Two new mutations in the HIF2A gene associated with erythrocytosis

Congenital or familial erythrocytosis/polycythemia can have many causes, and an emerging cause is genetic disruption of the oxygen-sensing pathway that regulates the Erythropoietin (EPO) gene. More specifically, recent studies have identified erythrocytosis-associated mutations in the HIF2A gene, which encodes for Hypoxia Inducible Factor-2a (HIF-2a), as well as in two genes that encode for proteins that regulate it, Prolyl Hydroxylase Domain protein 2 (PHD2) and the von Hippel Lindau tumor suppressor protein (VHL). We report here the identification of two new heterozygous HIF2A missense mutations, M535T, and F540L, both associated with erythrocytosis. Met-535 has previously been identified as a residue mutated in other patients with erythrocytosis; although, the mutation of this particular residue to Thr has not been reported. In contrast, Phe-540 has not been reported as a residue mutated in erythrocytosis, and we present evidence here that this mutation impairs interaction of HIF-2a with both VHL and PHD2. © 2012 Wiley Periodicals, Inc.

Organising for growth:Irish state administration 1958-2008

This paper analyses some key features of Irish public administration as it has developed since the foundation of the state, paying particular attention to the period from the late 1950s onward. During these decades, notwithstanding successive waves of concern expressed over the need for public sector reform, the evidence suggests an underlying lack of coherence in the evolution of the public administrationsystem that resulted in a poor capacity for effective policy coordination. Yet the drive toward economic modernisation also resulted in the creation of new state competence to support industrial development both directly and indirectly. These changes can be tracked organisationally, drawing on the database of the IRCHSS-funded Mapping the Irish State project.

Model selection for prognostic time-to-event gene signature discovery with applications in early breast cancer data

Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery. In this study we improve the prognostic signature discovery process through the application of the multivariate partial Cox model combined with the concordance index, hazard ratio of predictions, independence from available clinical covariates and biological enrichment as measures of signature performance. The proposed framework was applied to discover prognostic multigene signatures from early breast cancer data. The partial Cox model combined with the multiple performance measures were used in both guiding the selection of the optimal panel of prognostic genes and prediction of risk within cross validation without dichotomising the follow-up times at any stage. The signatures were successfully externally cross validated in independent breast cancer datasets, yielding a hazard ratio of 2.55 [1.44, 4.51] for the top ranking signature.

New genetic loci link adipose and insulin biology to body fat distribution

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

Genetic studies of body mass index yield new insights for obesity biology

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.