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 inits 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.