Regional development, commercialisation and target adoption of new integrated management techniques for Sheep industry

This Sheep CRC2 project is directed towards regional development of, support for, commercialisation and target adoption of, new integrated management techniques, which will lift productivity and better match product with market specification. The outputs and benefits will help support and improve the productivity and profitability of producers remaining in the industry, and support industry in the current move towards one in which both meat and wool will be joint drivers of industry productivity.

Genetic analysis for a shared biological basis between migraine and coronary artery disease

Objective: To apply genetic analysis of genome-wide association data to study the extent and nature of a shared biological basis between migraine and coronary artery disease (CAD). Methods: Four separate methods for cross-phenotype genetic analysis were applied on data from 2 large-scale genome-wide association studies of migraine (19,981 cases, 56,667 controls) and CAD (21,076 cases, 63,014 controls). The first 2 methods quantified the extent of overlapping risk variants and assessed the load of CAD risk loci in migraineurs. Genomic regions of shared risk were then identified by analysis of covariance patterns between the 2 phenotypes and by querying known genome-wide significant loci. Results: We found a significant overlap of genetic risk loci for migraine and CAD. When stratified by migraine subtype, this was limited to migraine without aura, and the overlap was protective in that patients with migraine had a lower load of CAD risk alleles than controls. Genes indicated by 16 shared risk loci point to mechanisms with potential roles in migraine pathogenesis and CAD, including endothelial dysfunction (PHACTR1) and insulin homeostasis (GIP). Conclusions: The results suggest that shared biological processes contribute to risk of migraine and CAD, but surprisingly this commonality is restricted to migraine without aura and the impact is in opposite directions. Understanding the mechanisms underlying these processes and their opposite relationship to migraine and CAD may improve our understanding of both disorders.

Genetic burden associated with varying degrees of disease severity in endometriosis

Endometriosis is primarily characterized by the presence of tissue resembling endometrium outside the uterine cavity and is usually diagnosed by laparoscopy. The most commonly used classification of disease, the revised American Fertility Society (rAFS) system to grade endometriosis into different stages based on disease severity (I to IV), has been questioned as it does not correlate well with underlying symptoms, posing issues in diagnosis and choice of treatment. Using two independent European genome-wide association (GWA) datasets and top-level classification of the endometriosis cases based on rAFS [minimal or mild (Stage A) and moderate-to-severe (Stage B) disease], we previously showed that Stage B endometriosis has greater contribution of common genetic variation to its aetiology than Stage A disease. Herein, we extend our previous analysis to four endometriosis stages [minimal (Stage I), mild (Stage II), moderate (Stage III) and severe (Stage IV) disease] based on the rAFS classification system and compared the genetic burden across stages. Our results indicate that genetic burden increases from minimal to severe endometriosis. For the minimal disease, genetic factors may contribute to a lesser extent than other disease categories. Mild and moderate endometriosis appeared genetically similar, making it difficult to tease them apart. Consistent with our previous reports, moderate and severe endometriosis showed greater genetic burden than minimal or mild disease. Overall, our results provide new insights into the genetic architecture of endometriosis and further investigation in larger samples may help to understand better the aetiology of varying degrees of endometriosis, enabling improved diagnostic and treatment modalities.

Leading Sheep II

Leading Sheep is an education framework for leading the adoption of new technologies and practices to increase the productivity of the Queensland sheep industry.

Leading Sheep III

Leading Sheep is a framework for supporting decision-making about technologies and practices to increase the profitability and productivity of the Queensland Sheep Businesses. Leading Sheep aims to achieve a high level of engagement with sheep businesses in Queensland to support their ongoing decision making processes about productivity and profitability.

