Clinical profiles of post-load glucose subgroups and their association with glycaemic traits over time: An IMI-DIRECT study.

AIM: To examine the hypothesis that, based on their glucose curves during a seven-point oral glucose tolerance test, people at elevated type 2 diabetes risk can be divided into subgroups with different clinical profiles at baseline and different degrees of subsequent glycaemic deterioration. METHODS: We included 2126 participants at elevated type 2 diabetes risk from the Diabetes Research on Patient Stratification (IMI-DIRECT) study. Latent class trajectory analysis was used to identify subgroups from a seven-point oral glucose tolerance test at baseline and follow-up. Linear models quantified the associations between the subgroups with glycaemic traits at baseline and 18 months. RESULTS: At baseline, we identified four glucose curve subgroups, labelled in order of increasing peak levels as 1-4. Participants in Subgroups 2-4, were more likely to have higher insulin resistance (homeostatic model assessment) and a lower Matsuda index, than those in Subgroup 1. Overall, participants in Subgroups 3 and 4, had higher glycaemic trait values, with the exception of the Matsuda and insulinogenic indices. At 18 months, change in homeostatic model assessment of insulin resistance was higher in Subgroup 4 (ß = 0.36, 95% CI 0.13-0.58), Subgroup 3 (ß = 0.30; 95% CI 0.10-0.50) and Subgroup 2 (ß = 0.18; 95% CI 0.04-0.32), compared to Subgroup 1. The same was observed for C-peptide and insulin. Five subgroups were identified at follow-up, and the majority of participants remained in the same subgroup or progressed to higher peak subgroups after 18 months. CONCLUSIONS: Using data from a frequently sampled oral glucose tolerance test, glucose curve patterns associated with different clinical characteristics and different rates of subsequent glycaemic deterioration can be identified.

Study profile: the Durban Diabetes Study (DDS): a platform for chronic disease research.

The Durban Diabetes Study (DDS) is a population-based cross-sectional survey of an urban black population in the eThekwini Municipality (city of Durban) in South Africa. The survey combines health, lifestyle and socioeconomic questionnaire data with standardised biophysical measurements, biomarkers for non-communicable and infectious diseases, and genetic data. Data collection for the study is currently underway and the target sample size is 10 000 participants. The DDS has an established infrastructure for survey fieldwork, data collection and management, sample processing and storage, managed data sharing and consent for re-approaching participants, which can be utilised for further research studies. As such, the DDS represents a rich platform for investigating the distribution, interrelation and aetiology of chronic diseases and their risk factors, which is critical for developing health care policies for disease management and prevention. For data access enquiries please contact the African Partnership for Chronic Disease Research (APCDR) at data@apcdr.org or the corresponding author.

H3Africa multi-centre study of the prevalence and environmental and genetic determinants of type 2 diabetes in sub-Saharan Africa: study protocol.

The burden and aetiology of type 2 diabetes (T2D) and its microvascular complications may be influenced by varying behavioural and lifestyle environments as well as by genetic susceptibility. These aspects of the epidemiology of T2D have not been reliably clarified in sub-Saharan Africa (SSA), highlighting the need for context-specific epidemiological studies with the statistical resolution to inform potential preventative and therapeutic strategies. Therefore, as part of the Human Heredity and Health in Africa (H3Africa) initiative, we designed a multi-site study comprising case collections and population-based surveys at 11 sites in eight countries across SSA. The goal is to recruit up to 6000 T2D participants and 6000 control participants. We will collect questionnaire data, biophysical measurements and biological samples for chronic disease traits, risk factors and genetic data on all study participants. Through integrating epidemiological and genomic techniques, the study provides a framework for assessing the burden, spectrum and environmental and genetic risk factors for T2D and its complications across SSA. With established mechanisms for fieldwork, data and sample collection and management, data-sharing and consent for re-approaching participants, the study will be a resource for future research studies, including longitudinal studies, prospective case ascertainment of incident disease and interventional studies.

Serum sex hormone-binding globulin and testosterone in relation to cardiovascular disease risk factors in young men: a population-based study.

