α-Synuclein Conformations in Plasma Distinguish Parkinson's Disease from Dementia with Lewy Bodies.

Spread and aggregation of misfolded α-synuclein (aSyn) within the brain is the pathologic hallmark of Lewy body diseases (LBD), including Parkinson's disease (PD) and dementia with Lewy bodies (DLB). While evidence exists for multiple aSyn protein conformations, often termed "strains" for their distinct biological properties, it is unclear whether PD and DLB result from aSyn strain differences, and biomarkers that differentiate PD and DLB are lacking. Moreover, while pathological forms of aSyn have been detected outside the brain ( e.g., in skin, gut, blood), the functional significance of these peripheral aSyn species is unclear. Here, we developed assays using monoclonal antibodies selective for two different aSyn species generated in vitro - termed Strain A and Strain B - and used them to evaluate human brain tissue, cerebrospinal fluid (CSF), and plasma, through immunohistochemistry, enzyme-linked immunoassay, and immunoblotting. Surprisingly, we found that plasma aSyn species detected by these antibodies differentiated individuals with PD vs. DLB in a discovery cohort (UPenn, n=235, AUC 0.83) and a multi-site replication cohort (Parkinson's Disease Biomarker Program, or PDBP, n=200, AUC 0.72). aSyn plasma species detected by the Strain A antibody also predicted rate of cognitive decline in PD. We found no evidence for aSyn strains in CSF, and ability to template aSyn fibrillization differed for species isolated from plasma vs. brain, and in PD vs. DLB. Taken together, our findings suggest that aSyn conformational differences may impact clinical presentation and cortical spread of pathological aSyn. Moreover, the enrichment of these aSyn strains in plasma implicates a non-central nervous system source.

GPNMB Biomarker Levels in GBA1 Carriers with Lewy Body Disorders.

BACKGROUND: The GPNMB single-nucleotide polymorphism rs199347 and GBA1 variants both associate with Lewy body disorder (LBD) risk. GPNMB encodes glycoprotein nonmetastatic melanoma protein B (GPNMB), a biomarker for GBA1-associated Gaucher's disease. OBJECTIVE: The aim of this study was to determine whether GPNMB levels (1) differ in LBD with and without GBA1 variants and (2) associate with rs199347 genotype. METHODS: We quantified GPNMB levels in plasma and cerebrospinal fluid (CSF) from 124 individuals with LBD with one GBA1 variant (121 plasma, 14 CSF), 631 individuals with LBD without GBA1 variants (626 plasma, 41 CSF), 9 neurologically normal individuals with one GBA1 variant (plasma), and 2 individuals with two GBA1 variants (plasma). We tested for associations between GPNMB levels and rs199347 or GBA1 status. RESULTS: GPNMB levels associate with rs199347 genotype in plasma (P = 0.022) and CSF (P = 0.007), but not with GBA1 status. CONCLUSIONS: rs199347 is a protein quantitative trait locus for GPNMB. GPNMB levels are unaltered in individuals carrying one GBA1 variant. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

GPNMB confers risk for Parkinson's disease through interaction with α-synuclein.

Many risk loci for Parkinson's disease (PD) have been identified by genome-wide association studies (GWASs), but target genes and mechanisms remain largely unknown. We linked the GWAS-derived chromosome 7 locus (sentinel single-nucleotide polymorphism rs199347) to GPNMB through colocalization analyses of expression quantitative trait locus and PD risk signals, confirmed by allele-specific expression studies in the human brain. In cells, glycoprotein nonmetastatic melanoma protein B (GPNMB) coimmunoprecipitated and colocalized with α-synuclein (aSyn). In induced pluripotent stem cell-derived neurons, loss of GPNMB resulted in loss of ability to internalize aSyn fibrils and develop aSyn pathology. In 731 PD and 59 control biosamples, GPNMB was elevated in PD plasma, associating with disease severity. Thus, GPNMB represents a PD risk gene with potential for biomarker development and therapeutic targeting.

Plasma MIA, CRP, and Albumin Predict Cognitive Decline in Parkinson's Disease.

