Prevalence of positive islet autoantibody in type 2 diabetes patients: a cross-sectional study in a Chinese community

in Endocrine Connections
Authors:
Xiangyu Gao Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, China

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Wanwan Sun Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, China

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Yi Wang Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, China

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Yawen Zhang Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, China

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Rumei Li Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, China

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Jinya Huang Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, China

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Yehong Yang Department of Endocrinology, Huashan Hospital, Fudan University, Shanghai, China

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Correspondence should be addressed to Y Yang: yehongyang@fudan.edu.cn

*(X Gao, W Sun and Y Wang contributed equally to this work)

DOI:
https://doi.org/10.1530/EC-19-0379
Volume/Issue:
Volume 8: Issue 11
Page Range:
1493–1502
Article Type:
Research Article
Online Publication Date:
Nov 2019
Copyright:
© 2019 The authors 2019
Open access

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Background

Islet autoantibodies occur in type 2 diabetes. Our study aimed to investigate the prevalence of positive islet autoimmunity in community patients with type 2 diabetes.

Methods

A total of 495 community patients with type 2 diabetes were recruited using the method of cluster sampling in this cross-sectional study. Three islet autoantibodies including glutamic acid decarboxylase antibody (GADA), insulin autoantibody (IAA) and islet cell antibody (ICA) were measured, and clinical characteristics involved in those individuals were evaluated.

Results

The positive rate of islet autoantibodies was 28.5% in total, while combinations of different autoantibodies were rarely seen. Compared with GADA-negative group, positive counterparts significantly tended to have lower levels of body mass index (BMI), waist-hip ratio (WHR), and urinary microalbumin (mALB) (P < 0.05). Adjusted for confounding factors, WHR, triglycerides (TG), and mALB seemed to be negative independent predictors of GADA (OR < 1, P < 0.05). Patients with positive IAA tended to receive insulin treatment (P < 0.0001). Besides, fasting blood glucose (FBG), serum levels of high-density lipoprotein cholesterol (HDL-CH), aspartate transaminase (AST), and γ-glutamyltransferase (GGT) were more likely to be higher in IAA positive subgroup in comparison with the negative counterparts. While after AST was adjusted by unconditional logistic regression analysis, history of insulin treatment, FBG, HDL-CH, and GGT were confirmed as positive predictors of IAA. Furthermore, in patients who were IAA positive, those treated with exogenous insulin tended to have longer duration of diabetes than non-insulin treatment counterparts (P < 0.0001). With regard to ICA, however, there were no significant differences between the two subgroups, except that serum level of AST/ALT seemed to be slightly different (P = 0.064).

Conclusion

These data suggested that type 2 diabetic community patients with positive GADA tended to be lean and were able to maintain normal lipid metabolism, while patients with positivity of IAA were frequently accompanied with insulin treatment and more closely associated with diabetic liver damage.

Abstract

Background

Islet autoantibodies occur in type 2 diabetes. Our study aimed to investigate the prevalence of positive islet autoimmunity in community patients with type 2 diabetes.

Methods

A total of 495 community patients with type 2 diabetes were recruited using the method of cluster sampling in this cross-sectional study. Three islet autoantibodies including glutamic acid decarboxylase antibody (GADA), insulin autoantibody (IAA) and islet cell antibody (ICA) were measured, and clinical characteristics involved in those individuals were evaluated.

Results

The positive rate of islet autoantibodies was 28.5% in total, while combinations of different autoantibodies were rarely seen. Compared with GADA-negative group, positive counterparts significantly tended to have lower levels of body mass index (BMI), waist-hip ratio (WHR), and urinary microalbumin (mALB) (P < 0.05). Adjusted for confounding factors, WHR, triglycerides (TG), and mALB seemed to be negative independent predictors of GADA (OR < 1, P < 0.05). Patients with positive IAA tended to receive insulin treatment (P < 0.0001). Besides, fasting blood glucose (FBG), serum levels of high-density lipoprotein cholesterol (HDL-CH), aspartate transaminase (AST), and γ-glutamyltransferase (GGT) were more likely to be higher in IAA positive subgroup in comparison with the negative counterparts. While after AST was adjusted by unconditional logistic regression analysis, history of insulin treatment, FBG, HDL-CH, and GGT were confirmed as positive predictors of IAA. Furthermore, in patients who were IAA positive, those treated with exogenous insulin tended to have longer duration of diabetes than non-insulin treatment counterparts (P < 0.0001). With regard to ICA, however, there were no significant differences between the two subgroups, except that serum level of AST/ALT seemed to be slightly different (P = 0.064).

Conclusion

These data suggested that type 2 diabetic community patients with positive GADA tended to be lean and were able to maintain normal lipid metabolism, while patients with positivity of IAA were frequently accompanied with insulin treatment and more closely associated with diabetic liver damage.

Keywords: type 2 diabetes; community patients; islet autoantibody; clinical characteristics

Introduction

Diabetes mellitus is an acknowledged global chronic disease affecting multiple organ systems with complications ranging from acute conditions such as hyperosmolar hyperglycemic state (HHS), diabetic ketoacidosis (DKA) to chronic conditions including diabetic retinopathy, diabetic nephropathy, and diabetic neuropathy, nonalcoholic fatty liver disease (NAFLD) and cardiovascular disease (1). The incidence of diabetes is on worrisome rise globally, especially in China (2). Historically, based on positivity of islet autoantibodies, diabetes mellitus had been classified into two clinical types: type 1 diabetes (T1DM) and type 2 diabetes (T2DM) (3, 4). The progressive destruction of islet β cell mass caused by islet autoimmunity was considered to be the main etiology of T1DM (5, 6), whereas T2DM tended to be insulin resistant and islet autoimmunity seemed not to be involved in this progress (7). Besides, there was a special form of diabetes termed as latent autoimmune diabetes in adults (LADA), which had clinical phenotype of T2DM and islet autoimmunity positivity of T1DM, and previous studies suggested that it indeed was a subtype of T1DM (8, 9, 10). However, increasing notable discoveries had provided evidence supporting the notion that islet autoimmunity is also a vital component involved in the pathogenesis and development of classical T2DM (11, 12, 13, 14). Typical islet autoantibodies such as glutamic acid decarboxylase antibody (GADA), insulin autoantibody (IAA), and islet cell antibody (ICA), which were considered as biomarkers of classical T1DM, were also reported to be involved in the prevalence of T2DM in recent years. Moreover, associations between these islet autoantibodies and related clinical features in T2DM were observed (15, 16). Previous researches suggested that the positivity of GADA was associated with thyroid and adrenal autoimmunity (17, 18, 19), and one recent Chinese study reported that ICA was related to systemic inflammation and positivity of IAA was more closely associated with insulin treatment (12).

