Genome-wide association study identifies novel loci associated with circulating phospho- and sphingolipid concentrations
Open accessAbstract
Phospho- and sphingolipids are crucial cellular and intracellular compounds. These lipids are required for active transport, a number of enzymatic processes, membrane formation, and cell signalling. Disruption of their metabolism leads to several diseases, with diverse neurological, psychiatric, and metabolic consequences. A large number of phospholipid and sphingolipid species can be detected and measured in human plasma. We conducted a meta-analysis of five European family-based genome-wide association studies (N = 4034) on plasma levels of 24 sphingomyelins (SPM), 9 ceramides (CER), 57 phosphatidylcholines (PC), 20 lysophosphatidylcholines (LPC), 27 phosphatidylethanolamines (PE), and 16 PE-based plasmalogens (PLPE), as well as their proportions in each major class. This effort yielded 25 genome-wide significant loci for phospholipids (smallest P-value = 9.88×10(-204)) and 10 loci for sphingolipids (smallest P-value = 3.10×10(-57)). After a correction for multiple comparisons (P-value<2.2×10(-9)), we observed four novel loci significantly associated with phospholipids (PAQR9, AGPAT1, PKD2L1, PDXDC1) and two with sphingolipids (PLD2 and APOE) explaining up to 3.1% of the variance. Further analysis of the top findings with respect to within class molar proportions uncovered three additional loci for phospholipids (PNLIPRP2, PCDH20, and ABDH3) suggesting their involvement in either fatty acid elongation/saturation processes or fatty acid specific turnover mechanisms. Among those, 14 loci (KCNH7, AGPAT1, PNLIPRP2, SYT9, FADS1-2-3, DLG2, APOA1, ELOVL2, CDK17, LIPC, PDXDC1, PLD2, LASS4, and APOE) mapped into the glycerophospholipid and 12 loci (ILKAP, ITGA9, AGPAT1, FADS1-2-3, APOA1, PCDH20, LIPC, PDXDC1, SGPP1, APOE, LASS4, and PLD2) to the sphingolipid pathways. In large meta-analyses, associations between FADS1-2-3 and carotid intima media thickness, AGPAT1 and type 2 diabetes, and APOA1 and coronary artery disease were observed. In conclusion, our study identified nine novel phospho- and sphingolipid loci, substantially increasing our knowledge of the genetic basis for these traits.
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Human genome-wide association studies link variants in PLEKHH1 with sphingolipid concentrations that, when altered, lead to neurological and psychiatric disease.
“Human genome-wide association studies link variants in PLEKHH1 with sphingolipid concentrations that, when altered, lead to neurological and psychiatric disease (49).”
From Comparative analysis of the domestic cat genome reveals genetic signatures underlying feline biology and domestication (2014) · cites this paper as [49]
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Membrane lipids: where they are and how they behave
van Meer, G., Voelker, D. R., & Feigenson, G. W. (2008) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2330 · Cited by 7,157 · see citing works
METAL: fast and efficient meta-analysis of genomewide association scans
Willer, C. J., Li, Y., & Abecasis, G. R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq340 · Cited by 5,205 · see citing works
Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487 · see citing works
Self-citationLarge-scale association analysis identifies 13 new susceptibility loci for coronary artery disease
Cardiogenics, Schunkert, H., the CARDIoGRAM Consortium, König, I. R., Kathiresan, S., Reilly, M. P., Assimes, T. L., Holm, H., Preuss, M., Stewart, A. F. R., et al. (2011) · Nature Genetics · doi:10.1038/ng.784 · Cited by 1,866 · see citing works
MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes
Li, Y., Willer, C. J., Ding, J., Scheet, P., & Abecasis, G. R. (2010) · Genetic Epidemiology · doi:10.1002/gepi.20533 · Cited by 1,843 · see citing works
GenABEL: an R library for genome-wide association analysis
Aulchenko, Y. S., Ripke, S., Isaacs, A., & van Duijn, C. M. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm108 · Cited by 1,836 · see citing works
Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis
The MAGIC investigators, Voight, B. F., The GIANT Consortium, Scott, L. J., Steinthorsdottir, V., Morris, A. P., Dina, C., Welch, R. P., Zeggini, E., Huth, C., et al. (2010) · Nature Genetics · doi:10.1038/ng.609 · Cited by 1,761 · see citing works
Biochemistry of Lipids, Lipoproteins and Membranes
(2021) · Elsevier eBooks · doi:10.1016/c2020-0-00089-7 · Cited by 1,400 · see citing works
Brügger, B., Erben, G., Sandhoff, R., Wieland, F., & Lehmann, W. D. (1997) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.94.6.2339 · Cited by 882 · see citing works
Genetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum
Gieger, C., Geistlinger, L., Altmaier, E., Hrabé de Angelis, M., Kronenberg, F., Meitinger, T., Mewes, H.-W., Wichmann, H.-E., Weinberger, K. M., Adamski, J., et al. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000282 · Cited by 737 · see citing works
Oxidative Stress and Cell Signalling
Poli, G., Leonarduzzi, G., Biasi, F., & Chiarpotto, E. (2004) · Current Medicinal Chemistry · doi:10.2174/0929867043365323 · Cited by 721 · see citing works
A genome-wide perspective of genetic variation in human metabolism
Illig, T., Gieger, C., Zhai, G., Römisch-Margl, W., Wang-Sattler, R., Prehn, C., Altmaier, E., Kastenmüller, G., Kato, B. S., Mewes, H.-W., et al. (2010) · Nature Genetics · doi:10.1038/ng.507 · Cited by 653 · see citing works
ConsensusPathDB--a database for integrating human functional interaction networks
Kamburov, A., Wierling, C., Lehrach, H., & Herwig, R. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn698 · Cited by 565 · see citing works
Zheng, W., Kollmeyer, J., Symolon, H., Momin, A. A., Munter, E., Wang, E. L., Kelly, S. L., Allegood, J. C., Liu, Y., Peng, Q., et al. (2006) · Biochimica et Biophysica Acta (BBA) - Biomembranes · doi:10.1016/j.bbamem.2006.08.009 · Cited by 561 · see citing works
Farooqui, A. A., Horrocks, L. A., & Farooqui, T. (2000) · Chemistry and Physics of Lipids · doi:10.1016/s0009-3084(00)00128-6 · Cited by 555 · see citing works
PAQR Proteins: A Novel Membrane Receptor Family Defined by an Ancient7-Transmembrane Pass Motif
Tang, Y., Hu, T., Arterburn, M., Boyle, B., Bright, J. M., Emtage, P. C. R., & Funk, W. D. (2005) · Journal of Molecular Evolution · doi:10.1007/s00239-004-0375-2 · Cited by 373 · see citing works
Wang, L., Folsom, A. R., Zheng, Z.-J., Pankow, J. S., & Eckfeldt, J. H. (2003) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/78.1.91 · Cited by 364 · see citing works
Lattices, rafts, and scaffolds: domain regulation of receptor signaling at the plasma membrane
Lajoie, P., Goetz, J. G., Dennis, J. W., & Nabi, I. R. (2009) · The Journal of Cell Biology · doi:10.1083/jcb.200811059 · Cited by 345 · see citing works
Liebisch, G., Lieser, B., Rathenberg, J., Drobnik, W., & Schmitz, G. (2004) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2004.09.003 · Cited by 336 · see citing works
The Organizing Potential of Sphingolipids in Intracellular Membrane Transport
Holthuis, J. C. M., Pomorski, T. G., Raggers, R. J., Sprong, H., & Gerrit van, M. E. E. R. (2001) · Physiological Reviews · doi:10.1152/physrev.2001.81.4.1689 · Cited by 317 · see citing works
Role of Lysophosphatidylcholine (LPC) in Atherosclerosis
Matsumoto, T., Kobayashi, T., & Kamata, K. (2007) · Current Medicinal Chemistry · doi:10.2174/092986707782793899 · Cited by 312 · see citing works
Hodge, A. M., English, D. R., O’Dea, K., Sinclair, A. J., Makrides, M., Gibson, R. A., & Giles, G. G. (2007) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/86.1.189 · Cited by 287 · see citing works
Malerba, G., Schaeffer, L., Xumerle, L., Klopp, N., Trabetti, E., Biscuola, M., Cavallari, U., Galavotti, R., Martinelli, N., Guarini, P., et al. (2008) · Lipids · doi:10.1007/s11745-008-3158-5 · Cited by 237 · see citing works
Genetic Determinants of Circulating Sphingolipid Concentrations in European Populations
Hicks, A. A., Pramstaller, P. P., Johansson, Å., Vitart, V., Rudan, I., Ugocsai, P., Aulchenko, Y. S., Franklin, C. S., Liebisch, G., Erdmann, J., et al. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000672 · Cited by 214 · see citing works
the CARDIoGRAM Consortium, Bis, J. C., Kavousi, M., Franceschini, N., Isaacs, A., Abecasis, G. R., Schminke, U., Post, W. S., Smith, A. V., Cupples, L. A., et al. (2011) · Nature Genetics · doi:10.1038/ng.920 · Cited by 212 · see citing works
Liebisch, G., Drobnik, W., Lieser, B., & Schmitz, G. (2002) · Clinical Chemistry · doi:10.1093/clinchem/48.12.2217 · Cited by 199 · see citing works
Mannheim, D., Herrmann, J., Versari, D., Gössl, M., Meyer, F. B., McConnell, J. P., Lerman, L. O., & Lerman, A. (2008) · Stroke · doi:10.1161/strokeaha.107.503193 · Cited by 180 · see citing works
Giller, T., Buchwald, P., Blum‐Kaelin, D., & Hunziker, W. H. (1992) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(18)42032-7 · Cited by 165 · see citing works
A comprehensive evaluation of SNP genotype imputation
Nothnagel, M., Ellinghaus, D., Schreiber, S., Krawczak, M., & Franke, A. (2008) · Human Genetics · doi:10.1007/s00439-008-0606-5 · Cited by 163 · see citing works
Isolation and characterization of cDNA clones for human apolipoprotein A-I.