OBJECTIVE: Reduced sex hormone-binding globulin (SHBG) concentration predicts insulin resistance and type 2 diabetes, but its association with cardiovascular disease (CVD) risk is unclear. We examined the association between SHBG and cardiovascular risk factors, independently of total testosterone (TT), in young men. DESIGN: Observational, cross-sectional study. SETTING: General community. PARTICIPANTS: The study included 2716 men aged 31 years in the Northern Finland Birth Cohort in 1996 with clinical examination data and fasting blood samples. OUTCOME VARIABLES: Blood pressure (BP), lipids and C-reactive protein (CRP) as biological CVD risk markers. RESULTS: SHBG concentration was significantly and inversely related to systolic and diastolic BP, triglycerides and CRP, but positively to HDL cholesterol after adjusting for insulin, BMI, waist circumference, smoking, education and physical activity (all P<0.05). These linearly graded associations persisted with additional adjustment for TT. SHBG was significantly associated with total cholesterol only with adjustment for covariates and TT (P<0.05). The direction and magnitude of associations between TT and risk factors were variable, but further adjustment for insulin, adiposity and SHBG showed positive associations between TT and BP, total and LDL-cholesterol and triglycerides and an inverse association with CRP (all P<0.05), but its relation with HDL-cholesterol was no longer significant. CONCLUSIONS: In this cohort of young adult men, higher SHBG concentration was associated with a more favourable CVD risk profile, independently of TT. SHBG concentration modified the associations of TT with CVD risk factors.

Fat depot-specific mRNA expression of novel loci associated with waist-hip ratio.

OBJECTIVE: We hypothesized that genes within recently identified loci associated with waist-hip ratio (WHR) exhibit fat depot-specific mRNA expression, which correlates with obesity-related traits. METHODS: Adipose tissue (AT) mRNA expression of 6 genes (TBX15/WARS2, STAB1, PIGC, ZNRF3 and GRB14) within these loci showing coincident cis-expression quantitative trait loci was measured in 222 paired samples of human visceral (vis) and subcutaneous (sc) AT. The relationship of mRNA expression levels with obesity-related quantitative traits was assessed by Pearson's correlation analyses. Multivariate linear relationships were assessed by generalized linear regression models. RESULTS: Whereas only PIGC, ZNFR3 and STAB1 mRNA expression in sc AT correlated nominally with WHR (P<0.05, adjusted for age and sex), mRNA expression of all studied genes in at least one of the fat depots correlated significantly with vis and/or sc fat area (P ranging from 0.05 to 4.0 × 10(6), adjusted for age and sex). Consistently, the transcript levels of WARS, PIGC and GRB14 were nominally associated with body mass index (BMI) (P ranging from 0.02 to 9.2 × 10(5), adjusted for age and sex). Moreover, independent of sex, obesity and diabetes status, differential expression between vis and sc AT was observed for all tested genes (P<0.01). Finally, the rs10195252 T-allele was nominally associated with increased GRB14 sc mRNA expression (P=0.025 after adjusting for age, sex and BMI). CONCLUSIONS: Our data including the inter-depot variability of mRNA expression suggests that genes within the WHR-associated loci might be involved in the regulation of fat distribution.

A common biological basis of obesity and nicotine addiction.

Smoking influences body weight such that smokers weigh less than non-smokers and smoking cessation often leads to weight increase. The relationship between body weight and smoking is partly explained by the effect of nicotine on appetite and metabolism. However, the brain reward system is involved in the control of the intake of both food and tobacco. We evaluated the effect of single-nucleotide polymorphisms (SNPs) affecting body mass index (BMI) on smoking behavior, and tested the 32 SNPs identified in a meta-analysis for association with two smoking phenotypes, smoking initiation (SI) and the number of cigarettes smoked per day (CPD) in an Icelandic sample (N=34,216 smokers). Combined according to their effect on BMI, the SNPs correlate with both SI (r=0.019, P=0.00054) and CPD (r=0.032, P=8.0 × 10(-7)). These findings replicate in a second large data set (N=127,274, thereof 76,242 smokers) for both SI (P=1.2 × 10(-5)) and CPD (P=9.3 × 10(-5)). Notably, the variant most strongly associated with BMI (rs1558902-A in FTO) did not associate with smoking behavior. The association with smoking behavior is not due to the effect of the SNPs on BMI. Our results strongly point to a common biological basis of the regulation of our appetite for tobacco and food, and thus the vulnerability to nicotine addiction and obesity.

