Marques-Coelho Diego, Iohan Lukas da Cruz Carvalho, Melo de Farias Ana Raquel, Flaig Amandine, Lambert Jean-Charles, Costa Marcos Romualdo
Brain Institute, Federal University of Rio Grande do Norte, Av. Nascimento de Castro, 2155, Natal, Brazil.
Bioinformatics Multidisciplinary Environment (BioME), Federal University of Rio Grande do Norte, Natal, Brazil.
NPJ Aging Mech Dis. 2021 Jan 4;7(1):2. doi: 10.1038/s41514-020-00052-5.
Alzheimer's disease (AD) is the leading cause of dementia in aging individuals. Yet, the pathophysiological processes involved in AD onset and progression are still poorly understood. Among numerous strategies, a comprehensive overview of gene expression alterations in the diseased brain could contribute for a better understanding of the AD pathology. In this work, we probed the differential expression of genes in different brain regions of healthy and AD adult subjects using data from three large transcriptomic studies: Mayo Clinic, Mount Sinai Brain Bank (MSBB), and ROSMAP. Using a combination of differential expression of gene and isoform switch analyses, we provide a detailed landscape of gene expression alterations in the temporal and frontal lobes, harboring brain areas affected at early and late stages of the AD pathology, respectively. Next, we took advantage of an indirect approach to assign the complex gene expression changes revealed in bulk RNAseq to individual cell types/subtypes of the adult brain. This strategy allowed us to identify previously overlooked gene expression changes in the brain of AD patients. Among these alterations, we show isoform switches in the AD causal gene amyloid-beta precursor protein (APP) and the risk gene bridging integrator 1 (BIN1), which could have important functional consequences in neuronal cells. Altogether, our work proposes a novel integrative strategy to analyze RNAseq data in AD and other neurodegenerative diseases based on both gene/transcript expression and regional/cell-type specificities.
阿尔茨海默病（AD）是老年人痴呆的主要病因。然而，AD发病和进展所涉及的病理生理过程仍知之甚少。在众多策略中，全面概述患病大脑中的基因表达改变有助于更好地理解AD病理学。在这项工作中，我们使用来自三项大型转录组学研究的数据，即梅奥诊所、西奈山脑库（MSBB）和ROSMAP，探究了健康和AD成年受试者不同脑区中基因的差异表达。通过结合基因差异表达和异构体开关分析，我们详细描绘了颞叶和额叶中基因表达改变的情况，这两个脑区分别在AD病理的早期和晚期受到影响。接下来，我们采用一种间接方法，将大量RNA测序中揭示的复杂基因表达变化分配到成年大脑的各个细胞类型/亚型中。这一策略使我们能够识别出AD患者大脑中先前被忽视的基因表达变化。在这些改变中，我们发现AD致病基因淀粉样前体蛋白（APP）和风险基因桥连整合因子1（BIN1）存在异构体开关，这可能对神经元细胞产生重要的功能影响。总之，我们的工作提出了一种基于基因/转录本表达以及区域/细胞类型特异性来分析AD和其他神经退行性疾病中RNA测序数据的新型综合策略。