Breslow, J. L., Ross, D. G., McPherson, J. D., Williams, H., Kurnit, D. M., NUSSBAUM, A. L., Karathanasis, S. K., & Zannis, V. I. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.22.6861 · Cited by 157 · see citing works
Genetic Analysis of Adult-Onset Autoimmune Diabetes
Howson, J. M. M., Rosinger, S., Smyth, D. J., Boehm, B. O., the ADBW-END Study Group, & Todd, J. A. (2011) · Diabetes · doi:10.2337/db11-0364 · Cited by 143 · see citing works
Biological pathway analysis by ArrayUnlock and Ingenuity Pathway Analysis
Jiménez-Marín, Á., Collado-Romero, M., Ramírez-Boo, M., Arce, C., & Garrido, J. J. (2009) · BMC Proceedings · doi:10.1186/1753-6561-3-s4-s6 · Cited by 138 · see citing works
Bakovic, M., Fullerton, M. D., & Michel, V. (2007) · Biochemistry and Cell Biology · doi:10.1139/o07-006 · Cited by 129 · see citing works
Aguado, B., & Campbell, R. D. (1998) · Journal of Biological Chemistry · doi:10.1074/jbc.273.7.4096 · Cited by 115 · see citing works
Unsaturated Fatty Acids Phosphorylate and Destabilize ABCA1 through a Phospholipase D2 Pathway
Wang, Y., & Oram, J. F. (2005) · Journal of Biological Chemistry · doi:10.1074/jbc.m506210200 · Cited by 101 · see citing works
Chartier, F., Bossu, J.-P., Laudet, V., Fruchart, J., & Laine, B. (1994) · Gene · doi:10.1016/0378-1119(94)90079-5 · Cited by 83 · see citing works
Engelmann, B., Koegl, C., Kulschar, R., & Schaipp, B. (1996) · Biochemical Journal · doi:10.1042/bj3150781 · Cited by 56 · see citing works
Broekman, M., Handin, R. I., Derksen, A., & Cohen, P. (1976) · Blood · doi:10.1182/blood.v47.6.963.963 · Cited by 49 · see citing works
Singh, D. K., & Subbaiah, P. V. (2006) · Journal of Lipid Research · doi:10.1194/jlr.m600421-jlr200 · Cited by 34 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Willer (2013) · doi:10.1038/ng.2797 · Cited by 2,983 · see citing works
Analytical Methods in Untargeted Metabolomics: State of the Art in 2015
Alonso, A., Marsal, S., & Julià, A. (2015) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2015.00023 · Cited by 685 · see citing works
Parks, B. W., Nam, E., Org, E., Kostem, E., Norheim, F., Hui, S. T., Pan, C., Civelek, M., Rau, C. D., Bennett, B. J., et al. (2013) · Cell Metabolism · doi:10.1016/j.cmet.2012.12.007 · Cited by 544 · see citing works
Montague, M. J., Li, G., Gandolfi, B., Khan, R., Aken, B. L., Searle, S. M. J., Minx, P., Hillier, L. W., Koboldt, D. C., Davis, B. W., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1410083111 · Cited by 340 · see citing works
A Genome-wide Association Study of the Human Metabolome in a Community-Based Cohort
Rhee, E. P., Ho, J. E., Chen, M., Shen, D., Cheng, S. C., Larson, M. G., Ghorbani, A., Shi, X. D., Helenius, I. T., O’Donnell, C. J., et al. (2013) · Cell Metabolism · doi:10.1016/j.cmet.2013.06.013 · Cited by 318 · see citing works
Large-scale Metabolomic Profiling Identifies Novel Biomarkers for Incident Coronary Heart Disease
Ganna, A., Salihović, S., Sundström, J., Broeckling, C. D., Hedman, Å. K., Magnusson, P. K. E., Pedersen, N. L., Larsson, A. O., Siegbahn, A. G., Zilmer, M., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004801 · Cited by 283 · see citing works
Genome-wide association analysis of plasma lipidome identifies 495 genetic associations
Ottensmann, L., Tabassum, R., Ruotsalainen, S., Gerl, M. J., Klose, C. D., Widén, E., FinnGen, Simons, K., Ripatti, S., & Pirinen, M. (2023) · Nature Communications · doi:10.1038/s41467-023-42532-8 · Cited by 271 · see citing works
Genome-wide characterization of circulating metabolic biomarkers
Karjalainen, M. K., Karthikeyan, S., Oliver‐Williams, C., Sliz, E., Allara, E., Fung, W. T., Surendran, P., Zhang, W., Jousilahti, P., Kristiansson, K., et al. (2024) · Nature · doi:10.1038/s41586-024-07148-y · Cited by 268 · see citing works
Ameur, A., Enroth, S., Johansson, Å., Zaboli, G., Igl, W., Johansson, A., Rivas, M. A., Daly, M. J., Schmitz, G., Hicks, A. A., et al. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.03.014 · Cited by 261 · see citing works
Zbieć-Piekarska, R., Spólnicka, M., Kupiec, T., Makowska, Ż., Spas, A., Parys-Proszek, A., Kucharczyk, K., Płoski, R., & Branicki, W. (2015) · Forensic Science International: Genetics · doi:10.1016/j.fsigen.2014.10.002 · Cited by 203 · see citing works
Watson, C. T., Roussos, P., Garg, P., Ho, D. J., Azam, N., Katsel, P. L., Haroutunian, V., & Sharp, A. J. (2016) · Genome Medicine · doi:10.1186/s13073-015-0258-8 · Cited by 201 · see citing works
Guan, W., Steffen, B. T., Lemaître, R. N., Wu, J. H. Y., Tanaka, T., Manichaikul, A. W., Foy, M., Rich, S. S., Wang, L., Nettleton, J. A., et al. (2014) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.113.000208 · Cited by 210 · see citing works
Draisma, H. H. M., Pool, R., Kobl, M., Jansen, R., Petersen, A.-K., Vaarhorst, A. A. M., Yet, İ., Haller, T., Demirkan, A., Esko, T., et al. (2015) · Nature Communications · doi:10.1038/ncomms8208 · Cited by 196 · see citing works
Genetic variation in metabolic phenotypes: study designs and applications
Suhre, K., & Gieger, C. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3314 · Cited by 187 · see citing works
