Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies.
Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies.
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DOI：
10.1016/s1474-4422(19)30320-5
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发表时间：
2019-12
期刊：
影响因子：
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通讯作者：
International Parkinson's Disease Genomics Consortium
中科院分区：
文献类型：
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作者：
Nalls MA;Blauwendraat C;Vallerga CL;Heilbron K;Bandres-Ciga S;Chang D;Tan M;Kia DA;Noyce AJ;Xue A;Bras J;Young E;von Coelln R;Simón-Sánchez J;Schulte C;Sharma M;Krohn L;Pihlstrøm L;Siitonen A;Iwaki H;Leonard H;Faghri F;Gibbs JR;Hernandez DG;Scholz SW;Botia JA;Martinez M;Corvol JC;Lesage S;Jankovic J;Shulman LM;Sutherland M;Tienari P;Majamaa K;Toft M;Andreassen OA;Bangale T;Brice A;Yang J;Gan-Or Z;Gasser T;Heutink P;Shulman JM;Wood NW;Hinds DA;Hardy JA;Morris HR;Gratten J;Visscher PM;Graham RR;Singleton AB;23andMe Research Team;System Genomics of Parkinson's Disease Consortium;International Parkinson's Disease Genomics Consortium
在过去的十年中，帕金森病（PD）的全基因组关联研究（GWAS）增加了有关该疾病的生物学知识的范围。我们试图使用最大的GWAS数据来识别新的风险位点，并进一步了解疾病的病因。我们进行了迄今为止最大的PD荟萃GWAS，涉及37.7K病例中的7.8M SNP分析，18.6K UK生物库代理病例（与PD有一级亲属关系）和1.4M对照。我们对GWAS数据进行了荟萃分析，以提名新的位点。然后，我们使用这些数据评估了遗传风险估计和预测模型。我们还利用大的基因表达和甲基化资源来检查可能的功能后果以及组织，细胞类型和生物途径富集所确定的风险因素。此外，我们通过遗传相关性随后进行孟德尔随机化来检查PD和其他感兴趣的表型之间的共享遗传风险。我们在78个基因组区域中发现了90个独立的全基因组重大风险信号，其中包括37个基因座中的38个新的独立风险信号。这90个变异解释了16-36%的PD遗传风险，这取决于患病率。在孟德尔随机化框架内整合甲基化和表达数据，在70个潜在GWAS基因座的风险信号中鉴定了pupillary相关基因，用于后续功能研究。组织特异性表达富集分析表明，PD基因座在大脑中高度富集，单细胞数据涉及特定的神经元细胞类型。我们发现，基因与脑容量、吸烟状况和教育程度有着显著的相关性。认知能力和PD风险之间的孟德尔随机化显示了强有力的关联。这些数据通过揭示许多额外的PD风险基因座，为这些风险因素提供生物学背景，并证明这种疾病的相当大的遗传成分仍未被识别，从而提供了迄今为止对PD遗传结构的最全面的理解。
Genome-wide association studies (GWASs) in Parkinson’s disease (PD) have increased the scope of biological knowledge about the disease over the past decade. We sought to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into disease etiology. We performed the largest meta-GWAS of PD to date, involving the analysis of 7.8M SNPs in 37.7K cases, 18.6K UK Biobank proxy-cases (having a first degree relative with PD), and 1.4M controls. We carried out a meta-analysis of this GWAS data to nominate novel loci. We then evaluated heritable risk estimates and predictive models using this data. We also utilized large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type and biological pathway enrichments for the identified risk factors. Additionally we examined shared genetic risk between PD and other phenotypes of interest via genetic correlations followed by Mendelian randomization. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of PD depending on prevalence. Integrating methylation and expression data within a Mendelian randomization framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested PD loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes, smoking status, and educational attainment. Mendelian randomization between cognitive performance and PD risk showed a robust association. These data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified.