GAD Antibody Positivity Predicts Type 2 Diabetes in an Adult Population

OBJECTIVE-To evaluate the significance of GAD antibodies (GADAs) and family history for type 1 diabetes (FHT1) or type 2 diabetes (FHT2) in nondiabetic subjects. RESEARCH DESIGN AND METHODS-GADAs were analyzed in 4,976 nondiabetic relatives of type 2 diabetic patients or control subjects from Finland. Altogether, 289 (5.9%) were GADA(+)-a total of 253 GADA(+) and 2,511 GADA(-) subjects participated in repeated oral glucose tolerance tests during a median time of 8.1 years. The risk of progression to diabetes was assessed using Cox regression analysis. RESULTS-Subjects within the highest quartile of GADA(+) (GADA(high)(+)) had more often first-degree FHT1 (29.2 vs. 7.9%, P < 0.00001) and GADA(+) type 2 diabetic (21.3 vs. 13.7%, P = 0.002) or nondiabetic (26.4 vs. 13.3%, P = 0.010) relatives than GADA(-) subjects. During the follow-up, the GADA(+) subjects developed diabetes significantly more often than the GADA(-) subjects (36/253 [14.2%] vs. 134/2,511 [5.3%], P < 0.00001). GADA(high)(+) conferred a 4.9-fold increased risk of diabetes (95% CI 2.8-8.5) compared with GADA(-)-seroconversion to positive during the follow-up was associated with 6.5-fold (2.8-15.2) and first-degree FHT1 with 2.2-fold (1.2-4.1) risk of diabetes. Only three subjects developed type 1 diabetes, and others had a non-insulin-dependent phenotype 1 year after diagnosis. GADA(+) and GADA(-) subjects did not clinically differ at baseline, but they were leaner and less insulin resistant after the diagnosis of diabetes. CONCLUSIONS-GADA positivity clusters in families with type 1 diabetes or latent autoimmune diabetes in adults. GADA positivity predicts diabetes independently of family history of diabetes, and this risk was further increased with high GADA concentrations

A Variant in the KCNQ1 Gene Predicts Future Type 2 Diabetes and Mediates Impaired Insulin Secretion

Objective- Two independent genome wide association studies for type 2 diabetes in Japanese have recently identified common variants in the KCNQ1 gene to be strongly associated with type 2 diabetes. Here we studied whether a common variant in KCNQ1 would influence BMI, insulin secretion and action and predict future type 2 diabetes in subjects from Sweden and Finland. Research design and methods- Risk of type 2 diabetes conferred by KCNQ1 rs2237895 was studied in 2,830 type 2 diabetes cases and 3,550 controls from Sweden (Malmö Case-Control) and prospectively in 16,061 individuals from the Malmö Preventive Project (MPP). Association between genotype and insulin secretion/action was assessed cross-sectionally in 3,298 non-diabetic subjects from the PPP-Botnia Study and longitudinally in 2,328 non-diabetic subjects from the Botnia Prospective Study (BPS). KCNQ1 expression (n=18) and glucose-stimulated insulin secretion (n=19) was measured in human islets from non-diabetic cadaver donors. Results. The C-allele of KCNQ1 rs2237895 was associated with increased risk of type 2 diabetes in both the case-control (OR 1.23 [1.12-1.34], p=5.6x10(-6)) and the prospective (OR 1.14 [1.06-1.22], p=4.8x10(-4)) studies. Furthermore, the C-allele was associated with decreased insulin secretion (CIR p=0.013; DI p=0.013) in the PPP-Botnia study and in the BPS at baseline (CIR p=3.6x10(-4); DI p=0.0058) and after follow-up (CIR p=0.0018; DI p=0.0030). C-allele carriers showed reduced glucose-stimulated insulin secretion in human islets (p=2.5x10(-6)). Conclusion. A common variant in the KCNQ1 gene is associated with increased risk of future type 2 diabetes in Scandinavians which partially can be explained by an effect on insulin secretion

GH peak response to GHRH-arginine: relationship to insulin resistance and other cardiovascular risk factors in a population of adults aged 50–90

