Blood Markers of Inflammation, Neurodegeneration, and Cardiovascular Risk in Early Parkinson's Disease

Proximity Elongation Assay and ELISA for the Identification of Serum Diagnostic Biomarkers in Parkinson's Disease and Progressive Supranuclear Palsy

Clinical differentiation of progressive supranuclear palsy (PSP) from Parkinson's disease (PD) is challenging due to overlapping phenotypes and late onset of PSP specific symptoms, highlighting the need for easily assessable biomarkers. We used proximity elongation assay (PEA) to analyze 460 proteins in serum samples from 46 PD, 30 PSP patients, and 24 healthy controls. ANCOVA was used to identify the most promising proteins and machine learning (ML) XGBoost and random forest algorithms to assess their classification performance. Promising proteins were also quantified by ELISA. Moreover, correlations between serum biomarkers and biological and clinical features were investigated. We identified five proteins (TFF3, CPB1, OPG, CNTN1, TIMP4) showing different levels between PSP and PD, which achieved good performance (AUC: 0.892) when combined by ML. On the other hand, when the three most significant biomarkers (TFF3, CPB1 and OPG) were analyzed by ELISA, there was no difference between groups. Serum levels of TFF3 positively correlated with age in all subjects' groups, while for OPG and CPB1 such a correlation occurred in PSP patients only. Moreover, CPB1 positively correlated with disease severity in PD, while no correlations were observed in the PSP group. Overall, we identified CPB1 correlating with PD severity, which may support clinical staging of PD. In addition, our results showing discrepancy between PEA and ELISA technology suggest that caution should be used when translating proteomic findings into clinical practice.

Parkinson's disease is characterized by vitamin B6-dependent inflammatory kynurenine pathway dysfunction

Parkinson's disease (PD) is a complex multisystem disorder clinically characterized by motor, non-motor, and premotor manifestations. Pathologically, PD involves neuronal loss in the substantia nigra, striatal dopamine deficiency, and accumulation of intracellular inclusions containing aggregates of α-synuclein. Recent studies demonstrate that PD is associated with dysregulated metabolic flux through the kynurenine pathway (KP), in which tryptophan is converted to kynurenine (KYN), and KYN is subsequently metabolized to neuroactive compounds quinolinic acid (QA) and kynurenic acid (KA). This multicenter study used highly sensitive liquid chromatography-tandem mass-spectrometry to compare blood and cerebral spinal fluid (CSF) KP metabolites between 158 unimpaired older adults and 177 participants with PD. Results indicate that increased neuroexcitatory QA/KA ratio in both plasma and CSF of PD participants associated with peripheral and cerebral inflammation and vitamin B6 deficiency. Furthermore, increased QA tracked with CSF tau and severity of both motor and non-motor PD clinical dysfunction. Importantly, plasma and CSF kynurenine metabolites classified PD participants with a high degree of accuracy (AUC = 0.897). Finally, analysis of metabolite data revealed subgroups with distinct KP profiles, and these were subsequently found to display distinct PD clinical features. Together, these data further support the hypothesis that the KP serves as a site of brain and periphery crosstalk, integrating B-vitamin status, inflammation and metabolism to ultimately influence PD clinical manifestation.

Vascular Impairment, Muscle Atrophy, and Cognitive Decline: Critical Age-Related Conditions

