Botnia Study Research Articles

Excess maternal transmission of variants in the THADA gene to offspring with type 2 diabetes.

Genome-wide association studies (GWAS) have identified more than 65 genetic loci associated with risk of type 2 diabetes. However, the contribution of distorted parental transmission of alleles to risk of type 2 diabetes has been mostly unexplored. Our goal was therefore to search for parent-of-origin effects (POE) among type 2 diabetes loci in families. Families from the Botnia study (n = 4,211, 1,083 families) were genotyped for 72 single-nucleotide polymorphisms (SNPs) associated with type 2 diabetes and assessed for POE on type 2 diabetes. The family-based Hungarian Transdanubian Biobank (HTB) (n = 1,463, >135 families) was used to replicate SNPs showing POE. Association of type 2 diabetes loci within families was also tested. Three loci showed nominal POE, including the previously reported variants in KCNQ1, for type 2 diabetes in families from Botnia (rs2237895: p POE = 0.037), which can be considered positive controls. The strongest POE was seen for rs7578597 SNP in the THADA gene, showing excess transmission of the maternal risk allele T to diabetic offspring (Botnia: p POE = 0.01; HTB p POE = 0.045). These data are consistent with previous evidence of allelic imbalance for expression in islets, suggesting that the THADA gene can be imprinted in a POE-specific fashion. Five CpG sites, including those flanking rs7578597, showed differential methylation between diabetic and non-diabetic donor islets. Taken together, the data emphasise the need for genetic studies to consider from which parent an offspring has inherited a susceptibility allele.

α-Hydroxybutyric Acid Is a Selective Metabolite Biomarker of Impaired Glucose Tolerance.

Plasma metabolites that distinguish isolated impaired glucose tolerance (iIGT) from isolated impaired fasting glucose (iIFG) may be useful biomarkers to predict IGT, a high-risk state for the development of type 2 diabetes. Targeted metabolomics with 23 metabolites previously associated with dysglycemia was performed with fasting plasma samples from subjects without diabetes at time 0 of an oral glucose tolerance test (OGTT) in two observational cohorts: RISC (Relationship Between Insulin Sensitivity and Cardiovascular Disease) and DMVhi (Diabetes Mellitus and Vascular Health Initiative). Odds ratios (ORs) for a one-SD change in the metabolite level were calculated using multiple logistic regression models controlling for age, sex, and BMI to test for associations with iIGT or iIFG versus normal. Selective biomarkers of iIGT were further validated in the Botnia study. α-Hydroxybutyric acid (α-HB) was most strongly associated with iIGT in RISC (OR 2.54 [95% CI 1.86-3.48], P value 5E-9) and DMVhi (2.75 [1.81-4.19], 4E-5) while having no significant association with iIFG. In Botnia, α-HB was selectively associated with iIGT (2.03 [1.65-2.49], 3E-11) and had no significant association with iIFG. Linoleoyl-glycerophosphocholine (L-GPC) and oleic acid were also found to be selective biomarkers of iIGT. In multivariate IGT prediction models, addition of α-HB, L-GPC, and oleic acid to age, sex, BMI, and fasting glucose significantly improved area under the curve in all three cohorts. α-HB, L-GPC, and oleic acid were shown to be selective biomarkers of iIGT, independent of age, sex, BMI, and fasting glucose, in 4,053 subjects without diabetes from three European cohorts. These biomarkers can be used in predictive models to identify subjects with IGT without performing an OGTT.

Identifying glucose thresholds for incident diabetes by physiological analysis: a mathematical solution.

