Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, National Center for Neurological Disorders, Shanghai, China.
Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China.
J Transl Med. 2022 Apr 21;20(1):181. doi: 10.1186/s12967-022-03377-9.
Genome-wide association studies (GWAS) have revealed numerous loci associated with stroke. However, the underlying mechanisms at these loci in the pathogenesis of stroke and effective stroke drug targets are elusive. Therefore, we aimed to identify causal genes in the pathogenesis of stroke and its subtypes.
Utilizing multidimensional high-throughput data generated, we integrated proteome-wide association study (PWAS), transcriptome-wide association study (TWAS), Mendelian randomization (MR), and Bayesian colocalization analysis to prioritize genes that contribute to stroke and its subtypes risk via affecting their expression and protein abundance in brain and blood.
Our integrative analysis revealed that ICA1L was associated with small-vessel stroke (SVS), according to robust evidence at both protein and transcriptional levels based on brain-derived data. We also identified NBEAL1 that was causally related to SVS via its cis-regulated brain expression level. In blood, we identified 5 genes (MMP12, SCARF1, ABO, F11, and CKAP2) that had causal relationships with stroke and stroke subtypes.
Together, via using an integrative analysis to deal with multidimensional data, we prioritized causal genes in the pathogenesis of SVS, which offered hints for future biological and therapeutic studies.
全基因组关联研究（GWAS）已经揭示了许多与中风相关的基因位点。然而，这些基因位点在中风发病机制和有效的中风药物靶点中的潜在机制仍然难以捉摸。因此，我们旨在确定中风及其亚型发病机制中的因果基因。
利用多维高通量数据，我们整合了蛋白质组关联研究（PWAS）、转录组关联研究（TWAS）、孟德尔随机化（MR）和贝叶斯共定位分析，优先考虑通过影响大脑和血液中基因的表达和蛋白丰度来增加中风及其亚型风险的基因。
我们的综合分析表明，根据大脑衍生数据在蛋白和转录水平上的稳健证据，ICA1L 与小血管中风（SVS）相关。我们还发现 NBEAL1 通过其顺式调控的大脑表达水平与 SVS 有因果关系。在血液中，我们确定了 5 个与中风和中风亚型有因果关系的基因（MMP12、SCARF1、ABO、F11 和 CKAP2）。
总之，我们通过使用综合分析来处理多维数据，优先考虑了 SVS 发病机制中的因果基因，为未来的生物学和治疗研究提供了线索。
