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Body mass index negatively regulates glycated albumin through insulin secretion in patients with type 2 diabetes mellitus
Clinica Chimica Acta 438 (2015) 19–23
Contents lists available at ScienceDirect
Clinica Chimica Acta journal homepage: www.elsevier.com/locate/clinchim
Body mass index negatively regulates glycated albumin through insulin secretion in patients with type 2 diabetes mellitus Masafumi Koga a,⁎, Takumi Hirata b, Soji Kasayama c, Yuko Ishizaka d, Minoru Yamakado d a
Department of Internal Medicine, Kawanishi City Hospital, Hyogo, Japan Foundation for Biomedical Research and Innovation, Hyogo, Japan Department of Medicine, Nissay Hospital, Osaka, Japan d Center for Multiphasic Health Testing and Services, Mitsui Memorial Hospital, Tokyo, Japan b c
a r t i c l e
i n f o
Article history: Received 24 January 2014 Received in revised form 8 July 2014 Accepted 25 July 2014 Available online 4 August 2014 Keywords: Glycated albumin HbA1c Type 2 diabetes mellitus Body mass index Insulin secretion
a b s t r a c t Background: Glycated albumin (GA) is known to be negatively regulated by body mass index (BMI) in nondiabetic subjects and patients with type 2 diabetes mellitus (T2DM). In non-diabetic subjects, a mechanism has been proposed in which chronic inflammation associated with obesity increases albumin metabolism and negatively regulates GA levels. However, whether this same mechanism exists in T2DM is unclear. We investigated the factor(s) which influence GA levels in T2DM patients. Methods: This study included 179 T2DM patients from among people undergoing complete medical examinations. Correlations between GA and the following variables were examined among fasting samples for T2DM patients: BMI, C-reactive protein (CRP), homeostasis model assessment for β-cell function (HOMA-β) and homeostasis model assessment for insulin resistance (HOMA-R). Results: BMI was significantly positively correlated with CRP, but CRP was not significantly correlated with GA. HOMA-β was significantly positively correlated with BMI and significantly negatively correlated with GA. Multivariate analysis showed that HOMA-β was a significant explanatory variable for GA, but not CRP and HOMA-R. Conclusions: Our findings suggest that insulin secretion plays a greater role than chronic inflammation in the mechanism by which BMI negatively regulates GA in T2DM patients. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Glycation of various proteins is known to be increased in diabetes mellitus compared to non-diabetes mellitus and some of these proteins are suggested to be involved in the onset and progression of chronic diabetic [1]. Among the glycated proteins, HbA1c is widely used as a marker of glycemic control [2,3]. HbA1c mainly reflects mean plasma glucose whereas glycated albumin (GA), another glycemic control marker, reflects both mean plasma glucose as well as postprandial plasma glucose [4–8]. Because glucose excursions are larger in type 1 diabetes mellitus than in type 2 diabetes mellitus (T2DM), GA is higher relative to HbA1c in these patients [6]. In addition, GA is a more significant explanatory variable than HbA1c and 1,5-anhydroglucitol as a marker for glucose excursions evaluated by continuous glucose monitoring (CGM) [8]. Glucose excursions and postprandial hyperglycemia have recently been reported to be associated with the onset and/or progression of cardiovascular disease [9,10]. Lower serum GA levels have been reported in non-diabetic obese children [11] and obese T2DM patients [12,13]. Moreover, we reported ⁎ Corresponding author. Tel.: +81 72 794 2321: fax: +81 72 794 6321. E-mail address: [email protected] (M. Koga).
http://dx.doi.org/10.1016/j.cca.2014.07.035 0009-8981/© 2014 Elsevier B.V. All rights reserved.
that body mass index (BMI) was significantly negatively correlated with GA in non-diabetic subjects [14]. In addition, C-reactive protein (CRP) is significantly negatively correlated with GA and multivariate analysis has shown that CRP is a significant negative explanatory variable for GA. Because CRP is elevated due to increased secretion of various cytokines in obesity [15], a theory has been proposed that the mechanism whereby GA is negatively regulated by BMI in non-diabetic subjects is based on increased albumin catabolism associated with chronic microinflammation [14,16]. However, whether this mechanism is also involved in T2DM patients, or whether GA is regulated by a different mechanism, is unclear. 2. Subjects, materials and methods 2.1. Study patients This study included 179 T2DM patients from among persons who had complete medical examinations at Mitsui Memorial Hospital in 2010. The clinical characteristics of the T2DM patients are shown in Table 1. T2DM was diagnosed based on diagnostic criteria of the American Diabetes Association (2009) [17]. Patients already diagnosed with T2DM and received anti-diabetic medication(s) were also
M. Koga et al. / Clinica Chimica Acta 438 (2015) 19–23
Table 1 Clinical characteristics of patients with type 2 diabetes.
