Fine-mapping of Parkinson's disease susceptibility loci identifies putative causal variants.

Fine-mapping of Parkinson's disease susceptibility loci identifies putative causal variants.
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DOI:
10.1093/hmg/ddab294
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发表时间:
2022-03-21
影响因子:
3.5
通讯作者:
Raj T
Raj T
中科院分区:
生物学2区
文献类型:
--
作者:
Schilder BM;Raj T

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最近的全基因组关联研究已经确定了78个与帕金森氏病易感性相关的基因座,但其潜在的机制在很大程度上仍不清楚。为了确定疾病风险的可能因果变异,我们使用四种不同的精细作图方法对这些与帕金森病相关的基因座进行了精细作图。然后,我们整合了多个细胞类型特定的表观基因组图谱,以确定每个变体的可能作用机制,使我们能够确定共同的单核苷酸多态性(SNPs),它破坏小胶质细胞中的LRRK2和FCGR2A调节元件,寡突胶质细胞中的MBNL2增强子,以及神经元中的DYRK1A增强子。这项对帕金森病的全基因组功能精细图谱研究极大地促进了我们对这种复杂疾病背后的因果机制的理解,同时避免了对虚假的、非因果机制的关注。总之,这些结果提供了一个强大的、全面的列表,列出了潜在的帕金森病风险的可能原因变异、基因和细胞类型,正如我们的精细定位的SNPs相对于领先的GWASSNPs在独立的功能影响注释中的持续更大的丰富所证明的那样。此外,我们的方法将每个基因座平均3/85的变异列为推定原因,使下游的实验研究更容易处理,更有可能产生与疾病相关的、可操作的结果。将帕金森氏症患者与年龄匹配的对照组进行比较的大规模研究已经确定了与该疾病相关的基因组的许多区域。然而,基因组的不同部分之间存在广泛的相关性,因此很难区分哪些遗传变异导致帕金森氏症,哪些只是与因果变异共同遗传。因此,我们应用了一套统计模型来识别最有可能的因果遗传变异(即精细定位)。然后,我们将这些遗传变异与各种组织和细胞类型的表观基因组和基因表达特征联系起来,以确定这些变异是如何导致疾病的。因此,这项研究提供了一份全面而有力的细胞和分子机制清单,可以作为开发更有效的帕金森疗法的靶点。
Recent genome-wide association studies have identified 78 loci associated with Parkinson’s disease susceptibility but the underlying mechanisms remain largely unclear. To identify likely causal variants for disease risk, we fine-mapped these Parkinson’s-associated loci using four different fine-mapping methods. We then integrated multi-assay cell type–specific epigenomic profiles to pinpoint the likely mechanism of action of each variant, allowing us to identify Consensus single nucleotide polymorphism (SNPs) that disrupt LRRK2 and FCGR2A regulatory elements in microglia, an MBNL2 enhancer in oligodendrocytes, and a DYRK1A enhancer in neurons. This genome-wide functional fine-mapping investigation of Parkinson’s disease substantially advances our understanding of the causal mechanisms underlying this complex disease while avoiding focus on spurious, non-causal mechanisms. Together, these results provide a robust, comprehensive list of the likely causal variants, genes and cell-types underlying Parkinson’s disease risk as demonstrated by consistently greater enrichment of our fine-mapped SNPs relative to lead GWAS SNPs across independent functional impact annotations. In addition, our approach prioritized an average of 3/85 variants per locus as putatively causal, making downstream experimental studies both more tractable and more likely to yield disease-relevant, actionable results. Large-scale studies comparing individuals with Parkinson’s disease to age-matched controls have identified many regions of the genome associated with the disease. However, there is widespread correlation between different parts of the genome, making it difficult to tell which genetic variants cause Parkinson’s and which are simply co-inherited with causal variants. We therefore applied a suite of statistical models to identify the most likely causal genetic variants (i.e. fine-mapping). We then linked these genetic variants with epigenomic and gene expression signatures across a wide variety of tissues and cell types to identify how these variants cause disease. Therefore, this study provides a comprehensive and robust list of cellular and molecular mechanisms that may serve as targets in the development of more effective Parkinson’s therapeutics.
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