Insulin Resistance is Associated with ...

478 Article

Insulin Resistance is Associated with Microangiopathy in Type 1 Diabetic Patients Treated with Intensive Insulin Therapy from the Onset of Disease

Authors

A. Uruska1, A. Araszkiewicz1, D. Zozulinska-Ziolkiewicz1, P. Uruski2, B. Wierusz-Wysocka1

Affiliations

1

Key words

Abstract ▼

received 29.12.2009 first decision 15.02.2010 accepted 24.02.2010 Bibliography DOI http://dx.doi.org/ 10.1055/s-0030-1249635 Published online: April 6, 2010 Exp Clin Endocrinol Diabetes 2010; 118: 478–484 © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart · New York ISSN 0947-7349 Correspondence Dr. A. Uruska Department of Internal Medicine and Diabetology Poznan University of Medical Sciences, Poland Raszeja Hospital Mickiewicza 2 60-834 Poznan Poland Tel.:/Fax: (0048) 61 8474579 [email protected]

Aim: The aim of the study was to evaluate the relationship between indirect parameters of insulin resistance (IR) and risk of microangiopathy in patients with type 1 diabetes (DM1), treated from the initial diagnosis with intensive insulin therapy. Methods: The study group consisted of 81 patients with DM1 (51 men, 30 women), aged 34 ± 6.4, and who were observed for 10 ± 1.5 years. Indirect parameters of IR were evaluated: waist circumference, waist to hip ratio (WHR), body mass index (BMI), daily insulin requirement, gain of weight from the beginning of the disease, lipid profile, estimated glucose disposal rate (eGDR), inflammatory markers and features of metabolic syndrome. Patients were divided into two groups depending on the presence or absence of microangiopathy. Results: In the group with microangiopathy (n = 36) in comparison with patients without com-

Introduction ▼ Despite great progress in the management of diabetes, its chronic complications still remain the principal cause of morbidity and mortality in patients with type 1 diabetes (DM1). The Diabetes Control and Complications Trial (DCCT) revealed that hyperglycaemia plays a crucial role in the development and progression of late diabetic complications (The Diabetes Control and Complications Trial Research Group, 1993). Other parameters which are considered as risk factors for diabetic angiopathy are hypertension, smoking dyslipidaemia (Koivisto et al., 1996) and lack of physical activity (Krcma et al., 2009). However, these factors do not fully explain the pathogenesis of micro- and macroangiopathy. Thus new, non-traditional, risk factors influenc-

plications (n = 45) we found: larger waist circumference (88.9 ± 11.7 vs. 83.7 ± 10.2 cm; p = 0.036), higher weight before diabetes (77.3 ± 17.0 vs. 67.0 ± 12.5 kg; p = 0.008), higher WHR (0.90 ± 0.08 vs. 0.86 ± 0.08; p = 0.048), higher level of triglycerides (1.3 ± 0.8 vs. 0.9 ± 0.3 mmol/l; p = 0.002) and lower eGDR (7.2 ± 2.4 vs. 8.8 ± 1.9 mg/kg/min; p = 0.0019). In patients with microangiopathy, features of metabolic syndrome were found more often (12 (33.3 %) vs. 4 (8.9 %); p = 0.006). A significant relationship, adjusted for sex, age and duration of diabetes, between eGDR and microangiopathy was revealed (OR 0.65 (95 %CI 0.49–0.86); p = 0.0037). Conclusion: The results show that in patients with DM1, treated from the initial diagnosis with intensive insulin therapy, there is an independent relationship between IR and the diabetic microangiopathy.

ing the development of diabetic complications in type 1 diabetic patients are still being investigated. Insulin resistance is one of the clinical factors which is evaluated in relations to the pathogenesis of vascular complications of diabetes. Initially, decreased insulin sensitivity was linked only with obesity and type 2 diabetes (Lillioja et al., 1993; Alberti et al., 2005; Reaven, 1988; Sainaghi et al., 2008). However, clinical features of insulin resistance are also present in many patients with DM1. Coexistence of this condition with diabetes with a proven autoimmune background is called “double diabetes” (Kilpatrick et al., 2007). Recently, it has been suggested that insulin resistance increases the risk of late diabetic complications in DM1 (Thorn et al., 2005; Orchard et al., 2003; Orchard et al., 2002). However, the groups

Uruska A et al. Insulin Resistance is Associated with Microangiopathy … Exp Clin Endocrinol Diabetes 2010; 118: 478–484

Downloaded by: Thieme Verlagsgruppe. Copyrighted material.

▶ diabetes mellitus type 1 ● ▶ insulin resistance ● ▶ risk factor ● ▶ microangiopathy ● ▶ glucose disposal rate ●

Department of Internal Medicine and Diabetology, Poznan University of Medical Sciences, Raszeja Hospital, Mickiewicza, Poznan, Poland 2 Department of Hypertensiology, Angiology and Internal Medicine, Poznan University of Medical Sciences, Dluga, Poznan, Poland

Article 479

Patients and Methods ▼ Setting and sample The study was performed on 81 caucasian patients (51 men, 30 women), with type 1 diabetes, recruited into the Poznan Prospective Study, with a mean age of 34 ± 6.4 years, and treated with intensive insulin therapy from the onset of the disease. The group has been assessed once a year since 1997 (follow-up period 10 ± 1.5 years) in the Department of Internal Medicine and Diabetes, Poznan University of Medical Sciences [Araszkiewicz et al., 2005; Araszkiewicz et al., 2008]. The aim of this analysis was to examine the relationship between selected parameters of insulin resistance and the incidence of diabetic microangiopathic complications. The clinical characteristics of the whole study group are shown in Table 1. All the subjects were informed about the aim of the study and gave their written consent. The study was approved by the local Ethical Committee.

Five-day teaching program in intensive insulin therapy During their first hospitalization at diagnosis of diabetes all the patients attended a five-day structured training program in order to acquire the skills for multiple daily insulin injections including adapting short-acting insulin doses before their main meals in accordance with the Diabetes Treatment and Teaching Program (DTTP) (Müller et al, 1999). The course covered the following topics: the nature of diabetes, self-monitoring, types of insulin and their action, diet, carbohydrate counting, hypoglycaemia and hyperglycaemia, sports and exercise, late diabetic complications and self-adjustment of the insulin dose. The train-

Table 1 Clinical characteristics of all patients in the study [data are means ± SD or n ( %)]. sex M/F age [years] duration of diabetes [years] smoking n ( %) hypertension n ( %) family history regarding diabetes type 1 n ( %) family history regarding diabetes type 2 n ( %) weight [kg] weight before symptoms of diabetes [kg] weight gain from the beginning of diabetes [kg] BMI [kg/m2] waist circumference [cm] waist circumference – male[cm] waist circumference – female [cm] WHR WHR – male WHR – female daily insulin requirement [U/kg/d] eGDR [ml/kg/min] eGDR ≥ 7.5 n ( %) metabolic syndrome n ( %) systolic blood pressure [mmHg] diastolic blood pressure [mmHg] FPG [mmol/l] PPG [mmol/l] HbA1c [ %] HbA1c (mean from years 1997–2007) [ %] TCH [mmol/l] TG [mmol/l] LDL-cholesterol [mmol/l] HDL-cholesterol [mmol/l] ApoB [g/l] ApoA1 [g/l] hsCRP [mg/dl] ALT [U/l] AST [U/l] GGTP [U/l] creatinine [μmol/l] GFR (MDRD) [ml/min/1.73 m2]

51/30 34.5 ± 6.4 10.0 ± 1.6 24 (29) 19 (23.5) 19 (23.5) 25 (31) 76.2 ± 15.1 71.6 ± 15.5 13.4 ± 10.5 24.7 ± 3.8 86.0 ± 11.1 90.4 ± 8.9 78.4 ± 10.6 0.88 ± 0.08 0.92 ± 0.06 0.81 ± 0.08 0.67 ± 0.19 8.1 ± 2.3 52 (64) 16 (20) 117.8 ± 15.2 74.5 ± 11.5 9.0 ± 2.8 8.9 ± 2.1 8.3 ± 1.6 8.2 ± 1.4 4.7 ± 0.1 1.1 ± 0.6 2.8 ± 0.8 1.7 ± 0.4 0.83 ± 0.22 1.69 ± 0.26 1.86 ± 2.12 19.5 ± 8.6 19.5 ± 5.9 26.2 ± 23.6 69.8 ± 11.5 111.2 ± 23.3

BMI – body mass index; WHR – waist to hip ratio; eGDR – estimated glucose disposal rate; FPG – fasting plasma glucose; PPG – postprandial plasma glucose; TCH – total cholesterol; TG - triglycerides; low density lipoproteins (LDL) cholesterol; high density lipoproteins (HDL) cholesterol, ApoB – apolipoprotein B; ApoA1 – apolipoprotein A1; hsCRP – C-reactive protein; ALT – alanine aminotransferase; AST – aspartate aminotransferase; GGTP – gamma-glutamyl transferase; GFR – glomerular filtration rate

ing course was conducted by a specially trained nurse educator and a diabetologist, psychologist and dietician. Instruction was delivered in a group setting with a maximum of 10 patients. Additionally, individual support was given in all cases. The objectives were to enable participants to improve their glycaemic control, reduce the risk of hypoglycaemia, enable dietary and lifestyle freedom, and reduce and delay the risk of late diabetic complications. All patients were treated with intensive insulin therapy from the onset of the disease. In year 2007 58 (71.6 %) patients used short acting analogues and 23 (28.4 %) regular insulin as pre-meal insulin and 16 (19.8 %) patients used long acting analogues and 65 (80.2 %) NPH insulin as basal insulin. One patient used insulin pump.



