Neuroimaging biomarkers and impaired olfaction in cognitively normal individuals

Abstract

Objective: There is a need for inexpensive noninvasive tests to identify older healthy persons at risk for Alzheimer disease (AD) for enrollment in AD prevention trials. Our objective was to examine whether abnormalities in neuroimaging measures of amyloid and neurodegeneration are correlated with odor identification (OI) in the population-based Mayo Clinic Study of Aging.

Methods: Cognitively normal (CN) participants had olfactory function assessed using the Brief Smell Identification Test (B-SIT), underwent magnetic resonance imaging (n = 829) to assess a composite AD signature cortical thickness and hippocampal volume (HVa), and underwent ¹¹ C-Pittsburgh compound B (n = 306) and ¹⁸ fluorodeoxyglucose (n = 305) positron emission tomography scanning to assess amyloid accumulation and brain hypometabolism, respectively. The association of neuroimaging biomarkers with OI was examined using multinomial logistic regression and simple linear regression models adjusted for potential confounders.

Results: Among 829 CN participants (mean age = 79.2 years; 51.5% men), 248 (29.9%) were normosmic and 78 (9.4%) had anosmia (B-SIT score < 6). Abnormal AD signature cortical thickness and reduced HVa were associated with decreased OI as a continuous measure (slope = -0.43, 95% confidence interval [CI] = -0.76 to -0.09, p = 0.01 and slope = -0.72, 95% CI = -1.15 to -0.28, p < 0.01, respectively). Reduced HVa, decreased AD signature cortical thickness, and increased amyloid accumulation were significantly associated with increased odds of anosmia.

Interpretation: Our findings suggest that OI may be a noninvasive, inexpensive marker for risk stratification, for identifying participants at the preclinical stage of AD who may be at risk for cognitive impairment and eligible for inclusion in AD prevention clinical trials. These cross-sectional findings remain to be validated prospectively. Ann Neurol 2017;81:871-882.

Figure 1

Forest plots for associations (slopes, 95%CI) of continuous cortical thickness and volume measures (i.e., amygdala and hippocampus) with continuous B-SIT as the outcome variable. The diamonds represent slopes (estimated change in B-SIT per unit increase in cortical thickness (in mm) and volume measures (in cm³)) from general linear models adjusted for age, sex, education. The solid horizontal lines represent the 95% confidence intervals. AD signature = an AD-signature cortical thickness measure was computed by averaging the cortical thickness for entorhinal, inferior temporal, middle temporal, and fusiform cortices.

Figure 2

Forest plots of associations (slopes, 95%CI) of continuous ¹⁸-F-FDG PET biomarkers with continuous B-SIT as the outcome variable. The diamonds represent slopes (estimated change in B-SIT per unit increase in FDG PET standardized uptake value ratio) from general linear models, adjusted for age, sex, education. The solid horizontal lines represent the 95% confidence intervals. AD signature = an AD signature ¹⁸F-FDG PET SUVR was calculated based on glucose metabolic rates from an AD signature meta-ROI and consisted of the average bilateral angular gyri, posterior cingulate, and inferior temporal cortical ROIs from both hemispheres normalized to pons and vermis uptake.