Literature DB >> 33523105

Identification of Candidate Parkinson Disease Genes by Integrating Genome-Wide Association Study, Expression, and Epigenetic Data Sets.

Demis A Kia1, David Zhang1, Sebastian Guelfi1, Claudia Manzoni2, Leon Hubbard3, Regina H Reynolds1, Juan Botía4, Mina Ryten1, Raffaele Ferrari1, Patrick A Lewis5,6, Nigel Williams3, Daniah Trabzuni1,7, John Hardy8, Nicholas W Wood1.   

Abstract

Importance: Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. Objective: To investigate what genes and genomic processes underlie the risk of sporadic PD. Design and Setting: This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. Main Outcomes and Measures: It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role.
Results: Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. Conclusions and Relevance: Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies.

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Mesh:

Year:  2021        PMID: 33523105      PMCID: PMC7851759          DOI: 10.1001/jamaneurol.2020.5257

Source DB:  PubMed          Journal:  JAMA Neurol        ISSN: 2168-6149            Impact factor:   18.302


  15 in total

1.  Genetic Analysis of Six Transmembrane Protein Family Genes in Parkinson's Disease in a Large Chinese Cohort.

Authors:  Yuwen Zhao; Kailin Zhang; Hongxu Pan; Yige Wang; Xiaoxia Zhou; Yaqin Xiang; Qian Xu; Qiying Sun; Jieqiong Tan; Xinxiang Yan; Jinchen Li; Jifeng Guo; Beisha Tang; Zhenhua Liu
Journal:  Front Aging Neurosci       Date:  2022-07-04       Impact factor: 5.702

2.  Editorial: Multi-omics, Epigenomics, and Computational Analysis of Neurodegenerative Disorders.

Authors:  Manoj Kumar Jaiswal
Journal:  Front Neurosci       Date:  2022-07-06       Impact factor: 5.152

3.  Functional Study of TMEM163 Gene Variants Associated with Hypomyelination Leukodystrophy.

Authors:  Huifang Yan; Shuyan Yang; Yiming Hou; Saima Ali; Adrian Escobar; Kai Gao; Ruoyu Duan; Thomas Kubisiak; Junyu Wang; Yu Zhang; Jiangxi Xiao; Yuwu Jiang; Ting Zhang; Ye Wu; Margit Burmeister; Qiang Wang; Math P Cuajungco; Jingmin Wang
Journal:  Cells       Date:  2022-04-09       Impact factor: 7.666

4.  Rab GTPases in Parkinson's disease: a primer.

Authors:  Antonio Jesús Lara Ordóñez; Rachel Fasiczka; Yahaira Naaldijk; Sabine Hilfiker
Journal:  Essays Biochem       Date:  2021-12-22       Impact factor: 8.000

5.  Prevalence of parkinsonism and Parkinson disease in urban and rural populations from Latin America: A community based study.

Authors:  Jorge J Llibre-Guerra; Matthew Prina; Ana Luisa Sosa; Daisy Acosta; Ivonne Z Jimenez-Velazquez; Mariella Guerra; Aquiles Salas; Juan C Llibre-Guerra; Adolfo Valvuerdi; Geeske Peeters; Ellen Ziegemeier; Isaac Acosta; Caroline Tanner; Jorge Juncos; Juan J Llibre Rodriguez
Journal:  Lancet Reg Health Am       Date:  2022-03

6.  Methylated Cytochrome P450 and the Solute Carrier Family of Genes Correlate With Perturbations in Bile Acid Metabolism in Parkinson's Disease.

Authors:  Sangeetha Vishweswaraiah; Sumeyya Akyol; Ali Yilmaz; Zafer Ugur; Juozas Gordevičius; Kyung Joon Oh; Patrik Brundin; Uppala Radhakrishna; Viviane Labrie; Stewart F Graham
Journal:  Front Neurosci       Date:  2022-03-31       Impact factor: 4.677

Review 7.  Advancing Personalized Medicine in Common Forms of Parkinson's Disease through Genetics: Current Therapeutics and the Future of Individualized Management.

Authors:  Xylena Reed; Artur Schumacher-Schuh; Jing Hu; Sara Bandres-Ciga
Journal:  J Pers Med       Date:  2021-03-01

Review 8.  Omics Data and Their Integrative Analysis to Support Stratified Medicine in Neurodegenerative Diseases.

Authors:  Valentina La Cognata; Giovanna Morello; Sebastiano Cavallaro
Journal:  Int J Mol Sci       Date:  2021-05-01       Impact factor: 5.923

Review 9.  Insights into Lewy body disease from rare neurometabolic disorders.

Authors:  Daniel Erskine; Johannes Attems
Journal:  J Neural Transm (Vienna)       Date:  2021-05-30       Impact factor: 3.575

Review 10.  Integration of functional genomics data to uncover cell type-specific pathways affected in Parkinson's disease.

Authors:  Viola Volpato
Journal:  Biochem Soc Trans       Date:  2021-11-01       Impact factor: 5.407

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