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Nat Commun. 2019 Sep 24;10(1):4329. doi: 10.1038/s41467-019-11954-8.

Genetic architecture of human plasma lipidome and its link to cardiovascular disease.

Collaborators (232)

Jalanko A, Kaprio J, Donner K, Kaunisto M, Mars N, Dada A, Shcherban A, Ganna A, Lehisto A, Kilpeläinen E, Brein G, Awaisa G, Harju J, Pärn K, Parolo PDB, Kajanne R, Lemmelä S, Sipilä TP, Sipilä T, Lyhs U, Llorens V, Niiranen T, Kristiansson K, Männikkö L, Jiménez MG, Perola M, Wong R, Kilpi T, Hiekkalinna T, Järvensivu E, Kaiharju E, Mattsson H, Laukkanen M, Laiho P, Lähteenmäki S, Sistonen T, Soini S, Ziemann A, Lehtonen A, Lertratanakul A, Georgantas B, Riley-Gillis B, Quarless D, Rahimov F, Heap G, Jacob H, Waring J, Davis JW, Smaoui N, Popovic R, Esmaeeli S, Waring J, Matakidou A, Challis B, Close D, Petrovski S, Karlsson A, Schleutker J, Pulkki K, Virolainen P, Kallio L, Mannermaa A, Heikkinen S, Kosma VM, Chen CY, Runz H, Liu J, Bronson P, John S, Lahdenperä S, Eaton S, Zhou W, Hendolin M, Tuovila O, Pakkanen R, Maranville J, Usiskin K, Hochfeld M, Plenge R, Yang R, Biswas S, Greenberg S, Laakkonen E, Kononen J, Paloneva J, Kujala U, Kuopio T, Laukkanen J, Kangasniemi E, Savinainen K, Laaksonen R, Arvas M, Ritari J, Partanen J, Hyvärinen K, Wahlfors T, Peterson A, Oh D, Chang D, Teng E, Strauss E, Kerchner G, Chen H, Chen H, Schutzman J, Michon J, Hunkapiller J, McCarthy M, Bowers N, Lu T, Bhangale T, Pulford D, Waterworth D, Kulkarni D, Xu F, Betts J, Gordillo JE, Hoffman J, Auro K, McCarthy L, Ghosh S, Ehm M, Pitkänen K, Mäkelä T, Loukola A, Joensuu H, Sinisalo J, Eklund K, Aaltonen L, Färkkilä M, Carpen O, Kauppi P, Tienari P, Ollila T, Tuomi T, Meretoja T, Pitkäranta A, Turunen J, Hannula-Jouppi K, Pikkarainen S, Seitsonen S, Koskinen M, Palomäki A, Rinne J, Metsärinne K, Elenius K, Pirilä L, Koulu L, Voutilainen M, Juonala M, Peltonen S, Aaltonen V, Loboda A, Podgornaia A, Chhibber A, Chu A, Fox C, Diogo D, Holzinger E, Eicher J, Gormley P, Mehta V, Wang X, Kettunen J, Pylkäs K, Kalaoja M, Karjalainen M, Hinttala R, Kaarteenaho R, Vainio S, Mantere T, Vainio S, Remes A, Huhtakangas J, Junttila J, Tasanen K, Huilaja L, Luodonpää M, Hautala N, Karihtala P, Kauppila S, Harju T, Blomster T, Soininen H, Harvima I, Pihlajamäki J, Kaarniranta K, Pelkonen M, Laakso M, Hiltunen M, Kiviniemi M, Kaipiainen-Seppänen O, Auvinen P, Kälviäinen R, Julkunen V, Malarstig A, Hedman Å, Marshall C, Whelan C, Lehtonen H, Parkkinen J, Linden K, Kalpala K, Miller M, Bing N, McDonough S, Chen X, Hu X, Wu Y, Auranen A, Jussila A, Uusitalo-Järvinen H, Kankaanranta H, Uusitalo H, Peltola J, Kähönen M, Isomäki P, Laitinen T, Salmi T, Muslin A, Wang C, Chatelain C, Xu E, Auge F, Call K, Klinger K, Crohns M, Gossel M, Palin K, Rivas M, Siirtola H, Tabuenca JG.

Author information

1
Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
2
Program in Medical and Population Genetics and Genetic Analysis Platform, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
3
Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
4
Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA.
5
Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
6
Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.
7
National Institute for Health and Welfare, Helsinki, Finland.
8
Research Programs Unit, Diabetes & Obesity, University of Helsinki and Department of Internal Medicine, Helsinki University Hospital, Helsinki, Finland.
9
Endocrinology, Abdominal Center, Helsinki University Hospital, Helsinki, Finland.
10
Lipotype GmbH, Dresden, Germany.
11
Łukasiewicz Research Network-PORT Polish Center for Technology Development, Stablowicka 147 Str., 54-066, Wroclaw, Poland.
12
Cardiovascular Division, Department of Medicine, Washington University School of Medicine, Saint Louis, MO, USA.
13
Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA.
14
McDonnell Genome Institute, Washington University School of Medicine, Saint Louis, MO, USA.
15
Department of Obstetrics and Gynecology, Tampere University Hospital and Tampere University, Faculty of Medicine and Health Technology, Tampere, Finland.
16
Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
17
Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA.
18
Department of Public Health, University of Helsinki, Helsinki, Finland.
19
Helsinki Institute for Information Technology HIIT and Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.
20
Minerva Foundation Institute for Medical Research, Biomedicum, Helsinki, Finland.
21
Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry, Analytic and Translational Genetics Unit, Department of Medicine, and the Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
22
Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.
23
Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland. samuli.ripatti@helsinki.fi.
24
Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA. samuli.ripatti@helsinki.fi.
25
Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland. samuli.ripatti@helsinki.fi.

Abstract

Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10-8), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD.

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