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Preclinical Alzheimer's disease biomarkers accurately predict cognitive and neuropathological outcomes.
Long, Justin M; Coble, Dean W; Xiong, Chengjie; Schindler, Suzanne E; Perrin, Richard J; Gordon, Brian A; Benzinger, Tammie L S; Grant, Elizabeth; Fagan, Anne M; Harari, Oscar; Cruchaga, Carlos; Holtzman, David M; Morris, John C.
Affiliation
  • Long JM; Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
  • Coble DW; Department of Neurology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
  • Xiong C; Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
  • Schindler SE; Division of Biostatistics, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
  • Perrin RJ; Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
  • Gordon BA; Division of Biostatistics, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
  • Benzinger TLS; Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
  • Grant E; Department of Neurology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
  • Fagan AM; Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
  • Harari O; Department of Neurology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
  • Cruchaga C; Department of Pathology and Immunology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
  • Holtzman DM; Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
  • Morris JC; Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis, St Louis, MO 63110, USA.
Brain ; 145(12): 4506-4518, 2022 12 19.
Article in En | MEDLINE | ID: mdl-35867858
ABSTRACT
Alzheimer's disease biomarkers are widely accepted as surrogate markers of underlying neuropathological changes. However, few studies have evaluated whether preclinical Alzheimer's disease biomarkers predict Alzheimer's neuropathology at autopsy. We sought to determine whether amyloid PET imaging or CSF biomarkers accurately predict cognitive outcomes and Alzheimer's disease neuropathological findings. This study included 720 participants, 42-91 years of age, who were enrolled in longitudinal studies of memory and aging in the Washington University Knight Alzheimer Disease Research Center and were cognitively normal at baseline, underwent amyloid PET imaging and/or CSF collection within 1 year of baseline clinical assessment, and had subsequent clinical follow-up. Cognitive status was assessed longitudinally by Clinical Dementia Rating®. Biomarker status was assessed using predefined cut-offs for amyloid PET imaging or CSF p-tau181/amyloid-ß42. Subsequently, 57 participants died and underwent neuropathologic examination. Alzheimer's disease neuropathological changes were assessed using standard criteria. We assessed the predictive value of Alzheimer's disease biomarker status on progression to cognitive impairment and for presence of Alzheimer's disease neuropathological changes. Among cognitively normal participants with positive biomarkers, 34.4% developed cognitive impairment (Clinical Dementia Rating > 0) as compared to 8.4% of those with negative biomarkers. Cox proportional hazards modelling indicated that preclinical Alzheimer's disease biomarker status, APOE ɛ4 carrier status, polygenic risk score and centred age influenced risk of developing cognitive impairment. Among autopsied participants, 90.9% of biomarker-positive participants and 8.6% of biomarker-negative participants had Alzheimer's disease neuropathological changes. Sensitivity was 87.0%, specificity 94.1%, positive predictive value 90.9% and negative predictive value 91.4% for detection of Alzheimer's disease neuropathological changes by preclinical biomarkers. Single CSF and amyloid PET baseline biomarkers were also predictive of Alzheimer's disease neuropathological changes, as well as Thal phase and Braak stage of pathology at autopsy. Biomarker-negative participants who developed cognitive impairment were more likely to exhibit non-Alzheimer's disease pathology at autopsy. The detection of preclinical Alzheimer's disease biomarkers is strongly predictive of future cognitive impairment and accurately predicts presence of Alzheimer's disease neuropathology at autopsy.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Alzheimer Disease / Cognitive Dysfunction Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Brain Year: 2022 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Alzheimer Disease / Cognitive Dysfunction Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Brain Year: 2022 Type: Article Affiliation country: United States