Genetic architecture of human plasma lipidome and its link to cardiovascular disease
Tabassum, R., Rämö, J. T., Ripatti, P., Koskela, J. T., Kurki, M., Karjalainen, J. M., Palta, P., Hassan, S., Núñez-Fontarnau, J., Kiiskinen, T., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11954-8 · Cited by 176 · see citing works
Inouye, M., Ripatti, S., Kettunen, J., Lyytikäinen, L., Oksala, N., Laurila, P., Kangas, A. J., Soininen, P., Savolainen, M. J., Viikari, J. S. A., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002907 · Cited by 165 · see citing works
Demirkan, A., Isaacs, A., Ugocsai, P., Liebisch, G., Struchalin, M., Rudan, I., Wilson, J. F., Pramstaller, P. P., Gyllensten, U., Campbell, H., et al. (2013) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2012.11.001 · Cited by 163 · see citing works
Lord, C. C., Thomas, G., & Brown, J. M. (2013) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2013.01.002 · Cited by 160 · see citing works
Pleiotropic genes for metabolic syndrome and inflammation
Kraja, A. T., Chasman, D. I., North, K. E., Reiner, A. P., Yanek, L. R., Kilpeläinen, T. O., Smith, J. A., Dehghan, A., Dupuis, J., Johnson, A. D., et al. (2014) · Molecular Genetics and Metabolism · doi:10.1016/j.ymgme.2014.04.007 · Cited by 147 · see citing works
Dimethylguanidino valeric acid is a marker of liver fat and predicts diabetes
O’Sullivan, J., Morningstar, J. E., Yang, Q., Zheng, B., Gao, Y. L., Jeanfavre, S., Scott, J. M., Fernandez, C., Zheng, H., O’Connor, S., et al. (2017) · Journal of Clinical Investigation · doi:10.1172/jci95995 · Cited by 136 · see citing works
Genetics of human metabolism: an update
Kastenmüller, G., Raffler, J., Gieger, C., & Suhre, K. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv263 · Cited by 128 · see citing works
The Serine Hydrolase ABHD6 Is a Critical Regulator of the Metabolic Syndrome
Thomas, G., Betters, J. L., Lord, C. C., Brown, A. L., Marshall, S., Ferguson, D., Sawyer, J. K., Davis, M. A., Melchior, J., Blume, L. C., et al. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.08.047 · Cited by 129 · see citing works
Gromovsky, A. D., Schugar, R. C., Brown, A. L., Helsley, R. N., Burrows, A. C., Ferguson, D., Zhang, R., Sansbury, B. E., Lee, R. G., Morton, R. E., et al. (2018) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/atvbaha.117.309660 · Cited by 115 · see citing works
Wu, J. H. Y., Lemaître, R. N., Manichaikul, A. W., Guan, W., Tanaka, T., Foy, M., Kabagambe, E. K., Djoussé, L., Siscovick, D. S., Fretts, A. M., et al. (2013) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.112.964619 · Cited by 115 · see citing works
He, M., Xu, M., Zhang, B., Liang, J., Chen, P., Lee, J.-Y., Johnson, T. A., Li, H., Yang, X., Dai, J., et al. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddu583 · Cited by 106 · see citing works
Metabolomics platforms for genome wide association studies—linking the genome to the metabolome
Adamski, J., & Suhre, K. (2012) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2012.10.003 · Cited by 113 · see citing works
Liu, Y., Li, X., Aryee, M. J., Ekström, T. J., Padyukov, L., Klareskog, L., Vandiver, A. R., Moore, A. Z., Tanaka, T., Ferrucci, L., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.02.011 · Cited by 106 · see citing works
Fall, T., Salihović, S., Brandmaier, S., Nowak, C., Ganna, A., Gustafsson, S., Broeckling, C. D., Prenni, J. E., Kastenmüller, G., Peters, A., et al. (2016) · Diabetologia · doi:10.1007/s00125-016-4041-1 · Cited by 109 · see citing works
Cadby, G., Giles, C., Melton, P. E., Huynh, K., Mellett, N. A., Duong, T., Nguyen, T. A., Cinel, M. A., Smith, A., Olshansky, G., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30875-7 · Cited by 104 · see citing works
Demographically-based evaluation of genomic regions under selection in domestic dogs
Freedman, A. H., Schweizer, R. M., Ortega-Del Vecchyo, D., Han, E., Davis, B. W., Gronau, I., Silva, P. M., Galaverni, M., Fan, Z., Marx, P., et al. (2016) · PLoS Genetics · doi:10.1371/journal.pgen.1005851 · Cited by 104 · see citing works
Pattaro, C., Gögele, M., Mascalzoni, D., Melotti, R., Schwienbacher, C., Grandi, A. D., Foco, L., D’Elia, Y., Linder, B., Fuchsberger, C., et al. (2015) · Journal of Translational Medicine · doi:10.1186/s12967-015-0704-9 · Cited by 103 · see citing works
Tintle, N., Pottala, J. V., Lacey, S., Vasan, R. S., Westra, J., Rogers, A., Clark, J., Olthoff, B., Larson, M. G., Harris, W. S., et al. (2014) · Prostaglandins Leukotrienes and Essential Fatty Acids · doi:10.1016/j.plefa.2014.11.007 · Cited by 90 · see citing works
Metabolomics based markers predict type 2 diabetes in a 14-year follow-up study
Liu, J., Semiz, S., van der Lee, S. J., van der Spek, A., Verhoeven, A., van Klinken, J. B., Sijbrands, E. J. G., Harms, A. C., Hankemeier, T., van Dijk, K. W., et al. (2017) · Metabolomics · doi:10.1007/s11306-017-1239-2 · Cited by 90 · see citing works
Johansson, Å., Andreassen, O. A., Brunak, S., Franks, P. W., Hedman, H., Loos, R. J. F., Meder, B., Melén, E., Wheelock, C. E., & Jacobsson, B. (2023) · Journal of Internal Medicine · doi:10.1111/joim.13640 · Cited by 98 · see citing works
