Poster Presentations

Session Title: Alzheimer's Disease (AD) including Non-Cognitive Aspects
Presentation Date: Friday, March 14 – Saturday, March 15, 2009

THE AIBL STUDY: BASELINE DATA FROM A MULTI-CENTRE, PROSPECTIVE LONGITUDINAL STUDY OF AGEING IN 1100 VOLUNTEERS

K. Ellis¹, C. Rowe², C. Masters³, R. Martins⁴, P. Hudson⁵, A. Milner⁵, L. Bevege⁵, D. Ames^6
1University of Melbourne, Melbourne, Australia, ²Austin Health, Melbourne, Australia, ³Mental Health Research Institute and & Centre for Neurosciences, University of Melbourne, Melbourne, Australia, ⁴Edith Cowan University, Perth, Australia, ⁵Neurosciences Australia, Melbourne, Australia, ⁶National Ageing Research Institute, Melbourne, Australia

The Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing (AIBL) is a three-year prospective longitudinal study of 1,102 volunteers from a cross-section of Australia's elderly population. The cohort comprises 1102 volunteers aged over 60 years [211 patients with AD (mean age 78.4 ±8.53 years), 125 patients with MCI (mean age 76.3 ±7.33 years), and 766 healthy volunteers (HV; 70.5 ±7.03 years)]. At baseline, volunteers completed lifestyle questionnaires and underwent comprehensive clinical and neuropsychology assessment. An 80ml blood sample was provided for clinical pathology, biomarker analysis, and storage in liquid nitrogen. 265 participants received a [C-11] PIB-PET scan (a measure of in vivo amyloid) and a MRI scan. AD patients performed worse on all neuropsychological measures compared to both HV and MCI groups, and MCI patients showed greater impairment than HVs (all p< 0.05). Neuroimaging subgroup results revealed a significant difference between groups in the PiB +ve volunteers (98% of AD patients, 64% of MCI patients and 29% of HVs). HVs with an apolipoprotein-E (ApoE) ε4 allele were significantly more likely to be PiB+ve than ApoE ε4 negative HVs (49% compared to 21%, respectively). Cross sectional analysis of baseline data will reveal links between cognition, brain amyloid burden, structural brain changes, biomarkers, and lifestyle. An 18-month follow-up will reveal risk factors associated with cognitive decline and identify early diagnostic indicators of AD. These findings will assist development of techniques to identify factors which may delay onset of AD, and provide a cohort suitable for early intervention studies.