Nevertheless, most previous studies have mainly focused on inpatients or outpatients based on hospitals or clinics, whose poor representation of the whole population of diabetic patients in a certain region might lead to bias. Furthermore, few studies have addressed the correlation between clinical biochemical features such as lipid metabolism, liver and kidney function, and islet autoimmunity in patients with T2DM. In order to further explore the epidemic and clinical characteristics that are distinctively related to islet autoantibodies in community patients with T2DM, we performed a cross-sectional study using the method of cluster sampling, with a total of 495 diabetic patients recruited from Wu Jing community (Shanghai, China). Islet autoantibodies including GADA, IAA, ICA, and clinical biochemical characteristics referring to lipid metabolism, liver and renal function were all determined among each participant. Thus, our current study aimed to identify the prevalence of positive islet autoimmunity in community patients with T2DM and its potential correlative factors.

Material and methods

Study population

A total of 495 participants from Wu Jing community, Min Hang district, Shanghai, China were consecutively recruited during the period from January to November, 2017 in this cross-sectional study, we applied the method of cluster sampling which can largely represent the total population of T2DM in Shanghai and even the Yangtze river delta region. All characters were clinically diagnosed as T2DM based on the criteria of Chinese Diabetes Society. Those who were under condition of acute infection, allergic disease or other autoimmune diseases were excluded. Islet autoantibodies including GADA, IAA, ICA and clinical biochemical patterns were measured among each subject. The study protocol was approved by Ethics Committee of Basic Medical College of Fudan University (2016-Y028) and Huashan Hospital affiliated to Fudan University (2016-320), and written informed consent was also obtained from all of individuals.

Autoantibody evaluation

Serum levels of islet autoantibodies including GADA, IAA, ICA were determined by enzyme-linked immunesorbent assay (ELISA) in the Department of Clinical Laboratory in Huashan Hospital (Shanghai, China). All samples were measured in duplicate. GADA was detected by ELISA kit (Euroimmun AG, Lübeck, Germany) according to the instruction of the manufacturer, and its positive criteria were defined as ≥5 IU/mL. The sensitivity and specificity of GADA ELISA kit were 92 and 98% respectively based on the Diabetes Autoantibody Standardization Program (DASP 2003). IAA and ICA were determined by ELISA kits (Biomerica, USA). We recorded the spectrophotometric readings (optical density (OD) in absorbance units) from each pore and calculated the average OD reading of the reference pore, negative pore, and positive controls pore, and then divided the average OD of samples and controls by the average OD of reference. The interpretation of results of ratio value was negative if <0.95, positive if >1.05, and indeterminate (borderline) if 0.95–1.05.

Clinical data collection

The basic epidemiological information such as age, gender, height, weight, body mass index (BMI), waist and hip circumference, duration of diabetes, history of insulin treatment, and diabetic family history were all collected except that the data from 13 cases were not available. Fasting blood samples and random urine samples were collected among each individual, series of biochemical characteristics including fasting blood glucose (FBG), hemoglobin A1c (HbA1C), low-density lipoprotein cholesterol (LDL-CH), high-density lipoprotein-cholesterol (HDL-CH), triglycerides (TG), total cholesterol (TCHOL), alanine aminotransferase (ALT), aspartate transaminase (AST), AST/ALT, γ-glutamyltransferase (GGT), urine creatinine (Ucr), urinary microalbumin (mALB), mALB/Ucr, serum creatinine (CREA), serum uric acid (UA), urea were also evaluated.

Statistical analysis

Quantitative data were presented as mean ± s.d. or median (P25,P75) and categorical data were summarized using frequencies as well as proportions or percentages of patients. To compare the differences between two independent groups divided by whether the autoantibody is positive or not, independent samples t-test was used for parametric data and Mann–Whitney U test or chi-square test for non-parametric counterpart. Since Spearman correlation analysis cannot be used to assess the correlation between levels in one variable and the qualitative variable, we divided clinical biochemical parameters which were continuous variables into two parts according to their medians, then, they were allowed to become categorical variables. The relationships between islet autoantibodies and clinical features were performed using Spearman correlation analysis. Furthermore, unconditional logistic regression analyses (also called binary logistic regression analysis) was used to analyze the independent factors of islet autoantibodies after adjusting for possible confounding variables. P values <0.05 were considered statistically significant. All analyses were performed using SPSS, version 22.0 (IBM).

Results

Prevalence of three islet autoantibodies individually or in combination among community patients with T2DM

In the present cross-sectional study, total 495 T2DM patients in a Chinese community were enrolled, islet autoantibody measurement were collected and presented in Table 1. The percentage of patients who had GADA was 8.28%, IAA 20.8% and ICA 3.03%, with 28.3% (n = 141) having at least one of them. The combination of different autoantibodies occur as a relative lower proportion with GADA + IAA (2.22%, n = 11), IAA + ICA (1.21%, n = 6) and GADA + ICA (0.20%, n = 1). Patients positive for all these three autoantibodies were not observed (Table 1).

Table 1

Detection of serum islet autoantibodies individually or its combination in community diabetic patients.
Islet autoantibody or its combination Number of positive Positive rate (%)
GADA (individual) 41 8.28
IAA (individual) 103 20.8
ICA (individual) 15 3.03
GADA + IAA 11 2.22
IAA + ICA 6 1.21
GADA + ICA 1 0.20
GADA + IAA + ICA 0 0
GADA/IAA/ICA 141 28.5
Total number of cases 495 –

‘+’ means simultaneously positive; ‘/’ means at least one autoantibody positive.

GADA, glutamic acid decarboxylase autoantibodies; IAA, insulin autoantibodies; ICA, islet cell cytoplasmic autoantibodies.

