Open Access

Low serum galectin-3 concentrations are associated with insulin resistance in patients with type 2 diabetes mellitus

  • Tsuyoshi Ohkura1Email author,
  • Youhei Fujioka1,
  • Risa Nakanishi1,
  • Hideki Shiochi1,
  • Keisuke Sumi1,
  • Naoya Yamamoto1,
  • Kazuhiko Matsuzawa2,
  • Shoichiro Izawa1,
  • Hiroko Ohkura2,
  • Etsuko Ueta3,
  • Masahiko Kato1,
  • Eiji Miyoshi4,
  • Shin-ichi Taniguchi2 and
  • Kazuhiro Yamamoto1
Diabetology & Metabolic Syndrome20146:106

DOI: 10.1186/1758-5996-6-106

Received: 12 July 2014

Accepted: 22 September 2014

Published: 27 September 2014

Abstract

Background

Galectin-3 is a family of soluble beta-galactoside-binding lectins that play many important regulatory roles in inflammation. Galectin-3-deficient mice have been shown to exhibit excess adiposity, hyperglycemia, insulin resistance and systemic inflammation. We investigated the association between serum galectin-3 and insulin resistance in patients with type 2 diabetes using a glucose clamp method.

Methods

This was a cross-sectional study. Twenty patients (mean fasting plasma glucose 7.6 mmol/L, HbA1c 7.2%, BMI 28.1 kg/m2) underwent a meal tolerance test and glucose clamp test. Participants were given a test meal and plasma glucose and insulin were measured at 0, 30, 60, 120 and 180 min. The glucose disposal rate was measured during hyperinsulinemic-euglycemic glucose clamps. Serum galectin-3 levels were measured using the enzyme-linked immunosorbent assay method.

Results

The mean serum galectin-3 level was 5103 pg/ml. Galectin-3 levels correlated significantly with the glucose disposal rate (R = 0.71, P < 0.001), fasting insulin (R = −0.56, P < 0.01), homeostasis model assessment for insulin resistance (R = −0.52, P < 0.05), and the insulin sensitivity index (R = 0.62, P < 0.005). Galectin-3 levels also positively correlated with the serum adiponectin level (R = 0.61, P < 0.05), but not with the high-sensitive C-reactive protein and interleukin-6 and −10.

Conclusions

These results suggest that low levels of serum galectin-3 are associated with insulin resistance in patients with type 2 diabetes.

Keywords

Galectin-3 Insulin resistance Type 2 diabetes mellitus

Background

Galectin-3 is a family of soluble beta-galactoside-binding lectins that play important regulatory roles in inflammation[1]. Galectin-3 has been reported to be a predictor of prognosis of heart failure[2]. In type 2 diabetes, it was reported that systemic galectin-3 is elevated in obesity and is negatively correlated with glycated hemoglobin[3]. Galectin-3 was also increased in the serum of patients with elevated C-reactive protein. Compared with hepatic and systemic venous serum, galectin-3 was higher in the portal venous serum suggesting that the splanchnic region is a major site of galectin-3 synthesis. The lower levels of galectin-3 in the hepatic venous serum compared with the portal venous serum demonstrate that galectin-3 is removed by the hepatic system.

However, the pathophysiology of galectin-3 in diabetes is not well-known. One report, using an animal model, found that galectin-3+/+mice developed delayed and sustained hyperglycemia in streptozotocin-induced diabetes, mononuclear cellular infiltration and reduced insulin content of islets[4]. This was also accompanied by the expression of proinflammatory cytokines[4]. Galectin-3−/− mice were relatively resistant to diabetogenesis as evaluated by measurements of glycemia, quantitative histology and insulin. Thus, galectin-3 is involved in immune mediated beta cell damage and is required for diabetogenesis in this model of the disease. Another study has revealed that the role of endogenous galectin-3 in beta cell apoptosis in the inflammatory milieu that occurs during diabetes pathogenesis, implicates impairment of the mitochondrial apoptotic pathway as a key event in the protection from beta cell apoptosis in the absence of galectin-3[5]. However, galectin-3 over-expression protected beta-cells from the cytotoxic effect of IL-1beta[6]. Moreover, Pang et al. showed that young (12-week-old) galectin-3 deficient mice fed a standard diet exhibited altered glucose homeostasis in the absence of obesity and associated abnormalities, thus suggesting a direct positive modulation of beta-cell function by galectin-3 independent of obesity-related inflammation[7]. A recent animal study reported that obese galectin-3−/− mice have increased body weight, total visceral adipose tissue, fasting blood glucose and insulin levels, homeostasis model assessment of insulin resistance (HOMA-IR), and markers of systemic inflammation compared with diet-matched wild-type animals[8]. Obesity induced by accelerated high fat diet in galectin-3-deficient mice was associated with systemic inflammation. Increased levels of interleukin (IL)-6 and reduced levels of IL-10 in the sera of obese galectin-3-deficient mice might contribute to amplified obesity-induced inflammation.

