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| Home > Publications database > Explainable AI identifies an AQP4 polymorphism-based risk score associated with brain amyloid burden |
| Home > Publications database > Explainable AI identifies an AQP4 polymorphism-based risk score associated with brain amyloid burden |
| Conference Presentation (After Call) | FZJ-2024-05304 |
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2024
Abstract: Aquaporin-4 (AQP4) is an integral component of the glymphatic system. Evidence exists that genetic variation of AQP4impacts Aβ clearance, clinical outcome in Alzheimer’s disease as well as sleep measures. We examined whether a risk scorecalculated from several AQP4 single-nucleotide polymorphisms (SNPs) is related to Aβ neuropathology measured by[18F]Florbetapir PET in older cognitively unimpaired individuals. In a rst step we used a machine learning approach withdecision tree ensembles and explainable articial intelligence (AI), namely SHapley Additive exPlanations (SHAP), to extractinformation on synergistic effects of AQP4 SNPs on brain amyloid burden from the Alzheimer's Disease NeuroimagingInitiative (ADNI) cohort. From this information, we formulated a sex-specic AQP4 SNP-based risk score and evaluated it onthe basis of data from the screening process of the Anti-Amyloid Treatment in Asymptomatic Alzheimer’s (A4/LEARN) study.We found in both cohorts signicant associations of the risk score with brain amyloid burden (multiple linear regression;ADNI females: p=0.001 , males: p=0.005; A4/LEARN females: p=0.014, males: p=0.102) and amyloid positivity (Cochran-Armitage trend test; ADNI females: p=0.002 , males: p=0.0007; A4/LEARN females: p=0.006, males: p=0.02). The resultssupport the hypothesis of an involvement of the glymphatic system, and particularly AQP4, in brain amyloid aggregationpathology. They suggest also that different AQP4 SNPs exert a synergistic effect on the build-up of brain amyloid burden.
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