Low alanine aminotransferase levels and higher number of cardiovascular events in people with Type 2 diabetes: analysis of the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) study.

AIMS: To determine whether alanine aminotransferase or gamma-glutamyltransferase levels, as markers of liver health and non-alcoholic fatty liver disease, might predict cardiovascular events in people with Type 2 diabetes.

METHODS: Data from the Fenofibrate Intervention and Event Lowering in Diabetes study were analysed to examine the relationship between liver enzymes and incident cardiovascular events (non-fatal myocardial infarction, stroke, coronary and other cardiovascular death, coronary or carotid revascularization) over 5 years.

RESULTS: Alanine aminotransferase level had a linear inverse relationship with the first cardiovascular event occurring in participants during the study period. After adjustment, for every 1 sd higher baseline alanine aminotransferase value (13.2 U/l), the risk of a cardiovascular event was 7% lower (95% CI 4-13; P=0.02). Participants with alanine aminotransferase levels below and above the reference range 8-41 U/l for women and 9-59 U/l for men, had hazard ratios for a cardiovascular event of 1.86 (95% CI 1.12-3.09) and 0.65 (95% CI 0.49-0.87), respectively (P=0.001). No relationship was found for gamma-glutamyltransferase.

CONCLUSIONS: The data may indicate that in people with Type 2 diabetes, which is associated with higher alanine aminotransferase levels because of prevalent non-alcoholic fatty liver disease, a low alanine aminotransferase level is a marker of hepatic or systemic frailty rather than health. This article is protected by copyright. All rights reserved.

Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study

BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.

METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone.

FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions.

INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.

Effects of defined mixtures of persistent organic pollutants (POPs) on multiple cellular responses in the human hepatocarcinoma cell line, HepG2, using high content analysis screening

Persistent organic pollutants (POPs) are toxic substances, highly resistant to environmental degradation, which can bio-accumulate and have long-range atmospheric transport potential. Most studies focus on single compound effects, however as humans are exposed to several POPs simultaneously, investigating exposure effects of real life POP mixtures on human health is necessary. A defined mixture of POPs was used, where the compound concentration reflected its contribution to the levels seen in Scandinavian human serum (total mix). Several sub mixtures representing different classes of POP were also constructed. The perfluorinated (PFC) mixture contained six perfluorinated compounds, brominated (Br) mixture contained seven brominated compounds, chlorinated (Cl) mixture contained polychlorinated biphenyls and also p,p'-dichlorodiphenyldichloroethylene, hexachlorobenzene, three chlordanes, three hexachlorocyclohexanes and dieldrin. Human hepatocarcinoma (HepG2) cells were used for 2h and 48h exposures to the seven mixtures and analysis on a CellInsight™ NXT High Content Screening platform. Multiple cytotoxic endpoints were investigated: cell number, nuclear intensity and area, mitochondrial mass and membrane potential (MMP) and reactive oxygen species (ROS). Both the Br and Cl mixtures induced ROS production but did not lead to apoptosis. The PFC mixture induced the ROS production and likely induced cell apoptosis accompanied by the dissipation of MMP. Synergistic effects were evident for ROS induction when cells were exposed to the PFC+Br mixture. No significant effects were detected in the Br+Cl, PFC+Cl or total mixtures, which contain the same concentrations of chlorinated compounds as the Cl mixture plus additional compounds; highlighting the need for further exploration of POP mixtures in risk assessment.

The Application of Geophysics to a Number of Threats to Irish Soils

In its 2002 Communication "Towards a Thematic Strategy on Soil Protection" (COM 2002, 179), the Commission identified the main threats to which soils in the EU are confronted. More recently, the EU published a Thematic Strategy for Soil Protection (COM 2006, 231) as well as a proposal for a Soil Framework Directive (COM 2006, 232). The proposed directive, if implemented, will require states to identify a number of specific soil degradation processes that have occurred or are likely to occur in the near future. This project applies a number of recent geophysical developments, in addition to a range of traditional approaches, to a number of areas of Irish concern to Thematic Strategy for Soil Protection and the proposed Soil Framework Directive.

A Scalable Runtime for the ECOSCALE Heterogeneous Exascale Hardware Platform

Exascale computation is the next target of high performance computing. In the push to create exascale computing platforms, simply increasing the number of hardware devices is not an acceptable option given the limitations of power consumption, heat dissipation, and programming models which are designed for current hardware platforms. Instead, new hardware technologies, coupled with improved programming abstractions and more autonomous runtime systems, are required to achieve this goal. This position paper presents the design of a new runtime for a new heterogeneous hardware platform being developed to explore energy efficient, high performance computing. By combining a number of different technologies, this framework will both simplify the programming of current and future HPC applications, as well as automating the scheduling of data and computation across this new hardware platform. In particular, this work explores the use of FPGAs to achieve both the power and performance goals of exascale, as well as utilising the runtime to automatically effect dynamic configuration and reconfiguration of these platforms.