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Aims/hypothesis Maturity-onset diabetes of the young is frequently misdiagnosed as type 1 or type 2 diabetes. A correct diagnosis of MODY is important for determining treatment, but can only be confirmed by molecular genetic testing. We aimed to compare the regional distribution of confirmed MODY cases in the UK and to estimate the minimum prevalence. Methods UK referrals for genetic testing in 2,072 probands and 1,280 relatives between 1996 and 2009 were examined by region, country and test result. Referral rate and prevalence were calculated using UK Census 2001 figures. Results MODY was confirmed in 1,177 (35%) patients, with HNF1A (52%) and GCK mutations (32%) being most frequent in probands confirmed with MODY. There was considerable regional variation in proband referral rates (from <20 per million in Wales and Northern Ireland to >50 per million for South West England and Scotland) and patients diagnosed with MODY (5.3 per million in Northern Ireland, 48.9 per million in South West England). Referral rates and confirmed cases were highly correlated (r = 0.96, p < 0.0001). The minimum prevalence of MODY was estimated to be 108 cases per million. Conclusions/interpretation Assuming this minimal prevalence throughout the UK then >80% of MODY is not diagnosed by molecular testing. The marked regional variation in the prevalence of confirmed MODY directly results from differences in referral rates. This could reflect variation in awareness of MODY or unequal access to genetic testing. Increased referral for diagnostic testing is required if the majority of MODY patients are to have the genetic diagnosis necessary for optimal treatment.

Aims/hypothesis Diagnosing MODY is difficult. To date, selection for molecular genetic testing for MODY has used discrete cut-offs of limited clinical characteristics with varying sensitivity and specificity. We aimed to use multiple, weighted, clinical criteria to determine an individual’s probability of having MODY, as a crucial tool for rational genetic testing. Methods We developed prediction models using logistic regression on data from 1,191 patients with MODY ( n  = 594), type 1 diabetes ( n  = 278) and type 2 diabetes ( n  = 319). Model performance was assessed by receiver operating characteristic (ROC) curves, cross-validation and validation in a further 350 patients. Results The models defined an overall probability of MODY using a weighted combination of the most discriminative characteristics. For MODY, compared with type 1 diabetes, these were: lower HbA 1c , parent with diabetes, female sex and older age at diagnosis. MODY was discriminated from type 2 diabetes by: lower BMI, younger age at diagnosis, female sex, lower HbA 1c , parent with diabetes, and not being treated with oral hypoglycaemic agents or insulin. Both models showed excellent discrimination (c-statistic = 0.95 and 0.98, respectively), low rates of cross-validated misclassification (9.2% and 5.3%), and good performance on the external test dataset (c-statistic = 0.95 and 0.94). Using the optimal cut-offs, the probability models improved the sensitivity (91% vs 72%) and specificity (94% vs 91%) for identifying MODY compared with standard criteria of diagnosis <25 years and an affected parent. The models are now available online at www.diabetesgenes.org . Conclusions/interpretation We have developed clinical prediction models that calculate an individual’s probability of having MODY. This allows an improved and more rational approach to determine who should have molecular genetic testing.

