Relation of Muscle Indices with Metabolic Parameters and C-Peptide in Type 2 Diabetes Mellitus

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1 ORIGINAL ARTICLE Relation of Muscle Indices with Metabolic Parameters and C-Peptide in Type 2 Diabetes Mellitus Sabah Tuzun 1, Can Oner 1, M. Resat Dabak 1, Halim Omer Kasikci 1 and Mehmet Sargin 2 ABSTRACT Objective: To assess the relation between bioimpedance measurements and metabolic parameters and C-peptide in patient with type 2 diabetes mellitus (DM). Study Design: Cross-sectional study. Place and Duration of Study: Kartal Dr Lutfi Kirdar Training and Research Hospital, Pendik Kaynarca Diabetes Center, Exercise and Metabolism Unit, between January and March Methodology: Patients with DM, aged less than 65 years, were assessed for bioimpedance analysis, fasting plasma glucose (FPG), HbA1c, C-peptide levels, triglyceride levels, LDL-cholesterol, and HDL-cholesterol levels. Skeletal muscle index, total muscle index, skeletal muscle percentage, and total muscle percentage were used for muscle-related analyses. Mann-Whitney U-test or independent t-test were used to compare differences between two independent groups. Pearson correlation test or Spearman correlation test were used to find out correlation between variables. Results: A total of 359 DM patients were enrolled in the study. Mean age was 51.6 ±8.0 years, and 278 (77.7%) of the participants were females. After adjusting age and gender variables, there was no relation between muscle-related measurements and FPG, triglyceride, LDL-cholesterol (p>0.05). However, there was muscle-related indexes (MRI) positively correlation with C-peptide and inversely associated with HDL-cholesterol (p<0.05). Conclusion: Muscle-related indices positively correlated with C-peptide, which showed endogenous insulin reserve. Key Words: Diabetes mellitus. Body compositions. Body fat distribution. Skeletal muscle. Visceral adipose tissue. INTRODUCTION Type 2 diabetes mellitus (DM), the prevalence of which is gradually increasing all over the world, is a disease that results from decreased insulin secretion due to β-cell dysfunction. 1 Visceral adipose tissue is a risk factor for DM, cardiovascular diseases and dyslipidemia. 1 Although some studies determined a relation between visceral adipose tissue and β-cell function and hyperglycemia, some other studies failed to determine such a relation. 2,3 In a study conducted in the subjects with metabolic syndrome, a relation was determined between body fat mass and HDL-cholesterol and triglyceride levels. 4 Decrease in muscle mass is frequently encountered in type 2 DM patients due to insulin resistance and high HbA1c level. 5,6 A study conducted in young adults determined a relation between muscle mass and triglyceride, HDL-cholesterol, and total cholesterol in non-obese subjects, whereas such a relation could not be determined in obese subjects. 7 1 Department of Family Medicine, Kartal Dr. Lutfi Kirdar Training and Research Hospital, Istanbul, Turkey. 2 Department of Family Medicine, Istanbul Medeniyet University Medical School, Istanbul, Turkey. Correspondence: Dr. Sabah Tuzun, MD, Clinic of Family Medicine, Kartal Dr. Lutfi Kirdar Training and Research Hospital, Istanbul, Turkey. sabahtuzun@gmail.com Received: January 10, 2017; Accepted: October 20, The present study aimed to determine the association between bioimpedance measurements and metabolic parameters and C-peptide in DM patients. METHODOLOGY The study group composed of DM patients under the age of 65 years, who visited Kartal Dr Lütfi Kirdar Training and Research Hospital, Pendik Kaynarca Diabetes Center, Exercise and Metabolism Unit, between January and March Patients with chronic renal insufficiency, chronic liver disease, type 1 diabetes mellitus, documented neuromuscular disease, and type 2 DM patients using insulin therapy were excluded in the study. In addition, patients at and over the age of 65 years were also not included in the study because of age-related increase in percentage of body fat and decrease in skeletal muscle mass and body fat. 1,9 The study was approved by the local Ethics Committee of Kartal Dr. Lütfi Kirdar Training and Research Hospital (Protocol No: /1009/487 Decision No:69). The data of the patients were gather from the patients records. All participants have been diagnosed with DM according to the American Diabetes Association 2015 criteria of fasting plasma glucose (FPG) 126 mg/dl or HbA1c 6.5%. 