The link between family history and risk of type 2 diabetes is not explained by anthropometric, lifestyle or genetic risk factors: the EPIC-InterAct study.

AIMS/HYPOTHESIS: Although a family history of type 2 diabetes is a strong risk factor for the disease, the factors mediating this excess risk are poorly understood. In the InterAct case-cohort study, we investigated the association between a family history of diabetes among different family members and the incidence of type 2 diabetes, as well as the extent to which genetic, anthropometric and lifestyle risk factors mediated this association. METHODS: A total of 13,869 individuals (including 6,168 incident cases of type 2 diabetes) had family history data available, and 6,887 individuals had complete data on all mediators. Country-specific Prentice-weighted Cox models were fitted within country, and HRs were combined using random effects meta-analysis. Lifestyle and anthropometric measurements were performed at baseline, and a genetic risk score comprising 35 polymorphisms associated with type 2 diabetes was created. RESULTS: A family history of type 2 diabetes was associated with a higher incidence of the condition (HR 2.72, 95% CI 2.48, 2.99). Adjustment for established risk factors including BMI and waist circumference only modestly attenuated this association (HR 2.44, 95% CI 2.03, 2.95); the genetic score alone explained only 2% of the family history-associated risk of type 2 diabetes. The greatest risk of type 2 diabetes was observed in those with a biparental history of type 2 diabetes (HR 5.14, 95% CI 3.74, 7.07) and those whose parents had been diagnosed with diabetes at a younger age (<50 years; HR 4.69, 95% CI 3.35, 6.58), an effect largely confined to a maternal family history. CONCLUSIONS/INTERPRETATION: Prominent lifestyle, anthropometric and genetic risk factors explained only a marginal proportion of the excess risk associated with family history, highlighting the fact that family history remains a strong, independent and easily assessed risk factor for type 2 diabetes. Discovering factors that will explain the association of family history with type 2 diabetes risk will provide important insight into the aetiology of type 2 diabetes.

The genetics of type 2 diabetes and its clinical relevance.

The increasing worldwide prevalence of type 2 diabetes (T2D) motivates efforts to use genetics to define key pathways involved in disease predisposition, and thereby to improve management of the disease. Research over the past 5 years has taken the total number of genetic loci implicated in T2D susceptibility beyond 60, and the emphasis is now shifting to the translation of these genetic insights into clinical value. Clinical translation may flow from the identification of novel therapeutic targets, but opportunities also exist with respect to individual prediction, diagnostic biomarkers and therapeutic optimization. To date, the main clinical impact has been seen for relatively rare, monogenic forms of diabetes rather than common T2D. However, the advent of high throughput sequencing approaches may herald discovery of rare and low frequency variants that offer greater translational potential.

Apolipoprotein M can discriminate HNF1A-MODY from Type 1 diabetes.

AIMS: Missed diagnosis of maturity-onset diabetes of the young (MODY) has led to an interest in biomarkers that enable efficient prioritization of patients for definitive molecular testing. Apolipoprotein M (apoM) was suggested as a biomarker for hepatocyte nuclear factor 1 alpha (HNF1A)-MODY because of its reduced expression in Hnf1a(-/-) mice. However, subsequent human studies examining apoM as a biomarker have yielded conflicting results. We aimed to evaluate apoM as a biomarker for HNF1A-MODY using a highly specific and sensitive ELISA. METHODS: ApoM concentration was measured in subjects with HNF1A-MODY (n = 69), Type 1 diabetes (n = 50), Type 2 diabetes (n = 120) and healthy control subjects (n = 100). The discriminative accuracy of apoM and of the apoM/HDL ratio for diabetes aetiology was evaluated. RESULTS: Mean (standard deviation) serum apoM concentration (µmol/l) was significantly lower for subjects with HNF1A-MODY [0.86 (0.29)], than for those with Type 1 diabetes [1.37 (0.26), P = 3.1 × 10(-18) ) and control subjects [1.34 (0.22), P = 7.2 × 10(-19) ). There was no significant difference in apoM concentration between subjects with HNF1A-MODY and Type 2 diabetes [0.89 (0.28), P = 0.13]. The C-statistic measure of discriminative accuracy for apoM was 0.91 for HNF1A-MODY vs. Type 1 diabetes, indicating high discriminative accuracy. The apoM/HDL ratio was significantly lower in HNF1A-MODY than other study groups. However, this ratio did not perform well in discriminating HNF1A-MODY from either Type 1 diabetes (C-statistic = 0.79) or Type 2 diabetes (C-statistic = 0.68). CONCLUSIONS: We confirm an earlier report that serum apoM levels are lower in HNF1A-MODY than in controls. Serum apoM provides good discrimination between HNF1A-MODY and Type 1 diabetes and warrants further investigation for clinical utility in diabetes diagnostics.