Plasma glucose thresholds for diagnosis of type 2 diabetes are currently based on outcome data (risk of retinopathy), an inherently ill-conditioned approach. A radically different approach is to consider the mechanisms that control plasma glucose, rather than its relation to an outcome. We developed a constraint optimization algorithm to find the minimal glucose levels associated with the maximized combination of insulin sensitivity and β-cell function, the two main mechanisms of glucose homeostasis. We used a training cohort of 1,474 subjects (22% prediabetic, 7.7% diabetic) in whom insulin sensitivity was measured by the clamp technique and β-cell function was determined by mathematical modeling of an oral glucose tolerance test. Optimized fasting glucose levels were ≤ 87 and ≤ 89 mg/dl in ≤ 45-yr-old women and men, respectively, and ≤ 92 and ≤ 95 mg/dl in >45-yr-old women and men, respectively; the corresponding optimized 2-h glucose levels were ≤ 96, ≤ 98, ≤ 103, and ≤ 105 mg/dl. These thresholds were validated in three prospective cohorts of nondiabetic subjects (Relationship Between Insulin Sensitivity and Cardiovascular Disease Study, Botnia Study, and Mexico City Diabetes Study) with baseline and follow-up oral glucose tolerance tests. Of 5,593 participants, 452 progressed to diabetes. Similarly, in the three cohorts, subjects with glucose levels above the estimated thresholds had an odds ratio of 3.74 (95% confidence interval = 2.64-5.48) of progressing, substantially higher than the risk carried by baseline conventionally defined prediabetes [odds ratio = 2.32 (95% confidence interval = 1.91-2.81)]. The concept that optimization of glucose concentrations by direct measures of insulin sensitivity and β-cell function identifies gender- and age-specific thresholds that bear on disease progression is proven in a physiologically sound, quantifiable manner.

Modelling of OGTT curve identifies 1 h plasma glucose level as a strong predictor of incident type 2 diabetes: results from two prospective cohorts.

The relevance of the OGTT in predicting type 2 diabetes is unclear. We assessed the performance of 14 OGTT glucose traits in type 2 diabetes prediction. We studied 2,603 and 2,386 Europeans from the Botnia study and Malmö Prevention Project (MPP) cohorts with baseline OGTT data. Over a follow-up period of 4.94 years and 23.5 years, 155 (5.95%) and 467 (19.57%) participants, respectively, developed type 2 diabetes. The main outcome was incident type 2 diabetes. One-hour plasma glucose (1h-PG) was a fair/good predictor of incident type 2 diabetes in the Botnia study and MPP (AUC for receiver operating characteristic [AUCROC] 0.80 [0.77, 0.84] and 0.70 [0.68, 0.73]). 1h-PG alone outperformed the prediction model of multiple clinical risk factors (age, sex, BMI, family history of type 2 diabetes) in the Botnia study and MPP (AUCROC 0.75 [0.72, 0.79] and 0.67 [0.64, 0.70]). The same clinical risk factors added to 1h-PG modestly increased prediction for incident type 2 diabetes (Botnia, AUCROC 0.83 [0.80, 0.86]; MPP, AUCROC 0.74 [0.72, 0.77]). 1h-PG also outperformed HbA1c in predicting type 2 diabetes in the Botnia cohort. A 1h-PG value of 8.9 mmol/l and 8.4 mmol/l was the optimal cut-point for initial screening and selection of high-risk individuals in the Botnia study and MPP, respectively, and represented 30% and 37% of all participants in these cohorts. High-risk individuals had a substantially increased risk of incident type 2 diabetes (OR 8.0 [5.5, 11.6] and 3.8 [3.1, 4.7]) and captured 75% and 62% of all incident type 2 diabetes in the Botnia study and MPP. 1h-PG is a valuable prediction tool for identifying adults at risk for future type 2 diabetes.

Genetic Variants Associated With Glycine Metabolism and Their Role in Insulin Sensitivity and Type 2 Diabetes

Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity–related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites—glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)—and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits.

Common variant in the HMGA2 gene increases susceptibility to nephropathy in patients with type 2 diabetes