8 Bioimpedance measurements of all participants were done using TANITA-48M device, and metabolic parameters of the patients were evaluated on the same day after a 12-hour fasting period. Fasting plasma Journal of the College of Physicians and Surgeons Pakistan 2017, Vol. 27 (11):

2 Sabah Tuzun, Can Oner, M. Resat Dabak, Halim Omer Kasikci and Mehmet Sargin glucose (FPG) was measured by hexokinase method, and triglyceride and HDL-cholesterol levels were analyzed by spectrophotometric method. In addition, HbA1c was measured by chromatographic method in Bio-rad variant II analyzer, and C-peptide levels were measured by chemiluminescence method. LDL cholesterol level was calculated by Friedewald formula. Body weight, height, body fat mass, total muscle mass, fourappendicular total muscle mass, and of the patients were assessed during bioimpedance analysis. Using these measurements, body mass index (BMI) was calculated as the ratio of body weight in kilograms to the height in square meters (kg/m 2 ). The formulas of the muscle-related indexes and percentages are summarized in Table I. Table I: The formulas of the muscle-related indexes and percentages. Formula Skeletal muscle index (kg/m 2 ) Total appendicular muscle mass / height 2 Total muscle index (kg/m 2 ) Total muscle mass / height 2 Skeletal muscle percentage (%) (Total appendicular muscle mass / weight) x 100 Total muscle percentage (%) (Total muscle mass / weight) x 100 Gender, age, BMI, skeletal muscle index, total muscle index, skeletal muscle percentage, total muscle percentage and body fat mass were the independent variables; whereas FPG, HbA1c, C-peptide, triglyceride, LDL-cholesterol, and HDL-cholesterol were the dependent variables. Data were analyzed using SPSS 22.0 program and presented as percentages and frequencies, mean ± standard deviation, median with interquartile ranges (IQR). Mann-Whitney U-test or independent t-test was used to compare differences between two independent groups. Pearson correlation test or Spearman correlation test was used to find out correlation between variables. A p-value less than 0.05 was considered significant. RESULTS A total of 359 DM patients were enrolled in the study. Two hundred seventy eight (77.7%) were females, mean age was 51.6 ±8.0 years, and mean BMI was 38.5 ±7.4 kg/m2 of the patients. Thirty-four (9.5%) of the participants were of normal-weight, 189 (52.6%) were obese and 136 (37.9%) were morbid obese. In addition, HbA1c was <7% in 162 (45.5%) and triglyceride level was >150 mg/dl in 196 (54.4%) of the participants. Age, metabolic parameters and bioimpedance measurements among gender is summarized in Table II. After adjusting age and gender, no relation was determined between BMI, body fat mass and FPG, HbA1c, triglyceride and LDL-cholesterol levels of the participants (p>0.05). Nevertheless, negative correlation was found between BMI and level of HDL-cholesterol and significantly positive correlation was observed between BMI and level of C-peptide (p=0.003 and p<0.001, respectively). While no correlation was determined between body fat mass and HDLcholesterol, there was positive correlation with C-peptide (p=0.10 and p<0.001, respectively). The relation between muscle-related measurements and metabolic parameters after adjustment of age and gender variables is summarized in Table III. After adjusting age and gender, there was strongly significant association BMI with body fat mass (r=0.79 and p<0.001). Moreover, with regard to the musclerelated measurements, significant correlation was found between skeletal muscle index and BMI and body fat mass (r=0.79; p<0.001 and