The genetic and epigenetic basis of type 2 diabetes and obesity.

Type 2 diabetes (T2D) and obesity are complex disorders that constitute major public health problems. The evidence for familial aggregation of both T2D and obesity is substantial. To date, more than 150 genetic loci are associated with the development of monogenic, syndromic, or multifactorial forms of T2D or obesity. However, the proportion of overall trait variance explained by these associated loci is modest (~5-10% for T2D, ~2% for body mass index (BMI)). Some of the familial aggregation not attributable to known genetic variation, as well as many of the effects of environmental exposures, may reflect epigenetic processes. In this review, we discuss the evidence concerning the genetic contribution to individual risk of T2D and obesity, and explore the potential role of epigenetic mechanisms. We also explain how genetics, epigenetics, and environment are likely to interact to define the individual risk of disease.

Impact of FTO genotypes on BMI and weight in polycystic ovary syndrome: a systematic review and meta-analysis.

AIMS/HYPOTHESIS: FTO gene single nucleotide polymorphisms (SNPs) have been shown to be associated with obesity-related traits and type 2 diabetes. Several small studies have suggested a greater than expected effect of the FTO rs9939609 SNP on weight in polycystic ovary syndrome (PCOS). We therefore aimed to examine the impact of FTO genotype on BMI and weight in PCOS. METHODS: A systematic search of medical databases (PubMed, EMBASE and Cochrane CENTRAL) was conducted up to the end of April 2011. Seven studies describing eight distinct PCOS cohorts were retrieved; seven were genotyped for SNP rs9939609 and one for SNP rs1421085. The per allele effect on BMI and body weight increase was calculated and subjected to meta-analysis. RESULTS: A total of 2,548 women with PCOS were included in the study; 762 were TT homozygotes, 1,253 had an AT/CT genotype, and 533 were AA/CC homozygotes. Each additional copy of the effect allele (A/C) increased the BMI by a mean of 0.19 z score units (95% CI 0.13, 0.24; p = 2.26 × 10(-11)) and body weight by a mean of 0.20 z score units (95% CI 0.14, 0.26; p = 1.02 × 10(-10)). This translated into an approximately 3.3 kg/m(2) increase in BMI and an approximately 9.6 kg gain in body weight between TT and AA/CC homozygotes. The association between FTO genotypes and BMI was stronger in the cohorts with PCOS than in the general female populations from large genome-wide association studies. Deviation from an additive genetic model was observed in heavier populations. CONCLUSIONS/INTERPRETATION: The effect of FTO SNPs on obesity-related traits in PCOS seems to be more than two times greater than the effect found in large population-based studies. This suggests an interaction between FTO and the metabolic context or polygenic background of PCOS.

A gene variant near ATM is significantly associated with metformin treatment response in type 2 diabetes: a replication and meta-analysis of five cohorts.