The triad of vascular impairment, muscle atrophy, and cognitive decline represents critical age-related conditions that significantly impact health. Vascular impairment disrupts blood flow, precipitating the muscle mass reduction seen in sarcopenia and the decline in neuronal function characteristic of neurodegeneration. Our limited understanding of the intricate relationships within this triad hinders accurate diagnosis and effective treatment strategies. This review analyzes the interrelated mechanisms that contribute to these conditions, with a specific focus on oxidative stress, chronic inflammation, and impaired nutrient delivery. The aim is to understand the common pathways involved and to suggest comprehensive therapeutic approaches. Vascular dysfunctions hinder the circulation of blood and the transportation of nutrients, resulting in sarcopenia characterized by muscle atrophy and weakness. Vascular dysfunction and sarcopenia have a negative impact on physical function and quality of life. Neurodegenerative diseases exhibit comparable pathophysiological mechanisms that affect cognitive and motor functions. Preventive and therapeutic approaches encompass lifestyle adjustments, addressing oxidative stress, inflammation, and integrated therapies that focus on improving vascular and muscular well-being. Better understanding of these links can refine therapeutic strategies and yield better patient outcomes. This study emphasizes the complex interplay between vascular dysfunction, muscle degeneration, and cognitive decline, highlighting the necessity for multidisciplinary treatment approaches. Advances in this domain promise improved diagnostic accuracy, more effective therapeutic options, and enhanced preventive measures, all contributing to a higher quality of life for the elderly population.

Tilorone mitigates the propagation of α-synucleinopathy in a midbrain-like organoid model

BACKGROUND

Parkinson's disease (PD) is a neurodegenerative condition characterized by the loss of dopaminergic neurons and the accumulation of Lewy-body protein aggregates containing misfolded α-synuclein (α-syn) in a phosphorylated form. The lack of effective models for drug screens has hindered drug development studies for PD. However, the recent development of in vitro brain-like organoids provides a new opportunity for evaluating therapeutic agents to slow the progression of this chronic disease.

METHODS

In this study, we used a 3D brain-like organoid model to investigate the potential of repurposing Tilorone, an anti-viral drug, for impeding the propagation of α-synucleinopathy. We assessed the effect of Tilorone on the uptake of fluorescently labeled α-syn preformed fibrils (sPFF) and sPFF-induced apoptosis using confocal microscopy. We also examined Tilorone's impact on the phosphorylation of endogenous α-syn induced by pathogenic sPFF by immunoblotting midbrain-like organoid extracts. Additionally, quantitative RT-PCR and proteomic profiling of sPFF-treated organoids were conducted to evaluate the global impact of Tilorone treatment on tissue homeostasis in the 3D organoid model.

RESULTS

Tilorone inhibits the uptake of sPFF in both mouse primary neurons and human midbrain-like organoids. Tilorone also reduces the phosphorylation of endogenous α-syn induced by pathogenic α-syn fibrils and mitigates α-syn fibril-induced apoptosis in midbrain-like organoids. Proteomic profiling of fibril-treated organoids reveals substantial alterations in lipid homeostasis by α-syn fibrils, which are reversed by Tilorone treatment. Given its safety profile in clinics, Tilorone may be further developed as a therapeutic intervention to alleviate the propagation of synucleinopathy in PD patients.

Sex-dependent effects of antimicrobials and lipopolysaccharide on blood-brain-barrier permeability in pubertal male and female CD1 mice

Exposure to stressors during puberty can disrupt normal development and possibly increase susceptibility to neurodegenerative disorders later in life. However, the mechanisms underlying the relationship between pubertal stress exposure and neurodegeneration remain unclear. As such, the current study was designed to examine the effects of pubertal antimicrobial (AMNS) and lipopolysaccharide (LPS) treatments on intestinal and blood-brain-barrier (BBB) permeability in male and female mice. Moreover, we also examined the sex-specific effects of pubertal AMNS and LPS treatments on gross motor activity, heart rate, and core body temperature. At four weeks of age, male and female CD1 mice were implanted with the G2 HR E-Mitter telemetry system. At five weeks of age, mice received 200 μL of broad-spectrum antimicrobial or water, through oral gavage, twice daily for seven days. Mice received an intraperitoneal injection of either saline or LPS at six weeks of age. BBB and intestinal permeability were examined 24 h, 72 h, and one week post-LPS/saline treatment. Telemetric data was collected for 48 h post-LPS/saline treatment. The results showed that pubertal AMNS and LPS treatments increased sickness behaviours and decreased body temperature and heart rate, in a sex-dependent manner. Furthermore, pubertal AMNS and LPS treatments resulted in sex-dependent regional increases in BBB permeability 24 h and 72 h post-LPS/saline treatment, while global increases in BBB permeability were only observed one week post-LPS/saline treatment. These results further our understanding of the combined effects of AMNS and LPS treatments on physiology and on the enduring negative changes observed following pubertal exposure to stressors.

