Liquid Chromatography-Mass Spectrometry (LC-MS)-Based Lipidomics for Studies of Body Fluids and Tissues

Molecular Biology of the Cell

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A comprehensive classification system for lipids

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The emerging field of lipidomics

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Shotgun lipidomics: Electrospray ionization mass spectrometric analysis and quantitation of cellular lipidomes directly from crude extracts of biological samples

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Large-Scale Human Metabolomics Studies: A Strategy for Data (Pre-) Processing and Validation

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MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data

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Dysregulation of lipid and amino acid metabolism precedes islet autoimmunity in children who later progress to type 1 diabetes

Orešič, M., Simell, S., Sysi-Aho, M., Näntö-Salonen, K., Seppänen-Laakso, T., Parikka, V., Katajamaa, M., Hekkala, A., Mattila, I., Keskinen, P., et al. (2008) · The Journal of Experimental Medicine · doi:10.1084/jem.20081800 · Cited by 449 · see citing works

Processing methods for differential analysis of LC/MS profile data

Katajamaa, M., & Orešič, M. (2005) · BMC Bioinformatics · doi:10.1186/1471-2105-6-179 · Cited by 400 · see citing works

Assessing the Nature of Lipid Raft Membranes

Niemelä, P. S., Ollila, O. H. S., Hyvönen, M., Karttunen, M., & Vattulainen, I. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030034 · Cited by 294 · see citing works

Nonlinear Data Alignment for UPLC−MS and HPLC−MS Based Metabolomics: Quantitative Analysis of Endogenous and Exogenous Metabolites in Human Serum

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Bioinformatics strategies for lipidomics analysis: characterization of obesity related hepatic steatosis

Yetukuri, L., Katajamaa, M., Medina‐Gómez, G., Seppänen‐Laakso, T., Vidal‐Puig, A., & Orešič, M. (2007) · BMC Systems Biology · doi:10.1186/1752-0509-1-12 · Cited by 263 · see citing works

A Systems Biology Strategy Reveals Biological Pathways and Plasma Biomarker Candidates for Potentially Toxic Statin-Induced Changes in Muscle

Laaksonen, R., Katajamaa, M., Päivä, H., Sysi‐Aho, M., Saarinen, L., Junni, P., Lütjohann, D., Smet, J., Coster, R. V., Seppänen‐Laakso, T., et al. (2006) · PLoS ONE · doi:10.1371/journal.pone.0000097 · Cited by 223 · see citing works

Informatics and computational strategies for the study of lipids

Yetukuri, L., Ekroos, K., Vidal‐Puig, A., & Orešič, M. (2007) · Molecular BioSystems · doi:10.1039/b715468b · Cited by 220 · see citing works

A shotgun tandem mass spectrometric analysis of phospholipids with normal‐phase and/or reverse‐phase liquid chromatography/electrospray ionization mass spectrometry

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Lipidomics: a new window to biomedical frontiers

Orešič, M., Hänninen, V. A., & Vidal‐Puig, A. (2008) · Trends in biotechnology · doi:10.1016/j.tibtech.2008.09.001 · Cited by 188 · see citing works

Sphingolipidomics: Methods for the comprehensive analysis of sphingolipids

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Shotgun Lipidomics by Tandem Mass Spectrometry under Data‐Dependent Acquisition Control

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From lipid analysis towards lipidomics, a new challenge for the analytical chemistry of the 21st century. Part I: Modern lipid analysis

Carrasco-Pancorbo, A., Navas-Iglesias, N., & Cuadros-Rodríguez, L. (2009) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2008.12.005 · Cited by 100 · see citing works

Human gut microbes impact host serum metabolome and insulin sensitivity

Pedersen, H. K., Gudmundsdottir, V., Nielsen, H. B., Hyotylainen, T., Nielsen, T., Jensen, B. A. H., Forslund, K., Hildebrand, F., Prifti, E., Falony, G., et al. (2016) · Nature · doi:10.1038/nature18646 · Cited by 2,116 · see citing works

The Dynamics of the Human Infant Gut Microbiome in Development and in Progression toward Type 1 Diabetes

Kostic, A. D., Gevers, D., Siljander, H., Vatanen, T., Hyötyläinen, T., Hämäläinen, A., Peet, A., Tillmann, V., Pöhö, P., Mattila, I. M., et al. (2015) · Cell Host & Microbe · doi:10.1016/j.chom.2015.01.001 · Cited by 1,165 · see citing works

Comprehensive analysis of lipids in biological systems by liquid chromatography-mass spectrometry

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Metabolomics: A Primer

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Deficient Endoplasmic Reticulum-Mitochondrial Phosphatidylserine Transfer Causes Liver Disease

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Objective Set of Criteria for Optimization of Sample Preparation Procedures for Ultra-High Throughput Untargeted Blood Plasma Lipid Profiling by Ultra Performance Liquid Chromatography–Mass Spectrometry

Sarafian, M. H., Gaudin, M., Lewis, M. R., Martin, F., Holmes, E. C., Nicholson, J. K., & Dumas, M. (2014) · Analytical Chemistry · doi:10.1021/ac500317c · Cited by 303 · see citing works