These results suggest that a low serum galectin-3 level is associated with hyperinsulinemia, insulin resistance and inflammation in type 2 diabetes. Furthermore, these reports suggest that a serum galectin-3 level is associated with beta cell function. Therefore, we hypothesize that low serum galectin-3 could be associated with insulin resistance and beta cell function in patients with type 2 diabetes. We measured serum galectin-3 levels in type 2 diabetes patients, and performed a glucose clamp method and a meal tolerance test (MTT) to evaluate insulin resistance and beta cell function.

Methods

Subjects

Twenty participants were subjected to a glucose clamp test and an MTT. Type 2 diabetes mellitus was diagnosed based on the criteria of the Japan Diabetes Society (JDS)[9]. The mean age of the patients was 53.6 years, mean BMI was 28.0 kg/m2, mean waist circumference was 95.8 cm, mean fasting plasma glucose (FPG) was 7.60 mmol/L and mean HbA1c was 7.25% (55 mmol/mol) (Table 1). Patients with ischemic heart disease, heart failure, pancreatic disease, liver disease, renal failure, or those taking diabetogenic medications such as corticosteroids were excluded from the study. Seven patients were on diet therapy alone and 13 were using oral hypoglycemic agents, including five on α-glucosidase inhibitors, five on dipeptidyl peptidase inhibitors, three on sulfonylurea, three on glinides and three on biguanides. None of the patients were using thiazolidinediones or insulin injections.
Table 1

Patient characteristics

N

20

Fasting insulin (pmol/L)

68.3 ± 41.6

Gender (male/female)

13/7

HOMA-IR

3.77 ± 2.33

Age (years)

53.6 ± 11.4

ISI

4.32 ± 2.26

BMI (kg/m2)

28.0 ± 3.8

Insulinogenic index

97.3 ± 117.1

Waist circumstance (cm)

95.8 ± 8.8

AUC glucose (mmol/L•h)

19.6 ± 3.5

FPG (mmol/L)

7.60 ± 1.18

AUC insulin (pmol/L•h)

448.0 ± 265.4

HbA1c (NGSP) (%)

7.25 ± 0.71

AUC insulin/AUC glucose

23.8 ± 14.3

(mmol/mol)

(55 ± 8)

hs-CRP (mg/dL)

0.16 ± 0.13

LDL-C (mmol/L)

3.33 ± 0.85

IL-6 (pg/ml)

2.96 ± 3.52

TG (mmol/L)

1.80 ± 0.89

IL-10 (pg/ml)

4.15 ± 2.93

HDL-C (mmol/L)

1.29 ± 0.37

adiponectin (μg/mL)

6.76 ± 3.57

GDR (mg · kg−1 · min−1)

5.33 ± 2.04

Proinsulin (pmol/L)

3.73 ± 3.32

Galectin-3 (pg/mL)

5103 ± 2239

Proinsulin/insulin ratio

0.09 ± 0.10

Data are means ± standard deviation.

BMI, body mass index; HbA1c, hemoglobin A1c; NGSP, National Glycohemoglobin Standardization Program; FPG, fasting plasma glucose; LDL-C, low-density lipoprotein cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, homeostasis model assessment of insulin resistance; ISI, insulin sensitivity index; AUC, area under the concentration–time curve; hs-CRP high-sensitive C reactive protein; IL, interleukin; GDR, glucose disposal rate.

This study was approved by the Ethics Committee of the Faculty of Medicine, Tottori University and was conducted in compliance with the ethical principles of the Declaration of Helsinki. Informed consent was obtained from all of the patients using a procedure approved by the Ethics Committee.

