Institute of Pharmaceutical Science, King's College London, London, UK.
Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
Transl Neurodegener. 2020 Sep 21;9(1):36. doi: 10.1186/s40035-020-00215-0.
There is an urgent need to understand the pathways and processes underlying Alzheimer's disease (AD) for early diagnosis and development of effective treatments. This study was aimed to investigate Alzheimer's dementia using an unsupervised lipid, protein and gene multi-omics integrative approach.
A lipidomics dataset comprising 185 AD patients, 40 mild cognitive impairment (MCI) individuals and 185 controls, and two proteomics datasets (295 AD, 159 MCI and 197 controls) were used for weighted gene co-expression network analyses (WGCNA). Correlations of modules created within each modality with clinical AD diagnosis, brain atrophy measures and disease progression, as well as their correlations with each other, were analyzed. Gene ontology enrichment analysis was employed to examine the biological processes and molecular and cellular functions of protein modules associated with AD phenotypes. Lipid species were annotated in the lipid modules associated with AD phenotypes. The associations between established AD risk loci and the lipid/protein modules that showed high correlation with AD phenotypes were also explored.
Five of the 20 identified lipid modules and five of the 17 identified protein modules were correlated with clinical AD diagnosis, brain atrophy measures and disease progression. The lipid modules comprising phospholipids, triglycerides, sphingolipids and cholesterol esters were correlated with AD risk loci involved in immune response and lipid metabolism. The five protein modules involved in positive regulation of cytokine production, neutrophil-mediated immunity, and humoral immune responses were correlated with AD risk loci involved in immune and complement systems and in lipid metabolism (the APOE ε4 genotype).
Modules of tightly regulated lipids and proteins, drivers in lipid homeostasis and innate immunity, are strongly associated with AD phenotypes.
迫切需要了解阿尔茨海默病（AD）的途径和过程，以便进行早期诊断和开发有效的治疗方法。本研究旨在采用无监督脂质组学、蛋白质组学和基因多组学整合方法研究阿尔茨海默病痴呆症。
使用包含 185 名 AD 患者、40 名轻度认知障碍（MCI）个体和 185 名对照者的脂质组学数据集以及包含 295 名 AD、159 名 MCI 和 197 名对照者的两个蛋白质组学数据集进行加权基因共表达网络分析（WGCNA）。分析了在每个模态内创建的模块与临床 AD 诊断、脑萎缩测量和疾病进展的相关性，以及它们彼此之间的相关性。通过基因本体论富集分析，研究了与 AD 表型相关的蛋白质模块的生物学过程和分子及细胞功能。注释了与 AD 表型相关的脂质模块中的脂质种类。还探讨了已建立的 AD 风险基因座与与 AD 表型高度相关的脂质/蛋白质模块之间的关联。
在鉴定的 20 个脂质模块中有 5 个模块和在鉴定的 17 个蛋白质模块中有 5 个模块与临床 AD 诊断、脑萎缩测量和疾病进展相关。包含磷脂、甘油三酯、鞘脂和胆固醇酯的脂质模块与涉及免疫反应和脂质代谢的 AD 风险基因座相关。涉及细胞因子产生的正调控、中性粒细胞介导的免疫和体液免疫反应的五个蛋白质模块与涉及免疫和补体系统以及脂质代谢的 AD 风险基因座（APOE ε4 基因型）相关。
受严密调控的脂质和蛋白质模块、脂质稳态和固有免疫的驱动因素与 AD 表型密切相关。
