Investigation of Exhaled Breath Samples from Patients with Alzheimer’s Disease Using Gas Chromatography-Mass Spectrometry and an Exhaled Breath Sensor System

Abstract

Exhaled breath is a body secretion, and the sampling process of this is simple and cost effective. It can be non-invasively collected for diagnostic procedures. Variations in the chemical composition of exhaled breath resulting from gaseous exchange in the extensive capillary network of the body are proposed to be associated with pathophysiological changes. In light of the foreseeable potential of exhaled breath as a diagnostic specimen, we used gas chromatography and mass spectrometry (GC-MS) to study the chemical compounds present in exhaled breath samples from patients with Alzheimer’s disease (AD), Parkinson’s disease (PD), and from healthy individuals as a control group. In addition, we also designed and developed a chemical-based exhaled breath sensor system to examine the distribution pattern in the patient and control groups. The results of our study showed that several chemical compounds, such as 1-phenantherol and ethyl 3-cyano-2,3-bis (2,5,-dimethyl-3-thienyl)-acrylate, had a higher percentage area in the AD group than in the PD and control groups. These results may indicate an association of these chemical components in exhaled breath with the progression of disease. In addition, in-house fabricated exhaled breath sensor systems, containing several types of gas sensors, showed significant differences in terms of the normalized response of the sensitivity characteristics between the patient and control groups. A subsequent clustering analysis was able to distinguish between the AD patients, PD patients, and healthy individuals using principal component analysis, Sammon’s mapping, and a combination of both methods, in particular when using the exhaled breath sensor array system A consisting of eight sensors. With this in mind, the exhaled breath sensor system could provide alternative option for diagnosis and be applied as a useful, effective tool for the screening and diagnosis of AD in the near future.

Can oral health and oral‐derived biospecimens predict progression of dementia?

“…This innovative approach is now being applied to neurodegenerative disease research. Though only in its infancy, changes in breath-derived VOC profiles are evident in several disease states, such as multiple sclerosis (Broza et al, 2017), AD (Mazzatenta, Pokorski, Sartucci, Domenici, & Di Giulio, 2015), Parkinson's disease (Nakhleh et al, 2015), and discriminating between the latter two neurodegenerative diseases are emerging (Lau, Yu, Lee, Huh, & Lim, 2017;Tisch et al, 2013). Mazzatenta et al, (2015 noted that AD patients exhibited a significant difference in breath frequency (p = .002) and maximum breath peak frequency (p = .02) compared to healthy subjects, possibly due to increased neuronal death or damage.…”

Plasmonic Sensing Studies of a Gas-Phase Cystic Fibrosis Marker in Moisture Laden Air

“…Real-time breath analysis presents many potential benefits. As such, there are various technologies such as electrochemistry [ 10 ], gas chromatography (GC) [ 11 ], mass spectrometry (MS) [ 11 , 12 ], and optical spectroscopy [ 13 , 14 ] that have been investigated and published over the last few decades. Currently, the conventional laboratory-based techniques for analyzing volatile organic compounds (VOCs) are thermal desorption (TD) GC-MS and nuclear-magnetic-resonance (NMR) [ 15 , 16 , 17 ].…”

Breath-based non-invasive diagnosis of Alzheimer’s disease: a pilot study

“…In addition to this, there have been at least four breath-based studies investigating the efficacy of diagnosing AD. These studies used gas chromatography-mass spectrometry (GC-MS) [18,19], Cyranose 320 electronic nose (eNose) [20], ion mobility spectro-scopy (IMS) [20] and custom-built sensor systems [18,19,21]. Three out of four of these studies investigated AD, as well as Parkinson's disease (PD), against control subjects.…”

“…The key disadvantage of using the decision tree approach is that the individual analytes are not suitable to differentiate patients with AD and PD from HC; instead, it is a combination and sequence of analytes that make prediction possible. Lau et al[19] used a custom-built exhaled breath sensors system and GC-MS to evaluate the breath of 60 subjects (20 AD, 20 PD and 20 controls). GC-MS results…”