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Output Catalog
ASAP is committed to accelerating the pace of discovery and informing a path to a cure for Parkinson’s disease through collaboration, research-enabling resources, and data sharing. We’ve created this catalog to showcase the research outputs and tools developed by ASAP-funded programs.
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Output Type
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Program
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CRN Team Name
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Theme
Characterizing Parkinson’s Disease Clinical and Biomarker Interactions in REM Sleep Behavior Disorder
a-syn SAA positivity, DaT positivity, and hyposmia are highly associated with each other. MDS Prodromal PD Probability scores may be useful predictors of near-term progression, and thus as a stratification factor in clinical research study design
Inflamed Microglia like Macrophages in the Central Nervous System of Prodromal Parkinson′s Disease
We investigated the role of inflammation in the pathogenesis of prodromal PD performing single-cell RNAseq analysis of CSF and blood from 111 individuals.
Dopamine transporter and synaptic vesicle sorting defects underlie auxilin-associated Parkinson’s disease
Auxilin participates in clathrin uncoating to facilitate presynaptic endocytosis. Loss-of-function mutations of auxilin (PARK19) cause Parkinson’s disease. Using auxilin KO mice, Vidyadhara et al. (2023) show that synaptic vesicle sorting…
A Markov random field model-based approach for differentially expressed gene detection from single-cell RNA-seq data
Single-cell RNA-sequencing technology enables the identification of cell-type-specific differential gene expressions. MARBLES, a new statistical model, effectively detects DE genes across conditions.
Dopamine transporter and synaptic vesicle sorting defects underlie auxilin-associated Parkinson’s disease
Auxilin participates in the uncoating of clathrin-coated vesicles (CCVs), thereby facilitating synaptic vesicle (SV) regeneration at presynaptic sites. Auxilin (DNAJC6/PARK19) loss-of-function mutations cause early-onset Parkinson’s disease…
Single-cell transcriptomic and proteomic analysis of Parkinson’s disease Brains
This article established a single-nucleus transcriptomic profile of the prefrontal cortex from postmortem human brains of six patients with PD and six age-matched controls.
scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles
The authors developed scNAT, a deep learning method that integrates paired scRNA-seq and scTCR-seq data to represent data in a unified latent space for downstream analysis.
Gut instincts in neuroimmunity from the eighteenth to twenty-first centuries
In this review, the authors revisit the history of gut-brain interactions in science and medicine, which dates back to at least the eighteenth century, and outline how concepts in this field have shifted and evolved across eras.
scNAT Data for “scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles”
The publication introduces scNAT, a deep learning method that integrates single-cell RNA and T cell receptor sequencing data for improved analysis of immune cell populations.
Human Postmortem-Derived Brain Sequencing Collection (Harmonized Collection)
The Human Postmortem-derived Brain Sequencing Collection is a harmonized repository comprised of sequencing data contributed by ASAP CRN teams.
README Guide for Code
The purpose of this document is to provide guidance on how to write README files for code.