r=0.34; p<0.001, respectively). While there was negative relationship between skeletal muscle percentage and body fat mass, no significant correlation was determined with BMI (p<0.001 and p=0.45, respectively). The significant relationship was observed between total muscle index and BMI and body fat mass (r=0.72, p<0.001 and r=0.24, p<0.001, respectively). Nevertheless, negative correlation was determined between total muscle percentage and BMI and body fat mass (p<0.001 and p<0.001, respectively). Table II: Age, metabolic parameters and bioimpedance measurements among genders (n=359). Male Female n (%) Mean ± SD n (%) Mean ±SD p* Age (year) 80 (22.3) 50.6 ± (77.4) 51.9 ± Fasting plasma glucose (mg/dl) 77 (21.7) ± (77.4) ± HbA1c (%) 79 (22.3) 7.8 ± (76.0) 7.4 ± LDL-cholesterol (mg/dl) 77 (21.7) ± (74.0) ± HDL-cholesterol (mg/dl) 78 (22.1) 40.2 ± (76.0) 46.4 ±9.9 <0.001 BMI (kg/m 2 ) 80 (22.4) 35.0 ± (77.0) 39.5 ±7.6 <0.001 Skeletal muscle index (kg/m 2 ) 60 (16.7) 10.6 ± (77.0) 10.2 ± Skeletal muscle percentage (%) 60 (16.7) 31.3 ± (77.0) 25.8 ±3.3 <0.001 Total muscle index (kg/m 2 ) 80 (22.4) 22.2 ± (77.0) 21.1 ± Total muscle percentage (%) 80 (22.4) 64.3 ± (77.0) 53.6 ±6.7 <0.001 Body fat mass (kg) 79 (22.3) 32.9 ± (75.0) 41.4 ±10.4 <0.001 n (%) Median [IQR] n (%) Median [IQR] p** C-peptide (ng/ml) 72 (20.0) 3.12 (1.88) 266 (74.0) 2.80 (1.50) 0.20 Triglyceride (mg/dl) 79 (22.3) (121.0) 274 (76.0) (118.8) 0.71 *Some variables were missing. **Student's t-test was performed; **Mann-Whitney test was performed. 674 Journal of the College of Physicians and Surgeons Pakistan 2017, Vol. 27 (11):

3 Relation of muscle indices with metabolic parameters and C-peptide in type 2 diabetes mellitus Table III: Relation between muscle-related measurements and metabolic parameters after adjustment of age and gender variables. Skeletal muscle index Skeletal muscle Total muscle index Total muscle (kg/m 2 ) percentage (%) (kg/m 2 ) percentage (%) FPG (mg/dl) r* p HbA1c (%) r* p C-peptide (ng/ml) r** p < < Triglyceride (mg/dl) r** p LDL-cholesterol (mg/dl) r* p HDL-cholesterol (mg/dl) r* p *Pearson correlation test was performed; **Spearman correlation test was performed. DISCUSSION Viseral adipose tissue plays an important role in the development of diabetes as a result of beta-cell dysfunction. 1,10 Moreover, sarcopenia as well, which is defined as progressive loss of skeletal muscle mass, may have an effect on blood glucose regulation and lipid profile. 1 Studies on elder people determined that impairment of the balance between skeletal muscle mass and fat mass without any change in BMI might play a role in metabolic syndrome, cardiovascular diseases and mortality The present study aimed to assess the relation of bioimpedance measurements with metabolic parameters and C-peptide levels in DM patients. Decrease in muscle mass, which is one of the critical target organs for insulin, may result in decreased insulin sensitivity and impaired glucose regulation. 14 A study determined no relation between skeletal muscle percentage and FPG and HbA1c in type 2 DM patients, whereas other studies determined both positive and negative correlations between skeletal muscle index and FPG. 1,11,15 In another study, significant relation was found between HbA1c and skeletal muscle percentage. 5 Nevertheless, there are studies indicating that sarcopenia may increase the risk of insulin resistance and that insulin resistance might be reduced by increasing the muscle mass. 1,9,16 Earlier studies determined negative correlation between skeletal muscle percentage and C-peptide and HOMA-IR levels in middle-aged patients with type 2 DM. 1,15 Nevertheless, another study found positive correlation between HOMA-IR and skeletal muscle index in elder people after adjusting age and gender variables. 