n Age (y) BMI (kg/m2) FPG (mg/dl) HbA1c (%) GA (%) log-CRP (mg/l) IRI (μU/ml) HOMA-R HOMA-β (%) Smoking (%) Anti-diabetic medicines (%) Anti-hypertensive medicines (%)
Total
Male
Female
179 62.3 ± 9.1 24.8 ± 3.7 130 ± 19 6.8 ± 0.5 17.0 ± 2.2 −1.3 ± 0.4 7.1 ± 4.0 2.3 ± 1.5 40.1 ± 22.9 35 (19.6) 52 (29.1) 59 (33.0)
148 62.3 ± 9.4 24.7 ± 3.6 132 ± 19 6.8 ± 0.5 17.1 ± 2.2 −1.3 ± 0.5 7.0 ± 4.1 2.3 ± 1.5 38.4 ± 21.8 33 (22.3) 44 (29.7) 51 (34.5)
31 62.3 ± 7.5 25.1 ± 4.3 120 ± 18⁎⁎ 6.7 ± 0.4 16.4 ± 1.7 −1.3 ± 04 7.4 ± 3.7 2.2 ± 1.1 48.4 ± 26.6⁎ 2 (6.5)⁎ 8 (25.8) 8 (25.8)
⁎ P b 0.05. ⁎⁎ P b 0.01 vs. male.
included. Patients with an elevated CRP (≥10 mg/l) [18], liver cirrhosis, renal disease or anemia were excluded. The institutional committee approved the protocol of this study, and all participants gave informed consent. Correlations between GA and the following variables were examined among fasting samples for T2DM patients: BMI, CRP, homeostasis model assessment for pancreatic β-cell function (HOMA-β) and homeostasis model assessment for insulin resistance (HOMA-R). 2.2. Laboratory methods Blood tests were performed after overnight fasting. Plasma glucose was determined by glucose oxidase methods. HbA1c, expressed as the National Glycohemoglobin Standardization Program value [19], was measured by high performance liquid chromatography. GA was determined by the enzymatic method using albumin-specific proteinase, ketoamine oxidase, and albumin assay reagent (Lucica GA-L; Asahi Kasei Pharma Co.) [20]. CRP was determined by means of latex-enhanced immunonephelometrics on a BNII Analyzer (Dade Behring), as described previously [21]. Serum insulin concentrations were determined by enzyme immunoassay using guinea pig antihuman insulin antibody. Pancreatic β cell function and insulin sensitivity were assessed by HOMA-β and HOMA-R [22]. HOMA-β and HOMA-R were calculated by the following formulae. HOMA-β (%) = IRI (μU/ml) × 360 / [fasting plasma glucose (FPG) (mg/dl) − 63]
0.5% (50.4 ± 5.5 mmol/mol), GA of 17.0 ± 2.2%, CRP (log transformed) of −1.3 ± 0.4 mg/dl, IRI 7.1 ± 4.0 μU/ml HOMA-β of 40.1 ± 22.9%, HOMA-R of 2.3 ± 1.5 (Table 1). Thirty-five patients (19.6%) were smokers, and patients receiving anti-diabetic medicine(s) and antihypertensive medicine(s) are 52 (29.1%) and 59 (33.0%), respectively. In the 52 patients receiving anti-diabetic medicine(s), one or a combination of medicines are as follows; sulfonylureas for 30, dipeptidyl peptidase-4 inhibitor for 30, biguanides for 22, thiazolidinediones for 10, α-glucosidase inhibitors for 10, glinides for 3, glucagon-like peptide-1 analogue for 1. HOMA-β was higher and FPG was lower in women than in men. There were fewer smokers in women than in men. Other variables including GA were not significantly different between women and men. BMI was not significantly correlated with HbA1c (R = 0.079, P = 0.290) but was significantly negatively correlated with GA (R = − 0.221, P = 0.003) (Fig. 1). In addition, CRP was significantly positively correlated with BMI (R = 0.363, P b 0.0001). However, CRP was significantly correlated with neither HbA1c nor GA (HbA1c; R = 0.133, P = 0.075, GA; R = − 0.015, P = 0.125) (Fig. 2). On the other hand, BMI was significantly positively correlated with HOMA-β, an index of insulin secretory function (R = 0.457, P b 0.0001). Even when two extreme obese patients (BMI N 40 kg/m2) were excluded, there was a significant positive correlation between BMI and HOMA-β (R = 0.417, P b 0.0001). HOMA-β was not significantly correlated with HbA1c (R = −0.085, P = 0.258), but was significantly negatively correlated with GA (R = −0.402, P b 0.0001) (Fig. 3). Multivariate analysis was performed with GA as an objective variable, and age, sex, FPG and BMI as explanatory variables (Model 1). FPG, age and BMI were selected as significant explanatory variables for GA (Table 2a). Next, CRP, HOMA-β and HOMA-R were added to the explanatory variables in Model 1 and multivariate analysis was performed (Model 2). HOMA-β was a significant explanatory variable for GA together with FPG and age, but CRP and HOMA-R were not. Moreover, BMI, which was a significant explanatory variable in Model 1, was not a significant explanatory variable in Model 2 (Table 2b). 4. Discussion As previously reported in T2DM patients [12,13], BMI was not significantly correlated with HbA1c but was significantly negatively correlated with GA in the present study. In addition, BMI was significantly
a The reference ranges of BMI, FPG, HbA1c, and GA were between 18.5 and 25 kg/m2, between 70 and 99 mg/dl, between 4.6% and 6.2% (27.5 and 43.8 mmol/mol), and between 11.7% and 16.0%, respectively. 2.3. Statistical analyses All data are shown as means ± SD. To correct for skewed distributions, serum CRP concentrations were logarithmically transformed [14]. To analyze the effects of explanatory variables on HbA1c or GA, univariate regression analysis as well as stepwise multivariate regression analysis was performed with StatView computer program ver 5.0 for Windows (Abacus Concepts). In the stepwise multiple regression analysis, the F value (variance ratio) for inclusion of variables was set at 4.0. A P value b 0.05 was considered statistically significant.
