Modulation of impulsive behaviours using transcranial random noise stimulation

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Assessment of High-Sensitivity C-Reactive Protein Levels as Diagnostic Discriminator of Maturity-Onset Diabetes of the Young Due to HNF1A Mutations

OBJECTIVE: Despite the clinical importance of an accurate diagnosis in individuals with monogenic forms of diabetes, restricted access to genetic testing leaves many patients with undiagnosed diabetes. Recently, common variation near the HNF1 homeobox A (HNF1A) gene was shown to influence C-reactive protein levels in healthy adults. We hypothesized that serum levels of high-sensitivity C-reactive protein (hs-CRP) could represent a clinically useful biomarker for the identification of HNF1A mutations causing maturity-onset diabetes of the young (MODY). RESEARCH DESIGN AND METHODS: Serum hs-CRP was measured in subjects with HNF1A-MODY (n = 31), autoimmune diabetes (n = 316), type 2 diabetes (n = 240), and glucokinase (GCK) MODY (n = 24) and in nondiabetic individuals (n = 198). The discriminative accuracy of hs-CRP was evaluated through receiver operating characteristic (ROC) curve analysis, and performance was compared with standard diagnostic criteria. Our primary analyses excluded approximately 11% of subjects in whom the single available hs-CRP measurement was >10 mg/l. RESULTS: Geometric mean (SD range) hs-CRP levels were significantly lower (

Low Frequency Variants in the Exons Only Encoding Isoform A of HNF1A Do Not Contribute to Susceptibility to Type 2 Diabetes

Background: There is considerable interest in the hypothesis that low frequency, intermediate penetrance variants contribute to the proportion of Type 2 Diabetes (T2D) susceptibility not attributable to the common variants uncovered through genome-wide association approaches. Genes previously implicated in monogenic and multifactorial forms of diabetes are obvious candidates in this respect. In this study, we focussed on exons 8-10 of the HNF1A gene since rare, penetrant mutations in these exons (which are only transcribed in selected HNF1A isoforms) are associated with a later age of diagnosis of Maturity onset diabetes of the young (MODY) than mutations in exons 1-7. The age of diagnosis in the subgroup of HNF1A-MODY individuals with exon 8-10 mutations overlaps with that of early multifactorial T2D, and we set out to test the hypothesis that these exons might also harbour low-frequency coding variants of intermediate penetrance that contribute to risk of multifactorial T2D. Methodology and principal findings: We performed targeted capillary resequencing of HNF1A exons 8-10 in 591 European T2D subjects enriched for genetic aetiology on the basis of an early age of diagnosis (≤ 45 years) and/or family history of T2D (≥ 1 affected sibling). PCR products were sequenced and compared to the published HNF1A sequence. We identified several variants (rs735396 [IVS9-24T>C], rs1169304 [IVS8+29T>C], c.1768+44C>T [IVS9+44C>T] and rd61953349 [c.1545G>A, p.T515T] but no novel non-synonymous coding variants were detected. Conclusions and significance: We conclude that low frequency, nonsynonymous coding variants in the terminal exons of HNF1A are unlikely to contribute to T2D-susceptibility in European samples. Nevertheless, the rationale for seeking low-frequency causal variants in genes known to contain rare, penetrant mutations remains strong and should motivate efforts to screen other genes in a similar fashion

Development and validation of multivariable clinical diagnostic models to identify type 1 diabetes requiring rapid insulin therapy in adults aged 18-50 years

This is the final version. Available on open access from BMJ Publishing Group via the DOI in this recordObjective: To develop and validate multivariable clinical diagnostic models to assist distinguishing between type 1 and type 2 diabetes in adults aged 18 to 50. Design: Multivariable logistic regression analysis was used to develop classification models integrating five pre-specified predictor variables, including clinical features (age of diagnosis, BMI) and clinical biomarkers (GADA and Islet Antigen 2 islet autoantibodies, Type 1 Diabetes Genetic Risk Score), to identify type 1 diabetes with rapid insulin requirement using data from existing cohorts. Setting: United Kingdom cohorts recruited from primary and secondary care. Participants: 1,352 (model development) and 582 (external validation) participants diagnosed with diabetes between the age of 18 and 50 years of white European origin. Main outcome measures: Type 1 diabetes was defined by rapid insulin requirement (within 3 years of diagnosis) and severe endogenous insulin deficiency (C-peptide <200pmol/L). Type 2 diabetes was defined by either a lack of rapid insulin requirement or, where insulin treated within 3 years, retained endogenous insulin secretion (C-peptide >600pmol/L at ≥5 years diabetes duration). Model performance was assessed using area under the receiver operating characteristic curve (ROC AUC), and internal and external validation. 4 Results: Type 1 diabetes was present in 13% of participants in the development cohort. All five predictor variables were discriminative and independent predictors of type 1 diabetes (p<0.001 for all) with individual ROC AUC ranging from 0.82 to 0.85. Model performance was high: ROC AUC range 0.90 [95%CI 0.88, 0.93] (clinical features only) to 0.97 [0.96, 0.98] (all predictors) with low prediction error. Results were consistent in external validation (clinical features and GADA ROC AUC 0.93 [0.90, 0.96]). Conclusions: Clinical diagnostic models integrating clinical features with biomarkers have high accuracy for identifying type 1 diabetes with rapid insulin requirement, and could assist clinicians and researchers in accurately identifying patients with type 1 diabetes.National Institute for Health Research (NIHR)European Community FP7Oxford Hospitals Charitable FundWellcome TrustMedical Research Council (MRC

Fucosylated AGP glycopeptides as biomarkers of HNF1A-Maturity onset diabetes of the young

Aims: We previously demonstrated that antennary fucosylated N-glycans on plasma proteins are regulated by HNF1A and can identify cases of Maturity-Onset Diabetes of the Young caused by HNF1A variants (HNF1A-MODY). Based on literature data, we further postulated that N-glycans with best diagnostic value mostly originate from alpha-1-acid glycoprotein (AGP). In this study we analyzed fucosylation of AGP in subjects with HNF1A-MODY and other types of diabetes aiming to evaluate its diagnostic potential. Methods: A recently developed LC-MS method for AGP N-glycopeptide analysis was utilized in two independent cohorts: a) 466 subjects with different diabetes subtypes to test the fucosylation differences, b) 98 selected individuals to test the discriminative potential for pathogenic HNF1A variants. Results: Our results showed significant reduction in AGP fucosylation associated to HNF1A-MODY when compared to other diabetes subtypes. Additionally, ROC curve analysis confirmed significant discriminatory potential of individual fucosylated AGP glycopeptides, where the best performing glycopeptide had an AUC of 0.94 (95% CI 0.90–0.99). Conclusions: A glycopeptide based diagnostic tool would be beneficial for patient stratification by providing information about the functionality of HNF1A. It could assist the interpretation of DNA sequencing results and be a useful addition to the differential diagnostic process.publishedVersio

Combining Information from Common Type 2 Diabetes Risk Polymorphisms Improves Disease Prediction

BACKGROUND: A limited number of studies have assessed the risk of common diseases when combining information from several predisposing polymorphisms. In most cases, individual polymorphisms only moderately increase risk (~20%), and they are thought to be unhelpful in assessing individuals' risk clinically. The value of analyzing multiple alleles simultaneously is not well studied. This is often because, for any given disease, very few common risk alleles have been confirmed. METHODS AND FINDINGS: Three common variants (Lys23 of KCNJ11, Pro12 of PPARG, and the T allele at rs7903146 of TCF7L2) have been shown to predispose to type 2 diabetes mellitus across many large studies. Risk allele frequencies ranged from 0.30 to 0.88 in controls. To assess the combined effect of multiple susceptibility alleles, we genotyped these variants in a large case-control study (3,668 controls versus 2,409 cases). Individual allele odds ratios (ORs) ranged from 1.14 (95% confidence interval [CI], 1.05 to 1.23) to 1.48 (95% CI, 1.36 to 1.60). We found no evidence of gene-gene interaction, and the risks of multiple alleles were consistent with a multiplicative model. Each additional risk allele increased the odds of type 2 diabetes by 1.28 (95% CI, 1.21 to 1.35) times. Participants with all six risk alleles had an OR of 5.71 (95% CI, 1.15 to 28.3) compared to those with no risk alleles. The 8.1% of participants that were double-homozygous for the risk alleles at TCF7L2 and Pro12Ala had an OR of 3.16 (95% CI, 2.22 to 4.50), compared to 4.3% with no TCF7L2 risk alleles and either no or one Glu23Lys or Pro12Ala risk alleles. CONCLUSIONS: Combining information from several known common risk polymorphisms allows the identification of population subgroups with markedly differing risks of developing type 2 diabetes compared to those obtained using single polymorphisms. This approach may have a role in future preventative measures for common, polygenic diseases

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr