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@ARTICLE{Levin:267497,
      author       = {Levin, Fedor and Grothe, Michel J and Dyrba, Martin and
                      Franzmeier, Nicolai and Teipel, Stefan J},
      collaboration = {Initiative, Alzheimer’s Disease Neuroimaging},
      title        = {{L}ongitudinal trajectories of cognitive reserve in
                      hypometabolic subtypes of {A}lzheimer's disease.},
      journal      = {Neurobiology of aging},
      volume       = {135},
      issn         = {0197-4580},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {DZNE-2024-00143},
      pages        = {26 - 38},
      year         = {2024},
      abstract     = {Previous studies have demonstrated resilience to AD-related
                      neuropathology in a form of cognitive reserve (CR). In this
                      study we investigated a relationship between CR and
                      hypometabolic subtypes of AD, specifically the typical and
                      the limbic-predominant subtypes. We analyzed data from 59
                      Aβ-positive cognitively normal (CN), 221 prodromal
                      Alzheimer's disease (AD) and 174 AD dementia participants
                      from the Alzheimer's Disease Neuroimaging Initiative (ADNI)
                      from ADNI and ADNIGO/2 phases. For replication, we analyzed
                      data from 5 Aβ-positive CN, 89 prodromal AD and 43 AD
                      dementia participants from ADNI3. CR was estimated as
                      standardized residuals in a model predicting cognition from
                      temporoparietal grey matter volumes and covariates. Higher
                      CR estimates predicted slower cognitive decline. Typical and
                      limbic-predominant hypometabolic subtypes demonstrated
                      similar baseline CR, but the results suggested a faster
                      decline of CR in the typical subtype. These findings support
                      the relationship between subtypes and CR, specifically
                      longitudinal trajectories of CR. Results also underline the
                      importance of longitudinal analyses in research on CR.},
      keywords     = {Humans / Alzheimer Disease: diagnostic imaging / Alzheimer
                      Disease: pathology / Cognitive Reserve / Brain: diagnostic
                      imaging / Brain: pathology / Cognition / Gray Matter:
                      diagnostic imaging / Gray Matter: pathology / Cognitive
                      Dysfunction: pathology / Alzheimer’s disease (Other) /
                      Alzheimer’s disease (Other) / Alzheimer’s disease
                      (Other) / Alzheimer’s disease (Other) / Cognitive reserve
                      (Other) / FDG-PET (Other) / Mild cognitive impairment
                      (Other) / Prodromal AD (Other) / Subtypes (Other)},
      cin          = {AG Teipel},
      ddc          = {610},
      cid          = {I:(DE-2719)1510100},
      pnm          = {353 - Clinical and Health Care Research (POF4-353)},
      pid          = {G:(DE-HGF)POF4-353},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:38157587},
      doi          = {10.1016/j.neurobiolaging.2023.12.003},
      url          = {https://pub.dzne.de/record/267497},
}