Type 2 diabetes is a chronic metabolic disorder associated with devastating microvascular complications. Genome-wide association studies have identified more than 60 genetic variants associated with type 2 diabetes and/or glucose and insulin traits, but their role in the progression of diabetes is not established. The aim of this study was to explore whether these variants were also associated with the development of nephropathy in patients with type 2 diabetes. We studied 28 genetic variants in 2,229 patients with type 2 diabetes from the local Malmö Scania Diabetes Registry (SDR) published during 2007-2010. Diabetic nephropathy (DN) was defined as micro- or macroalbuminuria and/or end-stage renal disease. Estimated glomerular filtration rate (eGFR) was assessed using the MDRD-4 formula. Replication genotyping of rs1531343 was performed in diabetic (Steno type 2 diabetes [n = 345], Genetics of Diabetes Audit and Research in Tayside Scotland [Go-DARTS] [n = 784]) and non-diabetic (Malmö Preventive Project [n = 2,523], Botnia study [n = 2,247]) cohorts. In the SDR, HMGA2 single-nucleotide polymorphism rs1531343 was associated with DN (OR 1.50, 95% CI 1.20, 1.87, p = 0.00035). In the combined analysis totalling 3,358 patients with type 2 diabetes (n = 1,233 cases, n = 2,125 controls), carriers of the C-allele had a 1.45-fold increased risk of developing nephropathy (95% CI 1.20, 1.75, p = 0.00010). Furthermore, the risk C-allele was associated with lower eGFR in patients with type 2 diabetes (n = 2,499, β ± SEM, -3.7 ± 1.2ml/min, p = 0.002) and also in non-diabetic individuals (n = 17,602, β ± SEM, -0.008 ± 0.003ml/min (log( e )), p = 0.006). These data demonstrate that the HMGA2 variant seems to be associated with increased risk of developing nephropathy in patients with type 2 diabetes and lower eGFR in both diabetic and non-diabetic individuals and could thus be a common denominator in the pathogenesis of type 2 diabetes and kidney complications.

An Evidence-Based Review of Exercise and Metabolic Syndrome

An Evidence-Based Review of Exercise and Metabolic Syndrome

Two-step approach for the prediction of future type 2 diabetes risk.

OBJECTIVETo develop a model for the prediction of type 2 diabetes mellitus (T2DM) risk on the basis of a multivariate logistic model and 1-h plasma glucose concentration (1-h PG).RESEARCH DESIGN AND METHODSThe model was developed in a cohort of 1,562 nondiabetic subjects from the San Antonio Heart Study (SAHS) and validated in 2,395 nondiabetic subjects in the Botnia Study. A risk score on the basis of anthropometric parameters, plasma glucose and lipid profile, and blood pressure was computed for each subject. Subjects with a risk score above a certain cut point were considered to represent high-risk individuals, and their 1-h PG concentration during the oral glucose tolerance test was used to further refine their future T2DM risk.RESULTSWe used the San Antonio Diabetes Prediction Model (SADPM) to generate the initial risk score. A risk-score value of 0.065 was found to be an optimal cut point for initial screening and selection of high-risk individuals. A 1-h PG concentration >140 mg/dL in high-risk individuals (whose risk score was >0.065) was the optimal cut point for identification of subjects at increased risk. The two cut points had 77.8, 77.4, and 44.8% (for the SAHS) and 75.8, 71.6, and 11.9% (for the Botnia Study) sensitivity, specificity, and positive predictive value, respectively, in the SAHS and Botnia Study.CONCLUSIONSA two-step model, based on the combination of the SADPM and 1-h PG, is a useful tool for the identification of high-risk Mexican-American and Caucasian individuals.

Heritability and familiality of type 2 diabetes and related quantitative traits in the Botnia Study

To study the heritability and familiality of type 2 diabetes and related quantitative traits in families from the Botnia Study in Finland. Heritability estimates for type 2 diabetes adjusted for sex, age and BMI are provided for different age groups of type 2 diabetes and for 34 clinical and metabolic traits in 5,810 individuals from 942 families using a variance component model (SOLAR). In addition, family means of these traits and their distribution across families are calculated. The strongest heritability for type 2 diabetes was seen in patients with age at onset 35-60 years (h (2) = 0.69). However, including patients with onset up to 75 years dropped the h (2) estimates to 0.31. Among quantitative traits, the highest h (2) estimates in all individuals and in non-diabetic individuals were seen for lean body mass (h (2) = 0.53-0.65), HDL-cholesterol (0.52-0.61) and suppression of NEFA during OGTT (0.63-0.76) followed by measures of insulin secretion (insulinogenic index [IG(30)] = 0.41-0.50) and insulin action (insulin sensitivity index [ISI] = 0.37-0.40). In contrast, physical activity showed rather low heritability (0.16-0.18), whereas smoking showed strong heritability (0.57-0.59). Family means of these traits differed two- to fivefold between families belonging to the lowest and highest quartile of the trait (p < 0.00001). To detect stronger genetic effects in type 2 diabetes, it seems reasonable to restrict inclusion of patients to those with age at onset 35-60 years. Sequencing of families with extreme quantitative traits could be an important next step in the dissection of the genetics of type 2 diabetes.

