| Mar 05, 2026 |
Saliva based diagnostic platform detects brain disorders with over 90 percent accuracy
Researchers developed a saliva based SERS platform that detects epilepsy, Parkinson's disease, and schizophrenia by analyzing protein structural changes with up to 98% accuracy.
(Nanowerk News) A collaborative research team in South Korea has developed a sensor platform that can identify epilepsy, Parkinson's disease, and schizophrenia from a single saliva sample, eliminating the need for blood draws or invasive cerebrospinal fluid collection. The saliva based diagnostic technology, described as the first of its kind worldwide, uses surface-enhanced Raman spectroscopy (SERS) to detect structural changes in disease-related proteins.
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The work was published in Advanced Materials ("Label‐Free SERS Fingerprinting of Neuroprotein Conformational Dynamics in Human Saliva") and involved researchers from the Korea Institute of Materials Science (KIMS), Korea University, and the College of Medicine at The Catholic University of Korea.
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Key Findings
- The platform classified epilepsy, schizophrenia, and Parkinson's disease from saliva with accuracy exceeding 90%, reaching as high as 98%.
- It detects structural changes in proteins, specifically fibrillation states, rather than relying on total protein concentration, a distinction described as a rare achievement globally.
- The technology amplifies weak Raman signals of biomolecules by more than a billion times using plasmonic hotspots formed on copper oxide and gold nanostructures.
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At the heart of the system is a Galvanic Molecular Entrapment (GME)–SERS platform. Unlike conventional diagnostic approaches that require blood samples or cerebrospinal fluid obtained through lumbar puncture, both costly and physically demanding procedures, this method works with a small volume of saliva.
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| Schematic illustration of saliva-based diagnosis of neurological disorders. By collecting only saliva samples, extremely weak Raman signals from neural proteins are significantly amplified using three-dimensional composite (AuS@CuO) nanostructured materials and subsequently analyzed through machine learning. This approach enables accurate differentiation and diagnosis of intractable neurological disorders such as Parkinson’s disease, schizophrenia, and epilepsy. (Image: Korea Institute of Materials Science)
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The platform relies on nanostructures composed of copper oxide and gold (Au–CuO) that naturally generate plasmonic hotspots as proteins are captured on their surface. These hotspots amplify the inherently weak Raman signals produced by biomolecules by a factor exceeding one billion, making it possible to resolve fine-grained molecular information that standard diagnostic techniques cannot access.
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A critical capability of the platform is its sensitivity to protein fibrillation, the process by which proteins shift from their normal monomeric form into aggregated fibril structures. Abnormal protein aggregation is a hallmark of several neurological conditions, and the ability to distinguish between monomers and fibrils in a saliva sample represents a fundamental departure from conventional diagnostics, which typically measure overall protein concentration without resolving structural detail.
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The research team validated the platform using clinical samples collected in collaboration with St. Vincent's Hospital. Saliva from 44 patients diagnosed with epilepsy, schizophrenia, or Parkinson's disease and 23 healthy controls was analyzed. Classification accuracy exceeded 90% across the three conditions and reached up to 98%, confirming the platform's ability to differentiate between distinct neurological disorders based on pathological protein signatures.
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Dr. Sung-Kyu Park, Principal Researcher at KIMS, stated, "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."
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Prof. Hosang Jung of Korea University added, "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."
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The study was led by Dr. Sung-Kyu Park of the Advanced Bio and Healthcare Materials Research Division at KIMS, alongside Prof. Hosang Jung's team at Korea University and researchers from The Catholic University of Korea's College of Medicine. The research was supported by the Ministry of Science and ICT through the KIMS basic research program and the NST Global TOP Strategic Research Group Program. The findings were published online on January 24 in Advanced Materials, which carries an impact factor of 26.8.
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Looking ahead, the team intends to develop portable Raman sensor-based point-of-care diagnostic devices and pursue technology transfer to companies in the medical and life-science sectors. If successfully commercialized, the platform could make routine neurological screening accessible outside traditional hospital settings, potentially enabling earlier intervention for conditions that currently depend on expensive imaging or invasive fluid sampling for diagnosis.
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SEO meta title: Saliva based diagnostic platform detects brain disorders with over 90 percent accuracy
Meta description: Researchers developed a saliva based SERS platform that detects epilepsy, Parkinson's disease, and schizophrenia by analyzing protein structural changes with up to 98% accuracy.
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