Parkinson's disease CA2-CA3 hippocampal atrophy is accompanied by increased cholinergic innervation in patients with normal cognition but not in patients with mild cognitive impairment

Although brain cholinergic denervation has been largely associated with cognitive decline in patients with Parkinson's disease (PD), new evidence suggests that cholinergic upregulation occurs in the hippocampus of PD patients without cognitive deficits. The specific hippocampal sectors and potential mechanisms of this cholinergic compensatory process have been further studied here, using MRI volumetry and morphometry coupled with molecular imaging using the PET radiotracer [18F]-Fluoroethoxybenzovesamicol ([18F]-FEOBV). Following a thorough screening procedure, 18 participants were selected and evenly distributed in three groups, including cognitively normal PD patients (PD-CN), PD patients with mild cognitive impairment (PD-MCI), and healthy volunteers (HV). Participants underwent a detailed neuropsychological assessment, structural MRI, and PET imaging with [18F]-FEOBV. Basal forebrain Ch1-Ch2 volumes were measured using stereotaxic mapping. Hippocampal subfields were automatically defined using the MAGeT-Brain segmentation algorithm. Cholinergic innervation density was quantified using [18F]-FEOBV uptake. Compared with HV, both PD-CN and PD-MCI displayed significantly reduced volumes in CA2-CA3 bilaterally. We found no other hippocampal subfield nor Ch1-Ch2 volume differences between the three groups. PET imaging revealed higher [18F]-FEOBV uptake in CA2-CA3 of the PD-CN compared with HV or PD-MCI. A positive correlation was observed between cognitive performances and [18F]-FEOBV uptake in the right CA2-CA3 subfield. Reduced volume, together with increased [18F]-FEOBV uptake, were observed specifically in the CA2-CA3 hippocampal subfields. However, while the volume change was observed in both PD-CN and PD-MCI, increased [18F]-FEOBV uptake was present only in the PD-CN group. This suggests that a cholinergic compensatory process takes place in the atrophied CA2-CA3 hippocampal subfields and might underlie normal cognition in PD.

Neuroimaging and fluid biomarkers in Parkinson's disease in an era of targeted interventions

A major challenge in Parkinson's disease is the variability in symptoms and rates of progression, underpinned by heterogeneity of pathological processes. Biomarkers are urgently needed for accurate diagnosis, patient stratification, monitoring disease progression and precise treatment. These were previously lacking, but recently, novel imaging and fluid biomarkers have been developed. Here, we consider new imaging approaches showing sensitivity to brain tissue composition, and examine novel fluid biomarkers showing specificity for pathological processes, including seed amplification assays and extracellular vesicles. We reflect on these biomarkers in the context of new biological staging systems, and on emerging techniques currently in development.

Plasma proteomics identify biomarkers predicting Parkinson's disease up to 7 years before symptom onset

Parkinson's disease is increasingly prevalent. It progresses from the pre-motor stage (characterised by non-motor symptoms like REM sleep behaviour disorder), to the disabling motor stage. We need objective biomarkers for early/pre-motor disease stages to be able to intervene and slow the underlying neurodegenerative process. Here, we validate a targeted multiplexed mass spectrometry assay for blood samples from recently diagnosed motor Parkinson's patients (n = 99), pre-motor individuals with isolated REM sleep behaviour disorder (two cohorts: n = 18 and n = 54 longitudinally), and healthy controls (n = 36). Our machine-learning model accurately identifies all Parkinson patients and classifies 79% of the pre-motor individuals up to 7 years before motor onset by analysing the expression of eight proteins-Granulin precursor, Mannan-binding-lectin-serine-peptidase-2, Endoplasmatic-reticulum-chaperone-BiP, Prostaglaindin-H2-D-isomaerase, Interceullular-adhesion-molecule-1, Complement C3, Dickkopf-WNT-signalling pathway-inhibitor-3, and Plasma-protease-C1-inhibitor. Many of these biomarkers correlate with symptom severity. This specific blood panel indicates molecular events in early stages and could help identify at-risk participants for clinical trials aimed at slowing/preventing motor Parkinson's disease.

