipha (Merck-Sante) provided medication and LifeScan donated materials during the DPP and DPPOS. This research was also supported, in part, by the intramural research programme of the NIDDK. LifeScan, Health O Meter, Hoechst Marion Roussel, Merck-Medco Managed Care, Merck, Nike Sports Marketing, SlimFast Foods and Quaker Oats donated materials, equipment or medicines for concomitant conditions. McKesson BioServices, Matthews Media Group and the Henry M. Jackson Foundation provided support services under subcontract with the coordinating centre. The sponsor of this study was represented on the Steering Committee and played a part in study design, how the study was done and publication. The funding agency was not represented on the writing group, although all members of the Steering Committee had input into the report’s contents. All authors in the writing group had access to all data. The opinions expressed are those of the investigators and do not necessarily reflect the views of the funding agencies. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Duality of interest

KM received an investigator-initiated project grant from Novo and has also received donations of medications or supplies with aggregate value >$10,000 for other research studies from Novo Nordisk, Sanofi, Merck and Abbott. MT received honoraria for speaking at symposium from Merck. All other authors declare that there is no duality of interest associated with their contribution to this manuscript.

Supplementary material

125_2018_4748_MOESM1_ESM.pdf (411 kb)
ESM (PDF 410 kb)

References

  1. 1.
    Goldberg RB (2009) Cytokine and cytokine-like inflammation markers, endothelial dysfunction, and imbalanced coagulation in development of diabetes and its complications. J Clin Endocrinol Metab 94(9):3171–3182.  https://doi.org/10.1210/jc.2008-2534 CrossRefPubMedGoogle Scholar
  2. 2.
    Sattar N, Wannamethee SG, Forouhi NG (2008) Novel biochemical risk factors for type 2 diabetes: pathogenic insights or prediction possibilities? Diabetologia 51(6):926–940.  https://doi.org/10.1007/s00125-008-0954-7 CrossRefPubMedGoogle Scholar
  3. 3.
    Diabetes Prevention Program Research Group, Knowler WC, Barrett-Connor E, Fowler SE et al (2002) Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 346:393–340CrossRefPubMedCentralGoogle Scholar
  4. 4.
    Kitabchi AE, Temprosa M, Knowler WC, Diabetes Prevention Program Research Group et al (2005) Role of insulin secretion and sensitivity in the evolution of type 2 diabetes in the Diabetes Prevention Program: effects of lifestyle intervention and metformin. Diabetes 54(8):2404–2414CrossRefPubMedGoogle Scholar
  5. 5.
    Expert Committee on the Diagnosis and Classification of Diabetes Mellitus (1997) Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 20(7):1183–1197.  https://doi.org/10.2337/diacare.20.7.1183 CrossRefGoogle Scholar
  6. 6.
    Lowe GD, Danesh J, Lewington S et al (2004) Tissue plasminogen activator antigen and coronary heart disease: prospective study and meta-analysis. Eur Heart J 25(3):252–259.  https://doi.org/10.1016/j.ehj.2003.11.004 CrossRefPubMedGoogle Scholar
  7. 7.
    Koenker R, Machado AF (1999) Goodness of Fit and Related Inference Processes for Quantile Regression. J Am Stat Assoc 94(448):1296–1310.  https://doi.org/10.1080/01621459.1999.10473882 CrossRefGoogle Scholar
  8. 8.
