The utility of assessing C-peptide in patients with insulin-treated type 2 diabetes: a cross-sectional study

Abstract

Aims

We aimed at evaluating residual β-cell function in insulin-treated patients with type 2 diabetes (T2D) while determining for the first time the difference in C-peptide level between patients on basal–bolus compared to those on the basal insulin scheme, considered as an early stage of insulin treatment, together with assessing its correlation with the presence of complications.

Methods

A total of 93 candidates with T2D were enrolled in this cross-sectional study and were categorized into two groups based on the insulin regimen: Basal–Bolus (BB) if on both basal and rapid acting insulin, and Basal (B) if on basal insulin only, without rapid acting injections. HbA1c, fasting C-peptide concentration and other metabolic parameters were recorded, as well as the patient medical history.

Results

The average fasting C-peptide was 1.81 ± 0.15 ng/mL, and its levels showed a significant inverse correlation with the duration of diabetes (r = -0.24, p = 0.03). Despite similar disease duration and metabolic control, BB participants displayed lower fasting C-peptide (p < 0.005) and higher fasting glucose (P = 0.01) compared with B patients. Concentrations below 1.09 ng/mL could predict the adoption of a basal–bolus treatment (Area 0.64, 95%CI:0.521–0.759, p = 0.038, sensitivity 45% and specificity 81%).

Conclusions

Insulin-treated patients with long-standing T2D showed detectable level of fasting C-peptide. Measuring the β-cell function may therefore guide toward effective therapeutic options when oral hypoglycemic agents prove unsuccessful.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

Data availability

The data are available from the corresponding author on reasonable request.

References

  1. 1.

    World Health Organization. Health topics. Obesity. https://www.who.int/topics/obesity/en/. https://www.who.int/topics/obesity/en/. 2020

  2. 2.

    Watanabe M, Risi R, De Giorgi F et al (2020) Obesity treatment within the Italian national healthcare system tertiary care centers: what can we learn? Eat Weight Disord. https://doi.org/10.1007/s40519-020-00936-1

    Article  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Hu FB (2011) Globalization of diabetes: the role of diet, lifestyle, and genes. Diabetes Care 34(6):1249–1257. https://doi.org/10.2337/dc11-0442

    Article  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Basciani S, Camajani E, Contini S et al (2020) Very-low-calorie ketogenic diets with whey, vegetable or animal protein in patients with obesity: a randomized pilot study. J Clin Endocrinol Metab 105:336. https://doi.org/10.1210/clinem/dgaa336

    Article  Google Scholar 

  5. 5.

    Basciani S, Costantini D, Contini S et al (2015) Safety and efficacy of a multiphase dietetic protocol with meal replacements including a step with very low calorie diet. Endocrine 48(3):863–870. https://doi.org/10.1007/s12020-014-0355-2

    CAS  Article  PubMed  Google Scholar 

  6. 6.

    Bruci A, Tuccinardi D, Tozzi R et al (2020) Very low-calorie ketogenic diet: a safe and effective tool for weight loss in patients with obesity and mild kidney failure. Nutrients. https://doi.org/10.3390/nu12020333

    Article  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Soare A, Khazrai YM, Del Toro R et al (2014) The effect of the macrobiotic Ma-Pi 2 diet versus the recommended diet in the management of type 2 diabetes: the randomized controlled MADIAB trial. Nutr Metab (Lond). https://doi.org/10.1186/1743-7075-11-39

    Article  Google Scholar 

  8. 8.

    Look ARG, Pi-Sunyer X, Blackburn G et al (2007) Reduction in weight and cardiovascular disease risk factors in individuals with type 2 diabetes: one-year results of the look AHEAD trial. Diabetes Care 30(6):1374–1383. https://doi.org/10.2337/dc07-0048

    Article  Google Scholar 

  9. 9.

    Watanabe M, Gangitano E, Francomano D et al (2018) Mangosteen extract shows a potent insulin sensitizing effect in obese female patients: a prospective randomized controlled pilot study. Nutrients. https://doi.org/10.3390/nu10050586

    Article  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Yilmaz Z, Piracha F, Anderson L, Mazzola N (2017) Supplements for diabetes mellitus: a review of the literature. J Pharm Pract 30(6):631–638. https://doi.org/10.1177/0897190016663070

    Article  PubMed  Google Scholar 

  11. 11.

