ArticleTranslational psychiatry2026
Establishment and validation of an Alzheimer's disease diagnostic model on the basis of exhaled volatile organic compound characteristics.
Article in Translational psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Exhaled volatile organic compounds (VOCs) have been investigated in some diseases, including cognitive impairment, in pilot studies. The present study aimed to explore the role of exhaled VOCs in identifying and differentiating patients with Alzheimer's disease (AD). The identification cohort included 241 participants: 99 AD patients (dementia=74, mild cognitive impairment (MCI) = 25), 59 non-AD dementia patients, and 83 cognitively unimpaired controls (CUCs). Proton transfer reaction time-of-flight mass spectrometry (PTR-TOFMS) was employed to detect exhaled VOCs. The differences in VOCs between the AD and CUC groups and between the AD dementia and non-AD dementia groups were compared separately. Furthermore, machine learning models for discriminating AD from CUC as well as AD dementia from non-AD dementia were established. The AD diagnostic model was further validated in an independent cohort of 44 AD patients (dementia=33, MCI = 11) and 35 CUCs. Moreover, we explored the possible metabolic pathways of AD-specific exhaled VOCs with the Human Metabolome Database (HMDB). We detected 60 different VOCs between the AD and CUC groups, among which the top ten were C
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