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3. Identification of biomarkers for glycaemic deterioration in type 2 diabetes

Author

Slieker, Roderick C., Donnelly, Louise A., Akalestou, Elina, Lopez-Noriega, Livia, Melhem, Rana, Güneş, Ayşim, Abou Azar, Frederic, Efanov, Alexander, Georgiadou, Eleni, Muniangi-Muhitu, Hermine, Sheikh, Mahsa, Giordano, Giuseppe N., Åkerlund, Mikael, Ahlqvist, Emma, Ali, Ashfaq, Banasik, Karina, Brunak, Søren, Barovic, Marko, Bouland, Gerard A., Burdet, Frédéric, Canouil, Mickaël, Dragan, Iulian, Elders, Petra J. M., Fernandez, Celine, Festa, Andreas, Fitipaldi, Hugo, Froguel, Phillippe, Gudmundsdottir, Valborg, Gudnason, Vilmundur, Gerl, Mathias J., van der Heijden, Amber A., Jennings, Lori L., Hansen, Michael K., Kim, Min, Leclerc, Isabelle, Klose, Christian, Kuznetsov, Dmitry, Mansour Aly, Dina, Mehl, Florence, Marek, Diana, Melander, Olle, Niknejad, Anne, Ottosson, Filip, Pavo, Imre, Duffin, Kevin, Syed, Samreen K., Shaw, Janice L., Cabrera, Over, Pullen, Timothy J., Simons, Kai, Solimena, Michele, Suvitaival, Tommi, Wretlind, Asger, Rossing, Peter, Lyssenko, Valeriya, Legido Quigley, Cristina, Groop, Leif, Thorens, Bernard, Franks, Paul W., Lim, Gareth E., Estall, Jennifer, Ibberson, Mark, Beulens, Joline W. J., ’t Hart, Leen M, Pearson, Ewan R., and Rutter, Guy A.

Published
2023
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4. Cholesteryl hemiazelate identified in CVD patients causes in vitro and in vivo inflammation

Author

Domingues, Neuza, Gaifem, Joana, Matthiesen, Rune, Saraiva, Diana P., Bento, Luís, Marques, André R.A., Soares, Maria I.L., Sampaio, Julio, Klose, Christian, Surma, Michal A., Almeida, Manuel S., Rodrigues, Gustavo, Gonçalves, Pedro Araújo, Ferreira, Jorge, e Melo, Ryan Gouveia, Pedro, Luís Mendes, Simons, Kai, Pinho e Melo, Teresa M.V.D., Cabral, M. Guadalupe, Jacinto, Antonio, Silvestre, Ricardo, Vaz, Winchil, and Vieira, Otília V.

Published
2023
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5. Genetic architecture of human plasma lipidome and its link to cardiovascular disease.

Author

Tabassum, Rubina, Rämö, Joel T, Ripatti, Pietari, Koskela, Jukka T, Kurki, Mitja, Karjalainen, Juha, Palta, Priit, Hassan, Shabbeer, Nunez-Fontarnau, Javier, Kiiskinen, Tuomo TJ, Söderlund, Sanni, Matikainen, Niina, Gerl, Mathias J, Surma, Michal A, Klose, Christian, Stitziel, Nathan O, Laivuori, Hannele, Havulinna, Aki S, Service, Susan K, Salomaa, Veikko, Pirinen, Matti, FinnGen Project, Jauhiainen, Matti, Daly, Mark J, Freimer, Nelson B, Palotie, Aarno, Taskinen, Marja-Riitta, Simons, Kai, and Ripatti, Samuli

Subjects
FinnGen Project, Plasma, Humans, Cardiovascular Diseases, Lipids, Genome-Wide Association Study, Lipidomics
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

Published
2019

6. Coronary Artery Disease Risk and Lipidomic Profiles Are Similar in Hyperlipidemias With Family History and Population‐Ascertained Hyperlipidemias

Author

Rämö, Joel T, Ripatti, Pietari, Tabassum, Rubina, Söderlund, Sanni, Matikainen, Niina, Gerl, Mathias J, Klose, Christian, Surma, Michal A, Stitziel, Nathan O, Havulinna, Aki S, Pirinen, Matti, Salomaa, Veikko, Freimer, Nelson B, Jauhiainen, Matti, Palotie, Aarno, Taskinen, Marja‐Riitta, Simons, Kai, and Ripatti, Samuli

