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P2‐244: Investigating Associations between APOE , CD33 with Measures of Alzheimer's Disease Severity Derived from Neuroimaging Data
Author(s) -
Casanova Ramon,
Hsu Fang-Chi,
Saldana Santiago,
Lutz Michael W.,
Kuchibhatla Maragatha,
Germain Cassandra M.,
Plassman Brenda L.,
Hayden Kathleen M.
Publication year - 2016
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.2016.06.1412
Subject(s) - apolipoprotein e , alzheimer's disease neuroimaging initiative , neuroimaging , allele , medicine , alzheimer's disease , psychology , disease , oncology , neuroscience , biology , genetics , gene
(BMI) is associated with reduced risk for future development of Alzheimer’s Diseases (AD), particularly in older subjects (Emmerzaal et al., 2015). Therefore, we sought to investigate how BMI in late middle aged and elderly subjects relates to regional cerebral metabolic rate of glucose (rCMRgl) and whether this relationship is influenced by the status of APOEε4 allele, a genetic risk for AD, or age. Methods: 197 cognitively healthy, non-diabetic subjects (59M/138F; age 61.066.3y; BMI 27.364.9kg*m), including homozygous (n1⁄440) and heterozygous (n1⁄458) carriers of the APOEε4 allele, underwent quantification of rCMRgl using 2-[F]-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography. Voxelwise multiple regression analyses across the whole brain and within specific regions of interest (ROI) including precuneus, posterior cingulate, parietal, temporal, prefrontal, and occipital brain regions were employed to investigate associations of BMI with rCMRgl and potential interactions with APOEε4 carrier status, age and gender. Furthermore, we applied the hypometabolic convergence index (HCI; Chen et al., 2011) in order to explore the relationship between BMI and AD typical hypometabolic patterns. Results:We found extensive and exclusively positive associations of BMI with rCMRgl in regions known to be affected by AD such as occipital, parietal, temporal (including the bilateral hippocampal region), and other brain regions (i.e. cerebellum, frontoinsular and subcortical regions). Confirmatory results were found for specific ROIs. A significant BMI by gender interaction was observed with stronger associations within the right temporal and the right orbitofrontal cortex in males. However, no significant BMI by APOEε4 carrier status interaction or BMI by age group interaction was detected. Additionally, BMI was negatively correlated with HCI, indicating less convergence to AD typical hypometabolic patterns in subjects with high BMI measures. Conclusions: BMI is positively associated with rCMRgl in healthy late middle aged and elderly subjects, including brain regions that are typically affected by AD, thus providing a potential explanation for the proposed beneficial effects of higher BMI with respect to AD development. These associations seem to be modified by gender, possibly as the result of differences in body composition, but not by APOEε4 genotype or age.