Lipocalin-2, glucose metabolism and chronic low-grade systemic inflammation in Chinese people

The design and recruitment of the population-based cross-sectional study has been described in detail elsewhere [14]. In 2007 China launched a national incidence trends of metabolic syndrome study. The data presented in this article are partially based on subsamples from Shanghai in eastern China (total 2598 subjects). All studied individuals came from the Simenerlu community of the Jingan District and the Jiangninglu community of the Putuo District in Shanghai, China. A multistage stratified cluster sampling method was used to select subjects from these two communities. Only one participant (> 50 year) was randomly selected from each household. In these 2598 subjects, 79 participants have previously diagnosed type 2 diabetes, all the others received the oral glucose tolerance test and 392 are newly diagnosed type 2 diabetes. In our study, all studied individuals were of southern Han Chinese ancestry and were residing in the metropolitan area of Shanghai aged 50-82 years. Briefly, a total of 2598 eligible participants (1106 men and 1492 women) were recruited. After excluding those who had previously diagnosed as type 2 diabetes and treated (n = 79), 2,519 individuals were eligible for the present analysis. Written consent was obtained from all the participants. The study was approved by the institutional review broad of Huashan Hospital.

A standardized questionnaire was used by trained physicians to collect information such as age, sex, smoking (yes/no), alcohol drinking (yes/no), and self-reported diabetes, hypertension, dyslipidemia. According to participants' responses to the corresponding questions, family history of diabetes was classified as yes or no.

All subjects were assessed after overnight fasting for at least 10 h. The details of anthropometric measurements including height, weight, waist circumference, hip circumference and blood pressure were carried by trained physicians. BMI was calculated as weight in kilograms divided by the square of height in meters and categorized as normal weight (< 24.0 kg/m²), or overweight (24-28 kg/m²), or obesity (≥ 28.0 kg/m²), according to the criteria for Chinese individuals [15].

Peripheral venous blood samples were collected. The fasting glucose, glucose 2 h after oral glucose tolerance test, total cholesterol, triglycerides, LDL-cholesterol and HDL-cholesterol were measured on an automatic analyzer (Hitachi 7080). Fasting insulin was determined by radioimmunoassay (Linco Research, St. Charles, MO). Insulin resistance was estimated using homeostasis model assessment index-insulin resistance (HOMA-IR).

Type 2 diabetes and prediabetes were defined by 2005 ADA criteria [16]. A fasting glucose level lower than 5.6 mmol/l and a 2 h OGTT plasma glucose level below 7.8 mmol/l were defined as normal glucose regulation (NGR). Impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) were defined as fasting glucose 5.6 to 6.9 mmol/l and 2 h OGTT plasma glucose 7.8 to 11.0 mmol/l respectively. Of 2519 participants, 392 had type 2 diabetes (screen-detected and treatment-naive), 335 had isolated-IFG (all screen-detected and treatment-naive), 353 had isolated-IGT (all screen-detected and treatment-naive), 296 had IFG + IGT (all screen-detected and treatment-naive) and 1143 had NGR.

The serum CRP, adiponectin, CXCL5 and lipocalin-2 were determined in duplicate by ELISA with Duoset kit (DY1707, DY1065, DY254 and DY1757, R&D Systems) as recommended by the manufacturer. The ELISA system had an intraassay coefficient of variation of 3.1-9.5% and an interassay coefficient of variation of 4.3-10.7%, respectively.

Normally distributed data were expressed as means ± SD, whereas variables with a skewed distribution were reported as median (interquartile range) and log transformed to approximate normality before analysis. Categorical variables were represented by frequency and percentage. Univariate and multivariable stepwise regression analysis were used to investigate the association of serum lipocalin-2 with clinical and biochemical characteristics. The stepwise regression procedure was used to obtain determinants of serum lipocalin-2, potential confounding variables including age, gender, smoking, alcohol drinking, family history of diabetes, serum CRP, serum adiponectin, serum CXCL5, HOMA-IR, BMI, waist circumference, and waist/hip ratio were controlled in the regression models. To study the association of impaired glucose regulation (IGR) with lipocalin-2, we defined subjects with normal glucose regulation as 0 (n = 1143), and impaired glucose regulation as 1 (n = 984), and excluded type 2 diabetic patients from logistic regression analysis. For the association of combined impaired glucose regulation and type 2 diabetes with lipocalin-2, we defined subjects with normal glucose regulation as 0 (n = 1143) and combined impaired glucose regulation and type 2 diabetes as 1 (n = 1376) in the logistic regression analyses. Homogeneity of groups was determined when the means showed significant differences. Means of these groups were compared by the Student-Newman-Keuls method. All statistical analysis was performed with the SPSS Statistical Package (version 13.0; SPSS Inc., Chicago, IL). A p value of less than 0.05 was considered to be statistically significant.

Our study involved 1143 subjects with NGR and 392 with newly diagnosed type 2 diabetes (Table 1). Among those with impaired glucose regulation, 335 had isolated IFG, 353 had isolated IGT, and 296 had IFG + IGT. There was no significant difference in sex distribution, alcohol drinking and serum LDL-c levels between these groups. The NGR and diabetes groups had the most favorable and unfavorable metabolic profiles, respectively. There was no significant difference in waist circumference, waist/hip ratio, and serum triacylglycerol levels between groups with isolated IFG, isolated IGT and IFG + IGT.

Body mass index, waist circumference, log₁₀ fasting serum insulin, log₁₀ HOMA-IR, total cholesterol, HDL-cholesterol and serum CXCL5 levels were independent determinants for serum lipocalin-2 concentrations in the stepwise linear regression analysis (Table 2). In univariate analysis, serum lipocalin-2 levels were closely associated with serum C-reactive protein (r = 0.131, p < 0.001). However, serum C-reactive protein was not an independent determinant for serum lipocalin-2 (p > 0.05).

Serum lipocalin-2 levels were significantly associated with fasting plasma glucose (r = 0.107, p < 0.001) and 2 h OGTT plasma glucose (r = 0.066, p = 0.009) in total population. Serum lipocalin-2 concentrations were significantly higher in subjects with isolated IFG, isolated IGT, IFG + IGT, and newly diagnosed type 2 diabetes compared with those of subjects with NGR (83.5, 92.4, 83.1, 89.2 ng/ml vs 69.2 ng/ml, respectively, all p < 0.01) after adjustment for age, gender, BMI, and family history of diabetes. There was no statistical difference between the four groups with glucose metabolism dysregulation (all p > 0.05, Figure 1).

Remarkably, as presented in Table 3, elevated lipocalin-2 was associated with increased risk of hyperglycemia. Elevated serum lipocalin indicated high risk for impaired glucose regulation (OR 1.30, 95% CI 1.23-1.62, p = 0.009) after adjustment for age, gender, smoking, alcohol drinking, family history of diabetes, serum CRP, serum adiponectin, serum CXCL5, HOMA-IR, BMI, waist/hip ratio, serum triacylglycerol, total cholesterol, HDL-cholesterol and LDL-cholesterol. The OR for subjects with impaired glucose regulation and type 2 diabetes was 1.31 (95% CI 1.21-1.69, p < 0.001).