Making More from Sheep Phase II : MMfS State Coordination – Queensland

Making More from Sheep (MMfS) is a majority market extension program funded by Meat & Livestock Australia (MLA) and Australian Wool Innovation (AWI). Phase II of MMfS commenced in Queensland with a business planning process in October 2010 and delivery from November 2010 until November 2013. Mr Tony Hamilton of the Department of Agriculture, Fisheries and Forestry (DAFF) was initially the State Coordinator with responsibility for planning, project implementation, monitoring and evaluation. He was replaced by Ms Nicole Sallur from DAFF towards the end of the project. Delivery involving partner organisations provided best practice management information and tools to sheep producers with target Key Performance Indicators (KPI’s) exceeded across all three tiers of engagement category. 31 events were delivered to 551 participants. Satisfaction and value scores averaged across all events measured 8.7 and 8.2 respectively. Operational recommendations have been included in the report.

Controlled exposure as a management tool for Glassers disease

Control of bacterial disease of pigs.

Hardwoods Nutrient/Disease Interactions

Interactions of nutrients and disease expression in hardwood plantations.

ACIAR Reduce pest disease related yield decrease in sweet potato Papua New Guinea

Develops and extends DEEDI and partner technologies, improves yields and quality by removing virus diseases and some pests. Objectives: 1.Develop and test sweet potato pest and disease control strategies 2.Increase dissemination and adoption of pathogen tested and Integrated Pest Management strategy for pest and disease control.

DAQ339A Pest and disease identification and management in herbs

The major objective is to produce an educational tool for growers and research/extension personnel to allow accurate identification of a range of pests and diseases encountered in herbs. To a lessor extent develop both a mechanism to manage beneficial insects in field crops pre-harvest and to identify some common seed borne diseases in herbs.

Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis

Common diseases such as endometriosis (ED), Alzheimer's disease (AD) and multiple sclerosis (MS) account for a significant proportion of the health care burden in many countries. Genome-wide association studies (GWASs) for these diseases have identified a number of individual genetic variants contributing to the risk of those diseases. However, the effect size for most variants is small and collectively the known variants explain only a small proportion of the estimated heritability. We used a linear mixed model to fit all single nucleotide polymorphisms (SNPs) simultaneously, and estimated genetic variances on the liability scale using SNPs from GWASs in unrelated individuals for these three diseases. For each of the three diseases, case and control samples were not all genotyped in the same laboratory. We demonstrate that a careful analysis can obtain robust estimates, but also that insufficient quality control (QC) of SNPs can lead to spurious results and that too stringent QC is likely to remove real genetic signals. Our estimates show that common SNPs on commercially available genotyping chips capture significant variation contributing to liability for all three diseases. The estimated proportion of total variation tagged by all SNPs was 0.26 (SE 0.04) for ED, 0.24 (SE 0.03) for AD and 0.30 (SE 0.03) for MS. Further, we partitioned the genetic variance explained into five categories by a minor allele frequency (MAF), by chromosomes and gene annotation. We provide strong evidence that a substantial proportion of variation in liability is explained by common SNPs, and thereby give insights into the genetic architecture of the diseases.

Identification of seven loci affecting mean telomere length and their association with disease

Interindividual variation in mean leukocyte telomere length (LTL) is associated with cancer and several age-associated diseases. We report here a genome-wide meta-analysis of 37,684 individuals with replication of selected variants in an additional 10,739 individuals. We identified seven loci, including five new loci, associated with mean LTL (P < 5 x 10(-8)). Five of the loci contain candidate genes (TERC, TERT, NAF1, OBFC1 and RTEL1) that are known to be involved in telomere biology. Lead SNPs at two loci (TERC and TERT) associate with several cancers and other diseases, including idiopathic pulmonary fibrosis. Moreover, a genetic risk score analysis combining lead variants at all 7 loci in 22,233 coronary artery disease cases and 64,762 controls showed an association of the alleles associated with shorter LTL with increased risk of coronary artery disease (21% (95% confidence interval, 5-35%) per standard deviation in LTL, P = 0.014). Our findings support a causal role of telomere-length variation in some age-related diseases.