Association Between Neuroinflammation and Parkinson's Disease: A Comprehensive Mendelian Randomization Study

The objective of the study is to determine the causal relationship and potential mechanisms between Parkinson's disease (PD) and neuroinflammatory and neurotoxic mediators. We conducted two-sample Mendelian randomization (2SMR) study and multivariable Mendelian randomization (MVMR) analysis to investigate the causality between PD and neuroinflammatory and neurotoxic mediators. The mediation analysis with MR was also conducted to determine the potential mediating effect of neuroinflammatory and neurotoxic mediators between asthma and PD. Genetically predicted levels of nine neuroinflammation were associated with changes in PD risk. The associations of PD with CCL24, galectin-3 levels, haptoglobin, and Holo-Transcobalamin-2 remained significant in multivariable analyses. The mediation analysis with MR revealed that asthma affects PD through CCL24 and galectin-3. The results showed neuroinflammation could affect the pathogenesis of PD. In the combined analysis of these nine variables, CCL24, galectin-3 levels, HP, and Holo-Transcobalamin-2 alone were found to be significant. Asthma plays an intermediary role through CCL24 and galectin-3 levels.

The Effect of Gut Microbiota-Targeted Interventions on Neuroinflammation and Motor Function in Parkinson's Disease Animal Models-A Systematic Review

Gut microbiome-targeted interventions such as fecal transplant, prebiotics, probiotics, synbiotics, and antibiotic gut depletion are speculated to be of potential use in delaying the onset and progression of Parkinson's disease by rebalancing the gut microbiome in the context of the gut-brain axis. Our study aims to organize recent findings regarding these interventions in Parkinson's disease animal models to identify how they affect neuroinflammation and motor outcomes. A systematic literature search was applied in PubMed, Web of Science, Embase, and SCOPUS for gut microbiome-targeted non-dietary interventions. Studies that investigated gut-targeted interventions by using in vivo murine PD models to follow dopaminergic cell loss, motor tests, and neuroinflammatory markers as outcomes were considered to be eligible. A total of 1335 studies were identified in the databases, out of which 29 were found to be eligible. A narrative systematization of the resulting data was performed, and the effect direction for the outcomes was represented. Quality assessment using the SYRCLE risk of bias tool was also performed. Out of the 29 eligible studies, we found that a significant majority report that the intervention reduced the dopaminergic cell loss (82.76%, 95% CI [64.23%, 94.15%]) produced by the induction of the disease model. Also, most studies reported a reduction in microglial (87.5%, 95% CI [61.65%, 98.45%]) and astrocytic activation (84,62%, 95% CI [54.55%, 98.08%]) caused by the induction of the disease model. These results were also mirrored in the majority (96.4% 95% CI [81.65%, 99.91%]) of the studies reporting an increase in performance in behavioral motor tests. A significant limitation of the study was that insufficient information was found in the studies to assess specific causes of the risk of bias. These results show that non-dietary gut microbiome-targeted interventions can improve neuroinflammatory and motor outcomes in acute Parkinson's disease animal models. Further studies are needed to clarify if these benefits transfer to the long-term pathogenesis of the disease, which is not yet fully understood. The study had no funding source, and the protocol was registered in the PROSPERO database with the ID number CRD42023461495.

Identification of cuproptosis-realated key genes and pathways in Parkinson's disease via bioinformatics analysis

INTRODUCTION

Parkinson's disease (PD) is the second most common worldwide age-related neurodegenerative disorder without effective treatments. Cuproptosis is a newly proposed conception of cell death extensively studied in oncological diseases. Currently, whether cuproptosis contributes to PD remains largely unclear.

