Emilsson Valur, Thorleifsson Gudmar, Zhang Bin, Leonardson Amy S, Zink Florian, Zhu Jun, Carlson Sonia, Helgason Agnar, Walters G Bragi, Gunnarsdottir Steinunn, Mouy Magali, Steinthorsdottir Valgerdur, Eiriksdottir Gudrun H, Bjornsdottir Gyda, Reynisdottir Inga, Gudbjartsson Daniel, Helgadottir Anna, Jonasdottir Aslaug, Jonasdottir Adalbjorg, Styrkarsdottir Unnur, Gretarsdottir Solveig, Magnusson Kristinn P, Stefansson Hreinn, Fossdal Ragnheidur, Kristjansson Kristleifur, Gislason Hjortur G, Stefansson Tryggvi, Leifsson Bjorn G, Thorsteinsdottir Unnur, Lamb John R, Gulcher Jeffrey R, Reitman Marc L, Kong Augustine, Schadt Eric E, Stefansson Kari
deCODE genetics, 101 Reykjavik, Iceland.
Nature. 2008 Mar 27;452(7186):423-8. doi: 10.1038/nature06758. Epub 2008 Mar 16.
Common human diseases result from the interplay of many genes and environmental factors. Therefore, a more integrative biology approach is needed to unravel the complexity and causes of such diseases. To elucidate the complexity of common human diseases such as obesity, we have analysed the expression of 23,720 transcripts in large population-based blood and adipose tissue cohorts comprehensively assessed for various phenotypes, including traits related to clinical obesity. In contrast to the blood expression profiles, we observed a marked correlation between gene expression in adipose tissue and obesity-related traits. Genome-wide linkage and association mapping revealed a highly significant genetic component to gene expression traits, including a strong genetic effect of proximal (cis) signals, with 50% of the cis signals overlapping between the two tissues profiled. Here we demonstrate an extensive transcriptional network constructed from the human adipose data that exhibits significant overlap with similar network modules constructed from mouse adipose data. A core network module in humans and mice was identified that is enriched for genes involved in the inflammatory and immune response and has been found to be causally associated to obesity-related traits.
常见的人类疾病是由许多基因和环境因素相互作用导致的。因此，需要一种更综合的生物学方法来揭示此类疾病的复杂性和病因。为了阐明肥胖等常见人类疾病的复杂性，我们分析了23720个转录本在基于大量人群的血液和脂肪组织队列中的表达情况，这些队列针对包括与临床肥胖相关的特征在内的各种表型进行了全面评估。与血液表达谱不同，我们观察到脂肪组织中的基因表达与肥胖相关特征之间存在显著相关性。全基因组连锁和关联图谱显示基因表达特征具有高度显著的遗传成分，包括近端（顺式）信号的强大遗传效应，在分析的两种组织中，50%的顺式信号重叠。在这里，我们展示了一个由人类脂肪数据构建的广泛转录网络，该网络与由小鼠脂肪数据构建的类似网络模块有显著重叠。在人类和小鼠中鉴定出一个核心网络模块，该模块富含参与炎症和免疫反应的基因，并且已被发现与肥胖相关特征存在因果关联。