HbA1c (%)
HOMA-R = IRI (μU/ml) × FPG (mg/dl) / 405
b
10
8
25
R = -0.221 P = 0.003
20 GA (%)
20
6
4
15 R = 0.079 P = 0.290
10 20 30 40 50 BMI (kg/m2)
10 10 20 30 40 50 BMI (kg/m2)
3. Results Participants included 148 males (82.7%) with a mean age of 62.3 ± 9.1 y, BMI of 24.8 ± 3.7 kg/m2, FPG of 130 ± 19 mg/dl, HbA1c of 6.8 ±
Fig. 1. Correlation of body mass index (BMI) with HbA1c (a) and glycated albumin (GA) (b) in 179 patients with type 2 diabetes mellitus. The upper value of reference range for HbA1c, and GA was shown as the dotted line.
M. Koga et al. / Clinica Chimica Acta 438 (2015) 19–23
b
50
HbA1c (%)
BMI (kg/m2)
40 30
c
10
8
25
20 GA (%)
a
21
6
15
20 10 -3
R = 0.363 P<0.0001
R = 0.133 P = 0.075
4 -3 -2 -1 0 1 log-CRP (mg/L)
-2 -1 0 1 log-CRP (mg/L)
10 -3
R = -0.115 P = 0.125
-2 -1 0 1 log-CRP (mg/L)
Fig. 2. Correlation of C-reactive protein (CRP) with body mass index (BMI) (a), HbA1c (b) and glycated albumin (GA) (c) in 179 patients with type 2 diabetes mellitus. The upper value of reference range for BMI, HbA1c and GA was shown as the dotted line.
positively correlated with CRP. This is probably because of the increased secretion of inflammatory cytokines associated with obesity [15]. We previously reported that in addition to a correlation between BMI and CRP in non-diabetes mellitus (non-DM), there is also a significant correlation between CRP and GA [14]. Therefore, we proposed a mechanism in non-DM in which chronic inflammation associated with obesity increases albumin metabolism, and as a result, GA is negatively regulated by BMI (Fig. 4a) [14]. In the present study, CRP was significantly correlated with neither HbA1c nor GA in T2DM patients. These findings suggest that chronic inflammation is not the primary mechanism of GA regulation by BMI in T2DM patients. In diabetic patients with coexisting Cushing's syndrome or nephrotic syndrome, in which albumin metabolism is increased, low GA levels have been reported [23,24]. Therefore, BMI is thought to also reflect abnormal albumin metabolism in T2DM patients. Accordingly, the absence of a correlation between CRP and GA in T2DM patients suggests that increased albumin metabolism due to chronic inflammation is unlikely (Fig. 4b). However, the molecular mechanism by which the action of CRP on albumin metabolism is attenuated in T2DM patients is unknown. This will require further investigation. In T2DM patients, BMI was significantly positively correlated with HOMA-β, an index of insulin secretory function. Similar results were reported by Funakoshi et al. [25]. The presumed mechanism is that with increased insulin resistance in obese patients, β-cell size increases as a compensatory mechanism, which results in an increase in insulin
b
50
HbA1c (%)
BMI (kg/m2)
40 30 20 10
R = 0.457 P<0.0001
0
50 100 150 HOMA-β (%)
c
10
8
25
20 GA (%)
a
secretion [25]. In fact, autopsy findings in T2DM patients have shown a correlation between BMI and β-cell size [26]. HOMA-β was negatively correlated with GA but was not correlated with HbA1c. We previously reported a significant negative correlation between insulin secretion and the GA/HbA1c ratio in T2DM patients [7]. This phenomenon is assumed to occur because with decreased insulin secretion, glucose excursions increase and postprandial hyperglycemia occurs, and thus GA, which reflects these glucose excursions, also increases. A negative correlation between insulin secretion and markers of glucose excursion assessed by CGM has also been reported [27]. In addition, significant negative correlations between markers of glucose excursions assessed by CGM and postprandial glucose with GA and the GA/HbA1c ratio have been reported [27–29]. Therefore, the negative correlation between HOMA-β and GA observed in the present study might be interpreted to reflect the effect of increases in HOMA-β to limit glucose excursions and/or postprandial hyperglycemia. Next, we performed multivariate analysis with GA as the objective variable to evaluate the mechanism by which BMI regulates GA in T2DM patients. BMI was a significant explanatory variable for GA in Model 1. However, with analysis after adding other explanatory variables (Model 2), BMI was no longer significant. Instead, HOMA-β became a significant explanatory variable for GA. This finding suggests that HOMA-β plays more of a central role than does BMI in the mechanism of GA regulation. Moreover, HOMA-R was not a significant explanatory variable for GA. This result is supported by a previous report that
6
4
15 R = -0.085 P = 0.258
0
50 100 150 HOMA-β (%)
10
R = -0.402 P < 0.0001
0
50 100 150 HOMA-β (%)
Fig. 3. Correlation of homeostasis model assessment for β-cell function (HOMA-β) with body mass index (BMI) (a), HbA1c (b) and glycated albumin (GA) (c) in 179 patients with type 2 diabetes mellitus. The upper value of reference range for BMI, HbA1c, and GA was shown as the dotted line.