17 In the present study, while there was no relation between muscle-related measurements and FPG, a relation was determined between HbA1c and only total muscle mass. In addition, positive correlation was observed between C-peptide and skeletal muscle index and total muscle index. These results might have occurred due to the fact that participants of other studies were selected among healthy young people or old people and BMI was lower as compared to the present study. Moreover, the lower mean HbA1c values and better glycemic control in the present study might have led to these outcomes. In a study conducted in elder population, a negative correlation was determined between skeletal muscle index and HDL-cholesterol in males; whereas no relation was found in females, and there was also no relation between skeletal muscle percentage and HDLcholesterol in either gender. 17 In another study conducted in elder people, significantly lower HDLcholesterol levels were demonstrated in those with versus without sarcopenia, and similar negative correlation was determined also between skeletal muscle index and HDL-cholesterol. 15 Some studies found positive correlation between skeletal muscle index and triglyceride and LDL-cholesterol but negative correlation with HDL. 11,18,19 Moreover, while a relation was found between skeletal muscle percentage and triglyceride, similar relation could not be found with LDLcholesterol. 11,15 In a cross-sectional study, conducted in elder people, there was a relation between skeletal muscle mass index and triglyceride in males but not in females. 17 The same study determined no relation between skeletal muscle percentage and triglyceride in either gender. 17 A study conducted in young people determined elevated triglyceride levels in the non-obese subjects with low skeletal muscle percentage in both genders, whereas similarly significant relation could not Journal of the College of Physicians and Surgeons Pakistan 2017, Vol. 27 (11):

4 Sabah Tuzun, Can Oner, M. Resat Dabak, Halim Omer Kasikci and Mehmet Sargin be demonstrated in obese subjects. 7 In the present study, no relation was found between triglyceride, LDLcholesterol and muscle-related measurements. This might have resulted from lower mean age and higher BMI of the participants as compared to the other studies. Adipocytes are important predisposing factors for insulin resistance associated with β-cell dysfunction, and C-peptide is a good indicator of β-cell function. 20 Studies found positive relation between BMI and FPG and, similar with the present study, elevated baseline C-peptide levels in diabetic obese subjects. 15,18-23 While earlier studies found no relation between BMI and LDL-cholesterol but with HDL-cholesterol, which is similar to the present study. 15,18,19 One of the limitations of the present study is the fact that bioimpedance analysis is a moderate method in terms of sensitivity and susceptibility determining elevated muscle mass together with elevated fat mass in obese subjects. 24 For this reason, using rather the methods with higher sensitivity and specificity than bioimpedance analysis may be more beneficial in evaluating muscle mass in obese subjects. 24 The other limitation is the lower number of male subjects, which makes the assessment of differences between genders difficult. CONCLUSION The outcomes unveiled the relation between C-peptide and skeletal muscle index, total muscle index, and body fat mass. In addition, it was determined that there is a relation between HDL-cholesterol and skeletal muscle index, skeletal muscle percentage and total muscle index. REFERENCES 1. Shishikura K, Tanimoto K, Sakai S, Tanimoto Y, Terasaki J, Hanafusa T. Association between skeletal muscle mass and insülin secretion in patient with type 2 diabetes mellitus. Endocr J 2014; 61: Gletsu-Miller N, Kahn HS, Gasevic D, Liang Z, Frediani JK, Torres WE, et al. Sagittal abdominal diameter and visceral adiposity: Correlates of beta-cell function and dysglycemia in severely obese women. Obes Surg 2013; 23: Wagenknecht LE, Langefeld CD, Scherzinger AL, Norris JM, Haffner SM, Saad MF, et al. Insulin sensitivity, insülin secretion, and abdominal fat. The insülin resistance atherosclerois study (IRAS) family study. 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