Meal tolerance test

After fasting for at least 12 h, the participants visited a morning clinic and consumed a test meal (total calories 460 kcal, carbohydrates 56.5 g, fat 18.0 g; protein 18.0 g) prepared by the JDS (JANEF E460F18, Kewpie Corporation, Tokyo, Japan)[10]. Plasma glucose and insulin were measured at 0 (fasting), 30, 60, 120, and 180 min after the meal. Plasma glucose was measured using the glucose oxidase method and plasma insulin using chemiluminescent immunoassays (CLIA) (human insulin CLIA kits, Kyowa Medix, Tokyo, Japan). Plasma insulin was defined as immunoreactive insulin (IRI). This method, using the meal tolerance test (MTT), is a well-established method in our hospital[11, 12].

HbA1c (JDS) was measured by high-performance liquid chromatography and was converted to National Glycohemoglobin Standardization Program (NGSP) values using the following certified equation, NGSP (%) = 1.02 × JDS (%) + 0.25%[13]. HbA1c (NGSP) values were also converted to International Federation of Clinical Chemistry (IFCC) values (mmol/mol) using the HbA1c converter developed by the National Institutes of Diabetes and Digestive and Kidney Diseases[14].

Euglycemic–hyperinsulinemic clamp

Glucose clamp studies were performed 2 days after the MTT. The patients were examined in the morning after an overnight fast. An antecubital vein was cannulated to administer the infusate. A dorsal vein was cannulated and kept warm to facilitate venous sampling and provide arterialized venous blood. Using an artificial endocrine pancreas (STG 55; Nikkiso, Shizuoka, Japan), the euglycemic–hyperinsulinemic clamp was performed to determine insulin sensitivity in peripheral tissues[15]. A primed constant infusion of insulin (100 mU/m2 · min) and computer-controlled exogenous infusion of glucose solution were used to achieve steady-state plasma insulin levels and maintain plasma glucose levels at 5.2 mmol/L (95 mg/dL). Using the insulin infusion protocol as previously reported, the steady-state plasma insulin level was 1200 pmol/L in patients with type 2 diabetes[16, 17]. The steady-state glucose infusion rate (GIR) was calculated at 90–120 min, and the mean GIR during that time was used as a marker of peripheral insulin sensitivity. The mean GIR was defined as the glucose disposal rate (GDR). The glucose clamp method is a well-established procedure in our hospital[18]. Some of the data of the current study were already published in the previous study[18].

Galectin-3, adiponectin, hs-CRP, IL-6, IL-10 and proinsulin assays

An enzyme-linked immunosorbent assay (ELISA) kit was used for measuring galectin-3 (Human Galectin-3 Assay Kit, Immuno-Biological Laboratories Co., Gunma, Japan)[19], plasma adiponectin (human adiponectin ELISA kit, Otsuka, Tokyo, Japan), plasma high-sensitive C reactive protein (hs-CRP) (human hs-CRP ELISA kit, Otsuka, Tokyo, Japan), plasma interleukin-6 (IL-6) and interleukin-10 (IL-10) (human IL-6, IL-10 Quantikine ELISA, R & D Systems, Inc., Minneapolis, USA) and plasma proinsulin (human intact proinsulin ELISA kit, Biovendor, Heidelberg, Germany).

Calculation of insulin resistance and secretion indices

HOMA-IR was calculated by FPG (mmol/L) × fasting IRI (F-IRI pmol/L)/135[20]. The insulin sensitivity index (ISI) was calculated by 10,000/√{[FPG (mmol/L) × F-IRI (pmol/L)] × [mean glucose × mean insulin during MTT]}[21]. Insulinogenic index was measured by [insulin (pmol/L) at 30 min – insulin (pmol/L) at 0 min]/[glucose (mmol/L) at 30 min – glucose (mmol/L) at 0 min][22].

Statistical analyses

Data are expressed as means ± standard error of the mean. The area under the curve (AUC) was calculated according to the trapezoidal rule. Correlations between parametric clinical variables and the galectin-3 were determined by Pearson’s correlation analysis. Multiple regression analysis was performed to examine an influencing factor of the serum galectin-3 level, the independent variables were: age, gender, BMI, waist circumference, FPG, HbA1c, fasting insulin, HOMA-IR, Insulinogenic Index, GDR, hs-CRP, IL-6, IL-10, proinsulin/insulin ratio, adiponectin, and triglyceride (TG). Values of P <0.05 were considered significant. SPSS software version 15.0 (SPSS, Chicago, IL, USA) was used for all analyses.

