An interaction map of circulating metabolites, immune gene networks, and their genetic regulation

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,...
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Autor*in:	Nath, Artika P. [verfasserIn] Ritchie, Scott C. Byars, Sean G. Fearnley, Liam G. Havulinna, Aki S. Joensuu, Anni Kangas, Antti J. Soininen, Pasi Wennerström, Annika Milani, Lili Metspalu, Andres Männistö, Satu Würtz, Peter Kettunen, Johannes Raitoharju, Emma Kähönen, Mika Juonala, Markus Palotie, Aarno Ala-Korpela, Mika Ripatti, Samuli Lehtimäki, Terho Abraham, Gad Raitakari, Olli Salomaa, Veikko Perola, Markus Inouye, Michael

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Anmerkung:	© The Author(s). 2017

Übergeordnetes Werk:	Enthalten in: Genome biology - London : BioMed Central, 2000, 18(2017), 1 vom: 01. Aug.
Übergeordnetes Werk:	volume:18 ; year:2017 ; number:1 ; day:01 ; month:08

Links:	Volltext

DOI / URN:	10.1186/s13059-017-1279-y

Katalog-ID:	SPR030029805

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520			\|a 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.
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700	1		\|a Salomaa, Veikko \|4 aut
700	1		\|a Perola, Markus \|4 aut
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allfields	10.1186/s13059-017-1279-y doi (DE-627)SPR030029805 (SPR)s13059-017-1279-y-e DE-627 ger DE-627 rakwb eng Nath, Artika P. verfasserin aut An interaction map of circulating metabolites, immune gene networks, and their genetic regulation 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 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. Ritchie, Scott C. aut Byars, Sean G. aut Fearnley, Liam G. aut Havulinna, Aki S. aut Joensuu, Anni aut Kangas, Antti J. aut Soininen, Pasi aut Wennerström, Annika aut Milani, Lili aut Metspalu, Andres aut Männistö, Satu aut Würtz, Peter aut Kettunen, Johannes aut Raitoharju, Emma aut Kähönen, Mika aut Juonala, Markus aut Palotie, Aarno aut Ala-Korpela, Mika aut Ripatti, Samuli aut Lehtimäki, Terho aut Abraham, Gad aut Raitakari, Olli aut Salomaa, Veikko aut Perola, Markus aut Inouye, Michael aut Enthalten in Genome biology London : BioMed Central, 2000 18(2017), 1 vom: 01. Aug. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:18 year:2017 number:1 day:01 month:08 https://dx.doi.org/10.1186/s13059-017-1279-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2017 1 01 08
spelling	10.1186/s13059-017-1279-y doi (DE-627)SPR030029805 (SPR)s13059-017-1279-y-e DE-627 ger DE-627 rakwb eng Nath, Artika P. verfasserin aut An interaction map of circulating metabolites, immune gene networks, and their genetic regulation 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 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. Ritchie, Scott C. aut Byars, Sean G. aut Fearnley, Liam G. aut Havulinna, Aki S. aut Joensuu, Anni aut Kangas, Antti J. aut Soininen, Pasi aut Wennerström, Annika aut Milani, Lili aut Metspalu, Andres aut Männistö, Satu aut Würtz, Peter aut Kettunen, Johannes aut Raitoharju, Emma aut Kähönen, Mika aut Juonala, Markus aut Palotie, Aarno aut Ala-Korpela, Mika aut Ripatti, Samuli aut Lehtimäki, Terho aut Abraham, Gad aut Raitakari, Olli aut Salomaa, Veikko aut Perola, Markus aut Inouye, Michael aut Enthalten in Genome biology London : BioMed Central, 2000 18(2017), 1 vom: 01. Aug. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:18 year:2017 number:1 day:01 month:08 https://dx.doi.org/10.1186/s13059-017-1279-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2017 1 01 08
allfields_unstemmed	10.1186/s13059-017-1279-y doi (DE-627)SPR030029805 (SPR)s13059-017-1279-y-e DE-627 ger DE-627 rakwb eng Nath, Artika P. verfasserin aut An interaction map of circulating metabolites, immune gene networks, and their genetic regulation 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 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. Ritchie, Scott C. aut Byars, Sean G. aut Fearnley, Liam G. aut Havulinna, Aki S. aut Joensuu, Anni aut Kangas, Antti J. aut Soininen, Pasi aut Wennerström, Annika aut Milani, Lili aut Metspalu, Andres aut Männistö, Satu aut Würtz, Peter aut Kettunen, Johannes aut Raitoharju, Emma aut Kähönen, Mika aut Juonala, Markus aut Palotie, Aarno aut Ala-Korpela, Mika aut Ripatti, Samuli aut Lehtimäki, Terho aut Abraham, Gad aut Raitakari, Olli aut Salomaa, Veikko aut Perola, Markus aut Inouye, Michael aut Enthalten in Genome biology London : BioMed Central, 2000 18(2017), 1 vom: 01. Aug. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:18 year:2017 number:1 day:01 month:08 https://dx.doi.org/10.1186/s13059-017-1279-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2017 1 01 08
