Genetics of gene expression and its effect on disease

• Published in: Nature (London) Vol. 452; no. 7186; pp. 423 - 428
• Main Authors: Schadt, Eric E, Stefansson, Kari, 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
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 27.03.2008; Nature Publishing; Nature Publishing Group
• Subjects: Adipose tissue; Adipose Tissue - metabolism; Adolescent; Adult; Aged; Aged, 80 and over; Animals; Biological and medical sciences; Biometrics; Blood; Blood - metabolism; Body fat; Body Mass Index; Cohort Studies; Disease; Environmental factors; European Continental Ancestry Group - genetics; Female; Gene expression; Gene Expression Profiling; Gene Expression Regulation - genetics; Genetics; Genome, Human; Humanities and Social Sciences; Humans; Iceland; Immune response; Lod Score; Male; Medical sciences; Metabolic diseases; Mice; Middle Aged; multidisciplinary; Obesity; Obesity - genetics; Polymorphism, Single Nucleotide - genetics; Quantitative Trait Loci - genetics; Sample Size; Science; Science (multidisciplinary); Statistical power; Waist-Hip Ratio; Iceland; United States > US; Human; Quantitative trait loci; Obesity; Genetic variability; Etiology; Nutrition disorder; Genetics; Genotype; Single nucleotide polymorphism; Gene expression; Nutritional status
• ISSN: 0028-0836; 1476-4687
• DOI: 10.1038/nature06758

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. Obesity gets complicated Complex human diseases result from the interplay of many genetic and environmental factors. To build up a picture of the factors contributing to one such disease, obesity, gene expression was evaluated as a quantitative trait in blood and adipose tissue samples from hundreds of Icelandic subjects aged 18 to 85. The results reveal a tendency to certain characteristic patterns of gene activation in the fatty tissues — though to a much lesser extent in the blood — of people with a higher body mass index. A transcriptional network constructed from the adipose tissue data has significant overlap with a network based on mouse adipose tissue data. Experimental support for the idea that complex diseases are emergent properties of molecular networks influenced by genes and environment comes from a study in mice. Mice were examined for disturbances in genetic expression networks that correlate with metabolic traits associated with obesity, diabetes and atherosclerosis. Three genes — Lpl , Lactb and Ppm1l — were identified as previously unknown obesity genes. This 'molecular network' approach raises the prospect that therapies might be directed at whole 'disease networks', rather than at one or two specific genes. In this paper gene expression is treated as a quantitative trait in both blood and adipose tissue, and associations between specific genetic loci and body mass index are identified using a molecular network approach.