TY - GEN
T1 - Probing the link between the APOE-ϵ4 allele and whole-brain gray matter using deep learning
AU - Abrol, Anees
AU - Hajjar, Ihab
AU - Calhoun, Vince
N1 - Funding Information:
This study was supported by National Institutes of Health (NIH) grants RF1AG063153, R01EB006841, and R01EB020407 and National Science Foundation grant 2112455 to Dr. Vince D. Calhoun.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The APOE-ϵ4 allele is a known genetic risk for Alzheimer's disease (AD). Thus, it can be reasoned that the APOE-ϵ4 allele would also impact neurodegeneration-associated structural brain changes. Here we probe if the APOE-ϵ4 genotype directly modulates the human brain's gray matter using a neural network trained on the whole-brain gray matter images from the cognitively normally aging (CN) and AD individuals. To investigate the linkage between the APOE-ϵ4 allele and whole-brain (voxel-wise) gray matter, we systematically profile our investigation in multiple classification tasks, including diagnostic classification and APOE-ϵ4 classification conjointly as well as independently. Results suggest that although the MRI data can reliably track and reflect neurodegenerative changes in the brain cross-sectionally, the APOE-ϵ4 status may not be distinguishable correspondingly. The nonexistence of a direct and convincing modulative effect of APOE-ϵ4 on the whole-brain gray matter indicates that the gray matter changes may be independent of the APOE-ϵ4 status, and instead characterize a non-APOE, comorbid mechanism in AD.
AB - The APOE-ϵ4 allele is a known genetic risk for Alzheimer's disease (AD). Thus, it can be reasoned that the APOE-ϵ4 allele would also impact neurodegeneration-associated structural brain changes. Here we probe if the APOE-ϵ4 genotype directly modulates the human brain's gray matter using a neural network trained on the whole-brain gray matter images from the cognitively normally aging (CN) and AD individuals. To investigate the linkage between the APOE-ϵ4 allele and whole-brain (voxel-wise) gray matter, we systematically profile our investigation in multiple classification tasks, including diagnostic classification and APOE-ϵ4 classification conjointly as well as independently. Results suggest that although the MRI data can reliably track and reflect neurodegenerative changes in the brain cross-sectionally, the APOE-ϵ4 status may not be distinguishable correspondingly. The nonexistence of a direct and convincing modulative effect of APOE-ϵ4 on the whole-brain gray matter indicates that the gray matter changes may be independent of the APOE-ϵ4 status, and instead characterize a non-APOE, comorbid mechanism in AD.
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U2 - 10.1109/EMBC48229.2022.9871338
DO - 10.1109/EMBC48229.2022.9871338
M3 - Conference contribution
C2 - 36086465
AN - SCOPUS:85138128921
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 3506
EP - 3509
BT - 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
Y2 - 11 July 2022 through 15 July 2022
ER -