Inherited Genetic Variants As Prognostic Markers For Colorectal Cancer
Funder
National Health and Medical Research Council
Funding Amount
$623,972.00
Summary
Bowel cancer is a major health burden. Surgical resection of the primary cancer is often possible at diagnosis, yet in many patients the cancer will recur. Together with mutations, inherited genetic variants influence the rate of bowel cancer growth. This study aims to identify inherited variants predictive of cancer recurrence. Improved prediction of recurrence will permit more targeted use of clinical interventions, tailored to the individual patient, ultimately improving patient survival.
Translation Of Glaucoma Blindness Genes To Improve Clinical Practice
Funder
National Health and Medical Research Council
Funding Amount
$856,795.00
Summary
Glaucoma is a common cause of irreversible blindness. It is currently difficult to predict which patients with the earliest signs of glaucoma will develop blinding stages of the disease. This study will investigate how genes and eye measurements can be used to predict the risk of developing severe glaucoma in people with early signs of disease. This will ensure that high risk individuals can access treatment early, while those at low risk can be spared unnecessary treatment and seen less often.
Identification And Function Of Genes That Increase Risk For Endometriosis
Funder
National Health and Medical Research Council
Funding Amount
$1,180,912.00
Summary
Endometriosis is a common disease that affects 7% of reproductive age women in Australia, resulting in pelvic pain, subfertility and painful periods. We have undertaken genetic studies that identified a number of candidate genes that show strong evidence for increasing a woman’s risk of having endometriosis. We now seek funding to investigate the functional roles that these endometriosis susceptibility genes play within the uterus, with the goal of identifying new treatments for endometriosis.
Gene Tests For Predicting Risk Of Developing Glaucoma
Funder
National Health and Medical Research Council
Funding Amount
$956,020.00
Summary
Glaucoma is a common cause of blindness. It is currently difficult to predict which patients with the earliest signs of glaucoma will go on to develop the blinding stages of the disease. This study will investigate how genes and othe eye measurements can be used to predict risk of developing glaucoma in people with early signs of disease.
Exploring The Role Of MiRSNPs In Diagnosis And Prognosis Of Prostate Cancer
Funder
National Health and Medical Research Council
Funding Amount
$428,065.00
Summary
Genetic variants, when used alongside PSA and family history, could be a better early biomarker to identify men predisposable to develop prostate cancer or/and to distinguish slowly progressive from aggressive disease. We will undertake a comprehensive study on a special class of genetic variants "miRSNPs" in the non-coding region of the prostate cancer related genes and will also identify their mechanism of action, and their potential as a biomarker for prostate cancer diagnosis and prognosis.
Clinical And Genetic Modifiers In The Progression To Cirrhosis In Hemochromatosis
Funder
National Health and Medical Research Council
Funding Amount
$68,539.00
Summary
Haemochromatosis is a disease related to a common genetic abnormality leading to progressive iron accumulation in tissues with the potential for liver fibrosis and eventually scarring of the liver. It has been noted that not all patients with haemochromatosis develop scarring of the liver and it is possible that this variation could be due to differences in lifestyle or health factors or alternatively due to genetic variability between patients. The study aims to investigate this further.
Activation Of TERT Gene Expression In Breast Carcinogenesis
Funder
National Health and Medical Research Council
Funding Amount
$693,440.00
Summary
A key step in the development of most cancers is the switching on of an enzyme, telomerase, that allows cancer cells to keep growing without limit. We will study the molecular details of this step using new techniques for functional analyses of the genome in human breast cells grown in the laboratory. Blocking telomerase has great potential for cancer treatment, so analysing how this enzyme gets switched on may identify new strategies for achieving this for breast cancer - and other cancers.
Advanced Whole-genome Approaches For Causative Variant Detection And Individual Risk Prediction Of Complex Traits In Human Populations.
Funder
National Health and Medical Research Council
Funding Amount
$356,014.00
Summary
The genomics era has demonstrated the true complexity of complex genetic traits, but brings promise for personalised genomic medicine in which diagnosis and treatment are tailored to individuals based on profiles recorded in their genome. This project aims to develop advanced statistical methods to better detect causative variants and to better predict an individual’s risk of disease. Our methods may lead to predictions of risk of disease for individuals that have clinical utility.
Development And Application Of Novel Bioinformatics Approaches To Identify Pathogenetic Mechanisms Underlying Migraine
Funder
National Health and Medical Research Council
Funding Amount
$320,891.00
Summary
Migraine is a public health problem. Although GWAS lead to robust findings, the mechanisms and therapeutic strategies are unknown. This is caused by limited sample size hampering obtaining large number of SNPs by GWAS. Integrating priori knowledge with bioinformatics studies is promising to discover hidden SNPs. Here, I will develop a novel approach to find novel genetic risk loci and genes by integrating comprehensive knowledge on SNPs and genes with GWAS instead of increasing sample.
Risk prediction models incorporating multiple risk factors (including genetic markers) are a recognised method to identify individuals at high risk of developing breast or colorectal cancer, but it is uncertain which model(s) currently perform best in a population setting. We aim to compare the predictive ability of each available model. Knowing which model performs best will facilitate early diagnosis, reduce overall costs by better targeting interventions and improve cancer survival.