Dyslipidaemia, glucose intolerance and cardiovascular disease mortality and morbidity in Europeans and Asians

Dyslipidaemia, a major risk factor of cardiovascular disease (CVD), is prevalent not only in diabetic patients but also in individuals with impaired glucose tolerance (IGT) or impaired fasting glucose (IFG). The aims of this study were: 1) to investigate lipid levels in relation to glucose in European (Study I) and Asian (Study II) populations without a prior history of diabetes; 2) to study the ethnic difference in lipid profiles controlling for glucose levels (Study III); 3) to estimate the relative risk for cardiovascular mortality (Study IV) and morbidity (Study V) associated with dyslipidaemia in individuals with different glucose tolerance status. Data of 15 European cohorts with 19 476 subjects (I and III) and 13 Asian cohorts with 19 763 individuals (II and III) from 21 countries aged 25-89 years, without a prior history of diabetes at enrollment, representing Asian Indian, Chinese, European, Japanese and Mauritian Indian, were compared. The lipid-CVD relationship was studied in 14 European cohorts of 17 763 men and women which provided with follow-up data on vital status, with 871 CVD deaths occurred during the average 10-year follow-up (IV). The impact of dyslipidaemia on incidence of coronary heart disease (CHD) in persons with different glucose categories (V) was further evaluated in 6 European studies, with 9087 individuals free of CHD at baseline and 457 developed CHD during follow-up. Z-scores of each lipid component were used in the data analysis (I, II, IV and V) to reduce the differences in methodology between studies. Analyses of cardiovascular mortality and morbidity were performed using Cox proportional hazards regression analysis adjusting for potential confounding factors. Within each glucose category, fasting plasma glucose (FPG) levels were correlated with increasing levels of triglycerides (TG), total cholesterol (TC), TC to high-density lipoprotein (HDL) ratio and non-HDL cholesterol (non-HDL-C) (p<0.05 in most of the ethnic groups) and inversely associated with HDL-C (p<0.05 in some, but not all, of the populations). The association of lipids with 2-h plasma glucose (2hPG) followed a similar pattern as that for the FPG, except the stronger association of HDL-C with 2hPG. Compared with Central & Northern (C & N) Europeans, multivariable adjusted odd ratios (95% CIs) for having low HDL-C were 4.74 (4.19-5.37), 5.05 (3.88-6.56), 3.07 (2.15-4.40) and 2.37 (1.67-3.35) in Asian Indian men but 0.12 (0.09-0.16), 0.07 (0.04-0.13), 0.11 (0.07-0.20) and 0.16 (0.08-0.32) in Chinese men who had normoglycaemia, prediabetes, undiagnosed and diagnosed diabetes, respectively. Similar results were obtained for women. The prevalence of low HDL-C remained higher in Asian Indians than in others even in individuals with LDL-C < 3 mmol/l. Dyslipidaemia was associated with increased CVD mortality or CHD incidence in individuals with isolated fasting hyperglycaemia or IFG, but not in those with isolated post-load hyperglycaemia or IGT. In conclusion, hyperglycaemia is associated with adverse lipid profiles in Europeans and Asians without a prior history of diabetes. There are distinct patterns of lipid profiles associated with ethnicity regardless of the glucose levels, suggesting that ethnic-specific strategies and guidelines on risk assessment and prevention of CVD are required. Dyslipidaemia predicts CVD in either diabetic or non-diabetic individuals defined based on the fasting glucose criteria, but not on the 2-hour criteria. The findings may imply considering different management strategies in people with fasting or post-load hyperglycaemia.

Using genomic data to make indirect (and unauthorized) estimates of disease risk

The number of genetic factors associated with common human traits and disease is increasing rapidly, and the general public is utilizing affordable, direct-to-consumer genetic tests. The results of these tests are often in the public domain. A combination of factors has increased the potential for the indirect estimation of an individual's risk for a particular trait. Here we explain the basic principals underlying risk estimation which allowed us to test the ability to make an indirect risk estimation from genetic data by imputing Dr. James Watson's redacted apolipoprotein E gene (APOE) information. The principles underlying risk prediction from genetic data have been well known and applied for many decades, however, the recent increase in genomic knowledge, and advances in mathematical and statistical techniques and computational power, make it relatively easy to make an accurate but indirect estimation of risk. There is a current hazard for indirect risk estimation that is relevant not only to the subject but also to individuals related to the subject; this risk will likely increase as more detailed genomic data and better computational tools become available.