An interaction map of circulating metabolites, immune-related gene networks and their genetic regulation   — ASN Events
  1. Schedule
  2. Session 5: Noncoding RNA and RNA Regulation
  3. An interaction map of circulating metabolites, immune-related gene networks and their genetic regulation  

An interaction map of circulating metabolites, immune-related gene networks and their genetic regulation   (#35)

Artika Nath 1 2 , Scott C Ritchie 2 3 , Liam G Fearnley 2 3 , Sean G Byars 2 3 , Aki S Havulinna 4 5 , Anni Joensuu 4 , Antti J Kangas 6 , Pasi Soininen 6 7 , Annika Wennerström 8 , Lili Milani 9 , Andres Metspalu 9 , Satu Männistö 10 , Mika Kähönen 11 , Markus Juonala 12 13 , Peter Würtz 6 14 , Johannes Kuttunen 4 6 15 , Mika Ala-Korpela 6 15 16 17 18 , Samuli Ripatti 5 19 , Terho Lehtimäki 20 , Gad Abraham 2 3 , Olli Raitakari 21 , Veikko Salomaa 4 , Markus Perola 4 5 22 , Michael Inouye 2 3
  1. Microbiology and Immunology, University of Melbourne, Parkville , Victoria , Australia
  2. Centre for Systems Genomics, School of BioSciences, The University of Melbourne, Melbourne, Victoria, Australia
  3. Department of Pathology, University of Melbourne, Parkville, Victoria, Australia
  4. National Institute for Health and Welfare,, Helsinki, Finland
  5. Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
  6. Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
  7. NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
  8. National Institute for Health and Welfare, Helsinki, Finland
  9. Estonian Genome Center, University of Tartu,, Tartu, Estonia
  10. National Institute for Health and Welfare, Helsinki, Finland
  11. Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Tampere, Finland
  12. Department of Medicine, University of Turku and Division of Medicine, Turku, Finland
  13. Murdoch Childrens Research Institute, Melbourne, Australia
  14. Biocenter Oulu, University of Oulu, Oulu, Oulu
  15. NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finlandd, Kuopio, Finland
  16. Oulu University Hospital, Oulu, Finland
  17. Computational Medicine, School of Social and Community Medicine, University of Bristol, Bristol, UK
  18. Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
  19. Department of Public Health, University of Helsinki, Helsinki, Finland
  20. Department of Clinical Chemistry, Fimlab Laboratories, School of Medicine, University of Tampere, Tampere, Finland
  21. Department of Clinical Physiology and Nuclear Medicine,, Turku University Hospital, Turku, Finland
  22. Estonian Genome Center, University of Tartu, Tartu , Estonia

The interaction between metabolism and the immune system plays a central role in many cardiometabolic diseases. However, the extent to which this interplay contributes to disease risk in natural populations remains largely unknown. Here, we integrated blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts (combined N=2,168), including a subset of 333 individuals with follow-up sampling after seven years. Through gene co-expression network analysis, we identified networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophils related activity, which topologically replicated between cohorts. We then performed association analysis of these 8 immune-related modules with 158 circulating metabolites and CRP, showing that each of these modules were significantly associated with diverse metabolites including lipoprotein subclasses, lipids, fatty acids, amino acids, and CRP. Further, for five of these modules, genome-wide scans revealed module expression quantitative trait loci with both cis and trans effects. The strongest module QTL was rs1354034, intronic to ARHGEF3, which affected the platelet activity module (meta-P-value = 7.35 x 10-28). Finally, we assessed the long-term stability of these interactions, finding that the metabolite associations for a mast cell and basophil-related module and the trans QTL effects of rs1354034 were largely maintained over a seven-year period. Taken together, this study provides a detailed map of natural variation at the immuno-metabolic interface in human blood and its genetic basis. The catalogue of immunometabolic interactions presented here may help explain differential disease susceptibility between individuals and guide subsequent mechanistic experiments.

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