Developing And Applying Biologically Plausible Statistical Models For Normal And Non-normal Family Data
Funder
National Health and Medical Research Council
Funding Amount
$339,700.00
Summary
Although molecular and computing advances have enabled more detailed investigations of inherited diseases and the ability to fit realistic statistical models to these data, limitations still exist when analysing family data. Often only basic statistical analyses are performed, due to the lack of understanding of complexities within the data and-or inability of researchers to fit appropriate statistical models. These factors have hampered the search for genes and environmental factors influencing ....Although molecular and computing advances have enabled more detailed investigations of inherited diseases and the ability to fit realistic statistical models to these data, limitations still exist when analysing family data. Often only basic statistical analyses are performed, due to the lack of understanding of complexities within the data and-or inability of researchers to fit appropriate statistical models. These factors have hampered the search for genes and environmental factors influencing common diseases. This project aims to develop novel, biologically realistic statistical models for investigation of common, complex diseases, such as heart disease and cancer, in families. These models will incorporate both measured and unmeasured genetic and environmental factors, and will be applicable to both normally distributed and non-normally distributed traits. Model fitting will use computer-intensive simulation techniques. Application of the models to data from two large pre-existing studies of international renown, the Victorian Family Heart Study and the Australian Prostate Cancer Family Study, will enable a better understanding of the genetic and environmental factors influencing heart disease and cancer. The models will also be applicable to many other studies of diseases which use data from families, and allow more accurate and useful information to be obtained from data. Software will also be made freely available to other researchers. This will ultimately translate into better outcomes from familial genetic research, and eventually, better prevention, detection, and treatment of the diseases.Read moreRead less
Action-reward Integration In The Amygdalocortical-striatal Network.
Funder
National Health and Medical Research Council
Funding Amount
$757,495.00
Summary
This research focuses on the neural bases of decision making, a general capacity affected by normal ageing, disorders associated with neurodegeneration, major psychiatric conditions, obesity and drug addiction. This program will contribute critical new knowledge on the brain systems through which cognitive and emotional processes are integrated to control choice and decision-making and the influence of neuropathology on this integrative process.
Resistant forms of childhood acute lymphoblastic leukaemia (ALL) constitute a leading cause of cancer-related deaths in children. Despite tremendous improvements in therapy, 25-30% of patients still experience a relapse and many of them occur in patients stratified as low risk. Further treatment is often toxic, frequently unsuccessful and carries the risk of significant long-term morbidity. For the design of more appropriate therapy, information on the biology of relapsed ALL is urgently require ....Resistant forms of childhood acute lymphoblastic leukaemia (ALL) constitute a leading cause of cancer-related deaths in children. Despite tremendous improvements in therapy, 25-30% of patients still experience a relapse and many of them occur in patients stratified as low risk. Further treatment is often toxic, frequently unsuccessful and carries the risk of significant long-term morbidity. For the design of more appropriate therapy, information on the biology of relapsed ALL is urgently required. The sequencing of the human genome and advanced screening technology (microarrays) allow the detailed analysis of expression patterns in large numbers of specimens. We propose to study the genetic features of this disease by investigating 28 childhood ALL patients from whom we have stored specimens received at two time points, one at diagnosis and one at relapse. The hypothesis of this study is that relapsed leukaemias display genetic features which are correlated to their resistance to therapy. The specific questions we will be asking are: (1) Which genes are expressed at high levels in leukaemia specimens at the time of relapse while not expressed (or expressed at lower levels) at the time of diagnosis and vice versa? (2) What is the function of differentially expressed genes? (3) Is the pattern of gene expression correlated with resistance to the particular drug therapy used? (4) Is the leukaemia clone at relapse related or unrelated to the clone present at diagnosis, as determined by receptor rearrangement? The expression levels of identified discriminator genes will be confirmed by real-time quantitative polymerase chain reaction (PCR). The quality of this set of specimens makes them particularly suited to achieve the stated goals, providing a unique opportunity to investigate drug resistance in childhood ALL. The data generated will provide the basis for the examination of genes suitable as new therapeutic targets.Read moreRead less
Novel Statistical Methods For Genetic Epidemiology
Funder
National Health and Medical Research Council
Funding Amount
$481,505.00
Summary
We are in the midst of a genomics revolution that is transforming epidemiology, medicine and drug discovery. However, the scarcity of sophisticated statistical techniques to deal with the complicated problems inherent in genetic investigations of complex diseases is currently the critical factor limiting the success of human gene discovery programs. Statistical genetic methodology is currently one of the fastest developing areas of epidemiology. In information-intensive' areas such as genetic ep ....We are in the midst of a genomics revolution that is transforming epidemiology, medicine and drug discovery. However, the scarcity of sophisticated statistical techniques to deal with the complicated problems inherent in genetic investigations of complex diseases is currently the critical factor limiting the success of human gene discovery programs. Statistical genetic methodology is currently one of the fastest developing areas of epidemiology. In information-intensive' areas such as genetic epidemiology, genomics, and proteomics, there is a high demand for data analysis and statistical skills. WA has some world class expertise in statistical science, both in academia and in industry. However, this expertise has not yet been applied in a system way to genetic data analysis. We propose to undertake advanced methodological research in statistical genetics and bioinformatics, to produce easy-to-use and accessible software tools and resources that allow methodological advances to be accessed by the Australian research community, and to apply our new methods and tools both to specific disease research and to the developing human genome epidemiology (HuGE) enterprise in WA. These new initiatives in methodological research will draw together a number of currently separate research strands and will provide new tools and resources that will allow applied Australian programs to improve the efficiency of their research into the causes of important. Methodological development in both bioinformatics and statistical genetics are recognized international areas of need.Read moreRead less