Clinical and biochemical features of individual islet autoantibodies positive or negative subgroup

Epidemic and clinical characteristics of 482 patients (including 211 males and 271 females) were grouped in Table 2 according to positivity of individual islet autoantibody, 13 cases were excluded because of missing basic epidemiological information. Compared with GADA-negative group, GADA-positive counterparts tended to have significant lower levels of BMI, WHR, and mALB (P < 0.05). Moreover, the levels of TG (P = 0.056), Ucr (P = 0.077) and UA (P = 0.093) in GADA-positive group were trending lower compared with those in GADA-negative group, in spite of no statistical significance. As presented in Table 2. The percentage of patients who received insulin treatment in IAA-positive group (29.1%) was markedly higher than that in IAA-negative group (7.14%) (P < 0.0001), as well as the level of FBG, HDL-CH, AST, GGT (P < 0.05). Furthermore, in order to exclude the interference of exogenous insulin use, we divided 103 IAA-positive patients into two groups according to whether they received insulin treatment to see if there are any differences. Among all 103 IAA-positive patients, 30 patients received insulin treatment and the other 73 patients did not. All clinical and biochemical characteristics detected above were compared between the two groups except for Ucr, mALB, U-mALB/Ucr (because of quite amount of missing data in insulin treatment group). As shown in Supplementary Table 1 (see section on supplementary data given at the end of this article), the duration of diabetes was longer among the 30 IAA positive patients that received exogenous insulin treatment as compared with the 73 who were not insulin treated. Other variables showed no significant differences between the two groups. No significant differences of biochemical characteristics between ICA-positive and -negative subgroups were observed, except that the serum level of AST/ALT in positive participants seemed slightly higher than that in negative counterparts (P = 0.064). Differences between two subgroups divided by positivity of individual autoantibody were presented more intuitively in Fig. 1.

Figure 1
Figure 1

Significant differences between subgroups divided by positivity of GADA or IAA. (A, B and C) GADA-positive group presents lower levels of BMI,WHR and mALB in comparison with negative counterparts; (D, E, F, G and H) IAA-positive group tends to show higher rate of insulin treatment and higher levels of FBG, HDL-CH,AST and GGT than negative ones. All comparison tests between the two groups were performed using the statistical method of Mann–Whitney U test. *P < 0.05; **P < 0.01, ***P < 0.001 and ****P < 0.0001. BMI, body mass index; WHR, waist-hip ratio; mALB, urinary microalbumin; FBG, fasting blood glucose; HDL-CH, high-density lipoprotein (cholesterol); AST, aspartate transaminase; GGT, r-glutamyltransferase; GADA, glutamic acid decarboxylase autoantibodies; IAA, insulin autoantibodies.

Citation: Endocrine Connections 8, 11; 10.1530/EC-19-0379

Table 2

Clinical and biochemical characteristics of each group classified regarding the positivity of islet autoantibodies.
GADA negative GADA positive P value IAA negative IAA positive P value ICA negative ICA positive P value
Number of patients 454 (91.7%) 41 / 392 (79.2%) 103 (20.8%) / 480 (97.0%) 15 /
Age (years) 65.0 ± 6.56 64.1 ± 7.82 0.389 64.9 ± 6.42 65.0 ± 7.57 0.894 64.9 ± 6.63 65.1 ± 8.13 0.900
Gender (male/female) 196/246 (44.3/55.7%) 15/25 0.404 170/212 (44.5/55.5%) 41/59 0.530 203/265 (43.4/56.6%) 8/6 0.307
BMI (kg/m2) 24.5 ± 3.06 23.0 ± 2.67 0.006a 24.3 ± 2.98 24.5 ± 3.35 0.616 24.3 ± 3.07 24.9 ± 2.64 0.585
WHR 0.91 ± 0.06 0.88 ± 0.05 0.003a 0.91 ± 0.05 0.91 ± 0.06 0.833 0.91 ± 0.05 0.92 ± 0.07 0.447
Duration of diabetes (years) 8.00 ± 5.37 8.55 ± 5.52 0.516 8.03 ± 5.31 8.13 ± 5.67 0.911 8.09 ± 5.38 6.79 ± 5.39 0.328
Insulin treatment 51 7 0.267 28 30 <0.0001b 57 1 0.568
Diabetic family history 115 (25.3%) 10 0.888 98 27 0.785 121 (25.2%) 4 0.819
FBG (mmol/L) 7.24 ± 1.53 7.55 ± 2.57 0.483 7.23 ± 1.71 7.40 ± 1.32 0.023c 7.28 ± 1.65 6.83 ± 0.99 0.373
HbA1C (%) 7.02 ± 1.10 7.27 ± 1.25 0.243 7.02 ± 1.11 7.15 ± 1.12 0.259 7.05 ± 1.11 6.76 ± 1.04 0.367
LDL-CH (mmol/L) 2.33 ± 0.99 2.13 ± 0.72 0.206 2.32 ± 0.98 2.29 ± 0.95 0.740 2.31 ± 0.97 2.48 ± 0.92 0.513
HDL-CH (mmol/L) 1.04 ± 0.41 1.14 ± 0.43 0.125 1.02 ± 0.41 1.15 ± 0.37 0.005a 1.05 ± 0.41 1.01 ± 0.28 0.739
TG (mmol/L) 2.09 ± 1.60 1.67 ± 1.12 0.056 2.01 ± 1.45 2.21 ± 1.95 0.749 2.05 ± 1.56 2.10 ± 1.94 0.583
TCHOL (mmol/L) 4.29 ± 1.28 4.00 ± 0.99 0.109 4.23 ± 1.30 4.41 ± 1.08 0.179 4.27 ± 1.27 4.32 ± 0.83 0.915
ALT (U/L) 10.1 ± 6.72 9.44 ± 3.11 0.388 9.97 ± 6.56 10.5 ± 6.26 0.284 10.1 ± 6.56 8.40 ± 3.68 0.202
AST (U/L) 18.4 ± 10.5 17.7 ± 8.10 0.797 17.9 ± 10.7 19.9 ± 8.34 0.002a 18.3 ± 10.3 18.8 ± 9.73 0.721
AST/ALT 2.08 ± 0.97 2.03 ± 0.77 0.810 2.05 ± 0.94 2.17 ± 0.98 0.193 2.07 ± 0.96 2.29 ± 0.65 0.064
GGT (U/L) 18.5 (12.3, 29.8) 20.0 (14.0, 28.3) 0.464 20.0 (13.0, 27.0) 22.0 (15.8, 31.3) 0.047c 20.0 (14.0, 28.0) 25.0 (16.0, 67.0) 0.113
Ucr (μmol/L) 10127 ± 7147 7498 ± 3778 0.077 10240 ± 7247 8599 ± 5553 0.121 9956 ± 7021 9208 ± 5888 0.694
UREA (mmol/L) 5.24 ± 1.55 5.52 ± 1.35 0.208 5.23 ± 1.58 5.39 ± 1.33 0.295 5.26 ± 1.55 5.27 ± 0.95 0.955
mALB (mg/L) 6.53 (3.75, 22.9) 4.23 (3.00, 10.4) 0.01c 6.39 (3.40, 21.3) 5.70 (3.45, 23.7) 0.698 6.30 (3.40, 21.4) 8.75 (3.15, 65.7) 0.498
U-mALB/Ucr (mg/g) 9.17 (4.59, 22.8) 5.85 (4.70, 16.7) 0.221 8.82 (4.48, 21.8) 8.80 (5.28, 23.9) 0.332 8.80 (4.58, 21.9) 13.0 (6.46, 67.2) 0.250
CREA (μmol/L) 64.5 ± 19.4 61.8 ± 17.6 0.406 64.0 ± 19.6 65.3 ± 17.8 0.511 64.3 ± 19.4 65.2 ± 12.7 0.678
UA (μmol/L) 281 ± 88.5 261 ± 107 0.093 281 ± 92.2 273 ± 82.8 0.273 279 ± 91.1 297 ± 59.0 0.286

