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Alzheimer’s disease (AD) is a neurodegenerative disorder characterised by the progressive loss of cognitive function resulting in dementia. In Australia, 1 in 10 people above the age of 65 will develop the disease. In 2012, the Australian Government recognised dementia as a national health priority area. Mild cognitive impairment (MCI) characterises an intermediate stage between the expected cognitive decline of normal ageing and the more serious decline of dementia. People with MCI are at increased risk of developing AD.

There is currently no cure for AD and treatment options to halt or slow progression are limited. A key factor in the development and implementation of such therapies will be the early identification of affected individuals or of individuals likely to become affected.

Lipid metabolism is tightly coupled to the onset and progression of MCI and AD although the details of this are poorly defined. A number of studies have identified lipids as putative biomarkers of AD risk [1–4]. However, studies to date have been limited both in terms of the coverage of the lipidome and the cohort size and suitability to identify and validate lipid biomarkers or to define the relationship between lipid metabolism, cognition and dementia.

We have performed one of the largest lipidomic studies of AD to date measuring 593 lipid species in almost 5000 samples. These represent five time points from around 1000 participants in the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study of Ageing cohort. We have identified 174 lipid species associated with AD and 47 lipid species associated with progression to AD (from healthy control (HC) or MCI status). We have developed a lipid signature (8 lipid species) that provides improved prediction (above traditional risk factors such as age, gender, BMI and cholesterol with an improvement in the AUC of 0.095 to 0.857, a categorical net reclassification index  (NRI) of 17 per cent and a continuous NRI of 85 per cent.

These findings promise to provide improved understanding of the role of lipids in disease pathogenesis as well as a clinically useful screen to predict who is at greatest risk of developing AD and when. However, to realise these outcomes we need to define the intracellular lipid metabolism associated with AD, and also validate our findings on independent cohorts.

We hypothesise that:

  1. Lipidomic analysis of platelets from the AIBL study will provide details of the intracellular lipid metabolism associated with AD.
  2. Analysis of independent cohorts will validate our findings and quantify the predictive ability of these new lipidomic biomarkers to provide risk assessment and early diagnosis of AD.

We have three specific aims:

  1. To analyse the AIBL lipidomic dataset, and use the data to refine our predictive models.
  2. To conduct lipidomic analysis of the platelet samples from the AIBL cohort.
  3. To validate our lipidomic biomarkers and profiles on three independent cohorts.

These studies will provide a detailed lipidomic analysis of the relationship with cognition, MCI and AD. The refinement and validation of our existing lipidomic biomarkers will enable early identification of those individuals at greatest risk and will be an important part of the solution to the growing dementia epidemic.

Importantly, understanding the complex relationships between lipid metabolism and dementia may provide us with new therapeutic targets for early intervention to halt the onset and progression of this devastating disease.  


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