22
M. Koga et al. / Clinica Chimica Acta 438 (2015) 19–23
Table 2 Stepwise multivariate regression analyses of glycated albumin (GA) levels in 180 patients with type 2 diabetes mellitus. a: Model 1 Variable
β
F
P
FPG Age BMI
0.460 0.184 −0.163
51.2 7.4 5.9
b0.0001 0.008 0.018
b: Model 2 Variable
β
F
P
FPG HOMA-β Age
0.373 −0.269 0.216
31.8 16.8 12.0
0.010 0.041 0.003
a: Model 1; Confounding variables included are age (years), body mass index (BMI; kg/m2), sex (female, 0; male, 1) and fasting plasma glucose (FPG; mg/dl). R2 = 0.254, F = 30.1 and P b 0.0001. β: standard regression coefficient, F: exclusion F value, P: significant probability. b: Model 2; Confounding variables included are age (years), BMI (kg/m2), sex (female, 0; male, 1), FPG (mg/dl), log transformed C-reactive protein (CRP; mg/l), homeostasis model assessment of insulin resistance (HOMA-R), and homeostasis model assessment for β-cell function (HOMA-β; %). R2 = 0.324, F = 32.2 and P b 0.0001. β: standard regression coefficient, F: exclusion F value, P: significant probability.
found the GA/HbA1c ratio to be correlated with insulin secretory function but not with insulin resistance [29]. Based on the above, BMI regulates insulin secretion in T2DM patients and insulin secretion regulates GA through its effects on glucose excursions and/or postprandial hyperglycemia (Fig. 4c). Our results demonstrate that in both non-DM and T2DM, GA is negatively regulated by BMI, but the mechanism of regulation differs. In non-DM, because GA regulation by BMI involves factors unrelated to plasma glucose, it is necessary to correct GA value by BMI to know the true GA value [5,30]. On the other hand, because GA regulation by BMI is related to plasma glucose itself in T2DM patients, correction for BMI is not necessary. The present study has some limitations. This study was a crosssectional survey and thus we were not able to determine any causal relationship among BMI, CPR and GA. Because T2DM patients were selected from among people undergoing complete medical examinations, insulin secretion was relatively preserved and glycemic control was
a
b
c
Fig. 4. Hypothesis on regulation of glycated albumin (GA) by body mass index (BMI) in subjects with non-diabetes mellitus (Non-DM) (a) and patients with type 2 diabetes mellitus (T2DM) (b, c). In non-DM, obesity and its related chronic inflammation are associated with lower GA levels (a). In T2DM patients, obesity and its related chronic inflammation are not mainly involved because C-reactive protein (CRP) does not correlate with GA (b). Instead, BMI is positively correlated with insulin secretion. When insulin secretion increases, GA levels decrease through decrease of postprandial hyperglycemia and/or glycemic excursion (c).
good in most patients, and a few were on drug therapy. In addition, none of the patients were using insulin. Therefore, further studies in patients with lower insulin secretory function who are receiving insulin therapy will be necessary to investigate whether a similar phenomenon is observed. Furthermore, fasting test results for insulin and glucose were used, but postprandial plasma glucose and insulin secretion could not be evaluated. Further studies will be necessary to investigate the relationship of these two variables as well as the relationship between postprandial insulin secretion and GA. In conclusion, our findings demonstrate that in T2DM patients, insulin secretion plays a greater role in GA formation than does increased albumin metabolism due to chronic inflammation through a mechanism by which BMI negatively regulates GA.
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M. Koga et al. / Clinica Chimica Acta 438 (2015) 19–23 [25] Funakoshi S, Fujimoto S, Hamasaki A, et al. Analysis of factors influencing pancreatic beta-cell function in Japanese patients with type 2 diabetes: association with body mass index and duration of diabetic exposure. Diabetes Res Clin Pract 2008;82:353–8. [26] Yoon KH, Ko SH, Cho JH, et al. Selective beta-cell loss and alpha-cell expansion in patients with type 2 diabetes mellitus in Korea. J Clin Endocrinol Metab 2003;88: 2300–8. [27] Ogawa A, Hayashi A, Kishihara E, Yoshino S, Takeuchi A, Shichiri M. New indices for predicting glycaemic variability. PLoS One 2012;7:e46517.
