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@INPROCEEDINGS{Beer:1030443,
      author       = {Beer, Simone and Elmenhorst, David and Bischof, Gerard
                      Nisal and Ramirez, Alfredo and Bauer, Andreas and Drzezga,
                      Alexander},
      title        = {{E}xplainable {AI} identifies an {AQP}4 polymorphism-based
                      risk score associated with brain amyloid burden},
      reportid     = {FZJ-2024-05304},
      year         = {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 arti􀀁cial 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-speci􀀁c 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 signi􀀁cant
                      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.},
      month         = {Jun},
      date          = {2024-06-17},
      organization  = {Lund Glymphatic symposium, Lund
                       (Sweden), 17 Jun 2024 - 20 Jun 2024},
      subtyp        = {After Call},
      cin          = {INM-2},
      cid          = {I:(DE-Juel1)INM-2-20090406},
      pnm          = {5253 - Neuroimaging (POF4-525) / 5252 - Brain Dysfunction
                      and Plasticity (POF4-525) / 5254 - Neuroscientific Data
                      Analytics and AI (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5253 / G:(DE-HGF)POF4-5252 /
                      G:(DE-HGF)POF4-5254},
      typ          = {PUB:(DE-HGF)6},
      url          = {https://juser.fz-juelich.de/record/1030443},
}