Smell Test May Be Best Way to Detect Early Alzheimer’s
New research from Columbia University Medical Center (CUMC), New York State Psychiatric Institute, and New York-Presbyterian suggests an odor identification test may prove useful in predicting cognitive decline and detecting early-stage Alzheimer’s disease.
The investigators performed two studies that found the smell identification test offers a practical, low-cost alternative to detecting Alzheimer’s. Researchers believe the test, called the University of Pennsylvania Smell Identification Test (UPSIT) is a practical, low-cost alternative to other tests that are often more invasive and expensive.
In one study, researchers administered UPSIT to 397 older adults (average age of 80 years) without dementia from a multiethnic population in northern Manhattan. Each of the participants also had an MRI scan to measure the thickness of the entorhinal cortex, the first area of the brain to be affected by Alzheimer’s disease.
Four years later, 50 participants (12.6 percent) had developed dementia, and nearly 20 percent had signs of cognitive decline.
The researchers found that low UPSIT scores, but not entorhinal cortical thickness, were significantly associated with dementia and Alzheimer’s disease. (Low UPSIT scores indicate decreased ability to correctly identify odors.)
Low UPSIT scores, but not entorhinal cortical thickness, also predicted cognitive decline, although entorhinal cortical thickness was significantly associated with UPSIT score in those who transitioned to dementia.
“Our research showed that odor identification impairment, and to a lesser degree, entorhinal cortical thickness, were predictors of the transition to dementia,” said Seonjoo Lee, Ph.D., presenting author.
“These findings support odor identification as an early predictor, and suggest that impairment in odor identification may precede thinning in the entorhinal cortex in the early clinical stage of Alzheimer’s disease.”
In another study, researchers from CUMC evaluated the usefulness of UPSIT and tests that measure the amount of amyloid in the brain (in higher amounts, the protein forms plaques in the brains of those with Alzheimer’s disease) in predicting memory decline.
The researchers administered UPSIT and performed either beta amyloid PET scanning or analysis of cerebrospinal fluid in 84 older adults (median age of 71 years). Of these, 58 participants had mild cognitive impairment. The researchers followed the participants for at least six months.
At follow-up, 67 percent of the participants had signs of memory decline. Testing positive for amyloid with either method, but not UPSIT score, predicted cognitive decline. However, participants with a score of less than 35 were more than three times as likely to have memory decline as those with higher UPSIT scores.
“Our research suggests that both UPSIT score and amyloid status predict memory decline,” said William Kreisl, M.D., a neurologist at New York-Presbyterian/Columbia.
“Younger age, higher education, and shorter follow-up may explain why UPSIT did not predict decline as strongly in this study as in previous studies. Although more research is needed, odor identification testing, which is much less expensive and easier to administer than PET imaging or lumbar puncture, may prove to be a useful tool in helping physicians counsel patients who are concerned about their risk of memory loss.”
Current methods are only capable of clinically detecting Alzheimer’s disease in the later stages of its development, when significant brain damage has already occurred.
“Our study adds to the growing body of evidence demonstrating the potential value of odor identification testing in the detection of early-stage Alzheimer’s disease,” said D.P. Devanand, M.D., professor of psychiatry at CUMC and senior author of both studies.
Nauert PhD, R. (2016). Smell Test May Be Best Way to Detect Early Alzheimer’s. Psych Central. Retrieved on March 24, 2018, from https://psychcentral.com/news/2016/07/27/smell-test-may-be-the-best-method-to-detect-early-alzheimers/107738.html