AbstractObjectiveTo determine whether the sensitivity and specificity of SNP chips are adequate for detecting rare pathogenic variants in a clinically unselected population.DesignRetrospective, population based diagnostic evaluation.Participants49 908 people recruited to the UK Biobank with SNP chip and next generation sequencing data, and an additional 21 people who purchased consumer genetic tests and shared their data online via the Personal Genome Project.Main outcome measuresGenotyping (that is, identification of the correct DNA base at a specific genomic location) using SNP chips versus sequencing, with results split by frequency of that genotype in the population. Rare pathogenic variants in the BRCA1 and BRCA2 genes were selected as an exemplar for detailed analysis of clinically actionable variants in the UK Biobank, and BRCA related cancers (breast, ovarian, prostate, and pancreatic) were assessed in participants through use of cancer registry data.ResultsOverall, genotyping using SNP chips performed well compared with sequencing; sensitivity, specificity, positive predictive value, and negative predictive value were all above 99% for 108 574 common variants directly genotyped on the SNP chips and sequenced in the UK Biobank. However, the likelihood of a true positive result decreased dramatically with decreasing variant frequency; for variants that are very rare in the population, with a frequency below 0.001% in UK Biobank, the positive predictive value was very low and only 16% of 4757 heterozygous genotypes from the SNP chips were confirmed with sequencing data. Results were similar for SNP chip data from the Personal Genome Project, and 20/21 individuals analysed had at least one false positive rare pathogenic variant that had been incorrectly genotyped. For pathogenic variants in the BRCA1 and BRCA2 genes, which are individually very rare, the overall performance metrics for the SNP chips versus sequencing in the UK Biobank were: sensitivity 34.6%, specificity 98.3%, positive predictive value 4.2%, and negative predictive value 99.9%. Rates of BRCA related cancers in UK Biobank participants with a positive SNP chip result were similar to those for age matched controls (odds ratio 1.31, 95% confidence interval 0.99 to 1.71) because the vast majority of variants were false positives, whereas sequence positive participants had a significantly increased risk (odds ratio 4.05, 2.72 to 6.03).ConclusionsSNP chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation.

Aims/hypothesis 6q24 transient neonatal diabetes mellitus (TNDM) is a rare form of diabetes presenting in the neonatal period that remits during infancy but, in a proportion of cases, recurs in later life. We aim to describe the clinical presentation of 6q24 TNDM in the largest worldwide cohort of patients with defined molecular aetiology, in particular seeking differences in presentation or clinical history between aetiological groups. Methods One-hundred and sixty-three patients with positively diagnosed 6q24 TNDM were ascertained from Europe, the Americas, Asia and Australia. Clinical data from referrals were recorded and stratified by the molecular aetiology of patients. Results 6q24 TNDM patients presented at a modal age of one day, with growth retardation and hyperglycaemia, irrespective of molecular aetiology. There was a positive correlation between age of presentation and gestational age, and a negative correlation between adjusted birthweight SD and age of remission. Congenital anomalies were significantly more frequent in patients with paternal uniparental disomy of chromosome 6 or hypomethylation of multiple imprinted loci defects than in those with 6q24 duplication or isolated hypomethylation defects. Patients with hypomethylation had an excess representation of assisted conception at 15%. Conclusions/interpretation This, the largest case series of 6q24 TNDM published, refines and extends the clinical phenotype of the disorder and confirms its clinical divergence from other monogenic TNDM in addition to identifying previously unreported clinical differences between 6q24 subgroups.

Aims/hypothesis The ABCC8 gene encodes the sulfonylurea receptor 1 (SUR1) subunit of the pancreatic beta cell ATP-sensitive potassium (K ATP ) channel. Inactivating mutations cause congenital hyperinsulinism (CHI) and activating mutations cause transient neonatal diabetes (TNDM) or permanent neonatal diabetes (PNDM) that can usually be treated with sulfonylureas. Sulfonylurea sensitivity is also a feature of HNF1A and HNF4A MODY, but patients referred for genetic testing with clinical features of these types of diabetes do not always have mutations in the HNF1A/4A genes. Our aim was to establish whether mutations in the ABCC8 gene cause MODY that is responsive to sulfonylurea therapy. Methods We sequenced the ABCC8 gene in 85 patients with a BMI <30 kg/m 2 , no family history of neonatal diabetes and who were deemed sensitive to sulfonylureas by the referring clinician or were sulfonylurea-treated. All had tested negative for mutations in the HNF1A and HNF4A genes. Results ABCC8 mutations were found in seven of the 85 (8%) probands. Four patients were heterozygous for previously reported mutations and four novel mutations, E100K, G214R, Q485R and N1245D, were identified. Only four probands fulfilled MODY criteria, with two diagnosed after 25 years and one patient, who had no family history of diabetes, as a result of a proven de novo mutation. Conclusions/interpretation ABCC8 mutations can cause MODY in patients whose clinical features are similar to those with HNF1A/4A MODY. Therefore, sequencing of ABCC8 in addition to the known MODY genes should be considered if such features are present, to facilitate optimal clinical management of these patients.

