For years, there has been discussions concerning Low Carbohydrate Diet (LCD) and Calorie Restriction (CR). Recent reports have showed efficacy of LCD such as randomized controlled trials, systematic review and meta-analyses [1-3].
Historically, Atkins and Bernstein originally have started LCD in western countries [4,5]. Consecutively, clinical predominance of LCD have been shown by investigators [6-9]. Furthermore, LCD has been applied widely to several diseases and impaired states, such as metabolic syndrome (Met-S), obesity, nonalcoholic fatty liver disease (NAFLD), cardiovascular disease, and so on [10-12]
On contrast, in Japan, the author have firstly introduced and reported LCD for T2DM in Japan and developed LCD in lots of opportunities [13,14]. Subsequently, we reported clinical studies concerning LCD with pathophysiological aspects [15-18].
In current study, we investigated urinary C-Peptide immunoreactivity (u-CPR) excretion in patients with Type 2 Diabetes mellitus (T2DM). Simultaneously, we measured the average glucose and Morbus (M) value, and studied the detail correlation among these biomarkers.
Subjects and Methods
In current study, the subjects included 84 patients with T2DM, which were 33 males and 51 females. They are 28-84 years old (yo) with 60.9 ± 10.9 (mean +/- SD) yo. in average, 63 yo in the median value.
Subjects were enrolled from the in-patients of the educational admission for further evaluation and treatment of T2DM. The protocol of diet therapy were as follows:
1) CR diet was provided on day 1 and 2, which had 60% carbohydrates, 25% lipids and 15% protein with 1400 kcal/day.
2) LCD was provided from 3 to 14 days, which had 12% carbohydrates, 64% lipids and 24% protein with 1400 kcal/day.
3) This LCD has been called super-LCD formula in our clinical research for LCD, which is one of the Very low-carbohydrate ketogenic diet (VLCKD) by the definitions of LCD [13-16].
Examinations included several kinds of glucose metabolism. The are 1) several basal biomarkers on admission, 2) daily profile of blood glucose 7 times a day on day 2 (CR) and day 4 (LCD), 3) u-CPR were measured on day 2 and day 4, 4) M value was calculated from blood glucose level.
Morbus (M) value
Data obtained from daily profile of blood glucose were calculated into Morbus (M) value. M value is the index which represents both blood sugar level and mean amplitude of glycemic excursions (MAGE) [19-22]. Regarding glucose variability, daily profiles of blood glucose has been measured 7 times a day, which data were calculated into average glucose and M value. M value has been proposed for researching average glucose and MAGE. This index has been calculated as a logarithmic transformation of the deviation of glycemia from an arbitrary assigned ideal glucose value. Clinically, ideal glucose level would be around 120 mg/dL, then M value uses 120 mg/dL for the standard level. Consequently, M value expresses both the average glucose value and the effect of glucose swings [19-22].
M value is calculated by the following formula: M = MBS + MW, where MW = (maximum blood glucose−minimum glucose)/20; MBS = the mean of MBSBS; MBSBS = individual M-value for each blood glucose value calculated as (absolute value of [10×log(blood glucose value/120)])3.
Concerning the interpretation of M value, the standard range would be <180, borderline 180-320 and abnormal >320. Adequate sampling times a day have been argued for detail and precise evaluation of glucose variability and MAGE. Similar results were found on 7 times or 20 times of sampling per day [19,22,23]. It also revealed similar results compared with the continuous glucose monitoring (CGM) [22,24].
In this study, obtained data was represented as the mean +/- standard deviation (SD) and also represented median, quartile of 25% and 75% in biomarkers. For statistical analyses, correlation coefficients were calculated using Pearson or Spearman test of the Microsoft Excel analytical tool, which is Four steps Excel Statistics 4th edition . A significance level of less than 5% was considered to be statistically significant.
This study was conducted in compliance with the ethical principles of the Declaration of Helsinki. It was also along with Japans Act on the Protection of Personal Information along with the Ministerial Ordinance on Good Clinical Practice (GCP) for Drug (Ordinance of Ministry of Health and Welfare No. 28 of March 27, 1997). Ethical committee meeting was held by physician, researchers, medical staff and legal expert. Informed consent was obtained from the subjects. The study was registered with UMIN #R000031211.
Subjects were classified into 4 groups according to M value. Data of M value in 4 groups were, 4–21, 23–66, 29–192, 200–728, respectively (Table 1). Each group has 21 subjects, and other results of biomarkers were shown in Table 1.
