A multigenerational study on phenotypic consequences of the most common causal variant of HNF1A-MODY.

AIMS/HYPOTHESIS: Systematic studies on the phenotypic consequences of variants causal of HNF1A-MODY are rare. Our aim was to assess the phenotype of carriers of a single HNF1A variant and genetic and clinical factors affecting the clinical spectrum. METHODS: We conducted a family-based multigenerational study by comparing heterozygous carriers of the HNF1A p.(Gly292fs) variant with the non-carrier relatives irrespective of diabetes status. During more than two decades, 145 carriers and 131 non-carriers from 12 families participated in the study, and 208 underwent an OGTT at least once. We assessed the polygenic risk score for type 2 diabetes, age at onset of diabetes and measures of body composition, as well as plasma glucose, serum insulin, proinsulin, C-peptide, glucagon and NEFA response during the OGTT. RESULTS: Half of the carriers remained free of diabetes at 23 years, one-third at 33 years and 13% even at 50 years. The median age at diagnosis was 21 years (IQR 17-35). We could not identify clinical factors affecting the age at conversion; sex, BMI, insulin sensitivity or parental carrier status had no significant effect. However, for 1 SD unit increase of a polygenic risk score for type 2 diabetes, the predicted age at diagnosis decreased by 3.2 years. During the OGTT, the carriers had higher levels of plasma glucose and lower levels of serum insulin and C-peptide than the non-carriers. The carriers were also leaner than the non-carriers (by 5.0 kg, p=0.012, and by 2.1 kg/m2 units of BMI, p=2.2 × 10-4, using the first adult measurements) and, possibly as a result of insulin deficiency, demonstrated higher lipolytic activity (with medians of NEFA at fasting 621 vs 441 µmol/l, p=0.0039; at 120 min during an OGTT 117 vs 64 µmol/l, p=3.1 × 10-5). CONCLUSIONS/INTERPRETATION: The most common causal variant of HNF1A-MODY, p.(Gly292fs), presents not only with hyperglycaemia and insulin deficiency, but also with increased lipolysis and markedly lower adult BMI. Serum insulin was more discriminative than C-peptide between carriers and non-carriers. A considerable proportion of carriers develop diabetes after young adulthood. Even among individuals with a monogenic form of diabetes, polygenic risk of diabetes modifies the age at onset of diabetes.

Relationship between insulin sensitivity and gene expression in human skeletal muscle.

BACKGROUND: Insulin resistance (IR) in skeletal muscle is a key feature of the pre-diabetic state, hypertension, dyslipidemia, cardiovascular diseases and also predicts type 2 diabetes. However, the underlying molecular mechanisms are still poorly understood. METHODS: To explore these mechanisms, we related global skeletal muscle gene expression profiling of 38 non-diabetic men to a surrogate measure of insulin sensitivity, i.e. homeostatic model assessment of insulin resistance (HOMA-IR). RESULTS: We identified 70 genes positively and 110 genes inversely correlated with insulin sensitivity in human skeletal muscle, identifying autophagy-related genes as positively correlated with insulin sensitivity. Replication in an independent study of 9 non-diabetic men resulted in 10 overlapping genes that strongly correlated with insulin sensitivity, including SIRT2, involved in lipid metabolism, and FBXW5 that regulates mammalian target-of-rapamycin (mTOR) and autophagy. The expressions of SIRT2 and FBXW5 were also positively correlated with the expression of key genes promoting the phenotype of an insulin sensitive myocyte e.g. PPARGC1A. CONCLUSIONS: The muscle expression of 180 genes were correlated with insulin sensitivity. These data suggest that activation of genes involved in lipid metabolism, e.g. SIRT2, and genes regulating autophagy and mTOR signaling, e.g. FBXW5, are associated with increased insulin sensitivity in human skeletal muscle, reflecting a highly flexible nutrient sensing.

Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array.