AIMS/HYPOTHESIS: In this study we aimed to replicate the previously reported association between the glycaemic response to metformin and the SNP rs11212617 at a locus that includes the ataxia telangiectasia mutated (ATM) gene in multiple additional populations. METHODS: Incident users of metformin selected from the Diabetes Care System West-Friesland (DCS, n = 929) and the Rotterdam Study (n = 182) from the Netherlands, and the CARDS Trial (n = 254) from the UK were genotyped for rs11212617 and tested for an association with both HbA(1c) reduction and treatment success, defined as the ability to reach the treatment target of an HbA(1c) ≤ 7 % (53 mmol/mol). Finally, a meta-analysis including data from literature was performed. RESULTS: In the DCS cohort, we observed an association between rs11212617 genotype and treatment success on metformin (OR 1.27, 95% CI 1.03, 1.58, p = 0.028); in the smaller Rotterdam Study cohort, a numerically similar but non-significant trend was observed (OR 1.45, 95% CI 0.87, 2.39, p = 0.15); while in the CARDS cohort there was no significant association. In meta-analyses of these three cohorts separately or combined with the previously published cohorts, rs11212617 genotype is associated with metformin treatment success (OR 1.24, 95% CI 1.04, 1.49, p = 0.016 and OR 1.25, 95% CI 1.33, 1.38, p = 7.8 × 10(-6), respectively). CONCLUSIONS/INTERPRETATION: A gene variant near ATM is significantly associated with metformin treatment response in type 2 diabetic patients from the Netherlands and the UK. This is the first robustly replicated common susceptibility locus found to be associated with metformin treatment response.

A large multi-centre European study validates high-sensitivity C-reactive protein (hsCRP) as a clinical biomarker for the diagnosis of diabetes subtypes.

AIMS/HYPOTHESIS: An accurate molecular diagnosis of diabetes subtype confers clinical benefits; however, many individuals with monogenic diabetes remain undiagnosed. Biomarkers could help to prioritise patients for genetic investigation. We recently demonstrated that high-sensitivity C-reactive protein (hsCRP) levels are lower in UK patients with hepatocyte nuclear factor 1 alpha (HNF1A)-MODY than in other diabetes subtypes. In this large multi-centre study we aimed to assess the clinical validity of hsCRP as a diagnostic biomarker, examine the genotype-phenotype relationship and compare different hsCRP assays. METHODS: High-sensitivity CRP levels were analysed in individuals with HNF1A-MODY (n = 457), glucokinase (GCK)-MODY (n = 404), hepatocyte nuclear factor 4 alpha (HNF4A)-MODY (n = 54) and type 2 diabetes (n = 582) from seven European centres. Three common assays for hsCRP analysis were evaluated. We excluded 121 participants (8.1%) with hsCRP values >10 mg/l. The discriminative power of hsCRP with respect to diabetes aetiology was assessed by receiver operating characteristic curve-derived C-statistic. RESULTS: In all centres and irrespective of the assay method, meta-analysis confirmed significantly lower hsCRP levels in those with HNF1A-MODY than in those with other aetiologies (z score -21.8, p < 5 × 10(-105)). HNF1A-MODY cases with missense mutations had lower hsCRP levels than those with truncating mutations (0.03 vs 0.08 mg/l, p < 5 × 10(-5)). High-sensitivity CRP values between assays were strongly correlated (r (2) ≥ 0.91, p ≤ 1 × 10(-5)). Across the seven centres, the C-statistic for distinguishing HNF1A-MODY from young adult-onset type 2 diabetes ranged from 0.79 to 0.97, indicating high discriminative accuracy. CONCLUSIONS/INTERPRETATION: In the largest study to date, we have established that hsCRP is a clinically valid biomarker for HNF1A-MODY in European populations. Given the modest costs and wide availability, hsCRP could translate rapidly into clinical practice, considerably improving diagnosis rates in monogenic diabetes.

Sequencing PDX1 (insulin promoter factor 1) in 1788 UK individuals found 5% had a low frequency coding variant, but these variants are not associated with Type 2 diabetes.

AIM: Genome-wide association studies have identified >30 common variants associated with Type 2 diabetes (>5% minor allele frequency). These variants have small effects on individual risk and do not account for a large proportion of the heritable component of the disease. Monogenic forms of diabetes are caused by mutations that occur in <1:2000 individuals and follow strict patterns of inheritance. In contrast, the role of low frequency genetic variants (minor allele frequency 0.1-5%) in Type 2 diabetes is not known. The aim of this study was to assess the role of low frequency PDX1 (also called IPF1) variants in Type 2 diabetes. METHODS: We sequenced the coding and flanking intronic regions of PDX1 in 910 patients with Type 2 diabetes and 878 control subjects. RESULTS: We identified a total of 26 variants that occurred in 5.3% of individuals, 14 of which occurred once. Only D76N occurred in >1%. We found no difference in carrier frequency between patients (5.7%) and control subjects (5.0%) (P=0.46). There were also no differences between patients and control subjects when analyses were limited to subsets of variants. The strongest subset were those variants in the DNA binding domain where all five variants identified were only found in patients (P=0.06). CONCLUSION: Approximately 5% of UK individuals carry a PDX1 variant, but there is no evidence that these variants, either individually or cumulatively, predispose to Type 2 diabetes. Further studies will need to consider strategies to assess the role of multiple variants that occur in <1 in 1000 individuals.