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[28] Saisho Y, Tanaka K, Abe T, Shimada A, Kawai T, Itoh H. Glycated albumin to glycated hemoglobin ratio reflects postprandial glucose excursion and relates to beta cell function in both type 1 and type 2 diabetes. Diabetol Int 2011;2:146–53. [29] Kim D, Kim KJ, Huh JH, et al. The ratio of glycated albumin to glycated haemoglobin correlates with insulin secretory function. Clin Endocrinol (Oxf) 2012;77:679–83. [30] Koga M, Murai J, Saito H, Mukai M, Kasayama S. Serum glycated albumin, but not glycated hemoglobin, is low in relation to glycemia in hyperuricemic men. Acta Diabetol 2010;47:173–7.
Contents lists available at ScienceDirect
Clinica Chimica Acta journal homepage: www.elsevier.com/locate/clinchim
Body mass index negatively regulates glycated albumin through insulin secretion in patients with type 2 diabetes mellitus Masafumi Koga a,⁎, Takumi Hirata b, Soji Kasayama c, Yuko Ishizaka d, Minoru Yamakado d a
Department of Internal Medicine, Kawanishi City Hospital, Hyogo, Japan Foundation for Biomedical Research and Innovation, Hyogo, Japan Department of Medicine, Nissay Hospital, Osaka, Japan d Center for Multiphasic Health Testing and Services, Mitsui Memorial Hospital, Tokyo, Japan b c
a r t i c l e
i n f o
Article history: Received 24 January 2014 Received in revised form 8 July 2014 Accepted 25 July 2014 Available online 4 August 2014 Keywords: Glycated albumin HbA1c Type 2 diabetes mellitus Body mass index Insulin secretion
a b s t r a c t Background: Glycated albumin (GA) is known to be negatively regulated by body mass index (BMI) in nondiabetic subjects and patients with type 2 diabetes mellitus (T2DM). In non-diabetic subjects, a mechanism has been proposed in which chronic inflammation associated with obesity increases albumin metabolism and negatively regulates GA levels. However, whether this same mechanism exists in T2DM is unclear. We investigated the factor(s) which influence GA levels in T2DM patients. Methods: This study included 179 T2DM patients from among people undergoing complete medical examinations. Correlations between GA and the following variables were examined among fasting samples for T2DM patients: BMI, C-reactive protein (CRP), homeostasis model assessment for β-cell function (HOMA-β) and homeostasis model assessment for insulin resistance (HOMA-R). Results: BMI was significantly positively correlated with CRP, but CRP was not significantly correlated with GA. HOMA-β was significantly positively correlated with BMI and significantly negatively correlated with GA. Multivariate analysis showed that HOMA-β was a significant explanatory variable for GA, but not CRP and HOMA-R. Conclusions: Our findings suggest that insulin secretion plays a greater role than chronic inflammation in the mechanism by which BMI negatively regulates GA in T2DM patients. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Glycation of various proteins is known to be increased in diabetes mellitus compared to non-diabetes mellitus and some of these proteins are suggested to be involved in the onset and progression of chronic diabetic [1]. Among the glycated proteins, HbA1c is widely used as a marker of glycemic control [2,3]. HbA1c mainly reflects mean plasma glucose whereas glycated albumin (GA), another glycemic control marker, reflects both mean plasma glucose as well as postprandial plasma glucose [4–8]. Because glucose excursions are larger in type 1 diabetes mellitus than in type 2 diabetes mellitus (T2DM), GA is higher relative to HbA1c in these patients [6]. In addition, GA is a more significant explanatory variable than HbA1c and 1,5-anhydroglucitol as a marker for glucose excursions evaluated by continuous glucose monitoring (CGM) [8]. Glucose excursions and postprandial hyperglycemia have recently been reported to be associated with the onset and/or progression of cardiovascular disease [9,10]. Lower serum GA levels have been reported in non-diabetic obese children [11] and obese T2DM patients [12,13]. Moreover, we reported ⁎ Corresponding author. Tel.: +81 72 794 2321: fax: +81 72 794 6321. E-mail address: [email protected] (M. Koga).
http://dx.doi.org/10.1016/j.cca.2014.07.035 0009-8981/© 2014 Elsevier B.V. All rights reserved.
that body mass index (BMI) was significantly negatively correlated with GA in non-diabetic subjects [14]. In addition, C-reactive protein (CRP) is significantly negatively correlated with GA and multivariate analysis has shown that CRP is a significant negative explanatory variable for GA. Because CRP is elevated due to increased secretion of various cytokines in obesity [15], a theory has been proposed that the mechanism whereby GA is negatively regulated by BMI in non-diabetic subjects is based on increased albumin catabolism associated with chronic microinflammation [14,16]. However, whether this mechanism is also involved in T2DM patients, or whether GA is regulated by a different mechanism, is unclear. 2. Subjects, materials and methods 2.1. Study patients This study included 179 T2DM patients from among persons who had complete medical examinations at Mitsui Memorial Hospital in 2010. The clinical characteristics of the T2DM patients are shown in Table 1. T2DM was diagnosed based on diagnostic criteria of the American Diabetes Association (2009) [17]. Patients already diagnosed with T2DM and received anti-diabetic medication(s) were also
M. Koga et al. / Clinica Chimica Acta 438 (2015) 19–23
Table 1 Clinical characteristics of patients with type 2 diabetes.