Data are showed as n (%), mean ± s.d. or median (P25, P75). P values refer to the comparison of the two subgroups by independent samples t-test or Mann–Whitney U test for continuous variables, and chi-square test for categorical variables. P value <0.05 was considered statistical significance. Significant differences are in bold and the significance level is indicated with superscript letters.

aP < 0.01, bP < 0.0001 and cP < 0.05,

ALT, alanine aminotransferase; AST, aspartate transaminase; BMI, body mass index; CREA, serum creatinine; FBG, fasting blood glucose; GADA, glutamic acid decarboxylase autoantibodies; GGT, γ-glutamyltransferase; HbA1c, hemoglobin A1c; HDL-CH, high-density lipoprotein (cholesterol); IAA, insulin autoantibodies; ICA, islet cell cytoplasmic autoantibodies; LDL-CH, low-density lipoprotein (cholesterol); mALB, urinary microalbumin; TCHOL, total cholesterol; TG, triglycerides; UA, serum uric acid; Ucr, urine creatinine; WHR, waist-hip ratio.

Correlation of islet autoantibodies with clinical characteristics in community diabetic patients

In order to explore the potential factors which might be related with islet autoimmunity in community patients with T2DM, we performed the Spearman correlation analysis between individual islet autoantibody and clinical features. As indicated in Table 3, BMI, WHR, TG, levels of mALB were significantly correlated with the levels of GADA in positive patients (r < 0, P < 0.05). Besides Ucr, UA levels were slightly negatively related to the levels of GADA in GADA-positive patients (P = 0.074, P = 0.059 respectively). With regard to IAA, history of insulin treatment, levels of FBG, HDL-CH, AST, GGT were positively correlated with the levels of IAA in IAA-positive patients (r > 0, P < 0.05). However, there were no factors that are related to the positivity of ICA, except for that serum level of AST/ALT which seemed mildly correlated (r = 0.083, P = 0.078).

Table 3

Correlation analysis between individual islet autoantibody and clinical features.
GADA positive (n = 41) IAA positive (n = 103) ICA positive (n = 15)
Age (years)
 r −0.018 0.020 0.042
 P 0.700 0.666 0.354
Gender (male/female)
 r −0.038 −0.029 0.047
 P 0.404 0.531 0.307
BMI (kg/m2)
 r −0.167 0.009 0.025
 P <0.0001a 0.841 0.583
WHR
 r −0.103 0.016 0.055
 P 0.021b 0.715 0.222
Duration of diabetes (years)
 r 0.002 0.029 −0.118
 P 0.965 0.516 0.329
Insulin treatment
 r 0.051 0.283 −0.026
 P 0.268 <0.0001a 0.569
Diabetic family history
 r −0.006 0.012 0.010
 P 0.888 0.785 0.820
FBG (mmol/L)
 r 0.065 0.094 −0.036
 P 0.146 0.038b 0.428
HbA1C (%)
 r 0.049 0.040 −0.007
 P 0.285 0.390 0.876
LDL-CH (mmol/L)
 r −0.040 −0.004 0.010
 P 0.378 0.379 0.824
HDL-CH (mmol/L)
 r 0.033 0.185 −0.020
 P 0.470 <0.0001a 0.652
TG (mmol/L)
 r −0.111 −0.046 −0.012
 P 0.014b 0.309 0.788
TCHOL (mmol/L)
 r −0.053 0.062 0.011
 P 0.238 0.171 0.812
ALT (U/L)
 r 0.070 0.047 −0.089
 P 0.118 0.295 0.202
AST (U/L)
 r −0.020 0.093 −0.019
 P 0.656 0.039b 0.668
AST/ALT
 r 0.002 0.035 0.079
 P 0.967 0.431 0.078
GGT (U/L)
 r −0.057 0.049 0.030
 P 0.209 0.047b 0.510
Ucr (μmol/L)
 r −0.082 −0.059 −0.071
 P 0.074 0.199 0.124
UREA (mmol/L)
 r 0.074 0.023 0.016
 P 0.100 0.603 0.727
mALB (mg/L)
 r −0.122 −0.051 0.024
 P 0.007c 0.262 0.605
U-mALB/Ucr (mg/g)
 r −0.090 0.002 0.024
 P 0.052 0.959 0.605
CREA (μmol/L)
 r −0.045 0.001 0.078
 P 0.323 0.974 0.683
UA (μmol/L)
 r −0.085 −0.062 0.056
 P 0.059 0.168 0.210

Data of r and P values were calculated from Spearman correlation analysis. A P value <0.05 was considered as statistically significant. Significant correlations were in bold and the significance level is indicated with superscript letters.

aP < 0.0001, bP < 0.05 and cP < 0.01.