Metabolome in progression to Alzheimer's disease

Orešič, M., Hyötyläinen, T., Herukka, S.-K., Sysi‐Aho, M., Mattila, I. M., Seppänan-Laakso, T., Julkunen, V., Gopalacharyulu, P. V., Hallikainen, M., Koikkalainen, J. R., et al. (2011) · Translational Psychiatry · doi:10.1038/tp.2011.55 · Cited by 280 · see citing works

Ultra Performance Liquid Chromatography and High Resolution Mass Spectrometry for the Analysis of Plant Lipids

Hummel, J., Segu, S., Li, Y., Irgang, S., Jüppner, J., & Giavalisco, P. (2011) · Frontiers in Plant Science · doi:10.3389/fpls.2011.00054 · Cited by 221 · see citing works

Statistical Methods for Handling Unwanted Variation in Metabolomics Data

Livera, A. M. D., Sysi‐Aho, M., Jacob, L., Gagnon-Bartsch, J. A., Castillo, S., Simpson, J. A., & Speed, T. P. (2015) · Analytical Chemistry · doi:10.1021/ac502439y · Cited by 195 · see citing works

Mammalian cell metabolomics: Experimental design and sample preparation

León, Z., García‐Cañaveras, J. C., Donato, M. T., & Lahoz, A. (2013) · Electrophoresis · doi:10.1002/elps.201200605 · Cited by 194 · see citing works

Lipidomics: Potential role in risk prediction and therapeutic monitoring for diabetes and cardiovascular disease

Meikle, P. J., Wong, G., Barlow, C. K., & Kingwell, B. A. (2014) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2014.02.001 · Cited by 185 · see citing works

Role of liquid chromatography–high-resolution mass spectrometry (LC-HR/MS) in clinical toxicology

Wu, A. H. B., Gerona, R. R. L., Armenian, P., French, D., Petrie, M. S., & Lynch, K. L. (2012) · Clinical Toxicology · doi:10.3109/15563650.2012.713108 · Cited by 184 · see citing works

Accurate Quantification of Lipid Species by Electrospray Ionization Mass Spectrometry — Meets a Key Challenge in Lipidomics

Yang, K., & Han, X. (2011) · Metabolites · doi:10.3390/metabo1010021 · Cited by 181 · see citing works

Mass Spectrometry Based Lipidomics: An Overview of Technological Platforms

Köfeler, H. C., Fauland, A., Rechberger, G. N., & Trötzmüller, M. (2012) · Metabolites · doi:10.3390/metabo2010019 · Cited by 181 · see citing works

Prediction of non-alcoholic fatty-liver disease and liver fat content by serum molecular lipids

Orešič, M., Hyötyläinen, T., Kotronen, A., Gopalacharyulu, P. V., Nygrén, H., Arola, J. T., Castillo, S., Mattila, I. M., Hakkarainen, A., Borra, R., et al. (2013) · Diabetologia · doi:10.1007/s00125-013-2981-2 · Cited by 168 · see citing works

Phospholipids and insulin resistance in psychosis: A lipidomics study of twin pairs discordant for schizophrenia

Orešič, M., Seppänen‐Laakso, T., Sun, D., Tang, J. P., Therman, S., Viehman, R., Mustonen, U., van Erp, T. G., Hyötyläinen, T., Thompson, P. M., et al. (2012) · eScholarship (California Digital Library) · Cited by 168 · see citing works

Human Tear Fluid Lipidome: From Composition to Function

Rantamäki, A. H., Seppänen‐Laakso, T., Orešič, M., Jauhiainen, M., & Holopainen, J. M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0019553 · Cited by 151 · see citing works

Lipidome as a predictive tool in progression to type 2 diabetes in Finnish men

Suvitaival, T., Bondia‐Pons, I., Yetukuri, L., Pöhö, P., Nolan, J. J., Hyötyläinen, T., Kuusisto, J., & Orešič, M. (2017) · Metabolism · doi:10.1016/j.metabol.2017.08.014 · Cited by 147 · see citing works

Integration of molecular profiles in a longitudinal wellness profiling cohort

Tebani, A., Gummesson, A., Zhong, W., Koistinen, I. S., Lakshmikanth, T., Olsson, L. M., Boulund, F., Neiman, M., Stenlund, H., Hellström, C., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18148-7 · Cited by 100 · see citing works

Sphingolipids as prognostic biomarkers of neurodegeneration, neuroinflammation, and psychiatric diseases and their emerging role in lipidomic investigation methods

van Kruining, D., Luo, Q., van Echten‐Deckert, G., Mielke, M. M., Bowman, A. P., Ellis, S. R., Oliveira, T. G., & Martínez‐Martínez, P. (2020) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2020.04.009 · Cited by 136 · see citing works

Lipidomics Applications for Discovering Biomarkers of Diseases in Clinical Chemistry

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Prolonged sleep restriction induces changes in pathways involved in cholesterol metabolism and inflammatory responses

