PT  - JOURNAL ARTICLE
AU  - Artika P. Nath
AU  - Scott C. Ritchie
AU  - Sean G. Byars
AU  - Liam G. Fearnley
AU  - Aki S. Havulinna
AU  - Anni Joensuu
AU  - Antti J. Kangas
AU  - Pasi Soininen
AU  - Annika Wennerström
AU  - Lili Milani
AU  - Andres Metspalu
AU  - Satu Männistö
AU  - Peter Würtz
AU  - Johannes Kettunen
AU  - Emma Raitoharju
AU  - Mika Kähönen
AU  - Markus Juonala
AU  - Aarno Palotie
AU  - Mika Ala-Korpela
AU  - Samuli Ripatti
AU  - Terho Lehtimäki
AU  - Gad Abraham
AU  - Olli Raitakari
AU  - Veikko Salomaa
AU  - Markus Perola
AU  - Michael Inouye
TI  - An interaction map of circulating metabolites, immune gene networks and their genetic regulation
AID  - 10.1101/089839
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 089839
4099  - http://biorxiv.org/content/early/2016/11/26/089839.short
4100  - http://biorxiv.org/content/early/2016/11/26/089839.full
AB  - The interaction between metabolism and the immune system plays a central role in many cardiometabolic diseases. We integrated blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts, including a subset with 7-year follow-up sampling. We identified topologically robust gene networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules showed complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) revealed five modules with mQTLs of both cis and trans effects. The strongest mQTL was in ARHGEF3 (rs1354034) and affected a module enriched for platelet function. Mast cell/basophil and neutrophil function modules maintained their metabolite associations during 7-year follow-up, while our strongest mQTL in ARHGEF3 also displayed clear temporal stability. This study provides a detailed map of natural variation at the blood immuno-metabolic interface and its genetic basis, and facilitates subsequent studies to explain inter-individual variation in cardiometabolic disease.