Prediction of Diabetes Using Serum C-Peptide

Article information

Endocrinol Metab. 2016;31(2):275-276
Publication date (electronic) : 2016 June 22
doi : https://doi.org/10.3803/EnM.2016.31.2.275
Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
Corresponding author: Hye Seung Jung. Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul 03080, Korea. Tel: +82-2-2072-0240, Fax: +82-2-764-2199, junghs@snu.ac.kr

Type 2 diabetes is generally regarded as an irreversible disease, and considering its effects on complications, prevention of diabetes is very important. Fortunately, type 2 diabetes is a preventable disease [1], and therefore the prediction of diabetes in high risk persons is a key issue. Such a prediction would be based on several genetic and environmental factors as well as insulin secretory capacity [23], because if the insulin secretion is enough to compensate for other risk factors, diabetes would not develop [4].

In this issue of Endocrinology and Metabolism, Kim et al. [5] suggested that C-peptide would be more effective in the prediction of diabetes compared to insulin. Among 140 adults without diabetes at baseline, 20% became diabetic during a mean follow-up of 55 months, and among the baseline examinations, C-peptide increase by glucose loading—which the authors referred to as the "C-peptidogenic index"—was the most predictive and independent index for future diabetes. Most previous studies have used serum insulin for the estimation of insulin secretion in the prediction of diabetes [234]; however, according to this study by Kim et al. [5], C-peptide measurement would be superior, especially during oral glucose tolerance tests. In addition, there is a report that the C-peptide based index was more closely correlated than the insulin-based index with β-cell mass in humans [6].

These findings that C-peptide is more related with β-cell mass and function than insulin might be a result of C-peptide metabolism being less vulnerable than insulin and more reproducible with lower variations [78].

Although this study was performed as a retrospective design, it is worth paying attention to the results because of the increased prevalence of prediabetes worldwide. Further investigation in large cohort as a prospective design would be needed to establish more accurate tools for the prediction of diabetes.

Notes

CONFLICTS OF INTEREST: No potential conflict of interest relevant to this article was reported.

References

1. Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002;346:393–403. 11832527.
2. Defronzo RA, Tripathy D, Schwenke DC, Banerji M, Bray GA, Buchanan TA, et al. Prediction of diabetes based on baseline metabolic characteristics in individuals at high risk. Diabetes Care 2013;36:3607–3612. 24062330.
3. Abdul-Ghani MA, Williams K, DeFronzo RA, Stern M. What is the best predictor of future type 2 diabetes? Diabetes Care 2007;30:1544–1548. 17384342.
4. Lyssenko V, Almgren P, Anevski D, Perfekt R, Lahti K, Nissen M, et al. Predictors of and longitudinal changes in insulin sensitivity and secretion preceding onset of type 2 diabetes. Diabetes 2005;54:166–174. 15616025.
5. Kim JD, Kang SJ, Lee MK, Park SE, Rhee EJ, Park CY, et al. C-peptide-based index is more related to incident type 2 diabetes in non-diabetic subjects than insulin-based index. Endocrinol Metab 2016;31:320–327.
6. Meier JJ, Menge BA, Breuer TG, Muller CA, Tannapfel A, Uhl W, et al. Functional assessment of pancreatic beta-cell area in humans. Diabetes 2009;58:1595–1603. 19509022.
7. Van Cauter E, Mestrez F, Sturis J, Polonsky KS. Estimation of insulin secretion rates from C-peptide levels. Comparison of individual and standard kinetic parameters for C-peptide clearance. Diabetes 1992;41:368–377. 1551497.
8. Utzschneider KM, Prigeon RL, Tong J, Gerchman F, Carr DB, Zraika S, et al. Within-subject variability of measures of beta cell function derived from a 2 h OGTT: implications for research studies. Diabetologia 2007;50:2516–2525. 17928990.

Article information Continued