Aho, V., Ollila, H. M., Kronholm, E., Bondia-Pons, I., Soininen, P., Kangas, A. J., Hilvo, M., Seppälä, I., Kettunen, J., Oikonen, M., et al. (2016) · Scientific Reports · doi:10.1038/srep24828 · Cited by 126 · see citing works

A computational framework to integrate high-throughput ‘-omics’ datasets for the identification of potential mechanistic links

Pedersen, H., Forslund, S. K., Guðmundsdóttir, V., Petersen, A. Ø., Hildebrand, F., Hyötyläinen, T., Nielsen, T., Hansen, T. F., Bork, P., Ehrlich, S. D., et al. (2018) · Nature Protocols · doi:10.1038/s41596-018-0064-z · Cited by 118 · see citing works

Circulating triacylglycerol signatures and insulin sensitivity in NAFLD associated with the E167K variant in TM6SF2

Zhou, Y., Llauradó, G., Orešič, M., Hyötyläinen, T., Orho‐Melander, M., & Yki‐Järvinen, H. (2014) · Journal of Hepatology · doi:10.1016/j.jhep.2014.10.010 · Cited by 112 · see citing works

Effects of ellagitannin‐rich berries on blood lipids, gut microbiota, and urolithin production in human subjects with symptoms of metabolic syndrome

Puupponen‐Pimiä, R., Seppänen‐Laakso, T., Kankainen, M., Maukonen, J., Törrönen, R., Kolehmainen, M., Leppänen, T., Moilanen, E., Nohynek, L. J., Aura, A., et al. (2013) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201300280 · Cited by 109 · see citing works

A reversed-phase capillary ultra-performance liquid chromatography–mass spectrometry (UPLC-MS) method for comprehensive top-down/bottom-up lipid profiling

Gao, X., Zhang, Q., Meng, D., Isaac, G., Zhao, R., Fillmore, T., Chu, R., Zhou, J., Tang, K., Hu, Z., et al. (2012) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-012-5773-5 · Cited by 97 · see citing works

Decreased Cord-Blood Phospholipids in Young Age–at–Onset Type 1 Diabetes

Torre, D. L., Seppänen‐Laakso, T., Larsson, H. E., Hyötyläinen, T., Ivarsson, S. A., Lernmark, Å., Orešič, M., & and the DiPiS Study Group (2013) · Diabetes · doi:10.2337/db13-0215 · Cited by 96 · see citing works

Lipidomics in Ulcerative Colitis Reveal Alteration in Mucosal Lipid Composition Associated With the Disease State

Diab, J., Hansen, T., Goll, R., Stenlund, H. C., Ahnlund, M., Jensen, E., Möritz, T., Florholmen, J., & Forsdahl, G. (2019) · Inflammatory Bowel Diseases · doi:10.1093/ibd/izz098 · Cited by 95 · see citing works

Opportunities and Challenges for Machine Learning in Rare Diseases

Decherchi, S., Pedrini, E., Mordenti, M., Cavalli, A., & Sangiorgi, L. (2021) · Frontiers in Medicine · doi:10.3389/fmed.2021.747612 · Cited by 93 · see citing works

Interaction between dietary lipids and gut microbiota regulates hepatic cholesterol metabolism

Caesar, R., Nygrén, H., Orešič, M., & Bäckhed, F. (2016) · Journal of Lipid Research · doi:10.1194/jlr.m065847 · Cited by 93 · see citing works

Optimizing the lipidomics workflow for clinical studies—practical considerations

Hyötyläinen, T., & Orešič, M. (2015) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-015-8633-2 · Cited by 92 · see citing works

Metabolic Regulation in Progression to Autoimmune Diabetes

Sysi‐Aho, M., Ermolov, A., Gopalacharyulu, P. V., Tripathi, A., Seppänen‐Laakso, T., Maukonen, J., Mattila, I. M., Ruohonen, S. T., Vähätalo, L. H., Yetukuri, L., et al. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002257 · Cited by 88 · see citing works

Cord Serum Lipidome in Prediction of Islet Autoimmunity and Type 1 Diabetes

Orešič, M., Gopalacharyulu, P. V., Mykkänen, J., Lietzén, N., Mäkinen, M., Nygrén, H., Simell, S., Simell, V., Hyöty, H., Veijola, R., et al. (2013) · Diabetes · doi:10.2337/db13-0159 · Cited by 87 · see citing works

Differential Intrahepatic Phospholipid Zonation in Simple Steatosis and Nonalcoholic Steatohepatitis

Wattacheril, J. J., Seeley, E. H., Angel, P. M., Chen, H., Bowen, B. P., Lanciault, C., Caprioli, R. M., Abumrad, N. N., & Flynn, C. R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057165 · Cited by 88 · see citing works

Systems biology strategies to study lipidomes in health and disease

Hyötyläinen, T., & Orešič, M. (2014) · Progress in Lipid Research · doi:10.1016/j.plipres.2014.06.001 · Cited by 82 · see citing works

