Plasma proteomics identify biomarkers predicting Parkinson’s disease up to 7 years before symptom onset
Moving along towards neuroprotection and even prevention of Parkinson’s disease (PD), we need to identify and validate biomarkers to support clinical diagnosis and clinical trials. The main hurdles are the typically late diagnosis and the lack of objective biomarkers enabling early diagnosis and reliable readouts in clinical trials.
Biomarkers can also help us to identify new pathways and targets for a better molecular understanding and treatment of the disease. Blood is the ultimate biomarker matrix: it is easy to collect and process under standardized conditions (by technicians and study nurses, for example). In recent years, studies have shown that there is a lot of peripheral pathology in PD (possibly early on), which should be reflected in peripheral samples.
Therefore, our research shifted from focusing on cerebrospinal fluid to the more accessible blood samples, while also concentrating more on early and even pre-motor diagnosis, and more recently, population-based cohorts.
The most recently published study from our group was initiated by last author Brit Mollenhauer, and Claudia Trenkwalder. For this study, peripheral blood samples were collected from two independent cohorts from our de novo Parkinson’s disease (DeNoPa) cohort, which is a prospective, longitudinal, single-center study from the Paracelsus-Elena-Klinik in Kassel, Germany, comprising deeply clinically phenotyped PD subjects, matched healthy controls (HC), and subjects with isolated REM-sleep behavior disorder (iRBD)— the strongest predictor of a neuronal synuclein disease like PD. We confirmed iRBD using state-of-the-art video-recorded polysomnography. We also added blood samples from independently collected drug-naïve PD subjects and other neurological disorders (OND) upon clinical investigation.
The translational mass spectrometry research group from the University College London, UK, led by Kevin Mills, applied state-of-the-art mass spectrometry proteomic phenotyping to identify blood biomarkers in the peripheral blood samples of our patients and controls. In the unbiased discovery phase (phase 0) involving 20 blood samples (10 HC, 10 PD), we identified proteins, suggesting an early inflammatory pattern in blood. In the validation phase (phase I), we built and applied a high-throughput and targeted proteomic assay to more than 100 blood samples from the independent validation cohort (99 PD, 36 HC, 18 iRBD, 41 OND).
The results led to a refined targeted proteomic panel including a multiplex of the reliably measured biomarkers. We analyzed this panel of 32 proteins in the DeNoPa cohort (phase II) with iRBD, and available follow-up sampling of up to 10 years.
Using this approach, we established a targeted multiplexed mass spectrometry assay in peripheral blood. The machine-learning model accurately identified all PD subjects and classified and predicted 79% of the phenoconverters from iRBD to PD or dementia with Lewy bodies up to 7 years before motor symptom onset. This was based on the analysis of the expression of these eight proteins: Granulin precursor (GRN), Mannan-binding-lectin-serine-peptidase-2 (MASP2), Endoplasmatic-reticulum-chaperone-BiP (HSPA5), Prostaglandin-H2-D-isomerase (PDGDS), Intercellular-adhesion molecule- 1 (ICAM1), Complement C3 (C3), Dickkopf-WNT-signalling pathway-inhibitor-3 (DKK3), and Plasma-protease-C1-inhibitor (SERPING1), all of which are involved in potential protective and detrimental pathways with respect to α-synuclein aggregation and dopaminergic cell loss.
By calculating correlations with clinical parameters such as the UPDRS and the MMSE, we found associations between these and multiple markers, including DKK3, PPP3CB, and C3, indicating that downregulation of Wnt-signalling pathways and increased activity of the complement cascade correlated with higher symptom severity scores and lower cognitive performance. Furthermore, we identified potential PD patients — based on the Neuronal α-Synuclein Disease biological definition and Integrated Staging System stage 2 — up to 7 years before the onset of motor PD by analyzing eight proteins in blood samples. This is ONE first small step towards a blood biomarker.
As the study was not powered to analyze whether the biomarker panel can predict time to progression to motor PD, the identified proteome panel still needs further thorough and independent validation. In addition, our proteomic approach does not assess the underlying cellular mechanisms involved. Therefore, the next step would be to analyze collected immune cells of study subjects, a project that has already been launched by first co-author Michael Bartl. This biomarker panel identifies interesting new pathways to move along and could eventually serve as a screening tool for high-risk subjects for future prevention trials.