Muscle Strength is a Marker of Insulin Resistance in Patients with Type 2 Diabetes: A Pilot Study

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1 ORIGINAL Muscle Strength is a Marker of Insulin Resistance in Patients with Type 2 Diabetes: A Pilot Study TAKUO NOMURA, YUKIO IKEDA*, SATOSHI NAKAO**, KENICHI ITO, KENJI ISHIDA**, TADASHI SUEHIRO* AND KOZO HASHIMOTO* Department of Physical Therapy, School of Comprehensive Rehabilitation, Osaka Prefecture University, Japan, *Department of Endocrinology, Metabolism and Nephrology, Kochi Medical School, Kochi University, Japan, **Department of Physical Medicine and Rehabilitation, Kochi Medical School, Kochi University, Japan Received April 4, 2007; Accepted August 7, 2007; Released online September 25, 2007 Correspondence to: Yukio Ikeda, M.D., Ph.D., Department of Endocrinology, Metabolism and Nephrology, Kochi Medical School, Kochi University, Kohasu, Oko-cho, Nankoku, Kochi , Japan Abstract. To examine the effect of muscle strength on insulin resistance, we investigated the association between quantitative lower-extremity muscle strength and insulin resistance index as evaluated by homeostasis model assessment (HOMA-IR) in patients with type 2 diabetes (20 men and 20 women, mean age ± SD: 53.3 ± 12.7 years). By simple linear regression analyses, the knee extension force normalized for body weight (%KEF) was found to be significantly correlated with HOMA-IR in both male (r = 0.510, P < 0.05) and female patients (r = 0.462, P < 0.05). Stepwise regression analysis also showed that %KEF was an independent determinant of HOMA-IR (β = 0.331, F = 5.400, P <0.005), as was BMI (β = 0.409, F = 8.260, P <0.05). Our data suggest that lower-extremity muscle strength is independently associated with insulin resistance, which seems to be consistent with previous reports that resistance training improves glycemic control in type 2 diabetic patients. Further studies based on a larger study population will be required to confirm this possibility. Key words: Muscle strength, Insulin resistance, Type 2 diabetes, Knee extension force TYPE 2 diabetes is characterized by pancreatic β-cell defects and insulin resistance of target tissues, such as skeletal muscle, adipose tissue and liver [1]. Skeletal muscle tissue is responsible for up to 40% of the total body weight and is a major site of insulin-mediated glucose uptake, which accounts for approximately 75% of whole body insulin-stimulated glucose uptake. Although muscle strength is closely related to muscle mass [2-4], it is also affected by muscle composition/quality such as fat accumulation in the muscle [5,6]. Furthermore, muscle strength but not muscle mass is independently associated with physical performance [7] and mortality [8], suggesting that muscle strength may represent comprehensive muscle ability. Recently, it has been reported that handgrip muscle strength is significantly associated with fasting insulin level or insulin resistance evaluated by homeostasis model assessment (HOMA-IR) in non-diabetic populations [9,10]. These observations are consistent with earlier reports that resistance training, as well as aerobic training, enhances insulin sensitivity and reduces blood glucose levels [11]. As well, in obese Japanese women, moderate intensity exercise that combines aerobic and resistance training has 1