ALT, alanine aminotransferase; AST, aspartate transaminase; BMI, body mass index; CREA, serum creatinine; FBG, fasting blood glucose; GADA, glutamic acid decarboxylase autoantibodies; GGT, γ-glutamyltransferase; HbA1c, hemoglobin A1c; HDL-CH, high-density lipoprotein (cholesterol); IAA, insulin autoantibodies; ICA, islet cell cytoplasmic autoantibodies; LDL-CH, low-density lipoprotein (cholesterol); mALB, urinary microalbumin; TCHOL, total cholesterol; TG, triglycerides; UA, serum uric acid; Ucr, urine creatinine; WHR, waist-hip ratio.

Independent factors that associated with islet autoimmunity

Next, in order to further address the independent factors associated with islet autoimmunity, we conducted the unconditional logistic regression analysis. All indexes with statistical significance (P < 0.05) or obvious tendency in the correlation analysis (P < 0.1) were incorporated into the regression analysis model, besides, clinical factors such as age, gender, and BMI were also included. As Table 4 showed, after adjustment for age, gender, BMI, Ucr and UA, WHR (OR = 0.40, 95% CI (0.17–0.95), P = 0.037), TG (OR = 0.36, 95% CI (0.17–0.79), P = 0.010), and mALB (OR = 0.36, 95% CI (0.17–0.79), P = 0.011) remained independently associated with the positivity of GADA. As for IAA, after confounding factors were adjusted, insulin treatment (OR = 18.94, 95% CI (8.49–42.24), P < 0.0001), and serum levels of FBG (OR = 4.13, 95% CI (2.15–7.94), P < 0.001), HDL-CH (OR = 2.30, 95% CI (1.34–3.96), P = 0.003), and AST (OR = 1.64, 95% CI (1.00–2.69), P = 0.05) were independently associated with the positivity of IAA. Furthermore, among all epidemical and biochemical features analyzed, no significant factors were observed as independently associated with ICA.

Table 4

Independent factors related to autoantibody positivity by unconditional logistic regression analysis.
OR (95% CI) P value
GADA
 Age (years) 1.00 (0.95–1.05) 0.945
 Gender 1.03 (0.49–2.20) 0.931
 BMI (kg/m2) 0.59 (0.27–1.30) 0.190
 WHR 0.40 (0.17–0.95) 0.037a
 TG (mmol/L) 0.36 (0.17–0.79) 0.010a
 Ucr (μmol/L) 1.00 (0.997–1.003) 0.930
 mALB (mg/L) 0.36 (0.17–0.79) 0.011a
 UA (μmol/L) 0.64 (0.30–1.36) 0.244
IAA
 Age (years) 1.01 (0.97–1.04) 0.713
 Gender 0.94 (0.57–1.55) 0.807
 BMI (kg/m2) 1.19 (0.73–1.95) 0.492
 Insulin treatment 18.9 (8.49–42.2) <0.0001b
 FBG (mmol/L) 4.13 (2.15–7.94) <0.001c
 HDL-CH (mmol/L) 2.30 (1.34–3.96) 0.003d
 AST (U/L) 1.64 (1.00–2.69) 0.050a
 GGT (U/L) 1.51 (1.00–2.28) 0.052
ICA
 Age (years) 1.00 (0.93–1.09) 0.914
 Gender 1.82 (0.62–5.37) 0.277
 BMI (kg/m2) 0.75 (0.26–2.26) 0.608
 AST/ALT 2.51 (0.77–8.15) 0.125

OR (95% CI) and P value were calculated by unconditional logistic regression and P value ≤0.05 were considered statistically significant. Significant correlations were in bold and the significance level is indicated with superscript letters.

aP ≤ 0.05, bP < 0.0001, cP < 0.001, dP < 0.01.

AST, aspartate transaminase; BMI, body mass index; CI, confidence interval; FBG, fasting blood glucose; GADA, glutamic acid decarboxylase autoantibodies; GGT, γ-glutamyltransferase; HDL-CH, high-density lipoprotein (cholesterol); IAA, insulin autoantibodies; ICA, islet cell cytoplasmic autoantibodies; mALB, Urinary microalbumin; OR, odds ratio; TG, triglycerides; UA, serum uric acid; Ucr, urine creatinine; WHR, waist-hip ratio.

Discussion

Several studies reported that islet autoimmunity, including T cell-mediated cellular immunity (20, 21) and humoral immunity in which autoantibodies played a vital role (10, 11, 12), both contributed to the pathogenesis and development of not only T1DM, but also T2DM. Furthermore, a series of evidence clued that the associations between islet autoimmunity and clinical features in T2DM occurs to some extent (18, 22, 23).

In this cross-sectional study, we carried out the method of cluster sampling and a total of 495 patients clinically diagnosed T2DM from Wu Jing community (Shanghai, China) were recruited as a representative of type 2 diabetic population in the Yangtze River delta region. Approximately 28.5% of those participants were at least one islet autoantibody positive, with 8.28% for individual GADA, 20.8% for individual IAA and 3.03% for individual ICA, which was roughly consistent with previous domestic and foreign studies (10, 12, 24). However, rare combinations of two or more autoantibodies were simultaneously observed in our study, which is in line with the previous report that the incidence of islet autoimmunity in Asians was lower than that in Northern Europeans (25, 26). The differences in dietary habits, environmental factors, ethnic factors and phenotypic characteristics could explain the heterogeneity in the prevalence and other characteristics of islet autoimmunity.

In agreement with the previous studies (18, 19, 27, 28), our findings presented that patients in GADA-positive subgroup tended to have significantly lower BMI, WHR and TG than those in negative group, suggesting that GADA-positive participants seemed to be leaner and to have less abdominal obesity. T2DM has always been considered as a chronic metabolic syndrome with higher BMI and waist circumference values, low HDL cholesterol levels, higher triglyceride levels, higher blood pressure (29), while we found in the current study that type 2 diabetic patients with positivity of GADA might maintain normal lipid metabolism, thereby avoiding to get fat. The characteristics presented above were much more similar to the phenotype of typical T1DM. Therefore, it was reasonable to believe that type 2 diabetic patients with the positivity of GADA were more likely to develop insulin treatment dependence. Besides, our data also showed that mALBs were negatively correlated with GADA levels (r = −0.122, P = 0.007) and served as an independent negative predictor of GADA (OR = 0.36, P = 0.011). Few previous studies were referred to associations between renal function and islet autoimmunity in T2DM, while a Chinese retrospective study reported that the incidence of microvascular complications including diabetic nephropathy were lower in LADA patients than that in T2DM patients at the early stage of diabetes (30). In this study, we also found GADA positivity is negatively related with the mALB levels. In our opinion, different pre-clinical periods of diabetes might be one reason for this phenomenon. For type 2 diabetic patients with islet autoimmunity, the destruction rate of islet function is more rapid than that of islet autoantibody-negative group, GADA-negative patients tend to undergo longer pre-clinical period and are at an increased risk of developing microvascular complications. Prospective studies about the renal function and GADA positivity is warranted.

