Gene4PD: A Comprehensive Genetic Database of Parkinson's Disease.

Bin Li,Jinchen Li,Jifeng Guo,Yi Zhang,Hongxu Pan,Qian Chen,Zhenghuan Fang,Qiao Zhou,Tengfei Luo,Rui Zhang,Zhenhua Liu,Xiaomeng Wang,Zheng Wang,Yuwen Zhao,Lixia Qin,Yijing Wang,Yan He,Beisha Tang,Li Jiang,Bin Lü ,Guizhe Zhao ,Yi Xie

doi:10.3389/fnins.2021.679568

Abstract

Parkinson’s disease (PD) is a complex neurodegenerative disorder with a strong genetic component. A growing number of variants and genes have been reported to be associated with PD; however, there is no database that integrate different type of genetic data, and support analyzing of PD-associated genes (PAGs). By systematic review and curation of multiple lines of public studies, we integrate multiple layers of genetic data (rare variants and copy-number variants identified from patients with PD, associated variants identified from genome-wide association studies, differentially expressed genes, and differential DNA methylation genes) and age at onset in PD. We integrated five layers of genetic data (8302 terms) with different levels of evidences from more than 3,000 studies and prioritized 124 PAGs with strong or suggestive evidences. These PAGs were identified to be significantly interacted with each other and formed an interconnected functional network enriched in several functional pathways involved in PD, suggesting these genes may contribute to the pathogenesis of PD. Furthermore, we identified 10 genes were associated with a juvenile-onset (age ≤ 30 years), 11 genes were associated with an early-onset (age of 30–50 years), whereas another 10 genes were associated with a late-onset (age > 50 years). Notably, the AAOs of patients with loss of function variants in five genes were significantly lower than that of patients with deleterious missense variants, while patients with VPS13C (P = 0.01) was opposite. Finally, we developed an online database named Gene4PD (http://genemed.tech/gene4pd) which integrated published genetic data in PD, the PAGs, and 63 popular genomic data sources, as well as an online pipeline for prioritize risk variants in PD. In conclusion, Gene4PD provides researchers and clinicians comprehensive genetic knowledge and analytic platform for PD, and would also improve the understanding of pathogenesis in PD.

Highlights

Parkinson’s disease (PD) is the second most common neurodegenerative disease (Alzheimer’s Association, 2014; Dorsey et al, 2007)
We collected five types of genomic data related to PD from the PubMed database with following search items: (1) rare variants identified from PD patients with “Parkinson × [Title/Abstract] AND [mutation (Title/Abstract) or variant (Title/Abstract)] AND gene [Title/Abstract]”; (2) Copy number variations (CNVs) in PD with “Parkinson × [Title/Abstract] AND [copy number variation (Title/Abstract) or CNV (Title/Abstract)]”; (3) associated SNPs identified from GWAS with “Parkinson × [Title/Abstract] AND GWAS[Title/Abstract]”; (4) differential expressed genes (DEGs) with “Parkinson × [Title/Abstract] AND transcriptome [Title/Abstract]”; (5) differentially expressed DNA methylation genes (DMGs) with “Parkinson × [Title/Abstract] AND DNA methylation [Title/Abstract].”
We screened out articles related to PD according to the exclusion criteria: (i) studies that focused on molecular mechanisms, rather than genetic studies; (ii) studies without original data for genomic information, which may cite from published studies, such as reviews or meta-analysis; and the inclusion criteria: (i) studies reported the genomic information of PD, (ii) studies reported the differential expressed genes of PD, (iii) studies reported the differentially expressed DNA methylation genes of PD

Summary

Introduction

Parkinson’s disease (PD) is the second most common neurodegenerative disease (Alzheimer’s Association, 2014; Dorsey et al, 2007). Copy number variations (CNVs), in PRKN and SNCA, have been highlighted to play a vital role in the development of heritable or sporadic PD (Konno et al, 2016; Mok et al, 2016; Taghavi et al, 2018) and several genes, such as ATP13A2 (Ramirez et al, 2006), PLA2G6 (Paisan-Ruiz et al, 2009), FBXO7 (Di Fonzo et al, 2009), PRKN (Djarmati et al, 2004; Lucking et al, 2000), PINK1 (Bonifati et al, 2005; Kumazawa et al, 2008), and PARK7 (Djarmati et al, 2004) were reported to be strongly associated with an early-onset age of PD (Searles Nielsen et al, 2013)

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Discussion

Conclusion