OBJECTIVE: Using a multi-cohort, discovery-replication-validation design, we sought new plasma biomarkers that predict which individuals with Parkinson's disease (PD) will experience cognitive decline. METHODS: In 108 discovery cohort PD individuals and 83 replication cohort PD individuals, we measured 940 plasma proteins on an aptamer-based platform. Using proteins associated with subsequent cognitive decline in both cohorts, we trained a logistic regression model to predict which patients with PD showed fast (> = 1 point drop/year on Montreal Cognitive Assessment [MoCA]) versus slow (< 1 point drop/year on MoCA) cognitive decline in the discovery cohort, testing it in the replication cohort. We developed alternate assays for the top 3 proteins and confirmed their ability to predict cognitive decline - defined by change in MoCA or development of incident mild cognitive impairment (MCI) or dementia - in a validation cohort of 118 individuals with PD. We investigated the top plasma biomarker for causal influence by Mendelian randomization (MR). RESULTS: A model with only 3 proteins (melanoma inhibitory activity protein [MIA], C-reactive protein [CRP], and albumin) separated fast versus slow cognitive decline subgroups with an area under the curve (AUC) of 0.80 in the validation cohort. The individuals with PD in the validation cohort in the top quartile of risk for cognitive decline based on this model were 4.4 times more likely to develop incident MCI or dementia than those in the lowest quartile. Genotypes at MIA single nucleotide polymorphism (SNP) rs2233154 associated with MIA levels and cognitive decline, providing evidence for MIA's causal influence. CONCLUSIONS: An easily obtained plasma-based predictor identifies individuals with PD at risk for cognitive decline. MIA may participate causally in development of cognitive decline. ANN NEUROL 2022;92:255-269.

Characterization of Parkinson's disease using blood-based biomarkers: A multicohort proteomic analysis.

BACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative disease affecting about 5 million people worldwide with no disease-modifying therapies. We sought blood-based biomarkers in order to provide molecular characterization of individuals with PD for diagnostic confirmation and prediction of progression. METHODS AND FINDINGS: In 141 plasma samples (96 PD, 45 neurologically normal control [NC] individuals; 45.4% female, mean age 70.0 years) from a longitudinally followed Discovery Cohort based at the University of Pennsylvania (UPenn), we measured levels of 1,129 proteins using an aptamer-based platform. We modeled protein plasma concentration (log10 of relative fluorescence units [RFUs]) as the effect of treatment group (PD versus NC), age at plasma collection, sex, and the levodopa equivalent daily dose (LEDD), deriving first-pass candidate protein biomarkers based on p-value for PD versus NC. These candidate proteins were then ranked by Stability Selection. We confirmed findings from our Discovery Cohort in a Replication Cohort of 317 individuals (215 PD, 102 NC; 47.9% female, mean age 66.7 years) from the multisite, longitudinally followed National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) Cohort. Analytical approach in the Replication Cohort mirrored the approach in the Discovery Cohort: each protein plasma concentration (log10 of RFU) was modeled as the effect of group (PD versus NC), age at plasma collection, sex, clinical site, and batch. Of the top 10 proteins from the Discovery Cohort ranked by Stability Selection, four associations were replicated in the Replication Cohort. These blood-based biomarkers were bone sialoprotein (BSP, Discovery false discovery rate [FDR]-corrected p = 2.82 × 10-2, Replication FDR-corrected p = 1.03 × 10-4), osteomodulin (OMD, Discovery FDR-corrected p = 2.14 × 10-2, Replication FDR-corrected p = 9.14 × 10-5), aminoacylase-1 (ACY1, Discovery FDR-corrected p = 1.86 × 10-3, Replication FDR-corrected p = 2.18 × 10-2), and growth hormone receptor (GHR, Discovery FDR-corrected p = 3.49 × 10-4, Replication FDR-corrected p = 2.97 × 10-3). Measures of these proteins were not significantly affected by differences in sample handling, and they did not change comparing plasma samples from 10 PD participants sampled both on versus off dopaminergic medication. Plasma measures of OMD, ACY1, and GHR differed in PD versus NC but did not differ between individuals with amyotrophic lateral sclerosis (ALS, n = 59) versus NC. In the Discovery Cohort, individuals with baseline levels of GHR and ACY1 in the lowest tertile were more likely to progress to mild cognitive impairment (MCI) or dementia in Cox proportional hazards analyses adjusting for age, sex, and disease duration (hazard ratio [HR] 2.27 [95% CI 1.04-5.0, p = 0.04] for GHR, and HR 3.0 [95% CI 1.24-7.0, p = 0.014] for ACY1). GHR's association with cognitive decline was confirmed in the Replication Cohort (HR 3.6 [95% CI 1.20-11.1, p = 0.02]). The main limitations of this study were its reliance on the aptamer-based platform for protein measurement and limited follow-up time available for some cohorts. CONCLUSIONS: In this study, we found that the blood-based biomarkers BSP, OMD, ACY1, and GHR robustly associated with PD across multiple clinical sites. Our findings suggest that biomarkers based on a peripheral blood sample may be developed for both disease characterization and prediction of future disease progression in PD.