Measuring Compounds in Exhaled Air to Detect Alzheimer's Disease and Parkinson's Disease.

Bach, Jan-Philipp; Gold, Maike; Mengel, David; Hattesohl, Akira; Lubbe, Dirk; Schmid, Severin; Tackenberg, Björn; Rieke, Jürgen; Maddula, Sasidhar; Baumbach, Jörg Ingo; Nell, Christoph; Boeselt, Tobias; Michelis, Joan Philipp; Alferink, Judith; Heneka, Michael; Oertel, Wolfgang; Jessen, Frank; Janciauskiene, Sabina; Vogelmeier, Claus; Dodel, Richard; ... (2015). Measuring Compounds in Exhaled Air to Detect Alzheimer's Disease and Parkinson's Disease. PLoS ONE, 10(7), e0132227. Public Library of Science 10.1371/journal.pone.0132227

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BACKGROUND

Alzheimer's disease (AD) is diagnosed based upon medical history, neuropsychiatric examination, cerebrospinal fluid analysis, extensive laboratory analyses and cerebral imaging. Diagnosis is time consuming and labour intensive. Parkinson's disease (PD) is mainly diagnosed on clinical grounds.

OBJECTIVE

The primary aim of this study was to differentiate patients suffering from AD, PD and healthy controls by investigating exhaled air with the electronic nose technique. After demonstrating a difference between the three groups the secondary aim was the identification of specific substances responsible for the difference(s) using ion mobility spectroscopy. Thirdly we analysed whether amyloid beta (Aβ) in exhaled breath was causative for the observed differences between patients suffering from AD and healthy controls.

METHODS

We employed novel pulmonary diagnostic tools (electronic nose device/ion-mobility spectrometry) for the identification of patients with neurodegenerative diseases. Specifically, we analysed breath pattern differences in exhaled air of patients with AD, those with PD and healthy controls using the electronic nose device (eNose). Using ion mobility spectrometry (IMS), we identified the compounds responsible for the observed differences in breath patterns. We applied ELISA technique to measure Aβ in exhaled breath condensates.

RESULTS

The eNose was able to differentiate between AD, PD and HC correctly. Using IMS, we identified markers that could be used to differentiate healthy controls from patients with AD and PD with an accuracy of 94%. In addition, patients suffering from PD were identified with sensitivity and specificity of 100%. Altogether, 3 AD patients out of 53 participants were misclassified. Although we found Aβ in exhaled breath condensate from both AD and healthy controls, no significant differences between groups were detected.

CONCLUSION

These data may open a new field in the diagnosis of neurodegenerative disease such as Alzheimer's disease and Parkinson's disease. Further research is required to evaluate the significance of these pulmonary findings with respect to the pathophysiology of neurodegenerative disorders.

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