Protecting Inshore and Demersal Finfish Identification of Critical Habitats for Juvenile Dhufish Workshop Report

A Juvenile Dhufish Workshop was held at the Western Australian Fisheries and Marine Research Laboratories (WAFMRL) on 18th March 2010, which was the first component of a State Natural Resource Management (NRM) funded project entitled “Protecting Inshore and Demersal Finfish - Identification of Critical Habitats for Juvenile Dhufish”. The primary objective of the workshop was to provide a forum for discussion in order to compile all biological, ecological and anecdotal information on the early life history of dhufish, to create hypotheses of habitat requirements for juvenile dhufish and provide recommendations as to which sampling methods should be used to confirm the presence of juveniles at the identified habitats and locations

Identification of critical habitats for juvenile dhufish (Glaucosoma hebraicum) NRM Project 09038 – Protecting Inshore and Demersal Finfish

The Western Australian dhufish (Glaucosoma hebraicum) is an iconic demersal species that is endemic to the lower west and south coasts of Western Australia (WA). Information on the critical habitat and distribution of juvenile dhufish, less than two years of age and ca 150 mm total length (TL), was limited to a single study in one area where they have been previously collected. Increasing the knowledge on the habitat types occupied by juvenile dhufish, the distribution of these habitats in the West Coast Bioregion and methods to potentially monitor the annual recruitment of the species are important in their management

A qualitative reflexive thematic analysis of innovation and regulation in hearing health care

Background: The hearing health sector is an example of a health sector that is experiencing a period of rapid innovation driven by digital technologies. These innovations will impact the types of interventions and services available to support the communication of deaf and hard-of-hearing individuals. This study explored the perceptions of informed participants on the topic of innovation and regulation within hearing healthcare in Australia and the United Kingdom (UK). Methods: Participants (N = 29, Australia [n = 16], UK [n = 13]) were purposively sampled and joined one of two online workshops. Participants included adults with hearing loss and family members, hearing health professionals, academics/researchers, representatives of hearing device manufacturers, regulators and policymakers. Workshop data were analysed using reflexive thematic analysis. Results: Participants conceptualised the hearing health sector as a network of organisations and individuals with different roles, knowledge and interests, in a state of flux driven by innovation and regulation. Innovation and regulation were perceived as mechanisms to ensure quality and mitigate risk within a holistic approach to care. Innovations encompassed technological as well as non-technological innovations of potential benefit to consumers. Participants agreed it was essential for innovation and regulation to be congruent with societal values. Critical to ethical congruence was the involvement of consumers throughout both innovation and regulation stages, and the use of innovation and regulation to tackle stigma and reduce health disparities. Participants expressed the desire for accessible and inclusive innovation in the context of fair, transparent and trustworthy commercial practices. Conclusions: This study explored how stakeholders within the hearing health sector understand and make sense of innovation and the role of regulation. Overall, and despite reservations relating to health care professionals’ changing roles and responsibilities, innovation and regulation were conceptualised as beneficial when situated in the context of holistic, whole-person, models of care. The results of this study will inform considerations to support the development and implementation of innovations and regulation within the hearing sector and across other health sectors influenced by technological advances

Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases.

Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non-demented controls, we investigated global disruptions in the co-regulation of genes in two neurodegenerative diseases, late-onset Alzheimer's disease (AD) and Huntington's disease (HD). We identified networks of differentially co-expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former dominant for both AD and HD and both patterns replicating in independent human cohorts of AD and aging. When aligning networks of DC patterns and physical interactions, we identified a 242-gene subnetwork enriched for independent AD/HD signatures. This subnetwork revealed a surprising dichotomy of gained/lost correlations among two inter-connected processes, chromatin organization and neural differentiation, and included DNA methyltransferases, DNMT1 and DNMT3A, of which we predicted the former but not latter as a key regulator. To validate the inter-connection of these two processes and our key regulator prediction, we generated two brain-specific knockout (KO) mice and show that Dnmt1 KO signature significantly overlaps with the subnetwork (P = 3.1 × 10(-12)), while Dnmt3a KO signature does not (P = 0.017)

Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease

Tissue-to-tissue coexpression networks between genes in hypothalamus, liver or adipose tissue enable identification of obesity-specific genes

Mapping the genetic architecture of gene expression in human liver

Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process. © 2008 Schadt et al

Multi-tissue coexpression networks reveal unexpected subnetworks associated with disease

Background Obesity is a particularly complex disease that at least partially involves genetic and environmental perturbations to gene-networks connecting the hypothalamus and several metabolic tissues, resulting in an energy imbalance at the systems level. Results To provide an inter-tissue view of obesity with respect to molecular states that are associated with physiological states, we developed a framework for constructing tissue-to-tissue coexpression networks between genes in the hypothalamus, liver or adipose tissue. These networks have a scale-free architecture and are strikingly independent of gene-gene coexpression networks that are constructed from more standard analyses of single tissues. This is the first systematic effort to study inter-tissue relationships and highlights genes in the hypothalamus that act as information relays in the control of peripheral tissues in obese mice. The subnetworks identified as specific to tissue-to-tissue interactions are enriched in genes that have obesity-relevant biological functions such as circadian rhythm, energy balance, stress response, or immune response. Conclusions Tissue-to-tissue networks enable the identification of disease-specific genes that respond to changes induced by different tissues and they also provide unique details regarding candidate genes for obesity that are identified in genome-wide association studies. Identifying such genes from single tissue analyses would be difficult or impossible

A New Liver Expression Quantitative Trait Locus Map From 1,183 Individuals Provides Evidence for Novel Expression Quantitative Trait Loci of Drug Response, Metabolic, and Sex-Biased Phenotypes

Expression quantitative trait locus (eQTL) studies in human liver are crucial for elucidating how genetic variation influences variability in disease risk and therapeutic outcomes and may help guide strategies to obtain maximal efficacy and safety of clinical interventions. Associations between expression microarray and genome-wide genotype data from four human liver eQTL studies (n = 1,183) were analyzed. More than 2.3 million cis-eQTLs for 15,668 genes were identified. When eQTLs were filtered against a list of 1,496 drug response genes, 187,829 cis-eQTLs for 1,191 genes were identified. Additionally, 1,683 sex-biased cis-eQTLs were identified, as well as 49 and 73 cis-eQTLs that colocalized with genome-wide association study signals for blood metabolite or lipid levels, respectively. Translational relevance of these results is evidenced by linking DPYD eQTLs to differences in safety of chemotherapy, linking the sex-biased regulation of PCSK9 expression to anti-lipid therapy, and identifying the G-protein coupled receptor GPR180 as a novel drug target for hypertriglyceridemia

Liver and Adipose Expression Associated SNPs Are Enriched for Association to Type 2 Diabetes

Genome-wide association studies (GWAS) have demonstrated the ability to identify the strongest causal common variants in complex human diseases. However, to date, the massive data generated from GWAS have not been maximally explored to identify true associations that fail to meet the stringent level of association required to achieve genome-wide significance. Genetics of gene expression (GGE) studies have shown promise towards identifying DNA variations associated with disease and providing a path to functionally characterize findings from GWAS. Here, we present the first empiric study to systematically characterize the set of single nucleotide polymorphisms associated with expression (eSNPs) in liver, subcutaneous fat, and omental fat tissues, demonstrating these eSNPs are significantly more enriched for SNPs that associate with type 2 diabetes (T2D) in three large-scale GWAS than a matched set of randomly selected SNPs. This enrichment for T2D association increases as we restrict to eSNPs that correspond to genes comprising gene networks constructed from adipose gene expression data isolated from a mouse population segregating a T2D phenotype. Finally, by restricting to eSNPs corresponding to genes comprising an adipose subnetwork strongly predicted as causal for T2D, we dramatically increased the enrichment for SNPs associated with T2D and were able to identify a functionally related set of diabetes susceptibility genes. We identified and validated malic enzyme 1 (Me1) as a key regulator of this T2D subnetwork in mouse and provided support for the association of this gene to T2D in humans. This integration of eSNPs and networks provides a novel approach to identify disease susceptibility networks rather than the single SNPs or genes traditionally identified through GWAS, thereby extracting additional value from the wealth of data currently being generated by GWAS