    Soare A, Del Toro R, Khazrai YM et al (2016) A 6-months follow-up study of the randomized controlled Ma–Pi macrobiotic dietary intervention (MADIAB trial) in type 2 diabetes. Nutr Diabetes 6(8):e222. https://doi.org/10.1038/nutd.2016.29

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Watanabe M, Tuccinardi D, Ernesti I et al (2020) Scientific evidence underlying contraindications to the ketogenic diet: an update. Obes Rev. https://doi.org/10.1111/obr.13053

    Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Tuccinardi D, Farr OM, Upadhyay J et al (2019) Lorcaserin treatment decreases body weight and reduces cardiometabolic risk factors in obese adults: a six-month, randomized, placebo-controlled, double-blind clinical trial. Diabetes Obes Metab 21(6):1487–1492. https://doi.org/10.1111/dom.13655

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    American Diabetes A (2019) 9. Pharmacologic approaches to glycemic treatment: standards of medical care in diabetes-2019. Diabetes Care 42:S90–S102. https://doi.org/10.2337/dc19-S009

    Article  Google Scholar 

  15. 15.

    Bretzel RG, Eckhard M, Landgraf W, Owens DR, Linn T (2009) Initiating insulin therapy in type 2 diabetic patients failing on oral hypoglycemic agents: basal or prandial insulin? The APOLLO trial and beyond. Diabetes Care 32(Suppl 2):S260-265. https://doi.org/10.2337/dc09-S319

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Centers for Disease Control and Prevention. National Diabetes Statistics Report (2020) Centers for disease control and prevention. US Department of Health and Human Services, Atlanta, GA

    Google Scholar 

  17. 17.

    Swinnen SG, Hoekstra JB, DeVries JH (2009) Insulin therapy for type 2 diabetes. Diabetes Care 32(Suppl 2):S253-259. https://doi.org/10.2337/dc09-S318

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Landin-Olsson M, Nilsson KO, Lernmark A, Sundkvist G (1990) Islet cell antibodies and fasting C-peptide predict insulin requirement at diagnosis of diabetes mellitus. Diabetologia 33(9):561–568. https://doi.org/10.1007/BF00404145

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    American Diabetes A (2020) 2. Classification and diagnosis of diabetes: standards of medical care in diabetes-2020. Diabetes Care 43:S14–S31. https://doi.org/10.2337/dc20-S002

    Article  Google Scholar 

  20. 20.

    Sabbah E, Savola K, Ebeling T et al (2000) Genetic, autoimmune, and clinical characteristics of childhood- and adult-onset type 1 diabetes. Diabetes Care 23(9):1326–1332. https://doi.org/10.2337/diacare.23.9.1326

    CAS  Article  PubMed  Google Scholar 

  21. 21.

    Di Stasio E, Maggi D, Berardesca E et al (2011) Blue eyes as a risk factor for type 1 diabetes. Diabetes Metab Res Rev 27(6):609–613. https://doi.org/10.1002/dmrr.1214

    Article  PubMed  Google Scholar 

  22. 22.

    Shields BM, Peters JL, Cooper C et al (2015) Can clinical features be used to differentiate type 1 from type 2 diabetes? a systematic review of the literature. BMJ Open 5(11):e009088. https://doi.org/10.1136/bmjopen-2015-009088

    Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Jones AG, McDonald TJ, Shields BM et al (2016) Markers of beta-cell failure predict poor glycemic response to glp-1 receptor agonist therapy in type 2 diabetes. Diabetes Care 39(2):250–257. https://doi.org/10.2337/dc15-0258

    CAS  Article  PubMed  Google Scholar 

  24. 24.