Results

Serum galectin-3 level of all participants was 5103 pg/mL (Table 1). The hs-CRP was 0.16 mg/d and adiponectin was 6.76 μg/mL. The FPG result of the MTT was 7.6 mmol/L, and the 2 h postprandial glucose was 10.6 mmol/L (Figure 1-a). Fasting insulin was 68.3 pmol/L and the 2 h postprandial insulin was 299.6 pmol/L (Figure 1-b). HOMA-IR was 3.77, ISI was 4.32 and the insulinogenic index was 97.3 (Table 1). During the steady state of glucose clamps, GDR was 5.33 mg · kg−1 · min−1 and the insulin level was 1159 ± 411 pmol/L. All results are given as means.
Figure 1

Plasma glucose and insulin responses during the meal tolerance test. Plasma glucose response during the meal tolerance test (a), and insulin response (b) during the meal tolerance test.

Galectin-3 level strongly correlated with the GDR in the glucose clamp method (R = 0.71, P <0.001) (Table 2, Figure 2-a). Galectin-3 level negatively correlated with fasting insulin (R = −0.56, P <0.01) (Figure 2-b), and HOMA-IR (R = −0.52, P <0.05) (Figure 2-c). Galectin-3 level also positively correlated with the ISI in MTT (R = 0.62, P <0.005) (Figure 2-d) and with adiponectin (R = 0.61, P <0.05) (Figure 2-e). The AUC of glucose did not correlate with galectin-3 (R = −0.02, P = 0.92). The AUC of insulin and the ratio of AUC-insulin/AUC-glucose had a tendency to correlate with galectin-3, but this was not significant (R = −0.41, P = 0.06; R = −0.44, P = 0.05, respectively) (Table 2). The insulinogenic index had a tendency for negative correlation with galectin-3, but was not significant (R = −0.22, P = 0.33) (Table 2). The proinsulin/insulin ratio had a tendency for positive correlation with galectin-3, but again, was not significant (R = 0.30, P = 0.20) (Table 2, Figure 2-f). There were no significant correlations between galectin-3 and FPG, HbA1c, BMI, waist circumstance, lipid profiles, hs-CPR, IL-6 and IL-10 (Table 2).
Table 2

Correlation coefficients between serum galectin-3 concentrations and other parameters

Correlation of galectin-3 with

Pearson correlation

P value

GDR

0.71

< 0.001

Fasting insulin

−0.56

< 0.01

HOMA-IR

−0.52

< 0.05

ISI

0.62

< 0.005

Insulinogenic Index

−0.22

0.33

AUC glucose

−0.02

0.92

AUC insulin

−0.41

0.06

AUC insulin/AUC glucose

−0.44

0.05

hs-CRP

−0.25

0.27

IL-6

0.08

0.75

IL-10

−0.15

0.53

Proinsulin/insulin ratio

0.30

0.20

adiponectin

0.61

< 0.05

BMI

−0.17

0.48

waist circumference

−0.24

0.29

FPG

0.11

0.61

HbA1c

−0.10

0.66

LDL-C

0.27

0.23

TG

−0.14

0.52

HDL-C

0.28

0.21

Correlation coefficients were determined using Pearson’s product moment correlation coefficient test.

GDR, glucose disposal rate; HOMA-IR, homeostasis model assessment of insulin resistance; ISI, insulin sensitivity index; AUC, area under the concentration–time curve; hs-CRP, high-sensitive C reactive protein; IL, interleukin; BMI, body mass index; FPG, fasting plasma glucose; LDL-C, low-density lipoprotein cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein cholesterol.

Figure 2

Correlation between galectin-3 and other parameters. Correlations between galectin-3 and GDR (a), fasting insulin (b), HOMA-IR (c), ISI (d), adiponectin (e), and proinsulin/insulin (PI/I) ratio (f) were calculated by simple regression analysis.

Using multiple regression analysis, we examined influence factors of serum galectin-3 level. The independent variables were: age, gender, BMI, waist circumference, FPG, HbA1c, fasting insulin, HOMA-IR, Insulinogenic Index, GDR, hs-CRP, IL-6, IL-10, proinsulin/insulin ratio, adiponectin, and TG. The significant standard partial regression coefficient was GDR 0.898 (P < 0.05) (Table 3).
Table 3

