TY  - JOUR
AU  - Beer, Simone
AU  - Elmenhorst, David
AU  - Bischof, Gerard N.
AU  - Ramirez, Alfredo
AU  - Bauer, Andreas
AU  - Drzezga, Alexander
TI  - Explainable artificial intelligence identifies an AQP4 polymorphism-based risk score associated with brain amyloid burden
JO  - Neurobiology of aging
VL  - 143
SN  - 0197-4580
CY  - Amsterdam [u.a.]
PB  - Elsevier Science
M1  - FZJ-2024-05303
SP  - 19 - 29
PY  - 2024
N1  - Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012), as well as by the A4 study (a4study.org).
AB  - Aquaporin-4 (AQP4) is hypothesized to be a component of the glymphatic system, a pathway for removing brain interstitial solutes like amyloid-β (Aβ). Evidence exists that genetic variation of AQP4 impacts Aβ clearance, clinical outcome in Alzheimer’s disease as well as sleep measures. We examined whether a risk score calculated from several AQP4 single-nucleotide polymorphisms (SNPs) is related to Aβ neuropathology in older cognitively unimpaired white individuals. We used a machine learning approach and explainable artificial intelligence to extract information on synergistic effects of AQP4 SNPs on brain amyloid burden from the ADNI cohort. From this information, we formulated a sex-specific AQP4 SNP-based risk score and evaluated it using data from the screening process of the A4 study. We found in both cohorts significant associations of the risk score with brain amyloid burden. The results support the hypothesis of an involvement of the glymphatic system, and particularly AQP4, in brain amyloid aggregation pathology. They suggest also that different AQP4 SNPs exert a synergistic effect on the build-up of brain amyloid burden.
LB  - PUB:(DE-HGF)16
C6  - 39208715
UR  - <Go to ISI:>//WOS:001316490600001
DO  - DOI:10.1016/j.neurobiolaging.2024.08.002
UR  - https://juser.fz-juelich.de/record/1030442
ER  -