2 been shown to increase adiponectin levels and decrease TNF-α levels [12]. However, the association between muscle strength and insulin resistance in diabetic patients has not previously been reported. Therefore, in this study, we examined the relationship between quantitative lower-extremity muscle strength and insulin resistance in patients with type 2 diabetes. Materials and Methods Subjects We recruited 40 patients with type 2 diabetes (20 men and 20 women, mean age ± SD: 53.3 ± 12.7 years) who were admitted to Kochi Medical School Hospital and attended the institutional Diabetes Education Program between January 2003 and June Diagnoses of type 2 diabetes were made in accord with the American Diabetes Association criteria [13]. Subjects receiving insulin therapy or antidiabetic drugs known to affect insulin sensitivity (thiazolidinediones and biguanides), and subjects with alcoholism, renal failure (serum creatinine > 1.5 mg/dl), liver disorders, cardiovascular disease, peripheral vascular disease, or symptomatic osteoarthropathy of lower-extremities were excluded from the study. Diabetic polyneuropathy was defined if the patient had at least one of the symptoms; pain, tingling, burning, or loss of sensation, and at least one of the objective signs on examination; decreased or absent achilles tendon reflex, or decreased vibratory sensation. According to these criteria, seven patients had polyneuropathy; however, there were no patients with severe symptomatic neuropathy who were unable to walk on their heels [14]. Twelve patients had regular exercise habits of more than 30 minutes exercise at least 2 days per week. All subjects gave informed consent to participate in this study. Measurements Maximal isometric muscle strength of knee extensors (quadriceps femoris) was evaluated using a dynamometer (Myoret, Kawasaki Heavy Industries Ltd., Tokyo, Japan). Measurements were performed in the sitting position with the knee and hip flexed to 90, and the dynamometer was applied at the ankle with stabilization at the thigh. Muscle strength was measured bilaterally and twice per side, and the average of the higher values of each leg was defined as the knee extension force (KEF). A ratio of KEF to body weight (%KEF) was calculated by dividing KEF (kg) by body weight (kg) and used in analyses. Venous blood was drawn after overnight fasting. Fasting plasma glucose (FPG), HbA 1c, serum insulin levels, total cholesterol (TC), HDL-cholesterol (HDL-C), and triglyceride (TG) concentrations were measured using standard techniques. LDL-cholesterol (LDL-C) was calculated using Friedewald s formula: LDL-C = TC TG/5 HDL-C. The degree of insulin resistance was estimated by HOMA, which was calculated by the following formula: HOMA-IR = fasting plasma glucose (mmol/l) serum insulin (µu/ml) / 22.5 [15]. Statistical analyses All data are presented as means ± SD. Comparisons of variables between two groups were performed using the Mann-Whitney U-test. Correlations between different parameters were determined using Pearson product-moment correlation coefficients. Multiple regression analysis was conducted using a stepwise method with a software program on a personal computer (SPSS, version 11.5J; SPSS Inc., Chicago, IL, USA). Sex (coded as male = 1, female = 2), age, body mass index (BMI), duration of diabetes, HbA 1c, TG, LDL-C, HDL-C, HOMA-IR, diabetic polyneuropathy (coded as absent=0, existing=1), and regular exercise habits (coded as no=1, yes=2) were incorporated as 2