Integration of Metabolomics and Expression of Glycerol-3-phosphate Acyltransferase (GPAM) in Breast Cancer—Link to Patient Survival, Hormone Receptor Status, and Metabolic Profiling

Brockmöller, S. F., Bucher, E., Müller, B. M., Budczies, J., Hilvo, M., Griffin, J. L., Orešič, M., Kallioniemi, O., Iljin, K., Loibl, S., et al. (2011) · Journal of Proteome Research · doi:10.1021/pr200685r · Cited by 77 · see citing works

Exercise training improves mitochondrial respiration and is associated with an altered intramuscular phospholipid signature in women with obesity

Mendham, A., Goedecke, J., Zeng, Y., Larsen, S., George, C., Hauksson, J., Smidt, M. F. F.-D., Chibalin, A., Olsson, T., & Chorell, E. (2021) · Diabetologia · doi:10.1007/s00125-021-05430-6 · Cited by 68 · see citing works

Lipidomics in nutrition and food research

Hyötyläinen, T., Bondia‐Pons, I., & Orešič, M. (2013) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201200759 · Cited by 71 · see citing works

Prenatal exposure to perfluoroalkyl substances modulates neonatal serum phospholipids, increasing risk of type 1 diabetes

McGlinchey, A., Sinioja, T., Lamichhane, S., Sen, P., Bodin, J., Siljander, H., Dickens, A. M., Geng, D., Carlsson, C., Duberg, D., et al. (2020) · Environment International · doi:10.1016/j.envint.2020.105935 · Cited by 61 · see citing works

Circulating Triacylglycerol Signatures in Nonalcoholic Fatty Liver Disease Associated With the I148M Variant in PNPLA3 and With Obesity

Hyysalo, J., Gopalacharyulu, P. V., Bian, H., Hyötyläinen, T., Leivonen, M., Jaser, N., Juuti, A., Honka, M., Nuutila, P., Olkkonen, V. M., et al. (2013) · Diabetes · doi:10.2337/db13-0774 · Cited by 61 · see citing works

PGC-1α Coordinates Mitochondrial Respiratory Capacity and Muscular Fatty Acid Uptake via Regulation of VEGF-B

Mehlem, A., Palombo, I., Wang, X., Hagberg, C. E., Eriksson, U., & Falkevall, A. (2016) · Diabetes · doi:10.2337/db15-1231 · Cited by 60 · see citing works

Novel Approach for Analysis of Bronchoalveolar Lavage Fluid (BALF) Using HPLC-QTOF-MS-Based Lipidomics: Lipid Levels in Asthmatics and Corticosteroid-Treated Asthmatic Patients

Kang, Y. P., Lee, W. J., Hong, J. Y., Lee, S. B., Park, J. H., Kim, D., Park, S., Park, C., Park, H., & Kwon, S. W. (2014) · Journal of Proteome Research · doi:10.1021/pr5002059 · Cited by 59 · see citing works

Metabolic Signatures of the Exposome—Quantifying the Impact of Exposure to Environmental Chemicals on Human Health

Orešič, M., McGlinchey, A. J., Wheelock, C. E., & Hyötyläinen, T. (2020) · Metabolites · doi:10.3390/metabo10110454 · Cited by 49 · see citing works

Plasma Biomarkers for Alzheimer’s Disease: Much Needed But Tough to Find

Bazenet, C. E., & Lovestone, S. (2012) · Biomarkers in Medicine · doi:10.2217/bmm.12.48 · Cited by 48 · see citing works

Three‐dimensional genetic networks among seed oil‐related traits, metabolites and genes reveal the genetic foundations of oil synthesis in soybean

Liu, J., Li, P., Zhang, Y., Guo, L., Li, G., Han, X., Dunwell, J. M., & Zhang, Y. (2020) · The Plant Journal · doi:10.1111/tpj.14788 · Cited by 48 · see citing works

The state of the art in plant lipidomics

Kehelpannala, C., Rupasinghe, T., Hennessy, T., Bradley, D. A., Ebert, B., & Roessner, U. (2021) · Molecular Omics · doi:10.1039/d1mo00196e · Cited by 46 · see citing works

Influence of sample preparation on lipidomics analysis of polar lipids in adipose tissue

López-Bascón, M. A., Calderón-Santiago, M., Sánchez-Ceinos, J., Fernández-Vega, A., Guzmán‐Ruiz, R., López‐Miranda, J., Malagón, M. M., & Priego‐Capote, F. (2017) · Talanta · doi:10.1016/j.talanta.2017.09.017 · Cited by 47 · see citing works

DGAT1 activity synchronises with mitophagy to protect cells from metabolic rewiring by iron depletion

Long, M., Sánchez-Martínez, Á., Longo, M., Suomi, F., Stenlund, H. C., Johansson, A. I., Ehsan, H., Salo, V. T., Montava‐Garriga, L., Naddafi, S., et al. (2022) · The EMBO Journal · doi:10.15252/embj.2021109390 · Cited by 46 · see citing works

