Research Paper Volume 16, Issue 2 pp 1555—1580
Joint analysis of proteome, transcriptome, and multi-trait analysis to identify novel Parkinson’s disease risk genes
- 1 Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
- 2 School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang, China
- 3 Zhengzhou Railway Vocational and Technical College, Zhengzhou 450000, Henan, China
- 4 NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
- 5 Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
- 6 Institute of Neuroscience, Zhengzhou University, Zhengzhou 450000, Henan, China
- 7 Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, Zhejiang, China
Received: February 20, 2023 Accepted: December 4, 2023 Published: January 17, 2024
https://doi.org/10.18632/aging.205444How to Cite
Copyright: © 2024 Shi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Genome-wide association studies (GWAS) have identified multiple risk variants for Parkinson’s disease (PD). Nevertheless, how the risk variants confer the risk of PD remains largely unknown. We conducted a proteome-wide association study (PWAS) and summary-data-based mendelian randomization (SMR) analysis by integrating PD GWAS with proteome and protein quantitative trait loci (pQTL) data from human brain, plasma and CSF. We also performed a large transcriptome-wide association study (TWAS) and Fine-mapping of causal gene sets (FOCUS), leveraging joint-tissue imputation (JTI) prediction models of 22 tissues to identify and prioritize putatively causal genes. We further conducted PWAS, SMR, TWAS, and FOCUS using a multi-trait analysis of GWAS (MTAG) to identify additional PD risk genes to boost statistical power. In this large-scale study, we identified 16 genes whose genetically regulated protein abundance levels were associated with Parkinson’s disease risk. We undertook a large-scale analysis of PD and correlated traits, through TWAS and FOCUS studies, and discovered 26 casual genes related to PD that had not been reported in previous TWAS. 5 genes (CD38, GPNMB, RAB29, TMEM175, TTC19) showed significant associations with PD at both the proteome-wide and transcriptome-wide levels. Our study provides new insights into the etiology and underlying genetic architecture of PD.
Abbreviations
PD: Parkinson’s disease; SNP: single nucleotide polymorphism; LBD: lewy body dementia; iRBD: idiopathic rapid eye movement sleep behavior disorder; GWAS: genome-wide association study; PWAS: proteome-wide association study; TWAS: transcriptome-wide association study; SMR: summary-data-based mendelian randomization; MTAG: multi-trait analysis of GWAS; PD MTAG: MTAG result of PD; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; eQTL: expression quantitative trait loci; pQTL: protein quantitative trait loci.