BACKGROUND: Epigenetic clocks have been recognized for their precise prediction of chronological age, age-related diseases, and all-cause mortality. Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC). Thus, it remains unclear to what extent EPIC contributes to increased precision and accuracy in the prediction of chronological age. RESULTS: We developed three blood-based epigenetic clocks for human adults using EPIC-based DNA methylation (DNAm) data from the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Gene Expression Omnibus (GEO) public repository: 1) an Adult Blood-based EPIC Clock (ABEC) trained on DNAm data from MoBa (n = 1592, age-span: 19 to 59 years), 2) an extended ABEC (eABEC) trained on DNAm data from MoBa and GEO (n = 2227, age-span: 18 to 88 years), and 3) a common ABEC (cABEC) trained on the same training set as eABEC but restricted to CpGs common to 450 K and EPIC. Our clocks showed high precision (Pearson correlation between chronological and epigenetic age (r) > 0.94) in independent cohorts, including GSE111165 (n = 15), GSE115278 (n = 108), GSE132203 (n = 795), and the Epigenetics in Pregnancy (EPIPREG) study of the STORK Groruddalen Cohort (n = 470). This high precision is unlikely due to the use of EPIC, but rather due to the large sample size of the training set. CONCLUSIONS: Our ABECs predicted adults' chronological age precisely in independent cohorts. As EPIC is now the dominant platform for measuring DNAm, these clocks will be useful in further predictions of chronological age, age-related diseases, and mortality.

Interaction between the obesity-risk gene FTO and the dopamine D2 receptor gene ANKK1/TaqIA on insulin sensitivity.

AIMS/HYPOTHESIS: Variations in FTO are the strongest common genetic determinants of adiposity, and may partly act by influencing dopaminergic signalling in the brain leading to altered reward processing that promotes increased food intake. Therefore, we investigated the impact of such an interaction on body composition, and peripheral and brain insulin sensitivity. METHODS: Participants from the Tübingen Family study (n = 2245) and the Malmö Diet and Cancer study (n = 2921) were genotyped for FTO SNP rs8050136 and ANKK1 SNP rs1800497. Insulin sensitivity in the caudate nucleus, an important reward area in the brain, was assessed by fMRI in 45 participants combined with intranasal insulin administration. RESULTS: We found evidence of an interaction between variations in FTO and an ANKK1 polymorphism that associates with dopamine (D2) receptor density. In cases of reduced D2 receptor availability, as indicated by the ANKK1 polymorphism, FTO variation was associated with increased body fat and waist circumference and reduced peripheral insulin sensitivity. Similarly, altered central insulin sensitivity was observed in the caudate nucleus in individuals with the FTO obesity-risk allele and diminished D2 receptors. CONCLUSIONS/INTERPRETATION: The effects of variations in FTO are dependent on dopamine D2 receptor density (determined by the ANKK1 polymorphism). Carriers of both risk alleles might, therefore, be at increased risk of obesity and diabetes.

Gene-lifestyle interaction and type 2 diabetes: the EPIC interact case-cohort study.

BACKGROUND: Understanding of the genetic basis of type 2 diabetes (T2D) has progressed rapidly, but the interactions between common genetic variants and lifestyle risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention. METHODS AND FINDINGS: The InterAct study includes 12,403 incident T2D cases and a representative sub-cohort of 16,154 individuals from a cohort of 340,234 European participants with 3.99 million person-years of follow-up. We studied the combined effects of an additive genetic T2D risk score and modifiable and non-modifiable risk factors using Prentice-weighted Cox regression and random effects meta-analysis methods. The effect of the genetic score was significantly greater in younger individuals (p for interaction  = 1.20×10-4). Relative genetic risk (per standard deviation [4.4 risk alleles]) was also larger in participants who were leaner, both in terms of body mass index (p for interaction  = 1.50×10-3) and waist circumference (p for interaction  = 7.49×10-9). Examination of absolute risks by strata showed the importance of obesity for T2D risk. The 10-y cumulative incidence of T2D rose from 0.25% to 0.89% across extreme quartiles of the genetic score in normal weight individuals, compared to 4.22% to 7.99% in obese individuals. We detected no significant interactions between the genetic score and sex, diabetes family history, physical activity, or dietary habits assessed by a Mediterranean diet score. CONCLUSIONS: The relative effect of a T2D genetic risk score is greater in younger and leaner participants. However, this sub-group is at low absolute risk and would not be a logical target for preventive interventions. The high absolute risk associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.

