Exhaled breath is feasible for mild cognitive impairment detection: A diagnostic study with portable micro-gas chromatography

BackgroundMild cognitive impairment (MCI) is an important prodromal stage of Alzheimer's disease (AD), affecting 69 million individuals worldwide. At present, there is a lack of a community-applicable tool for MCI screening. Exhaled breath volatile organic compounds (VOCs) have been used to distinguish MCI from cognitively normal (CN) individuals only in small sample size studies and the efficacy has not been compared with blood biomarkers.ObjectiveThis diagnostic study aimed to assess the feasibility of using exhaled breath VOCs detection by a portable micro-gas chromatography (μGC) device as a screening tool to discriminate MCI from CN individuals in a community population.MethodsA detection model was developed and optimized from five distinct machine learning algorithms based on the differential VOCs between 240 MCI and 241 CN individuals. Among these 481 participants, five plasma biomarkers were measured in 397 individuals (166 MCI and 231 CN).ResultsThe final model (481 individuals) incorporating eight differential VOCs showed good performance with an area under the receiver-operating characteristic curve (AUC) of 0.84 (95% confidence interval (95% CI): 0.83-0.85). The AUC of the VOC model (0.80, 95% CI: 0.69-0.90) was higher than that of the plasma model (0.77, 95% CI: 0.65-0.88) (397 individuals).ConclusionsThe detection of exhaled breath VOCs by a portable μGC device is feasible for MCI screening in community populations, potentially facilitating early detection and intervention strategies for individuals at high risk.

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Publication Details

Journal
Journal of Alzheimer s Disease
Published
2025-02-16
DOI
https://doi.org/10.1177/13872877251319553
Citations
2
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
Field-Weighted Citation Impact
1.35

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article

Exhaled breath is feasible for mild cognitive impairment detection: A diagnostic study with portable micro-gas chromatography

Sitong Chen, Yuhang Lin, Han Zhang, Yilin Xia et al.
2 citations
Journal of Alzheimer s Disease
Advanced Chemical Sensor Technologies
1.35
article

Exhaled breath is feasible for mild cognitive impairment detection: A diagnostic study with portable micro-gas chromatography

Sitong Chen, Yuhang Lin, Han Zhang, Yilin Xia, Qian Geng, Yong Feng, Debo Li, Wanlin Lai, Junqi Wang, Wanling Li, Ling Jin, Zijie Huang, Lei Chen, Ruiqi Yang, Yutong Fu
article en
2 citations

Abstract

BackgroundMild cognitive impairment (MCI) is an important prodromal stage of Alzheimer's disease (AD), affecting 69 million individuals worldwide. At present, there is a lack of a community-applicable tool for MCI screening. Exhaled breath volatile organic compounds (VOCs) have been used to distinguish MCI from cognitively normal (CN) individuals only in small sample size studies and the efficacy has not been compared with blood biomarkers.ObjectiveThis diagnostic study aimed to assess the feasibility of using exhaled breath VOCs detection by a portable micro-gas chromatography (μGC) device as a screening tool to discriminate MCI from CN individuals in a community population.MethodsA detection model was developed and optimized from five distinct machine learning algorithms based on the differential VOCs between 240 MCI and 241 CN individuals. Among these 481 participants, five plasma biomarkers were measured in 397 individuals (166 MCI and 231 CN).ResultsThe final model (481 individuals) incorporating eight differential VOCs showed good performance with an area under the receiver-operating characteristic curve (AUC) of 0.84 (95% confidence interval (95% CI): 0.83-0.85). The AUC of the VOC model (0.80, 95% CI: 0.69-0.90) was higher than that of the plasma model (0.77, 95% CI: 0.65-0.88) (397 individuals).ConclusionsThe detection of exhaled breath VOCs by a portable μGC device is feasible for MCI screening in community populations, potentially facilitating early detection and intervention strategies for individuals at high risk.

Journal of Alzheimer s DiseaseVol. 104(3)
Sichuan University (CN), West China Hospital of Sichuan University (CN), South China Institute of Collaborative Innovation (CN)
Sichuan Province Science and Technology Support Program
Reduced inequalities
Openalex Percentile: Top 22%
Advanced Chemical Sensor Technologies
1.35
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