Fastingblood glucose and HbA1c value increased from group 1 to group 4 in order (Figure 1). Each median value was 114, 137, 163, 216 mg/dL, and 6.2, 8.0, 7.8, 9.2%, respectively. The average glucose on day 4 was decreased from that on day 2 in 4 groups (Figure 2). Average glucose in median from day 2 to day 4 in each group was 123 to 107 mg/dL, 164 to 130 mg/dL, 193 to 156 mg/dL, 277 to 201 mg/dL, respectively.
Figure 5: Correlation between blood glucose and HbA1c.Significant correlation was observed between u-CPR on day 2 (CR) and day 4 (LCD) (p<0.01), in which the regression curve showed y=0.75x + 4.5 (Figure 6a). There is no significant correlation of ratio for day 4 to day 2 between average glucose and u-CPR (Figure 6b)
When calculated on daily profile of blood glucose into M value, it decreased from day 2 to day 4 in group 2,3 and 4 (Figure 3). M value in median from day 2 to day 4 in each group was 6.3 to 9, 41 to 7, 108 to 16, 367 to 88, respectively.
U-CPR on day 2 and day 4 are shown in Figure 4. In each group, decreased value from day to day 4 was 88 to 58, 53 to 35, 65 to 52, 74 to 64, respectively.
There is significant
correlation between blood glucose in average on day 2 and day 4 (p<0.01)
(Figure 5a). There is significant correlation between blood glucose in average
and HbA1c (p<0.01) in which the regression curve showed y = 0.02 x + 4.2
Significant correlation was observed between u-CPR on day 2 (CR) and day 4 (LCD) (p<0.01), in which the regression curve showed y=0.75x + 4.5 (Figure 6a). There is no significant correlation of ratio for day 4 to day 2 between average glucose and u-CPR (Figure 6b).
There is significant correlation between M value on day 2 and day4 (p<0.01) (Figure 7a). There is no significant correlation of ratio of day 2 and 4 between M value and u-CPR (Figure 7b).
Recently, fundamental and clinical research of LCD have been developed and prevalent [26,27], and we have continued research for LCD with proposal for medical practice [28-30].
In this study, we examined changes in average glucose, M value, urinary CPR in 2 days after diet changed from CR to LCD. We also investigated the correlation among these biomarkers, and clarified efficacy of LCD for the improvement of the profile of blood glucose in short period.
M value has been useful marker that would evaluated elevated blood glucose and increased MAGE. In this diabetic research field, we have continued to study the detail of glucose variability using M value [18,30,31].
As for current study, we divided into 4 groups according to M value. Group 1 was mild, and group 4 was severe in degree of diabetes. In Groups 2, 3 and 4, mean glucose and M values clearly decreased from day 2 to 4. On contrast, group 1 includes mild diabetes or pre-diabetic subjects. In other words, it seems that blood glucose and HbA1c are close to normal people, and the insulin secretion ability is preserved proportionally.
In group 1, blood sugar in median decreased from 123 to 107 mg/dL, and u-CPR decreased remarkably from 88 to 55 mg/day. For meal protocols, CR for day 1, 2. and LCD for day 3,4 were provided. In comparison of day 2 and day 4, the carbohydrate ratio is 60% vs. 12%, the carbohydrate amount per day is 210 g vs. 42 g. This difference in carbohydrate intake possibly leads to lowering of blood glucose and lowering of CPR in urine, with mutual correlation.
Average glucose decreased in group 1 from day 2 to day 4, but the M value did not decrease. The reason would be that the M value is calculated with the absolute value of blood glucose away from 120 mg / dL, which is ideal blood glucose level.
Actually, several cases in group 1 showed almost normal range of blood glucose at day 2. These cases developed decreased blood glucose around 80-100 mg/L at day 4. That is why M value in group 1 did not decrease from day 2 to day 4 [32,33].
In the protocol of this study, diet therapy was changed from CR to LCD for T2DM. Among them, the main investigation were u-CPR measurements in 2 days apart, and it was possible to analyze the relationship with mean blood sugar and M value simultaneously. As a result, the reduction in carbohydrate intake decreased blood glucose level and glucose fluctuation, especially leading to a drastic decrease in M value.