A family history of diabetes is associated with reduced physical fitness in the Prevalence, Prediction and Prevention of Diabetes (PPP)–Botnia study

We studied the impact of a family history of type 2 diabetes on physical fitness, lifestyle factors and diabetes-related metabolic factors. The Prevalence, Prediction and Prevention of Diabetes (PPP)-Botnia study is a population-based study in Western Finland, which includes a random sample of 5,208 individuals aged 18 to 75 years identified through the national Finnish Population Registry. Physical activity, dietary habits and family history of type 2 diabetes were assessed by questionnaires and physical fitness by a validated 2 km walking test. Insulin secretion and action were assessed based upon OGTT measurements of insulin and glucose. A family history of type 2 diabetes was associated with a 2.4-fold risk of diabetes and lower physical fitness (maximal aerobic capacity 29.2 +/- 7.2 vs 32.1 +/- 7.0, p = 0.01) despite having similar reported physical activity to that of individuals with no family history. The same individuals also had reduced insulin secretion adjusted for insulin resistance, i.e. disposition index (p < 0.001) despite having higher BMI (27.4 +/- 4.6 vs 26.0 +/- 4.3 kg/m(2), p < 0.001). Individuals with a family history of type 2 diabetes are characterised by lower physical fitness, which cannot solely be explained by lower physical activity. They also have an impaired capacity of beta cells to compensate for an increase in insulin resistance imposed by an increase in BMI. These defects should be important targets for interventions aiming at preventing type 2 diabetes in individuals with inherited susceptibility to the disease.

The shape of plasma glucose concentration curve during OGTT predicts future risk of type 2 diabetes

The aim of the study is to assess the relationship between the shape of plasma glucose concentration during the OGTT and future risk for T2DM. 2445 non-diabetic subjects from the Botnia study received an OGTT at baseline and after 7-8 years of follow-up. NGT and IFG subjects who returned their plasma glucose concentration following an ingested glucose load below FPG within 60 min had increased insulin sensitivity, greater insulin secretion and lower risk for future T2DM compared to NGT and IFG subjects whose post-load plasma glucose concentration required 120 min or longer to return their plasma glucose level to FPG level. IGT subjects who had a lower plasma glucose concentration at 1-h compared to 2-h during OGTT had greater insulin sensitivity, better beta cell function and lower risk for future T2DM. These data suggest that the shape of glucose curve can be utilized to assess future risk for T2DM.

An investigation of serum concentration of apoM as a potential MODY3 marker using a novel ELISA

To investigate the fitness of serum apolipoprotein M (apoM) concentration as a marker for maturity-onset diabetes of the young 3 (MODY3). This study consisted of two parts. A family study included 71 carriers of the P291fsinsC mutation in hepatocyte nuclear factor-1alpha (HNF-1alpha) from the Finnish Botnia study, 53 of whom were diabetic, and 75 matched family controls. A second, case-control study included 24 MODY3 patients, 17 healthy MODY3 mutation carriers, 11 MODY1 patients, 18 type 2 diabetes patients and 19 healthy control individuals. Subjects in the case-control study were recruited from the Botnia study or the Clinic of Endocrinology, Malmö University Hospital. Serum apoM levels were measured using a novel ELISA based on two monoclonal apoM antibodies. In the family study, mean serum apoM was 10% lower in female carriers of the P291fsinsC mutation compared to the family controls (P = 0.0058), a difference which remained significant after adjustment for diabetes status. There was no observed difference between groups for men. In the case-control study, no significant difference in apoM concentration was observed between MODY3 and type 2 diabetes patients, neither before nor after adjustment for total cholesterol. Female carriers of the P291fsinsC mutation in HNF-1alpha displayed slightly lower apoM serum levels. This difference is too small for apoM to be reliably employed as a biomarker for HNF-1alpha mutation status.

