Wei Zihan, Iyer Meghna R, Zhao Benjamin, Deng Jennifer, Mitchell Cassie S
Laboratory for Pathology Dynamics, Department of Biomedical Engineering, Georgia Institute of Technology & Emory University School of Medicine, Atlanta, GA 30322, USA.
Center for Machine Learning at Georgia Tech, Atlanta, GA 30332, USA.
Int J Mol Sci. 2024 Dec 15;25(24):13450. doi: 10.3390/ijms252413450.
The overlapping molecular pathophysiology of Alzheimer's Disease (AD), Amyotrophic Lateral Sclerosis (ALS), and Frontotemporal Dementia (FTD) was analyzed using relationships from a knowledge graph of 33+ million biomedical journal articles. The unsupervised learning rank aggregation algorithm from SemNet 2.0 compared the most important amino acid, peptide, and protein (AAPP) nodes connected to AD, ALS, or FTD. FTD shared 99.9% of its nodes with ALS and AD; AD shared 64.2% of its nodes with FTD and ALS; and ALS shared 68.3% of its nodes with AD and FTD. The results were validated and mapped to functional biological processes using supervised human supervision and an external large language model. The overall percentages of mapped intersecting biological processes were as follows: inflammation and immune response, 19%; synapse and neurotransmission, 19%; cell cycle, 15%; protein aggregation, 12%; membrane regulation, 11%; stress response and regulation, 9%; and gene regulation, 4%. Once normalized for node count, biological mappings for cell cycle regulation and stress response were more prominent in the intersection of AD and FTD. Protein aggregation, gene regulation, and energetics were more prominent in the intersection of ALS and FTD. Synapse and neurotransmission, membrane regulation, and inflammation and immune response were greater at the intersection of AD and ALS. Given the extensive molecular pathophysiology overlap, small differences in regulation, genetic, or environmental factors likely shape the underlying expressed disease phenotype. The results help prioritize testable hypotheses for future clinical or experimental research.
利用一个包含3300多万篇生物医学期刊文章的知识图谱中的关系,分析了阿尔茨海默病(AD)、肌萎缩侧索硬化症(ALS)和额颞叶痴呆(FTD)重叠的分子病理生理学。SemNet 2.0的无监督学习排名聚合算法比较了与AD、ALS或FTD相关的最重要的氨基酸、肽和蛋白质(AAPP)节点。FTD与ALS和AD共享其99.9%的节点;AD与FTD和ALS共享其64.2%的节点;ALS与AD和FTD共享其68.3%的节点。使用人工监督和外部大语言模型对结果进行验证,并将其映射到功能性生物学过程。映射的交叉生物学过程的总体百分比如下:炎症和免疫反应,19%;突触和神经传递,19%;细胞周期,15%;蛋白质聚集,12%;膜调节,11%;应激反应和调节,9%;以及基因调节,4%。一旦根据节点数量进行归一化,细胞周期调节和应激反应的生物学映射在AD和FTD的交叉点更为突出。蛋白质聚集、基因调节和能量学在ALS和FTD的交叉点更为突出。突触和神经传递、膜调节以及炎症和免疫反应在AD和ALS的交叉点更为显著。鉴于广泛的分子病理生理学重叠,调节、遗传或环境因素的微小差异可能塑造潜在的表达疾病表型。这些结果有助于为未来的临床或实验研究确定可检验假设的优先级。