South Korean scientists have developed a saliva-based technology that could improve the early detection of major neurological disorders, including epilepsy, Parkinson’s disease, and schizophrenia.
The method analyses structural changes in proteins associated with these conditions using only a small saliva sample. Researchers say the approach could reduce reliance on invasive procedures such as blood tests and cerebrospinal fluid analysis, as well as expensive imaging techniques like PET scans.
The study was led by Dr Sung-Gyu Park of the Advanced Bio and Healthcare Materials Research Division at the Korea Institute of Materials Science (KIMS). The project involved collaboration with Professor Ho Sang Jung’s team at Korea University and researchers from the College of Medicine at The Catholic University of Korea. Clinical validation was conducted with St. Vincent’s Hospital.
The findings were published online on 24 January in the journal Advanced Materials, which has an impact factor of 26.8.
The research introduces the Galvanic Molecular Entrapment SERS platform. The system combines galvanic replacement with surface enhanced Raman scattering to capture and amplify biomolecular signals.
It uses nanostructures made of copper oxide and gold. When proteins are captured within these structures, plasmonic hotspots form around them. These hotspots amplify weak Raman signals of biomolecules by more than one billion times, allowing researchers to detect subtle structural changes in proteins.
One example is the shift from monomers to fibrils, a process known as protein fibrillation. Such structural changes are key pathological indicators in many neurological disorders but have been difficult to measure reliably using conventional methods.
The team analysed saliva samples from 67 individuals, including 13 patients with epilepsy, 21 patients with schizophrenia, 10 patients with Parkinson’s disease, and 23 healthy controls.
The Parkinson’s cases were inferred from the total group of 44 neurological patients compared with the control group.
Researchers applied a logistic regression model to the SERS spectral data to classify the samples. The model achieved overall accuracy above 90% and reached up to 98% when distinguishing specific disorders. Some reports indicate an overall classification accuracy of 93.94% across the conditions.
The researchers attribute this performance to their focus on structural changes in neuroproteins rather than simply measuring protein concentrations, an approach they describe as rare in the field.
Dr Sung-Gyu Park, principal researcher at KIMS, said: “An era has begun in which brain disease conditions can be assessed through simple saliva analysis without the need for costly PET imaging or cerebrospinal fluid testing. As the work has been published in a top-tier international journal, the originality and innovation of the technology have now been formally recognized worldwide.”
Professor Ho Sang Jung of Korea University said: “Given its non-invasive and low-cost nature, the technology holds significant potential for expansion beyond hospital outpatient settings to include home-based diagnostic devices.”
The research team plans to advance commercialisation through portable Raman sensor based point of care devices and pursue technology transfer to medical and life science companies.
Funding was provided by the Ministry of Science and ICT through the KIMS basic research programme and the NST Global TOP Strategic Research Group Program.
Experts say the technology could support more accessible diagnostics for neurological conditions, where early intervention can improve patient outcomes. Further validation with larger patient groups will be needed, but the platform’s sensitivity and specificity suggest it may be capable of detecting protein changes linked to brain disorders before symptoms become severe.