The positivity rate of IAA (20.8%) in our study is lower than that in previous reports (12, 31), which could be due to the less insulin treatment in community diabetic patients rather than outpatients or inpatients were recruited in our study. IAA originally referred to autoantibody induced by insulin which are secreted by islet β cell, while it was also induced along with the exogenous insulin treatment. Indeed, in the present study, the prevalence of IAA was largely influenced by exogenous insulin therapy (OR = 18.94, P < 0.0001). Besides, in order to exclude the interference of exogenous insulin use, we divided IAA-positive patients into two groups according to whether they received insulin treatment to see if there were any differences. We found that the duration of diabetes in patients who received exogenous insulin treatment was longer than those non-insulin treatment patients, and it may be that patients with longer course of disease have more severe damage to islet function and become more dependent on insulin therapy. Furthermore, level of FBG also seemed as a positive predictor of IAA (OR = 4.13, P < 0.001), maybe patients with positive IAA tended to be under a condition in which blood glucose was difficult to be controlled in comparison with IAA-negative counterparts. Besides, our study found that HDL-CH were positively associated with IAA (r = 0.185, P < 0.0001), as reported in a previous study, type 2 diabetic patients with GADA positive showed higher HDL-CH (32, 33), and whether IAA might also play a crucial role in regulating lipid metabolism and protecting macrovascular terms need to be further elucidated.

Interestingly, according to our study, both IAA and ICA were positively associated to several biochemical indicators of liver damage, including AST, GGT, AST/ALT. Liver diseases such as autoimmune hepatitis, non-alcoholic steatohepatitis (NASH), cirrhosis even liver cancer were presented to be correlated with diabetes mellitus (34, 35). Nevertheless, the internal correlation between islet autoantibodies and diabetic liver damage is poorly understood. In our study, Spearman correlation analysis showed that AST (r = 0.093, P = 0.039) and GGT (r = 0.049, P = 0.047) were positively associated with IAA. Presumably, the reason might be that increased circulating islet autoantibodies would induce systemic autoimmune and chronic inflammatory status. An Italian study demonstrated that type 2 diabetic patients with presence of GADA were in high risk for thyroid and adrenal autoimmunity (18). Thus, it was most likely that autoimmune liver disease were generated meanwhile under the condition of islet autoimmunity. Moreover, a research referring to children presented that childhood autoimmune hepatitis is associated with a high frequency of ICA and IAA (36), which is in line with our current study among adult patients to some extent.

In this cross-sectional study, we investigated the prevalence of islet autoantibodies in patients with T2DM from one Chinese community and analyzed the correlation between clinical biochemical characteristics and islet autoantibodies, in order to explore the intrinsic factors of islet autoimmunity in T2DM. T2DM tended to be a chronic disorder caused by comprehensive factors of autoimmunity, metabolism dysfunction and systemic inflammation, and so forth. Furthermore, islet autoimmunity is closely related to metabolic syndrome, liver and kidney function. Limited by the small sample size, some of the results illustrated above need to be confirmed by multi-center large sample study. Of course, much more researches need to focus on the islet autoimmune patterns of T2DM, in order to obtain a deeper understanding and provide new ideas for the diagnosis, treatment and prevention of diabetes mellitus.

Conclusion

To conclude, our current study suggested that type 2 diabetic community patients with high prevalence of GADA tended to maintain normal lipid metabolism and avoid metabolic syndrome. However, positivity of IAA was frequently accompanied with insulin treatment and was more closely associated with diabetic liver damage.

Supplementary data

This is linked to the online version of the paper at https://doi.org/10.1530/EC-19-0379.

Declaration of interest

The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.

Funding

This work was supported by National Key R&D Program of China (2016YFC1305105) and National Natural Science Foundation of China (81670751).

Ethics approval

The study was approved by Ethics Committee of Basic Medical College of Fudan University (2016-Y028) and Huashan Hospital affiliated to Fudan University (2016-320), and written informed consent was obtained from all of subjects.

Data availability

The data from this study may be obtained from the corresponding author, given appropriate justification.

Author contribution statement

Xiangyu Gao analyzed the data, illustrated the results and wrote the manuscript, Wanwan Sun helped direct statistical methods and Yi Wang helped collect and analyze the data, these authors contributed equally. While Yehong Yang contributed to the conception, design of the study, and provided critical suggestions of the manuscript. Yawen Zhang, Rumei Li and Jinya Huang were mainly responsible for samples collection and information input. All authors read and approved the final manuscript.

Acknowledgements

The authors are very grateful to Dr Buyue Zhang from the Department of Clinical Laboratory, Huashan Hospital for her technical help and to Dr Xiaona Qiao for her help in modifying and polishing the manuscript grammatically and linguistically.

References

  • 1↑

    Nickerson HD, Dutta S. Diabetic complications: current challenges and opportunities. Journal of Cardiovascular Translational Research 2012 375–379. (https://doi.org/10.1007/s12265-012-9388-1)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2↑

    Diabetes in China: mapping the road ahead. Lancet: Diabetes and Endocrinology 2014 923. (https://doi.org/10.1016/S2213-8587(14)70189-5)

  • 3 ↑

    Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Report of the Expert Committee on the diagnosis and classification of diabetes mellitus. Diabetes Care 1997 1183–1197. (https://doi.org/10.2337/diacare.20.7.1183)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4↑

    McCance DR, Hanson RL, Pettitt DJ, Bennett PH, Hadden DR, Knowler WC. Diagnosing diabetes mellitus – do we need new criteria? Diabetologia 1997 247–255. (https://doi.org/10.1007/s001250050671)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 5↑

