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@INPROCEEDINGS{Wisch:283056,
      author       = {Wisch, Julie K and McKay, Nicole S and Zammit, Matthew D
                      and Christian, Bradley T and Schultz, Stephanie A and
                      Millar, Peter R and Barthélemy, Nicolas R and Ryan, Natalie
                      S and Renton, Alan E and Vermunt, Lisa and Joseph-Mathurin,
                      Nelly and Shirzadi, Zahra and Strain, Jeremy F and Chrem,
                      Patricio and Daniels, Alisha and Chhatwal, Jasmeer P and
                      Cruchaga, Carlos and Ibanez, Laura and Jucker, Mathias and
                      Day, Gregory S and Lee, Jae-Hong and Levin, Johannes and
                      Llibre-Guerra, Jorge J and Aguillon, David and Roh, Jee Hoon
                      and Supnet-Bell, Charlene and Xiong, Chengjie and Schindler,
                      Suzanne E and Wang, Guoqiao and Li, Yan and Koeppe, Robert
                      and Jack, Clifford R and Morris, John C and McDade, Eric and
                      Bateman, Randall J and Benzinger, Tammie L S and Ances, Beau
                      and Betthauser, Tobey J and Gordon, Brian A},
      collaboration = {Network, Dominantly Inherited Alzheimer},
      title        = {{V}alidation of {A}myloid {C}hronicity in {A}utosomal
                      {D}ominant {A}lzheimer {D}isease},
      journal      = {Alzheimer's and dementia},
      volume       = {21},
      number       = {Suppl 2},
      issn         = {1552-5260},
      reportid     = {DZNE-2025-01463},
      pages        = {e103008},
      year         = {2025},
      abstract     = {Alzheimer Disease (AD) pathology evolves over decades, and
                      understanding this progression is critical to the
                      understanding of the disease and timing therapeutic
                      interventions. Since individuals with Autosomal Dominant AD
                      (ADAD) develop symptoms around the same age as their parent,
                      it is possible to predict symptom onset and stage
                      individuals by their estimated years to symptom onset (EYO).
                      This approach does not generalize to other forms of AD, thus
                      there is a pressing need for the timecourse of ADAD to be
                      defined in broadly relevant terms. The objective of this
                      project is to validate the Sampled Iterative Local
                      Approximation (SILA) algorithm in a cohort with a known
                      disease timecourse. SILA generates an estimate of time from
                      amyloid positivity (Atime) based on longitudinal PET data.We
                      evaluated Atime in a longitudinal ADAD sample (N = 316) with
                      PET PiB data in three ways. First, we compared predicted age
                      at amyloid positive (A+) to observed age at A+ for
                      individuals who became A+ during enrollment. Next, using
                      linear regression, we compared estimated age at A+ to
                      estimated age at symptom onset (EYO=0). Finally, we used
                      generalized additive models to compare the amount of
                      variance in concurrent cognitive performance explained both
                      Atime and EYO.We observed a mean average error of 1.15 years
                      between actual age at A+ (N = 26) and the SILA-predicted
                      Atime. Across all participants, SILA-estimated age at A+
                      explained $39\%$ of the variance in estimated age at symptom
                      onset (β = 0.918, p < 0.0001). Finally, we observed a
                      nonlinear association between cognition and both Atime and
                      EYO. Atime explained $19\%$ of the variance in the general
                      cognitive composite while EYO explained $43\%$ of the
                      variance.SILA produces a valid estimate of time-from-amyloid
                      positivity in ADAD. This work allows for disease stage in
                      ADAD to be compared to staging for broad forms of AD, which
                      was not previously possible using EYO. However, this work
                      also illustrates that there is a high degree of
                      heterogeneity in preclinical disease duration that is not
                      explained by amyloid alone.},
      month         = {Jul},
      date          = {2025-07-27},
      organization  = {Alzheimer’s Association
                       International Conference, Toronto
                       (Canada), 27 Jul 2025 - 31 Jul 2025},
      keywords     = {Humans / Alzheimer Disease: diagnostic imaging / Alzheimer
                      Disease: diagnosis / Alzheimer Disease: metabolism /
                      Positron-Emission Tomography / Male / Female / Biomarkers:
                      metabolism / Longitudinal Studies / Aged / Disease
                      Progression / Middle Aged / Algorithms / Amyloid
                      beta-Peptides: metabolism / Brain: diagnostic imaging /
                      Brain: metabolism / Biomarkers (NLM Chemicals) / Amyloid
                      beta-Peptides (NLM Chemicals)},
      cin          = {AG Jucker},
      ddc          = {610},
      cid          = {I:(DE-2719)1210001},
      pnm          = {352 - Disease Mechanisms (POF4-352)},
      pid          = {G:(DE-HGF)POF4-352},
      typ          = {PUB:(DE-HGF)1 / PUB:(DE-HGF)16},
      pubmed       = {pmid:41451762},
      pmc          = {pmc:PMC12741810},
      doi          = {10.1002/alz70856_103008},
      url          = {https://pub.dzne.de/record/283056},
}