Profiling the Functional Genetics of Health and Disease using BrainGENIE: The Brain Gene Expression and Network Imputation Engine

摘要 脑部疾病的病理生理学仍不清楚，因为我们无法研究活体中的相关组织。 人类受试者。死后的脑组织是有用的，但昂贵，稀有，而且严重混乱 死前因素和死亡因素。这两个事实激发了人们寻找替代战略的灵感，例如 使用替代标记，如基于血液的基因表达。为了提高这一广泛使用的严谨性 方法，我们开发了一种新的计算方法，称为脑基因表达和网络 利用血液和脑基因之间的生物相似性的归罪引擎(BrainGENIE) 基于血液基因表达谱预测脑组织转录组谱的表达。 BrainGENIE从根本上不同于其他转录组分配方法，并捕获了许多 大脑转录组的变异比例更大，比例也更大。BrainGENIE有能力 预测大脑转录组的大约9%-57%，这将产生大约1.8倍的增长 覆盖范围相对于“黄金标准”方法PrediXcan，这极大地提高了我们的统计能力 检测与疾病相关的基因和途径。我们的建议包含三个具体目标，以改善我们的 方法，并阐明神经精神障碍的生物学途径。目标1：完善 BrainGENIE捕获目前我们的方法没有很好预测的额外基因。目标2：申请 BrainGENIE支持我们收集公开的和内部的数据来预测大脑区域特定基因 8,000多名活人的表达谱，并发现特定区域的基因表达模式 与神经精神障碍和神经退行性疾病有关。目标3：传播BrainGenie 作为独立软件，供其他研究人员自由使用。在最近的遗传和基因组研究的指导下，我们 假设将在神经精神障碍中发现类似的基因失调模式 在涉及先天免疫、染色质重塑、神经发育和神经传递的途径中。 将神经退行性疾病纳入我们的分析将使我们能够确定基因表达 在更广泛的大脑疾病中，这种模式是相同的。我们还希望确定特定于障碍的和 大脑区域特定的转录转录关联。我们的项目将使我们能够对生物学进行新的探索 活人大脑中出现的变化，并创造了改善诊断的机会， 干预和治疗。

Abstract The pathophysiology of brain disorders remains unknown because we cannot study the relevant tissue in living human subjects. Postmortem brain tissue is useful, but expensive, rare, and critically confounded by antemortem and agonal factors. These two facts have inspired the search for alternative strategies, such as the use of surrogate markers like blood-based gene expression. To improve the rigor of this widely used approach, we developed a novel computational method called the Brain Gene Expression and Network Imputation Engine (BrainGENIE) that leverages biological comparability between blood and brain gene expression to predict transcriptome profiles for brain tissue based on blood gene-expression profiles. BrainGENIE is fundamentally different from other transcriptome-imputation methods, and captures a much larger proportion of the variance in—and larger fraction of—the brain transcriptome. BrainGENIE is capable of predicting approximately 9–57% of the brain transcriptome, which yields an approximate 1.8-fold increase in coverage relative to the “gold standard” method PrediXcan, and which greatly improves our statistical power to detect genes and pathways associated with disease. Our proposal contains three Specific Aims to improve our method and shed light on biological pathways underlying neuropsychiatric disorders. Aim 1: Refine BrainGENIE to capture additional genes that are not currently well predicted by our method. Aim 2: Apply BrainGENIE to our collection of publicly available and in-house data to predict brain-region-specific gene expression profiles for over 8,000 living persons, and discover region-specific gene-expression patterns associated with neuropsychiatric disorders and neurodegenerative diseases. Aim 3: Disseminate BrainGENIE as stand-alone software for other researchers to use freely. Guided by recent genetic and genomic studies, we hypothesize that comparable patterns of gene dysregulation will be found across neuropsychiatric disorders among pathways involving innate immunity, chromatin remodeling, neurodevelopment, and neurotransmission. Inclusion of neurodegenerative disorders in our analysis will allow us to determine whether gene expression patterns are shared across a broader range of brain disorders. We also expect to identify disorder-specific and brain-region-specific transcriptomic associations. Our project will enable new lines of inquiry into biological changes that emerge in the brains of living persons, and create opportunities to improve diagnostics, intervention, and treatment.