Serum, plasma and erythrocyte membrane lipidomes in infants fed formula supplemented with bovine milk fat globule membranes

Grip, T., Dyrlund, T. S., Ahonen, L. L., Domellöf, M., Hernell, O., Hyötyläinen, T., Knip, M., Lönnerdal, B. L., Orešič, M., & Timby, N. (2018) · Pediatric Research · doi:10.1038/s41390-018-0130-9 · Cited by 46 · see citing works

Metabolome and fecal microbiota in monozygotic twin pairs discordant for weight: a Big Mac challenge

Bondia‐Pons, I., Maukonen, J., Mattila, I. M., Rissanen, A., Saarela, M., Kaprio, J. A., Hakkarainen, A., Lundbom, J., Lundbom, N. M. I., Hyötyläinen, T., et al. (2014) · The FASEB Journal · doi:10.1096/fj.14-250167 · Cited by 44 · see citing works

Integrated LC/MS-based lipidomics and transcriptomics analyses revealed lipid composition heterogeneity between pectoralis intramuscular fat and abdominal fat and its regulatory mechanism in chicken

Wang, D., Qin, P., Zhang, K., Wang, Y., Guo, Y., Cheng, Z., Li, Z., Tian, Y., Kang, X., Li, H., et al. (2023) · Food Research International · doi:10.1016/j.foodres.2023.113083 · Cited by 44 · see citing works

Analytical approaches for lipidomics and its potential applications in neuropsychiatric disorders

Sethi, S., Hayashi, M. A. F., Sussulini, A., Tasić, L., & Brietzke, E. M. (2015) · The World Journal of Biological Psychiatry · doi:10.3109/15622975.2015.1117656 · Cited by 44 · see citing works

The Gut Microbiota Modulates Glycaemic Control and Serum Metabolite Profiles in Non-Obese Diabetic Mice

Greiner, T. U., Hyötyläinen, T., Knip, M., Bäckhed, F., & Orešič, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0110359 · Cited by 43 · see citing works

Extending metabolome coverage for untargeted metabolite profiling of adherent cultured hepatic cells

García‐Cañaveras, J. C., López, S. A., Castell, J. V., Donato, M. T., & Lahoz, A. (2016) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-015-9227-8 · Cited by 43 · see citing works

Evaluation of Extraction Protocols for Simultaneous Polar and Non-Polar Yeast Metabolite Analysis Using Multivariate Projection Methods

Tambellini, N. P., Zaremberg, V., Turner, R. J., & Weljie, A. M. (2013) · Metabolites · doi:10.3390/metabo3030592 · Cited by 42 · see citing works

Changes in the Lipidomic Profile of Aqueous Humor in Open-Angle Glaucoma

Cabrerizo, J., Urcola, A., & Vecino, E. (2017) · Journal of Glaucoma · doi:10.1097/ijg.0000000000000603 · Cited by 42 · see citing works

Uncovering Structural Diversity of Unsaturated Fatty Acyls in Cholesteryl Esters via Photochemical Reaction and Tandem Mass Spectrometry

Ren, J., Franklin, E. T., & Xia, Y. (2017) · Journal of the American Society for Mass Spectrometry · doi:10.1007/s13361-017-1639-6 · Cited by 41 · see citing works

Comparative Nontargeted Profiling of Metabolic Changes in Tissues and Biofluids in High-Fat Diet-Fed Ossabaw Pig

Hanhineva, K., Barri, T., Kolehmainen, M., Pekkinen, J., Pihlajamäki, J., Vesterbacka, A., Solano-Aguilar, G. I., Mykkänen, H. M., Dragsted, L. O., Urban, J. F., et al. (2013) · Journal of Proteome Research · doi:10.1021/pr400257d · Cited by 40 · see citing works

Concentrations of Purine Metabolites Are Elevated in Fluids from Adults and Infants and in Livers from Mice Fed Diets Depleted of Bovine Milk Exosomes and their RNA Cargos

Aguilar-Lozano, A., Baier, S. R., Grove, R. A., Shu, J., Giraud, D., Leiferman, A., Mercer, K. E., Cui, J., Badger, T. M., Adamec, J., et al. (2018) · Journal of Nutrition · doi:10.1093/jn/nxy223 · Cited by 39 · see citing works

A Phospholipid Profile at 4 Months Predicts the Onset of Celiac Disease in at-Risk Infants

Auricchio, R., Galatola, M., Cielo, D., Amoresano, A., Caterino, M., Vita, E. D., Illiano, A., Troncone, R., Greco, L., & Ruoppolo, M. (2019) · Scientific Reports · doi:10.1038/s41598-019-50735-7 · Cited by 39 · see citing works

Serum metabolite profile associates with the development of metabolic co-morbidities in first-episode psychosis

Suvitaival, T., Mantere, O., Kieseppä, T., Mattila, I. M., Pöhö, P., Hyötyläinen, T., Suvisaari, J., & Orešič, M. (2016) · Translational Psychiatry · doi:10.1038/tp.2016.222 · Cited by 38 · see citing works

