A Multi-national Trial To Predict Treatment Response In Subtypes Of Depression
Funder
National Health and Medical Research Council
Funding Amount
$387,489.00
Summary
Treatment of MDD using trial and error can have serious consequences. It can prolong the patient’s suffering (depression is associated with substantial morbidity, and mortality), prolong their absence from work and other productive activity and increase the burden on their family-carers. This multi-national study will collect genetics, brain function and behavioural data from a large number of participants, allowing for sensitive predictors of response to be determined.
Predictors Of Response To Antidepressants: Utility Of Behavioural, Neuroimaging And Genetics Data
Funder
National Health and Medical Research Council
Funding Amount
$310,071.00
Summary
Major depressive disorder (MDD) is projected to cause the second greatest global burden of disease by 2020, highlighting the urgent need for valid predictors of effective treatment response. Currently, there are no accurate predictors of response to antidepressants in MDD, and successful treatment relies greatly on 'trial and error'. This process is demanding on health resources, and may be a factor in the high suicide rates in depressed patients. Previous research on treatment response has been ....Major depressive disorder (MDD) is projected to cause the second greatest global burden of disease by 2020, highlighting the urgent need for valid predictors of effective treatment response. Currently, there are no accurate predictors of response to antidepressants in MDD, and successful treatment relies greatly on 'trial and error'. This process is demanding on health resources, and may be a factor in the high suicide rates in depressed patients. Previous research on treatment response has been limited by recruitment of small, heterogeneous patient samples, lack of placebo control, and a failure to examine task related activity in brain imaging studies. Perhaps one of the more troubling aspects of research that aims to predict treatment response to antidepressant medications is the use of commonly used outcome measures such as the Hamilton Rating Depression Scale (HAM-D), which were developed long before current classification systems of depression came into use. The US Federal Drug Administration has recently identified what they call a translational gap such that behavioural and biological measures are the most robust for detection of disorders such as depression, yet these measures remain to be translated into clinical tools that can be used to evaluate treatment. The aim of the current study therefore is to determine whether genetic variability is related to treatment outcome as defined by a more objective outcome measure (facial expression perception) using a randomised controlled design. The study will also determine whether brain measures (fMRI, EEG) enhance the prediction of SSRI response to both clinical and behavioural measures, over and above the genetic contribution.Read moreRead less
Increased Vulnerability To Stress During Opiate Dependence: Molecular, Anatomical, And Behavioural Correlates
Funder
National Health and Medical Research Council
Funding Amount
$272,640.00
Summary
Heroin addiction is a major health and societal problem in Australia. It is consistently associated with an adverse impact upon individual users, their families, and communities. It is a chronically relapsing condition for which few, if any effective prevention and treatment strategies exist. Moreover, why an individual initiates and maintains heroin taking remains unclear. Stress and negative emotions have a strong impact on heroin use. Stress may drive some individuals to start using heroin, s ....Heroin addiction is a major health and societal problem in Australia. It is consistently associated with an adverse impact upon individual users, their families, and communities. It is a chronically relapsing condition for which few, if any effective prevention and treatment strategies exist. Moreover, why an individual initiates and maintains heroin taking remains unclear. Stress and negative emotions have a strong impact on heroin use. Stress may drive some individuals to start using heroin, stress increases the pleasurable effects of heroin and stress increases the aversive effects of heroin withdrawal. These effects will encourage addiction and discourage addicts from seeking treatment. Stress can also cause an otherwise drug-free individual to relapse to heroin addiction despite having been drug-free for some time. In this project we will study why stress has such a large impact on heroin addicts and heroin addiction. We will test the hypothesis that heroin use actually produces profound alterations in the neural network in the brain which controls responses to stress. This project uses a simple animal model of heroin addiction whereby rats are injected with morphine to study the regulation of several genes which are important in responding to stress. We will also study how this exposure and changes in gene expression alter neurobiological, cardiovascular, and behavioural responses to stress. This project will identify parts of the brain that are altered during heroin addiction, and will also identify why heroin addicts are more vulnerable to stress than the general population. Therefore, this project will help us to identify targets for therapeutic intervention (both psychological and pharmacological) and possibly disrupt the addictive cycle.Read moreRead less
Brain Connectivity Imaging Markers To Confirm Diagnosis For Bipolar Vs. Unipolar Depression – A Connectome Approach.
