Characteristics of Latent Autoimmune Diabetes in China
Characteristics of Latent Autoimmune Diabetes in China
This cross-sectional study was conducted from June 2006 to January 2010. Patients were recruited consecutively from 46 centers (university-affiliated teaching hospitals) in 25 major cities, representing 53% of the total Chinese population aged ≥30 years. The patient population includes 15 major ethnic groups of which the majority (in excess of 98%) is Han. The ethics review committee/institutional review board of each study center approved the study protocol. The study was conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent. Inclusion criteria were as follows: 1) diagnosis of diabetes (World Health Organization [WHO] 99 criteria) at age ≥30.0 years, 2) disease duration of <1 year, 3) no ketoacidosis in the first 6 months after the diagnosis of diabetes, and 4) insulin independence (usage of insulin <1 month) for 6 months after diagnosis. Exclusion criteria were as follows: 1) secondary diabetes, 2) diabetes in pregnancy and gestational diabetes mellitus, and 3) malignancy. LADA was defined according to the Immunology of Diabetes Society (IDS) criteria: GADA-positive patients, initially non–insulin requiring for at least 6 months, diagnosed over the age of 30 years. GADA-negative subjects were diagnosed with type 2 diabetes. Detailed medical history was obtained by study physicians before collection of fasting blood samples. A 6-month follow-up stage was carried out to confirm the diabetic ketoacidosis status and insulin therapy for all subjects. We recruited 5,324 patients and eliminated 444 patients (8.3%) because disease duration at ascertainment was >1.0 year, age was under 30 years, or they developed diabetic ketoacidosis or insulin dependency within 6 months postdiagnosis. By the IDS criteria, 287 had LADA, representing 5.9% of those 4,880 subjects meeting the study criteria. Among all 287 LADA patients, 180 subjects consented to the genetic study. An approximately equal number (174 subjects) of age-, sex-, and center-matched GADA-negative type 2 diabetes samples for genetic analysis were collected as well. The oral glucose tolerance test was used to verify normal glucose tolerance among healthy control subjects from a community-based study for reference HLA-DQ genotyping (Fig. 1). Serum samples for antibody assays and whole blood samples for genotyping were shipped to the Diabetes Center of Central South University, Changsha, China, with transportation on ice within 1 day. Blood samples were stored at −80°C before analysis.
(Enlarge Image)
Figure 1.
Flowchart of LADA China Study. OGTT, oral glucose tolerance test.
Body height, weight, waist circumference, hip circumference, and blood pressure were recorded by study physicians/coordinates. Overweight and obesity was defined as BMI ≥25 kg/m (WHO criteria). Hypertension was defined as systolic and diastolic blood pressure ≥140 or ≥90 mmHg, respectively, or current use of antihypertensive medications. Dyslipidemia was defined as serum triglycerides ≥1.7 mmol/L, HDL cholesterol <1.04 mmol/L for men and <1.30 mmol/L for women, or currently taking medication for hyperlipidemia. Metabolic syndrome was defined using advised National Cholesterol Education Program–Adult Treatment Panel III criteria, involving achievement of three or more of the following: 1) waist circumference ≥90 cm (Asian male) or ≥80 cm (Asian female); 2) triglyceride ≥1.7 mmol/L, 3) HDL cholesterol <1.04 mmol/L (male) or <1.30 mmol/L (female), 4) systolic/diastolic blood pressure ≥130/85 mmHg, and 5) fasting plasma glucose ≥5.6 mmol/L. Lipids, HbA1c, and fasting C-peptide (FCP) were assayed at the study sites by standard methods. GADA was analyzed in the core laboratory (Central South University) by radioligand assay as previously described; all samples were measured in duplicate. Positive samples were repeated to confirm their positivity. GADA positivity was determined as the 99.5th percentile of 188 healthy control subjects, i.e., as ≥18 units/mL (WHO unit) and revalidated when positive. The sensitivity and specificity of GADA assays were 82 and 98% respectively, as evaluated in the 4th Diabetes Autoantibody Standardization Program (unpublished data). Intra- and interassay coefficients of variation were 8.9 and 11.2%, respectively. Genomic DNA was extracted from anticoagulated peripheral blood using a phenol-chloroform method. HLA-DQA1 and -DQB1 genotypes were defined using PCR to amplify exon 2 of both DQA1 and DQB1 genes followed by standard DNA sequencing-based typing.
Statistical analysis was performed using SPSS statistical software (version 13; SPSS, Chicago, IL). Normally distributed data were expressed as means ± SD. Variables with a skewed distribution were reported as median (range) and log transformed to approximate normality before analysis. Frequency differences were compared using χ test or Fisher exact test when appropriate. Independent Student t test or one-way ANOVA were used to compare the means between the groups as appropriate. Data for GADA titer were transformed using log base 10 to normalize their distribution. Logistic regression models were used to adjust the potential confounding variables including geographic area, ethnicity, age, BMI, and sex for LADA. P < 0.05 was considered significant.