    Knip M, Siljander H. Autoimmune mechanisms in type 1 diabetes. Autoimmunity Reviews 2008 550–557. (https://doi.org/10.1016/j.autrev.2008.04.008)

  • 6↑

    Eisenbarth GS. Update in type 1 diabetes. Journal of Clinical Endocrinology and Metabolism 2007 2403–2407. (https://doi.org/10.1210/jc.2007-0339)

  • 7↑

    Brooks-Worrell B, Palmer JP. Immunology in the Clinic Review Series; focus on metabolic diseases: development of islet autoimmune disease in type 2 diabetes patients: potential sequelae of chronic inflammation. Clinical and Experimental Immunology 2012 40–46. (https://doi.org/10.1111/j.1365-2249.2011.04501.x)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8↑

    Fourlanos S, Dotta F, Greenbaum CJ, Palmer JP, Rolandsson O, Colman PG, Harrison LC. Latent autoimmune diabetes in adults (LADA) should be less latent. Diabetologia 2005 2206–2212. (https://doi.org/10.1007/s00125-005-1960-7)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9↑

    Panczel P, Hosszufalusi N, Bornemisza B, Horvath L, Janoskuti L, Fust G, Rajczy K, Vatay A, Prohaszka Z, Madacsy L, et al.Latent autoimmune diabetes in adults (LADA): part of the clinical spectrum of type-1 diabetes mellitus of autoimmune origin. Orvosi Hetilap 2001 2571–2578.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10↑

    Genovese S, Bazzigaluppi E, Goncalves D, Ciucci A, Cavallo MG, Purrello F, Anello M, Rotella CM, Bardini G, Vaccaro O, et al.Clinical phenotype and beta-cell autoimmunity in Italian patients with adult-onset diabetes. European Journal of Endocrinology 2006 441–447. (https://doi.org/10.1530/eje.1.02115)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11↑

    Pietropaolo M, Barinas-Mitchell E, Pietropaolo SL, Kuller LH, Trucco M. Evidence of islet cell autoimmunity in elderly patients with type 2 diabetes. Diabetes 2000 32–38. (https://doi.org/10.2337/diabetes.49.1.32)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12↑

    Li R, Huang J, Yu Y, Yang Y. Islet autoantibody patterns in patients with type 2 diabetes aged 60 and higher: a cross-sectional study in a Chinese hospital. Frontiers in Endocrinology 2018 260. (https://doi.org/10.3389/fendo.2018.00260)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13↑

    Kolb H, Mandrup-Poulsen T. An immune origin of type 2 diabetes? Diabetologia 2005 1038–1050. (https://doi.org/10.1007/s00125-005-1764-9)

  • 14↑

    Fatima A, Khawaja KI, Burney S, Minhas K, Mumtaz U, Masud F. Type 1 and type 2 diabetes mellitus: are they mutually exclusive? Singapore Medical Journal 2013 396–400. (https://doi.org/10.11622/smedj.2013141)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15↑

    Pipi E, Marketou M, Tsirogianni A. Distinct clinical and laboratory characteristics of latent autoimmune diabetes in adults in relation to type 1 and type 2 diabetes mellitus. World Journal of Diabetes 2014 505–510. (https://doi.org/10.4239/wjd.v5.i4.505)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16↑

    Wod M, Yderstraede KB, Halekoh U, Beck-Nielsen H, Hojlund K. Metabolic risk profiles in diabetes stratified according to age at onset, islet autoimmunity and fasting C-peptide. Diabetes Research and Clinical Practice 2017 62–71. (https://doi.org/10.1016/j.diabres.2017.09.014)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17↑

    Mahadeb YP, Gruson D, Buysschaert M, Hermans MP. What are the characteristics of phenotypic type 2 diabetic patients with low-titer GAD65 antibodies? Acta Diabetologica 2014 103–111. (https://doi.org/10.1007/s00592-013-0513-7)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18↑

    Gambelunghe G, Forini F, Laureti S, Murdolo G, Toraldo G, Santeusanio F, Brunetti P, Sanjeevi CB, Falorni A. Increased risk for endocrine autoimmunity in Italian type 2 diabetic patients with GAD65 autoantibodies. Clinical Endocrinology 2000 565–573. (https://doi.org/10.1046/j.1365-2265.2000.00983.x)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19↑

    Romkens TE, Kusters GC, Netea MG, Netten PM. Prevalence and clinical characteristics of insulin-treated, anti-GAD-positive, type 2 diabetic subjects in an outpatient clinical department of a Dutch teaching hospital. Netherlands Journal of Medicine 2006 114–118.

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20↑

    Goel A, Chiu H, Felton J, Palmer JP, Brooks-Worrell B. T-cell responses to islet antigens improves detection of autoimmune diabetes and identifies patients with more severe beta-cell lesions in phenotypic type 2 diabetes. Diabetes 2007 2110–2115. (https://doi.org/10.2337/db06-0552)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21↑

    Brooks-Worrell BM, Reichow JL, Goel A, Ismail H, Palmer JP. Identification of autoantibody-negative autoimmune type 2 diabetic patients. Diabetes Care 2011 168–173. (https://doi.org/10.2337/dc10-0579)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22↑

    Muazu SB, Okpe I, Anumah F. The prevalence and characteristics of latent autoimmune diabetes in adults subset among type two diabetes mellitus patients in Northern Nigeria. Annals of African Medicine 2016 163–170. (https://doi.org/10.4103/1596-3519.194277)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23↑

    Arranz Martin A, Lecumberri Pascual E, Brito Sanfiel MÁ, Andia Melero V, Nattero Chavez L, Sanchez Lopez I, Canovas Molina G, Arrieta Blanco F, Gonzalez Perez Del Villar N & Grupo de Diabetes de la Sociedad de Endocrinología, Nutrición y Diabetes de Madrid (SENDIMAD). Clinical and metabolic profile of patients with latent autoimmune diabetes in adults in specialized care in Madrid. Endocrinologia, Diabetes y Nutricion 2017 34–39. (https://doi.org/10.1016/j.endinu.2016.09.001)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24↑

    Turner R, Stratton I, Horton V, Manley S, Zimmet P, Mackay IR, Shattock M, Bottazzo GF, Holman R. UKPDS 25: autoantibodies to islet-cell cytoplasm and glutamic acid decarboxylase for prediction of insulin requirement in type 2 diabetes. UK Prospective Diabetes Study Group. Lancet 1997 1288–1293. (https://doi.org/10.1016/s0140-6736(97)03062-6)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25↑

