Genome-wide association study (GWAS) has seen great strides in revealing initial insights into the genetic architecture of Parkinson’s disease (PD). Since GWAS signals often reside in non-coding regions, relatively few of the associations have implicated specific biological mechanisms. Here, we aimed to integrate the GWAS results with large-scale expression quantitative trait loci (eQTL) in 13 brain tissues to identify candidate causal genes for PD. We conducted a transcriptome-wide association study (TWAS) for PD using the summary statistics of over 480,000 individuals from the most recent PD GWAS. We identified 18 genes significantly associated with PD after Bonferroni corrections. The most significant gene, LRRC37A2, was associated with PD in all 13 brain tissues, such as in the hypothalamus (P = 6.12 × 10⁻²²) and nucleus accumbens basal ganglia (P = 5.62 × 10⁻²¹). We also identified eight conditionally independent genes, including four new genes at known PD loci: CD38, LRRC37A2, RNF40, and ZSWIM7. Through conditional analyses, we demonstrated that several of the GWAS significant signals on PD could be driven by genetically regulated gene expression. The most significant TWAS gene LRRC37A2 accounts for 0.855 of the GWAS signal at its loci, and ZSWIM7 accounts for all the GWAS signals at its loci. We further identified several phenotypes previously associated with PD by querying the single nucleotide polymorphisms (SNPs) in the final model of the identified genes in phenome databases. In conclusion, we prioritized genes that are likely to affect PD by using a TWAS approach and identified phenotypes associated with PD.

全基因组关联研究 (GWAS) 在揭示对帕金森病 (PD) 遗传结构的初步见解方面取得了长足的进步。由于 GWAS 信号通常位于非编码区域，因此相对较少的关联与特定的生物学机制有关。在这里，我们旨在将 GWAS 结果与 13 个脑组织中的大规模表达数量性状基因座 (eQTL) 相结合，以确定 PD 的候选因果基因。我们使用来自最近 PD GWAS 的超过 480,000 个人的汇总统计数据对 PD 进行了转录组范围关联研究 (TWAS)。在 Bonferroni 校正后，我们确定了 18 个与 PD 显着相关的基因。最重要的基因LRRC37A2与所有 13 种脑组织中的 PD 相关，例如下丘脑（P = 6.12 × 10 ^-22）和伏隔核基底神经节（P  = 5.62 × 10 ^-21）。我们还鉴定了八个条件独立的基因，包括已知 PD 基因座的四个新基因：CD38、LRRC37A2、RNF40和ZSWIM7。通过条件分析，我们证明了几个 GWAS 对 PD 的重要信号可以由遗传调节的基因表达驱动。最重要的 TWAS 基因LRRC37A2占其基因座 GWAS 信号的 0.855，而ZSWIM7占其位点的所有 GWAS 信号。我们通过查询表型数据库中已识别基因的最终模型中的单核苷酸多态性 (SNP)，进一步识别了以前与 PD 相关的几种表型。总之，我们通过使用 TWAS 方法对可能影响 PD 的基因进行了优先排序，并确定了与 PD 相关的表型。