Subregional neuroanatomical change as a biomarker for Alzheimer's disease

Authors:
  • TIThe Alzheimer'S Disease Neuroimaging Initiative
    The Alzheimer'S Disease Neuroimaging Initiative
  • MWMichael Weiner
    Michael Weiner
  • LTLeon Thal
    Leon Thal
  • RPRonald Petersen
    Ronald Petersen
  • CJClifford R. Jack
    Clifford R. Jack
  • WJWilliam Jagust
    William Jagust
  • JTJohn Trojanowki
    John Trojanowki
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Abstract
Regions of the temporal and parietal lobes are particularly damaged in Alzheimer's disease (AD), and this leads to a predictable pattern of brain atrophy. In vivo quantification of subregional atrophy, such as changes in cortical thickness or structure volume, could lead to improved diagnosis and better assessment of the neuroprotective effects of a therapy. Toward this end, we have developed a fast and robust method for accurately quantifying cerebral structural changes in several cortical and subcortical regions using serial MRI scans. In 169 healthy controls, 299 subjects with mild cognitive impairment (MCI), and 129 subjects with AD, we measured rates of subregional cerebral volume change for each cohort and performed power calculations to identify regions that would provide the most sensitive outcome measures in clinical trials of disease-modifying agents. Consistent with regional specificity of AD, temporal-lobe cortical regions showed the greatest disease-related changes and significantly outperformed any of the clinical or cognitive measures examined for both AD and MCI. Global measures of change in brain structure, including whole-brain and ventricular volumes, were also elevated in AD and MCI, but were less salient when compared to changes in normal subjects. Therefore, these biomarkers are less powerful for quantifying disease-modifying effects of compounds that target AD pathology. The findings indicate that regional temporal lobe cortical changes would have great utility as outcome measures in clinical trials and may also have utility in clinical practice for aiding early diagnosis of neurodegenerative disease.

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