Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA; Data Tecnica International, Glen Echo, MD, USA.
Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA.
Lancet Neurol. 2019 Dec;18(12):1091-1102. doi: 10.1016/S1474-4422(19)30320-5.
Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease.
We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used 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 Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation.
Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. 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 Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10).
These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data.
The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources).
在过去的十年中,全基因组关联研究(GWAS)极大地增加了我们对帕金森病的生物学认识。我们旨在利用最大的 GWAS 数据集合来鉴定新的风险基因座,并进一步深入了解帕金森病的病因。
我们对来自欧洲血统样本的 17 个帕金森病 GWAS 数据集进行了荟萃分析,以确定疾病风险的新基因座。这些数据集包含了所有可用的数据。然后,我们使用这些数据来估计遗传风险,并开发遗传风险的预测模型。我们还使用大型基因表达和甲基化资源来研究可能的功能后果,以及鉴定风险因素的组织、细胞类型和生物学途径富集。此外,我们通过遗传相关性和孟德尔随机化来研究帕金森病与其他感兴趣的表型之间的共享遗传风险。
在 2017 年 10 月 1 日至 2018 年 8 月 9 日期间,我们分析了 37688 例病例、18618 例英国生物银行代理病例(即没有帕金森病但有一级亲属患有该病的个体)和 140 万例对照中 780 个基因组区域的 780 万个单核苷酸多态性。我们在 78 个基因组区域中确定了 90 个独立的全基因组显著风险信号,包括 37 个基因座中的 38 个新的独立风险信号。这些 90 个变体根据患病率解释了帕金森病 16-36%的遗传风险。在孟德尔随机化框架内整合甲基化和表达数据,在 GWAS 基因座的后续功能研究中鉴定了与 70 个风险信号相关的假定基因。组织特异性表达富集分析表明,帕金森病基因座主要富集于大脑,单细胞数据提示特定的神经元细胞类型也参与其中。我们发现与脑容量(颅内容量的错误发现率校正后 p=0.0035,壳核容量的 p=0.024)、吸烟状况(p=0.024)和教育程度(p=0.038)之间存在显著的遗传相关性。认知表现与帕金森病风险之间的孟德尔随机化显示出稳健的关联(p=8.00e-10)。
这些数据提供了迄今为止最全面的帕金森病遗传风险调查,据我们所知,通过揭示许多额外的帕金森病风险基因座,为这些风险因素提供了生物学背景,并表明该疾病的相当大一部分遗传成分尚未被识别。这些来自欧洲血统数据集的关联需要用更多样化的数据进行后续研究。
美国国立卫生研究院(NIH)下属的国家老龄化研究所、迈克尔·J·福克斯基金会和帕金森基金会(详见附录中的完整资助来源列表)。