studied included patients with different disease durations at baseline and treated with various models of insulin therapy. Thus, the knowledge concerning the association between decreased insulin sensitivity and diabetic angiopathy is still limited. Additionally, there is continuous discussion concerning the methods of insulin resistance assessment in DM1. The gold standard for determining insulin sensitivity in this group of patients is the euglycaemic insulin clamp technique of DeFronzo (DeFronzo et al., 1979). However, this technique is too complicated and expensive for clinical practice. On the other hand, homeostasis model assessment (HOMA) is not applicable to this group of patients because it was created on the basis of a population with type 2 diabetes. Indirect parameters of insulin resistance such as anthropometric data, features of the metabolic syndrome or inflammatory markers, correlated with clamp technique results, have also been suggested (Stern et al., 2005; McLaughlin et al., 2003). A few studies have used the metabolic syndrome definition itself in DM1 patients (Kilpatrick et al., 2007; Thorn et al., 2005). More recently, a validated method for estimating the glucose disposal rate (eGDR, estimated glucose disposal rate) has been developed. This calculates a score, based on the patients’ clinical features, which shows a close relationship to insulin resistance when formally measured by the clamp method and is presented as a mathematical equation (Williams et al., 2000). The aim of this study was to assess the relationship between selected, indirect parameters of insulin resistance and microangiopathy in patients with DM1 treated with intensive insulin therapy from the onset of the disease.

480 Article

All the participants completed a standarized questionnaire including details of sex, age, medical history, duration of diabetes, treatment, smoking status, blood glucose self control, family history regarding diabetes, weight at birth and weight before symptoms of diabetes and weight at diagnosis. All the patients underwent a complete physical examination with anthropometric measurements and blood pressure check. Blood pressure was measured twice by the Korotkoff method in the sitting position, after 10 min rest, using a mercury manometer. We diagnosed arterial hypertension if the mean blood pressure was more than 140/90 mmHg, or the patient had had arterial hypertension diagnosed previously and had received appropriate treatment. Blood samples were collected, in a fasting state after a period of rest, with minimal occlusion of the vein using the S-Monovette blood collection system. Plasma glucose, serum total cholesterol (TCH), high density lipoproteins (HDL) cholesterol, low density lipoproteins (LDL) cholesterol, triglycerids (TG), apolipoprotein A1 (ApoA1) and apolipoprotein B (ApoB) levels, C-peptide and creatinine levels, liver function parameters aspartate aminotransferase (AST), alanine aminotransferase (ALT) and gammaglutamyl transferase (GGTP) levels were measured using standard methods. HbA1c (glycated hemoglobin) was measured using high-performance liquid chromatography (HPLC) with the Variant Hemoglobin A1c Program (Bio-Rad Laboratories, Hercules, CA, USA). Patients had their HbA1c assessed twice a year. The mean value of HbA1c over the 10 years was calculated as the mean value from the results in the years 1997–2007. We also assessed mean fasting, and mean 2-h postprandial glycaemia as the mean value from the three following measurements of fasting glycaemia and measurements of glycaemia 2 h after breakfast, lunch and dinner in the self-assessment profile. The glomerular filtartion rate (GFR) was calculated according to the Modification of Diet in Renal Disease Study Equation (MDRD) (Levey et al., 1999). The serum C-reactive protein (CRP) concentration was assessed by highly sensitive microparticle enzyme immunoassay. Test sensitivity was 0.03 mg/l.

Microangiopathy outcomes at follow-up Screening for diabetic retinopathy was performed by two experienced ophthalmologists using direct ophthalmoscopy through dilated pupils followed, if necessary, by fluorescent angiography. Retinal photographs were taken of each eye using a Fundus Camera VISUSCAM (Zeiss, Germany). After mydriasis with 1 % Tropicamide, two 45 ° photographs, macular and nasal, were taken of each eye. Retinopathy was classified according to the American Academy of Ophthalmology scale as: mild non-proliferative, moderate non-proliferative, severe non-proliferative or proliferative diabetic retinopathy. Diabetic nephropathy was detected at the stage of albuminuria. Assessment of albuminuria was performed by measurement of urinary albumin excretion over 24 h. Albuminuria was defined as an urinary albumin excretion rate between 30 and 300 mg/ 24 h in two of three samples collected over 3 months. Diabetic nephropathy was defined as the presence of albuminuria in connection with diabetes of over 10 years duration, or with diagnosed diabetic retinopathy (Nelson et al., 2007). The neuropathy assessment was performed using pressure sensation (10 g monofilament perception), vibration perception (128 Hz tuning fork or neurotesiometer), temperature sensation and ankle reflexes tests. Diabetic neuropathy was diagnosed in

patients with two or more of the following four components: the presence of symptoms of neuropathy, the absence of ankle tendon reflexes, abnormal scores for pressure and/or of vibration perception.