Dorothy Hodgkin Lecture 2010. From hype to hope? A journey through the genetics of Type 2 diabetes.

Recent advances in genetic analysis have enabled researchers to perform genome-wide surveys for common DNA sequence variants associated with risk of Type 2 diabetes and related traits. Over the past 4 years, these endeavours have extended the number of proven Type 2 diabetes-susceptibility loci from a handful to the current total of over 40. Each of these loci provides an opportunity to uncover insights into the biology of glucose regulation and the pathogenesis of Type 2 diabetes, insights which should support clinical translation to identify novel ways of treating and preventing disease. Here, I describe (i) progress in identification of diabetes-susceptibility loci; (ii) biological insights that have been gained in the relatively short period since these loci were discovered; and (iii) the challenges that need to be addressed if we are to maximize the translational benefits of this research.

Common nonsynonymous substitutions in SLCO1B1 predispose to statin intolerance in routinely treated individuals with type 2 diabetes: a go-DARTS study.

SLCO1B1 gene variants are associated with severe statin-induced myopathy. We examined whether these variants are also associated with general statin intolerance in a large population of patients with type 2 diabetes receiving statins as part of routine clinical care. A total of 4,196 individuals were genotyped for rs4149056 (Val174Ala) and rs2306283 (Asp130Asn). Intolerance was defined by serum biochemistry and also by discontinuation, switching, or reduction in dose of the prescribed statin drug. Ala174 was associated with higher intolerance (odds ratio = 2.05, P = 0.043), whereas Asp130 was associated with lower intolerance (odds ratio = 0.71, P = 0.026). Ala174 was associated with a lower low-density lipoprotein cholesterol (LDLc) response to statins (P = 0.01) whereas 130D was associated with a greater LDLc response to statins (P = 0.048), as previously reported; however, this association was no longer present when data for statin-intolerant individuals were removed from the analysis. This study suggests that common genetic variants selected for an extreme phenotype of statin-induced myopathy also predispose to more common milder statin intolerance and may, for this reason, impact lipid-lowering efficacy.

A role for coding functional variants in HNF4A in type 2 diabetes susceptibility.

AIMS/HYPOTHESIS: Rare mutations in the gene HNF4A, encoding the transcription factor hepatocyte nuclear factor 4α (HNF-4A), account for ~5% of cases of MODY and more frequent variants in this gene may be involved in multifactorial forms of diabetes. Two low-frequency, non-synonymous variants in HNF4A (V255M, minor allele frequency [MAF] ~0.1%; T130I, MAF ~3.0%)-known to influence downstream HNF-4A target gene expression-are of interest, but previous type 2 diabetes association reports were inconclusive. We aimed to evaluate the contribution of these variants to type 2 diabetes susceptibility through large-scale association analysis. METHODS: We genotyped both variants in at least 5,745 cases and 14,756 population controls from the UK and Denmark. We also undertook an expanded association analysis that included previously reported and novel genotype data obtained in Danish, Finnish, Canadian and Swedish samples. A meta-analysis incorporating all published association studies of the T130I variant was subsequently carried out in a maximum sample size of 14,279 cases and 26,835 controls. RESULTS: We found no association between V255M and type 2 diabetes in either the initial (p = 0.28) or the expanded analysis (p = 0.44). However, T130I demonstrated a modest association with type 2 diabetes in the UK and Danish samples (additive per allele OR 1.17 [95% CI 1.08-1.28]; p = 1.5 × 10⁻4), which was strengthened in the meta-analysis (OR 1.20 [95% CI 1.10-1.30]; p = 2.1 × 10⁻5). CONCLUSIONS/INTERPRETATION: Our data are consistent with T130I as a low-frequency variant influencing type 2 diabetes risk, but are not conclusive when judged against stringent standards for genome-wide significance. This study exemplifies the difficulties encountered in association testing of low-frequency variants.