METHODS

The dataset GSE22491 was studied as the training dataset, and GSE100054 was the validation dataset. According to the expression levels of cuproptosis-related genes (CRGs) and differentially expressed genes (DEGs) between PD patients and normal samples, we obtained the differentially expressed CRGs. The protein-protein interaction (PPI) network was achieved through the Search Tool for the Retrieval of Interacting Genes. Meanwhile, the disease-associated module genes were screened from the weighted gene co-expression network analysis (WGCNA). Afterward, the intersection genes of WGCNA and PPI were obtained and enriched using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, the key genes were identified from the datasets. The receiver operating characteristic curves were plotted and a PPI network was constructed, and the PD-related miRNAs and key genes-related miRNAs were intersected and enriched. Finally, the 2 hub genes were verified via qRT-PCR in the cell model of the PD and the control group.

RESULTS

525 DEGs in the dataset GSE22491 were identified, including 128 upregulated genes and 397 downregulated genes. Based on the PPI network, 41 genes were obtained. Additionally, the dataset was integrated into 34 modules by WGCNA. 36 intersection genes found from WGCNA and PPI were significantly abundant in 7 pathways. The expression levels of the genes were validated, and 2 key genes were obtained, namely peptidase inhibitor 3 (PI3) and neuroserpin family I member 1 (SERPINI1). PD-related miRNAs and key genes-related miRNAs were intersected into 29 miRNAs including hsa-miR-30c-2-3p. At last, the qRT-PCR results of 2 hub genes showed that the expressions of mRNA were up-regulated in PD.

CONCLUSION

Taken together, this study demonstrates the coordination of cuproptosis in PD. The key genes and miRNAs offer novel perspectives in the pathogenesis and molecular targeting treatment for PD.

Proximity extension assay-based proteomics studies in neurodegenerative disorders and multiple sclerosis

Neurodegenerative diseases impact the structure and operation of the nervous system, causing progressive and irreparable harm. Efforts for distinguishing neurodegenerative diseases in their early stages are continuing. Despite several biomarkers being identified, there is always search for more accurate and abundant ones. Additionally, it can be difficult to pinpoint the precise neurodegenerative disorder affecting a patient as the symptoms of these conditions frequently overlap. Numerous studies have shown that pathological changes occur years before clinical signs appear. Therefore, it is crucial to discover blood-based biomarkers for neurodegenerative diseases for easier and earlier diagnosis. Proximity extension assay is a unique proteomics method that uses antibodies linked to oligonucleotides for quantifying proteins with real-time PCR. Proximity extension assay can identify even low-quantity proteins using a small volume of specimens with increased sensitivity compared to conventional methods. In this article, we reviewed the employment of proximity extension assay technology to detect biomarkers or protein profiles for several neurodegenerative diseases.

Protein profile pattern analysis: A multifarious, in vitro diagnosis technique for universal screening

Universal health care is attracting increased attention nowadays, because of the large increase in population all over the world, and a similar increase in life expectancy, leading to an increase in the incidence of non-communicable (various cancers, coronary diseases, neurological and old-age-related diseases) and communicable diseases/pandemics like SARS-COVID 19. This has led to an immediate need for a healthcare technology that should be cost-effective and accessible to all. A technology being considered as a possible one at present is liquid biopsy, which looks for markers in readily available samples like body fluids which can be accessed non- or minimally- invasive manner. Two approaches are being tried now towards this objective. The first involves the identification of suitable, specific markers for each condition, using established methods like various Mass Spectroscopy techniques (Surface-Enhanced Laser Desorption/Ionization Mass Spectroscopy (SELDI-MS), Matrix-Assisted Laser Desorption/Ionization (MALDI-MS), etc., immunoassays (Enzyme-Linked Immunoassay (ELISA), Proximity Extension Assays, etc.) and separation methods like 2-Dimensional Polyacrylamide Gel Electrophoresis (2-D PAGE), Sodium Dodecyl-Sulfate Polyacrylamide Gel Electrophoresis (SDS-PAGE), Capillary Electrophoresis (CE), etc. In the second approach, no attempt is made the identification of specific markers; rather an efficient separation method like High-Performance Liquid Chromatography/ Ultra-High-Performance Liquid Chromatography (HPLC/UPLC) is used to separate the protein markers, and a profile of the protein pattern is recorded, which is analysed by Artificial Intelligence (AI)/Machine Learning (MI) methods to derive characteristic patterns and use them for identifying the disease condition. The present report gives a summary of the current status of these two approaches and compares the two in the use of their suitability for universal healthcare.