    Bray GA, Jablonski KA, Fujimoto WY, Diabetes Prevention Program Research Group et al (2008) Relation of central adiposity and body mass index to the development of diabetes in the Diabetes Prevention Program. Am J Clin Nutr 87(5):1212–1218.  https://doi.org/10.1093/ajcn/87.5.1212 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Schmidt MI, Duncan BB, Sharrett AR et al (1999) Markers of inflammation and prediction of diabetes mellitus in adults (Atherosclerosis Risk in Communities study): a cohort study. Lancet 353(9165):1649–1652.  https://doi.org/10.1016/S0140-6736(99)01046-6 CrossRefPubMedGoogle Scholar
  10. 10.
    Lindsay RS, Funahashi T, Hanson RL et al (2002) Adiponectin and development of type 2 diabetes in the Pima Indian population. Lancet 360(9326):57–58.  https://doi.org/10.1016/S0140-6736(02)09335-2 CrossRefPubMedGoogle Scholar
  11. 11.
    Festa A, D’Agostino R Jr, Tracy RP, Insulin Resistance Atherosclerosis Study et al (2002) Elevated levels of acute-phase proteins and plasminogen activator inhibitor-1 predict the development of type 2 diabetes: the insulin resistance atherosclerosis study. Diabetes 51(4):1131–1137.  https://doi.org/10.2337/diabetes.51.4.1131 CrossRefPubMedGoogle Scholar
  12. 12.
    Duncan BB, Schmidt MI, Pankow JS, Atherosclerosis Risk in Communities Study et al (2003) Low-grade systemic inflammation and the development of type 2 diabetes: the atherosclerosis risk in communities study. Diabetes 52(7):1799–1805.  https://doi.org/10.2337/diabetes.52.7.1799 CrossRefPubMedGoogle Scholar
  13. 13.
    Meigs JB, Hu FB, Rifai N, Manson JE (2004) Biomarkers of endothelial dysfunction and risk of type 2 diabetes mellitus. JAMA 291(16):1978–1986.  https://doi.org/10.1001/jama.291.16.1978 CrossRefPubMedGoogle Scholar
  14. 14.
    Herder C, Baumert J, Thorand B et al (2006) Chemokines as risk factors for type 2 diabetes: results from the MONICA/KORA Augsburg study, 1984-2002. Diabetologia 49(5):921–929.  https://doi.org/10.1007/s00125-006-0190-y CrossRefPubMedGoogle Scholar
  15. 15.
    Hernestål-Boman J, Norberg M, Jansson JH et al (2012) Signs of dysregulated fibrinolysis precede the development of type 2 diabetes mellitus in a population-based study. Cardiovasc Diabetol 11:15224CrossRefGoogle Scholar
  16. 16.
    Julia C, Czernichow S, Charnaux N et al (2014) Relationships between adipokines, biomarkers of endothelial function and inflammation and risk of type 2 diabetes. Diabetes Res Clin Pract 105(2):231–238.  https://doi.org/10.1016/j.diabres.2014.05.001 CrossRefPubMedGoogle Scholar
  17. 17.
    Wannamethee SG, Lowe GD, Rumley A et al (2007) Adipokines and risk of type 2 diabetes in older men. Diabetes Care 30(5):1200–1205.  https://doi.org/10.2337/dc06-2416 CrossRefPubMedGoogle Scholar
  18. 18.
    Kadowaki T, Yamauchi T, Kubota N et al (2006) Adiponectin and adiponectin receptors in insulin resistance, diabetes, and the metabolic syndrome. J Clin Invest 116(7):1784–1792.  https://doi.org/10.1172/JCI29126 CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Tao C, Sifuentes A, Holland WL (2014) Regulation of glucose and lipid homeostasis by adiponectin: effects on hepatocytes, pancreatic β cells and adipocytes. Best Pract Res Clin Endocrinol Metab 28(1):43–58.  https://doi.org/10.1016/j.beem.2013.11.003 CrossRefPubMedGoogle Scholar
  20. 20.
    Cesari M, Pahor M, Incalzi RA (2010) Plasminogen activator inhibitor-1 (PAI-1): a key factor linking fibrinolysis and age-related subclinical and clinical conditions. Cardiovasc Ther 28(5):e72–e91.  https://doi.org/10.1111/j.1755-5922.2010.00171.x CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Juhan-Vague I, Thompson SG, Jespersen J (1993) Involvement of the hemostatic system in the insulin resistance syndrome: a study of 1500 patients with angina pectoris. Arterioscler Thromb 13(12):1865–1873.  https://doi.org/10.1161/01.ATV.13.12.1865 CrossRefPubMedGoogle Scholar