Subjects
Atherosclerosis, Digestive Diseases, Heart Disease, Cardiovascular, Aetiology, 2.1 Biological and endogenous factors, Adult, Cholesterol, LDL, Coronary Artery Disease, Family, Female, Finland, Humans, Hypercholesterolemia, Hyperlipidemias, Hypertriglyceridemia, Lipidomics, Male, Medical History Taking, Middle Aged, Proportional Hazards Models, Triglycerides, coronary artery disease, family study, high-risk populations, hypercholesterolemia, hypertriglyceridemia, lipids and lipoproteins, high‐risk populations, Cardiorespiratory Medicine and Haematology
Abstract

Background We asked whether, after excluding familial hypercholesterolemia, individuals with high low-density lipoprotein cholesterol ( LDL -C) or triacylglyceride levels and a family history of the same hyperlipidemia have greater coronary artery disease risk or different lipidomic profiles compared with population-based hyperlipidemias. Methods and Results We determined incident coronary artery disease risk for 755 members of 66 hyperlipidemic families (≥2 first-degree relatives with similar hyperlipidemia) and 19 644 Finnish FINRISK population study participants. We quantified 151 circulating lipid species from 550 members of 73 hyperlipidemic families and 897 FINRISK participants using mass spectrometric shotgun lipidomics. Familial hypercholesterolemia was excluded using functional LDL receptor testing and genotyping. Hyperlipidemias ( LDL -C or triacylglycerides >90th population percentile) associated with increased coronary artery disease risk in meta-analysis of the hyperlipidemic families and the population cohort (high LDL -C: hazard ratio, 1.74 [95% CI, 1.48-2.04]; high triacylglycerides: hazard ratio, 1.38 [95% CI, 1.09-1.74]). Risk estimates were similar in the family and population cohorts also after adjusting for lipid-lowering medication. In lipidomic profiling, high LDL -C associated with 108 lipid species, and high triacylglycerides associated with 131 lipid species in either cohort (at 5% false discovery rate; P-value range 0.038-2.3×10-56). Lipidomic profiles were highly similar for hyperlipidemic individuals in the families and the population ( LDL -C: r=0.80; triacylglycerides: r=0.96; no lipid species deviated between the cohorts). Conclusions Hyperlipidemias with family history conferred similar coronary artery disease risk as population-based hyperlipidemias. We identified distinct lipidomic profiles associated with high LDL -C and triacylglycerides. Lipidomic profiles were similar between hyperlipidemias with family history and population-ascertained hyperlipidemias, providing evidence of similar and overlapping underlying mechanisms.

Published
2019

10. Lipidomic approach for stratification of Acute Myeloid Leukemia patients

Author

Thiede, Christian, Ehninger, Gerhard, Simons, Kai, Grzybek, Michal, and Stefanko, Adam

Subjects
Quantitative Biology - Tissues and Organs, Quantitative Biology - Biomolecules, Quantitative Biology - Cell Behavior, Quantitative Biology - Molecular Networks
Abstract

The pathogenesis and progression of many tumors, including hematologic malignancies is highly dependent on enhanced lipogenesis. De novo fatty-acid synthesis permits accelerated proliferation of tumor cells by providing structural components to build the membranes. It may also lead to alterations of physicochemical properties of the formed membranes, which can have an impact on signaling or even increase resistance to drugs in cancer cells. Cancer type-specific lipid profiles would allow understanding the actual effects of lipid changes and therefore could potentially serve as fingerprints for individual tumors and be explored as diagnostic markers. We have used shotgun MS approach to identify lipid patterns in different types of acute myeloid leukemia (AML) patients that either show no karyotype changes or belong to t(8;21) or inv16 types. The observed differences in lipidomes of t(8;21) and inv(16) patients, as compared to AML patients without karyotype changes, concentrate mostly on substantial modulation of ceramides/sphingolipids synthesis. Also significant changes in the physicochemical properties of the membranes, between the t(8;21) and the other patients, were noted that were related to a marked alteration in the saturation levels of lipids. The revealed differences in lipid profiles of various AML types increase our understanding of the affected biochemical pathways and can potentially serve as diagnostic tools., Comment: 20 pages, 3 figures, 1 table

Published
2016

11. Shotgun mass spectrometry-based lipid profiling identifies and distinguishes between chronic inflammatory diseases

Author

Matthiesen, Rune, Lauber, Chris, Sampaio, Julio L., Domingues, Neuza, Alves, Liliana, Gerl, Mathias J., Almeida, Manuel S., Rodrigues, Gustavo, Araújo Gonçalves, Pedro, Ferreira, Jorge, Borbinha, Cláudia, Pedro Marto, João, Neves, Marisa, Batista, Frederico, Viana-Baptista, Miguel, Alves, Jose, Simons, Kai, Vaz, Winchil L.C., and Vieira, Otilia V.

