Rahman Most Tahmina, Saeed Fahad, Bozdag Serdar
Department of Computer Science and Engineering, University of North Texas, 1155 Union Circle #311366 Denton, Texas 76203, United States.
BioDiscovery Institute, University of North Texas, 1155 Union Circle #311366 Denton, Texas 76203, United States.
bioRxiv. 2024 Nov 15:2024.11.12.623269. doi: 10.1101/2024.11.12.623269.
Alzheimer's disease (AD) is a neurogenerative disease that affects millions worldwide with no effective treatment. Several studies have been conducted to decipher to genomic underpinnings of AD. Due to its complex nature, many genes have been found to be associated with AD. Despite these findings, the pathophysiology of the disease is still elusive. To discover new putative AD-associated genes, in this study, we integrated multimodal gene and phenotype datasets of AD using network biology methods to prioritize potential AD-related genes. We constructed a multiplex heterogeneous network composed of patient and gene similarity networks utilizing phenotypic and omics datasets of AD patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We applied PhenoGeneRanker to traverse this network to discover potential AD-associated genes. To assess the impact of each network layer and seed gene, we also run PhenoGeneRanker on different variants of the network and seed genes. Our results showed that top-ranked genes captured several known AD-related genes and were enriched in Gene Ontology (GO) terms related to AD. We also observed that several top-ranked genes that are not in AD-associated gene list had literature supporting their potential relevance to AD.
阿尔茨海默病（AD）是一种神经退行性疾病，全球数以百万计的人受其影响，且尚无有效治疗方法。已经开展了多项研究来破解AD的基因组基础。由于其性质复杂，已发现许多基因与AD相关。尽管有这些发现，该疾病的病理生理学仍然难以捉摸。为了发现新的潜在AD相关基因，在本研究中，我们使用网络生物学方法整合了AD的多模态基因和表型数据集，以对潜在的AD相关基因进行优先级排序。我们利用来自阿尔茨海默病神经影像倡议（ADNI）数据库的AD患者的表型和组学数据集，构建了一个由患者和基因相似性网络组成的多重异质网络。我们应用PhenoGeneRanker遍历该网络以发现潜在的AD相关基因。为了评估每个网络层和种子基因的影响，我们还在网络和种子基因的不同变体上运行了PhenoGeneRanker。我们的结果表明，排名靠前的基因捕获了几个已知的AD相关基因，并在与AD相关的基因本体（GO）术语中富集。我们还观察到，一些不在AD相关基因列表中的排名靠前的基因有文献支持它们与AD的潜在相关性。
