TY - JOUR
T1 - Whole blood co-expression modules associate with metabolic traits and type 2 diabetes
T2 - an IMI-DIRECT study
AU - Gudmundsdottir, Valborg
AU - Pedersen, Helle Krogh
AU - Mazzoni, Gianluca
AU - Allin, Kristine H.
AU - Artati, Anna
AU - Beulens, Joline W.
AU - Banasik, Karina
AU - Brorsson, Caroline
AU - Cederberg, Henna
AU - Chabanova, Elizaveta
AU - De Masi, Federico
AU - Elders, Petra J.
AU - Forgie, Ian
AU - Giordano, Giuseppe N.
AU - Grallert, Harald
AU - Gupta, Ramneek
AU - Haid, Mark
AU - Hansen, Torben
AU - Hansen, Tue H.
AU - Hattersley, Andrew T.
AU - Heggie, Alison
AU - Hong, Mun-Gwan
AU - Jones, Angus G.
AU - Koivula, Robert
AU - Kokkola, Tarja
AU - Laakso, Markku
AU - Løngreen, Peter
AU - Mahajan, Anubha
AU - Mari, Andrea
AU - McDonald, Timothy J.
AU - McEvoy, Donna
AU - Musholt, Petra B.
AU - Pavo, Imre
AU - Prehn, Cornelia
AU - Ruetten, Hartmut
AU - Ridderstrale, Martin
AU - Rutters, Femke
AU - Sharma, Sapna
AU - Slieker, Roderick C.
AU - Syed, Ali
AU - Tajes, Juan Fernandez
AU - Thomas, Cecilia Engel
AU - Thomsen, Henrik S.
AU - Vangipurapu, Jagadish
AU - Vestergaard, Henrik
AU - Vinuela, Ana
AU - Wesolowska-Andersen, Agata
AU - Walker, Mark
AU - Adamski, Jerzy
AU - Schwenk, Jochen M.
AU - McCarthy, Mark
AU - Pearson, Ewan
AU - Dermitzakis, Emmanouil
AU - Franks, Paul W.
AU - Pedersen, Oluf
AU - Brunak, Søren
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Type 2 diabetes
KW - Transcriptomics
KW - Co-expression modules
KW - Omics data integration
KW - GENE-EXPRESSION PROFILES
KW - GENOME-WIDE ASSOCIATION
KW - INSULIN-RESISTANCE
KW - MONONUCLEAR-CELLS
KW - BIOMARKERS
KW - COUNT
KW - RISK
KW - TRANSCRIPTOME
KW - INFLAMMATION
KW - DRIVERS
U2 - 10.1186/s13073-020-00806-6
DO - 10.1186/s13073-020-00806-6
M3 - Journal article
C2 - 33261667
VL - 12
JO - Genome Medicine
JF - Genome Medicine
SN - 1756-994X
IS - 1
M1 - 109
ER -