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Genetics of gene expression and its effect on disease

Abstract

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.

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Figure 1: eQTL mapping in human blood and adipose tissue.
Figure 2: Genome-wide association screens for eSNPs.
Figure 3: The human and mouse gene transcriptional networks.

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Gene Expression Omnibus

Data deposits

All the gene expression data generated for this study have been deposited into the GEO database under accession numbers GSE7965 and GPL3991. The authors declare competing financial interests: details accompany the full-text HTML version of the paper at www.nature.com/nature.

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Acknowledgements

The authors acknowledge the participating families and the staff at the Clinical Research Centre for their cooperation. Genotyping service was provided at the deCode Genetics genotyping facilities.

Author Contributions V.E., E.E.S., K.S. and G.T. wrote the paper. G.T., E.E.S., A.K., D.G. and F.Z. performed statistical analysis. Tissue sampling and/or molecular profiling was carried out by H.G.G., T.S., B.G.L., G.H.E., S.C., M.M., Aslaug Jonasdottir, Adalbjorg Jonasdottir, G.B. and K.K. V.E., J.Z., U.T., A.S.L., A.H., B.Z., G.B.W., S. Gunnarsdottir, S. Gretarsdottir, K.P.M., V.S., I.R., A.H., U.S., H.S., R.F., J.R.G., K.S., M.L.R. and J.R.L. performed the genetic analysis and/or data-mining. K.S. and E.E.S. contributed equally to this work.

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Correspondence to Eric E. Schadt or Kari Stefansson.

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Competing interests

The following authors own stocks in either deCode Genetics, Inc. or Merck & Co., Inc.: V.E., E.E.S., G.T., G.B., S.C., M.M., J.Z., Aslaug Jonasdottir, Adalbjorg Jonasdottir, K.K., U.T., A.S.L., A.H., B.Z., G.B.W., F.Z., S. Gunnarsdottir, S. Gretarsdottir, K.P.M., V.S., I.R., D.G., A.H., U.S. H.S., R.F., A.K., K.S., J.R.G., M.L.R. and J.R.L.

Supplementary information

Supplementary Information

The file contains Supplementary Results with additional references, Supplementary Tables 1-7 and Supplementary Figures 1-7 with Legends. The file contains Supplementary Results on the probes overlapping SNPs, distribution of cis eSNPs as regards the location of probes, detection of trans eQTLs and eQTL hotspots, comparison of expression linkage and association results and finally the additional information regarding genes in the mouse MEMN that have been shown to be causal for metabolic diseases. Tables include a summary of cohort description (Supplementary Table 1), results on the re-sequencing of array probes (Supplementary Table 2), expression trait vs. clinical trait correlations (Supplementary Table 3), heritability and eQTL results (Supplementary Tables 4 and 5), detection of significant trans eQTLs and eQTL hotspots (Supplementary Table 6) and finally the pathway enrichment for the gene sets in the MEMN module (Supplementary Table 7). The figures show chromosomal distribution of eQTLs in IFB in the real data and a simulated dataset (Supplementary Figure 1), distribution of BMI, gene expression vs. BMI correlations and heritability in the IFA cohort (Supplementary Figure 2), the agreement between the linkage and association data (Supplementary Figure 3), distribution of cis eSNPs as regards the location of probes (Supplementary Figure 4), the localization and specificity of the association signal (Supplementary Figure 5), the gene set overlap between the male and female specific MEMN module in humans (Supplementary Figure 6) and finally the comparison between the connectivity structure of the MEMN genes in between the females and males. (PDF 828 kb)

Supplementary description

The file contains description of the RNA sample processing, the design of the arrays, quality controlling and processing of the probe hybridization. Here, appropriate references and Figure 1 (as an example of the data display) are provided as well. (PDF 179 kb)

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Emilsson, V., Thorleifsson, G., Zhang, B. et al. Genetics of gene expression and its effect on disease. Nature 452, 423–428 (2008). https://doi.org/10.1038/nature06758

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