Multiple regression analysis to examine an influencing factor of the galectin-3

R2 = 0.767 R = 0.876

Partial regression coefficients

Standard partial regression coefficients

P value

Age

0.329

0.055

0.93

Gender

−0.007

0.503

0.38

BMI

−1.667

0.723

0.17

Waist circumference

−0.2481

−0.871

0.05

FPG

0.125

−0.829

0.08

HbA1c

−0.102

0.080

0.89

Fasting insulin

−0.564

−0.837

0.07

HOMA-IR

0.023

−0.098

0.337

Insulinogenic Index

0.402

−0.066

0.480

GDR

0.713

0.898

0.03

hs-CRP

−0.257

0.355

0.55

IL-6

−0.075

−0.196

0.75

IL-10

−0.146

0.274

0.65

Proinsulin/insulin ratio

0.297

0.833

0.08

adiponectin

0.614

−0.394

0.51

TG

−0.110

−0.266

0.66

The independent variables were: age, gender, BMI, waist circumference, FPG, HbA1c, fasting insulin, HOMA-IR, Insulinogenic Index, GDR, hs-CRP, IL-6, IL-10, proinsulin/insulin ratio, adiponectin, and TG. The significant standard partial regression coefficient was GDR 0.898 (P < 0.05).

BMI, body mass index; FPG, fasting plasma glucose; HOMA-IR, homeostasis model assessment of insulin resistance; GDR, glucose disposal rate; hs-CRP, high-sensitive C reactive protein; IL, interleukin; TG, triglyceride.

Discussion

This study indicates that low serum galectin-3 concentrations strongly correlates with insulin resistance and hyperinsulinemia, evaluated by glucose clamp method, HOMA-IR, and ISI. Another study reported that obese galectin-3 knockout mice had increased fasting blood glucose and insulin levels, HOMA-IR and markers of systemic inflammation compared with diet-matched wild type animals[8]. Our study indicates that low levels of serum galectin-3 in patients with type 2 diabetes have insulin resistance and hyperinsulinemia similar to galectin-3 knockout mice. Although the area under the curve for glucose, for insulin and for the ratio insulin/glucose was not significantly associated with galectin-3 levels, there were significant associations between galection-3 and GDR, HOMA-IR, and ISI. These results suggested that the concentration of galectin-3 mainly affects insulin resistance rather than glucose levels.

Furthermore, galectin-3 was strongly correlated with adiponectin, which is an insulin sensitizer molecule. Pang et al. demonstrate the development of excess adiposity and systemic inflammation in galectin-3 deficiency that was associated with impaired fasting glucose levels and reduced adipose tissue expression of adiponectin and PPARγ[7]. These results suggest that the concentrations of galectin-3 and adiponectin are low in type 2 diabetes patients with insulin resistance, indicating that the combination of low galectin-3 and adiponectin induce strong insulin resistance.

An animal study reported that CRP and IL-6 were significantly increased in the sera of galectin-3 deficient mice given a high-fat diet, whereas the levels of IL-10 were significantly decreased compared with the diet-matched wild type mice[8]. In our study, hs-CRP, IL-6 and IL-10 were not correlated with galectin-3. IL-10 has a protective role in type 2 diabetes by increasing insulin sensitivity in skeletal muscle[23]. We presumed that low levels of plasma galectin-3 and IL-10 reflect insulin sensitivity in skeletal muscle, because the glucose clamp technique mainly reflects insulin sensitivity in skeletal muscle. However, there was no correlation between IL-10 and galectin-3 levels in this study. Further investigations are needed because the pathophysiology of type 2 diabetes patients may be different from that of galectin-3 knockout mice. We consider that galectin-3 is associated with adiponectin rather than inflammation in patients with type 2 diabetes.

In our study, galectin-3 had a weak tendency towards negative correlation with the insulinogenic index, and a positive correlation with the proinsulin/insulin ratio. The proinsulin/insulin ratio is a marker of beta cell stress[12]. Galectin-3−/− mice were relatively resistant to diabetogenesis as evaluated by glycemia, quantitative histology and insulin content in streptozotocin induced diabetes[4]. These results imply that low levels of serum galectin-3 induce insulin resistance and hyperinsulinemia, but also may protect beta cell function. However, galectin-3 over-expression protected beta-cells from the cytotoxic effect of IL-1beta[6]. Moreover, young (12-week-old) galectin-3 deficient mice fed a standard diet exhibited altered glucose homeostasis in the absence of obesity and associated abnormalities[7]. Thus suggesting a direct positive modulation of beta-cell function by galectin-3 independent of obesity-related inflammation. In this study, there was no significant association, because one patient with low galectin-3 showed high PI/I ratio. The small number of our study has limitations, further investigations are needed. As the multiple regression analysis shows, we consider that galectin-3 is associated with insulin resistance rather than insulin secretion in patients with type 2 diabetes.

