A conceptual framework and ethics analysis for prevention trials of Alzheimer Disease

Prog Neurobiol. 2013 Nov:110:114-23. doi: 10.1016/j.pneurobio.2012.12.001. Epub 2013 Jan 21.


As our understanding of the neurobiology of Alzheimer Disease deepens, it has become evident that early intervention is critical to achieving successful therapeutic impact. The availability of diagnostic criteria for preclinical Alzheimer Disease adds momentum to research directed at this goal and even to prevention. The landscape of therapeutic research is thus poised to undergo a dramatic shift in the next 5-10 years, with clinical trials involving subjects at risk for Alzheimer Disease who have few or no symptoms. These trials will also likely rely heavily on genetics, biomarkers, and or risk factor stratification to identify individuals at risk for Alzheimer Disease. Here, we propose a conceptual framework to guide this next generation of pharmacological and non-pharmacological clinical pursuit, and discuss some of the foreseeable ethical considerations that may accompany them.

Keywords: AD; ADNI; API; APOE; Alzheimer Disease; Alzheimer Prevention Initiative; Alzheimer's Disease Neuroimaging Initiative; Aβ; BioM+; BioM−; Biomarkers; CSF; DIAN; Dominantly Inherited Alzheimer Network; EOFAD; Ethics; FDA; Food and Drug Agency; MRI; PET; PiB-PET; Prevention; REVEAL; Risk Evaluation and Education for Alzheimer's Disease; Treatment; [(11)C]Pittsburgh compound B positron emission tomography; amyloid beta; apolipoprotein E; biomarker-negative; biomarker-positive; cerebrospinal fluid; early-onset familial Alzheimer Disease; magnetic resonance imaging; positron emission tomography.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Alzheimer Disease / diagnosis
  • Alzheimer Disease / genetics
  • Alzheimer Disease / prevention & control*
  • Biomarkers
  • Clinical Trials as Topic / ethics*
  • Clinical Trials as Topic / methods*
  • Health Information Management* / ethics
  • Health Information Management* / methods
  • Health Information Management* / trends
  • Humans
  • Risk Factors


  • Biomarkers