allfieldsGer	10.1186/s13059-017-1279-y doi (DE-627)SPR030029805 (SPR)s13059-017-1279-y-e DE-627 ger DE-627 rakwb eng Nath, Artika P. verfasserin aut An interaction map of circulating metabolites, immune gene networks, and their genetic regulation 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 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. Ritchie, Scott C. aut Byars, Sean G. aut Fearnley, Liam G. aut Havulinna, Aki S. aut Joensuu, Anni aut Kangas, Antti J. aut Soininen, Pasi aut Wennerström, Annika aut Milani, Lili aut Metspalu, Andres aut Männistö, Satu aut Würtz, Peter aut Kettunen, Johannes aut Raitoharju, Emma aut Kähönen, Mika aut Juonala, Markus aut Palotie, Aarno aut Ala-Korpela, Mika aut Ripatti, Samuli aut Lehtimäki, Terho aut Abraham, Gad aut Raitakari, Olli aut Salomaa, Veikko aut Perola, Markus aut Inouye, Michael aut Enthalten in Genome biology London : BioMed Central, 2000 18(2017), 1 vom: 01. Aug. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:18 year:2017 number:1 day:01 month:08 https://dx.doi.org/10.1186/s13059-017-1279-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2017 1 01 08
allfieldsSound	10.1186/s13059-017-1279-y doi (DE-627)SPR030029805 (SPR)s13059-017-1279-y-e DE-627 ger DE-627 rakwb eng Nath, Artika P. verfasserin aut An interaction map of circulating metabolites, immune gene networks, and their genetic regulation 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2017 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. Ritchie, Scott C. aut Byars, Sean G. aut Fearnley, Liam G. aut Havulinna, Aki S. aut Joensuu, Anni aut Kangas, Antti J. aut Soininen, Pasi aut Wennerström, Annika aut Milani, Lili aut Metspalu, Andres aut Männistö, Satu aut Würtz, Peter aut Kettunen, Johannes aut Raitoharju, Emma aut Kähönen, Mika aut Juonala, Markus aut Palotie, Aarno aut Ala-Korpela, Mika aut Ripatti, Samuli aut Lehtimäki, Terho aut Abraham, Gad aut Raitakari, Olli aut Salomaa, Veikko aut Perola, Markus aut Inouye, Michael aut Enthalten in Genome biology London : BioMed Central, 2000 18(2017), 1 vom: 01. Aug. (DE-627)326173617 (DE-600)2040529-7 1474-760X nnns volume:18 year:2017 number:1 day:01 month:08 https://dx.doi.org/10.1186/s13059-017-1279-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2017 1 01 08
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title_sort	interaction map of circulating metabolites, immune gene networks, and their genetic regulation
title_auth	An interaction map of circulating metabolites, immune gene networks, and their genetic regulation
abstract	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. © The Author(s). 2017
abstractGer	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. © The Author(s). 2017
abstract_unstemmed	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. © The Author(s). 2017
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title_short	An interaction map of circulating metabolites, immune gene networks, and their genetic regulation
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author2	Ritchie, Scott C. Byars, Sean G. Fearnley, Liam G. Havulinna, Aki S. Joensuu, Anni Kangas, Antti J. Soininen, Pasi Wennerström, Annika Milani, Lili Metspalu, Andres Männistö, Satu Würtz, Peter Kettunen, Johannes Raitoharju, Emma Kähönen, Mika Juonala, Markus Palotie, Aarno Ala-Korpela, Mika Ripatti, Samuli Lehtimäki, Terho Abraham, Gad Raitakari, Olli Salomaa, Veikko Perola, Markus Inouye, Michael
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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.</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ritchie, Scott C.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Byars, Sean G.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Fearnley, Liam G.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Havulinna, Aki S.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Joensuu, Anni</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kangas, Antti J.</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Soininen, Pasi</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wennerström, Annika</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Milani, Lili</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Metspalu, Andres</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Männistö, Satu</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Würtz, Peter</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kettunen, Johannes</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Raitoharju, Emma</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kähönen, Mika</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Juonala, Markus</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Palotie, Aarno</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ala-Korpela, Mika</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ripatti, Samuli</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lehtimäki, Terho</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Abraham, Gad</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Raitakari, Olli</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Salomaa, Veikko</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Perola, Markus</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Inouye, Michael</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Genome biology</subfield><subfield code="d">London : BioMed Central, 2000</subfield><subfield code="g">18(2017), 1 vom: 01. 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An interaction map of circulating metabolites, immune gene networks, and their genetic regulation

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