n Age (y) BMI (kg/m2) FPG (mg/dl) HbA1c (%) GA (%) log-CRP (mg/l) IRI (μU/ml) HOMA-R HOMA-β (%) Smoking (%) Anti-diabetic medicines (%) Anti-hypertensive medicines (%)
Total
Male
Female
179 62.3 ± 9.1 24.8 ± 3.7 130 ± 19 6.8 ± 0.5 17.0 ± 2.2 −1.3 ± 0.4 7.1 ± 4.0 2.3 ± 1.5 40.1 ± 22.9 35 (19.6) 52 (29.1) 59 (33.0)
148 62.3 ± 9.4 24.7 ± 3.6 132 ± 19 6.8 ± 0.5 17.1 ± 2.2 −1.3 ± 0.5 7.0 ± 4.1 2.3 ± 1.5 38.4 ± 21.8 33 (22.3) 44 (29.7) 51 (34.5)
31 62.3 ± 7.5 25.1 ± 4.3 120 ± 18⁎⁎ 6.7 ± 0.4 16.4 ± 1.7 −1.3 ± 04 7.4 ± 3.7 2.2 ± 1.1 48.4 ± 26.6⁎ 2 (6.5)⁎ 8 (25.8) 8 (25.8)
⁎ P b 0.05. ⁎⁎ P b 0.01 vs. male.
included. Patients with an elevated CRP (≥10 mg/l) [18], liver cirrhosis, renal disease or anemia were excluded. The institutional committee approved the protocol of this study, and all participants gave informed consent. Correlations between GA and the following variables were examined among fasting samples for T2DM patients: BMI, CRP, homeostasis model assessment for pancreatic β-cell function (HOMA-β) and homeostasis model assessment for insulin resistance (HOMA-R). 2.2. Laboratory methods Blood tests were performed after overnight fasting. Plasma glucose was determined by glucose oxidase methods. HbA1c, expressed as the National Glycohemoglobin Standardization Program value [19], was measured by high performance liquid chromatography. GA was determined by the enzymatic method using albumin-specific proteinase, ketoamine oxidase, and albumin assay reagent (Lucica GA-L; Asahi Kasei Pharma Co.) [20]. CRP was determined by means of latex-enhanced immunonephelometrics on a BNII Analyzer (Dade Behring), as described previously [21]. Serum insulin concentrations were determined by enzyme immunoassay using guinea pig antihuman insulin antibody. Pancreatic β cell function and insulin sensitivity were assessed by HOMA-β and HOMA-R [22]. HOMA-β and HOMA-R were calculated by the following formulae. HOMA-β (%) = IRI (μU/ml) × 360 / [fasting plasma glucose (FPG) (mg/dl) − 63]
0.5% (50.4 ± 5.5 mmol/mol), GA of 17.0 ± 2.2%, CRP (log transformed) of −1.3 ± 0.4 mg/dl, IRI 7.1 ± 4.0 μU/ml HOMA-β of 40.1 ± 22.9%, HOMA-R of 2.3 ± 1.5 (Table 1). Thirty-five patients (19.6%) were smokers, and patients receiving anti-diabetic medicine(s) and antihypertensive medicine(s) are 52 (29.1%) and 59 (33.0%), respectively. In the 52 patients receiving anti-diabetic medicine(s), one or a combination of medicines are as follows; sulfonylureas for 30, dipeptidyl peptidase-4 inhibitor for 30, biguanides for 22, thiazolidinediones for 10, α-glucosidase inhibitors for 10, glinides for 3, glucagon-like peptide-1 analogue for 1. HOMA-β was higher and FPG was lower in women than in men. There were fewer smokers in women than in men. Other variables including GA were not significantly different between women and men. BMI was not significantly correlated with HbA1c (R = 0.079, P = 0.290) but was significantly negatively correlated with GA (R = − 0.221, P = 0.003) (Fig. 1). In addition, CRP was significantly positively correlated with BMI (R = 0.363, P b 0.0001). However, CRP was significantly correlated with neither HbA1c nor GA (HbA1c; R = 0.133, P = 0.075, GA; R = − 0.015, P = 0.125) (Fig. 2). On the other hand, BMI was significantly positively correlated with HOMA-β, an index of insulin secretory function (R = 0.457, P b 0.0001). Even when two extreme obese patients (BMI N 40 kg/m2) were excluded, there was a significant positive correlation between BMI and HOMA-β (R = 0.417, P b 0.0001). HOMA-β was not significantly correlated with HbA1c (R = −0.085, P = 0.258), but was significantly negatively correlated with GA (R = −0.402, P b 0.0001) (Fig. 3). Multivariate analysis was performed with GA as an objective variable, and age, sex, FPG and BMI as explanatory variables (Model 1). FPG, age and BMI were selected as significant explanatory variables for GA (Table 2a). Next, CRP, HOMA-β and HOMA-R were added to the explanatory variables in Model 1 and multivariate analysis was performed (Model 2). HOMA-β was a significant explanatory variable for GA together with FPG and age, but CRP and HOMA-R were not. Moreover, BMI, which was a significant explanatory variable in Model 1, was not a significant explanatory variable in Model 2 (Table 2b). 4. Discussion As previously reported in T2DM patients [12,13], BMI was not significantly correlated with HbA1c but was significantly negatively correlated with GA in the present study. In addition, BMI was significantly
a The reference ranges of BMI, FPG, HbA1c, and GA were between 18.5 and 25 kg/m2, between 70 and 99 mg/dl, between 4.6% and 6.2% (27.5 and 43.8 mmol/mol), and between 11.7% and 16.0%, respectively. 2.3. Statistical analyses All data are shown as means ± SD. To correct for skewed distributions, serum CRP concentrations were logarithmically transformed [14]. To analyze the effects of explanatory variables on HbA1c or GA, univariate regression analysis as well as stepwise multivariate regression analysis was performed with StatView computer program ver 5.0 for Windows (Abacus Concepts). In the stepwise multiple regression analysis, the F value (variance ratio) for inclusion of variables was set at 4.0. A P value b 0.05 was considered statistically significant.
