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.
-
Output Type
-
Program
-
CRN Team Name
-
Theme
Release Notes – ASAP CRN Cloud
Summary: Release notes for version 1.0.0 of CRN Cloud platform, released on June 25, 2024, detailing latest updates and enhancements.
Evaluation Of The Rims2 Locus As A Risk Locus For Parkinson’s Disease Dementia
Liu et al. found RIMS2 locus linked to dementia in Parkinson's disease. Our study with 2536 individuals found no association with RIMS2 or other loci. More research is needed to uncover biological factors influencing Parkinson's dementia.
SNP Genotyping and ApoE Genotyping
Protocol outlines DNA extraction from blood, quality control, SNP, and APOE genotyping. Adapted from PRoBaND SNP Genotyping and ApoE Genotyping Protocol by Malek et al. for Parkinson's Disease study.
CD8 Cell Density In Substantia Nigra And Cerebral Peduncle Image Analysi
QuPath is a bioimage analysis software designed for digital pathology and whole slide image analysis. This protocol describes how to measure CD8 density in the substantia nigra and cerebral peduncle using haematoxylin and DAB-stained brain sections.
Lentivirus plasmids for sgRNA: pLV[Exp]-U6>NT-Seq1-hPGK>mApple
Plasmid: Plasmid vector encoding a non-targeting sgRNA sequence under a U6 promoter and a mApple fluorescent reporter. Generated by Vectorbuilder in the pLV[Exp] backbone
LiD genetic determinants study under CPH regression models
Code to perform the study of LiD genetic determinants under CPH regression models and functional annotation analyses.
Vesicular dysfunction and pathways to neurodegeneration
In this review, the pathways that have emerged as critical for neuronal survival in the human brain are discussed, illustrating the diversity of proteins and cellular events with three molecular case studies from different neurological diseases.
Regulation of mitophagy by the NSL complex underlies genetic risk for Parkinson’s disease: Bioinformatic Prioritisation and Hit Validation
This protocol describes the Bioinformatic Prioritization of PD GWAS candidates for High Content Screening, and Hit Validation by allele-specific expression (ASE) analysis.
huw-morris-lab/PDD_GWSS
The manuscript by Real et al. investigates the relationship between LRP1B and APOE loci and the onset of Parkinson’s disease dementia, utilizing specific code for analysis.
Long-read RNA seq analysis using Talon
This is a pipeline that takes fastq data as input, generates fastq stats using nanostat, performs fastq processing and filtering using pychopper, maps the reads to the genome using minimap2, and uses talon to assemble and quantify transcripts.
PINK1: From Parkinson’s disease to mitophagy and back again
This perspective discusses the implications of a 2010 PLOS Biology paper (https://doi.org/10.1371/journal.pbio.1000298) that shed light on the functional importance of PINK1 in the mitophagy cascade.
Protein interaction network analysis for Mendelian diseases
This protocol describes the steps to use experimentally validated human data to create a protein-protein interaction network (PPIN) based on disease causative genes. Network analysis (combination of topological functional analyses) will lead to the…
Western blotting for LRRK2 signalling in macrophages
This protocol describes the immunoblotting for components of the LRRK2 signalling pathway (LRRK2, LRRK2 pS935 and phospho-Rabs) using Invitrogen NuPage SDS-PAGE reagents and the BioRad Turbo Blot transfer system.
Leucine-rich repeat kinase 2 at a glance
An overview of current knowledge about LRRK2 function, dysfunction, and links to disease.
Combining biomarkers for prognostic modelling of Parkinson’s disease
Parkinson's disease progression varies among patients. Predicting progression accurately is crucial for clinical trial selection. Blood biomarkers like serum NfL, along with genetic factors (GBA, APOE) can enhance prediction beyond age and phenotype.
