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.
Background: Observational studies in Parkinson’s disease (PD) have focused on relatively small numbers of research participants who are studied extensively. The Molecular Integration in Neurological Diagnosis Initiative at the University of Pennsylvania aims to characterize molecular and clinical features of PD in every patient in a large academic center. Objective: To determine the feasibility and interest in a global-capture biomarker research protocol. Additionally, to describe the clinical characteristics and GBA and LRRK2 variant carrier status among participants. Methods: All patients at UPenn with a clinical diagnosis of PD were eligible. Informed consent included options for access to the medical record, future recontact, and use of biosamples for additional studies. A blood sample and a completed questionnaire were obtained from participants. Targeted genotyping for four GBA and eight LRRK2 variants was performed, with plasma and DNA banked for future research. Results: Between September 2018 and December 2019, 704 PD patients were approached for enrollment; 652 (92.6%) enrolled, 28 (3.97%) declined, and 24 (3.41%) did not meet eligibility criteria. Median age was 69 (IQR 63_75) years, disease duration was 5.41 (IQR 2.49_9.95) years, and 11.10%of the cohort was non-white. Disease risk-associated variants in GBA were identified in 39 participants (5.98%) and in LRRK2 in 16 participants (2.45%). Conclusions: We report the clinical and genetic characteristics of PD patients in an all-comers, global capture protocol from an academic center. Patient interest in participation and yield for identification of GBA and LRRK2 mutation carriers is high, demonstrating feasibility of PD clinic-wide molecular characterization.
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 declinedefined by change in MoCA or development of incident mild cognitive impairment (MCI) or dementiain 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.
Objective: Using a multi-cohort, Discovery-Replication-Validation design, we sought new plasma biomarkers that predict which PD individuals 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 associating with subsequent cognitive decline in both cohorts, we trained a logistic regression model to predict which PD patients showed fast (>=1 point drop/year on Montreal Cognitive Assessment (MoCA)) vs. 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 three 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 PD individuals. We investigated the top plasma biomarker for causal influence by Mendelian randomization. Results: A model with only three proteins (Melanoma Inhibitory Activity Protein (MIA), C-Reactive Protein (CRP), albumin) separated Fast vs. Slow cognitive decline subgroups with an AUC of 0.80 in the Validation Cohort. Validation Cohort PD individuals 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 SNP rs2233154 associated with MIA levels and cognitive decline, providing evidence for MIA's causal influence. Conclusions: An easily-obtained plasma-based predictor identifies PD individuals at risk for cognitive decline. MIA may participate causally in development of cognitive decline.
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