Lipidomic profiling identifies signatures of metabolic risk
Yin, X., Willinger, C. M., Keefe, J. A., Liu, J., Fernández‐Ortíz, A., Ibáñez, B., Peñalvo, J. L., Adourian, A. S., Chen, G., Corella, D., et al. (2019) · EBioMedicine · doi:10.1016/j.ebiom.2019.10.046 · Cited by 89 · see citing works
Narzo, A. D., Houten, S. M., Kosoy, R., Huang, R., Vaz, F. M., Hou, R., Wei, G., Wang, W., Comella, P., Dodatko, T., et al. (2021) · Gastroenterology · doi:10.1053/j.gastro.2021.11.015 · Cited by 86 · see citing works
Fatty acid desaturase 1 gene polymorphisms control human hepatic lipid composition
Wang, L., Athinarayanan, S. J., Jiang, G., Chalasani, N., Zhang, M., & Liu, W. (2014) · Hepatology · doi:10.1002/hep.27373 · Cited by 86 · see citing works
Mielke, M. M., Bandaru, V. V. R., Han, D., An, Y., Resnick, S. M., Ferrucci, L., & Haughey, N. J. (2015) · Aging Cell · doi:10.1111/acel.12369 · Cited by 85 · see citing works
Coras, R., Murillo‐Saich, J., & Gumá, M. (2020) · Cells · doi:10.3390/cells9040827 · Cited by 85 · see citing works
Integrated Metabolomics and Genomics
Shah, S. H., & Newgard, C. B. (2015) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.114.000223 · Cited by 81 · see citing works
Lone, M. A., Hülsmeier, A. J., Saied, E. M., Karsai, G., Arenz, C., von Eckardstein, A., & Hornemann, T. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2002391117 · Cited by 81 · see citing works
The emerging roles and therapeutic potential of cyclin-dependent kinase 11 (CDK11) in human cancer
Zhou, Y., Shen, J. K., Hornicek, F. J., Kan, Q., & Duan, Z. (2016) · Oncotarget · doi:10.18632/oncotarget.8519 · Cited by 81 · see citing works
Sphingolipid Homeostasis in the Endoplasmic Reticulum and BeyondPreprint
Breslow, D. K. (2013) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a013326 · Cited by 80 · see citing works
An exome array study of the plasma metabolome
Rhee, E. P., Yang, Q., Yu, B., Liu, X., Cheng, S. C., Deik, A., Pierce, K. A., Bullock, K. H., Ho, J. E., Levy, D. A., et al. (2016) · Nature Communications · doi:10.1038/ncomms12360 · Cited by 71 · see citing works
Integrating lipidomics and genomics: emerging tools to understand cardiovascular diseases
Tabassum, R., & Ripatti, S. (2021) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-020-03715-4 · Cited by 70 · see citing works
Lipidome‐ and Genome‐Wide Study to Understand Sex Differences in Circulatory Lipids
Tabassum, R., Ruotsalainen, S., Ottensmann, L., Gerl, M. J., Klose, C. D., Tukiainen, T., Pirinen, M., Simons, K., Widén, E., & Ripatti, S. (2022) · Journal of the American Heart Association · doi:10.1161/jaha.122.027103 · Cited by 65 · see citing works
Barlovič, D. P., Harjutsalo, V., Sandholm, N., Forsblom, C. M., Groop, P., & on behalf of the FinnDiane Study Group (2020) · Diabetologia · doi:10.1007/s00125-020-05201-9 · Cited by 65 · see citing works
McGurk, K. A., Keavney, B. D., & Nicolaou, A. (2021) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2021.04.021 · Cited by 65 · see citing works
Harshfield, E. L., Fauman, E. B., Stacey, D., Paul, D. S., Ziemek, D., Ong, R. M. Y., Danesh, J., Butterworth, A. S., Rasheed, A., Sattar, T., et al. (2021) · BMC Medicine · doi:10.1186/s12916-021-02087-1 · Cited by 64 · see citing works
Systems Epidemiology: A New Direction in Nutrition and Metabolic Disease Research
Cornelis, M. C., & Hu, F. B. (2013) · Current Nutrition Reports · doi:10.1007/s13668-013-0052-4 · Cited by 61 · see citing works
Wittenbecher, C., Cuadrat, R. R. C., Johnston, L., Eichelmann, F., Jäger, S., Kuxhaus, O., Prada, M., Fabiola Del Greco, M., Hicks, A. A., Hoffman, P., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28496-1 · Cited by 62 · see citing works
Al‐Khelaifi, F., Diboun, I., Donati, F., Botrè, F., Abraham, D., Hingorani, A. D., Albagha, O., Georgakopoulos, C. G., Suhre, K., Yousri, N. A., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-56496-7 · Cited by 61 · see citing works
Hu, Y., Li, H., Lu, L., Manichaikul, A. W., Zhu, J., Chen, Y.-D. I., Sun, L. D., Liang, S., Siscovick, D. S., Steffen, L. M., et al. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw002 · Cited by 59 · see citing works
Computational approaches for systems metabolomics
Krumsiek, J., Bartel, J., & Theis, F. J. (2016) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2016.04.009 · Cited by 59 · see citing works
Sphingolipids in Psychiatric Disorders and Pain Syndromes
Mühle, C., Reichel, M., Gulbins, E., & Kornhuber, J. (2013) · Handbook of Experimental Pharmacology · doi:10.1007/978-3-7091-1511-4_22 · Cited by 58 · see citing works
The GenABEL Project for statistical genomics
Karssen, L. C., van Duijn, C. M., & Aulchenko, Y. S. (2016) · F1000Research · doi:10.12688/f1000research.8733.1 · Cited by 58 · see citing works
Hysi, P. G., Mangino, M., Christofidou, P., Falchi, M., Karoly, E. D., NIHR Bioresource Investigators, Mohney, R. P., Valdes, A. M., Spector, T. D., & Menni, C. (2022) · Metabolites · doi:10.3390/metabo12010061 · Cited by 55 · see citing works
