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Memory-Related Frontal Brainwaves Predict Transition to Mild Cognitive Impairment in Healthy Older Individuals Five Years Before Diagnosis

Journal Article · · Journal of Alzheimer's Disease
DOI:https://doi.org/10.3233/jad-200931· OSTI ID:1787481
 [1];  [2];  [3];  [4];  [5];  [6];  [4];  [7];  [8]
  1. Univ. of Kentucky, Lexington, KY (United States). College of Medicine. Dept. of Behavioral Science; Univ. of Kentucky, Lexington, KY (United States). College of Medicine. Sanders-Brown Center on Aging. Alzheimer’s Disease Center
  2. Chinese Academy of Sciences (CAS), Beijing (China). Inst. of Psychology. Key Lab. of Mental Health
  3. Univ. of Kentucky, Lexington, KY (United States). College of Medicine. Dept. of Neurology; Univ. of Kentucky, Lexington, KY (United States). College of Medicine. Sanders-Brown Center on Aging. Alzheimer’s Disease Center
  4. Univ. of Kentucky, Lexington, KY (United States). College of Medicine. Dept. of Neurology; Univ. of Kentucky, Lexington, KY (United States). College of Medicine. Sanders-Brown Center on Aging. Alzheimer’s Disease Center
  5. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  6. Univ. of Tennessee, Knoxville, TN (United States). Dept. of Mechanical, Aerospace, and Biomedical Engineering
  7. Univ. of Kentucky, Lexington, KY (United States). College of Art and Sciences. Dept. of Statistics; Univ. of Kentucky, Lexington, KY (United States). College of Medicine. Sanders-Brown Center on Aging. Alzheimer’s Disease Center
  8. Univ. of Kentucky, Lexington, KY (United States). College of Public Health. Dept. of Epidemiology; Univ. of Kentucky, Lexington, KY (United States). College of Medicine. Sanders-Brown Center on Aging. Alzheimer’s Disease Center
Background: Early prognosis of high-risk older adults for amnestic mild cognitive impairment (aMCI), using noninvasive and sensitive neuromarkers, is key for early prevention of Alzheimer’s disease. We have developed individualized measures in electrophysiological brain signals during working memory that distinguish patients with aMCI from age-matched cognitively intact older individuals. Objective: Here we test longitudinally the prognosis of the baseline neuromarkers for aMCI risk. We hypothesized that the older individuals diagnosed with incident aMCI already have aMCI-like brain signatures years before diagnosis. Methods: Electroencephalogram (EEG) and memory performance were recorded during a working memory task at baseline. The individualized baseline neuromarkers, annual cognitive status, and longitudinal changes in memory recall scores up to 10 years were analyzed. Results: Seven of the 19 cognitively normal older adults were diagnosed with incident aMCI for a median 5.2 years later. The seven converters’ frontal brainwaves were statistically identical to those patients with diagnosed aMCI (n = 14) at baseline. Importantly, the converters’ baseline memory-related brainwaves (reduced mean frontal responses to memory targets) were significantly different from those who remained normal. Furthermore, differentiation pattern of left frontal memory-related responses (targets versus nontargets) was associated with an increased risk hazard of aMCI (HR = 1.47, 95% CI 1.03, 2.08). Conclusion: The memory-related neuromarkers detect MCI-like brain signatures about five years before diagnosis. The individualized frontal neuromarkers index increased MCI risk at baseline. These noninvasive neuromarkers during our Bluegrass memory task have great potential to be used repeatedly for individualized prognosis of MCI risk and progression before clinical diagnosis.
Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
National Institute of Health (NIH); USDOE Office of Science (SC)
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
1787481
Journal Information:
Journal of Alzheimer's Disease, Journal Name: Journal of Alzheimer's Disease Journal Issue: 2 Vol. 79; ISSN 1387-2877
Publisher:
IOS PressCopyright Statement
Country of Publication:
United States
Language:
English

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