Demonstrating stratification in a European American population.

Population stratification occurs in case-control association studies when allele frequencies differ between cases and controls because of ancestry. Stratification may lead to false positive associations, although this issue remains controversial. Empirical studies have found little evidence of stratification in European-derived populations, but potentially significant levels of stratification could not be ruled out. We studied a European American panel discordant for height, a heritable trait that varies widely across Europe. Genotyping 178 SNPs and applying standard analytical methods yielded no evidence of stratification. But a SNP in the gene LCT that varies widely in frequency across Europe was strongly associated with height (P < 10(-6)). This apparent association was largely or completely due to stratification; rematching individuals on the basis of European ancestry greatly reduced the apparent association, and no association was observed in Polish or Scandinavian individuals. The failure of standard methods to detect this stratification indicates that new methods may be required.

PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes.

DNA microarrays can be used to identify gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1alpha and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.

Cohort profile: Epigenetics in Pregnancy (EPIPREG) - population-based sample of European and South Asian pregnant women with epigenome-wide DNA methylation (850k) in peripheral blood leukocytes.

Pregnancy is a valuable model to study the association between DNA methylation and several cardiometabolic traits, due to its direct potential to influence mother's and child's health. Epigenetics in Pregnancy (EPIPREG) is a population-based sample with the aim to study associations between DNA-methylation in pregnancy and cardiometabolic traits in South Asian and European pregnant women and their offspring. This cohort profile paper aims to present our sample with genetic and epigenetic data and invite researchers with similar cohorts to collaborative projects, such as replication of ours or their results and meta-analysis. In EPIPREG we have quantified epigenome-wide DNA methylation in maternal peripheral blood leukocytes in gestational week 28±1 in Europeans (n = 312) and South Asians (n = 168) that participated in the population-based cohort STORK Groruddalen, in Norway. DNA methylation was measured with Infinium MethylationEPIC BeadChip (850k sites), with technical validation of four CpG sites using bisulphite pyrosequencing in a subset (n = 30). The sample is well characterized with few missing data on e.g. genotype, universal screening for gestational diabetes, objectively measured physical activity, bioelectrical impedance, anthropometrics, biochemical measurements, and a biobank with maternal serum and plasma, urine, placenta tissue. In the offspring, we have repeated ultrasounds during pregnancy, cord blood, and anthropometrics up to 4 years of age. We have quantified DNA methylation in peripheral blood leukocytes in nearly all eligible women from the STORK Groruddalen study, to minimize the risk of selection bias. Genetic principal components distinctly separated Europeans and South Asian women, which fully corresponded with the self-reported ethnicity. Technical validation of 4 CpG sites from the methylation bead chip showed good agreement with bisulfite pyrosequencing. We plan to study associations between DNA methylation and cardiometabolic traits and outcomes.

Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study.

Type 2 diabetes (T2D) is a global public health challenge. Whilst the advent of genome-wide association studies has identified >400 genetic variants associated with T2D, our understanding of its biological mechanisms and translational insights is still limited. The EPIC-InterAct project, centred in 8 countries in the European Prospective Investigations into Cancer and Nutrition study, is one of the largest prospective studies of T2D. Established as a nested case-cohort study to investigate the interplay between genetic and lifestyle behavioural factors on the risk of T2D, a total of 12,403 individuals were identified as incident T2D cases, and a representative sub-cohort of 16,154 individuals was selected from a larger cohort of 340,234 participants with a follow-up time of 3.99 million person-years. We describe the results from a genome-wide association analysis between more than 8.9 million SNPs and T2D risk among 22,326 individuals (9,978 cases and 12,348 non-cases) from the EPIC-InterAct study. The summary statistics to be shared provide a valuable resource to facilitate further investigations into the genetics of T2D.

