Scientists achieve 95 percent accuracy detecting Parkinson’s with breakthrough test

Scientists have announced a breakthrough in Parkinson’s disease detection using a new immuno-infrared sensor (iRS) test that analyzes cerebrospinal fluid for protein misfolding, offering hope for earlier diagnosis of this progressive neurological condition. Study results were published in EMBO Molecular Medicine.

Researchers from Ruhr University Bochum’s PRODI Center for Protein Diagnostics developed the iRS test that identifies misfolded alpha-synuclein proteins in spinal fluid. The technology achieved 95% accuracy in distinguishing between individuals with and without Parkinson’s disease when tested across two independent studies involving 134 participants.

“Parkinson’s disease is characterized by the loss of dopaminergic nerve cells in the brain, which usually leads to increasing motor impairments as the symptoms progress,” explained Professor Klaus Gerwert, the study’s lead researcher and PRODI’s founding director.

The challenge with Parkinson’s diagnosis lies in timing. By the time characteristic symptoms like tremors and walking difficulties appear, more than half of the brain’s dopamine-producing cells have already died. The progressive nature of the condition means brain damage is often irreversible by the clinical diagnosis stage.

The iRS testing approach measures the structural changes in alpha-synuclein proteins, which transform from normal alpha-helical shapes to beta-sheet formations in Parkinson’s patients. The misfolded proteins eventually form larger complexes called oligomers, ultimately creating the familiar Lewy bodies found in Parkinson’s patients’ brains.

Unlike existing diagnostic methods, the iRS technology provides more than a simple positive or negative result. Researchers noted it measures a continuum of protein misfolding, potentially allowing doctors to track disease progression and treatment effectiveness over time.

The research team had previously applied this technology to Alzheimer’s disease detection, where it successfully predicted dementia risk up to 17 years before clinical diagnosis. The platform’s adaptation to Parkinson’s represents an important advance in neurological disease detection.

The study’s authors emphasize that early detection could enable interventions before significant neurological damage occurs. While current treatments focus on managing symptoms through dopamine supplements, earlier diagnosis might eventually support preventive therapies targeting protein misfolding before substantial cell loss happens.