Translational Neurogenomics Laboratory, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, Brisbane, QLD, 4006, Australia.
Genetic Epidemiology Laboratory, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, Brisbane, QLD, 4006, Australia.
Alzheimers Res Ther. 2020 Apr 16;12(1):43. doi: 10.1186/s13195-020-00611-8.
Genome-wide association studies (GWAS) have successfully identified multiple independent genetic loci that harbour variants associated with Alzheimer's disease, but the exact causal genes and biological pathways are largely unknown.
To prioritise likely causal genes associated with Alzheimer's disease, we used S-PrediXcan to integrate expression quantitative trait loci (eQTL) from the Genotype-Tissue Expression (GTEx) study and CommonMind Consortium (CMC) with Alzheimer's disease GWAS summary statistics. We meta-analysed the GTEx results using S-MultiXcan, prioritised disease-implicated loci using a computational fine-mapping approach, and performed a biological pathway analysis on the gene-based results.
We identified 126 tissue-specific gene-based associations across 48 GTEx tissues, targeting 50 unique genes. Meta-analysis of the tissue-specific associations identified 73 genes whose expression was associated with Alzheimer's disease. Additional analyses in the dorsolateral prefrontal cortex from the CMC identified 12 significant associations, 8 of which also had a significant association in GTEx tissues. Fine-mapping of causal gene sets prioritised gene candidates in 10 Alzheimer's disease loci with strong evidence for causality. Biological pathway analyses of the meta-analysed GTEx data and CMC data identified a significant enrichment of Alzheimer's disease association signals in plasma lipoprotein clearance, in addition to multiple immune-related pathways.
Gene expression data from brain and peripheral tissues can improve power to detect regulatory variation underlying Alzheimer's disease. However, the associations in peripheral tissues may reflect tissue-shared regulatory variation for a gene. Therefore, future functional studies should be performed to validate the biological meaning of these associations and whether they represent new pathogenic tissues.
全基因组关联研究 (GWAS) 已成功鉴定出多个独立的遗传位点，这些位点含有与阿尔茨海默病相关的变异。但确切的因果基因和生物学途径仍知之甚少。
为了确定与阿尔茨海默病相关的可能因果基因，我们使用 S-PrediXcan 将基因型-组织表达 (GTEx) 研究和 CommonMind 联盟 (CMC) 的表达数量性状基因座 (eQTL) 与阿尔茨海默病 GWAS 汇总统计数据进行整合。我们使用 S-MultiXcan 对 GTEx 结果进行荟萃分析，使用计算精细映射方法对疾病涉及的位点进行优先级排序，并对基于基因的结果进行生物学途径分析。
我们在 48 个 GTEx 组织中鉴定出 126 个组织特异性基于基因的关联，针对 50 个独特的基因。组织特异性关联的荟萃分析确定了 73 个基因，其表达与阿尔茨海默病相关。在 CMC 的背外侧前额叶皮层进行的额外分析确定了 12 个显著关联，其中 8 个在 GTEx 组织中也有显著关联。因果基因集的精细映射优先考虑了 10 个阿尔茨海默病位点的基因候选物，这些基因候选物具有很强的因果关系证据。对 GTEx 数据和 CMC 数据进行的基于基因的荟萃分析的生物学途径分析确定了在血浆脂蛋白清除中，除了多个免疫相关途径外，阿尔茨海默病关联信号显著富集。
来自大脑和外周组织的基因表达数据可以提高检测阿尔茨海默病潜在调节变异的能力。但是，外周组织中的关联可能反映了基因的组织共享调节变异。因此，未来的功能研究应进行，以验证这些关联的生物学意义以及它们是否代表新的发病组织。