Published
2021
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12. Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study

Author

Slieker, Roderick C., Donnelly, Louise A., Fitipaldi, Hugo, Bouland, Gerard A., Giordano, Giuseppe N., Åkerlund, Mikael, Gerl, Mathias J., Ahlqvist, Emma, Ali, Ashfaq, Dragan, Iulian, Festa, Andreas, Hansen, Michael K., Mansour Aly, Dina, Kim, Min, Kuznetsov, Dmitry, Mehl, Florence, Klose, Christian, Simons, Kai, Pavo, Imre, Pullen, Timothy J., Suvitaival, Tommi, Wretlind, Asger, Rossing, Peter, Lyssenko, Valeriya, Legido-Quigley, Cristina, Groop, Leif, Thorens, Bernard, Franks, Paul W., Ibberson, Mark, Rutter, Guy A., Beulens, Joline W. J., ‘t Hart, Leen M., and Pearson, Ewan R.

Published
2021
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13. Polygenic scores for complex traits are associated with changes in concentration of circulating lipid species.

Author

Tabassum, Rubina, Mars, Nina, Parolo, Pietro Della Briotta, Gerl, Mathias J., Klose, Christian, Pirinen, Matti, Simons, Kai, Widén, Elisabeth, and Ripatti, Samuli

Subjects
BLOOD lipids, TYPE 2 diabetes, THROMBOEMBOLISM, BODY mass index, ARACHIDONIC acid
Abstract

Understanding perturbations in circulating lipid levels that often occur years or decades before clinical symptoms may enhance our understanding of disease mechanisms and provide novel intervention opportunities. Here, we assessed if polygenic scores (PGSs) for complex traits could detect lipid dysfunctions related to the traits and provide new biological insights. We constructed genome-wide PGSs (approximately 1 million genetic variants) for 50 complex traits in 7,169 Finnish individuals with routine clinical lipid profiles and lipidomics measurements (179 lipid species). We identified 678 associations (P < 9.0 × 10−5) involving 26 traits and 142 lipids. Most of these associations were also validated with the actual phenotype measurements where available (89.5% of 181 associations where the trait was available), suggesting that these associations represent early signs of physiological changes of the traits. We detected many known relationships (e.g., PGS for body mass index (BMI) and lysophospholipids, PGS for type 2 diabetes and triacyglycerols) and those that suggested potential target for prevention strategies (e.g., PGS for venous thromboembolism and arachidonic acid). We also found association of PGS for favorable adiposity with increased sphingomyelins levels, suggesting a probable role of sphingomyelins in increased risk for certain disease, e.g., venous thromboembolism as reported previously, in favorable adiposity despite its favorable metabolic effect. Altogether, our study provides a comprehensive characterization of lipidomic alterations in genetic predisposition for a wide range of complex traits. The study also demonstrates potential of PGSs for complex traits to capture early, presymptomatic lipid alterations, highlighting its utility in understanding disease mechanisms and early disease detection. Could changes in levels of circulating lipid species be predictive of disease? This study reveals that polygenic scores for a range of complex traits are associated with changes in concentration of circulating lipid species. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Multi-omics subgroups associated with glycaemic deterioration in type 2 diabetes: an IMI-RHAPSODY Study

Author

Li, Shiying, primary, Dragan, Iulian, additional, Tran, Van Du T., additional, Fung, Chun Ho, additional, Kuznetsov, Dmitry, additional, Hansen, Michael K., additional, Beulens, Joline W. J., additional, Hart, Leen M. ‘t, additional, Slieker, Roderick C., additional, Donnelly, Louise A., additional, Gerl, Mathias J., additional, Klose, Christian, additional, Mehl, Florence, additional, Simons, Kai, additional, Elders, Petra J. M., additional, Pearson, Ewan R., additional, Rutter, Guy A., additional, and Ibberson, Mark, additional