Berberine Could Ameliorate Cardiac Dysfunction via Interfering Myocardial Lipidomic Profiles in the Rat Model of Diabetic Cardiomyopathy

Dong, S., Zhang, S., Chen, Z., Zhang, R., Tian, L., Cheng, L., Shang, F., & Sun, J. (2018) · Frontiers in Physiology · doi:10.3389/fphys.2018.01042 · Cited by 37 · see citing works

Scoparone affects lipid metabolism in primary hepatocytes using lipidomics

Zhang, A., Qiu, S., Sun, H. J., Zhang, T., Guan, Y., Han, Y., Yan, G., & Wang, X. (2016) · Scientific Reports · doi:10.1038/srep28031 · Cited by 36 · see citing works

Optimization of metabolite extraction of human vein tissue for ultra performance liquid chromatography-mass spectrometry and nuclear magnetic resonance-based untargeted metabolic profiling

Anwar, M. A., Vorkas, P. A., Li, J. V., Shalhoub, J., Want, E. J., Davies, A. H., & Holmes, E. C. (2015) · The Analyst · doi:10.1039/c5an01041a · Cited by 35 · see citing works

Effects of a Lacto-Ovo-Vegetarian Diet on the Plasma Lipidome and Its Association with Atherosclerotic Burden in Patients with Coronary Artery Disease—A Randomized, Open-Label, Cross-over Study

Djekic, D., Shi, L. S., Calais, F., Carlsson, F., Landberg, R., Hyötyläinen, T., & Fröbert, O. (2020) · Nutrients · doi:10.3390/nu12113586 · Cited by 35 · see citing works

The Influence of Sample Collection Methodology and Sample Preprocessing on The Blood Metabolic Profile

Jørgenrud, B., Jäntti, S. E., Mattila, I. M., Pöhö, P., Rnningen, K. S., Yki‐Järvinen, H., Orešič, M., & Hyötyläinen, T. (2015) · Bioanalysis · doi:10.4155/bio.15.16 · Cited by 35 · see citing works

Combined extraction of acyl carnitines and 26:0 lysophosphatidylcholine from dried blood spots: Prospective newborn screening for X-linked adrenoleukodystrophy

Sandlers, Y., Moser, A. B., Hubbard, W. C., Kratz, L. E., Jones, R. O., & Raymond, G. V. (2012) · Molecular Genetics and Metabolism · doi:10.1016/j.ymgme.2011.11.195 · Cited by 38 · see citing works

NMR- and MS-based metabolomics: various organ responses following naphthalene intervention

Ling, Y. S., Liang, H., Chung, M.-H., Lin, M.-H., & Lin, C. (2014) · Molecular BioSystems · doi:10.1039/c4mb00090k · Cited by 33 · see citing works

Prepartal dietary energy alters transcriptional adaptations of the liver and subcutaneous adipose tissue of dairy cows during the transition period

Selim, S., Salin, S., Taponen, J., Vanhatalo, A., Kokkonen, T., & Elo, K. (2014) · Physiological Genomics · doi:10.1152/physiolgenomics.00115.2013 · Cited by 33 · see citing works

Modulation of saturation and chain length of fatty acids in Saccharomyces cerevisiae for production of cocoa butter‐like lipids

Bergenholm, D., Gossing, M., Wei, Y., Siewers, V., & Nielsen, J. (2018) · Biotechnology and Bioengineering · doi:10.1002/bit.26518 · Cited by 33 · see citing works

Ultraperformance convergence chromatography‐high resolution tandem mass spectrometry for lipid biomarker profiling and identification

Jones, J. W., Carter, C. L., Li, F., Yu, J., Pierzchalski, K., Jackson, I. L., Vujašković, Ž., & Kane, M. A. (2016) · Biomedical Chromatography · doi:10.1002/bmc.3822 · Cited by 32 · see citing works

Isoenergetic diets differing in their n‐3 fatty acid and polyphenol content reflect different plasma and HDL‐fraction lipidomic profiles in subjects at high cardiovascular risk

Bondia‐Pons, I., Pöhö, P., Bozzetto, L., Vetrani, C., Patti, L., Aura, A., Annuzzi, G., Hyötyläinen, T., Rivellese, A. A., & Orešič, M. (2014) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201400155 · Cited by 31 · see citing works

Quantitative modeling of human liver reveals dysregulation of glycosphingolipid pathways in nonalcoholic fatty liver disease

Sen, P., Govaere, O., Sinioja, T., McGlinchey, A., Geng, D., Ratziu, V., Bugianesi, E., Schattenberg, J. M., Vidal-Puig, A., Allison, M., et al. (2022) · iScience · doi:10.1016/j.isci.2022.104949 · Cited by 28 · see citing works

Triomics Analysis of Imatinib-Treated Myeloma Cells Connects Kinase Inhibition to RNA Processing and Decreased Lipid Biosynthesis

Breitkopf, S. B., Yuan, M., Helenius, K., Lyssiotis, C. A., & Asara, J. M. (2015) · Analytical Chemistry · doi:10.1021/acs.analchem.5b03040 · Cited by 27 · see citing works