Assessment of Improved Prediction Beyond Traditional Risk Factors

The moderate predictive performance of cardiovascular disease risk models necessitates more studies that investigate the incremental value of novel biomarkers. In recent years, many new biomarkers have been evaluated for their ability to improve prediction of cardiovascular disease beyond traditional risk factors, including C-reactive protein, coronary artery calcium, and single-nucleotide polymorphisms in the 9p21 region.1 The interest in novel biomarkers is propelled, in part, by emerging discoveries from genomewide association studies of genetic variants associated with risk for many common diseases.2 Nonetheless, family history, an “old” tool in clinical practice—crucial for the diagnosis and management of genetic disorders—has not been adequately explored for its value in risk assessment and prevention of common diseases.3 Positive family history is a strong risk factor for cardiovascular diseases,4,5 reflecting the consequences of genetic and nongenetic risk factors that are shared among relatives. From a practical perspective, family history is a strong determinant of disease that is relatively easy to assess. For this reason, family history is advocated as a useful tool for identifying individuals at increased risk of disease and for tailoring preventive interventions.4,6,7 However, the challenge is to show that this knowledge has clinical utility for improving health.8 Article see p 97 In this issue of Circulation: Cardiovascular Genetics , Scheuner et al9 report the incremental value of adding family history information to the General Cardiovascular Risk Profile to improve identification of individuals with advanced coronary artery calcification. The incremental value of family history in disease prediction is assessed in several questions10: 1. Does family history improve prediction beyond traditional risk factors? 2. Does improved prediction change treatment decisions or health recommendations? 3. Do these changes improve health outcomes or have other benefits? 4. Do the incremental benefits outweigh the extra costs? This evaluation is a stepwise …

Minimal Contribution of Fasting Hyperglycemia to the Incidence of Type 2 Diabetes in Subjects With Normal 2-h Plasma Glucose

OBJECTIVETo assess the relative contribution of increased fasting and postload plasma glucose concentrations to the incidence of type 2 diabetes in subjects with a normal 2-h plasma glucose concentration.RESEARCH DESIGN AND METHODSA total of 3,450 subjects with 2-h plasma glucose concentration <140 mg/dl at baseline were followed up in the San Antonio Heart Study (SAHS) and the Botnia Study for 7–8 years. The incidence of type 2 diabetes at follow-up was related to the fasting, 1-h, and 2-h plasma glucose concentrations.RESULTSIn subjects with 2-h plasma glucose <140 mg/dl, the incidence of type 2 diabetes increased with increasing fasting plasma glucose (FPG) and 1-h and 2-h plasma glucose concentrations. In a multivariate logistic analysis, after adjustment for all diabetes risk factors, the FPG concentration was a strong predictor of type 2 diabetes in both the SAHS and the Botnia Study (P < 0.0001). However, when the 1-h plasma glucose, but not 2-h plasma glucose, concentration was added to the model, FPG concentration was no longer a significant predictor of type 2 diabetes in both studies (NS). When subjects were matched for the level of 1-h plasma glucose concentration, the incidence of type 2 diabetes markedly increased with the increase in 1-h plasma glucose, but the increase in FPG was not associated with a significant increase in the incidence of type 2 diabetes.CONCLUSIONSAn increase in postload glycemia in the normal range is associated with an increase in the incidence of type 2 diabetes. After controlling for 1-h plasma glucose concentration, the increase in FPG concentration is not associated with an increase in the incidence of type 2 diabetes.

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

OBJECTIVETwo independent genome-wide association studies for type 2 diabetes in Japanese subjects have recently identified common variants in the KCNQ1 gene that are strongly associated with type 2 diabetes. Here we studied whether a common variant in KCNQ1 would influence BMI as well as insulin secretion and action and predict future type 2 diabetes in subjects from Sweden and Finland.RESEARCH DESIGN AND METHODSRisk of type 2 diabetes conferred by KCNQ1 rs2237895 was studied in 2,830 type 2 diabetic case subjects and 3,550 control subjects 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 nondiabetic subjects from the Prevalence, Prediction and Prevention of Diabetes (PPP)-Botnia Study and longitudinally in 2,328 nondiabetic subjects from the Botnia Prospective Study (BPS). KCNQ1 expression (n = 18) and glucose-stimulated insulin secretion (n = 19) were measured in human islets from nondiabetic cadaver donors.RESULTSThe C-allele of KCNQ1 rs2237895 was associated with increased risk of type 2 diabetes in both the Malmö Case-Control (odds ratio 1.23 [95% CI 1.12–1.34]; P = 5.6 × 10−6) and the prospective (1.14 [1.06–1.22]; P = 4.8 × 10−4) studies. Furthermore, the C-allele was associated with decreased insulin secretion (corrected insulin response [CIR] P = 0.013; disposition index [DI] P = 0.013) in the PPP-Botnia Study and in the BPS at baseline (CIR P = 3.6 × 10−4; 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 = 2.5 × 10−6).CONCLUSIONSA 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.

