Earlier Detection of Alzheimer's Disease: ADNI Yielding Answers
Earlier detection of Alzheimer's disease (AD) may soon become a reality, according to findings from new studies conducted in collaboration with the Alzheimer's Disease Neuroimaging Initiative (ADNI). Brain imaging (PET/MRI) and biochemical biomarkers and neuropsychological assessment techniques are under study, with the goal of detecting the earliest signs of disease, before dementia occurs and brain pathology (beta-amyloid plaques and neurofibrillary tangles) becomes extensive. "[Early diagnosis is critical for the eventual early intervention with better drugs, once they are developed]," according to Ronald Petersen, PhD, MD, of the Mayo Clinic College of Medicine (Rochester, MN) and the Alzheimer's Association (Chicago, IL). Dr. Petersen moderated "New Results from ADNI," a press conference held at the 2009 International Conference on Alzheimer's Disease (ICAD 2009), held in Vienna, Austria, July 11-16, 2009. ADNI is a $60 million, 5-year, public-private consortium funded primarily by the National Institute on Aging, of the National Institutes of Health (NIH), with private sector support through the Foundation for NIH.
"The clinical symptoms of mild cognitive impairment (MCI) alone are not enough to allow for the early diagnosis of AD," according to Michael Ewers, PhD, of Trinity College Dublin. People with MCI may revert back to normal, or a disorder other than early stage AD may explain their condition. Dr. Ewers' group examined data on cerebrospinal fluid (CSF) markers; MRI brain volume measurements; and standard memory, learning, and brain function tests from 345 ADNI participants: 81 with AD, 163 with amnestic MCI, and 101 elderly healthy controls. They found that memory test results could reach a classification accuracy of 89.9%, and adding MRI volume measurements of the left hippocampus raised it to 94%. The accuracy of this combination reached 95.6% in validation studies, and it was the most robust predictor.
According to Susan M. Landau, PhD, of the University of California, Berkeley, low baseline FDG-PET measurements, combined with poor memory recall, in people with MCI reliably predicted progression to AD during the two-year period in a study of data from 85 ADNI participants. People who tested positive had a 15-fold increase in their likelihood of developing AD. Dawn Matthews, of Abiant, Inc. (Deerfield, IL), presented promising results from another PET study, measuring decline in cerebral glucose metabolism, which focused on t he hippocampus. The study was conducted by Lisa Mosconi, PhD, and Mony de Leon, PhD, of New York University School of Medicine, in 79 healthy, 111 MCI, and 60 AD subjects.
The selection of subjects with memory loss that will eventually progress to AD for clinical trials with developmental therapies is expected to be the initial application of early detection technologies. According to Dr. Petersen, the five or six clinical trials that have been conducted in MCI failed, possibly because of the inability to select subjects who, in the absence of effective treatment, would convert to AD (or possibly because the drugs were not effective). Although these failures led pharmaceutical companies to abandon MCI trials, Dr. Petersen expects more trials for MCI in the near future. At least several are in the planning stages; notably, some may choose to refer to "early AD," rather than MCI.
[Note that "MCI" is a well-known and appreciated syndrome by clinicians, according to a survey of neurologists who belong to the American Academy of Neurology and identify their practices as "geriatric." (Scott Roberts, PhD, University of Michigan School of Public Health, and Jason Karlawish, MD, University of Michigan School of Public Health; ICAD 2009, poster S4-04-04.]
Application of these technologies to the prediction of MCI to AD conversion in the general populations is a longer-term proposition for several reasons. Brain imaging techniques are expensive and CSF techniques are invasive, and neither could be easily justified at present because of the lack of an available disease-modifying (preventive) treatment. Although individuals at high risk might implement disease-modifying lifestyle changes, the level of proof of their effectiveness is not likely to be sufficient to move these technologies from use as research tools to widespread use anytime soon. Extrapolation of data from such a specialized clinical trial to the general population is also problematic.