4.5 Article

Differential FDDNP PET Patterns in Nondemented Middle-Aged and Older Adults

Journal

AMERICAN JOURNAL OF GERIATRIC PSYCHIATRY
Volume 17, Issue 5, Pages 397-406

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1097/JGP.0b013e318198750b

Keywords

Mild cognitive impairment; positron emission tomography; amyloid neuritic plaques; neurofibrillary tangles

Funding

  1. NIH [P01-AG024831, AG13308, P50 AG 16570, MH/AG58156, MH52453, AG10123, M01-RR00865]
  2. DOE [DE-FC03-87ER60615]
  3. GCRC Program
  4. Larry L. Hillblom Foundation
  5. Rotary CART Fund
  6. Alzheimer's Association
  7. UCLA Alzheimer's Disease Research Center (NIA/NIH) [AG16570]
  8. Turken Foundation
  9. Fran and Ray Stark Foundation Fund for Alzheimer's Disease Research
  10. Ahmanson Foundation
  11. Lovelace Foundation
  12. Judith Olenick Elgart Fund for Research on Brain Aging
  13. John D. French Foundation for Alzheimer's Research
  14. Tamkin Foundation
  15. Alzheimer's Disease Program
  16. California Department of Public Health
  17. Health and Human Services Agency
  18. UCLA Jayne
  19. Terry Semel Institute

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Objective: The authors explored whether positron emission tomography (PET) with 2-(1-{6-[(2-[fluorine-18]fluoroethyl)(methyl) amino]-2-naphthyl} ethylidene)malononitrile (FDDNP), a molecule that binds to plaques and tangles in vitro, might identify homogeneous subgroups of persons in middle-aged and older persons with mild cognitive impairment (MCI) or normal cognition. Participants: Fifty-six subjects (MCI, N = 29; normal cognition, N = 27). Measurements: FDDNP-PET scans were performed. Logan parametric images were produced using cerebellum as a reference region, and relative distribution volumes were obtained for regions of interest (ROIs) known to accumulate plaques and tangles in Alzheimer disease (AD). Cluster analysis was used to identify subgroups of subjects according to FDDNP signal distribution. Once the FDDNP clusters were identified, the authors then characterized the clusters also with respect to diagnosis and cognitive test performances and conducted analyses on cluster differences in these variables. Results: The authors identified three FDDNP clusters: high signal in lateral temporal and posterior cingulate ROIs (high temporal-posterior cingulate HT/PC); low signal in all ROIs (low global [LG] cluster); high frontal and parietal signal with intermediate temporal and posterior cingulate signal (HF/PA). Most MCI subjects belonged to the HT/PC and HF/PA clusters, whereas most cognitively normal subjects were in the LG cluster. On cognitive tests, the HT/PC and the HF/PA clusters performed significantly worse than LG but did not significantly differ from each other. Conclusions: This approach may be useful in identifying potential high-risk imaging cluster patterns. Longitudinal follow-up would be performed to determine the association of these subgroups with diagnostic and functional outcome. (Am J Geriatr Psychiatry 2009; 17: 397-406)

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