Published
2024
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16. Integrative analysis of prognostic biomarkers derived from multiomics panels helps discrimination of chronic kidney disease trajectories in people with type 2 diabetes

Author

Kammer, Michael, Heinzel, Andreas, Willency, Jill A., Duffin, Kevin L., Mayer, Gert, Simons, Kai, Gerl, Mathias J., Klose, Christian, Heinze, Georg, Reindl-Schwaighofer, Roman, Hu, Karin, Perco, Paul, Eder, Susanne, Rosivall, Laszlo, Mark, Patrick B., Ju, Wenjun, Kretzler, Matthias, McCarthy, Mark I., Heerspink, Hiddo L., Wiecek, Andrzej, Gomez, Maria F., and Oberbauer, Rainer

Published
2019
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18. A Lipid E-MAP Identifies Ubx2 as a Critical Regulator of Lipid Saturation and Lipid Bilayer Stress

Author

Surma, Michal A, Klose, Christian, Peng, Debby, Shales, Michael, Mrejen, Caroline, Stefanko, Adam, Braberg, Hannes, Gordon, David E, Vorkel, Daniela, Ejsing, Christer S, Farese, Robert, Simons, Kai, Krogan, Nevan J, and Ernst, Robert

Subjects
Biochemistry and Cell Biology, Biological Sciences, Nutrition, 1.1 Normal biological development and functioning, Underpinning research, Generic health relevance, Blotting, Western, Carrier Proteins, Cell Membrane, Cells, Cultured, Computational Biology, Epistasis, Genetic, Fatty Acid Desaturases, Flow Cytometry, Homeostasis, Immunoprecipitation, Lipid Bilayers, Lipid Metabolism, Membrane Lipids, Oligonucleotide Array Sequence Analysis, Phosphatidylcholines, Protein Interaction Mapping, Protein Transport, Saccharomyces cerevisiae, Saccharomyces cerevisiae Proteins, Stearoyl-CoA Desaturase, Medical and Health Sciences, Developmental Biology, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Biological membranes are complex, and the mechanisms underlying their homeostasis are incompletely understood. Here, we present a quantitative genetic interaction map (E-MAP) focused on various aspects of lipid biology, including lipid metabolism, sorting, and trafficking. This E-MAP contains ∼250,000 negative and positive genetic interaction scores and identifies a molecular crosstalk of protein quality control pathways with lipid bilayer homeostasis. Ubx2p, a component of the endoplasmic-reticulum-associated degradation pathway, surfaces as a key upstream regulator of the essential fatty acid (FA) desaturase Ole1p. Loss of Ubx2p affects the transcriptional control of OLE1, resulting in impaired FA desaturation and a severe shift toward more saturated membrane lipids. Both the induction of the unfolded protein response and aberrant nuclear membrane morphologies observed in cells lacking UBX2 are suppressed by the supplementation of unsaturated FAs. Our results point toward the existence of dedicated bilayer stress responses for membrane homeostasis.

Published
2013

19. Modulation of Myelopoiesis Progenitors Is an Integral Component of Trained Immunity

Author

Mitroulis, Ioannis, Ruppova, Klara, Wang, Baomei, Chen, Lan-Sun, Grzybek, Michal, Grinenko, Tatyana, Eugster, Anne, Troullinaki, Maria, Palladini, Alessandra, Kourtzelis, Ioannis, Chatzigeorgiou, Antonios, Schlitzer, Andreas, Beyer, Marc, Joosten, Leo A.B., Isermann, Berend, Lesche, Mathias, Petzold, Andreas, Simons, Kai, Henry, Ian, Dahl, Andreas, Schultze, Joachim L., Wielockx, Ben, Zamboni, Nicola, Mirtschink, Peter, Coskun, Ünal, Hajishengallis, George, Netea, Mihai G., and Chavakis, Triantafyllos

Published
2018
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24. Raft Lipids as Common Components of Human Extracellular Amyloid Fibrils

Author

Gellermann, Gerald P., Appel, Thomas R., Tannert, Astrid, Radestock, Anja, Hortschansky, Peter, Schroeckh, Volker, Leisner, Christian, Lütkepohl, Tim, Shtrasburg, Shmuel, Röcken, Christoph, Pras, Mordechai, Linke, Reinhold P., Diekmann, Stephan, Fändrich, Marcus, and Simons, Kai

