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

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

Authors :
Gudmundsdottir, Valborg
Pedersen, Helle Krogh
Mazzoni, Gianluca
Allin, Kristine H.
Artati, Anna
Beulens, Joline W.
Banasik, Karina
Brorsson, Caroline
Cederberg, Henna
Chabanova, Elizaveta
De Masi, Federico
Elders, Petra J.
Forgie, Ian
Giordano, Giuseppe N.
Grallert, Harald
Gupta, Ramneek
Haid, Mark
Hansen, Torben
Hansen, Tue H.
Hattersley, Andrew T.
Heggie, Alison
Hong, Mun-Gwan
Jones, Angus G.
Koivula, Robert
Kokkola, Tarja
Laakso, Markku
Longreen, Peter
Mahajan, Anubha
Mari, Andrea
McDonald, Timothy J.
McEvoy, Donna
Musholt, Petra B.
Pavo, Imre
Prehn, Cornelia
Ruetten, Hartmut
Ridderstrale, Martin
Rutters, Femke
Sharma, Sapna
Slieker, Roderick C.
Syed, Ali
Tajes, Juan Fernandez
Thomas, Cecilia Engel
Thomsen, Henrik S.
Vangipurapu, Jagadish
Vestergaard, Henrik
Vinuela, Ana
Wesolowska-Andersen, Agata
Walker, Mark
Adamski, Jerzy
Schwenk, Jochen M.
McCarthy, Mark, I
Pearson, Ewan
Dermitzakis, Emmanouil
Franks, Paul W.
Pedersen, Oluf
Brunak, Soren
Gudmundsdottir, Valborg
Pedersen, Helle Krogh
Mazzoni, Gianluca
Allin, Kristine H.
Artati, Anna
Beulens, Joline W.
Banasik, Karina
Brorsson, Caroline
Cederberg, Henna
Chabanova, Elizaveta
De Masi, Federico
Elders, Petra J.
Forgie, Ian
Giordano, Giuseppe N.
Grallert, Harald
Gupta, Ramneek
Haid, Mark
Hansen, Torben
Hansen, Tue H.
Hattersley, Andrew T.
Heggie, Alison
Hong, Mun-Gwan
Jones, Angus G.
Koivula, Robert
Kokkola, Tarja
Laakso, Markku
Longreen, Peter
Mahajan, Anubha
Mari, Andrea
McDonald, Timothy J.
McEvoy, Donna
Musholt, Petra B.
Pavo, Imre
Prehn, Cornelia
Ruetten, Hartmut
Ridderstrale, Martin
Rutters, Femke
Sharma, Sapna
Slieker, Roderick C.
Syed, Ali
Tajes, Juan Fernandez
Thomas, Cecilia Engel
Thomsen, Henrik S.
Vangipurapu, Jagadish
Vestergaard, Henrik
Vinuela, Ana
Wesolowska-Andersen, Agata
Walker, Mark
Adamski, Jerzy
Schwenk, Jochen M.
McCarthy, Mark, I
Pearson, Ewan
Dermitzakis, Emmanouil
Franks, Paul W.
Pedersen, Oluf
Brunak, Soren
Publication Year :
2020

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 signal

Details

Database :
OAIster
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1234751700
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1186.s13073-020-00806-6