Olfactory Testing and Gray Matter Volume: A Combined Approach to Predict the Conversion to Alzheimer

嗅觉测试和灰质体积:预测阿尔茨海默病转化的联合方法

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Abstract

Background/Objectives: Olfactory decline is common in normal aging and frequent in neurodegenerative diseases such as Alzheimer's disease (AD). Therefore, it has been suggested as a marker for the Mild Cognitive Impairment (MCI) progression to AD. Although suggested, the relationship between olfactory deficits and cerebral atrophy in MCI conversion to AD is still debated. This study aims at investigating the olfaction-related morphological and behavioural alterations in MCI in order to understand whether they can predict the progression to AD. Methods: Twenty-seven MCI patients and thirty-five healthy controls (HCs) took part in the study, with follow-up showing conversion to AD in thirteen patients (converter-MCI, cMCI). The Burgarth Sniffin' Sticks Tests (threshold-TT, discrimination-DT, identification-IT) assessed the olfactory capacities. The Voxel-Based Morphometry (VBM) analysis investigated the atrophic patterns. Results: The Receiving Operating Characteristics analyses demonstrated that DT and IT could distinguish HC from MCI (DT Area Under Curve-AUC = 0.8; IT AUC = 0.8), as well as cMCI from sMCI (stable) patients (DT AUC = 0.7; IT AUC = 0.6), similarly to memory and executive functions tests. Olfactory performance positively correlated with memory tests in sMCI (all rhos ≥ 0.8, all ps < 0.01), whereas it positively correlated with executive functions in cMCI (all rhos ≥ 0.6, all ps < 0.05). VBM results revealed distinct atrophic patterns in cMCI, especially in the olfactory cortex, that were already present at the MCI diagnosis, before AD conversion. A larger volume of the olfactory cortex was associated with better memory and executive functions. Conclusions: Quantitative olfactory and morphological patterns represent non-invasive, predictive biomarkers of the MCI progression to AD; thus, their assessments at MCI onset allows earlier interventions for MCI patients.

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