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O2‐02‐03: The prognostic value of different subtypes of mild cognitive impairment (MCI) and their association to CSF and genetic markers in the prospective cohort study descripa
Author(s) -
Damian Marinella,
Visser Pieter Jelle,
Froelich Lutz
Publication year - 2010
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2010.05.308
Subject(s) - dementia , cognition , cluster (spacecraft) , psychology , prospective memory , cognitive impairment , medicine , cohort , psychomotor learning , effects of sleep deprivation on cognitive performance , prospective cohort study , executive functions , episodic memory , audiology , psychiatry , disease , computer science , programming language
classes of biomarkers to predict time to progression. 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 normalized by total intracranial volume (HF/TIV) was measured from FreeSurfer. We used a new method of combining CSF Ab42 and PIB PET measures to produce equivalent measures of Ab amyloid deposition from either biomarker source. Measures of brain Ab amyloid were expressed in the cortical to cerebellar ratio units typically used to measure PIB PET retention and are referred to as ‘‘Ab amyloid load’’ whether derived from CSF Ab42 or actual PIB PET. ‘‘Ab amyloid load’’ was ascertained by CSF in 165 and by PIB PET imaging in 53 subjects. Results: Over a median progression-free follow up time of 1.7 years, 86 subjects converted from MCI to AD. The overall HR for predicting progression was 2.5 for Ab amyloid load (Fig 1) and 2.4 for HF/TIV (Fig 2). The relationship between hazard of progressing and increasingly abnormal HF/TIV was linear. In contrast there was some evidence of non linearity in this relationship for Ab amyloid load such that a ceiling was reached in the relative hazard as Ab amyloid load exceeded a value of approximately 2.0. MRI and Ab amyloid load both remained significant in models that included both biomarkers as predictors. Conclusions: Biomarkers of neurodegeneration (i.e. atrophy on MRI) and brain Ab amyloid deposition predict conversion from MCI to AD independently and also provide complimentary predictive information. However, the relationships between the hazard of progressing and increasingly abnormal values in these two classes of biomarkers differs in a manner suggesting that the hazard of progressing is more immediately related to brain atrophy than to brain Ab amyloid at the upper end of the biomarker severity range.