  22. 22.
    Roldán V, Marín F, Lip GY, Blann AD (2003) Soluble E-selectin in cardiovascular disease and its risk factors. A review of the literature. Thromb Haemost 90(6):1007–1020.  https://doi.org/10.1160/TH02-09-0083 CrossRefPubMedGoogle Scholar
  23. 23.
    Stern MP (1995) Diabetes and cardiovascular disease. The “common soil” hypothesis. Diabetes 44(4):369–374.  https://doi.org/10.2337/diab.44.4.369 CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Mather KJ, Funahashi T, Matsuzawa Y, Diabetes Prevention Program et al (2008) Adiponectin, change in adiponectin, and progression to diabetes in the Diabetes Prevention Program. Diabetes 57(4):980–986.  https://doi.org/10.2337/db07-1419 CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Li S, Shin HJ, Ding EL, van Dam RM (2009) Adiponectin levels and risk of type 2 diabetes: a systematic review and meta-analysis. JAMA 302(2):179–188.  https://doi.org/10.1001/jama.2009.976 CrossRefPubMedGoogle Scholar
  26. 26.
    Festa A, Williams K, Tracy RP, Wagenknecht LE, Haffner SM (2006) Progression of plasminogen activator inhibitor-1 and fibrinogen levels in relation to incident type 2 diabetes. Circulation 113(14):1753–1759.  https://doi.org/10.1161/CIRCULATIONAHA.106.616177 CrossRefPubMedGoogle Scholar
  27. 27.
    Hamdy O, Ledbury S, Mullooly C et al (2003) Lifestyle modification improves endothelial function in obese subjects with the insulin resistance syndrome. Diabetes Care 26(7):2119–2125.  https://doi.org/10.2337/diacare.26.7.2119 CrossRefPubMedGoogle Scholar
  28. 28.
    Mather KJ, Verma S, Anderson TJ (2001) Improved endothelial function with metformin in type 2 diabetes mellitus. J Am Coll Cardiol 37(5):1344–1350.  https://doi.org/10.1016/S0735-1097(01)01129-9 CrossRefPubMedGoogle Scholar
  29. 29.
    Florez H, Castillo-Florez S, Mendez A et al (2006) C-reactive protein is elevated in obese patients with the metabolic syndrome. Diabetes Res Clin Pract 71(1):92–100.  https://doi.org/10.1016/j.diabres.2005.05.003 CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Ronald B. Goldberg
    • 1
  • George A. Bray
    • 2
  • Santica M. Marcovina
    • 3
  • Kieren J. Mather
    • 4
  • Trevor J. Orchard
    • 5
  • Leigh Perreault
    • 6
  • Marinella Temprosa
    • 7
  • Diabetes Prevention Program Research Group
    • 8
  1. 1.Division of Endocrinology, Diabetes and Metabolism, Diabetes Research InstituteUniversity of Miami Miller School of MedicineMiamiUSA
  2. 2.Clinical Obesity, Pennington Biomedical Research CenterLouisiana State University Medical CenterBaton RougeUSA
  3. 3.Northwest Lipid Metabolism and Diabetes Research Laboratories, University of Washington, Northwest Lipid Research LabsSeattleUSA
  4. 4.Department of MedicineIndiana University School of MedicineIndianapolisUSA
  5. 5.Department of EpidemiologyUniversity of Pittsburgh Graduate School of Public HealthPittsburghUSA
  6. 6.Department of MedicineUniversity of Colorado Anschutz Medical CampusAuroraUSA
  7. 7.Department of Epidemiology and Biostatistics, Biostatistics Center and Milken Institute School of Public HealthGeorge Washington UniversityRockvilleUSA
  8. 8.c/o Diabetes Prevention Program Coordinating Center, The Biostatistics CenterMilken Institute School of Public Health George Washington UniversityRockvilleUSA

Personalised recommendations