Amity Institute of Neuropsychology & Neurosciences, Amity University, Noida 201303, India.
School of Life Sciences, Jawaharlal Nehru University, New Delhi 110067, India.
Biomolecules. 2022 Mar 15;12(3):451. doi: 10.3390/biom12030451.
Dementia-a syndrome affecting human cognition-is a major public health concern given to its rising prevalence worldwide. Though multiple research studies have analyzed disorders such as Alzheimer's disease and Frontotemporal dementia using a systems biology approach, a similar approach to dementia syndrome as a whole is required. In this study, we try to find the high-impact core regulating processes and factors involved in dementia's protein-protein interaction network. We also explore various aspects related to its stability and signal propagation. Using gene interaction databases such as STRING and GeneMANIA, a principal dementia network (PDN) consisting of 881 genes and 59,085 interactions was achieved. It was assortative in nature with hierarchical, scale-free topology enriched in various gene ontology (GO) categories and KEGG pathways, such as negative and positive regulation of apoptotic processes, macroautophagy, aging, response to drug, protein binding, etc. Using a clustering algorithm (Louvain method of modularity maximization) iteratively, we found a number of communities at different levels of hierarchy in PDN consisting of 95 "motif-localized hubs", out of which, 7 were present at deepest level and hence were key regulators (KRs) of PDN (HSP90AA1, HSP90AB1, EGFR, FYN, JUN, CELF2 and CTNNA3). In order to explore aspects of network's resilience, a knockout (of motif-localized hubs) experiment was carried out. It changed the network's topology from a hierarchal scale-free topology to scale-free, where independent clusters exhibited greater control. Additionally, network experiments on interaction of druggable genome and motif-localized hubs were carried out where UBC, EGFR, APP, CTNNB1, NTRK1, FN1, HSP90AA1, MDM2, VCP, CTNNA1 and GRB2 were identified as hubs in the resultant network (RN). We finally concluded that stability and resilience of PDN highly relies on motif-localized hubs (especially those present at deeper levels), making them important therapeutic intervention candidates. HSP90AA1, involved in heat shock response (and its master regulator, i.e., HSF1), and EGFR are most important genes in pathology of dementia apart from KRs, given their presence as KRs as well as hubs in RN.
痴呆症是一种影响人类认知的综合征，由于其在全球的患病率不断上升，因此成为一个主要的公共卫生关注点。尽管有多项研究采用系统生物学方法分析了阿尔茨海默病和额颞叶痴呆等疾病，但仍需要采用类似的方法来研究整个痴呆症综合征。在这项研究中，我们试图找到涉及痴呆症蛋白质-蛋白质相互作用网络的高影响核心调节过程和因素。我们还探讨了与其稳定性和信号传播相关的各个方面。使用基因相互作用数据库，如 STRING 和 GeneMANIA，我们构建了一个由 881 个基因和 59085 个相互作用组成的主要痴呆症网络（PDN）。该网络具有层次结构和无标度拓扑性质，富集了各种基因本体论（GO）类别和 KEGG 途径，如凋亡过程的负调控和正调控、巨自噬、衰老、对药物的反应、蛋白质结合等。通过反复使用聚类算法（模块度最大化的 Louvain 方法），我们在 PDN 中发现了不同层次的多个社区，其中包含 95 个“基序定位枢纽”，其中 7 个位于最深层次，因此是 PDN 的关键调节因子（KRs）（HSP90AA1、HSP90AB1、EGFR、FYN、JUN、CELF2 和 CTNNA3）。为了探索网络弹性的各个方面，我们进行了敲除（基序定位枢纽）实验。该实验将网络的拓扑结构从层次无标度拓扑结构改变为无标度拓扑结构，其中独立的簇表现出更大的控制能力。此外，我们还对可药用基因组和基序定位枢纽之间的相互作用进行了网络实验，结果鉴定出 UBC、EGFR、APP、CTNNB1、NTRK1、FN1、HSP90AA1、MDM2、VCP、CTNNA1 和 GRB2 是网络中的枢纽。最后，我们得出结论，PDN 的稳定性和弹性高度依赖于基序定位枢纽（特别是那些位于更深层次的枢纽），这使它们成为重要的治疗干预候选物。除了 KR 之外，HSP90AA1 还参与了热休克反应（及其主调节因子，即 HSF1），EGFR 是痴呆症病理学中除 KR 之外最重要的基因，因为它们既是 KR 也是 RN 中的枢纽。