Insulin resistance parameters We assessed indirect parameters of insulin resistance, such as the body mass index (BMI), waist circumference, waist-to-hip ratio (WHR), daily insulin requirement, estimated glucose disposal rate (eGDR) according to Williams and the presence of features of metabolic syndrome. The measurement of height and weight was performed using the same medical scales for all the patients. Weight was measured to an accuracy of 100 g and height to 0.5 cm. The waist and hip circumferences were assessed using a non-elastic tape to an accuracy of 1 mm. Weight before diabetes was defined as weight before symptoms of diabetes (such as i.e. loss of weight). Weight gain was calculated as remainder of actual weight and weight at diagnosis of diabetes. BMI was calculated from the following equation: BMI = weight (kg)/squared height (m2) and WHR = waist circumference (cm)/ hip circumference (cm). The patient’s insulin requirement was measured in units of total daily insulin dose (U) per kilogram body weight (kg). The estimated glucose disposal rate-eGDR was calculated according to the following formula: 24.31– (12.22 × WHR) – (3.29 × arterial hypertension 0/1)–(0.57 × HbA1c), where the units are mg/kg/min (Kilpatrick et al., 2007; Williams et al., 2000). Wiliams et al. created a validation of a score based on clinical factors to determine the extent of insulin resistance in type 1 diabetes. The value of the cut-off point was 7.5 mg/kg/ min; patients with eGDR below 7.5 mg/kg/min were assumed to be insulin resistant, according to the clamp technique of DeFronzo (DeFronzo et al., 1979). The whole group had eGDR assessed during the follow-up in year 2007. The metabolic syndrome was defined according to the International Diabetes Federation (IDF) criteria (Alberti et al., 2005). Central obesity was defined as waist circumference ≥ 94 cm (in male subjects) and ≥ 80 cm (in female subjects). In addition to central obesity, diagnosis of the metabolic syndrome requires the presence of any two additional criteria, such as an increased level of triglicerides ( > 1.7 mmol/l), reduced HDL cholesterol ( < 1.03 mmol/l in male subjects and < 1.29 mmol/l in female subjects), raised blood pressure (systolic ≥ 130 mmHg, diastolic ≥ 85 mmHg), or an increased level of fasting plasma glucose ( > 5.6 mmol/l). All patients were assumed to fulfill the last criterion.

Statistical analysis All data are expressed as means ± SD or percentage of subjects. The patients were divided into two groups, according to the presence or absence of microangiopathic complications of diabetes. The statistical analysis was performed using the STATISTICA 6.0 program. The Mann-Whitney or t-Student’s tests and Fisher’s test or the Chi2 test were used to assess differences between groups with, and without, diabetic complications. The backward logistic regression model was used to estimate the odds ratio (OR) for diabetic microangiopathic events, adjusted for age, sex and duration of diabetes. Differences with a probability value < 0.05 were considered statistically significant.



Data collection procedures

RETINOPATHY

NEPHROPATHY n=12

n=5

n=8 n=7 n=1

n=1

n=2 NEUROPATHY Fig. 1 Distribution of types of complications in group with diabetic microangiopathy.

Results ▼ After approximately a 10-year follow-up, we found microangiopathic complications in 36 of the patients (44.4 %). In these 36, background retinopathy was found in 25 subjects (69 %), nephropathy in 28 subjects (77.8 %) and neuropathy in 11 subjects (31 %). 7 patients presented all three complications and 15 patients had only one complication (8 with nephropathy, 5 retinopathy and 2 neuropathy). The most common combination ▶ Fig. 1). was retinopathy with nephropathy 12 (33.3 %) (● Patients with microangiopathy, compared with subjects without any complication, had higher values of fasting plasma glucose (FPG) (9.7 ± 2.9 vs. 8.4 ± 2.6 mmol/l, p = 0.035), 2-h postprandial plasma glucose (PPG) (9.7 ± 2.2 vs. 8.2 ± 1.7 mmol/l, p = 0.0036), HbA1c (8.9 ± 1.3 vs. 7.9 ± 1.6 %, p = 0.0016), mean HbA1c from years 1997–2007 (8.8 ± 1.5 vs. 7.6 ± 1.2 %, p = 0.0001), TG (1.3 ± 0.8 vs. 0.9 ± 0.3 mmol/l, p = 0.002), GGTP (32.8 ± 30.2 vs. 20.7 ± 14.5 U/l, p = 0.019), waist circumference (88.9 ± 11.7 vs. 83.7 ± 10.2 cm, p = 0.036), WHR (0.90 ± 0.08 vs. 0.86 ± 0.08, p = 0.048), weight before diabetes (77.3 ± 17.0 vs. 67.0 ± 12.5 kg, p = 0.008) and lower values of eGDR (7.2 ± 2.4 vs. 8.8 ± 1.9 mg/kg/min, p = 0.0019) than patients without microangiopathy. Results for waist circumference and WHR were statistically significant only for the whole group, but not when divided for males and females. Moreover, the features of metabolic syndrome were present more often in patients with microangiopathy than in those without (12 (33.3 %) vs. 4 (8.9 %), p = 0.006) (Table 2). Patients with higher values of eGDR were less likely to develop microangiopathic complications, adjusted for age, sex and duration of diabetes (OR 0.65 (95 %CI 0.49–0.86); p = 0.0037) ▶ Fig. 2). (●

