AMYPAD - Amyloid Imaging to Prevent Alzheimer's Disease
Published March 15, 2022 | Version v1
Journal article Open

Spatial-Temporal Patterns of Amyloid-β Accumulation: A Subtype and Stage Inference Model Analysis

Creators

  • 1. Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, De Boelelaan 1117, Amsterdam, Netherlands
  • 2. Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain; IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
  • 3. Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, United States
  • 4. Philip Scheltens,
  • 5. Alzheimer Center and Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Epidemiology & Data science, De Boelelaan 1117, Amsterdam, Netherlands
  • 6. Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, De Boelelaan 1117, Amsterdam, Netherlands; Centre for Medical Image Computing, and Queen Square Institute of Neurology, UCL, United Kingdom
  • 7. Faculty of Medicine of the University of Geneva, Geneva, Switzerland; CIMC - Centre d'Imagerie Médicale de Cornavin, Place de Cornavin 18, 1201 Genève 1201 Genève; Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden; Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, P. R. China
  • 8. Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain; IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain

Description

Abstract:

Background and objectives: Currently, amyloid-β (Aβ) staging models assume a single spatial-temporal progression of amyloid accumulation. We assessed evidence for Aβ accumulation subtypes by applying the data-driven Subtype and Stage Inference (SuStaIn) model to amyloid-PET data.

Methods: Amyloid-PET data of 3010 subjects were pooled from 6 cohorts (ALFA+, EMIF-AD, ABIDE, OASIS, and ADNI). Standardized uptake value ratios (SUVr) were calculated for 17 regions. We applied the SuStaIn algorithm to identify consistent subtypes in the pooled dataset based on the cross-validation information criterion (CVIC) and the most probable subtype/stage classification per scan. The effect of demographics and risk factors on subtype assignment was assessed using multinomial logistic regression.

Results: Participants were mostly cognitively unimpaired (N=1890, 62.8%), had a mean age of 68.72 (SD=9.1), 42.1% was APOE-ε4 carrier, and 51.8% was female. While a one-subtype model recovered the traditional amyloid accumulation trajectory, SuStaIn identified an optimal of three subtypes, referred to as Frontal, Parietal, and Occipital based on the first regions to show abnormality. Of the 788 (26.2%) with strong subtype assignment (>50% probability), the majority was assigned to Frontal (N=415, 52.5%), followed by Parietal (N=199, 25.3%), and Occipital subtypes (N=175, 22.2%). Significant differences across subtypes included distinct proportions of APOE-ε4 carriers (Frontal:61.8%, Parietal:57.1%, Occipital:49.4%), subjects with dementia (Frontal:19.7%, Parietal:19.1%, Occipital:31.0%) and lower age for the Parietal subtype (Frontal/Occipital:72.1y, Parietal:69.3y). Higher amyloid (Centiloid) and CSF p-tau burden was observed for the Frontal subtype, while Parietal and Occipital did not differ. At follow-up, most subjects (81.1%) maintained baseline subtype assignment and 25.6% progressed to a later stage.

Discussion: While a one-trajectory model recovers the established pattern of amyloid accumulation, SuStaIn determined that three subtypes were optimal, showing distinct associations to AD risk factors. Nonetheless, further analyses to determine clinical utility is warranted.

Notes

This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 115952. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and EFPIA. This communication reflects the views of the authors and neither IMI nor the European Union and EFPIA are liable for any use that may be made of the information contained herein.

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Additional details

Funding

European Commission
AMYPAD – Amyloid imaging to Prevent Alzheimer’s Disease – Sofia ref.: 115952 115952