Galectin-3 is also one of the pattern recognition receptors that bind and mediate the degradation of modified lipoproteins and advanced glycation end products (AGE)[24]. In contrast to other receptors for AGE, galectin-3 protects from AGE-induced tissue injury. Therefore, galectin-3 ablation accelerates AGE-induced atherogenesis[25]. These results suggest that low levels of serum galectin-3 also induce atherosclerosis, and therefore, galectin-3 is an important molecule in type 2 diabetes.

Our study has several limitations, including the small number of patients and the variable nature of the medications for diabetes used by the study participants. Thus, our results require confirmation by a larger study. It is possible that the different medications used by the subjects modified the insulin responses in the MTT. For instance, metformin has been associated with lower systemic galectin-3[3]. In our study, three patients were treated with metformin, which could have affected galectin-3 levels. A control group of insulin resistant non-diabetic subjects would be helpful in this regard, we are investigating a control group of insulin resistant non-diabetic subjects now. Despite these limitations, we consider that our study contributes to better understanding of the pathophysiology of type 2 diabetes.

Conclusion

Our results suggest that low levels of serum galectin-3 are associated with insulin resistance in patients with type 2 diabetes.

Abbreviations

AUC: 

Area under the curve

AGE: 

Advanced glycation end product

ELISA: 

Enzyme-linked immunosorbent assay

FPG: 

Fasting plasma glucose

GDR: 

Glucose disposal rate

GIR: 

Glucose infusion rate

HOMA-IR: 

Homeostasis model assessment for insulin resistance

hs-CRP: 

high-sensitive C-reactive protein

IL: 

Interleukin

IRI: 

Immunoreactive insulin

ISI: 

Insulin sensitivity index

JDS: 

Japan Diabetes Society

MTT: 

Meal tolerance test.

Declarations

Acknowledgments

This study was supported by the Japan Diabetes Foundation (2013), grants for young researchers from the Japan Association for Diabetes Education and Care (2013), Tottori University Faculty of Medicine Research Grant (2013) and Tottori University Hospital Research Grant (2012, 2013). We thank Ms. Haruka Okada, Ms. Yoshiko Oda, and Ms. Maki Kameda for her excellent technical assistance. This work was carried out at Tottori University Faculty of Medicine, Tottori, Japan.

Authors’ Affiliations

(1)
Division of Cardiovascular Medicine, Endocrinology and Metabolism, Department of Molecular Medicine and Therapeutics, Tottori University Faculty of Medicine
(2)
Department of Regional Medicine, Tottori University Faculty of Medicine
(3)
School of Health Science, Tottori University Faculty of Medicine
(4)
Department of Molecular Biochemistry and Clinical Investigation, Osaka University Graduate School of Medicine

