Neurogenetics and Dementia

The Neurogenetics and Dementia Lab uses genetics to understand disease processes, identify biomarkers and provide access to therapies for dementia.

Dementia is the second leading cause of death for all Australians. Alzheimer’s disease is the most common form of dementia, predicted to affect 152M globally by 2050. Common late onset Alzheimer’s disease is caused by age-related failure of clearance of toxic proteins (β-amyloid and tau) from the brain leading to an immune response. Successful treatment or prevention relies on the ability to identify those at high risk or the earliest disease stages.

The Neurogenetics and Dementia Lab run one of the largest cohort studies in the world focused on those at high risk and in the earliest disease stages of Alzheimer’s disease, for the identification of affordable, accessible and scalable biomarkers for dementia diagnosis and screening, to be prepared for the best use of newly developed drugs and lifestyle interventions as they become available.

In addition the Neurogenetics and Dementia Lab carry out large scale genetic studies, including the use of genetic risk prediction and the identification of causal disease processes in Alzheimer’s disease and dementia.

CURRENT RESEARCH

  • PISA (the Prospective Imaging Study of Aging: Genes, Brain and Behaviour)

PISA is a longitudinal cohort of middle-aged and older Australians aged 40-80 years. PISA is pioneering the use of genetic risk prediction in participant recruitment, aiming to identify high-risk participants to discover biological markers of early neuropathology, identify modifiable risk factors, and establish the very earliest phenotypic and neuronal signs of AD onset. In PISA Online, 4,900 participants have completed self-report surveys with >30 validated instruments including those related to memory and cognition, medical history, lifestyle, linkage to Medicare Benefit Scheme (MBS) and PBS records and online cognitive testing. In PISA Onsite, a subset of over 400 subjects genetically enriched for risk of AD have been assessed longitudinally (2yr follow-up). New baseline and follow-up assessments are continuing at QIMRB in Brisbane and sites in Newcastle and Melbourne.

  • Genetic risk Prediction for Alzheimer’s disease (AD)

We are working to improve testing and diagnosis for AD by determining the most accurate and clinically useful genetic profiles for identifying those at high risk of AD, predicting disease onset and progression, and response to treatment and interventions. Profiles of accessible biomarkers will be tested in combination including polygenic scores, cognitive testing, blood-based protein biomarkers, enabling the development of strategies for screening and the better targeting of treatment and interventions to improve health outcomes.

  • ADNeT (the Australian Dementia Network)
  • ADNeT is a network of leading scientists and researchers, working together to:

      1) establish the first dementia clinical quality registry to track, benchmark, and report on the clinical care of people with dementia;
      2) establish consistent best practice guidelines for the diagnosis and treatment of dementia; and
      3) facilitate the development of effective therapies by providing detailed dementia screening of patients suitable for participation in clinical trials

      We carry out Brisbane-based participant screening for ADNeT screening and trials, and work with the ADNeT volunteer registry, including carrying out blood and saliva sample collection and processing, genotyping and neuropsychological testing.

    • Genetic Epidemiology in Alzheimer’s disease and related traits
    • We carry out and contribute data to large scale genome-wide association studies (GWAS) meta analyses to identify genetic variants affecting mental health and ageing related traits.

      We also use large scale genetic data generated from GWAS to understand the relationships between diseases and traits and test causality. Understanding the causal relationships between diseases and traits is key in the design of treatments and interventions. Evidence from observational studies does not take into account whether a risk factor is independently causal and clinical trials are expensive, lengthy and not always possible. We use our large scale genetic datasets together with those that are publically available (such as published GWAS summary statistics and data from UK biobank) to carry out the latest methods in genetic epidemiology. This includes polygenic risk scores (PRS) analysis, pathway-specific genetic risk scores, the investigation of variation within co-expression networks, and Mendelian Randomization (MR) to understand causal relationships between potentially casual traits and AD.

Staff

  • Jessica Adsett, Project co-ordinator
  • Jonathan Flint, Visiting PhD Student
  • Kerrie McAloney, Project co-ordinator
  • Lina Gomez, Research data technician
  • Niklas Schultze, Research assistant
  • Yifan Sun, Research assistant

Internal Collaborators

External Collaborators

  • PISA (Prospective Imaging Study of Aging) study co-CIs across multiple institutions and disciplines including Michael Breakspear (University of Newcastle), Jurgen Fripp (CSIRO), and Gail Robinson (UQ).
  • Petroula Proitsi, Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University of London, UK, on AD Genetic Epidemiology.
  • QADS (Queensland Aging and Dementia Study; Imaging, Lifestyle, Genetics and Biomarkers) aiming to 1) support, consolidate and expand the Brisbane, Qld based healthy ageing and dementia cohorts; 2) Support a screening site in Brisbane, to provide more Queenslanders with access to the latest potential therapies through participation in trials; 3) Investigate and develop novel digital and diagnostic technologies. With co-CIs Jurgen Fripp (CSIRO), Elizabeth Coulson (UQ) and Robert Adams (UQ and RBWH).
  • Simon Laws, lead AIBL study researcher at the Edith Cowan University (ECU) genetics and epigenetics studies. I have recently been appointed Adjunct Associate Professor at Simon’s department at ECU to facilitate collaboration and future co-supervision of students.
  • Chris Fowler, lead AIBL study researcher at the Florey in Melbourne on blood-based biomarker studies, combining sample sets.
  • Nicolas Ashton, University of Gothenburg, Sweden on plasma protein biomarkers.
  • Paul Thompson and Neda Jahanshad, University of Southern California, USA, on analysis of neuroimaging and genetics data.
  • Allan McRae, Queensland Brain Institute, UQ on DNA methylation data analysis.
  • Wayne Leifert, CSIRO Adelaide, saliva sample collection in the PISA cohort for protein biomarker analysis.
  • Enedia Mioshi, University of East Anglia, UK, on caregiver burden analysis in the PISA study.
  • Adam Vogel, University of Melbourne and Chief Science Officer and Founder of Redenlab, speech acoustic analysis in the PISA study.
  • Perminder Sachdev and Karen Mather, at the University of New South Wales, to carry out joint analysis with the Older Australian Twin Study (OATS) and the Memory and Aging Study (MAS).
  • Member of world leading AD genetics consortia including GERAD, the UK-based Alzheimer’s GWAS consortium, the Alzheimer’s Exome Sequencing Group, and IGAP (International Genomics of Alzheimer’s Project), a worldwide GWAS Meta-analysis consortium, for which I implemented the joining of Australian cohorts. I have contributed genetic data to all the major large-scale genetic association studies for AD.
  • I work with international leaders in the field of psychiatric genetics and other complex traits, contributing to data world-leading genome-wide association studies.

We gratefully acknowledge the support of the following organisations and funding bodies:

  • MRFF-Dementia, Ageing and Aged Care Mission scheme grant CIC ($4,000,000) 2021-2026
  • NHMRC ideas grant (CIB) Optimising the therapeutic value of cholinesterase inhibitors in Alzheimer’s disease ($820,242)
  • Perpetual IMPACT Philanthropy Grant (81,000) 2022-2024