Aims/hypothesis Mutations in the GCK and HNF1A genes are the most common cause of the monogenic forms of diabetes known as ‘maturity-onset diabetes of the young’. GCK encodes the glucokinase enzyme, which acts as the pancreatic glucose sensor, and mutations result in stable, mild fasting hyperglycaemia. A progressive insulin secretory defect is seen in patients with mutations in the HNF1A and HNF4A genes encoding the transcription factors hepatocyte nuclear factor-1 alpha and -4 alpha. A molecular genetic diagnosis often changes management, since patients with GCK mutations rarely require pharmacological treatment and HNF1A/4A mutation carriers are sensitive to sulfonylureas. These monogenic forms of diabetes are often misdiagnosed as type 1 or 2 diabetes. Best practice guidelines for genetic testing were developed to guide testing and reporting of results. Methods A workshop was held to discuss clinical criteria for testing and the interpretation of molecular genetic test results. The participants included 22 clinicians and scientists from 13 countries. Draft best practice guidelines were formulated and edited using an online tool ( http://www.coventi.com ). Results An agreed set of clinical criteria were defined for the testing of babies, children and adults for GCK , HNF1A and HNF4A mutations. Reporting scenarios were discussed and consensus statements produced. Conclusions/interpretation Best practice guidelines have been established for monogenic forms of diabetes caused by mutations in the GCK , HNF1A and HNF4A genes. The guidelines include both diagnostic and predictive genetic tests and interpretation of the results.

Aims The gene SLC2A2 encodes GLUT2, which is found predominantly in pancreas, liver, kidney and intestine. In mice, GLUT2 is the major glucose transporter into pancreatic beta cells, and biallelic Slc2a2 inactivation causes lethal neonatal diabetes. The role of GLUT2 in human beta cells is controversial, and biallelic SLC2A2 mutations cause Fanconi–Bickel syndrome (FBS), with diabetes rarely reported. We investigated the potential role of GLUT2 in the neonatal period by testing whether SLC2A2 mutations can present with neonatal diabetes before the clinical features of FBS appear. Methods We studied SLC2A2 in patients with transient neonatal diabetes mellitus (TNDM; n  = 25) or permanent neonatal diabetes mellitus (PNDM; n  = 79) in whom we had excluded the common genetic causes of neonatal diabetes, using a combined approach of sequencing and homozygosity mapping. Results Of 104 patients, five (5%) were found to have homozygous SLC2A2 mutations, including four novel mutations (S203R, M376R, c.963+1G>A, F114LfsX16). Four out of five patients with SLC2A2 mutations presented with isolated diabetes and later developed features of FBS. Four out of five patients had TNDM (16% of our TNDM cohort of unknown aetiology). One patient with PNDM remains on insulin at 28 months. Conclusions SLC2A2 mutations are an autosomal recessive cause of neonatal diabetes that should be considered in consanguineous families or those with TNDM, after excluding common causes, even in the absence of features of FBS. The finding that patients with homozygous SLC2A2 mutations can have neonatal diabetes supports a role for GLUT2 in the human beta cell.

Heterozygous activating mutations in KCNJ11, which encodes the Kir6.2 subunit of the pancreatic ATP-sensitive potassium (K(ATP)) channel, cause both permanent and transient neonatal diabetes. A minority of patients also have neurological features. The identification of a KCNJ11 mutation has important therapeutic implications, as many patients can replace insulin injections with sulfonylurea tablets. We aimed to determine the age of presentation of patients with KCNJ11 mutations and to examine if there was a relationship between genotype and phenotype. KCNJ11 was sequenced in 239 unrelated patients from 21 countries, who were diagnosed with permanent diabetes before 2 years of age. Thirty-one of the 120 patients (26%) diagnosed in the first 26 weeks of life had a KCNJ11 mutation; no mutations were found in the 119 cases (0%) diagnosed after this age. Fourteen different heterozygous mutations were identified, with the majority resulting from de novo mutations. These include seven novel mutations: H46Y, R50Q, G53D C166Y, K170T, L164P and Y330S. All 11 probands with the most common mutation, R201H, had isolated diabetes. In contrast, developmental delay in addition to diabetes was seen in four of five probands with the V59M mutation and two of four with the R201C mutation. Five patients with developmental delay, epilepsy and neonatal diabetes (DEND) syndrome had unique mutations not associated with other phenotypes. KCNJ11 mutations are a common cause of permanent diabetes diagnosed in the first 6 months and all patients diagnosed in this age group should be tested. There is a strong genotype-phenotype relationship with the mutation being an important determinant of associated neurological features.