References

  1. Yang RY, Rabinovich GA, Liu FT: Galectins: Structure, function and therapeutic potential. Expert Rev Mol Med. 2008, 13: e17-e39.View ArticleGoogle Scholar
  2. de Boer RA, Lok DJ, Jaarsma T, van der Meer P, Voors AA, Hillege HL, van Veldhuisen DJ: Predictive value of plasma galectin-3 levels in heart failure with reduced and preserved ejection fraction. Ann Med. 2011, 43: 60-68. 10.3109/07853890.2010.538080.PubMed CentralView ArticlePubMedGoogle Scholar
  3. Weigert J, Neumeier M, Wanninger J, Bauer S, Farkas S, Scherer MN, Schnitzbauer A, Schäffler A, Aslanidis C, Schölmerich J, Buechler C: Serum galectin-3 is elevated in obesity and negatively correlates with glycosylated hemoglobin in type 2 diabetes. J Clin Endocrinol Metab. 2010, 95: 1404-1411. 10.1210/jc.2009-1619.View ArticlePubMedGoogle Scholar
  4. Mensah-Brown EP, Al Rabesi Z, Shahin A, Al Shamsi M, Arsenijevic N, Hsu DK, Liu FT, Lukic ML: Targeted disruption of the galectin-3 gene results in decreased susceptibility to multiple low dose streptozotocin-induced diabetes in mice. Clin Immunol. 2009, 130: 83-88. 10.1016/j.clim.2008.08.024.View ArticlePubMedGoogle Scholar
  5. Saksida T, Nikolic I, Vujicic M, Nilsson UJ, Leffler H, Lukic ML, Stojanovic I, Stosic-Grujicic S: Galectin-3 deficiency protects pancreatic islet cells from cytokine-triggered apoptosis in vitro. J Cell Physiol. 2013, 228: 1568-1576. 10.1002/jcp.24318.View ArticlePubMedGoogle Scholar
  6. Karlsen AE, Størling ZM, Sparre T, Larsen MR, Mahmood A, Størling J, Roepstorff P, Wrzesinski K, Larsen PM, Fey S, Nielsen K, Heding P, Ricordi C, Johannesen J, Kristiansen OP, Christensen UB, Kockum I, Luthman H, Nerup J, Pociot F: Immune-mediated beta-cell destruction in vitro and in vivo-A pivotal role for galectin-3. Biochem Biophys Res Commun. 2006, 344: 406-415. 10.1016/j.bbrc.2006.03.105.View ArticlePubMedGoogle Scholar
  7. Pang J, Rhodes DH, Pini M, Akasheh RT, Castellanos KJ, Cabay RJ, Cooper D, Perretti M, Fantuzzi G: Increased adiposity, dysregulated glucose metabolism and systemic inflammation in Galectin-3 KO mice. PLoS One. 2013, 8: e57915-10.1371/journal.pone.0057915.PubMed CentralView ArticlePubMedGoogle Scholar
  8. Pejnovic N, Pantic J, Jovanovic I, Radosavljevic G, Milovanovic M, Nikolic I, Zdravkovic NS, Djukic AL, Arsenijevic NN, Lukic ML: Galectin-3 deficiency accelerates high-fat diet induced obesity and amplifies inflammation in adipose tissue and pancreatic islets. Diabetes. 2013, 62: 1932-1944. 10.2337/db12-0222.PubMed CentralView ArticlePubMedGoogle Scholar
  9. Kuzuya T, Nakagawa S, Satoh J, Kanazawa Y, Iwamoto Y, Kobayashi M, Nanjo K, Sasaki A, Seino Y, Ito C, Shima K, Nonaka K, Kadowaki T: Committee of the Japan Diabetes Society on the diagnostic criteria of diabetes mellitus: Report of the Committee on the classification and diagnostic criteria of diabetes mellitus. Diabetes Res Clin Pract. 2002, 55: 65-85. 10.1016/S0168-8227(01)00365-5.View ArticlePubMedGoogle Scholar
  10. Yoshino G, Tominaga M, Hirano T, Shiba T, Kashiwagi A, Tanaka A, Tada N, Onuma T, Egusa G, Kuwashima M, Sanke T, Oikawa S, Honda K, Tachikawa T: The test meal A:A pilot model for the international standard of test meal for an assessment of both postprandial hyperglycemia and hyperlipidemia. J Jpn Diabetes Soc. 2006, 49: 361-371.Google Scholar
  11. Sumi K, Ohkura T, Yamamoto N, Fujioka Y, Matsuzawa K, Izawa S, Shiochi H, Kinoshita H, Ohkura H, Kato M, Yamamoto K, Taniguchi SI: Long-term miglitol administration suppresses postprandial glucose-dependent insulinotropic polypeptide secretion. Diabetol Int. 2013, 4: 190-196. 10.1007/s13340-013-0116-0.View ArticleGoogle Scholar
  12. Ohkura T, Inoue K, Fujioka Y, Nakanishi R, Shiochi H, Sumi K, Yamamoto N, Matsuzawa K, Izawa S, Ohkura H, Kato M, Yamamoto K, Taniguchi SI: The proinsulin/insulin (PI/I) ratio is reduced by postprandial targeting therapy in type 2 diabetes mellitus: a small-scale clinical study. BMC Res Notes. 2013, 6: 453-10.1186/1756-0500-6-453.PubMed CentralView ArticlePubMedGoogle Scholar