Research Design and Methods
This cross-sectional study was conducted from June 2006 to January 2010. Patients were recruited consecutively from 46 centers (university-affiliated teaching hospitals) in 25 major cities, representing 53% of the total Chinese population aged ≥30 years. The patient population includes 15 major ethnic groups of which the majority (in excess of 98%) is Han. The ethics review committee/institutional review board of each study center approved the study protocol. The study was conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent. Inclusion criteria were as follows: 1) diagnosis of diabetes (World Health Organization [WHO] 99 criteria) at age ≥30.0 years, 2) disease duration of <1 year, 3) no ketoacidosis in the first 6 months after the diagnosis of diabetes, and 4) insulin independence (usage of insulin <1 month) for 6 months after diagnosis. Exclusion criteria were as follows: 1) secondary diabetes, 2) diabetes in pregnancy and gestational diabetes mellitus, and 3) malignancy. LADA was defined according to the Immunology of Diabetes Society (IDS) criteria: GADA-positive patients, initially non–insulin requiring for at least 6 months, diagnosed over the age of 30 years. GADA-negative subjects were diagnosed with type 2 diabetes. Detailed medical history was obtained by study physicians before collection of fasting blood samples. A 6-month follow-up stage was carried out to confirm the diabetic ketoacidosis status and insulin therapy for all subjects. We recruited 5,324 patients and eliminated 444 patients (8.3%) because disease duration at ascertainment was >1.0 year, age was under 30 years, or they developed diabetic ketoacidosis or insulin dependency within 6 months postdiagnosis. By the IDS criteria, 287 had LADA, representing 5.9% of those 4,880 subjects meeting the study criteria. Among all 287 LADA patients, 180 subjects consented to the genetic study. An approximately equal number (174 subjects) of age-, sex-, and center-matched GADA-negative type 2 diabetes samples for genetic analysis were collected as well. The oral glucose tolerance test was used to verify normal glucose tolerance among healthy control subjects from a community-based study for reference HLA-DQ genotyping (Fig. 1). Serum samples for antibody assays and whole blood samples for genotyping were shipped to the Diabetes Center of Central South University, Changsha, China, with transportation on ice within 1 day. Blood samples were stored at −80°C before analysis.
(Enlarge Image)
Figure 1.
Flowchart of LADA China Study. OGTT, oral glucose tolerance test.
Clinical Characteristics and Biochemical Measurements
Body height, weight, waist circumference, hip circumference, and blood pressure were recorded by study physicians/coordinates. Overweight and obesity was defined as BMI ≥25 kg/m (WHO criteria). Hypertension was defined as systolic and diastolic blood pressure ≥140 or ≥90 mmHg, respectively, or current use of antihypertensive medications. Dyslipidemia was defined as serum triglycerides ≥1.7 mmol/L, HDL cholesterol <1.04 mmol/L for men and <1.30 mmol/L for women, or currently taking medication for hyperlipidemia. Metabolic syndrome was defined using advised National Cholesterol Education Program–Adult Treatment Panel III criteria, involving achievement of three or more of the following: 1) waist circumference ≥90 cm (Asian male) or ≥80 cm (Asian female); 2) triglyceride ≥1.7 mmol/L, 3) HDL cholesterol <1.04 mmol/L (male) or <1.30 mmol/L (female), 4) systolic/diastolic blood pressure ≥130/85 mmHg, and 5) fasting plasma glucose ≥5.6 mmol/L. Lipids, HbA1c, and fasting C-peptide (FCP) were assayed at the study sites by standard methods. GADA was analyzed in the core laboratory (Central South University) by radioligand assay as previously described; all samples were measured in duplicate. Positive samples were repeated to confirm their positivity. GADA positivity was determined as the 99.5th percentile of 188 healthy control subjects, i.e., as ≥18 units/mL (WHO unit) and revalidated when positive. The sensitivity and specificity of GADA assays were 82 and 98% respectively, as evaluated in the 4th Diabetes Autoantibody Standardization Program (unpublished data). Intra- and interassay coefficients of variation were 8.9 and 11.2%, respectively. Genomic DNA was extracted from anticoagulated peripheral blood using a phenol-chloroform method. HLA-DQA1 and -DQB1 genotypes were defined using PCR to amplify exon 2 of both DQA1 and DQB1 genes followed by standard DNA sequencing-based typing.
Statistical Analysis
Statistical analysis was performed using SPSS statistical software (version 13; SPSS, Chicago, IL). Normally distributed data were expressed as means ± SD. Variables with a skewed distribution were reported as median (range) and log transformed to approximate normality before analysis. Frequency differences were compared using χ test or Fisher exact test when appropriate. Independent Student t test or one-way ANOVA were used to compare the means between the groups as appropriate. Data for GADA titer were transformed using log base 10 to normalize their distribution. Logistic regression models were used to adjust the potential confounding variables including geographic area, ethnicity, age, BMI, and sex for LADA. P < 0.05 was considered significant.
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