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IC‐P‐133: A review of published genetic studies using ADNI multimodality quantitative phenotypes: MRI, PET, fluid biomarkers, cognition and clinical status
Author(s) -
Shen Li,
Thompson Paul,
Potkin Steven,
Stone David,
Kim Sungeun,
Nho Kwangsik,
Ramanan Vijay,
Green Robert,
Foroud Tatiana,
Farrer Lindsay,
Moore Jason,
Bertram Lars,
Weiner Michael,
Saykin Andrew
Publication year - 2013
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.2013.05.130
Subject(s) - genome wide association study , neuroimaging , imaging genetics , alzheimer's disease neuroimaging initiative , apolipoprotein e , computational biology , genetic association , phenotype , genetic model , quantitative trait locus , biology , genotype , bioinformatics , cognition , cognitive impairment , medicine , neuroscience , genetics , single nucleotide polymorphism , gene , disease
Resonance Imaging data (MRI) were collected from 9 Normal (NC), 40 Mild Cognitive Impairment (MCI), and 10 probable AD subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). They all were administered the Rey Auditory Verbal Learning Test Delayed Recall (ReyAVLT) within one month of the MRI. A computational anatomy-based cortical thickness technique was performed on the MRI scans, and linear regression models were applied to detect associations between performance on the Rey AVLT tests and cortical thickness in both the left and right cerebral hemispheres. Results: As predicted, there were significant bilateral associations between cortical thickness and delayed verbal memory performance in the inferior parietal (BA 39 and 40), temporoparietal (BA 37) and visual association cortices (BA 18,19) bilaterally. Additionally the left hemisphere showed significant atrophy in the frontal cortex (BA 6,8,9) and the right hemisphere showed significant atrophy in the subgenus cortex. Conclusions: These results demonstrate that verbal memory performance is strongly associated with cortical thickness, which has previously been shown to be a predictor for AD. Our findings nicely align with the observations of others, who have reported activation in the fronto-parieto-occipital network during immediate and delayed recall tasks. Computational anatomy techniques have been increasingly utilized in human brain studies. Our cortical thickness technique is a promising in vivo biomarker tool that may prove useful for early diagnosis.