  13. Kashiwagi A, Kasuga M, Araki E, Oka Y, Hanafusa T, Ito H, Tominaga M, Oikawa S, Noda M, Kawamura T, Sanke T, Namba M, Hashiramoto M, Sasahara T, Nishio Y, Kuwa K, Ueki K, Takei I, Umemoto M, Murakami M, Yamakado M, Yatomi Y, Ohashi H: Committee on the Standardization of Diabetes Mellitus-Related Laboratory Testing of Japan Diabetes Society, “International clinical harmonization of glycated hemoglobin in Japan: From Japan Diabetes Society to National Glycohemoglobin Standardization Program values. J Diabetes Invest. 2012, 3: 39-40. 10.1111/j.2040-1124.2012.00207.x.View ArticleGoogle Scholar
  14. National Institutes of Diabetes and Digestive and Kidney Diseases, the HbA1c converter, [article online]. 1999, Available from http://www.ngsp.org/convert1.asp
  15. DeFronzo RA, Tobin JD, Andres R: Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol. 1979, 237: 214-223.Google Scholar
  16. Kawamori R, Matsuhisa M, Kinoshita J, Mochizuki K, Niwa M, Arisaka T, Ikeda M, Kubota M, Wada M, Kanda T, Ikebuchi M, Tohdo R, Yamasaki Y: Pioglitazone enhances splanchnic glucose uptake as well as peripheral glucose uptake in non-insulin-dependent diabetes mellitus. AD-4833 Clamp-OGL Study Group. Diabetes Res Clin Pract. 1998, 41: 35-43. 10.1016/S0168-8227(98)00056-4.View ArticlePubMedGoogle Scholar
  17. Tamura Y, Tanaka Y, Sato F, Choi JB, Watada H, Niwa M, Kinoshita J, Ooka A, Kumashiro N, Igarashi Y, Kyogoku S, Maehara T, Kawasumi M, Hirose T, Kawamori R: Effects of diet and exercise on muscle and liver intracellular lipid contents and insulin sensitivity in type 2 diabetic patients. J Clin Endocrinol Metab. 2005, 90: 3191-3196. 10.1210/jc.2004-1959.View ArticlePubMedGoogle Scholar
  18. Ohkura T, Shiochi H, Fujioka Y, Sumi K, Yamamoto N, Matsuzawa K, Izawa S, Kinoshita H, Ohkura H, Kato M, Taniguchi SI, Yamamoto K: 20/(fasting C-peptide x fasting plasma glucose) is a simple and effective index of insulin resistance in patients with type 2 diabetes mellitus: a preliminary report. Cardiovasc Diabetol. 2013, 12: 21-10.1186/1475-2840-12-21.PubMed CentralView ArticlePubMedGoogle Scholar
  19. Inohara H, Segawa T, Miyauchi A, Yoshii T, Nakahara S, Raz A, Maeda M, Miyoshi E, Kinoshita N, Yoshida H, Furukawa M, Takenaka Y, Takamura Y, Ito Y, Taniguchi N: Cytoplasmic and serum galectin-3 in diagnosis of thyroid malignancies. Biochem Biophys Res Commun. 2008, 376: 605-610. 10.1016/j.bbrc.2008.09.041.View ArticlePubMedGoogle Scholar
  20. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC: Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985, 28: 412-419. 10.1007/BF00280883.View ArticlePubMedGoogle Scholar
  21. Matsuda M, DeFronzo RA: Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp. Diabetes Care. 1999, 22: 1462-1470. 10.2337/diacare.22.9.1462.View ArticlePubMedGoogle Scholar
  22. Seltzer HS, Allen EW, Herron AL, Brennan MT: Insulin secretion in response to glycemic stimulus: relation of delayed initial release to carbohydrate intolerance in mild diabetes mellitus. J Clin Invest. 1967, 46: 323-335. 10.1172/JCI105534.PubMed CentralView ArticlePubMedGoogle Scholar
  23. Hong EG, Ko HJ, Cho YR, Kim HJ, Ma Z, Yu TY, Friedline RH, Kurt-Jones E, Finberg R, Fischer MA, Granger EL, Norbury CC, Hauschka SD, Philbrick WM, Lee CG, Elias JA, Kim JK: Interleukin-10 prevents diet induced insulin resistance by attenuating macrophage and cytokine response in skeletal muscle. Diabetes. 2009, 58: 2525-2535. 10.2337/db08-1261.PubMed CentralView ArticlePubMedGoogle Scholar
  24. Zhu W, Sano H, Nagai R, Fukuhara K, Miyazaki A, Horiuchi S: The role of galectin-3 in endocytosis of advanced glycation end products and modified low density lipoproteins. Biochem Biophys Res Commun. 2001, 280: 1183-1188. 10.1006/bbrc.2001.4256.View ArticlePubMedGoogle Scholar
  25. Iacobini C, Menini S, Ricci C, Scipioni A, Sansoni V, Cordone S, Taurino M, Serino M, Marano G, Federici M, Pricci F, Pugliese G: Accelerated lipid-induced atherogenesis in galectin-3-deficient mice: role of lipoxidation via receptor-mediated mechanisms. Arterioscler Thromb Vasc Biol. 2009, 29: 831-836. 10.1161/ATVBAHA.109.186791.View ArticlePubMedGoogle Scholar

Copyright

© Ohkura et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Advertisement