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OBJECTIVE--To examine bβ-cell function across a spectrum of glycemia among Asian Indians, a population experiencing type 2 diabetes development at young ages despite low BMI. RESEARCH DESIGN AND METHODS--One-thousand two-hundred sixty-four individuals without known diabetes in the Diabetes Community Lifestyle Improvement Program in Chennai, India, had a 75-g oral glucose tolerance test, with glucose and insulin measured at 0, 30, and 120 min. Type 2 diabetes, isolated impaired fasting glucose (iIFG), isolated impaired glucose tolerance (iIGT), combined impaired fasting glucose and impaired glucose tolerance, and normal glucose tolerance (NGT) were defined by American Diabetes Association guidelines. Measures included insulin resistance and sensitivity (homeostasis model assessment of insulin resistance [HOMA-IR], modified Matsuda Index, 1/fasting insulin) and bβ-cell function (oral disposition index = [Δinsulin0-30/Δ glucose0-30] x [1/fasting insulin]). RESULTS--Mean age was 44.2 years (SD, 9.3) and BMI 27.4 kg/m² (SD, 3.8); 341 individuals had NGT, 672 had iIFG, IGT, or IFG plus IGT, and 251 had diabetes. Patterns of insulin resistance or sensitivity were similar across glycemic categories. With mild dysglycemia, the absolute differences in age- and sex-adjusted oral disposition index (NGT vs. iIFG, 38%; NGT vs. iIGT, 32%) were greater than the differences in HOMA-IR (NGT vs. iIFG, 25%; NGT vs. iIGT, 23%; each, 0.0001). Compared with NGT and adjusted for age, sex, BMI, waist circumference, and family history, the odds of mild dysglycemia were more significant per SD of oral disposition index (iIFG: odds ratio [OR], 0.36; 95% CI, 0.23-0.55; iIGT: OR, 0.37; 95% CI, 0.24-0.56) than per SD of HOMA-IR (iIFG: OR, 1.69; 95% CI, 1.23-2.33; iIGT: OR, 1.53; 95% CI, 1.11-2.11). CONCLUSIONS--Asian Indians with mild dysglycemia have reduced bβ-cell function, regardless of age, adiposity, insulin sensitivity, or family history. Strategies in diabetes prevention should minimize loss of ββ-cell function. [ABSTRACT FROM AUTHOR]

OBJECTIVE -- The objectives of this study were to determine age- and sex-specific concentrations of adiponectin in Asian Indian teenagers and adults and to assess whether its blood levels correlated with insulin resistance and other cardiometabolic parameters. RESEARCH DESIGN AND METHODS-- We studied 196 teenagers (94 boys, 102 girls) 12-18 years of age, selected from a cohort of 2,640 individuals from a cross-sectional school-based survey in Chennai, India. For comparison, adiponectin and plasma insulin were measured in 84 healthy adults. Correlation of adiponectin with plasma levels of insulin, proinsulin, insulin resistance, anthropometry, and family history of diabetes were studied. RESULTS-- Adiponectin showed a sex dimorphism, with girls having higher values (in micro;g/ml) (10.3 ± 5.0) than boys (8.4 ± 3.5) (P < 0.0001), and it showed a positive correlation with HDL cholesterol in boys only and not with other lipid parameters, insulin resistance, proinsulin, anthropometry, and family history of diabetes. In the adults, adiponectin correlated with fasting glucose and inversely with triglycerides. CONCLUSIONS-- In Asian Indian adults and teenagers, adiponectin did not correlate directly with measures of insulin sensitivity, overweight, and other cardiometabolic variables. This was at variance with several reports in other populations showing an inverse association of adiponectin with insulin resistance, proinsulin, and BMI, suggesting ethnic differences in the relationship of adiponectin with insulin sensitivity. The role of adiponectin in relation to action of insulin needs more detailed studies in Asian Indians. [ABSTRACT FROM AUTHOR]

