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Your Ear Wax Can Reveal if You Have Parkinson's Disease
Your Ear Wax Can Reveal if You Have Parkinson's Disease

Newsweek

timea day ago

  • Health
  • Newsweek

Your Ear Wax Can Reveal if You Have Parkinson's Disease

Based on facts, either observed and verified firsthand by the reporter, or reported and verified from knowledgeable sources. Newsweek AI is in beta. Translations may contain inaccuracies—please refer to the original content. The levels of the natural bodily oil sebum in ear wax could be used to detect Parkinson's disease early, according to a new study. Changes in sebum have previously been linked with the neurodegenerative disorder, with those with the condition having sebum that gives off a characteristic smell. Furthermore, volatile organic compounds (VOCs) released by sebum are impacted by processes involved in the progression of Parkinson's, including neurodegeneration, oxidative stress and systemic inflammation. The stumbling block to making use of this information, however, has been than environmental factors like air pollution and humidity can also affect the composition of sebum, meaning that sampling from the skin may not provide reliable information. To get around this, chemists Hao Dong, Danhua Zhu and colleagues turned to ear wax—which can both be easily sampled but, coming from the skin in the ear canal, is protected from environmental alteration. A stock image of a woman using a cotton swab on her ear. A stock image of a woman using a cotton swab on her ear. fizkes/Getty Images In their study, the researchers collected ear wax samples from 209 people–108 of whom have received a Parkinson's diagnosis—and analyzed their composition using gas chromatography and mass spectrometry. Four of the VOCs detected in the ear wax of those with Parkinson's disease were found to significantly different to the VOCs in healthy subjects. (Specifically, the study concluded that ethylbenzene, 4-ethyltoluene, pentanal and 2-pentadecyl-1,3-dioxolane are potential biomarkers for Parkinson's disease.) Next, the team trained an artificial intelligence olfactory system to analyze VOC data. This system was able to categorize ear wax samples with 94 percent accuracy, with the researchers saying this could lead to a first-line screening tool for early-onset Parkinson's. Dong said: "This method is a small-scale single-center experiment in China. The next step is to conduct further research at different stages of the disease, in multiple research centers and among multiple ethnic groups, in order to determine whether this method has greater practical application value." Parkinson's disease is the second-most common neurodegenerative disorder in the U.S, after Alzheimer's disease. Symptoms of the condition include tremors, slow movement, stiffness and impaired balance—given Parkinson's progressive nature, these conditions gradually and increasingly impact a person's ability to walk, talk and swallow. Approximately 500,000 Americans are diagnosed with Parkinson's disease, most of whom are over the age of 60. However, it's thought that many people go undiagnosed for years. Indeed, some experts have suggested that as many as one million Americans could have the condition, according to the National Institute of Neurological Disorders and Stroke. The cost of treating Parkinson's disease is an estimated $14 billion each year—and with the number of diagnoses expected to double in the U.S. by 2040, early detection is key. Current testing methods typically entail clinical rating scales and neural imaging, but screening for the disease with ear wax samples could be relatively inexpensive in comparison, the ACS suggests. At present, most treatments can only slow the disease progression rather than curing it, but an earlier diagnosis could offer a window to prevent the progression prior to the onset of motor impairments. Do you have a tip on a health story that Newsweek should be covering? Do you have a question about Parkinson's? Let us know via health@ Reference Chen, X., Li, Y., Pan, C., Weng, S., Xie, X., Zhou, B., Dong, H., & Zhu, D. (2025). An Artificial Intelligence Olfactory-Based Diagnostic Model for Parkinson's Disease Using Volatile Organic Compounds from Ear Canal Secretions. Analytical Chemistry, 97(24), 12633–12641.

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