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

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          Abstract

          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.

          Author Summary

          Gene expression profiling of human tissues typically reveals a complex structure of co-regulation of gene expression that has yet to be explored with regard to the genetic and environmental sources of covariance or its implications for quantitative and clinical traits. Here we show that peripheral blood samples from multiple studies can be described by nine common axes of variation that collectively explain up to one half of all transcriptional variance in blood. Specific axes diverge according to environmental variables such as lifestyle and infectious disease exposure, but a strong genetic component to axis regulation is also inferred. As few as 10 “blood-informative transcripts” (BITs) can be used to define each axis and potentially classify individuals with respect to multiple aspects of their blood and immune function. The analysis of longitudinal profiles of one individual shows how these change relative to clinical shifts in metabolic profile following viral infection. The notion that gene expression diverges along genetic paths of least resistance defined by these axes has important implications for interpreting differential expression in case-control studies of disease.

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          Author and article information

          Contributors
          Role: Editor
          Journal
          PLoS Genet
          PLoS Genet
          plos
          plosgen
          PLoS Genetics
          Public Library of Science (San Francisco, USA )
          1553-7390
          1553-7404
          March 2013
          March 2013
          14 March 2013
          : 9
          : 3
          : e1003362
          Affiliations
          [1 ]Center for Integrative Genomics, School of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America
          [2 ]Saint Justine Children's Hospital, University of Montreal, Montreal, Quebec, Canada
          [3 ]Center for Health Discovery and Well Being, Emory University Midtown Hospital, Atlanta, Georgia, United States of America
          University of Chicago, United States of America
          Author notes

          The authors have declared that no competing interests exist.

          Conceived and designed the experiments: GG KLB. Performed the experiments: DA YI. Analyzed the data: MP JK APN GG. Wrote the paper: MP GG.

          Article
          PGENETICS-D-12-02473
          10.1371/journal.pgen.1003362
          3597511
          23516379
          401e7ce7-4ba8-4c64-bc1d-765733d501f9
          Copyright @ 2013

          This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

          History
          : 2 October 2012
          : 18 January 2013
          Page count
          Pages: 13
          Funding
          This work was supported by start-up funding to GG from the Georgia Tech Research Institute. Funding for the DILGOM study was provided by the Academy of Finland, grant 118065. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
          Categories
          Research Article
          Biology
          Genomics
          Genome Expression Analysis
          Immunology
          Genetics of the Immune System
          Systems Biology

          Genetics
          Genetics

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