. Brain Aβ amyloid measures and MRI are complimentary predictors of progression from MCI to AD. Human Amyloid Imaging 2010 Meeting Abstracts. 2010 April 9;

Abstract:

Introduction: Biomarkers of brain Aβ amyloid deposition, measured either by CSF or PIB PET imaging, are significant predictors of future progression from MCI to AD, as are MRI measures of brain atrophy. Our objective was to compare these two classes of biomarkers to predict time to progression and evaluate their effect on the hazard of progressing.

Methods: A total of 218 MCI subjects were identified from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). The primary outcome was time to conversion from a diagnosis of MCI to AD. Hippocampal volume was measured from FreeSurfer and adjusted for total intracranial volume. We used a new method of converting CSF Aβ42 into PIB PET units and combining CSF and PIB PET imaging data to produce equivalent measures of “brain Aβ amyloid load” from either biomarker source.

Results: Over a median progression-free follow-up time of 1.7 years, 86 subjects progressed from MCI to AD. The overall hazard ratio [(HR); 95% CI] for progression based on comparing the upper vs the lower quartiles was 2.5 (1.4 to 4.3) for Aβ amyloid load and 2.6 (1.9 to 3.6) for comparing the lower to the upper quartile for hippocampal volume. The relationship between hazard of progressing and increasingly abnormal hippocampal volume (functional form) was linear. In contrast, there was evidence of non-linearity for Aβ amyloid load in the form of a plateau in terms of risk. MRI and Aβ amyloid load remained significant in models that included both biomarkers as predictors.

Conclusions: Biomarkers of neurodegeneration (i.e. atrophy on MRI) and brain Aβ amyloid deposition predict conversion from MCI to AD independently and also provide complimentary predictive information. However, the functional form of these two classes of biomarkers differs such that at some point additional amyloid load does not confer additional risk.

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  1. Toronto: HAI Amyloid Imaging Conference Abstracts