Published
2005

29. Orm family proteins mediate sphingolipid homeostasis.

Author

Breslow, David K, Collins, Sean R, Bodenmiller, Bernd, Aebersold, Ruedi, Simons, Kai, Shevchenko, Andrej, Ejsing, Christer S, and Weissman, Jonathan S

Subjects
Cell Line, Hela Cells, Humans, Saccharomyces cerevisiae, Asthma, Multiprotein Complexes, Phosphoric Monoester Hydrolases, Fatty Acids, Monounsaturated, Sphingolipids, Saccharomyces cerevisiae Proteins, Amino Acid Sequence, Conserved Sequence, Protein Binding, Phosphorylation, Homeostasis, Multigene Family, Molecular Sequence Data, Serine C-Palmitoyltransferase, HeLa Cells, Fatty Acids, Monounsaturated, General Science & Technology
Abstract

Despite the essential roles of sphingolipids both as structural components of membranes and critical signalling molecules, we have a limited understanding of how cells sense and regulate their levels. Here we reveal the function in sphingolipid metabolism of the ORM genes (known as ORMDL genes in humans)-a conserved gene family that includes ORMDL3, which has recently been identified as a potential risk factor for childhood asthma. Starting from an unbiased functional genomic approach in Saccharomyces cerevisiae, we identify Orm proteins as negative regulators of sphingolipid synthesis that form a conserved complex with serine palmitoyltransferase, the first and rate-limiting enzyme in sphingolipid production. We also define a regulatory pathway in which phosphorylation of Orm proteins relieves their inhibitory activity when sphingolipid production is disrupted. Changes in ORM gene expression or mutations to their phosphorylation sites cause dysregulation of sphingolipid metabolism. Our work identifies the Orm proteins as critical mediators of sphingolipid homeostasis and raises the possibility that sphingolipid misregulation contributes to the development of childhood asthma.

Published
2010

40. Multi-omics subgroups associated with glycaemic deterioration in type 2 diabetes: an IMI-RHAPSODY Study.

Author

Shiying Li, Dragan, Iulian, Tran, Van Du T., Chun Ho Fung, Kuznetsov, Dmitry, Hansen, Michael K., Beulens, Joline W. J., t Hart, Leen M., Slieker, Roderick C., Donnelly, Louise A., Gerl, Mathias J., Klose, Christian, Mehl, Florence, Simons, Kai, Elders, Petra J. M., Pearson, Ewan R., Rutter, Guy A., and Ibberson, Mark

Subjects
TYPE 2 diabetes, MULTIOMICS, INTERLEUKIN receptors, BLOOD lipids, INSULIN, INSULIN sensitivity, INSULIN aspart
Abstract

Introduction: Type 2 diabetes (T2D) onset, progression and outcomes differ substantially between individuals. Multi-omics analyses may allow a deeper understanding of these differences and ultimately facilitate personalised treatments. Here, in an unsupervised "bottom-up" approach, we attempt to group T2D patients based solely on -omics data generated from plasma. Methods: Circulating plasma lipidomic and proteomic data from two independent clinical cohorts, Hoorn Diabetes Care System (DCS) and Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS), were analysed using Similarity Network Fusion. The resulting patient network was analysed with Logistic and Cox regression modelling to explore relationships between plasma -omic profiles and clinical characteristics. Results: From a total of 1,134 subjects in the two cohorts, levels of 180 circulating plasma lipids and 1195 proteins were used to separate patients into two subgroups. These differed in terms of glycaemic deterioration (Hazard Ratio=0.56;0.73), insulin sensitivity and secretion (C-peptide, p=3.7e-11;2.5e-06, DCS and GoDARTS, respectively; Homeostatic model assessment 2 (HOMA2)-B; -IR; -S, p=0.0008;4.2e-11;1.1e-09, only in DCS). The main molecular signatures separating the two groups included triacylglycerols, sphingomyelin, testican-1 and interleukin 18 receptor. Conclusions: Using an unsupervised network-based fusion method on plasma lipidomics and proteomics data from two independent cohorts, we were able to identify two subgroups of T2D patients differing in terms of disease severity. The molecular signatures identified within these subgroups provide insights into disease mechanisms and possibly new prognostic markers for T2D. [ABSTRACT FROM AUTHOR]

Published
2024
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