HAPT2D: high accuracy of prediction of T2D with a model combining basic and advanced data depending on availability.

OBJECTIVE: Type 2 diabetes arises from the interaction of physiological and lifestyle risk factors. Our objective was to develop a model for predicting the risk of T2D, which could use various amounts of background information. RESEARCH DESIGN AND METHODS: We trained a survival analysis model on 8483 people from three large Finnish and Spanish data sets, to predict the time until incident T2D. All studies included anthropometric data, fasting laboratory values, an oral glucose tolerance test (OGTT) and information on co-morbidities and lifestyle habits. The variables were grouped into three sets reflecting different degrees of information availability. Scenario 1 included background and anthropometric information; Scenario 2 added routine laboratory tests; Scenario 3 also added results from an OGTT. Predictive performance of these models was compared with FINDRISC and Framingham risk scores. RESULTS: The three models predicted T2D risk with an average integrated area under the ROC curve equal to 0.83, 0.87 and 0.90, respectively, compared with 0.80 and 0.75 obtained using the FINDRISC and Framingham risk scores. The results were validated on two independent cohorts. Glucose values and particularly 2-h glucose during OGTT (2h-PG) had highest predictive value. Smoking, marital and professional status, waist circumference, blood pressure, age and gender were also predictive. CONCLUSIONS: Our models provide an estimation of patient's risk over time and outweigh FINDRISC and Framingham traditional scores for prediction of T2D risk. Of note, the models developed in Scenarios 1 and 2, only exploited variables easily available at general patient visits.

A variant within the FTO confers susceptibility to diabetic nephropathy in Japanese patients with type 2 diabetes.

To explore novel genetic loci for diabetic nephropathy, we performed genome-wide association studies (GWAS) for diabetic nephropathy in Japanese patients with type 2 diabetes. We analyzed the association of 5,768,242 single nucleotide polymorphisms (SNPs) in Japanese patients with type 2 diabetes, 2,380 nephropathy cases and 5,234 controls. We further performed GWAS for diabetic nephropathy using independent Japanese patients with type 2 diabetes, 429 cases and 358 controls and the results of these two GWAS were combined with an inverse variance meta-analysis (stage-1), followed by a de novo genotyping for the candidate SNP loci (p < 1.0 × 10(-4)) in an independent case-control study (Stage-2; 1,213 cases and 1,298 controls). After integrating stage-1 and stage-2 data, we identified one SNP locus, significantly associated with diabetic nephropathy; rs56094641 in FTO, P = 7.74 × 10(-10). We further examined the association of rs56094641 with diabetic nephropathy in independent Japanese patients with type 2 diabetes (902 cases and 1,221 controls), and found that the association of this locus with diabetic nephropathy remained significant after integrating all association data (P = 7.62 × 10(-10)). We have identified FTO locus as a novel locus for conferring susceptibility to diabetic nephropathy in Japanese patients with type 2 diabetes.

Common single nucleotide polymorphisms in TCF7L2 are reproducibly associated with type 2 diabetes and reduce the insulin response to glucose in nondiabetic individuals.

