Nath, A., Ritchie, S., Byars, S., Fearnley, L., Havulinna, A., Joensuu, A., Kangas, A., Soininen, P., Wennerström, A., Milani, L., Metspalu, A., Männistö, S., Würtz, P., Kettunen, J., Raitoharju, E., Kähönen, M., Juonala, M., Palotie, A., Ala-Korpela, M., Ripatti, S., Lehtimäki, T., Abraham, G., Raitakari, O., Salomaa, V., Perola, M., Inouye, M. (2017) An interaction map of circulating metabolites, immune gene networks, and their genetic regulation. Genome Biology, 18 (1). doi:10.1186/s13059-017-1279-y
An interaction map of circulating metabolites, immune gene networks, and their genetic regulation
|Author:||Nath, Artika P.1,2; Ritchie, Scott C.2,3; Byars, Sean G.3,4;|
1Department of Microbiology and Immunology, The University of Melbourne
2Systems Genomics Lab, Baker Heart and Diabetes Institute
3Department of Pathology, The University of Melbourne
4School of BioSciences, The University of Melbourne
5National Institute for Health and Welfare
6Institute for Molecular Medicine Finland, University of Helsinki
7Computational Medicine, Faculty of Medicine, University of Oulu
8NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland
9University of Tartu, Estonian Genome Center
10Diabetes and Obesity Research Program, University of Helsinki
11Biocenter Oulu, University of Oulu
12Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere
13Department of Clinical Physiology, University of Tampere and Tampere University Hospital
14Department of Medicine, University of Turku and Division of Medicine, Turku University Hospital
15Murdoch Childrens Research Institute
16Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital
17Program in Medical and Population Genetics, Broad Institute of Harvard and MIT
18Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital
19Computational Medicine, School of Social and Community Medicine, University of Bristol
20Medical Research Council Integrative Epidemiology Unit, University of Bristol
21Department of Public Health, University of Helsinki
22Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital
23Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku
|Online Access:||PDF Full Text (PDF, 3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe201709148606
|Publish Date:|| 2017-09-14
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.
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
This study was supported by funding from National Health and Medical Research Council of Australia (NHMRC) grant APP1062227. MI was supported by an NHMRC and Australian Heart Foundation Career Development Fellowship (no. 1061435). GA was supported by an NHMRC Early Career Fellowship (no. 1090462). APN and SR were supported by an Australian Postgraduate Award. PW was supported by the Academy of Finland (no. 312476 and 312477). VS was supported by the Finnish Foundation for Cardiovascular Research. This study was further supported by the Strategic Research Funding from the University of Oulu, Finland, the Sigrid Juselius Foundation, the Academy of Finland (grant numbers 141136, 269517, 283045, 294834, and 297338), the Yrjö Jahnsson Foundation, the Emil Aaltonen Foundation, the Novo Nordisk Foundation, and the Finnish Diabetes Research Foundation. ER was supported by the Academy of Finland (no. 285902). The Young Finns Study has been financially supported by the Academy of Finland: grants 286284 (T.L.), 134309 (Eye), 126925, 121584, 124282, 129378 (Salve), 117787 (Gendi), and 41071 (Skidi); the Social Insurance Institution of Finland; Competitive State Research Financing of the Expert Responsibility area of Tampere, Turku and Kuopio University Hospitals (grant X51001); Juho Vainio Foundation; Paavo Nurmi Foundation; Finnish Foundation for Cardiovascular Research; Finnish Cultural Foundation; Tampere Tuberculosis Foundation; Emil Aaltonen Foundation; Yrjö Jahnsson Foundation; Signe and Ane Gyllenberg Foundation; and Diabetes Research Foundation of Finnish Diabetes Association. MJ was supported by the Paulo Foundation, Maud Kuistila Foundation, and Finnish Medical Foundation. The DILGOM study and the National FINRISK study are supported by the Academy of Finland (grant numbers 139 and 635). The quantitative serum NMR metabolomics platform and its development have been supported by the Academy of Finland, TEKES—the Finnish Funding Agency for Technology and Innovation, the Sigrid Juselius Foundation, and the strategic and infrastructural research funding from the University of Oulu, Finland, as well as by the British Heart Foundation, the Wellcome Trust, and the Medical Research Council, UK. MP is also supported by EU FP7 under grant agreements 313010 (BBMRI-LPC), 305280 (MIMOmics), and HZ2020 633589 (Ageing with Elegans). MAK works in a Unit that is supported by the University of Bristol and UK Medical Research Council (MC_UU_1201/1). A.M. and L.M. were supported by EU H2020 grants 692145, the Estonian Research Council Grant IUT20-60, and European Union through the European Regional Development Fund (Project No. 2014-2020.4.01.15-0012 GENTRANSMED).
|Academy of Finland Grant Number:||
294834 (Academy of Finland Funding decision)
297338 (Academy of Finland Funding decision)
The study data are available to the scientific community based on a written application to the THL Biobank and Finnish biobank legislation. Instructions for submitting an application are given in the website of the Biobank (https://www.thl.fi/en/web/thl-biobank/for-researchers). The materials used in the study include open source software, cited as appropriate. Other scripts can be requested from the authors directly.
© The Author(s). 2017 Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.