Mapping the human brain proteome: opportunities, challenges, and clinical potential

INTRODUCTION

Due to the segmented functions and complexity of the human brain, the characterization of molecular profiles within specific areas such as brain structures and biofluids is essential to unveil the molecular basis for structure specialization as well as the molecular imbalance associated with neurodegenerative and psychiatric diseases.

AREAS COVERED

Much of our knowledge about brain functionality derives from neurophysiological, anatomical, and transcriptomic approaches. More recently, laser capture and imaging proteomics, technological and computational developments in LC-MS/MS, as well as antibody/aptamer-based platforms have allowed the generation of novel cellular, spatial, and posttranslational dimensions as well as innovative facets in biomarker validation and druggable target identification.

EXPERT OPINION

Proteomics is a powerful toolbox to functionally characterize, quantify, and localize the extensive protein catalog of the human brain across physiological and pathological states. Brain function depends on multi-dimensional protein homeostasis, and its elucidation will help us to characterize biological pathways that are essential to properly maintain cognitive functions. In addition, comprehensive human brain pathological proteomes may be the basis in computational drug-repositioning methods as a strategy for unveiling potential new therapies in neurodegenerative and psychiatric disorders.

Peripheral immunity and risk of incident brain disorders: a prospective cohort study of 161,968 participants

Whether peripheral immunity prospectively influences brain health remains controversial. This study aims to investigate the longitudinal associations between peripheral immunity markers with incident brain disorders. A total of 161,968 eligible participants from the UK Biobank were included. We investigated the linear and non-linear effects of peripheral immunity markers including differential leukocytes counts, their derived ratios and C-reactive protein (CRP) on the risk of dementia, Parkinson's disease (PD), stroke, schizophrenia, bipolar affective disorder (BPAD), major depressive disorder (MDD) and anxiety, using Cox proportional hazard models and restricted cubic spline models. Linear regression models were used to explore potential mechanisms driven by brain structures. During a median follow-up of 9.66 years, 16,241 participants developed brain disorders. Individuals with elevated innate immunity markers including neutrophils, monocytes, platelets, neutrophil-to-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII) had an increased risk of brain disorders. Among these markers, neutrophils exhibited the most significant correlation with risk of dementia (hazard ratio 1.08, 95% confidence interval 1.04-1.12), stroke (HR 1.06, 95% CI 1.03-1.09), MDD (HR 1.13, 95% CI 1.10-1.16) and anxiety (HR 1.07, 95% CI 1.04-1.10). Subgroup analysis revealed age-specific and sex-specific associations between innate immunity markers with risk of dementia and MDD. Neuroimaging analysis highlighted the associations between peripheral immunity markers and alterations in multiple cortical, subcortical regions and white matter tracts, typically implicated in dementia and psychiatric disorders. These findings support the hypothesis that neuroinflammation is important to the etiology of various brain disorders, offering new insights into their potential therapeutic approaches.

Inflammatory Blood Biomarkers Are Associated with Long-Term Clinical Disease Severity in Parkinson's Disease