HbA1c (%)
HOMA-R = IRI (μU/ml) × FPG (mg/dl) / 405
b
10
8
25
R = -0.221 P = 0.003
20 GA (%)
20
6
4
15 R = 0.079 P = 0.290
10 20 30 40 50 BMI (kg/m2)
10 10 20 30 40 50 BMI (kg/m2)
3. Results Participants included 148 males (82.7%) with a mean age of 62.3 ± 9.1 y, BMI of 24.8 ± 3.7 kg/m2, FPG of 130 ± 19 mg/dl, HbA1c of 6.8 ±
Fig. 1. Correlation of body mass index (BMI) with HbA1c (a) and glycated albumin (GA) (b) in 179 patients with type 2 diabetes mellitus. The upper value of reference range for HbA1c, and GA was shown as the dotted line.
M. Koga et al. / Clinica Chimica Acta 438 (2015) 19–23
b
50
HbA1c (%)
BMI (kg/m2)
40 30
c
10
8
25
20 GA (%)
a
21
6
15
20 10 -3
R = 0.363 P<0.0001
R = 0.133 P = 0.075
4 -3 -2 -1 0 1 log-CRP (mg/L)
-2 -1 0 1 log-CRP (mg/L)
10 -3
R = -0.115 P = 0.125
-2 -1 0 1 log-CRP (mg/L)
Fig. 2. Correlation of C-reactive protein (CRP) with body mass index (BMI) (a), HbA1c (b) and glycated albumin (GA) (c) in 179 patients with type 2 diabetes mellitus. The upper value of reference range for BMI, HbA1c and GA was shown as the dotted line.
positively correlated with CRP. This is probably because of the increased secretion of inflammatory cytokines associated with obesity [15]. We previously reported that in addition to a correlation between BMI and CRP in non-diabetes mellitus (non-DM), there is also a significant correlation between CRP and GA [14]. Therefore, we proposed a mechanism in non-DM in which chronic inflammation associated with obesity increases albumin metabolism, and as a result, GA is negatively regulated by BMI (Fig. 4a) [14]. In the present study, CRP was significantly correlated with neither HbA1c nor GA in T2DM patients. These findings suggest that chronic inflammation is not the primary mechanism of GA regulation by BMI in T2DM patients. In diabetic patients with coexisting Cushing's syndrome or nephrotic syndrome, in which albumin metabolism is increased, low GA levels have been reported [23,24]. Therefore, BMI is thought to also reflect abnormal albumin metabolism in T2DM patients. Accordingly, the absence of a correlation between CRP and GA in T2DM patients suggests that increased albumin metabolism due to chronic inflammation is unlikely (Fig. 4b). However, the molecular mechanism by which the action of CRP on albumin metabolism is attenuated in T2DM patients is unknown. This will require further investigation. In T2DM patients, BMI was significantly positively correlated with HOMA-β, an index of insulin secretory function. Similar results were reported by Funakoshi et al. [25]. The presumed mechanism is that with increased insulin resistance in obese patients, β-cell size increases as a compensatory mechanism, which results in an increase in insulin
b
50
HbA1c (%)
BMI (kg/m2)
40 30 20 10
R = 0.457 P<0.0001
0
50 100 150 HOMA-β (%)
c
10
8
25
20 GA (%)
a
secretion [25]. In fact, autopsy findings in T2DM patients have shown a correlation between BMI and β-cell size [26]. HOMA-β was negatively correlated with GA but was not correlated with HbA1c. We previously reported a significant negative correlation between insulin secretion and the GA/HbA1c ratio in T2DM patients [7]. This phenomenon is assumed to occur because with decreased insulin secretion, glucose excursions increase and postprandial hyperglycemia occurs, and thus GA, which reflects these glucose excursions, also increases. A negative correlation between insulin secretion and markers of glucose excursion assessed by CGM has also been reported [27]. In addition, significant negative correlations between markers of glucose excursions assessed by CGM and postprandial glucose with GA and the GA/HbA1c ratio have been reported [27–29]. Therefore, the negative correlation between HOMA-β and GA observed in the present study might be interpreted to reflect the effect of increases in HOMA-β to limit glucose excursions and/or postprandial hyperglycemia. Next, we performed multivariate analysis with GA as the objective variable to evaluate the mechanism by which BMI regulates GA in T2DM patients. BMI was a significant explanatory variable for GA in Model 1. However, with analysis after adding other explanatory variables (Model 2), BMI was no longer significant. Instead, HOMA-β became a significant explanatory variable for GA. This finding suggests that HOMA-β plays more of a central role than does BMI in the mechanism of GA regulation. Moreover, HOMA-R was not a significant explanatory variable for GA. This result is supported by a previous report that