Biochemical insights from population studies with genetics and metabolomics
Suhre, K., Raffler, J., & Kastenmüller, G. (2015) · Archives of Biochemistry and Biophysics · doi:10.1016/j.abb.2015.09.023 · Cited by 55 · see citing works
Systematic analysis of the regulatory functions of microRNAs in chicken hepatic lipid metabolism
Li, H., Ma, Z., Jia, L., Li, Y., Xu, C., Wang, T., Han, R., Jiang, R., Li, Z., Sun, G., et al. (2016) · Scientific Reports · doi:10.1038/srep31766 · Cited by 56 · see citing works
Tahir, U. A., Katz, D. H., Ávila-Pacheco, J., Bick, A. G., Pampana, A., Robbins, J., Yu, Z., Chen, Z., Benson, M. D., Cruz, D. E., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32275-3 · Cited by 52 · see citing works
Ceramides are fuel gauges on the drive to cardiometabolic disease
Wilkerson, J. L., Tatum, S. M., Holland, W. L., & Summers, S. A. (2024) · Physiological Reviews · doi:10.1152/physrev.00008.2023 · Cited by 59 · see citing works
A large-scale genome–lipid association map guides lipid identification
Linke, V., Overmyer, K. A., Miller, I. J., Brademan, D. R., Hutchins, P. D., Trujillo, E. A., Reddy, T. R., Russell, J. D., Cushing, E. M., Schueler, K. L., et al. (2020) · Nature Metabolism · doi:10.1038/s42255-020-00278-3 · Cited by 54 · see citing works
Genetic Determinants of P Wave Duration and PR Segment
Verweij, N., Leach, I. M., van den Boogaard, M., van Veldhuisen, D. J., Christoffels, V. M., Study, L. C., Hillege, H. L., van Gilst, W. H., Barnett, P., de Boer, R. A., et al. (2014) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.113.000373 · Cited by 53 · see citing works
Lu, Y., Vaarhorst, A. A. M., Merry, A. H. H., Dollé, M. E. T., Hovenier, R., Imholz, S., Schouten, L. J., Heijmans, B. T., Müller, M. M., Slagboom, P. E., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0041681 · Cited by 52 · see citing works
Lysophospholipid acyltransferases
Agarwal, A. K. (2012) · Current Opinion in Lipidology · doi:10.1097/mol.0b013e328354fcf4 · Cited by 52 · see citing works
Endogenous Production of Long-Chain Polyunsaturated Fatty Acids and Metabolic Disease Risk
Murff, H. J., & Edwards, T. L. (2014) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-014-0418-1 · Cited by 51 · see citing works
Amin, N., Jovanova, O., Adams, H. H. H., Dehghan, A., Kavousi, M., Vernooij, M. W., Peeters, R. P., de Vrij, F. M. S., van der Lee, S. J., van Rooij, J., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.101 · Cited by 50 · see citing works
A Mendelian Randomization Study of Metabolite Profiles, Fasting Glucose, and Type 2 Diabetes
Liu, J., van Klinken, J. B., Semiz, S., van Dijk, K. W., Verhoeven, A., Hankemeier, T., Harms, A. C., Sijbrands, E. J. G., Sheehan, N. A., van Duijn, C. M., et al. (2017) · Diabetes · doi:10.2337/db17-0199 · Cited by 48 · see citing works
The Identification of Key Genes and Pathways in Glioma by Bioinformatics Analysis
Liu, M., Xu, Z., Du, Z., Wu, B., Jin, T., Xu, K., Xu, L., Li, E., & Xu, H. (2017) · Journal of Immunology Research · doi:10.1155/2017/1278081 · Cited by 50 · see citing works
Graham, E., Lee, J. K., Price, M., Tarailo‐Graovac, M., Matthews, A., Engelke, U. F. H., Tang, J. S., Kluijtmans, L. A. J., Wevers, R. A., Wasserman, W. W., et al. (2018) · Journal of Inherited Metabolic Disease · doi:10.1007/s10545-018-0139-6 · Cited by 50 · see citing works
Ottesen, E. W., Singh, N. N., Luo, D., Kaas, B., Gillette, B., Seo, J., Jorgensen, H. J., & Singh, R. N. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad259 · Cited by 48 · see citing works
Li, Y., Sekula, P., Wuttke, M., Wahrheit, J., Hausknecht, B., Schultheiß, U. T., Gronwald, W., Schlosser, P., Tucci, S., Ekici, A. B., et al. (2018) · Journal of the American Society of Nephrology · doi:10.1681/asn.2017101099 · Cited by 48 · see citing works
Metabolomics and ischaemic heart disease
Rasmiena, A. A., Ng, T. W., & Meikle, P. J. (2012) · Clinical Science · doi:10.1042/cs20120268 · Cited by 48 · see citing works
van Son, M., Enger, E. G., Grove, H., Ros‐Freixedes, R., Kent, M., Lien, S., & Grindflek, E. H. (2017) · BMC Genomics · doi:10.1186/s12864-017-3752-0 · Cited by 48 · see citing works
Burkhardt, R., Kirsten, H., Beutner, F., Holdt, L. M., Gross, A., Teren, A., Tönjes, A., Becker, S., Krohn, K., Kovacs, P. L., et al. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005510 · Cited by 46 · see citing works
Metabolic, Reproductive, and Neurologic Abnormalities in Agpat1-Null Mice
Agarwal, A. K., Tunison, K., Dalal, J. S., Nagamma, S., Hamra, F. K., Sankella, S., Shao, X., Auchus, R. J., & Garg, A. (2017) · Endocrinology · doi:10.1210/en.2017-00511 · Cited by 47 · see citing works
Smith, C. E., Follis, J. L., Nettleton, J. A., Foy, M., Wu, J. H. Y., Ma, Y., Tanaka, T., Manichakul, A. W., Wu, H., Chu, A. Y., et al. (2015) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201400734 · Cited by 46 · see citing works
Ung, C., Sanchez, A. V., Shen, L., Davoudi, S., Ahmadi, T., Navarro-Gomez, D., Chen, C. J., Hancock, H., Penman, A. D., Hoadley, S., et al. (2017) · Vision Research · doi:10.1016/j.visres.2017.03.007 · Cited by 45 · see citing works