Recently, common noncoding variants in the TCF7L2 gene were strongly associated with increased risk of type 2 diabetes in samples from Iceland, Denmark, and the U.S. We genotyped 13 single nucleotide polymorphisms (SNPs) across TCF7L2 in 8,310 individuals in family-based and case-control designs from Scandinavia, Poland, and the U.S. We convincingly confirmed the previous association of TCF7L2 SNPs with the risk of type 2 diabetes (rs7903146T odds ratio 1.40 [95% CI 1.30-1.50], P = 6.74 x 10(-20)). In nondiabetic individuals, the risk genotypes were associated with a substantial reduction in the insulinogenic index derived from an oral glucose tolerance test (risk allele homozygotes have half the insulin response to glucose of noncarriers, P = 0.003) but not with increased insulin resistance. These results suggest that TCF7L2 variants may act through insulin secretion to increase the risk of type 2 diabetes.

TXNIP regulates peripheral glucose metabolism in humans.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is characterized by defects in insulin secretion and action. Impaired glucose uptake in skeletal muscle is believed to be one of the earliest features in the natural history of T2DM, although underlying mechanisms remain obscure. METHODS AND FINDINGS: We combined human insulin/glucose clamp physiological studies with genome-wide expression profiling to identify thioredoxin interacting protein (TXNIP) as a gene whose expression is powerfully suppressed by insulin yet stimulated by glucose. In healthy individuals, its expression was inversely correlated to total body measures of glucose uptake. Forced expression of TXNIP in cultured adipocytes significantly reduced glucose uptake, while silencing with RNA interference in adipocytes and in skeletal muscle enhanced glucose uptake, confirming that the gene product is also a regulator of glucose uptake. TXNIP expression is consistently elevated in the muscle of prediabetics and diabetics, although in a panel of 4,450 Scandinavian individuals, we found no evidence for association between common genetic variation in the TXNIP gene and T2DM. CONCLUSIONS: TXNIP regulates both insulin-dependent and insulin-independent pathways of glucose uptake in human skeletal muscle. Combined with recent studies that have implicated TXNIP in pancreatic beta-cell glucose toxicity, our data suggest that TXNIP might play a key role in defective glucose homeostasis preceding overt T2DM.

Improved prandial glucose control with lower risk of hypoglycemia with nateglinide than with glibenclamide in patients with maturity-onset diabetes of the young type 3.

OBJECTIVE: To study the effect of the short-acting insulin secretagogue nateglinide in patients with maturity-onset diabetes of the young type 3 (MODY3), which is characterized by a defective insulin response to glucose and hypersensitivity to sulfonylureas. RESEARCH DESIGN AND METHODS: We compared the acute effect of nateglinide, glibenclamide, and placebo on prandial plasma glucose and serum insulin, C-peptide, and glucagon excursions in 15 patients with MODY3. After an overnight fast, they received on three randomized occasions placebo, 1.25 mg glibenclamide, or 30 mg nateglinide before a standard 450-kcal test meal and light bicycle exercise for 30 min starting 140 min after the ingestion of the first test drug. RESULTS: Insulin peaked earlier after nateglinide than after glibenclamide or placebo (median [interquartile range] time 70 [50] vs. 110 [20] vs. 110 [30] min, P = 0.0002 and P = 0.0025, respectively). Consequently, compared with glibenclamide and placebo, the peak plasma glucose (P = 0.031 and P < 0.0001) and incremental glucose areas under curve during the first 140 min of the test (P = 0.041 and P < 0.0001) remained lower after nateglinide. The improved prandial glucose control with nateglinide was achieved with a lower peak insulin concentration than after glibenclamide (47.0 [26.0] vs. 80.4 [71.7] mU/l; P = 0.023). Exercise did not induce hypoglycemia after nateglinide or placebo, but after glibenclamide six patients experienced symptomatic hypoglycemia and three had to interrupt the test. CONCLUSIONS: A low dose of nateglinide prevents the acute postprandial rise in glucose more efficiently than glibenclamide and with less stimulation of peak insulin concentrations and less hypoglycemic symptoms.

Automated pathway and reaction prediction facilitates in silico identification of unknown metabolites in human cohort studies.

