Early diagnosis is crucial to slowing the progression of Parkinson's disease as much as possible. The existing diagnostic tools that make this possible can be very expensive and subject to subjective assessments. Chinese scientists have been researching an affordable alternative and appear to have succeeded. However, the technology behind “earwax diagnostics” is still in its infancy.
Researchers in Analytical Chemistry have developed an innovative and affordable method for detecting Parkinson's disease at an early stage using cerumen, or earwax, which consists of a mixture of shed skin flakes, sebum and hairs produced by glands in the ear canal.
Analysis of volatile organic compounds
The method involves the analysis of volatile organic compounds (VOCs) in earwax. In a cohort of 209 participants, including 108 Parkinson's patients, cerumen samples were collected and analysed using gas chromatography–mass spectrometry. Four of these volatile organic compounds, namely ethylbenzene, 4-ethyltoluene, pentanal and 2-pentadecyl-1,3-dioxolane, showed significant differences between patients and controls and are therefore, according to the researchers, potential PD biomarkers.
Based on these chemical profiles, the researchers developed an Artificially Intelligent Olfactory (AIO) system. This model mimics the human sense of smell and has been trained on the VOC data from earwax. In validation tests, the AIO screening distinguished between samples from people with and without Parkinson's disease with 94 percent accuracy. Unlike sebum (oil) from the skin, which can be affected by air pollution and moisture, earwax provides a protected environment in which disease-related metabolic changes (such as neurodegeneration, systemic inflammation and oxidative stress) are better preserved.
Follow-up research
Although this one-off, small-scale study in China is a groundbreaking proof of concept, the authors emphasise the need for extensive follow-up research. We are now going to test in multiple centres, different stages of Parkinson's disease and diverse ethnic groups to confirm its practical value," said lead researcher Hao Dong. If the results are positive, the combination of earwax profiling and AI screening could become a method for early Parkinson's detection that can even be performed by a general practitioner.
Early diagnosis could ultimately lead to targeted interventions, lower healthcare costs and better patient outcomes. By linking an everyday biological sample to advanced AI analysis, this method fits seamlessly with the trend towards affordable, non-invasive diagnostics in neurology. With the global prevalence of Parkinson's disease on the rise, earwax-based screening could offer a scalable solution to detect the disease earlier and more accurately than ever before.
Early Parkinson's diagnosis
A great deal of research is being conducted worldwide into methods for detecting Parkinson's at the earliest possible stage. Earlier this year, researchers at the Cleveland Clinic Genome Centre presented an innovative application of AI-driven systems biology to identify risk genes for Parkinson's disease. By linking genetic variants to brain-specific DNA and protein interaction data, they discovered which genes are affected by changes in non-coding DNA regions. Known genes such as SNCA and LRRK2 were confirmed as key players in neuroinflammation.
Another development in this context was the discovery that the retinas of people with Parkinson's disease respond differently to light stimuli than those of healthy subjects. In a study, electroretinography (using an electrode on the lower eyelid) was used to measure the retinal response in 20 recently diagnosed patients and an age-matched healthy control group. Clear differences were found, suggesting that retinal examination could serve as a non-invasive biomarker for early Parkinson's detection.
