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Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: An IMI-DIRECT study.
Genome Med. 12:109 (2020)
Verlagsversion
Forschungsdaten
DOI
PMC
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.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Co-expression Modules ; Omics Data Integration ; Transcriptomics ; Type 2 Diabetes; Gene-expression Profiles; Genome-wide Association; Insulin-resistance; Mononuclear-cells; Biomarkers; Count; Risk; Transcriptome; Inflammation; Drivers
ISSN (print) / ISBN
1756-994X
e-ISSN
1756-994X
Zeitschrift
Genome Medicine
Quellenangaben
Band: 12,
Heft: 1,
Artikelnummer: 109
Verlag
BioMed Central
Verlagsort
Campus, 4 Crinan St, London N1 9xw, England
Nichtpatentliteratur
Publikationen
Begutachtungsstatus
Peer reviewed
Institut(e)
Molekulare Endokrinologie und Metabolismus (MEM)
Institute of Epidemiology II (EPI2)
CCG Biomarker for the subclassification of T2DM (KKG-KDB)
CCG Nutrigenomics and Type 2 Diabetes (KKG-KDN)
Institute of Epidemiology II (EPI2)
CCG Biomarker for the subclassification of T2DM (KKG-KDB)
CCG Nutrigenomics and Type 2 Diabetes (KKG-KDN)
Förderungen
Innovative Medicines Initiative ()