Discussion ▼ The majority of studies that have examined insulin resistance in diabetic patients have focused on type 2 diabetes. Nowadays, when overweight and physical inactivity are becoming significantly prevalent, insulin resistance has also become a clinical problem in DM1. Our study has clearly shown that insulin resistance in DM1 is associated with increased risk of microangiopathy. These data are consistent with the results from the Pittsburgh Epidemiology of Diabetes Complications Study. That study has

found low eGDR to be associated with the risk of nephropathy (Orchard et al., 2002). In the DCCT the authors revealed that a low eGDR value, and not insulin dosage or features of metabolic syndrome, is related to the highest subsequent risk of developing micro- and macrovascular complications, independently of assigned treatment (Kilpatrick et al., 2007). The analysis of the cross-sectional FinnDiane Study (Finnish Diabetic Nephropathy Study) also showed that type 1 diabetic patients with microalbuminuria had lower eGDR. Additionally, Thorn et al. found the metabolic syndrome to be 3-fold more common in type 1 diabetic patients with microalbuminuria and with retinopathy (Thorn et al., 2005). The above results are confirmed by studies using the clamp technique to assess insulin resistance in DM1. Ekstrand et al. stated that in patients with DM1 with microalbuminuria, insulin sensitivity was significantly lower than in patients without vascular complications (Ekstrand et al., 1998). Likewise Yip et al. found that patients with type 1 diabetes with microalbuminuria and higher blood pressure values had higher insulin resistance than those without albuminuria (Yip et al., 1993). There are several mechanisms that could explain the correlations between insulin resistance and the development of diabetic angiopathy. Accumulation of visceral fat is accompanied by a low-grade inflammatory process, as adipose tissue releases several proinflammatory cytokines, mostly tumor necrosis factor alfa (TNF-α) and interleukin-6 (IL-6), which induce the production of acute phase proteins by the liver (Fernández-Real and Ricart, 2003). There are several markers reflecting activation of oxidative stress and the inflammatory process in diabetic patients that could be prognostic factors for diabetic complications (Brownlee, 2005; Savage et al., 2005). One of the best explored inflammatory marker is high-sensitivity CRP. It is an acute-phase protein that is considered both a general marker of inflammation and a predictor of cardiovascular events (Bruno et al., 2009). However, we have not found any significant differences between the mean values of hsCRP between groups with and without microangiopathy. Interestingly, the DM1 patients with microangiopathy in the study group had features characteristic for insulin resistance syndrome in phenotype and as well as in their style of life. The frequency of smoking and hypertension has been more common in the group with microangiopathy. Our findings have revealed additionally, that the presence of microangiopathy was associated with indirect parameters of insulin resistance: higher waist circumference, WHR and serum TG levels. These data have been consistent with the results of a European-wide cohort study of individuals with type 1 diabetes, the EURODIAB Prospective Complications Study. Chaturvedi et al. showed that WHR and TG levels, which are both markers of insulin resistance, were independent risk factors strongly related to the incidence of retinopathy (Chaturvedi et al., 2001). Additionally, in our study we have been observed worse glycaemic control in association with vascular complications. Chronic hyperglycaemia induces glucotoxicity which may contribute to reduced peripheral glucose uptake and increased insulin resistance (Yki-Järvinen, 1992). Moreover, better glycaemic control in patients with type 1 diabetes is related to increased insulin sensitivity and reduction of glucose production by the liver (Yki-Järvinen and Koivisto, 1984). These results could be of special importance, as the whole group has been equally educated at baseline and treated with intensive insulin therapy from the onset of the disease. Even in the DCCT, patients enrolled to the study had had mean duration



Article 481

482 Article

n ( %) sex M/F age [years] Duration of diabetes [years] smoking n ( %) hypertension n ( %) weight [kg] weight before symptoms of diabetes [kg] weight gain from the beginning of diabetes [kg] BMI [kg/m2] waist circumference [cm] waist circumference – male [cm] waist circumference – female [cm] WHR WHR – male WHR – female daily insulin requirement [U/kg/d] eGDR [mg/kg/min] eGDR < 7.5 n ( %) metabolic syndrome n ( %) systolic blood pressure [mmHg] diastolic blood pressure [mmHg] FPG [mmol/l] PPG [mmol/l] HbA1c [ %] HbA1c (mean from years 1997-2007) [ %] TCH [mmol/l] TG [mmol/l] LDL-cholesterol [mmol/l] HDL-cholesterol [mmol/l] ApoB [g/l] ApoA1 [g/l] hsCRP [mg/l] ALT [U/l] AST [U/l] GGTP [U/l] creatinine [μmol/l] GFR (MDRD) [ml/min/1.73 m2]