Two‐dimensional LC‐MS/MS to enhance ceramide and phosphatidylcholine species profiling in mouse liver

Ling, Y. S., Liang, H., Lin, M.-H., Tang, C., Wu, K., Kuo, M., & Lin, C. (2014) · Biomedical Chromatography · doi:10.1002/bmc.3162 · Cited by 28 · see citing works

Exposure to per- and polyfluoroalkyl substances associates with an altered lipid composition of breast milk

Lamichhane, S., Siljander, H., Duberg, D., Honkanen, J. K., Virtanen, S. M., Orešič, M., Knip, M., & Hyötyläinen, T. (2021) · Environment International · doi:10.1016/j.envint.2021.106855 · Cited by 27 · see citing works

Lipidomic Analyses Reveal Modulation of Lipid Metabolism by the PFAS Perfluoroundecanoic Acid (PFUnDA) in Non-Obese Diabetic Mice

Hyötyläinen, T., Bodin, J., Duberg, D., Dirven, H. A. A. M., Nygaard, U. C., & Orešič, M. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.721507 · Cited by 27 · see citing works

Hyperosmolarity-induced lipid droplet formation depends on ceramide production by neutral sphingomyelinase 2

Robciuc, A., Hyötyläinen, T., Jauhiainen, M., & Holopainen, J. M. (2012) · Journal of Lipid Research · doi:10.1194/jlr.m026732 · Cited by 27 · see citing works

Insulin sensitivity depends on the route of glucose administration

Mingrone, G., Panunzi, S., Gaetano, A. D., Ahlin, S., Spuntarelli, V., Bondia‐Pons, I., Barbieri, C., Capristo, E., Gastaldelli, A., & Nolan, J. J. (2020) · Diabetologia · doi:10.1007/s00125-020-05157-w · Cited by 24 · see citing works

An Exercise Intervention to Unravel the Mechanisms Underlying Insulin Resistance in a Cohort of Black South African Women: Protocol for a Randomized Controlled Trial and Baseline Characteristics of Participants

Goedecke, J., Mendham, A., Clamp, L., Nankam, P. A. N., Smidt, M. F. F.-D., Phiri, L., Micklesfield, L., Keswell, D., Woudberg, N., Lecour, S., et al. (2018) · JMIR Research Protocols · doi:10.2196/resprot.9098 · Cited by 22 · see citing works

Novel methodologies in metabolic profiling with a focus on molecular diagnostic applications

Hyötyläinen, T. (2012) · Expert Review of Molecular Diagnostics · doi:10.1586/erm.12.33 · Cited by 26 · see citing works

Metabolomics in the Studies of Islet Autoimmunity and Type 1 Diabetes

Orešič, M. (2012) · The Review of Diabetic Studies · doi:10.1900/rds.2012.9.236 · Cited by 26 · see citing works

VEGF-B ablation in pancreatic β-cells upregulates insulin expression without affecting glucose homeostasis or islet lipid uptake

Ning, F. C., Jensen, N., Mi, J., Lindström, W., Bălan, M., Muhl, L., Eriksson, U., Nilsson, I., & Nyqvist, D. (2020) · Scientific Reports · doi:10.1038/s41598-020-57599-2 · Cited by 25 · see citing works

Quantitative genome-scale metabolic modeling of human CD4+ T cell differentiation reveals subset-specific regulation of glycosphingolipid pathways

Sen, P., Andrabi, S. B. A., Buchacher, T., Khan, M. M., Ullah, U., Lindeman, T., Alves, M. A., Hinkkanen, V., Kemppainen, E., Dickens, A. M., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109973 · Cited by 24 · see citing works

Reliability of LipidSearch software identification and its application to assess the effect of dry salting on the long-chain free fatty acid profile of tilapia muscles

Wu, T., Guo, H., Lu, Z., Zhang, T., Zhao, R., Tao, N., Wang, X., & Zhong, J. Q. (2020) · Food Research International · doi:10.1016/j.foodres.2020.109791 · Cited by 24 · see citing works

In-depth structural characterization of phospholipids by pairing solution photochemical reaction with charge inversion ion/ion chemistry

Franklin, E. T., Betancourt, S. K., Randolph, C. E., McLuckey, S. A., & Xia, Y. (2019) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-018-1537-1 · Cited by 22 · see citing works

The Metabolome in Finnish Carriers of the MYBPC3-Q1061X Mutation for Hypertrophic Cardiomyopathy

Jørgenrud, B., Jalanko, M., Heliö, T. M., Jääskeläinen, P., Laine, M., Hilvo, M., Nieminen, M. S., Laakso, M., Hyötyläinen, T., Orešič, M., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0134184 · Cited by 23 · see citing works

Overexpression of PPARγ Specifically in Pancreatic β-Cells Exacerbates Obesity-Induced Glucose Intolerance, Reduces β-Cell Mass, and Alters Islet Lipid Metabolism in Male Mice

