Publications by authors named "N O Amari"

Observational studies in Parkinson's disease (PD) deeply characterize relatively small numbers of participants. The Molecular Integration in Neurological Diagnosis Initiative seeks to characterize molecular and clinical features of every PD patient at the University of Pennsylvania (UPenn). The objectives of this study are to determine the feasibility of genetic characterization in PD and assess clinical features by sex and GBA1/LRRK2 status on a clinic-wide scale.

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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.

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In this study, for the first time, the anti-inflammatory antioxidant, anti-tyrosinase and antimicrobial property of subsp leaf-bud extract have been investigated. The anti-inflammatory activity was determined in vivo by reducing carrageenan-induced hind paw edema in mice, while the antiradical function was evaluated using DPPH, total antioxidant capacity (TAC) and reduction power assays. The extract induced a significant reduction of the edema, from 1 to 6 h in a dose-dependent manner (150, 200 and 300 mg/kg).

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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 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).

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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.

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