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Breath-based non-invasive diagnosis of Alzheimer’s disease : a pilot study
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Tiele, Akira, Wicaksono, Alfian, Daulton, Emma, Ifeachor, Emmanuel, Eyre, Victoria, Clarke, Sophie, Timings, Leanne, Pearson, Stephen, Covington, James A. and Li, Xinzhong (2020) Breath-based non-invasive diagnosis of Alzheimer’s disease : a pilot study. Journal of Breath Research, 14 (2). doi:10.1088/1752-7163/ab6016
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WRAP-breath-based-non-invasive-diagnosis-Alzheimer’s-disease-pilot-study-Covington-2019.pdf - Accepted Version Embargoed item. Restricted access to Repository staff only until 14 February 2021. Contact author directly, specifying your specific needs. - Requires a PDF viewer. Available under License Creative Commons Attribution Non-commercial No Derivatives. Download (460Kb) |
Official URL: http://dx.doi.org/10.1088/1752-7163/ab6016
Abstract
Early detection of Alzheimer's disease (AD) will help researchers to better understand the disease and develop improved treatments. Recent developments have thus focused on identifying biomarkers for mild cognitive impairment due to AD (MCI) and AD during the preclinical phase. The aim of this pilot study is to determine whether exhaled volatile organic compounds (VOCs) can be used as a non-invasive method to distinguish controls from MCI, controls from AD and to determine whether there are differences between MCI and AD. The study used gas chromatography – ion mobility spectrometry (GC-IMS) techniques. Confounding factors, such as age, smoking habits, gender and alcohol consumption are investigated to demonstrate the efficacy of results. One hundred subjects were recruited including 50 controls, 25 AD and 25 MCI patients. The subject cohort was age- and gender-matched to minimise bias. Breath samples were analysed using a commercial GC-IMS instrument (G.A.S. BreathSpec, Dortmund, Germany). Data analysis indicates that the GC-IMS signal was consistently able to separate between diagnostic groups [AUC±95%, sensitivity, specificity], controls vs MCI: [0.77 (0.64 – 0.90), 0.68, 0.80], controls vs AD: [0.83 (0.72 – 0.94), 0.60, 0.96], and MCI vs AD: [0.70 (0.55 – 0.85), 0.60, 0.84]. VOC analysis indicates that six compounds play a crucial role in distinguishing between diagnostic groups. Analysis of possible confounding factors indicate that gender, age, smoking habits and alcohol consumption have insignificant influence on breath content. This pilot study confirms the utility of exhaled breath analysis to distinguish between AD, MCI and control subjects. Thus, GC-IMS offers great potential as a non-invasive, high-throughput, diagnostic technique for diagnosing and potentially monitoring AD in a clinical setting.
| Item Type: | Journal Article | |||||||||
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| Subjects: | Q Science > QC Physics Q Science > QD Chemistry Q Science > QP Physiology R Medicine > RC Internal medicine |
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| Divisions: | Faculty of Science > Engineering | |||||||||
| Library of Congress Subject Headings (LCSH): | Alzheimer's disease, Mild cognitive impairment, Volatile organic compounds, Gas chromatography, Ion mobility spectroscopy, Breath tests, Respiration -- Analysis | |||||||||
| Journal or Publication Title: | Journal of Breath Research | |||||||||
| Publisher: | Institute of Physics Publishing Ltd. | |||||||||
| ISSN: | 1752-7163 | |||||||||
| Official Date: | 14 February 2020 | |||||||||
| Dates: |
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| Date of first compliant deposit: | 2 January 2020 | |||||||||
| Volume: | 14 | |||||||||
| Number: | 2 | |||||||||
| DOI: | 10.1088/1752-7163/ab6016 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||
| RIOXX Funder/Project Grant: |
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