36 (44.4 %) 24/12 34.8 ± 6.1 10.1 ± 1.6 15 (42 %) 12 (33 %) 78.3 ± 15.7 77.3 ± 17.1 12.5 ± 11.2 25.1 ± 4.5 88.9 ± 11.7 92.0 ± 9.2 82.7 ± 14.0 0.9 ± 0.08 0.93 ± 0.05 0.83 ± 0.1 0.66 ± 0.18 7.2 ± 2.4 19 (53 %) 12 (33 %) 121.4 ± 12.6 76.8 ± 10.9 9.7 ± 2.9 9.7 ± 2.2 8.9 ± 1.3 8.8 ± 1.5 4.9 ± 1.1 1.3 ± 0.8 2.9 ± 0.9 1.6 ± 0.4 0.87 ± 0.26 1.71 ± 0.28 2.00 ± 1.99 20.6 ± 9.9 19.9 ± 7.1 32.8 ± 30.2 68.1 ± 11.5 115.0 ± 23.4

No 45 (55.6 %) 27/18 34.2 ± 6.6 9.9 ± 1.5 9 (20 %) 7 (15.6 %) 74.5 ± 14.6 67.0 ± 12.5 14.1 ± 9.9 24.4 ± 3.2 83.7 ± 10.2 89.1 ± 8.5 75.6 ± 6.65 0.86 ± 0.08 0.90 ± 0.07 0.79 ± 0.06 0.68 ± 0.19 8.8 ± 1.9 10 (22 %) 4 (8.9 %) 114.9 ± 16.6 72.6 ± 11.7 8.4 ± 2.6 8.2 ± 1.7 7.9 ± 1.6 7.6 ± 1.2 4.6 ± 0.8 0.9 ± 0.3 2.7 ± 0.7 1.7 ± 0.4 0.79 ± 0.18 1.69 ± 0.24 1.76 ± 2.24 18.7 ± 7.4 19.2 ± 4.9 20.7 ± 14.5 70.7 ± 11.5 108.2 ± 23.0

p 0.53 0.54 0.77 0.03 0.06 0.26 0.008 0.51 0.38 0.036 0.24 0.075 0.04 0.08 0.22 0.65 0.0019 0.004 0.006 0.06 0.09 0.035 0.0036 0.0016 0.0001 0.63 0.002 0.31 0.13 0.28 0.69 0.19 0.48 0.99 0.019 0.28 0.11

Table 2 Clinical characteristics of patients with and without diabetic microangiopathy [data are means ± SD or n ( %)].

BMI – body mass index; WHR – waist to hip ratio; eGDR – estimated glucose disposal rate; FPG – fasting plasma glucose; PPG – postprandial plasma glucose; TCH – total cholesterol; TG - triglycerides; low density lipoproteins (LDL) cholesterol; high density lipoproteins (HDL) cholesterol, ApoB – apolipoprotein B; ApoA1 – apolipoprotein A1; hsCRP – C-reactive protein; ALT – alanine aminotransferase; AST – aspartate aminotransferase; GGTP – gamma-glutamyl transferase; GFR – glomerular filtration rate;

Logistic regression p=0.0037

GDR Age

p=0.73

Time of duration

p=0.93 p=0.27

Sex 0.00

0.25

0.50

0.75

1.00

1.25

1.50

1.75

Odds ratio Fig. 2 The results of a logistic regression model: the odds ratio (OR (95 %CI)) for diabetic microangiopathy events, adjusted for age, sex and duration of diabetes. eGDR – estimated glucose disposal rate.

of diabetes 2.6 + 1.4 years (The Diabetes Control and Complications Trial Research Group, 1993). Mean HbA1c values over the ten years study period has shown that the group without microangiopathy had significantly better longtime glycaemic control. Both groups had similar daily insulin requirement per kg body weight. This fact could be explained that patients with microangiopathy in reality need higher doses of insulin in order to reach better glycaemic control. The clinical implications of these findings have been that insulin resistance may be identified by clinical factors and simple measurements. Moreover, our study has shown the need to identify insulin resistant type 1 diabetic subjects who are at higher risk of developing vascular complications. Finally, an interesting parameter in assessing insulin resistance could be the results of liver dysfunction, as the role of the liver in pathogenesis of insulin resistance is well known. Elevated hepatic enzymes have been interpreted as markers of visceral fat, hepatic steatosis and hepatic insulin resistance (Perry et al.,



Microangiopathy Yes

Article 483

Conclusions ▼ 1. Our findings have confirmed the realationship of persistent hyperglycaemia and insulin resistance with chronic microangiopathic complications in patients with type 1 diabetes. 2. This study has shown the usefulness of indirect parameters of insulin resistance in evaluation of the risk of the diabetic microangiopathy in type 1 diabetic patients.