    Lee A, Morley J (1999) Classification of type 2 diabetes by clinical response to metformin-troglitazone combination and C-Peptide criteria. Endocr Pract 5(6):305–313. https://doi.org/10.4158/EP.5.6.305

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Jones AG, Besser RE, Shields BM, McDonald TJ, Hope SV, Knight BA, Hattersley AT (2012) Assessment of endogenous insulin secretion in insulin treated diabetes predicts postprandial glucose and treatment response to prandial insulin. BMC Endocr Disord. https://doi.org/10.1186/1472-6823-12-6

    Article  PubMed  PubMed Central  Google Scholar 

  26. 26.

    White MG, Shaw JA, Taylor R (2016) Type 2 diabetes: the pathologic basis of reversible beta-cell dysfunction. Diabetes Care 39(11):2080–2088. https://doi.org/10.2337/dc16-0619

    CAS  Article  PubMed  Google Scholar 

  27. 27.

    Pieralice S, Pozzilli P (2018) Latent autoimmune diabetes in adults: a review on clinical implications and management. Diabetes Metab J 42(6):451–464. https://doi.org/10.4093/dmj.2018.0190

    Article  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Foley JE, Bunck MC, Moller-Goede DL et al (2011) Beta cell function following 1 year vildagliptin or placebo treatment and after 12 week washout in drug-naive patients with type 2 diabetes and mild hyperglycaemia: a randomised controlled trial. Diabetologia 54(8):1985–1991. https://doi.org/10.1007/s00125-011-2167-8

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Chon S, Gautier JF (2016) An update on the effect of incretin-based therapies on beta-cell function and mass. Diabetes Metab J 40(2):99–114. https://doi.org/10.4093/dmj.2016.40.2.99

    Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Kaneto H, Obata A, Kimura T et al (2017) Beneficial effects of sodium-glucose cotransporter 2 inhibitors for preservation of pancreatic beta-cell function and reduction of insulin resistance. J Diabetes 9(3):219–225. https://doi.org/10.1111/1753-0407.12494

    CAS  Article  PubMed  Google Scholar 

  31. 31.

    Leighton E, Sainsbury CA, Jones GC (2017) A Practical review of C-peptide testing in diabetes. Diabetes Ther 8(3):475–487. https://doi.org/10.1007/s13300-017-0265-4

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Alves MT, Ortiz MMO, Dos Reis G et al (2019) The dual effect of C-peptide on cellular activation and atherosclerosis: protective or not? Diabetes Metab Res Rev 35(1):e3071. https://doi.org/10.1002/dmrr.3071

    CAS  Article  PubMed  Google Scholar 

  33. 33.

    Covic AM, Schelling JR, Constantiner M, Iyengar SK, Sedor JR (2000) Serum C-peptide concentrations poorly phenotype type 2 diabetic end-stage renal disease patients. Kidney Int 58(4):1742–1750. https://doi.org/10.1046/j.1523-1755.2000.00335.x

    CAS  Article  PubMed  Google Scholar 

  34. 34.

    Haffner SM, Miettinen H, Stern MP (1997) Are risk factors for conversion to NIDDM similar in high and low risk populations? Diabetologia 40(1):62–66. https://doi.org/10.1007/s001250050643

    CAS  Article  PubMed  Google Scholar 

Download references

Acknowledgements

We are grateful to the study participants and the nurse Milena Rosati who contributed to patients’ management.

Funding

This research did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector.

Author information

Affiliations

Authors

Contributions

PP SM DT RG designed the study. RG, DT, DM, AP, GD, SP, EF conducted research. DT and MW performed analyses. DT, SP, RG, MW, PP and SM wrote the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Pozzilli Paolo.

Ethics declarations

Conflicts of interests

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Ethical approval

The study has been approved by the University Campus Bio-Medico Ethics Committee # 54/20 OSS ComEt CBM.

Informed consent

All patients signed an informed consent.

Consent for publication

The manuscript received the consent to be published.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Managed by Antonio Secchi.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 418 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Dario, T., Riccardo, G., Silvia, P. et al. The utility of assessing C-peptide in patients with insulin-treated type 2 diabetes: a cross-sectional study. Acta Diabetol 58, 411–417 (2021). https://doi.org/10.1007/s00592-020-01634-1

Download citation

Keywords

  • C-peptide
  • Insulin treatment
  • Beta cell
  • Type 2 diabetes