Shared and Sex-Specific Genetic Risk for Parkinson's Disease Risk Across European Populations

GP2 ❤️ Open Science 😍

Last Updated: December 2025

Summary

This is the online repository for the manuscript titled "Shared and Sex-Specific Genetic Risk for Parkinson's Disease Risk Across European Populations". This study presents the largest sex-stratified genome-wide association study (GWAS) meta-analysis of Parkinson's disease (PD) risk to date, including 226,196 individuals (18,145 female PD cases, 95,558 female controls; 28,747 male PD cases, and 83,746 male controls) from European populations. We identified 57 genome-wide significant association signals, including five novel risk loci with sex-specific effects, and provide functional annotation and colocalization analyses.

Citation

(pending publication)

Data Statement

• All GP2 data are hosted in collaboration with the Accelerating Medicines Partnership in Parkinson's disease and are available via application at https://amp-pd.org/register-for-amp-pd. For up-to-date information on GP2 data acquisition, access, and policies, visit https://gp2.org/.
  • This study utilized GP2 releases 9 (10.5281/zenodo.14510099) and 10 (10.5281/zenodo.15748014). Genotyping imputation, quality control, ancestry prediction, and processing were performed using GenoTools (v1.0.0), publicly available on GitHub.
• UK Biobank data were accessed under Application Number 33601 (https://www.ukbiobank.ac.uk/use-our-data/apply-for-access/).
• Fox Insight data are available at https://foxinsight.michaeljfox.org/register.

Helpful Links

• GP2 Website
  • GP2 Cohort Dashboard
• Introduction to GP2
  • Other GP2 Manuscripts (PubMed)

Repository Orientation

The analyses/ directory includes analyses discussed in the manuscript, organized by analysis type:

THIS_REPO/
├── LICENSE
├── README.md
└── analyses/
    ├── GWAS/
    │   └── GWAS.ipynb
    ├── beta-beta/
    │   ├── betabeta_MF.ipynb
    │   └── gp2_vars_v2.txt
    ├── LDSC/
    │   └── male_female_LDSC.ipynb
    ├── forest_plots/
    │   ├── forest_plots.ipynb
    │   └── combined_forest_data.csv
    ├── locusCompare/
    │   └── locusCompare_setAxes_R.r
    └── coloc/
        ├── 01_define_loci.ipynb
        ├── 02_coloc_results.ipynb
        ├── coloc_GTEx_cisQTL_v10.v4.R
        ├── topSNPs.txt
        └── loci_500kb_topSNPs.tsv

Analysis Notebooks

Languages: Python, bash, and R

Directory	Notebook/Script	Description
GWAS/	GWAS.ipynb	Sex-stratified data prep and GWAS meta-analyses across GP2 as an example
beta-beta/	betabeta_MF.ipynb	Beta-beta plots comparing effect sizes between male and female meta-analyses using 157 variants from GP2 et al. 2025; correlation analysis of sex-specific effects
	gp2_vars_v2.txt	List of 157 PD risk variants from GP2 et al. 2025 used for beta-beta comparison
LDSC/	male_female_LDSC.ipynb	Linkage disequilibrium score regression (LDSC) analysis
forest_plots/	forest_plots.ipynb	Forest plot generation
	combined_forest_data.csv	Summary statistics for forest plot generation including beta estimates, standard errors, and p-values for both sexes
locusCompare/	locusCompare_setAxes_R.r	R script for creating locusCompare plots comparing GWAS signals between males and females at specific loci
coloc/	01_define_loci.ipynb	Definition of genomic loci for colocalization analysis; extraction of lead SNPs and surrounding regions from sex-stratified GWAS
	02_coloc_results.ipynb	Processing and filtering of colocalization results; identification of sex-specific and sex-shared eQTL colocalization signals
	coloc_GTEx_cisQTL_v10.v4.R	Bayesian colocalization analysis using COLOC method with GTEx v10 brain eQTL data across 13 brain tissues; calculation of posterior probabilities for shared causal variants
	topSNPs.txt	List of lead SNPs for colocalization analysis
	loci_500kb_topSNPs.tsv	Genomic coordinates (±500kb) around lead SNPs for colocalization analysis

Software

Software	Version(s)	Resource URL	RRID	Notes
PLINK	1.9 and 2.0	http://www.cog-genomics.org/plink/	RRID:SCR_001757	Used for GWAS and meta-analyses
LDSC	1.0.1	https://github.com/bulik/ldsc	RRID:SCR_017248	Used for genetic correlation and heritability estimation
FUMA	v1.5.3	https://fuma.ctglab.nl/	RRID:SCR_017346	Used for functional annotation and LD clumping
COLOC	5.2.3	https://github.com/chr1swallace/coloc	-	Used for colocalization analysis with GTEx eQTLs
GenoTools	1.0.0	https://github.com/GP2code/GenoTools	-	Used for QC, ancestry prediction, and imputation
KING	2.2.5	https://www.kingrelatedness.com/	RRID:SCR_018787	Used for relatedness estimation
Python	3.10.15	http://www.python.org/	RRID:SCR_008394	pandas, numpy, seaborn, matplotlib, scipy; used for data wrangling and visualization
R	4.3.3	http://www.r-project.org/	RRID:SCR_001905	forestplot, coloc, ggplot2; used for statistical analysis and visualization

Contact

For questions about this analysis, please contact:

• Data and Working Group Committee (dawg@gp2.org)