Acknowledgements ▼ The authors are indebted to Professor Geoffrey Shaw for his editorial assistance. We thank to Dr J. Krasnik and Dr M. Meller for cooperation.

Grant support: Poznan University of Medical Sciences 501-0102234382-08137.

Conflict of Interest : No potential conflict of interest relevant to this article was reported. References 1 Alberti KGMM, Zimmet P, Shaw J. IDF Epidemiology Task Force Consensus Group The metabolic syndrome – a new worldwide definition. Lancet 2005; 366: 1059–10621 2 Araszkiewicz A, Zozulinska-Ziolkiewicz D, Trepinska M et al. High knowledge about diabetes decreases the likelihood of retinopathy in type 1 diabetic patients treated with intensive insulin therapy from the onset of the disease. Arch Med Sci 2005; 1: 205–210 3 Araszkiewicz A, Zozulinska-Ziolkiewicz D, Trepinska M et al. Knowledge after five-day teaching program in intensive insulin therapy performed at the onset of type 1 diabetes influences the development of late diabetic complications. Diabetes Res Clin Pract. 2008; 81: 61–67 4 Arkkila PE, Koskinen PJ, Kantola IM et al. Diabetic complications are associated with liver enzyme activities in people with type 1 diabetes. Diabetes Res Clin Pract 2001; 52: 113–118 5 Brownlee M. The pathobiology of diabetic complications. A unifying mechanism. Diabetes 2005; 54: 1615–1625 6 Bruno G, Fornengo P, Novelli G et al. C-reactive protein and 5-year survival in type 2 diabetes: the Casale Monferrato Study. Diabetes 2009; 58: 926–933 7 Chaturvedi N, Sjoelie AK, Porta M et al. EURODIAB Prospective Complications Study: Markers of insulin resistance are strong risk factors for retinopathy incidence in type 1 diabetes. Diabetes Care 2001; 24 (2): 284–289 8 DeFronzo RA, Tobin JD, Andres R. Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol 1979; 237: E214–E223 9 Ekstrand AV, Groop PH, Grönhagen-Riska C. Insulin resistance precedes microalbuminuria in patients with insulin-dependent diabetes mellitus. Nephrol Dial Transplant 1998; 13: 3079–3083 10 Fernández-Real JM, Ricart W. Insulin resistance and chronic cardiovascular inflammatory syndrome. Endocr Rev 2003; 24: 278–301 11 Kilpatrick ES, Rigby AS, Atkin SL. Insulin resistance, the metabolic syndrome, and complication risk in type 1 diabetes: “double diabetes” in the Diabetes Control and Complications Trial. Diabetes Care 2007; 30: 707–712 12 Koivisto VA, Stevens LK, Mattock M et al. The EURODIAB IDDM Complications Study Group. Cardiovascular disease and its risk factors in IDDM in Europe. Diabetes Care 1996; 19: 689–697 13 Krcma M, Cechurova D, Jankovec Z et al. Effect of mild increase of physical activity on microvasculary reactivity in obese subjects with diabetes mellitus type 2. Exp Clin Endocrinol Diabetes 2009; 117: 150–152 14 Levey AS, Bosch JP, Lewis JB et al. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation Modification of Diet in Renal Disease Study Group. Ann Intern Med 1999; 130: 461–470 15 Lillioja S, Mott DM, Spraul M et al. Insulin resistance and insulin secretory dysfunction as precursors of non-insulin-dependent diabetes mellitus: prospective studies of Pima Indians. N Engl J Med 1993; 329: 1988–1992 16 McLaughlin T, Abbasi F, Cheal K et al. Use of metabolic markers to identify overweight individuals who are insulin resistant. Ann Intern Med 2003; 139: 802–809 17 Müller UA, Femerling M, Reinauer KM et al. Intensified treatment and education of type 1 diabetes as clinical routine A nationwide qualitycircle experience in Germany. ASD (the Working Group on Structured Diabetes Therapy of the German Diabetes Association). Diabetes Care 1999; 22 (Suppl 2): B29–B34 18 Nelson RG, Tuttle KR, KDOQI Clinical Practice Guidelines and Clinical Practice Recommendations for Diabetes and Chronic Kidney Disease. Am J Kidney Dis 2007; 49: S12–S154 19 Orchard TJ, Chang YF, Ferrell RE et al. Nephropathy in type 1 diabetes: a manifestation of insulin resistance and multiple genetic susceptibilities? Further evidence from the Pittsburgh Epidemiology of Diabetes Complication Study. Kidney Int 2002; 62: 963–970