Common variants of hepatocyte nuclear factor 1beta are associated with type 2 diabetes in a Chinese population.

OBJECTIVEHepatocyte nuclear factor 1β (HNF1β) is a transcription factor that is critical for pancreatic cell formation and glucose homeostasis. Previous studies have reported that common variants of HNF1β were associated with type 2 diabetes in Caucasians and West Africans. However, analysis in the subjects from the Botnia study and Malmö Preventive Project produced conflicting results, and the role for HNF1β in type 2 diabetes susceptibility remains unclear. We therefore investigated common variants across the HNF1β gene in a Chinese population.RESEARCH DESIGN AND METHODSFifteen tagging single nucleotide polymorphisms (SNPs) were analyzed for association with type 2 diabetes in subjects with type 2 diabetes (n = 1,859) and normal glucose regulation (n = 1,785).RESULTSConsistent with the initial study, we observed evidence that the risk G allele of rs4430796 in intron 2 was significantly associated with type 2 diabetes (odds ratio 1.16 [95% CI 1.05–1.29], P = 0.0035, empirical P = 0.0475). Furthermore, the at-risk G allele was associated with earlier age at diagnosis in the type 2 diabetic subjects (P = 0.0228).CONCLUSIONSThe result of this study provides evidence that variants in the HNF1β region contribute to susceptibility to type 2 diabetes in the Chinese population.

Fasting Versus Postload Plasma Glucose Concentration and the Risk for Future Type 2 Diabetes

OBJECTIVE—The purpose of this study was to assess the efficacy of the postload plasma glucose concentration in predicting future risk of type 2 diabetes, compared with prediction models based on measurement of the fasting plasma glucose (FPG) concentration.RESEARCH DESIGN AND METHODS—A total of 2,442 subjects from the Botnia Study, who were free of type 2 diabetes at baseline, received an oral glucose tolerance test (OGTT) at baseline and after 7–8 years of follow-up. Future risk for type 2 diabetes was assessed with area under the receiver-operating characteristic curve for prediction models based up measurement of the FPG concentration 1) with or without a 1-h plasma glucose concentration during the OGTT and 2) with or without the metabolic syndrome.RESULTS—Prediction models based on measurement of the FPG concentration were weak predictors for the risk of future type 2 diabetes. Addition of a 1-h plasma glucose concentration markedly enhanced prediction of the risk of future type 2 diabetes. A cut point of 155 mg/dl for the 1-h plasma glucose concentration during the OGTT and presence of the metabolic syndrome were used to stratify subjects in each glucose tolerance group into low, intermediate, and high risk for future type 2 diabetes.CONCLUSIONS—The plasma glucose concentration at 1 h during the OGTT is a strong predictor of future risk for type 2 diabetes and adds to the prediction power of models based on measurements made during the fasting state. A plasma glucose cut point of 155 mg/dl plus the Adult Treatment Panel III criteria for the metabolic syndrome can be used to stratify nondiabetic subjects into low-, intermediate-, and high-risk groups.

CCAAT/Enhancer Binding Protein α (C/EBPα) in Adipose Tissue Regulates Genes in Lipid and Glucose Metabolism and a Genetic Variation in C/EBPα Is Associated with Serum Levels of Triglycerides