Scholz, M. R., Horn, K., Pott, J., Gross, A., Kleber, M. E., Delgado, G. E., Mishra, P. P., Kirsten, H., Gieger, C., Müller‐Nurasyid, M., et al. (2022) · Nature Communications · doi:10.1038/s41467-021-27706-6 · Cited by 45 · see citing works
Puentes, A. D. L. G., Montes, R., Tonato, A. M. C., Torres-Espínola, F. J., García, M. A., de Almeida, L., Aguirre, M. B., Guerendiain, M., Castellote, A. I., Moreno, M. S., et al. (2017) · PLoS ONE · doi:10.1371/journal.pone.0179135 · Cited by 44 · see citing works
Karjalainen, J.-P., Mononen, N., Hutri‐Kähönen, N., Lehtimäki, M., Hilvo, M., Kauhanen, D., Juonala, M., Viikari, J. S. A., Kähönen, M. A. P., Raitakari, O. T., et al. (2019) · Journal of Lipid Research · doi:10.1194/jlr.m092809 · Cited by 43 · see citing works
Rapid Growth and Childhood Obesity Are Strongly Associated with LysoPC(14:0)
Rzehak, P., Hellmuth, C., Uhl, O., Kirchberg, F. F., Peißner, W., Harder, U., Grote, V., Weber, M., Xhonneux, A., Langhendries, J., et al. (2014) · Annals of Nutrition and Metabolism · doi:10.1159/000365037 · Cited by 43 · see citing works
Hsieh, P., Hallmark, B., Watkins, J. C., Karafet, T. M., Osipova, L. P., Gutenkunst, R. N., & Hammer, M. F. (2017) · Molecular Biology and Evolution · doi:10.1093/molbev/msx226 · Cited by 39 · see citing works
Potential Role of Omega-3 Polyunsaturated Fatty Acids in Pediatric Food Allergy
Sartorio, M. U. A., Pendezza, E., Coppola, S., Paparo, L., D’Auria, E., Zuccotti, G., & Canani, R. B. (2021) · Nutrients · doi:10.3390/nu14010152 · Cited by 40 · see citing works
Metabolomics in epidemiology: from metabolite concentrations to integrative reaction networks
Fearnley, L. G., & Inouye, M. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw046 · Cited by 40 · see citing works
Teslovich, T. M., Kim, D. S., Yin, X., Stančáková, A., Jackson, A., Wielscher, M., Naj, A. C., Perry, J. R. B., Huyghe, J. R., Stringham, H. M., et al. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy067 · Cited by 36 · see citing works
Genome-Wide Association Studies of Metabolite Concentrations (mGWAS): Relevance for Nephrology
Köttgen, A., Raffler, J., Sekula, P., & Kastenmüller, G. (2018) · Seminars in Nephrology · doi:10.1016/j.semnephrol.2018.01.009 · Cited by 37 · see citing works
Kaur, K., Lesseur, C., Deyssenroth, M. A., Kloog, I., Schwartz, J. D., Marsit, C. J., & Chen, J. (2022) · Environmental Research · doi:10.1016/j.envres.2022.113066 · Cited by 36 · see citing works
Ponsuksili, S., Du, Y., Muráni, E., Schwerin, M., & Wimmers, K. (2012) · Genetics · doi:10.1534/genetics.112.143081 · Cited by 32 · see citing works
Maternal Nutrition, Genetics, and Human Milk Lipids
Innis, S. M. (2013) · Current Nutrition Reports · doi:10.1007/s13668-013-0048-0 · Cited by 35 · see citing works
Genetics of the human metabolome, what is next?
Dharuri, H. K., Demirkan, A., van Klinken, J. B., Mook-Kanamori, D. O., van Duijn, C. M., Hoen, P. A. C. ’., & van Dijk, K. W. (2014) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2014.05.030 · Cited by 34 · see citing works
Barman, M., Nilsson, S., Naluai, Å. T., Sandin, A., Wold, A. E., & Sandberg, A. (2015) · Nutrients · doi:10.3390/nu7125521 · Cited by 34 · see citing works
Rämö, J. T., Ripatti, P., Tabassum, R., Söderlund, S., Matikainen, N., Gerl, M. J., Klose, C. D., Surma, M. A., Stitziel, N. O., Havulinna, A. S., et al. (2019) · Journal of the American Heart Association · doi:10.1161/jaha.119.012415 · Cited by 34 · see citing works
Kalsbeek, A., Veenstra, J., Westra, J., Disselkoen, C., Koch, K., McKenzie, K. A., O’Bott, J., Woude, J. V., Fischer, K., Shearer, G. C., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0194882 · Cited by 33 · see citing works
Tissue-specific Co-expression of Long Non-coding and Coding RNAs Associated with Breast Cancer
Wu, W., Wagner, E. K., Hao, Y., Rao, X., Dai, H., Han, J., Chen, J., Storniolo, A. M., Liu, Y., & He, C. (2016) · Scientific Reports · doi:10.1038/srep32731 · Cited by 32 · see citing works
A Human XPC Protein Interactome—A Resource
Lubin, A., Zhang, L., Chen, H., White, V., & Gong, F. (2013) · International Journal of Molecular Sciences · doi:10.3390/ijms15010141 · Cited by 31 · see citing works
Andersen, M. K., Jørsboe, E., Sandholt, C. H., Grarup, N., Jørgensen, M. E., Færgeman, N. J., Bjerregaard, P., Pedersen, O. B., Moltke, I., Hansen, T. F., et al. (2016) · PLoS Genetics · doi:10.1371/journal.pgen.1006119 · Cited by 30 · see citing works
Nonadditive Effects of Genes in Human Metabolomics
Tsepilov, Y. A., Shin, S., Soranzo, N., Spector, T. D., Prehn, C. P., Adamski, J., Kastenmüller, G., Wang‐Sattler, R., Strauch, K., Gieger, C., et al. (2015) · Genetics · doi:10.1534/genetics.115.175760 · Cited by 30 · see citing works
Tremblay, B. L., Guénard, F., Lamarche, B., Përusse, L., & Vohl, M. (2018) · Nutrition Research · doi:10.1016/j.nutres.2018.10.003 · Cited by 29 · see citing works
Li‐Gao, R., Hughes, D. A., van Klinken, J. B., de Mutsert, R., Rosendaal, F. R., Mook-Kanamori, D. O., Timpson, N. J., & van Dijk, K. W. (2021) · Diabetes · doi:10.2337/db21-0397 · Cited by 28 · see citing works