1998). One of the parameters which could refer to liver function is GGTP activity (Penn and Worthington, 1983). Although GGTP has been regarded as a marker of excessive alcohol consumption and liver disease, neither of these factors explains the relationship between diabetes and GGTP levels within the normal range (Wannamethee et al., 2005). Serum GGTP levels were raised in obese individuals and a particularly strong association with central obesity has been described. Perry et al. observed that a raised serum GGTP level is an independent risk factor for type 2 diabetes and may be a simple and reliable marker of visceral and hepatic fat and, by inference, of hepatic insulin resistance (Perry et al., 1998). Moreover, GGTP and ALT levels, even within the normal range, correlate with increasing hepatic fat (Tiikkainen et al., 2003). Our data have shown that the group with microangiopathy has significantly higher serum GGTP levels, but within the normal range. Many other studies have shown that diabetic patients, especially those with vascular complications, have elevated GGTP activities, independently of their alcohol consumption (Chaturvedi et al., 2001; Penn and Worthington, 1983; Arkkila et al., 2001). In the EURODIAB Prospective Complications Study the incidence of retinopathy was associated with higher serum GGTP levels (Chaturvedi et al., 2001). Arkkila et al. revealed a positive association between GGTP activity and neuropathy as well as severity of retinopathy that was independent of alcohol consumption, BMI and metabolic control (Arkkila et al., 2001). Interestingly, it has also been suggested that GGTP might be an early marker of oxidative stress (Wannamethee et al., 2005), which is closely related to the pathogenesis of diabetic complications (Brownlee, 2005). In summary, this study has shown that assessing insulin resistance by calculating the eGDR identified those type 1 diabetic patients who are at greater risk of developing microangiopathy. Moreover, the IDF definition of the metabolic syndrome has appeared to have some utility in distinguishing those type 1 diabetic patients most likely to have small vessel disease. Other indirect parameters of insulin resistance, such as serum triglicerides level and GGTP activity, have seemed to be helpful in assessing insulin resistance and their higher values have been connected with the presence of diabetic microangiopathy. We would like to emphasize that this has been an unique type 1 diabetes group where the rules of intensive insulin therapy were implemented at the onset of the disease. The role of hyperglycaemia in the pathogenesis of chronic complications of type 1 diabetes has been confirmed and proved by assessing the mean 10-year HbA1c value.

484 Article 28 Thorn LM, Forsblom C, Fagerudd J et al. FinnDiane Study Group Metabolic syndrome in type 1 diabetes: association with diabetic nephropathy and glycaemic control (the FinnDiane study). Diabetes Care 2005; 28: 2019–2024 29 Wannamethee SG, Shaper AG, Lennon L et al. Hepatic enzymes, the metabolic syndrome, and the risk of type 2 diabetes in older men. Diabetes Care 2005; 28: 2913–2918 30 Williams KV, Erbey JR, Becker D et al. Can clinical factors estimate insulin resistance in type 1 diabetes? Diabetes 2000; 49: 626–632 31 Yip J, Mattock MB, Morocutti A et al. Insulin resistance in insulindependent diabetic patients with microalbuminuria. Lancet 1993; 342: 883–887 32 Yki-Järvinen H. Glucose toxicity. Endocr Rev 1992; 13: 415–431 33 Yki-Järvinen H, Koivisto VA. Continuous subcutaneous insulin infusion therapy decreases insulin resistance in type 1 diabetes. J Clin. Endocrinol Metab 1984; 58: 659–666 34 Tiikkainen M, Bergholm R, Vehkavaara S et al. Effects of identical weight loss on body composition and features of insulin resistance in obese women with high and low liver fat content. Diabetes 2003; 52: 701–707


20 Orchard TJ, Olson JC, Erbey JR et al. Insulin resistance-related factors, but not glycaemia, predict coronary artery disease in type 1 diabetes: 10-year follow-up data from the Pittsburgh Epidemiology of Diabetes Complications Study. Diabetes Care 2003; 26: 1374–1379 21 Perry IJ, Wannamethee SG, Shaper AG. Prospective study of serum gamma-glutamyltransferase and risk of NIDDM. Diabetes Care 1998; 21: 732–737 22 Penn R, Worthington DJ. Is serum gamma-glutamyltransferase a misleading test? Br Med J (Clin Res Ed) 1983; 286: 531–535 23 Reaven G. Banting Lecture 1988: Role of insulin resistance in human disease. Diabetes 1988; 37: 1595–1607 24 Sainaghi PP, Castello L, Bergamasco L et al. Metabolic characteristics of glucose intolerance: the critical role of obesity. Exp Clin Endocrinol Diabetes 2008; 116: 86–93 25 Savage DB, Petersen KF, Shulman GI. Mechanisms of insulin resistance in humans and possible links with inflammation. Hypertension 2005; 45: 828–833 26 Stern SE, Williams K, Ferrannini E et al. Identification of individuals with insulin resistance using routine clinical measurements. Diabetes 2005; 54: 333–339 27 The Diabetes Control and Complications Trial Research Group. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med 1993; 329: 977–986
