UK Dementia Research Institute at Cardiff University, School of Medicine, Cardiff, CF24 4HQ, UK.
Division of Infection and Immunity, School of Medicine, Systems Immunity Research Institute, Cardiff University, Cardiff, CF14 4XN, UK.
Genes (Basel). 2021 Mar 20;12(3):443. doi: 10.3390/genes12030443.
Late-onset Alzheimer's disease (LOAD), the most common cause of dementia, and a huge global health challenge, is a neurodegenerative disease of uncertain aetiology. To deliver effective diagnostics and therapeutics, understanding the molecular basis of the disease is essential. Contemporary large genome-wide association studies (GWAS) have identified over seventy novel genetic susceptibility loci for LOAD. Most are implicated in microglial or inflammatory pathways, bringing inflammation to the fore as a candidate pathological pathway. Among the most significant GWAS hits are three complement genes: , encoding the fluid-phase complement inhibitor clusterin; encoding complement receptor 1 (CR1); and recently, encoding the complement enzyme C1s. Complement activation is a critical driver of inflammation; changes in complement genes may impact risk by altering the inflammatory status in the brain. To assess complement gene association with LOAD risk, we manually created a comprehensive complement gene list and tested these in gene-set analysis with LOAD summary statistics. We confirmed associations of and genes with LOAD but showed no significant associations for the complement gene-set when excluding and . No significant association with other complement genes, including , was seen in the IGAP dataset; however, these may emerge from larger datasets.
迟发性阿尔茨海默病(LOAD)是最常见的痴呆症病因,也是一个全球性的健康挑战,是一种病因不明的神经退行性疾病。为了提供有效的诊断和治疗,了解疾病的分子基础是至关重要的。当代的全基因组关联研究(GWAS)已经确定了超过 70 个新的遗传易感性 LOAD 位点。大多数与小胶质细胞或炎症途径有关,使炎症成为候选病理途径。在最重要的 GWAS 命中中,有三个补体基因: ,编码液相关补体抑制剂载脂蛋白; 编码补体受体 1(CR1);最近, 编码补体酶 C1s。补体激活是炎症的关键驱动因素;补体基因的变化可能通过改变大脑中的炎症状态来影响风险。为了评估补体基因与 LOAD 风险的关联,我们手动创建了一个全面的补体基因列表,并使用 LOAD 汇总统计数据对其进行了基因集分析。我们证实了 和 基因与 LOAD 之间的关联,但在排除 和 时,补体基因集没有显著关联。在 IGAP 数据集,没有看到其他补体基因,包括 ,与 LOAD 有显著关联;然而,这些可能会在更大的数据集上显现出来。