In addition, insulin secretion was suppressed due to a decrease in blood glucose spike, leading to decreased u-CPR excretion which is an indicator of insulin secretion. From the above, it can be said that the series of pathophysiological pathway in diabetes has been improved in the short term. These results suggest that LCD would have remarkable efficacy for nutritional treatment of diabetes.
Significant correlation between blood glucose in average and HbA1c (p<0.01) was observed. Its regression curve would indicate that HbA1c (%) = 0.02 x AG (mg/dL) + 4.2. When x axis and y axis changes each other, the equation becomes AG = 25.3 x HbA1c – 12.2.
Well-known equation has been reported by Nathan et al. which was AG = 28.7 x HbA1c – 46.7 analyzed from 2700 samples . As a comparison, substitute HbA 1 c = 7, 8, 9% into our formula and Nathans formula. Then, the result is 165.1 vs 154.2 mg / dL, 190.2 vs 182.9 mg / dL, 215.5 vs 211.6 mg / dL, and both estimated values are near and compatible.
We measured average blood glucose 7 times a day. It is said that the difference from the measurement of 20 times in the past is small and that the reliability is actually high. The subjects in this research were 84 cases of type 2 diabetes, including cases where HbA1c was low. Several cases in group 1 may showed lower HbA1c and blood glucose may be a higher than that of normal subjects which has the same HbA1c level.
On the other hand, study by Nathan et al. included type 1 diabetes, type 2 diabetes and normal individuals. Therefore, in regions where HbA1c is low, blood sugar levels are expected to be lower because there are many samples of normal subjects. Actually, if we enter 6% as HbA1c level into both formulas of ours and Nathan, data would be 139.6 mg/dL vs 125.5 mg/dL.
U-CPR has been a simple and useful test in the diagnosis of diabetes . It has been said that u-CPR and serum CPR has been said to be highly correlated . Recently, measurement of u-CPR with creatinine would be recommended for more accurate result [37,38].
C-peptide is clinically simple, noninvasive and useful examination for diabetes. Its application would be spreading in various situation, such as outpatient, in-patients and postprandial measurements [39-41].
In this study, we reported the changes in average glucose, M value and urine CPR value after meal change from CR to LCD. Associated with several correlation among them, and our results would become basic data for pathophysiological analysis of glucose metabolism of future research.
The part of the content of this article was presented at the 90th Scientific Meeting of Japan Endocrine Society (JES) Annual Congress, Kyoto, 2017. The authors would like to thank the patients and staffs for their cooperation and support.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
1) van Wyk HJ, Davis RE, Davies JS. A critical review of low-carbohydrate diets in people with Type 2 diabetes (2016) Diabet Med 33: 148-157. https://doi.org/10.1111/dme.12964
2) Snorgaard O, Poulsen GM, Andersen HK, Astrup A. Systematic review and meta-analysis of dietary carbohydrate restriction in patients with type 2 diabetes (2017) BMJ Open Diabetes Res Care 5: e000354. http://dx.doi.org/10.1136/bmjdrc-2016-000354
3) Namazi N, Larijani B, Azadbakht L. Low-Carbohydrate-Diet Score and its Association with the Risk of Diabetes: A Systematic Review and Meta-Analysis of Cohort Studies (2017) Horm Metab Res 49: 565-571.
4) Atkins R. Dr. Atkins new diet revolution, Rev edn (1998) Avon books, New York, USA.
5) Bernstein RK. Dr. Bernsteins Diabetes solution: The Complete Guide to Achieving Normal Blood Sugars (2007) Little, Brown US, New York, USA.
6) Accurso A, Bernstein RK, Dahlqvist A, Draznin B, Feinman RD, Fine EJ et al. Dietary carbohydrate restriction in type 2 diabetes mellitus and metabolic syndrome: time for a critical appraisal (2008) Nutr Metab (Lond) 5: 9. https://doi.org/10.1186/1743-7075-5-9
7) Shai I, Schwarzfuchs D, Henkin Y, Shahar DR, Witkow S, et al. Weight loss with a low-carbohydrate, mediterranean, or low-fat diet (2008) N Engl J Med 359: 229-241.
8) Schwarzfuchs D, Golan R, Shai I. Four-year follow-up after two-year dietary interventions (2012) N Engl J Med 367: 1373-1374.