6
4
15 R = -0.085 P = 0.258
0
50 100 150 HOMA-β (%)
10
R = -0.402 P < 0.0001
0
50 100 150 HOMA-β (%)
Fig. 3. Correlation of homeostasis model assessment for β-cell function (HOMA-β) with body mass index (BMI) (a), HbA1c (b) and glycated albumin (GA) (c) in 179 patients with type 2 diabetes mellitus. The upper value of reference range for BMI, HbA1c, and GA was shown as the dotted line.
22
M. Koga et al. / Clinica Chimica Acta 438 (2015) 19–23
Table 2 Stepwise multivariate regression analyses of glycated albumin (GA) levels in 180 patients with type 2 diabetes mellitus. a: Model 1 Variable
β
F
P
FPG Age BMI
0.460 0.184 −0.163
51.2 7.4 5.9
b0.0001 0.008 0.018
b: Model 2 Variable
β
F
P
FPG HOMA-β Age
0.373 −0.269 0.216
31.8 16.8 12.0
0.010 0.041 0.003
a: Model 1; Confounding variables included are age (years), body mass index (BMI; kg/m2), sex (female, 0; male, 1) and fasting plasma glucose (FPG; mg/dl). R2 = 0.254, F = 30.1 and P b 0.0001. β: standard regression coefficient, F: exclusion F value, P: significant probability. b: Model 2; Confounding variables included are age (years), BMI (kg/m2), sex (female, 0; male, 1), FPG (mg/dl), log transformed C-reactive protein (CRP; mg/l), homeostasis model assessment of insulin resistance (HOMA-R), and homeostasis model assessment for β-cell function (HOMA-β; %). R2 = 0.324, F = 32.2 and P b 0.0001. β: standard regression coefficient, F: exclusion F value, P: significant probability.
found the GA/HbA1c ratio to be correlated with insulin secretory function but not with insulin resistance [29]. Based on the above, BMI regulates insulin secretion in T2DM patients and insulin secretion regulates GA through its effects on glucose excursions and/or postprandial hyperglycemia (Fig. 4c). Our results demonstrate that in both non-DM and T2DM, GA is negatively regulated by BMI, but the mechanism of regulation differs. In non-DM, because GA regulation by BMI involves factors unrelated to plasma glucose, it is necessary to correct GA value by BMI to know the true GA value [5,30]. On the other hand, because GA regulation by BMI is related to plasma glucose itself in T2DM patients, correction for BMI is not necessary. The present study has some limitations. This study was a crosssectional survey and thus we were not able to determine any causal relationship among BMI, CPR and GA. Because T2DM patients were selected from among people undergoing complete medical examinations, insulin secretion was relatively preserved and glycemic control was
a
b
c
Fig. 4. Hypothesis on regulation of glycated albumin (GA) by body mass index (BMI) in subjects with non-diabetes mellitus (Non-DM) (a) and patients with type 2 diabetes mellitus (T2DM) (b, c). In non-DM, obesity and its related chronic inflammation are associated with lower GA levels (a). In T2DM patients, obesity and its related chronic inflammation are not mainly involved because C-reactive protein (CRP) does not correlate with GA (b). Instead, BMI is positively correlated with insulin secretion. When insulin secretion increases, GA levels decrease through decrease of postprandial hyperglycemia and/or glycemic excursion (c).
good in most patients, and a few were on drug therapy. In addition, none of the patients were using insulin. Therefore, further studies in patients with lower insulin secretory function who are receiving insulin therapy will be necessary to investigate whether a similar phenomenon is observed. Furthermore, fasting test results for insulin and glucose were used, but postprandial plasma glucose and insulin secretion could not be evaluated. Further studies will be necessary to investigate the relationship of these two variables as well as the relationship between postprandial insulin secretion and GA. In conclusion, our findings demonstrate that in T2DM patients, insulin secretion plays a greater role in GA formation than does increased albumin metabolism due to chronic inflammation through a mechanism by which BMI negatively regulates GA.
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