Distinguishing idiopathic Parkinson's disease from other parkinsonian syndromes by breath test.

INTRODUCTION: Diagnosis of different parkinsonian syndromes is linked with high misdiagnosis rates and various confounding factors. This is particularly problematic in its early stages. With this in mind, the current pilot study aimed to distinguish between Idiopathic Parkinson's Disease (iPD), other Parkinsonian syndromes (non-iPD) and healthy subjects, by a breath test that analyzes the exhaled volatile organic compounds using a highly sensitive nanoarray. METHODS: Breath samples of 44 iPD, 16 non-iPD patients and 37 healthy controls were collected. The samples were passed over a nanoarray and the resulting electrical signals were analyzed with discriminant factor analysis as well as by a K-fold cross-validation method, to test the accuracy of the model. RESULTS: Comparison of non-iPD with iPD states yielded 88% sensitivity, 88% accuracy, and 88% Receiver Operating Characteristic area under the curve in the training set samples with known identity. The validation set of this comparison scored 81% sensitivity and accuracy and 92% negative predictive value. Comparison between atypical parkinsonism states and healthy subjects scored 94% sensitivity and 85% accuracy in the training set samples with known identity. The validation set of this comparison scored 81% sensitivity and 78% accuracy. The obtained results were not affected by l-Dopa or MAO-B inhibitor treatment. CONCLUSIONS: Exhaled breath analysis with nanoarray is a promising approach for a non-invasive, inexpensive, and portable technique for differentiation between different Parkinsonian states. A larger cohort is required in order to establish the clinical usefulness of the method.

Unique volatolomic signatures of TP53 and KRAS in lung cells.

BACKGROUND: Volatile organic compounds (VOCs) are potential biomarkers for cancer detection in breath, but it is unclear if they reflect specific mutations. To test this, we have compared human bronchial epithelial cell (HBEC) cell lines carrying the KRAS(V12) mutation, knockdown of TP53 or both with parental HBEC cells. METHODS: VOC from headspace above cultured cells were collected by passive sampling and analysed by thermal desorption gas chromatography mass spectrometry (TD-GC-MS) or sensor array with discriminant factor analysis (DFA). RESULTS: In TD-GC-MS analysis, individual compounds had limited ability to discriminate between cell lines, but by applying DFA analysis combinations of 20 VOCs successfully discriminated between all cell types (accuracies 80-100%, with leave-one-out cross validation). Sensor array detection DFA demonstrated the ability to discriminate samples based on their cell type for all comparisons with accuracies varying between 77% and 93%. CONCLUSIONS: Our results demonstrate that minimal genetic changes in bronchial airway cells lead to detectable differences in levels of specific VOCs identified by TD-GC-MS or of patterns of VOCs identified by sensor array output. From the clinical aspect, these results suggest the possibility of breath analysis for detection of minimal genetic changes for earlier diagnosis or for genetic typing of lung cancers.

Analysis of exhaled breath for diagnosing head and neck squamous cell carcinoma: a feasibility study.

BACKGROUND: Squamous cell carcinoma of the head and neck (HNSCC) are wide-spread cancers that often lead to disfigurement and loss of important functions such as speech and ingestion. To date, HNSCC has no adequate method for early detection and screening. METHODS: Exhaled breath samples were collected from 87 volunteers; 62 well-defined breath samples from 22 HNSCC patients (larynx and pharynx), 21 patients with benign tumours (larynx and pharynx) and 19 healthy controls were analysed in a dual approach: (i) chemical analysis using gas chromatography/mass spectrometry (GC-MS) and (ii) breath-print analysis using an array of nanomaterial-based sensors, combined with a statistical algorithm. RESULTS: Gas chromatography/mass spectrometry identified ethanol, 2-propenenitrile and undecane as potential markers for HNSCC and/or benign tumours of the head and neck. The sensor-array-based breath-prints could clearly distinguish HNSCC both from benign tumours and from healthy states. Within the HNSCC group, patients could be classified according to tumour site and stage. CONCLUSIONS: We have demonstrated the feasibility of a breath test for a specific, clinically interesting application: distinguishing HNSCC from tumour-free or benign tumour states, as well as for staging and locating HNSCC. The sensor array used here could form the basis for the development of an urgently needed non-invasive, cost-effective, fast and reliable point-of-care diagnostic/screening tool for HNSCC.