- Authors
- Demirkan, A., van Duijn, C. M., Ugocsai, P., Isaacs, A., Pramstaller, P. P., Liebisch, G., Wilson, J. F., Johansson, Å., Rudan, I., Aulchenko, Y. S., Kirichenko, A. V., Janssens, A. C. J. W., Jansen, R. C., Gnewuch, C., Domingues, F. S., Pattaro, C., Wild, S. H., Jonasson, I., Polasek, O., Zorkoltseva, I. V., Hofman, A., Karssen, L. C., Struchalin, M., Floyd, J., Igl, W., Biloglav, Z., Broer, L., Pfeufer, A., Pichler, I., Campbell, S., Zaboli, G., Kolcic, I., Rivadeneira, F., Huffman, J., Hastie, N. D., Uitterlinden, A., Franke, L., Franklin, C. S., Vitart, V., DIAGRAM Consortium, Nelson, C. P., Preuss, M., CARDIoGRAM Consortium, Bis, J. C., O'Donnell, C. J., Franceschini, N., CHARGE Consortium, Witteman, J. C. M., Axenovich, T., Oostra, B. A., Meitinger, T., Hicks, A. A., Hayward, C., Wright, A. F., Gyllensten, U., Campbell, H., Schmitz, G., & on behalf of the EUROSPAN consortium
- Affiliations
- Erasmus MC (NL)
- Eurac Research (IT)
- University Hospital Regensburg (DE)
- University of Edinburgh (GB)
- Uppsala University (SE)
- University of Split (HR)
- Russian Academy of Sciences (RU)
- University of Groningen (NL)
- Wellcome Sanger Institute (GB)
- University of Zagreb (HR)
- Institute of Genetics and Cancer (GB)
- University Medical Center Groningen (NL)
- University of Leicester (GB)
- University of Lübeck (DE)
- University of Washington (US)
- University of North Carolina at Chapel Hill (US)
- Helmholtz Munich (DE)
- Corresponding author
- Isaacs, Aaron
- ORCID
- Demirkan, Ayşe
- Isaacs, Aaron
- Pramstaller, Peter P.
- Liebisch, Gerhard
- Wilson, James F.
- Johansson, Åsa
- Rudan, Igor
- Aulchenko, Yurii S.
- Janssens, A. Cecile J. W.
- Domingues, Francisco S.
- Pattaro, Cristian
- Wild, Sarah H.
- Zorkoltseva, Irina V.
- Karssen, Lennart C.
- Struchalin, Maksim
- Igl, Wilmar
- Biloglav, Zrinka
- Broer, Linda
- Pichler, Irene
- Rivadeneira, Fernando
- Huffman, Jennifer
- Hastie, Nicholas D.
- Franke, Lude
- Franklin, Christopher S.
- Nelson, Christopher P.
- Preuss, Michael
- Bis, Joshua C.
- Franceschini, Nora
- Axenovich, Tatiana
- Meitinger, Thomas
- Hicks, Andrew A.
- Hayward, Caroline
- Gyllensten, Ulf
- Schmitz, Gerd
- Venue
- PLoS Genetics
- Publisher
- Public Library of Science (PLoS)
- Published
- 2012-02-16
- Volume
- 8
- Issue
- 2
- Pages
- e1002490
- ISSN
- 1553-7390 (ISSN-L)
- 1553-7404
- PMC
- PMC3280968
- OpenAlex
- W2132495615
- Cited by
- 205
- References
- 39
- Citations by year
- 2026: 3 · 2025: 10 · 2024: 11 · 2023: 14 · 2022: 14 · 2021: 12 · 2020: 13 · 2019: 20 · 2018: 16 · 2017: 17 · 2016: 16 · 2015: 14 · 2014: 22 · 2013: 13 · 2012: 10
- FWCI
- 2.31
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Genetics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (acceptedVersion, other-oa)
- Leicester Research Archive (University of Leicester) (acceptedVersion, other-oa)
- Research Explorer (The University of Manchester) (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
- KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion)
- Figshare (submittedVersion, cc-by)
- IRIS (submittedVersion)
- Open Research Exeter (University of Exeter) (submittedVersion, cc-by)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
- SERVAL (Université de Lausanne) (submittedVersion)
- Spiral (Imperial College London) (submittedVersion, other-oa)
- OPUS (Augsburg University) (submittedVersion, cc-by)
- Open Research (University of Surrey) (submittedVersion)
- Hirsla (Landspítali University Hospital) (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Apollo (cc-by)
- Funders
- Wellcome Trust (202272, 090532)
- Royal Society
- European Commission (018947, LSHG-CT-2006-01947, 202272)
- Russian Foundation for Basic Research (047.017.043, NWORFBR 047.017.043)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (047.016.009, NWO-RFBR 047.017.043, RFBR 047.017.043, 047.017.043)
- Centre for Medical Systems Biology
- Provincia autonoma di Bolzano - Alto Adige
- National Institutes of Health (UL1TR000124)
- Medical Research Council
- National Heart, Lung, and Blood Institute (R01HL105756)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK063491)
- National Center for Advancing Translational Sciences
- H2020 European Research Council
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Sphingolipid Metabolism and Signaling
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biochemistry › Lipid metabolism and biosynthesis
- Keywords
- phospholipids, sphingolipids, plasma lipid levels, genetic loci, sphingomyelin, ceramide, phosphatidylcholine, lysophosphatidylcholine, phosphatidylethanolamine, plasmalogens, PKD2L1, phospholipase D2, apolipoprotein E, fatty acid elongation, fatty acid saturation, glycerophospholipids
- MeSH terms
- Delta-5 Fatty Acid Desaturase, Diabetes Mellitus, Type 2, Humans, Phospholipids, Sphingolipids, Genome, Human, Polymorphism, Single Nucleotide, Databases, Genetic, White People, Genome-Wide Association Study, Genetic Loci, Carotid Intima-Media Thickness
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