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
Dissecting Genetic Variation For Human Complex Diseases And Traits
Funder
National Health and Medical Research Council
Funding Amount
$135,821.00
Summary
Understanding the pattern of inheritance for human common diseases such as cancers, obesity, diabetes and mental illness, is of key importance for disease diagnosis, treatment and prevention. In this project, we will develop statistical methods and software tools to analyse DNA and clinical data to better understand the genetic basis of human common diseases and to predict a person�s risk of developing disease.
Investigating The Interplay Of Gene And Environment In Childhood And Adolescent Mental Health
Funder
National Health and Medical Research Council
Funding Amount
$386,298.00
Summary
Mental health and substance use disorders account for 60-70% of the overall disease burden among young Australians. This research aims to fully explore the gene-environment interplay in childhood and adolescent mental health. The potential outcomes of this research include: improved understanding of genetic and environmental architecture for single disorder, and the high comorbidity between disorders; guidance for personalised intervention based on one’s genetic background.
Development And Evaluation Of Statistical Methods And Software For Analysis Of Complex Genetic Disease Data
Funder
National Health and Medical Research Council
Funding Amount
$1,250,371.00
Summary
What are the major factors underpinning complex genetic diseases like diabetes, bipolar disorder or cancer? To answer this question new tools are needed, including software for mining the human genome with interactions between the genome and environment being incorporated. This is our focus. It will form the basis of a superior understanding of the overall process leading to disease and hence better predictions with important ramifications for new treatments and health care planning.
Many recent gene mapping efforts have focused on population based approaches instead of previously used family based approaches. One of the limiting factors with population based approaches is the cost of the technology - each participant must be evaluated (or genotyped) for hundreds of thousands of genetic markers. The cost can be reduced by using an approach which pools individuals together for genotyping, with statistical models used to deal with the problems that this creates.
Finding The Genetic Causes Of Asthma: The Australian Asthma Genetics Consortium (AAGC)
Funder
National Health and Medical Research Council
Funding Amount
$1,697,639.00
Summary
Asthma is a major burden on individuals and health systems. Despite many decades of research, no major effective new treatments for asthma have emerged recently. We will establish a large international consortium to systematically test nearly all known human genes to identify those that influence asthma susceptibility. We expect to identify pathways not previously implicated in asthma and so lead to a potential breakthrough in the development of more effective treatments.
Mapping EQTL To Dissect The Genetic Basis Of Complex Trait Variation
Funder
National Health and Medical Research Council
Funding Amount
$719,525.00
Summary
People vary in traits such as height and blood pressure and in their susceptibility to common disease. Part of these differences between individuals is because of their genetic make-up. This research is about understanding which of the genes are involved in common variation and how they work. In particular, the researchers investigate if variation in DNA sequence causes genes to be expressed more or less and how gene expression affects risk of disease.
I am a clinical researcher determining: a) the role of altered airway structure, particularly airway smooth muscle and extracellular matrix, in asthma and COPD; and b) the prevalence of, and risk factors for, respiratory disease in general populations.