Hogh, K. N., Craig, M. N., Uy, C. E., Nygrén, H., Asadi, A., Speck, M., Fraser, J. D., Rudecki, A. P., Baker, R. K., Orešič, M., et al. (2014) · Endocrinology · doi:10.1210/en.2014-1076 · Cited by 20 · see citing works

High-Dose Simvastatin Exhibits Enhanced Lipid-Lowering Effects Relative to Simvastatin/Ezetimibe Combination Therapy

Snowden, S. G., Grapov, D., Settergren, M., D’Alexandri, F. L., Haeggström, J. Z., Fiehn, O., Hyötyläinen, T., Pedersen, T. L., Newman, J. W. I., Orešič, M., et al. (2014) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.114.000606 · Cited by 19 · see citing works

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Lipid profile migration during the tilapia muscle steaming process revealed by a transactional analysis between MS data and lipidomics data

Sun, R., Wu, T., Guo, H., Xu, J., Chen, J., Tao, N., Wang, X., & Zhong, J. Q. (2021) · npj Science of Food · doi:10.1038/s41538-021-00115-1 · Cited by 18 · see citing works

Triboelectric Nanogenerator Ion Mobility–Mass Spectrometry for In-Depth Lipid Annotation

Bouza, M., Li, Y., Wang, A. C., Wang, Z. L., & Fernández, F. M. (2021) · Analytical Chemistry · doi:10.1021/acs.analchem.0c05145 · Cited by 18 · see citing works

Improved Peripheral and Hepatic Insulin Sensitivity after Lifestyle Interventions in Type 2 Diabetes Is Associated with Specific Metabolomic and Lipidomic Signatures in Skeletal Muscle and Plasma

Chorell, E., Otten, J., Stomby, A., Ryberg, M., Waling, M. U., Hauksson, J. B., Svensson, M., & Olsson, T. (2021) · Metabolites · doi:10.3390/metabo11120834 · Cited by 17 · see citing works

Circulating metabolic signatures of rapid and slow progression to type 1 diabetes in islet autoantibody-positive children

Lamichhane, S., Sen, P., Dickens, A. M., Kråkström, M., Ilonen, J., Lempainen, J., Hyöty, H., Lahesmaa, R., Veijola, R., Toppari, J., et al. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1211015 · Cited by 17 · see citing works

Label-Free SERS and MD Analysis of Biomarkers for Rapid Point-of-Care Sensors Detecting Head and Neck Cancer and Infections

Farnesi, E., Rinaldi, S., Liu, C., Ballmaier, J., Guntinas‐Lichius, O., Schmitt, M. P., Cialla‐May, D., & Popp, J. (2023) · Sensors · doi:10.3390/s23218915 · Cited by 17 · see citing works

Metabolomics in Alzheimer's disease research

Ibáñez, C., Simó, C., & Cifuentes, A. (2013) · Electrophoresis · doi:10.1002/elps.201200694 · Cited by 16 · see citing works

Changes in lipidomic profile of aqueous humour in Fuchs endothelial dystrophy

Cabrerizo, J., Urcola, A., Vecino, E., & Melles, G. R. J. (2017) · Acta Ophthalmologica · doi:10.1111/aos.13374 · Cited by 14 · see citing works

Exposure to persistent organic pollutants alters the serum metabolome in non-obese diabetic mice

Sinioja, T., Bodin, J., Duberg, D., Dirven, H. A. A. M., Berntsen, H. F., Zimmer, K. E., Nygaard, U. C., Orešič, M., & Hyötyläinen, T. (2022) · Metabolomics · doi:10.1007/s11306-022-01945-0 · Cited by 14 · see citing works

The role of lipids in corneal diseases and dystrophies: a systematic review

Rowsey, T. G., & Karamichos, D. (2017) · Clinical and Translational Medicine · doi:10.1186/s40169-017-0158-1 · Cited by 14 · see citing works

The DEXLIFE study methods: Identifying novel candidate biomarkers that predict progression to type 2 diabetes in high risk individuals

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Global Lipidomics Profiling by a High Resolution LC-MS Platform

Züllig, T., Trötzmüller, M., & Köfeler, H. C. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1410-5_3 · Cited by 6 · see citing works

Liquid Chromatography-Mass Spectrometry (LC-MS)-Based Analysis of Molecular Lipids in Algae Samples

Nygrén, H., Seppänen‐Laakso, T., & Rischer, H. (2017) · Methods in molecular biology · doi:10.1007/7651_2017_108 · Cited by 7 · see citing works

Bulk Untargeted LC-MS/MS Lipidomics v1Preprint

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High-Resolution Liquid Chromatography–Mass Spectrometry for Lipidomics

Harvey, F. C., Collao, V., & Bhattacharya, S. K. (2023) · Methods in molecular biology · doi:10.1007/978-1-0716-2966-6_4 · Cited by 8 · see citing works

Lipid Identification by Untargeted Tandem Mass Spectrometry Coupled with Ultra-High-Pressure Liquid Chromatography

Gugiu, G. B. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-6996-8_8 · Cited by 5 · see citing works