3 predictive variables for analysis of %KEF. Variables were considered as independent determinants if the F value was greater than 4.0. Statistical significance was defined as P <0.05. Results There were no significant differences between male and female patients for age, duration of diabetes, BMI, FPG, HbA 1c, TG, LDL-C, and HDL-C concentrations, insulin, or HOMA-IR. On the other hand, male patients showed significantly higher %KEF compared with female patients (Table 1). Although %KEF tended to be higher in patients with regular exercise habits compared to those without (65.3 ± 15.1 vs 54.3 ± 18.4%, respectively; P = 0.078), no difference was detected between patients with and without diabetic polyneuropathy (60.9 ± 19.2 vs 56.9 ± 18.0%, respectively). By simple linear regression analyses, no correlations were detected between %KEF and age, duration of diabetes, FPG, HbA 1c levels, TG, LDL-C, or HDL-C concentrations (Table 2). Although there was a significant correlation between %KEF and BMI in female patients, there was no such correlation detected in male patients. On the other hand, %KEF was inversely correlated with fasting insulin levels and HOMA-IR in both male and female patients (Fig.1). Stepwise multiple regression analysis showed that sex, age, HOMA-IR, and exercise habits were significant determinants of %KEF (Table 3). Another regression analysis in which HOMA-IR and %KEF were entered as dependent and independent variables, respectively (total R 2 = 0.385, P <0.0005), showed that %KEF was a significant determinant of HOMA-IR (β = 0.331, F = 5.400, P <0.005), as was BMI (β = 0.409, F = 8.260, P <0.05). Discussion We demonstrated that %KEF was significantly correlated with HOMA-IR in a small cohort of type 2 diabetic patients. Multiple regression analysis showed that HOMA-IR was significantly associated with %KEF, as were age, sex, and exercise habits. Another regression analysis for HOMA-IR confirmed that %KEF was an independent determinant of HOMA-IR. Lazarus et al. [9] and Abbatecola et al. [10] showed significant correlations of handgrip muscle strength to fasting insulin level and HOMA-IR, respectively. Although these results were obtained from large cohorts, subjects who had chronic medical conditions including diabetes were excluded from the study populations. To our knowledge, our study is the first report showing a significant association between quantitative muscle strength and insulin resistance in type 2 diabetic patients. Skeletal muscle, as well as the liver and adipose tissue, plays a key role in glucose disposal. Muscle strength depends largely on muscle mass [2-4], but it is also affected by muscle quality [5,6]. Lipid content in skeletal muscle is inversely correlated with insulin sensitivity not only in animal models but also in a human population [16]. Furthermore, it has been shown that higher plasma levels of cytokines interleukin-6 and TNF-α, both of which are proinflammatory and known to induce insulin resistance, are associated with lower muscle mass and strength in well-functioning elderly people [17]. Thus, muscle strength may represent comprehensive muscle ability and therefore low muscle strength could be a marker for impaired skeletal muscle glucose disposal that is closely associated with whole-body insulin resistance. On the other hand, in patients with type 2 diabetes, insulin resistance per se may lead to impairment of muscle strength and performance; since insulin, mainly by inhibiting muscle protein breakdown, plays a major role in regulating muscle protein metabolism. Furthermore, insulin also stimulates mitochondrial protein synthesis, and this stimulation is a crucial factor for the maintenance of mitochondria proteins and their functional activity [18]. Indeed, in type 2 diabetic patients with defective insulin action, a lack of effect of insulin treatment on muscle mitochondrial protein synthesis and cytochrome C 3

4 oxidase, a key enzyme for ATP production, has been reported [19]. These structural and functional changes in skeletal muscle caused by defective insulin action could be associated with muscle weakness and reduced endurance capacity, which in turn may aggravate insulin resistance. Aging influences muscle strength and insulin resistance that is characterized by reduced peripheral glucose utilization with preserved suppression of hepatic glucose production [20]. Although, among our diabetic patients, no significant correlation was detected between %KEF and age by simple linear regression analyses, multiple regression analysis clearly showed that age was an independent contributor to %KEF, as were HOMA-IR, sex, and exercise habits. An age-related decline in the synthesis rate of skeletal muscle myosin heavy chain, a key protein in the contractile apparatus, has been reported, and this could contribute to the muscle weakness [21]. In addition, both mitochondrial protein synthesis and muscle mitochondrial oxidative enzyme activities reduce with age [21]. These age-related changes in skeletal muscle that include reduced muscle mass/strength and mitochondrial dysfunction, may, in combination with reduced physical activity, decrease total energy expenditure and aggravate insulin resistance, It has been reported that muscle strength of extensors and flexors at the ankle are highly affected by diabetic polyneuropathy [22]. The same investigators also reported that the strength of knee flexors, but not of knee extensors, were significantly lower in patients with diabetic polyneuropathy than in those without. Therefore, among muscle groups of the lower-extremities, knee extensors may be the most suitable for evaluating the contribution of muscle strength to insulin resistance independent of polyneuropathy. Indeed, our present study in which patients with severe polyneuropathy were excluded showed no difference in %KEF between patients with and without polyneuropathy. Furthermore, the clinical significance of KEF normalized for body weight as a risk for loss of basic movement ability has been largely confirmed [23,24]; therefore, the measure of %KEF can with reasonable confidence be used to estimate both insulin resistance and functional performance at a specific time in diabetic patients. Our results that lower-extremity muscle strength is independently associated with insulin resistance estimated by HOMA seems to be consistent with previous reports that resistance training has beneficial effects on glucose metabolism in type 2 diabetic patients [11]. However, our association study is underpowered to present definitive conclusions because of the small number of study subjects. Additionally, since we recruited patients who attended the institutional Diabetes Education Program on admission, their metabolic controls were generally poor. It was reported that poor glycemic control is associated with poor muscle quality, defined as muscle strength per regional muscle mass in diabetic patients [25]. Therefore, we need to verify the accuracy of our results in a general diabetic population. We hope that further studies based on a larger diabetic outpatient population will help to confirm these results. References 1. DeFronzo RA, Bonadonna RC, Ferrannini E (1992) Pathogenesis of NIDDM. A balanced overview. Diabetes Care 15: Reed RL, Pearlmutter L, Yochum K, Meredith KE, Mooradian AD (1991) The relationship between muscle mass and muscle strength in the elderly. J Am Geriatr Soc 39: Metter EJ, Lynch N, Conwit R, Lindle R, Tobin J, Hurley B (1999) Muscle quality and age: cross-sectional and longitudinal comparisons. J Gerontol A Biol Sci Med Sci 54: B207-B Landers KA, Hunter GR, Wetzstein CJ, Bamman MM, Weinsier RL (2001) The interrelationship among muscle mass, strength, and the ability to perform physical tasks of daily living in younger and older women. J Gerontol A Biol Sci Med Sci 56: B443-B448. 4

5 5. Goodpaster BH, Carlson CL, Visser M, Kelley DE, Scherzinger A, Harris TB, Stamm E, Newman AB (2001) Attenuation of skeletal muscle and strength in the elderly: The Health ABC Study. J Appl Physiol 90: Visser M, Goodpaster BH, Kritchevsky SB, Newman AB, Nevitt M, Rubin SM, Simonsick EM, Harris TB (2005) Muscle mass, muscle strength, and muscle fat infiltration as predictors of incident mobility limitations in well-functioning older persons. J Gerontol A Biol Sci Med Sci 60: Visser M, Newman AB, Nevitt MC, Kritchevsky SB, Stamm EB, Goodpaster BH, Harris TB (2000) Reexamining the sarcopenia hypothesis. Muscle mass versus muscle strength. Health, Aging, and Body Composition Study Research Group. Ann N Y Acad Sci 904: Newman AB, Kupelian V, Visser M, Simonsick EM, Goodpaster BH, Kritchevsky SB, Tylavsky FA, Rubin SM, Harris TB (2006) Strength, but not muscle mass, is associated with mortality in the health, aging and body composition study cohort. J Gerontol A Biol Sci Med Sci 61: Lazarus R, Sparrow D, Weiss ST (1997) Handgrip strength and insulin levels: cross-sectional and prospective associations in the Normative Aging Study. Metabolism 46: Abbatecola AM, Ferrucci L, Ceda G, Russo CR, Lauretani F, Bandinelli S, Barbieri M, Valenti G, Paolisso G (2005) Insulin resistance and muscle strength in older persons. J Gerontol A Biol Sci Med Sci 60: Eves ND, Plotnikoff RC (2006) Resistance training and type 2 diabetes. Considerations for implementation at the population level. Diabetes Care 29: Kondo T, Kobayashi I, Murakami M (2006) Effect of exercise on circulating adipokine levels in obese young women. Endocr J 53: The 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: Dyck PJ, Karnes JL, O'Brien PC, Litchy WJ, Low PA, Melton LJ 3rd. (1992) The Rochester Diabetic Neuropathy Study: reassessment of tests and criteria for diagnosis and staged severity. Neurology 42: Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC (1985) Homeostasis model assessment: insulin resistance and β cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28: Pan DA, Lillioja S, Kriketos AD, Milner MR, Baur LA, Bogardus C, Jenkins AB, Storlien LH (1997) Skeletal muscle triglyceride levels are inversely related to insulin action. Diabetes 46: Visser M, Pahor M, Taaffe DR, Goodpaster BH, Simonsick EM, Newman AB, Nevitt M, Harris TB (2002) Relationship of interleukin-6 and tumor necrosis factor-α with muscle mass and muscle strength in elderly men and women: the Health ABC Study. J Gerontol Med Sci 57A: M Guillet C, Boirie Y (2005) Insulin resitance: a contributing factor to age-related muscle mass loss? Diabetes Metab 31: 5S20-5S Halvatsiotis P, Short KR, Bigelow M, Nair KS (2002) Synthesis rate of muscle proteins, muscle functions, and amino acid kinetics in type 2 diabetes. Diabetes 51: DeFronzo RA (1979) Glucose intolerance and aging: evidence for tissue insensitivity to insulin. Diabetes 28: Nair KS (2005) Aging muscle. Am J Clin Nutr 81: Andersen H, Nielsen S, Mogensen CE, Jakobsen J (2004) Muscle strength in type 2 diabetes. Diabetes 53: Ploutz-Snyder LL, Manini T, Ploutz-Snyder RJ, Wolf DA (2002) Functionally relevant thresholds of quadriceps femoris strength. J Gerontol A Biol Sci Med Sci 57: B Eriksrud O, Bohannon RW (2003) Relationship of knee extension force to independence in sit-to-stand performance in patients receiving acute rehabilitation. Phys Ther 83:

6 25. Park SW, Goodpaster BH, Strotmeyer ES, De Rekeneire N, Harris TB, Schwartz AV, Tylavsky FA, Newman AB (2006) Decreased muscle strength and quality in older adults with type 2 diabetes. The Health, Aging, and Body Composition Study. Diabetes 55:

7 Table 1. Clinical characteristics of study subjects Variables Male Female P n Age (years) 53 ± ± 12 N.S. Duration of diabetes (years) 6.4 ± ± 6.7 N.S. Body mass index (kg/m 2 ) 25.5 ± ± 4.9 N.S. Diabetes treatment at study Diet/oral hypoglycemic agents (n) 3/17 5/15 N.S. Fasting plasma glucose (mg/dl) 144 ± ± 49 N.S. HbA 1C (%) 8.9 ± ± 1.6 N.S. LDL-cholesterol (mg/dl) 116 ± ± 35 N.S. HDL-cholesterol (mg/dl) 40 ± ± 16 N.S. Triglyceride (mg/dl) 138 ± ± 105 N.S. Insulin (µu/ml) 4.4 ± ± 2.9 N.S. HOMA-IR 1.6 ± ± 1.4 N.S. %KEF (%) 67 ± ± Data are presented as number or mean ± SD. Statistical differences between males and females were tested using the Mann-Whitney U-test or chi-square test. N.S.: not significant. 7

8 Table 2. Simple linear regression analysis for %KEF in diabetic patients Variables Male (n = 20) Female (n = 20) Age Duration of diabetes Body mass index ** Fasting plasma glucose HbA 1C LDL-cholesterol HDL-cholesterol Triglyceride Insulin ** * HOMA-IR ** ** Single linear univariate correlations were evaluated by Pearson s correlation coefficient. Correlation coefficients (r) are indicated. *P < 0.1, **P <

9 Table 3. Stepwise multiple regression analysis for %KEF in diabetic patients Variables β F P HOMA-IR <0.005 Age <0.005 Sex <0.005 Exercise habits <0.05 HDL-cholesterol N.S. HbA 1C N.S. Body mass index N.S. Diabetes duration N.S. Fasting plasma glucose N.S. LDL-cholesterol N.S. Triglyceride N.S. Diabetic polyneuropathy N.S. Total R 2 =0.559, P< (n=40) A stepwise regression analysis was performed. The F value for the inclusion and exclusion of variables was set at 4.0 at each step. Sex: men = 1, women = 2. Exercise habits: no = 1, yes = 2. Diabetic polyneuropathy: absent = 1, existing = 2. β: Partial regression coefficient. 9

10 Males Females Fasting serum insulin [µu/ml] n=20 r = P = n=20 r = P = HOMA-IR n=20 r = P = n=20 r= P = % KEF % KEF Fig. 1. Correlations between %KEF and fasting serum insulin levels or HOMA-IR in type 2 diabetic patients %KEF values and fasting serum insulin levels or HOMA-IR score in male (n = 20) and female (n = 20) patients are plotted. Correlation coefficients (r) and P values are indicated. 10