CCAAT/enhancer binding protein alpha (C/EBPalpha) is a transcription factor involved in adipogenesis and hepatic glucose and lipid metabolism. The aim of the study was to test the hypothesis that adipose tissue C/EBPalpha regulates genes in lipid and glucose metabolism and to test for an association between a polymorphism in C/EBPalpha and metabolic parameters. Adipose tissue C/EBPalpha mRNA expression was analyzed at four time points in obese subjects with (n = 12) and without (n = 12) the metabolic syndrome during caloric restriction (450 kcal/d for 16 wk) using DNA microarray and real-time PCR. Adenoviral overexpression of C/EBPalpha was used to identify genes regulated by C/EBPalpha in 3T3-L1 cells. Association between a genetic variation in C/EBPalpha (rs12691) and metabolic parameters was tested in the Swedish Obese Subjects (SOS) study (n = 528) and replicated in Finnish individuals from the Botnia type 2 diabetes study (n = 4,866). During caloric restriction, adipose tissue C/EBPalpha mRNA levels were reduced in subjects with the metabolic syndrome (P = 0.024) and correlated to metabolic parameters. In 3T3-L1 cells, C/EBPalpha regulated the expression of adiponectin; hexokinase 2; lipoprotein lipase; diacylglycerol O-acyltransferase 1 and 2; ATP-binding cassette, sub-family D, member 2; acyl-coenzyme A synthetase long-chain family member 1; CD36; and hydroxysteroid 11-beta dehydrogenase 1. Furthermore, the expression of the human homologs, except adiponectin, correlated to C/EBPalpha mRNA levels in human adipose tissue. The AA genotype of rs12691 was associated with higher serum triglyceride levels in the SOS study (P = 0.022), and this association was replicated in the Botnia study (P = 0.041). Adipose tissue C/EBPalpha regulates several genes in glucose and lipid metabolism, and a genetic variation in C/EBPalpha is associated with triglycerides in two independent populations.

Common Variants in Maturity-Onset Diabetes of the Young Genes and Future Risk of Type 2 Diabetes

Mutations in the hepatocyte nuclear factor (HNF)-1alpha, HNF-4alpha, glucokinase (GCK), and HNF-1beta genes cause maturity-onset diabetes of the young (MODY), but it is not known whether common variants in these genes predict future type 2 diabetes. We tested 14 previously associated polymorphisms in HNF-1alpha, HNF-4alpha, GCK, and HNF-1beta for association with type 2 diabetes-related traits and future risk of type 2 diabetes in 2,293 individuals from the Botnia study (Finland) and in 15,538 individuals from the Malmö Preventive Project (Sweden) with a total follow-up >360,000 years. The polymorphism rs1169288 in HNF-1alpha strongly predicted future type 2 diabetes (hazard ratio [HR] 1.2, P = 0.0002). Also, SNPs rs4810424 and rs3212198 in HNF-4alpha nominally predicted future type 2 diabetes (HR 1.3 [95% CI 1.0-1.6], P = 0.03; and 1.1 [1.0-1.2], P = 0.04). The rs2144908 polymorphism in HNF-4alpha was associated with elevated rate of hepatic glucose production during a hyperinsulinemic-euglycemic clamp (P = 0.03) but not with deterioration of insulin secretion over time. The SNP rs1799884 in the GCK promoter was associated with elevated fasting plasma glucose (fPG) concentrations that remained unchanged during the follow-up period (P = 0.4; SE 0.004 [-0.003-0.007]) but did not predict future type 2 diabetes (HR 0.9 [0.8-1.0], P = 0.1). Polymorphisms in HNF-1beta (transcription factor 2 [TCF2]) did not significantly influence insulin or glucose values nor did they predict future type 2 diabetes. In conclusion, genetic variation in both HNF-1alpha and HNF-4alpha predict future type 2 diabetes, whereas variation in the GCK promoter results in a sustained but subtle elevation of fPG that is not sufficient to increase risk for future type 2 diabetes.

Association of Microsatellite Polymorphisms of the Human 14q13.2 Region with Type 2 Diabetes Mellitus in Latvian and Finnish Populations

A polymorphic microsatellite in intron 6 of the human proteasome core particle PSMA6 gene (HSMS006), and four other microsatellites localized upstream on human chromosome 14q13.2 (HSMS801, HSMS702, HSMS701, HSMS602), were genotyped in 104 type 2 diabetic patients and 129 age-matched control subjects from Latvia and replicated in 91 type 2 diabetic patients and 88 age-matched healthy control subjects from the Botnia Study in Finland. In type 2 diabetic patients from both populations the HSMS006 (TG)22 allele was two times more frequent compared to the control group. In the Latvian population the (CAA)8 allele of the HSMS602 marker was less frequent in the diabetic group, as was the (AC)24 allele of microsatellite HSMS801. Allele frequencies of the HSMS701 and 702 repeats were similar in healthy controls and type 2 diabetic patients. In conclusion, our data suggest that variants in the PSMA6 gene on chromosome 14q13.2 are associated with type 2 diabetes.