9) Atallah R, Filion KB, Wakil SM, Genest J, Joseph L, et al. Long-Term Effects of 4 Popular Diets on Weight Loss and Cardiovascular Risk Factors: A Systematic Review of Randomized Controlled Trials (2014) Circ Cardiovasc Qual Outcomes 7: 815-827. https://doi.org/10.1161/CIRCOUTCOMES.113.000723
10) Hashimoto Y, Fukuda T, Oyabu C, Tanaka M, Asano M, et al. Impact of low-carbohydrate diet on body composition: meta-analysis of randomized controlled studies (2016) Obes Rev 17: 499-509. https://doi.org/10.1111/obr.12405
11) Haghighatdoost F, Salehi-Abargouei A, Surkan PJ, Azadbakht L. The effects of low carbohydrate diets on liver function tests in nonalcoholic fatty liver disease: A systematic review and meta-analysis of clinical trials (2016) J Res Med Sci 21: 53. https://dx.doi.org/10.4103%2F1735-1995.187269
12) Tokuchi Y, Nakamura Y, Munekata Y, Tokuchi F. Low carbohydrate diet-based intervention for obstructive sleep apnea and primary hypothyroidism in an obese Japanese man (2016) Asia Pac Fam Med 15: 4. https://doi.org/10.1186/s12930-016-0029-8
13) Ebe K, Ebe Y, Yokota S, Matsumoto T, Hashimoto M, et al. Low Carbohydrate diet (LCD) treated for three cases as diabetic diet therapy (2004) Kyoto Medical Association Journal 51: 125-129.
14) Bando H, Nakamura T. Carbo-count therapy and low carbohydrate diet (LCD) (2008) The Journal of the Therapy 90: 3105-3111.
15) Bando H, Ebe K, Nakamura T, Bando M, Yonei Y. Low Carbohydrate Diet (LCD): Long and short-term effects and hyperketonemia (2016) Glycative Stress Research 3: 193-204.
16) Muneta T, Kawaguchi E, Nagai Y, Matsumoto M, Ebe K, et al. Ketone body elevation in placenta, umbilical cord, newborn and mother in normal delivery (2016) Glycative Stress Research 3: 133-140.
17) Bando H, Ebe K, Sakamoto K, Ogawa T, Bando M, et al. Remarkable Weight Reduction for Low Carbohydrate Diet (LCD): Case Report (2017) Diabetes Case Rep 2: 130.
18) Bando H, Ebe K, Muneta T, Bando M, Yonei Y. Effect of low carbohydrate diet on type 2 diabetic patients and usefulness of M-value (2017) diabetes Res Open J 3: 9-16.
19) Schlichtkrull J, Munck O, Jersild M. The M-value, an index of blood sugar control in diabetics (1965) Acta Med Scand 177: 95-102. https://doi.org/10.1111/j.0954-6820.1965.tb01810.x
20) Service FJ, Molnar GD, Rosevear JW, Ackerman E, Gatewood LC, et al. Mean amplitude of glycemic excursions, a measure of diabetic instability (1970) Diabetes 19: 644-655. https://doi.org/10.2337/diab.19.9.644
21) Moberg E, Kollind M, Lins PE, Adamson U. Estimation of blood-glucose variability in patients with insulin-dependent diabetes mellitus (1993) Scand J Clin Lab Invest 53: 507-514
22) Siegelaar SE, Holleman F, Hoekstra JBL Devries JH. Glucose Variability; Does It Matter? (2010) Endocrine Reviews 31: 171-182. https://doi.org/10.1210/er.2009-0021
23) Monnier L, Colette C. Glycemic Variability: Can We Bridge the Divide Between Controversies? (2011) Diabetes Care 34: 1058-1059. https://dx.doi.org/10.2337%2Fdc11-0071
24) McDonnell CM, Donath SM, Vidmar SI, Werther GA, Cameron FJ; A novel approach to continuous glucose analysis utilizing glycemic variation (2005) Diabetes Technol Ther 7: 253-263.
25) Yanai H. Four step excel statistics, 4th Edition (2015) Seiun-sha Publishing Co.Ltd, Tokyo, Japan.
