Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study

Valborg Gudmundsdottir, Helle Krogh Pedersen, Gianluca Mazzoni, Kristine H. Allin, Anna Artati, Joline W. Beulens, Karina Banasik, Caroline Brorsson, Henna Cederberg, Elizaveta Chabanova, Federico De Masi, Petra J. Elders, Ian Forgie, Giuseppe N. Giordano, Harald Grallert, Ramneek Gupta, Mark Haid, Torben Hansen, Tue H. Hansen, Andrew T. HattersleyAlison Heggie, Mun-Gwan Hong, Angus G. Jones, Robert Koivula, Tarja Kokkola, Markku Laakso, Peter Løngreen, Anubha Mahajan, Andrea Mari, Timothy J. McDonald, Donna McEvoy, Petra B. Musholt, Imre Pavo, Cornelia Prehn, Hartmut Ruetten, Martin Ridderstrale, Femke Rutters, Sapna Sharma, Roderick C. Slieker, Ali Syed, Juan Fernandez Tajes, Cecilia Engel Thomas, Henrik S. Thomsen, Jagadish Vangipurapu, Henrik Vestergaard, Ana Vinuela, Agata Wesolowska-Andersen, Mark Walker, Jerzy Adamski, Jochen M. Schwenk, Mark McCarthy, Ewan Pearson, Emmanouil Dermitzakis, Paul W. Franks, Oluf Pedersen, Søren Brunak*

*Corresponding author for this work

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Abstract

Background The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. Methods Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. Results We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling. Conclusions Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.

Original languageEnglish
Article number109
JournalGenome Medicine
Volume12
Issue number1
Number of pages17
ISSN1756-994X
DOIs
Publication statusPublished - 2020

Keywords

  • Type 2 diabetes
  • Transcriptomics
  • Co-expression modules
  • Omics data integration
  • GENE-EXPRESSION PROFILES
  • GENOME-WIDE ASSOCIATION
  • INSULIN-RESISTANCE
  • MONONUCLEAR-CELLS
  • BIOMARKERS
  • COUNT
  • RISK
  • TRANSCRIPTOME
  • INFLAMMATION
  • DRIVERS

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