Identification of metabolites in non-targeted metabolomics continues to be a bottleneck in metabolomics studies in large human cohorts. Unidentified metabolites frequently emerge in the results of association studies linking metabolite levels to, for example, clinical phenotypes. For further analyses these unknown metabolites must be identified. Current approaches utilize chemical information, such as spectral details and fragmentation characteristics to determine components of unknown metabolites. Here, we propose a systems biology model exploiting the internal correlation structure of metabolite levels in combination with existing biochemical and genetic information to characterize properties of unknown molecules. Levels of 758 metabolites (439 known, 319 unknown) in human blood samples of 2279 subjects were measured using a non-targeted metabolomics platform (LC-MS and GC-MS). We reconstructed the structure of biochemical pathways that are imprinted in these metabolomics data by building an empirical network model based on 1040 significant partial correlations between metabolites. We further added associations of these metabolites to 134 genes from genome-wide association studies as well as reactions and functional relations to genes from the public database Recon 2 to the network model. From the local neighborhood in the network, we were able to predict the pathway annotation of 180 unknown metabolites. Furthermore, we classified 100 pairs of known and unknown and 45 pairs of unknown metabolites to 21 types of reactions based on their mass differences. As a proof of concept, we then looked further into the special case of predicted dehydrogenation reactions leading us to the selection of 39 candidate molecules for 5 unknown metabolites. Finally, we could verify 2 of those candidates by applying LC-MS analyses of commercially available candidate substances. The formerly unknown metabolites X-13891 and X-13069 were shown to be 2-dodecendioic acid and 9-tetradecenoic acid, respectively. Our data-driven approach based on measured metabolite levels and genetic associations as well as information from public resources can be used alone or together with methods utilizing spectral patterns as a complementary, automated and powerful method to characterize unknown metabolites.

Contribution of known and unknown susceptibility genes to early-onset diabetes in scandinavia: evidence for heterogeneity.

In an attempt to identify novel susceptibility genes predisposing to early-onset diabetes (EOD), we performed a genome-wide scan using 433 markers in 222 individuals (119 with diabetes) from 29 Scandinavian families with > or =2 members with onset of diabetes < or =45 years. The highest nonparametric linkage (NPL) score, 2.7 (P < 0.01), was observed on chromosome 1p (D1S473/D1S438). Six other regions on chromosomes 3p, 7q, 11q, 18q, 20q, and 21q showed a nominal P value <0.05. Of the EOD subjects in these 29 families, 20% were GAD antibody positive and 68% displayed type 1 diabetes HLA risk alleles (DQB*02 or 0302). Mutations in maturity-onset diabetes of the young (MODY) 1-5 genes and the A3243G mitochondrial DNA mutation were detected by single-strand conformation polymorphism and direct sequencing. To increase homogeneity, we analyzed a subsample of five families with autosomal dominant inheritance of EOD (greater than or equal to two members with age at diagnosis < or =35 years). The highest NPL scores were found on chromosome 1p (D1S438-D1S1665; NPL 3.0; P < 0.01) and 16q (D16S419; NPL 2.9; P < 0.01). After exclusion of three families with MODY1, MODY3, and mitochondrial mutations, the highest NPL scores were observed on chromosomes 1p (D1S438; NPL 2.6; P < 0.01), 3p (D3S1620; NPL 2.2; P < 0.03), 5q (D5S1465; NPL 2.1; P < 0.03), 7q (D7S820; NPL 2.0; P < 0.03), 18q (D18S535; NPL 1.9; P < 0.04), 20q (D20S195; NPL 2.5; P < 0.02), and 21q (D21S1446; NPL 2.2; P < 0.03). We conclude that considerable heterogeneity exists in Scandinavian subjects with EOD; 24% had MODY or maternally inherited diabetes and deafness, and approximately 60% were GAD antibody positive or had type 1 diabetes-associated HLA genotypes. Our data also point at putative chromosomal regions, which could harbor novel genes that contribute to EOD.

5' flanking variants of resistin are associated with obesity.

