Blood-Informative Transcripts Define Nine Common Axes of Peripheral Blood Gene Expression

We describe a novel approach to capturing the covariance structure of peripheral blood gene expression that relies on the identification of highly conserved Axes of variation. Starting with a comparison of microarray transcriptome profiles for a new dataset of 189 healthy adult participants in the Emory-Georgia Tech Center for Health Discovery and Well-Being (CHDWB) cohort, with a previously published study of 208 adult Moroccans, we identify nine Axes each with between 99 and 1,028 strongly co-regulated transcripts in common. Each axis is enriched for gene ontology categories related to sub-classes of blood and immune function, including T-cell and B-cell physiology and innate, adaptive, and anti-viral responses. Conservation of the Axes is demonstrated in each of five additional population-based gene expression profiling studies, one of which is robustly associated with Body Mass Index in the CHDWB as well as Finnish and Australian cohorts. Furthermore, ten tightly co-regulated genes can be used to define each Axis as “Blood Informative Transcripts” (BITs), generating scores that define an individual with respect to the represented immune activity and blood physiology. We show that environmental factors, including lifestyle differences in Morocco and infection leading to active or latent tuberculosis, significantly impact specific axes, but that there is also significant heritability for the Axis scores. In the context of personalized medicine, reanalysis of the longitudinal profile of one individual during and after infection with two respiratory viruses demonstrates that specific axes also characterize clinical incidents. This mode of analysis suggests the view that, rather than unique subsets of genes marking each class of disease, differential expression reflects movement along the major normal Axes in response to environmental and genetic stimuli.

本研究提出一种全新方法，用于解析外周血基因表达的协方差结构，该方法核心为识别高度保守的变异轴（Axes of variation）。本研究以埃默里-佐治亚理工学院健康发现与福祉中心（CHDWB）队列中189名健康成人的全新数据集的微阵列转录组谱，与已发表的208名摩洛哥成人队列的转录组谱进行比较为起点，共识别出9条变异轴，每条变异轴均包含99至1028个协同调控的共有转录本。每条变异轴均富集有与血液及免疫功能亚类相关的基因本体（Gene Ontology, GO）术语，涵盖T细胞、B细胞生理过程以及固有免疫、适应性免疫与抗病毒应答等通路。另有5项基于人群的基因表达谱研究均验证了该变异轴的保守性，其中1项研究在CHDWB队列、芬兰队列与澳大利亚队列中，均发现变异轴与体质量指数（Body Mass Index, BMI）存在显著关联。此外，每条变异轴可通过10个紧密共调控的基因进行定义，此类基因被称为‘血液信息转录本（Blood Informative Transcripts, BITs）’；通过计算该类转录本的得分，可表征个体对应的免疫活性与血液生理状态。本研究发现，包括摩洛哥人群生活方式差异在内的环境因素，以及引发活动性或潜伏性肺结核的感染，均会对特定变异轴产生显著影响；同时，变异轴得分也存在显著的遗传力。在个性化医疗场景下，对1名个体感染两种呼吸道病毒期间及感染后的纵向转录组谱进行重新分析的结果显示，特定变异轴亦可用于表征临床事件。此种分析模式表明，疾病并非由独特的基因子集所标记，而是差异表达反映了机体在环境与遗传刺激下，沿主要正常变异轴发生的动态变化。