Thank you for visiting our Virtual Hall. Please take a moment to view the below presentations. These presentations are from our researchers whose presentation were not premiered during our Community Conference. 

Brendan Tan

Longitudinal Mapping of Cortical Morphometry Changes in Huntington’s Disease

This study investigated cortical folding in Huntington’s disease to understand how disease progression impacts the surface of the cortex. Cortical morphometry changes in two brain regions of interest, the lateral occipital and precentral gyri, were examined. We used existing neuroimaging data from IMAGE-HD, comprising 26 pre-symptomatic, 26 symptomatic and 24 healthy control individuals at three separate time points (baseline, 18-month, 30-month) and found significantly reduced cortical folding and thickness between groups in both hemispheres of the lateral occipital and precentral regions. We also found a Group by Time interaction for Local gyrification index in the right hemisphere lateral occipital region. Additionally, lower local gyrification index and cortical thickness were associated with higher disease burden score. These findings demonstrate that significant longitudinal decline in right hemisphere local gyrification index is evident during manifest disease in lateral occipital cortex and that these changes are more profound in individuals with greater disease burden score.


Cory Wasser

Gut imbalance in Huntington’s disease: associations among gut microbiota, neuropsychological outcomes, and clinical indicators of disease progression

 Emerging evidence links the gut-brain axis to neurodegenerative diseases. We investigated the environment within the gut (microbiome) in 43 people with Huntington’s disease (HD) and 37 people without HD. Participants provided faecal samples and completed cognitive, mood and gut questionnaires, and took probiotic or placebo capsules for six weeks. We report the first evidence of an altered gut microbiome in people with HD. We found that in HD, that the gut was less rich and with different structure compared to people without HD. Certain gut bacteria was also related to HD clinical symptoms (motor signs and thinking skills) as well as estimated disease progression. Probiotics did not alter constitution of the gut microbiome or HD symptoms. Overall, we provide the first evidence that the gut is affected in HD, with links between gut bacteria and HD clinical outcomes. These results highlight the importance of gut biomarkers and the prospect of future therapeutic interventions targeting the gut in HD.

Link to published paper:

Brendan McLaren

Less physical activity and more time in bed found to associate with poorer cognitive performance in HD

Healthy sleep and physical activity habits benefit cognitive (thinking skills) performance in the general population and in Parkinson’s and Alzheimer’s disease. However, the relationship between sleep, physical activity and cognition in Huntington’s disease is poorly understood. The aim of this project was to begin to better understand how sleep and physical activity habits relate to cognitive performance in HD. Forty-two participants (20 diagnosed with HD and 22 pre-diagnosis) wore Fitbit One sleep and activity monitors and completed questionnaires and cognitive tasks on their smartphones for one week. We found that participants who were less physically active and those that spent more time in bed trying to sleep at night during the week had poorer cognitive functioning at the end of the week. Now we have evidence that physical activity and time spent in bed trying to sleep have important relationships with cognitive functioning in HD, we can now conduct interventions to see if improving the sleep and physical activity habits of people with HD can help them to improve their cognitive performance and functioning.

Pubuditha Abeyasinghe

Statistical Modelling to Track HD Progression

In my brief presentation, I will highlight some of the work I am doing as a postdoctoral research fellow at Monash University. My work in Huntington’s Disease is focused on mathematical/statistical modeling of the disease progression leading towards finding a better stratification method of symptom profiles. I will summarize the results of my initial work where we combined three big data sets in HD and explain the possible implications of those to future clinical trials.