Diabetes and obesity have long been known to be related. The recently characterized adipocyte hormone resistin (also called FIZZ3/ADSF) has been implicated as a molecular link between impaired glucose tolerance (IGT) and obesity in mice. A search for sequence variants at the human resistin locus identified nine single-nucleotide polymorphisms (SNPs) but no coding variants. An investigation into the association of these SNPs with diabetes and obesity revealed two 5' flanking variants (g.-537 and g.-420), in strong linkage disequilibrium, that are associated with BMI. In nondiabetic individuals from the Quebec City area and the Saguenay-Lac-St-Jean region of Quebec, the g.-537 mutation (allelic frequency = 0.04) was significantly associated with an increase in BMI (P = 0.03 and P = 0.01, respectively). When the data from these two populations were combined and adjusted for age and sex, both the g.-537 (odds ratio [OR] 2.72, 95% CI 1.28-5.81) and the g.-420 variants (1.58, 1.06-2.35) were associated with an increased risk for a BMI > or =30 kg/m(2). In contrast, in case/control and family-based study populations from Scandinavia, we saw no effect on BMI with either of these promoter variants. No association was seen with diabetes in any of the population samples.

A genome-wide scan in families with maturity-onset diabetes of the young: evidence for further genetic heterogeneity.

Maturity-onset diabetes of the young (MODY) is a heterogeneous single gene disorder characterized by non-insulin-dependent diabetes, an early onset and autosomal dominant inheritance. Mutations in six genes have been shown to cause MODY. Approximately 15-20% of families fitting MODY criteria do not have mutations in any of the known genes. These families provide a rich resource for the identification of new MODY genes. This will potentially enable further dissection of clinical heterogeneity and bring new insights into mechanisms of beta-cell dysfunction. To facilitate the identification of novel MODY loci, we combined the results from three genome-wide scans on a total of 23 families fitting MODY criteria. We used both a strict parametric model of inheritance with heterogeneity and a model-free analysis. We did not identify any single novel locus but provided putative evidence for linkage to chromosomes 6 (nonparametric linkage [NPL]score 2.12 at 71 cM) and 10 (NPL score 1.88 at 169-175 cM), and to chromosomes 3 (heterogeneity LOD [HLOD] score 1.27 at 124 cM) and 5 (HLOD score 1.22 at 175 cM) in 14 more strictly defined families. Our results provide evidence for further heterogeneity in MODY.

Screening for MODY mutations, GAD antibodies, and type 1 diabetes--associated HLA genotypes in women with gestational diabetes mellitus.

OBJECTIVE: To investigate whether genetic susceptibility to type 1 diabetes or maturity-onset diabetes of the young (MODY) increases susceptibility to gestational diabetes mellitus (GDM). RESEARCH DESIGN AND METHODS: We studied mutations in MODY1-4 genes, the presence of GAD antibodies, and HLA DQB1 risk genotypes in 66 Swedish women with GDM and a family history of diabetes. An oral glucose tolerance test was repeated in 46 women at 1 year postpartum. RESULTS: There was no increase in type 1 diabetes-associated HLA-DQB1 alleles or GAD antibodies when compared with a group of type 2 diabetic patients (n = 82) or healthy control subjects (n = 86). Mutations in known MODY genes were identified in 3 of the 66 subjects (1 MODY2, 1 MODY3, and 1 MODY4). Of the 46 GDM subjects, 2 had diabetes (4%) and 17 had impaired glucose tolerance (IGT) (37%) at 1 year postpartum. Of the two subjects who developed manifest diabetes, one carried a MODY3 mutation (A203H in the hepatocyte nuclear factor-1alpha gene). There was no increase in high-risk HLA alleles or GAD antibodies in the women who had manifest diabetes or IGT at 1 year postpartum. CONCLUSIONS: MODY mutations but not autoimmunity contribute to GDM in Swedish women with a family history of diabetes and increase the risk of subsequent diabetes.