India has the greatest number of diabetic subjects in any one country, but the genetic basis of type 2 diabetes mellitus in India is poorly understood. Common non-coding variants in the transcription factor 7-like 2 gene (TCF7L2) have recently been strongly associated with increased risk of type 2 diabetes in European populations. We investigated whether TCF7L2 variants are also associated with type 2 diabetes mellitus in the Indian population. We genotyped type 2 diabetes patients (n = 955) and ethnically matched control subjects (n = 399) by sequencing three single nucleotide polymorphisms (SNPs) (rs7903146, rs12255372 and rs4506565) in TCF7L2. We observed a strong association with all the polymorphisms, including rs12255372 (odds ratio [OR] 1.50 [95% CI = 1.24-1.82], p = 4.0 x 10(-5)), rs4506565 (OR 1.48 [95% CI = 1.24-1.77], p = 2.0 x 10(-5)) and rs7903146 (OR 1.46 [95% CI = 1.22-1.75], p = 3.0 x 10(-5)). All three variants showed increased relative risk when homozygous rather than heterozygous, with the strongest risk for rs12255372 (OR 2.28 [95% CI = 1.40-3.72] vs OR 1.43 [95% CI = 1.11-1.83]). We found no association of the TCF7L2 genotypes with age at diagnosis, BMI or WHR, but the risk genotype at rs12255372 was associated with higher fasting plasma glucose (p = 0.001), higher 2-h plasma glucose (p = 0.0002) and higher homeostasis model assessment of insulin resistance (HOMA-R; p = 0.012) in non-diabetic subjects. Our study in Indian subjects replicates the strong association of TCF7L2 variants with type 2 diabetes in other populations. It also provides evidence that variations in TCF7L2 may play a crucial role in the pathogenesis of type 2 diabetes by influencing both insulin secretion and insulin resistance. TCF7L2 is an important gene for determining susceptibility to type 2 diabetes mellitus and it transgresses the boundaries of ethnicity.

Background: Hepatocyte nuclear factor-1 beta (HNF-1β) is a widely distributed transcription factor which plays a critical role in embryonic development of the kidney, pancreas, liver, and Mullerian duct. Thirty HNF-1β mutations have been reported in patients with renal cysts and other renal developmental disorders, young-onset diabetes, pancreatic atrophy, abnormal liver function tests, and genital tract abnormalities. Methods: We sequenced the HNF-1β gene in 160 unrelated subjects with renal disease, 40% of whom had a personal/family history of diabetes. Results: Twenty three different heterozygous HNF-1β mutations were identified in 23/160 subjects (14%), including 10 novel mutations (V61G, V110G, S148L, K156E, Q176X, R276Q, S281fsinsC, R295P, H324fsdelCA, Q470X). Seven (30%) cases were proven to be due to de novo mutations. Renal cysts were found in 19/23 (83%) patients (four with glomerulocystic kidney disease, GCKD) and diabetes in 11/23 (48%, while three other families had a family history of diabetes. Only 26% of families met diagnostic criteria for maturity-onset diabetes of the young (MODY) but 39% had renal cysts and diabetes (RCAD). We found no clear genotype/phenotype relationships. Conclusion: We report the largest series to date of HNF-1β mutations and confirm HNF-1β mutations as an important cause of renal disease. Despite the original description of HNF-1β as a MODY gene, a personal/family history of diabetes is often absent and the most common clinical manifestation is renal cysts. Molecular genetic testing for HNF-1β mutations should be considered in patients with unexplained renal cysts (including GCKD), especially when associated with diabetes, early-onset gout, or uterine abnormalities.