Association of fenofibrate therapy with long-term cardiovascular risk in statin-treated patients with type 2 diabetes

IMPORTANCE: Patients with type 2 diabetes are at high risk of cardiovascular disease (CVD) in part owing to hypertriglyceridemia and low high-density lipoprotein cholesterol. It is unknown whether adding triglyceride-lowering treatment to statin reduces this risk. OBJECTIVE: To determine whether fenofibrate reduces CVD risk in statin-treated patients with type 2 diabetes. DESIGN, SETTING, AND PARTICIPANTS: Posttrial follow-up of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Lipid Study between July 2009 and October 2014; 5 years of follow-up were completed for a total of 9.7 years at general community and academic outpatient research clinics in the United States and Canada. Of the original 5518 ACCORD Lipid Trial participants, 4644 surviving participants were selected based on the presence of type 2 diabetes and either prevalent CVD or CVD risk factors and high-density lipoprotein levels less than 50 mg/dL (<55 mg/dL for women and African American individuals). INTERVENTIONS: Passive follow-up of study participants previously treated with fenofibrate or masked placebo. MAIN OUTCOMES AND MEASURES: Occurrence of cardiovascular outcomes including primary composite outcome of fatal and nonfatal myocardial infarction and stroke in all participants and in prespecified subgroups. RESULTS: The 4644 follow-on study participants were broadly representative of the original ACCORD study population and included significant numbers of women (n = 1445; 31%), nonwhite individuals (n = 1094; 21%), and those with preexisting cardiovascular events (n = 1620; 35%). Only 4.3% of study participants continued treatment with fenofibrate following completion of ACCORD. High-density lipoprotein and triglyceride values rapidly equalized among participants originally randomized to fenofibrate or placebo. Over a median total postrandomization follow-up of 9.7 years, the hazard ratio (HR) for the primary study outcome among participants originally randomized to fenofibrate vs placebo (HR, 0.93; 95% CI, 0.83-1.05; P = .25) was comparable with that originally observed in ACCORD (HR, 0.92; 95% CI, 0.79-1,08; P = .32). Despite these overall neutral results, we continued to find evidence that fenofibrate therapy effectively reduced CVD in study participants with dyslipidemia, defined as triglyceride levels greater than 204 mg/dL and high-density lipoprotein cholesterol levels less than 34 mg/dL (HR, 0.73; 95% CI, 0.56-0.95). CONCLUSIONS AND RELEVANCE: Extended follow-up of ACCORD-lipid trial participants confirms the original neutral effect of fenofibrate in the overall study cohort. The continued observation of heterogeneity of treatment response by baseline lipids suggests that fenofibrate therapy may reduce CVD in patients with diabetes with hypertriglyceridemia and low high-density lipoprotein cholesterol. A definitive trial of fibrate therapy in this patient population is needed to confirm these findings. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00000620

Developing the digital self-determined learner through heutagogical design

This empirical qualitative study investigates whether the introduction of heutagogy in contemporary nursing education can foster the development of the digital self-determined learner, who is prepared to work and live in the fourth industrial age and beyond. The impact of heutagogical design on learner process and outcomes is explored through qualitative framework analysis of learner data and reflective educator observations. Findings suggest that with careful scaffolding and courage in remaining true to the educational philosophy, this approach has the potential to develop learners who demonstrate key principles of heutagogy including non-linear learning, learner agency, capability, self-reflection and metacognition and double-loop learning. This innovative study provides insight into the process of developing the self-determined learner and encourages further research into flexible and learner-centred approaches across Higher Education

An integrated map of structural variation in 2,504 human genomes

Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association. © 2015 Macmillan Publishers Limited. All rights reserved

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

Integrative functional genomic analysis of human brain development and neuropsychiatric risks

To broaden our understanding of human neurodevelopment, we profiled transcriptomic and epigenomic landscapes across brain regions and/or cell types for the entire span of prenatal and postnatal development. Integrative analysis revealed temporal, regional, sex, and cell type-specific dynamics.We observed a global transcriptomic cup-shaped pattern, characterized by a late fetal transition associated with sharply decreased regional differences and changes in cellular composition and maturation, followed by a reversal in childhood-adolescence, and accompanied by epigenomic reorganizations. Analysis of gene coexpression modules revealed relationships with epigenomic regulation and neurodevelopmental processes. Genes with genetic associations to brain-based traits and neuropsychiatric disorders (including MEF2C, SATB2, SOX5, TCF4, and TSHZ3) converged in a small number of modules and distinct cell types, revealing insights into neurodevelopment and the genomic basis of neuropsychiatric risks

The GENCODE pseudogene resource.

BACKGROUND: Pseudogenes have long been considered as nonfunctional genomic sequences. However, recent evidence suggests that many of them might have some form of biological activity, and the possibility of functionality has increased interest in their accurate annotation and integration with functional genomics data. RESULTS: As part of the GENCODE annotation of the human genome, we present the first genome-wide pseudogene assignment for protein-coding genes, based on both large-scale manual annotation and in silico pipelines. A key aspect of this coupled approach is that it allows us to identify pseudogenes in an unbiased fashion as well as untangle complex events through manual evaluation. We integrate the pseudogene annotations with the extensive ENCODE functional genomics information. In particular, we determine the expression level, transcription-factor and RNA polymerase II binding, and chromatin marks associated with each pseudogene. Based on their distribution, we develop simple statistical models for each type of activity, which we validate with large-scale RT-PCR-Seq experiments. Finally, we compare our pseudogenes with conservation and variation data from primate alignments and the 1000 Genomes project, producing lists of pseudogenes potentially under selection. CONCLUSIONS: At one extreme, some pseudogenes possess conventional characteristics of functionality; these may represent genes that have recently died. On the other hand, we find interesting patterns of partial activity, which may suggest that dead genes are being resurrected as functioning non-coding RNAs. The activity data of each pseudogene are stored in an associated resource, psiDR, which will be useful for the initial identification of potentially functional pseudogenes