PDF(Pubmed)
Abstract：
Despite the significant burden, cost, and worse prognosis of Alzheimer\'s disease (AD) with behavioral and psychological symptoms of dementia (BPSD), little is known about the molecular causes of these symptoms. Using antemortem assessments of BPSD in AD, we demonstrate that individual BPSD can be grouped into 4 domain factors in our cohort: affective, apathy, agitation, and psychosis. Then, we performed a transcriptome-wide analysis for each domain utilizing bulk RNA-seq of post-mortem anterior cingulate cortex (ACC) tissues. Though all 4 domains are associated with a predominantly downregulated pattern of hundreds of differentially expressed genes (DEGs), most DEGs are unique to each domain, with only 22 DEGs being common to all BPSD domains, including TIMP1. Weighted gene co-expression network analysis (WGCNA) yielded multiple transcriptional modules that were shared between BPSD domains or unique to each domain, and NetDecoder was used to analyze context-dependent information flow through the biological network. For the agitation domain, we found that all DEGs and a highly associated transcriptional module were functionally enriched for ECM-related genes including TIMP1, TAGLN, and FLNA. Another unique transcriptional module also associated with the agitation domain was enriched with genes involved in post-synaptic signaling, including DRD1, PDE1B, CAMK4, and GABRA4. By comparing context-dependent changes in DEGs between cases and control networks, ESR1 and PARK2 were implicated as two high-impact genes associated with agitation that mediated significant information flow through the biological network. Overall, our work establishes unique targets for future study of the biological mechanisms of BPSD and resultant drug development.
摘要：
尽管负担很大,成本,阿尔茨海默病（AD）伴痴呆的行为和心理症状（BPSD）的预后较差，对这些症状的分子原因知之甚少。使用AD患者BPSD的死前评估，我们证明了个体BPSD在我们的队列中可以分为4个领域因素：情感，冷漠,激动,和精神病。然后，我们利用死后前扣带皮质(ACC)组织的大量RNA-seq对每个结构域进行了全转录组分析.尽管所有4个结构域都与数百个差异表达基因（DEG）的主要下调模式相关，大多数DEG对每个域都是唯一的，所有BPSD域都只有22个DEG，包括TIMP1。加权基因共表达网络分析（WGCNA）产生了多个转录模块，这些模块在BPSD结构域之间共享或每个结构域独特。NetDecoder用于分析通过生物网络的上下文相关信息流。对于搅动域，我们发现所有DEGs和高度相关的转录模块在功能上富集了ECM相关基因，包括TIMP1，TAGLN，还有FLNA.另一个独特的转录模块也与搅动结构域相关，富含参与突触后信号传导的基因，包括DRD1、PDE1B、CAMK4和GABRA4。通过比较案例和控制网络之间DEG的上下文相关变化，ESRl和PARK2被认为是与激动相关的两个高影响基因，它们介导了通过生物网络的重要信息流。总的来说,我们的工作为未来研究BPSD的生物学机制和由此产生的药物开发建立了独特的靶标.