Funder
National Health and Medical Research Council
Funding Amount
$434,369.00
Summary
Differentiating Bipolar disorders from Unipolar Depression is a major clinical challenge. This misdiagnosis hinders optimal clinical care and has many deleterious consequences such self-harm, increased chances of suicide, poor prognosis, and greater health care costs related to this disorder. This project will provide urgently-needed advance in accurate identification of Bipolar disorders using Magnetic Resonance Imaging and remove one of the key obstacles to accurate diagnosis.
Sudden Cardiac Arrest: Improving Detection Of Patients At Risk
Funder
National Health and Medical Research Council
Funding Amount
$838,845.00
Summary
Sudden cardiac death accounts for ~10% of deaths in our community. Many of these deaths occur in people who could otherwise have had many more years of productive life ahead of them. The aim of our research is to determine the underlying mechanisms so that we can develop better tools for detecting underlying problems before they become life threatening and potentially develop new treatments to modify the underlying causes.
Developmental Schizotypy In The General Population: Early Risk Factors And Predictive Utility.
Funder
National Health and Medical Research Council
Funding Amount
$830,952.00
Summary
This study will determine early childhood risk factors for psychosis-proneness in children aged 11 years, and emerging signs and symptoms of mental health disorders of these children, using population data from the NSW Child Development Study. Determining risk for psychosis as early as possible in the life course will enable the provision of preventative interventions to children at critical points in development.
The Biology Of Risk For Bipolar Disorder: Genetic Effects In A High-risk Longitudinal Study
Funder
National Health and Medical Research Council
Funding Amount
$856,412.00
Summary
Bipolar disorder is a severe mood disorder affecting over 350,000 Australians. Some children of bipolar disorder patients will also become ill, although currently we have no tools to predict which of these genetically at-risk young individuals will eventually develop symptoms. This study will use genetic information plus brain structural changes to predict which at-risk individuals are likely to become ill. This study will help elucidate early clinical and biological markers of bipolar disorder.
Improved seasonal rainfall prediction for grain growers using farm level data and novel modelling. Successful grain production, a key export commodity for Australia, depends heavily on reliable seasonal forecasts. However, the highly variable climate means that for Australia’s 25,000 grain growers current forecasts lack detail in space and time. Using a combination of fuzzy classification and artificial neural networks, this project will develop a locally detailed continuously updating data-driv ....Improved seasonal rainfall prediction for grain growers using farm level data and novel modelling. Successful grain production, a key export commodity for Australia, depends heavily on reliable seasonal forecasts. However, the highly variable climate means that for Australia’s 25,000 grain growers current forecasts lack detail in space and time. Using a combination of fuzzy classification and artificial neural networks, this project will develop a locally detailed continuously updating data-driven seasonal forecast system using high density climate data from the 17,000 Grain Growers Association members and climate drivers such as sea surface temperature from the Bureau of Meteorology. After validation against observed data, the forecasts will be delivered via a web-based portal to users.Read moreRead less
Neuronal Substrate Of Choice In The Rat Whisker System
Funder
National Health and Medical Research Council
Funding Amount
$405,851.00
Summary
Humans and other animals can optimise their goal-directed behaviour by linking stimuli or actions to consequent positive and negative rewards. How does an animal generate such associations, and make decisions in the natural environment where the associations are often uncertain, at times contradictory, and continuously changing? This project uses rat whisker system as an animal model to identify the neuronal basis of perceptual decision making and the role of context.