An altered immune response has been identified as a pathophysiological factor in Parkinson's disease (PD). We aimed to identify blood immunity-associated proteins that discriminate PD from controls and that are associated with long-term disease severity in PD patients. Immune response-derived proteins in blood plasma were measured using Proximity Extension Technology by OLINK in a cohort of PD patients (N = 66) and age-matched healthy controls (N = 52). In a selection of 30 PD patients, we evaluated changes in protein levels 7-10 years after the baseline and assessed correlations with motor and cognitive assessments. Data from the Parkinson's Disease Biomarkers Program (PDBP) cohort and the Parkinson's Progression Markers Initiative (PPMI) cohort were used for independent validation. PD patients showed an altered immune response compared to controls based on a panel of four proteins (IL-12B, OPG, CXCL11, and CSF-1). The expression levels of five inflammation-associated proteins (CCL23, CCL25, TNFRSF9, TGF-alpha, and VEGFA) increased over time in PD and were partially associated with more severe motor and cognitive symptoms at follow-up. Increased CCL23 levels were associated with cognitive decline and the APOE4 genotype. Our findings provide further evidence for an altered immune response in PD that is associated with disease severity in PD over a long period of time.

No Correlation between Plasma GPNMB Levels and Multiple System Atrophy in Chinese Cohorts

BACKGROUND

Glycoprotein nonmetastatic melanoma protein B (GPNMB) has been demonstrated to mediate pathogenicity in Parkinson's disease (PD) through interactions with α-synuclein, and plasma GPNMB tended to be a novel biomarker for PD.

OBJECTIVE

The goal of this study was to investigate whether plasma GPNMB could act as a potential biomarker for the clinical diagnosis and severity monitoring of multiple system atrophy (MSA), another typical synucleinopathy.

METHODS

Plasma GPNMB levels in patients with MSA, patients with PD, and healthy control subjects (HCs) were quantified using enzyme-linked immunosorbent assays.

RESULTS

A total of 204 patients with MSA, 65 patients with PD, and 207 HCs were enrolled. The plasma GPNMB levels in patients with MSA were similar to those in HCs (P = 0.251) but were significantly lower than those in patients with PD (P = 0.003). Moreover, there was no significant correlation detected between the plasma GPNMB levels and disease severity scores of patients with MSA.

CONCLUSIONS

No evidence was detected for the biomarker potential of plasma GPNMB in MSA. © 2023 International Parkinson and Movement Disorder Society.

Inflammatory Biomarkers in Newly Diagnosed Patients With Parkinson Disease and Related Neurodegenerative Disorders

BACKGROUND AND OBJECTIVES

Neuroinflammation contributes to Parkinson disease (PD) pathology, and inflammatory biomarkers may aid in PD diagnosis. Proximity extension assay (PEA) technology is a promising method for multiplex analysis of inflammatory markers. Neuroinflammation also plays a role in related neurodegenerative diseases, such as dementia with Lewy bodies (DLB) and Alzheimer disease (AD). The aim of this work was to assess the value of inflammatory biomarkers in newly diagnosed patients with PD and in patients with DLB and AD.

METHODS

Patients from the Norwegian ParkWest and Dementia Study of Western Norway longitudinal cohorts (PD, n = 120; DLB, n = 15; AD, n = 27) and 44 normal controls were included in this study. A PEA inflammation panel of 92 biomarkers was measured in the CSF. Disease-associated biomarkers were identified using elastic net (EN) analysis. We assessed the discriminatory power of disease-associated biomarkers using receiver operating characteristic (ROC) curve analysis and estimated the optimism-adjusted area under the curve (AUC) using the bootstrapping method.

RESULTS

EN analysis identified 9 PEA inflammatory biomarkers (ADA, CCL23, CD5, CD8A, CDCP1, FGF-19, IL-18R1, IL-6, and MCP-2) associated with PD. Seven of the 9 biomarkers were included in a diagnostic panel, which was able to discriminate between those with PD and controls (optimism-adjusted AUC 0.82). Our 7-biomarker PD panel was also able to distinguish PD from DLB and from AD. In addition, 4 inflammatory biomarkers were associated with AD and included in a panel, which could distinguish those with AD from controls (optimism-adjusted AUC 0.87). Our 4-biomarker AD panel was also able to distinguish AD from DLB and from PD.

DISCUSSION

In our exploratory study, we identified a 7-biomarker panel for PD and a 4-biomarker panel for AD. Our findings indicate potential inflammation-related biomarker candidates that could contribute toward PD-specific and AD-specific diagnostic panels, which should be further explored in other larger cohorts.