Type 2 diabetes [T2D] and the metabolic syndrome are far more common and presents at a younger age in people of South Asian origin. The aim of the study was to determine the heritability of common traits associated with diabetes in South Indian families and compare them to those obtained in British white Caucasians. 1094 subjects from 296 families were studied from a community-based cross-sectional study in Chennai, India. Clinical details, anthropometric measures and fasting bloods were taken from all available family members. Heritabilities [h²] were calculated for individual waits using SOLAR v4.0.3. corrected for age, sex and BMI. h² [SE] for waist was 0.50 [0.06], WHR 0.33 [0.06], body fat 0.39 [0.07], BMR 0.57 [0.06], systolic (s)BP 0.30 [0.06], triglycerides (tg) 0.53 [0.06] and fasting glucose (FBG) 0.37 [0.06]. All p values were <0.0001. The h² values using a similar model implemented in SOLAR were generally higher than for a healthy white population in the UK (Freeman et al 2002: WHR 0.15 [0.11], sBP 0.14 [0.07], Tg 0.20 [0.08] and FBG 0.20 [0.08]) whereas they were similar apart from FBG to non diabetic relatives of patients with T2D ascertained for the Diabetes UK Warren2 family collection (Mills et al 2004: WHR 0.22 [0.08], sBP 0.30 [0.1], Tg 0.51 [0.1] and FBG 0.81 [0.09]). These studies suggest that risk variables for diabetes which are strongly influenced by lifestyle have an increased genetic component in south Asians compared healthy white Europeans. [ABSTRACT FROM AUTHOR]

We and others in a variety of ethnic groups have previously described associations of various SNPs of the uncoupling protein genes UCP2 and UCP3 (located within 17 kb of each other on chromosome 11q13) with both central fat disposition and BMI. The aim of this study was to do a replication study in South Indian subjects using a family based approach and selecting SNP's by' a priori hypothesis' defined by a previous association with obesity/waits in other studies and/or functional data. Five SNPs were studied; 1 by Ampliflour (UCP2-866 rs659366), 1 by SNAPSHOT (UCP3Y210Y rs2075577), 2 by TaqMan (UCP3-55 rs1800849, UCP2 A55V rs660339) and one by PCR-RFLP (UCP2 exon 8 INDEL) in 882 South Indian participants from 236 families ascertained from community based study of healthy families living in Chennai, India. Statistical analysis was performed using SOLAR and anthropometric variables were corrected for age and sex. The QTLD analysis showed the BMI was associated to the UCP3 rs1800849 (AA 23.9±0.29, AB 23.5±0.32, BB 23.0±0.5, p=0.027) and UCP3 rs2075577 (AA 24.6±0.37, AB 24.0±0.30, BB 23.4±0.39, p=0.022). Waist circumference to the UCP2 rs660339 (AA 84.3±0A8, AB 85.1±0.41, BB 85.9±0.65, p=0.028). Body fat percentage to UCP2 rs660339 (AA 22.9±0.31, AB 23.2±0.27, BB 23.5±0.42, p=0.048) and UCP2 rs659366 (AA 22.7±0.31, AB 22.9±0.26, BB 23.27±0.41, p=0.076). This detailed analysis confirms associations between anthropometric traits and the UCP2/UCP3 locus but that separate SNPs are associated with either BMI or fat distribution. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine the prevalence of, and risk factors for, diabetic neuropathy among Asian Indian type 2 diabetic subjects. Subjects were recruited from CURES, a population-based study conducted on a representative population of Chennai city in south India. Of the 1529 known diabetic [KD] subjects, 1382 participated in the study [response rate: 90.4%]; in addition, 354 newly detected diabetic [NDD] subjects were also randomly selected. Neuropathy was diagnosed if the vibratory perception threshold of the right great toe measured by biothesiometry (Biomedical Instrument Co., Newbury, Ohio, USA) was ≥25. Of the total of 1736 individuals, biothesiometry studies were performed in 1632 subjects (94.0% response rate). The overall prevalence of neuropathy was 11% [age-standardized-5.8%], while it was 12.2% [age-standardized-6.5%] and 10% [age-standardized-5.2%] in male and female subjects respectively. The prevalence of neuropathy was significantly higher among KD subjects compared to NDD subjects [12.1% vs 6.8%, p=0.006]. It was also higher among subjects with diabetic retinopathy [26.9% vs 16.9%, p=0.001] and proteinuria [9.6% vs 5.3%, p=0.019] compared to those without. There was a linear increase in the prevalence of neuropathy with increasing age among both genders [p<0.0001]. The odds ratio (OR) for neuropathy in subjects having duration of diabetes >15 years was 5.51 [95% confidence interval (CI): 3.04-10.01, p<0.0001]. Multivariate logistic regression analysis showed age [OR: 1.16, 95% CI: 1.13-1.19, p<0.001], height [OR: 1.04, 95% CI: 1.01 -1.07, p=0.016] and fasting plasma glucose [OR: 1.00, 95% CI: 1.00 -1.01, p=0.001] to be significantly associated with neuropathy. Duration of diabetes showed an association with neuropathy but significance was lost when age was introduced into the model. This is the first population-based data on prevalence of diabetic neuropathy from India, which has the largest number of diabetic patients in the world. [ABSTRACT FROM AUTHOR]