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F4‐05‐01: ASSOCIATIONS BETWEEN PLASMA NFL AND BRAIN PET IN ALZHEIMER'S DISEASE
Author(s) -
Benedet Andrea Lessa,
Leuzy Antoine,
Pascoal Tharick A.,
Ashton Nicholas J.,
Mathotaarachchi Sulantha,
Savard Melissa,
Therriault Joseph,
Kang Min Su,
Chamoun Mira,
Schöll Michael,
Gauthier Serge,
Zetterberg Henrik,
Rosa-Neto Pedro,
Blennow Kaj
Publication year - 2019
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.2019.06.4729
Subject(s) - posterior cingulate , neuroimaging , positron emission tomography , cerebrospinal fluid , dementia , amyloid (mycology) , medicine , alzheimer's disease , voxel , pathology , psychology , neuroscience , nuclear medicine , disease , cortex (anatomy) , radiology
2015). Here, we analyzed baseline brain imaging measurements of amyloid-b (Ab) plaque deposition, precuneus glucose hypometabolism, and hippocampal volume from 242 cognitively unimpaired 30-53 year-old PSEN1 E280A mutation carriers and non-carriers in the Alzheimer’s Prevention Initiative (API) ADAD Colombia Trial, characterized their relationships with age, and estimated their AAO in the mutation carrier group. Methods: Baseline florbetapir PET, fluorodeoxyglucose (FDG) PET, and volumetric MRI images from 167 mutation carriers and 75 age matched noncarriers were analyzed using previously established pipelines (Fleisher, 2015; Su 2015) to characterize 1) Ab plaque burden using meancortical-to-pontine florbetapir standard uptake value ratios (SUVRs), 2) cerebral glucose hypometabolism using precuneusto-whole brain FDGSUVRs, and 3) neurodegeneration using hippocampal-to-intracranial volume ratios. Linear regression models were used to characterize biomarker associations with age in the two genetic groups. AAOs, defined as the age at which mean biomarker values diverge significantly between the mutation carrier and non-carrier groups, were estimated using both approximate t-tests and the 95% confidence interval (CI) band of age associations. Results: AAO of mean cortical increases in florbetapir SUVR, decreases in precuneus FDG SUVR, and declines in hippocampal volume were less than 30 years, 36 (95%CI 30-40) years, and 42 (95% CI 37-48) years, respectively. Conclusions: This study provides information about associations between baseline brain imaging measurements and age in a large number of cognitively unimpaired PSEN1 E280A mutation carriers and non-carriers from the API ADAD Colombia Trial. Findings are roughly consistent with observational studies of ADAD (Bateman, 2012; Fleisher 2015), and the extent to which they support the hypothetical ordering of biomarker changes in preclinical AD (Jack 2018) will be presented.