Global microRNA expression profiles in insulin target tissues in a spontaneous rat model of type 2 diabetes.

AIMS/HYPOTHESIS: MicroRNAs regulate a broad range of biological mechanisms. To investigate the relationship between microRNA expression and type 2 diabetes, we compared global microRNA expression in insulin target tissues from three inbred rat strains that differ in diabetes susceptibility. METHODS: Using microarrays, we measured the expression of 283 microRNAs in adipose, liver and muscle tissue from hyperglycaemic (Goto-Kakizaki), intermediate glycaemic (Wistar Kyoto) and normoglycaemic (Brown Norway) rats (n = 5 for each strain). Expression was compared across strains and validated using quantitative RT-PCR. Furthermore, microRNA expression variation in adipose tissue was investigated in 3T3-L1 adipocytes exposed to hyperglycaemic conditions. RESULTS: We found 29 significantly differentiated microRNAs (p(adjusted) < 0.05): nine in adipose tissue, 18 in liver and two in muscle. Of these, five microRNAs had expression patterns that correlated with the strain-specific glycaemic phenotype. MiR-222 (p(adjusted) = 0.0005) and miR-27a (p(adjusted) = 0.006) were upregulated in adipose tissue; miR-195 (p(adjusted) = 0.006) and miR-103 (p(adjusted) = 0.04) were upregulated in liver; and miR-10b (p(adjusted) = 0.004) was downregulated in muscle. Exposure of 3T3-L1 adipocytes to increased glucose concentration upregulated the expression of miR-222 (p = 0.008), miR-27a (p = 0.02) and the previously reported miR-29a (p = 0.02). Predicted target genes of these differentially expressed microRNAs are involved in pathways relevant to type 2 diabetes. CONCLUSION: The expression patterns of miR-222, miR-27a, miR-195, miR-103 and miR-10b varied with hyperglycaemia, suggesting a role for these microRNAs in the pathophysiology of type 2 diabetes, as modelled by the Gyoto-Kakizaki rat. We observed similar patterns of expression of miR-222, miR-27a and miR-29a in adipocytes as a response to increased glucose levels, which supports our hypothesis that altered expression of microRNAs accompanies primary events related to the pathogenesis of type 2 diabetes.

Lack of significant effects of the type 2 diabetes susceptibility loci JAZF1, CDC123/CAMK1D, NOTCH2, ADAMTS9, THADA, and TSPAN8/LGR5 on diabetes and quantitative metabolic traits.

Recently, several novel loci reaching genome-wide significance levels for type 2 diabetes (T2D) were identified through a meta-analysis of three genome-wide scans and large-scale follow-up. The aim of our study was to investigate the association of these loci with T2D and related subphenotypes in two cohorts from Germany. We performed an association study of 9 SNPs in or around JAZF1, CDC123/ CAMK1D, NOTCH2, BCL11A, ADAMTS9, VEGFA, DCD, THADA, and TSPAN8/ LGR5 with T2D and related quantitative traits (fasting insulin and glucose, indices derived from OGTT) in the isolated population of Sorbs (205 cases and 695 controls) and in a mixed German population (Leipzig) (938 subjects with and 918 without T2D). None of the variants was associated with T2D, but the meta-analysis of both cohorts revealed a modest trend of association of rs7578597 in THADA with T2D (p=0.055). Furthermore, Sorbian subjects homozygous for the rs7578597 T-allele had lower mean 30-minute plasma insulin when compared with carriers of the C-allele (p<0.05). The T-allele was also nominally associated with higher fasting plasma glucose in the Leipzig cohort (p<0.05). Although several other SNPs showed some evidence for association with T2D-related traits the effects were not replicated within our study. Associations of the T2D-risk alleles with T2D or related subphenotypes were overall very weak in the approximately 2 700 subjects studied. This is compatible with the modest effect size of these "second sweep" variants, which will require large-scale association studies on quantitative traits to clarify their role in the pathophysiology of T2D.