OBJECTIVE: To assess the GH response to GHRH-arginine in apparently healthy adults in relation to cardiovascular risk factors. DESIGN: Cross-sectional. PATIENTS: Eighty-six male and female volunteers aged 50–90. MEASUREMENTS: GH peak response to GHRH-arginine and cardiovascular risk factors, including obesity, insulin resistance, low levels of high density lipoprotein (HDL) cholesterol, elevated triglycerides, and hypertension. The primary outcome measurement was GH response to GHRH-arginine. The relationship between GH peak responses and cardiovascular risk factors was determined after data collection. RESULTS: GH peaks were highly variable, ranging from 2·3 to 185 µg/l (14% with GH peaks < 9 µg/l). An increasing number of cardiovascular risk factors were associated with a lower mean GH peak (P < 0·0001). By univariate analysis, fasting glucose, insulin, body mass index (BMI), HDL cholesterol and triglycerides were significantly associated with GH peak (all P < 0·0001). Multiple regression analysis revealed that fasting glucose, fasting insulin, BMI, triglycerides and sex accounted for 54% of GH peak variability. The role of abdominal fat as it relates to GH peak was explored in a subset of 45 subjects. Trunk fat and abdominal subregion fat measured by dual energy X-ray absorptiometry (DXA) were inversely related to GH peak (P < 0·008 and 0·001, respectively). Analysis of this subgroup by multiple regression revealed that subregion abdominal fat became the significant obesity-related determinant of GH peak, but still lagged behind fasting insulin and glucose. CONCLUSIONS: GH response to secretagogues was highly variable in apparently healthy adults aged 50–90 years. Peak GH was significantly related to fasting glucose, insulin, BMI, HDL cholesterol, triglycerides, trunk fat and abdominal subregion fat, with fasting glucose ranking first by multiple regression analysis. There was a strong relationship between cardiovascular risk factors and low GH, with individual risk factors being additive. Although these data do not differentiate between low GH being a cause or an effect of these cardiovascular risk factors, they indicate that the relationship between low GH and increased cardiovascular risk may be physiologically important in the absence of pituitary disease

Genome Wide Meta-analysis Highlights the Role of Genetic Variation in RARRES2 in the Regulation of Circulating Serum Chemerin.

Chemerin is an adipokine proposed to link obesity and chronic inflammation of adipose tissue. Genetic factors determining chemerin release from adipose tissue are yet unknown. We conducted a meta-analysis of genome-wide association studies (GWAS) for serum chemerin in three independent cohorts from Europe: Sorbs and KORA from Germany and PPP-Botnia from Finland (total N = 2,791). In addition, we measured mRNA expression of genes within the associated loci in peripheral mononuclear cells by micro-arrays, and within adipose tissue by quantitative RT-PCR and performed mRNA expression quantitative trait and expression-chemerin association studies to functionally substantiate our loci. Heritability estimate of circulating chemerin levels was 16.2% in the Sorbs cohort. Thirty single nucleotide polymorphisms (SNPs) at chromosome 7 within the retinoic acid receptor responder 2 (RARRES2)/Leucine Rich Repeat Containing (LRRC61) locus reached genome-wide significance (p<5.0×10?8) in the meta-analysis (the strongest evidence for association at rs7806429 with p = 7.8×10?14, beta = ?0.067, explained variance 2.0%). All other SNPs within the cluster were in linkage disequilibrium with rs7806429 (minimum r2 = 0.43 in the Sorbs cohort). The results of the subgroup analyses of males and females were consistent with the results found in the total cohort. No significant SNP-sex interaction was observed. rs7806429 was associated with mRNA expression of RARRES2 in visceral adipose tissue in women (p<0.05 after adjusting for age and body mass index). In conclusion, the present meta-GWAS combined with mRNA expression studies highlights the role of genetic variation in the RARRES2 locus in the regulation of circulating chemerin concentrations

Adiponectin levels in people with Latent Autoimmune Diabetes-a case control study

<p>Abstract</p> <p>Background</p> <p>To examine adiponectin levels in people with Latent Autoimmune Diabetes in Adults using a matched pair case control study.</p> <p>Findings</p> <p>Patients with LADA (n = 64), were matched for sex with type 2 diabetic and non-diabetic controls. A matched paired T-test was used to examine average adiponectin levels in the LADA patients' versus controls. The average adiponectin level for the LADA patients was 9.96 μg/ml compared to 6.4 μg/ml for Type 2 matched controls and 9.6 μg/ml for non-diabetic controls. Mean difference for the LADA-type 2 comparison was calculated after data was log transformed and showed a difference of 1.58 μg/ml (95%CI: 1.28-1.95, p = 0.0001). There was no significant difference between LADA and non-diabetic controls (p = 0.54).</p> <p>Conclusions</p> <p>Adiponectin levels are higher among people with LADA compared to those with type 2 diabetes and are equivalent to levels seen in non-diabetic controls. This suggests that risk of complications in LADA, as with type 1 diabetes may be related more to glycaemic control rather than to factors of the metabolic syndrome.</p

Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution.

To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity