Glucokinase (GCK) Mutations and Their Characterization in MODY2 Children of Southern Italy

Type 2 Maturity Onset Diabetes of the Young (MODY2) is a monogenic autosomal disease characterized by a primary defect in insulin secretion and hyperglycemia. It results from GCK gene mutations that impair enzyme activity. Between 2006 and 2010, we investigated GCK mutations in 66 diabetic children from southern Italy with suspected MODY2. Denaturing High Performance Liquid Chromatography (DHPLC) and sequence analysis revealed 19 GCK mutations in 28 children, six of which were novel: p.Glu40Asp, p.Val154Leu, p.Arg447Glyfs, p.Lys458_Cys461del, p.Glu395_Arg397del and c.580-2A>T. We evaluated the effect of these 19 mutations using bioinformatic tools such as Polymorphism Phenotyping (Polyphen), Sorting Intolerant From Tolerant (SIFT) and in silico modelling. We also conducted a functional study to evaluate the pathogenic significance of seven mutations that are among the most severe mutations found in our population, and have never been characterized: p.Glu70Asp, p.His137Asp, p.Phe150Tyr, p.Val154Leu, p.Gly162Asp, p.Arg303Trp and p.Arg392Ser. These seven mutations, by altering one or more kinetic parameters, reduced enzyme catalytic activity by >40%. All mutations except p.Glu70Asp displayed thermal-instability, indeed >50% of enzyme activity was lost at 50°C/30 min. Thus, these seven mutations play a pathogenic role in MODY2 insurgence. In conclusion, this report revealed six novel GCK mutations and sheds some light on the structure-function relationship of human GCK mutations and MODY2

Internal and external forcing of multidecadal Atlantic climate variability over the past 1,200 years

The North Atlantic experiences climate variability on multidecadal scales, which is sometimes referred to as Atlantic multidecadal variability. However, the relative contributions of external forcing such as changes in solar irradiance or volcanic activity and internal dynamics to these variations are unclear. Here we provide evidence for persistent summer Atlantic multidecadal variability from AD 800 to 2010 using a network of annually resolved terrestrial proxy records from the circum-North Atlantic region. We find that large volcanic eruptions and solar irradiance minima induce cool phases of Atlantic multidecadal variability and collectively explain about 30% of the variance in the reconstruction on timescales greater than 30 years. We are then able to isolate the internally generated component of Atlantic multidecadal variability, which we define as the Atlantic multidecadal oscillation. We find that the Atlantic multidecadal oscillation is the largest contributor to Atlantic multidecadal variability over the past 1,200 years. We also identify coherence between the Atlantic multidecadal oscillation and Northern Hemisphere temperature variations, leading us to conclude that the apparent link between Atlantic multidecadal variability and regional to hemispheric climate does not arise solely from a common response to external drivers, and may instead reflect dynamic processes

AKAPs integrate genetic findings for autism spectrum disorders

Contains fulltext : 115371.pdf (publisher's version ) (Open Access)Autism spectrum disorders (ASDs) are highly heritable, and six genome-wide association studies (GWASs) of ASDs have been published to date. In this study, we have integrated the findings from these GWASs with other genetic data to identify enriched genetic networks that are associated with ASDs. We conducted bioinformatics and systematic literature analyses of 200 top-ranked ASD candidate genes from five published GWASs. The sixth GWAS was used for replication and validation of our findings. Further corroborating evidence was obtained through rare genetic variant studies, that is, exome sequencing and copy number variation (CNV) studies, and/or other genetic evidence, including candidate gene association, microRNA and gene expression, gene function and genetic animal studies. We found three signaling networks regulating steroidogenesis, neurite outgrowth and (glutamatergic) synaptic function to be enriched in the data. Most genes from the five GWASs were also implicated-independent of gene size-in ASDs by at least one other line of genomic evidence. Importantly, A-kinase anchor proteins (AKAPs) functionally integrate signaling cascades within and between these networks. The three identified protein networks provide an important contribution to increasing our understanding of the molecular basis of ASDs. In addition, our results point towards the AKAPs as promising targets for developing novel ASD treatments

Performance of PREM1,2,6, MMRpredict, and MMRpro in detecting Lynch syndrome among endometrial cancer cases

PURPOSE: Lynch syndrome accounts for 2-5% of endometrial cancer cases. Lynch syndrome prediction models have not been evaluated among endometrial cancer cases. METHODS: Area under the receiver operating curve (AUC), sensitivity and specificity of PREMM(1,2,6), MMRpredict, and MMRpro scores were assessed among 563 population-based and 129 clinic-based endometrial cancer cases. RESULTS: A total of 14 (3%) population-based and 80 (62%) clinic-based subjects had pathogenic mutations. PREMM(1,2,6), MMRpredict, and MMRpro were able to distinguish mutation carriers from noncarriers (AUC of 0.77, 0.76, and 0.77, respectively), among population-based cases. All three models had lower discrimination for the clinic-based cohort, with AUCs of 0.67, 0.64, and 0.54, respectively. Using a 5% cutoff, sensitivity and specificity were as follows: PREMM(1,2,6), 93% and 5% among population-based cases and 99% and 2% among clinic-based cases; MMRpredict, 71% and 64% for the population-based cohort and 91% and 0% for the clinic-based cohort; and MMRpro, 57% and 85% among population-based cases and 95% and 10% among clinic-based cases. CONCLUSION: Currently available prediction models have limited clinical utility in determining which patients with endometrial cancer should undergo genetic testing for Lynch syndrome. Immunohistochemical analysis and microsatellite instability testing may be the best currently available tools to screen for Lynch syndrome in endometrial cancer patients