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. 2017 Aug 1;18(1):146.
doi: 10.1186/s13059-017-1279-y.

An Interaction Map of Circulating Metabolites, Immune Gene Networks, and Their Genetic Regulation

Free PMC article

An Interaction Map of Circulating Metabolites, Immune Gene Networks, and Their Genetic Regulation

Artika P Nath et al. Genome Biol. .
Free PMC article


Background: Immunometabolism plays a central role in many cardiometabolic diseases. However, a robust map of immune-related gene networks in circulating human cells, their interactions with metabolites, and their genetic control is still lacking. Here, we integrate blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts (total N = 2168), including a subset of individuals with matched multi-omic data at 7-year follow-up.

Results: We identify topologically replicable gene networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules show complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, small molecules, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) reveal five modules with mQTLs that have both cis and trans effects. The strongest mQTL is in ARHGEF3 (rs1354034) and affects a module enriched for platelet function, independent of platelet counts. Modules of mast cell/basophil and neutrophil function show temporally stable metabolite associations over 7-year follow-up, providing evidence that these modules and their constituent gene products may play central roles in metabolic inflammation. Furthermore, the strongest mQTL in ARHGEF3 also displays clear temporal stability, supporting widespread trans effects at this locus.

Conclusions: This study provides a detailed map of natural variation at the blood immunometabolic interface and its genetic basis, and may facilitate subsequent studies to explain inter-individual variation in cardiometabolic disease.

Conflict of interest statement

Ethics approval and consent to participate

The study, data sharing, and analyses were given ethics approval by the THL Biobank of Finland (#BB2016_60). DILGOM14 re-examination by the Coordinating Ethics Committee of the Helsinki and Uusimaa Hospital District with the decision number 332/13/03/00/2013. YFS ethics approval for the study research protocols was given by the Joint Commission on Ethics of Turku University and Turku University Central Hospital (ETMK 88/180/2010). All subjects have given written informed consent.

Competing interests

AJK, PS, and PW are shareholders and report employment relations for Nightingale Health Ltd, a company offering NMR-based metabolite profiling.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Fig. 1
Fig. 1
The study design. GO Gene Ontology, SNP single nucleotide polymorphism
Fig. 2
Fig. 2
Module and expression QTL analysis. a Manhattan plot of meta-analyzed P values from the DILGOM/YFS module QTL analysis. The lead SNP and its closest genes are noted. Each significant mQTL locus is colored by module. The horizontal dashed line represents genome-wide (meta- P value <5 × 10−8) significance. bd Circular plots summarizing the individual gene associations (meta-P value <5 × 10−8) for the lead module QTLs in the VRM, PM, and NM. Lead SNPs and cis genes are labeled outside the ring. PM platelet module, VRM viral response module, CCLM cytotoxic cell-like module, NM neutrophil module, BCM B-cell activity module
Fig. 3
Fig. 3
Metabolite measure associations with immune gene modules. Circular heatmap of associations between individual metabolite measure and the module eigengene of each module (colored by FDR-adjusted P values). Concentric circles represent modules, with numbers in parentheses denoting total number of metabolite measures associated with that module at FDR-adjusted P value <6.25 × 10–3. NM neutrophil module, LLM lipid leukocyte module, GIMA/GIMB general immune module A/B, PM platelet module, CCLM cytotoxic cell-like module, BCM B-cell activity module, VRM viral response module. See Additional file 1: Table S1 for full metabolite descriptions
Fig. 4
Fig. 4
Temporally stable metabolite measure associations with the LLM. a Circular heatmap for association between each metabolite measure and the LLM. b Comparison of the effect size estimates of metabolite measure association with LLM in DILGOM07 and DILGOM14 shows that the overall association patterns are consistent across the two time-points. Colors denote metabolites that are significantly associated with the LLM in DILGOM07 only (orange), DILGOM14 only (blue), and across both time-points (green). The grey dashed line is the x = y line

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