    Kumar A, de Leiva A. Latent autoimmune diabetes in adults (LADA) in Asian and European populations. Diabetes/Metabolism Research and Reviews 2017 33 e2890. (https://doi.org/10.1002/dmrr.2890)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26↑

    Ong YH, Koh WCA, Ng ML, Tam ZY, Lim SC, Boehm BO & Adult-Onset Autoimmune Diabetes Mellitus Consortium (ADAMS). Glutamic acid decarboxylase and islet antigen 2 antibody profiles in people with adult-onset diabetes mellitus: a comparison between mixed ethnic populations in Singapore and Germany. Diabetic Medicine 2017 1145–1153. (https://doi.org/10.1111/dme.13358)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27↑

    Xiang Y, Huang G, Shan Z, Pan L, Luo S, Yang L, Shi L, Li Q, Leslie RD, Zhou Z. Glutamic acid decarboxylase autoantibodies are dominant but insufficient to identify most Chinese with adult-onset non-insulin requiring autoimmune diabetes: LADA China study 5. Acta Diabetologica 2015 1121–1127. (https://doi.org/10.1007/s00592-015-0799-8)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28↑

    Unnikrishnan AG, Singh SK, Sanjeevi CB. Prevalence of GAD65 antibodies in lean subjects with type 2 diabetes. Annals of the New York Academy of Sciences 2004 118–121. (https://doi.org/10.1196/annals.1337.018)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29↑

    Isomaa B, Almgren P, Tuomi T, Forsen B, Lahti K, Nissen M, Taskinen MR, Groop L. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 2001 683–689. (https://doi.org/10.2337/diacare.24.4.683)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30↑

    Lu J, Hou X, Zhang L, Hu C, Zhou J, Pang C, Pan X, Bao Y, Jia W. Associations between clinical characteristics and chronic complications in latent autoimmune diabetes in adults and type 2 diabetes. Diabetes/Metabolism Research and Reviews 2015 411–420. (https://doi.org/10.1002/dmrr.2626)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31↑

    Kawasaki E, Nakamura K, Kuriya G, Satoh T, Kuwahara H, Kobayashi M, Abiru N, Yamasaki H, Eguchi K. Autoantibodies to insulin, insulinoma-associated antigen-2, and zinc transporter 8 improve the prediction of early insulin requirement in adult-onset autoimmune diabetes. Journal of Clinical Endocrinology and Metabolism 2010 707–713. (https://doi.org/10.1210/jc.2009-1733)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32↑

    Zinman B, Kahn SE, Haffner SM, O’Neill MC, Heise MA, Freed MI & ADOPT Study Group. Phenotypic characteristics of GAD antibody-positive recently diagnosed patients with type 2 diabetes in North America and Europe. Diabetes 2004 3193–3200. (https://doi.org/10.2337/diabetes.53.12.3193)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 33↑

    Davis TM, Wright AD, Mehta ZM, Cull CA, Stratton IM, Bottazzo GF, Bosi E, Mackay IR, Holman RR. Islet autoantibodies in clinically diagnosed type 2 diabetes: prevalence and relationship with metabolic control (UKPDS 70). Diabetologia 2005 695–702. (https://doi.org/10.1007/s00125-005-1690-x)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 34↑

    Amarapurkar D, Das HS. Chronic liver disease in diabetes mellitus. Tropical Gastroenterology 2002 3–5.

  • 35↑

    Tolman KG, Fonseca V, Dalpiaz A, Tan MH. Spectrum of liver disease in type 2 diabetes and management of patients with diabetes and liver disease. Diabetes Care 2007 734–743. (https://doi.org/10.2337/dc06-1539)

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36↑

    da Silva ME, Porta G, Goldberg AC, Bittencourt PL, Fukui RT, Correia MR, Miura IK, Pugliese RS, Baggio VL, Cancado EL, et al.Diabetes mellitus-related autoantibodies in childhood autoimmune hepatitis. Journal of Pediatric Endocrinology and Metabolism 2002 831–840. (https://doi.org/10.1515/jpem.2002.15.6.831)

    • PubMed
    • Search Google Scholar
    • Export Citation

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Online ISSN:
2049-3614
Copyright:
© 2019 The authors 2019
Page(s):
10
Article Type:
Research Article
Received Date:
17 Oct 2019
Accepted Date:
23 Oct 2019
Online Publication Date:
Nov 2019
Keywords:
type 2 diabetes; community patients; islet autoantibody; clinical characteristics
  • Figure 1
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    Figure 1

    Significant differences between subgroups divided by positivity of GADA or IAA. (A, B and C) GADA-positive group presents lower levels of BMI,WHR and mALB in comparison with negative counterparts; (D, E, F, G and H) IAA-positive group tends to show higher rate of insulin treatment and higher levels of FBG, HDL-CH,AST and GGT than negative ones. All comparison tests between the two groups were performed using the statistical method of Mann–Whitney U test. *P < 0.05; **P < 0.01, ***P < 0.001 and ****P < 0.0001. BMI, body mass index; WHR, waist-hip ratio; mALB, urinary microalbumin; FBG, fasting blood glucose; HDL-CH, high-density lipoprotein (cholesterol); AST, aspartate transaminase; GGT, r-glutamyltransferase; GADA, glutamic acid decarboxylase autoantibodies; IAA, insulin autoantibodies.

Figure 1

Significant differences between subgroups divided by positivity of GADA or IAA. (A, B and C) GADA-positive group presents lower levels of BMI,WHR and mALB in comparison with negative counterparts; (D, E, F, G and H) IAA-positive group tends to show higher rate of insulin treatment and higher levels of FBG, HDL-CH,AST and GGT than negative ones. All comparison tests between the two groups were performed using the statistical method of Mann–Whitney U test. *P < 0.05; **P < 0.01, ***P < 0.001 and ****P < 0.0001. BMI, body mass index; WHR, waist-hip ratio; mALB, urinary microalbumin; FBG, fasting blood glucose; HDL-CH, high-density lipoprotein (cholesterol); AST, aspartate transaminase; GGT, r-glutamyltransferase; GADA, glutamic acid decarboxylase autoantibodies; IAA, insulin autoantibodies.