Mazzatenta Andrea, Pokorski Mieczyslaw, Sartucci Ferdinando, Domenici Luciano, Di Giulio Camillo
Physiology and Physiopathology Section, Department of Neuroscience, Imaging and Clinical Science, University of Chieti-Pescara 'G. d'Annunzio', Chieti, Italy; Neuroscience Institute, CNR-Pisa; Department of Clinical and Experimental Medicine, Unit of Neurology, Pisa University Medical School, Pisa, Italy.
Public Higher Medical Professional School, Opole, Poland; Institute of Psychology, Opole University, Opole, Poland.
Respir Physiol Neurobiol. 2015 Apr;209:81-4. doi: 10.1016/j.resp.2014.10.001. Epub 2014 Oct 13.
Alzheimer's disease (AD) is a profoundly life changing condition and once diagnosis occurs, this is typically at a relatively late stage into the disease process. Therefore, a shift to earlier diagnosis, which means several decades before the onset of the typical manifestation of the disease, will be an important step forward for the patient. A promising diagnostic and screening tool to answer this purpose is represented by breath and exhaled volatile organic compounds (VOCs) analysis. In fact, human exhaled breath contains several thousand of VOCs that vary in abundance and number in correlation with the physiological status. The exhaled VOCs reflect the metabolism, including the neuronal ones, in healthy and pathological conditions. A growing number of studies clearly demonstrate the effectiveness of VOCs analysis in identifying pathologies, including neurodegenerative diseases. In the present study we recorded, in real time, breath parameters and exhaled VOCs. We were able to demonstrate a significant alteration in breath parameters induced by the pathology of AD. Further, we provide the putative VOCs fingerprint of AD. These vital findings are an important step toward the early diagnosis of AD.
阿尔茨海默病（AD）是一种会深刻改变生活的疾病，一旦确诊，通常已处于疾病进程的相对晚期。因此，向早期诊断的转变，即在该病典型症状出现前几十年进行诊断，对患者来说将是重要的进步。一种有望用于此目的的诊断和筛查工具是呼吸及呼出挥发性有机化合物（VOCs）分析。事实上，人体呼出的气体含有数千种VOCs，其丰度和数量会随生理状态而变化。呼出的VOCs反映了健康和病理状态下的新陈代谢，包括神经元的新陈代谢。越来越多的研究清楚地证明了VOCs分析在识别包括神经退行性疾病在内的各种病症方面的有效性。在本研究中，我们实时记录了呼吸参数和呼出的VOCs。我们能够证明AD病理导致呼吸参数发生显著改变。此外，我们提供了AD的推定VOCs指纹图谱。这些重要发现是迈向AD早期诊断的重要一步。
