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@ARTICLE{Beer:1030442,
      author       = {Beer, Simone and Elmenhorst, David and Bischof, Gerard N.
                      and Ramirez, Alfredo and Bauer, Andreas and Drzezga,
                      Alexander},
      title        = {{E}xplainable artificial intelligence identifies an {AQP}4
                      polymorphism-based risk score associated with brain amyloid
                      burden},
      journal      = {Neurobiology of aging},
      volume       = {143},
      issn         = {0197-4580},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2024-05303},
      pages        = {19 - 29},
      year         = {2024},
      note         = {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).},
      abstract     = {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.},
      cin          = {INM-2},
      ddc          = {610},
      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)16},
      pubmed       = {39208715},
      UT           = {WOS:001316490600001},
      doi          = {10.1016/j.neurobiolaging.2024.08.002},
      url          = {https://juser.fz-juelich.de/record/1030442},
}