26) Nakamura Y, Okuda N, Okamura T, Kadota A, Miyagawa N, et al. Low-carbohydrate diets and cardiovascular and total mortality in Japanese: a 29-year follow-up of NIPPON DATA80 (2014) Br J Nutr 112: 916-924. https://doi.org/10.1017/S0007114514001627
27) Feinman RD, Pogozelski WK, Astrup A, Bernstein RK, Fine EJ, et al. Dietary carbohydrate restriction as the first approach in diabetes management: Critical review and evidence base (2015) Nutrition 31: 1-13. https://doi.org/10.1016/j.nut.2014.06.011
28) Meng Y, Bai H, Wang S, Li Z, Wang Q, Chen L. Efficacy of low carbohydrate diet for type 2 diabetes mellitus management: A systematic review and meta-analysis of randomized controlled trials (2017) Diabetes Res Clin Pract 131: 124-131. https://doi.org/10.1016/j.diabres.2017.07.006
29) Bando H, Ebe K, Muneta T, Bando M, Yonei Y. Proposal for Insulinogenic Index (IGI)-Carbo70 as Experimental Evaluation for Diabetes (2017) J Clin Exp Endocrinol 1: 102.
30) Ebe K, Bando H, Yamamoto K, Bando M, Yonei Y. Daily carbohydrate intake correlates with HbA1c in low carbohydrate diet (LCD). (2018) J Diabetol 1: 4-9.
31) Bando H, Ebe K, Muneta T, Bando M, Yonei Y. Investigation of uric acid and cystatin C on low-carbohydrate diet (LCD) (2017) Diabetes Res Open J 3: 31-38.
32) Service FH. Glucose variability (2013) Diabetes 62: 1398-1404.
33) Baghurst P. Calculating the mean amplitude of glycemic excursion from continuous glucose monitoring data: an automated algorithm (2011) Diabetes Technol Ther 13: 296-302. https://doi.org/10.1089/dia.2010.0090
34) Nathan DM, Kuenen J, Borg R, Zheng H, Schoenfeld D, et al. A1c-Derived Average Glucose Study Group. Translating the A1C assay into estimated average glucose values (2008) Diabetes Care 31: 1473-1478. https://doi.org/10.2337/dc08-0545
35) Jones AG, Hattersley AT. The clinical utility of C-peptide measurement in the care of patients with diabetes. Diabet Med. 2013;30(7):803-17. https://doi.org/10.1111/dme.12159 .
36) Aoki Y. Variation of endogenous insulin secretion in association with treatment status: assessment by serum C-peptide and modified urinary C-peptide (1991) Diabetes Res Clin Pract.14: 165-173. https://doi.org/10.1016/0168-8227(91)90017-8
37) Bowman P, McDonald TJ, Shields BM, Knight BA, Hattersley AT. Validation of a single-sample urinary C-peptide creatinine ratio as a reproducible alternative to serum C-peptide in patients with Type 2 diabetes (2011) Diabet Med 29: 90-93. https://doi.org/10.1111/j.1464-5491.2011.03428.x
38) Besser RE, Ludvigsson J, Jones AG, McDonald TJ, Shields BM, et al. Urine C-peptide creatinine ratio is a noninvasive alternative to the mixed-meal tolerance test in children and adults with type 1 diabetes (2011) Diabetes Care 34: 607-609. https://doi.org/10.2337/dc10-2114
39) McDonald TJ, Perry MH. Detection of C-Peptide in Urine as a Measure of Ongoing Beta Cell Function (2016) Methods Mol Bio 1433: 93-102. https://doi.org/10.1007/7651_2016_330
40) Sonoda R, Tanaka K, Kikuchi T, Onishi Y, Takao T, Tahara T, et al. C-Peptide Level in Fasting Plasma and Pooled Urine Predicts HbA1c after Hospitalization in Patients with Type 2 Diabetes Mellitus (2016) PLoS One 11: e0147303. https://doi.org/10.1371/journal.pone.0147303
Saisho Y. Postprandial C-Peptide to Glucose Ratio as a Marker of β Cell Function: Implication for the Management of Type 2 Diabetes (2016) Int J Mol Sci 17: E744. https://doi.org/10.3390/ijms17050744
author: Hiroshi Bando, Tokushima University/Medical Research,
Nakashowa 1-61, Tokushima 770-0943 Japan Tel: +81-90-3187-2485, E-mail: firstname.lastname@example.org
Citation: Bando H, Ebe K, Muneta T, Bando M, Yonei Y. Urinary C-Peptide Excretion for Diabetic Treatment in Low Carbohydrate Diet (LCD) (2018) Journal of Obesity and Diabetes 1: 13-18
Urinary C-peptide (u-CPR), Low Carbohydrate Diet (LCD), Morbus value (M value), type 2 diabetes mellitus (T2DM), Average Glucose (AG)