159 results on '"Hansen, Tue H."'
Search Results
2. Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits
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Brown, Andrew A., Fernandez-Tajes, Juan J., Hong, Mun-gwan, Brorsson, Caroline A., Koivula, Robert W., Davtian, David, Dupuis, Théo, Sartori, Ambra, Michalettou, Theodora-Dafni, Forgie, Ian M., Adam, Jonathan, Allin, Kristine H., Caiazzo, Robert, Cederberg, Henna, De Masi, Federico, Elders, Petra J. M., Giordano, Giuseppe N., Haid, Mark, Hansen, Torben, Hansen, Tue H., Hattersley, Andrew T., Heggie, Alison J., Howald, Cédric, Jones, Angus G., Kokkola, Tarja, Laakso, Markku, Mahajan, Anubha, Mari, Andrea, McDonald, Timothy J., McEvoy, Donna, Mourby, Miranda, Musholt, Petra B., Nilsson, Birgitte, Pattou, Francois, Penet, Deborah, Raverdy, Violeta, Ridderstråle, Martin, Romano, Luciana, Rutters, Femke, Sharma, Sapna, Teare, Harriet, ‘t Hart, Leen, Tsirigos, Konstantinos D., Vangipurapu, Jagadish, Vestergaard, Henrik, Brunak, Søren, Franks, Paul W., Frost, Gary, Grallert, Harald, Jablonka, Bernd, McCarthy, Mark I., Pavo, Imre, Pedersen, Oluf, Ruetten, Hartmut, Walker, Mark, Adamski, Jerzy, Schwenk, Jochen M., Pearson, Ewan R., Dermitzakis, Emmanouil T., and Viñuela, Ana
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- 2023
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3. The gut microbiota in multiple sclerosis varies with disease activity
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Thirion, Florence, Sellebjerg, Finn, Fan, Yong, Lyu, Liwei, Hansen, Tue H., Pons, Nicolas, Levenez, Florence, Quinquis, Benoit, Stankevic, Evelina, Søndergaard, Helle B., Dantoft, Thomas M., Poulsen, Casper S., Forslund, Sofia K., Vestergaard, Henrik, Hansen, Torben, Brix, Susanne, Oturai, Annette, Sørensen, Per Soelberg, Ehrlich, Stanislav D., and Pedersen, Oluf
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- 2023
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4. Large-scale association analyses identify host factors influencing human gut microbiome composition
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Kurilshikov, Alexander, Medina-Gomez, Carolina, Bacigalupe, Rodrigo, Radjabzadeh, Djawad, Wang, Jun, Demirkan, Ayse, Le Roy, Caroline I, Raygoza Garay, Juan Antonio, Finnicum, Casey T, Liu, Xingrong, Zhernakova, Daria V, Bonder, Marc Jan, Hansen, Tue H, Frost, Fabian, Rühlemann, Malte C, Turpin, Williams, Moon, Jee-Young, Kim, Han-Na, Lüll, Kreete, Barkan, Elad, Shah, Shiraz A, Fornage, Myriam, Szopinska-Tokov, Joanna, Wallen, Zachary D, Borisevich, Dmitrii, Agreus, Lars, Andreasson, Anna, Bang, Corinna, Bedrani, Larbi, Bell, Jordana T, Bisgaard, Hans, Boehnke, Michael, Boomsma, Dorret I, Burk, Robert D, Claringbould, Annique, Croitoru, Kenneth, Davies, Gareth E, van Duijn, Cornelia M, Duijts, Liesbeth, Falony, Gwen, Fu, Jingyuan, van der Graaf, Adriaan, Hansen, Torben, Homuth, Georg, Hughes, David A, Ijzerman, Richard G, Jackson, Matthew A, Jaddoe, Vincent WV, Joossens, Marie, Jørgensen, Torben, Keszthelyi, Daniel, Knight, Rob, Laakso, Markku, Laudes, Matthias, Launer, Lenore J, Lieb, Wolfgang, Lusis, Aldons J, Masclee, Ad AM, Moll, Henriette A, Mujagic, Zlatan, Qibin, Qi, Rothschild, Daphna, Shin, Hocheol, Sørensen, Søren J, Steves, Claire J, Thorsen, Jonathan, Timpson, Nicholas J, Tito, Raul Y, Vieira-Silva, Sara, Völker, Uwe, Völzke, Henry, Võsa, Urmo, Wade, Kaitlin H, Walter, Susanna, Watanabe, Kyoko, Weiss, Stefan, Weiss, Frank U, Weissbrod, Omer, Westra, Harm-Jan, Willemsen, Gonneke, Payami, Haydeh, Jonkers, Daisy MAE, Arias Vasquez, Alejandro, de Geus, Eco JC, Meyer, Katie A, Stokholm, Jakob, Segal, Eran, Org, Elin, Wijmenga, Cisca, Kim, Hyung-Lae, Kaplan, Robert C, Spector, Tim D, Uitterlinden, Andre G, Rivadeneira, Fernando, Franke, Andre, Lerch, Markus M, Franke, Lude, Sanna, Serena, D’Amato, Mauro, and Pedersen, Oluf
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Microbiology ,Biological Sciences ,Genetics ,Human Genome ,Biotechnology ,Clinical Research ,Digestive Diseases ,Nutrition ,2.1 Biological and endogenous factors ,Aetiology ,Oral and gastrointestinal ,Adolescent ,Adult ,Bifidobacterium ,Child ,Child ,Preschool ,Cohort Studies ,Female ,Gastrointestinal Microbiome ,Genetic Variation ,Genome-Wide Association Study ,Humans ,Lactase ,Linkage Disequilibrium ,Male ,Mendelian Randomization Analysis ,Metabolism ,Quantitative Trait Loci ,RNA ,Ribosomal ,16S ,Medical and Health Sciences ,Developmental Biology ,Agricultural biotechnology ,Bioinformatics and computational biology - Abstract
To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 of 410 genera were detected in more than 95% of samples. A genome-wide association study of host genetic variation regarding microbial taxa identified 31 loci affecting the microbiome at a genome-wide significant (P
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- 2021
5. Microbially Produced Imidazole Propionate Is Associated With Heart Failure and Mortality
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Alves, Renato, Amouyal, Chloe, Andersson Galijatovic, Ehm Astrid, Andreelli, Fabrizio, Barthelemy, Olivier, Bastard, Jean-Philippe, Batisse, Jean-Paul, Berland, Magalie, Bittar, Randa, Blüher, Matthias, Bork, Peer, Bourron, Olivier, Camus, Mickael, Cassuto, Dominique, Ciangura, Cecile, Coelho, Luis Pedro, Collet, Jean-Philippe, Dumas, Marc-Emmanuel, Ehrlich, S. Dusko, Engelbrechtsen, Line, Fezeu, Leopold, Forslund, Sofia, Fromentin, Sebastien, Galan, Pilar, Giral, Philippe, Gøtze, Jens Peter, Hansen, Torben, Hansen, Tue H., Hartemann, Agnes, Hartmann, Bolette, Hercberg, Serge, Holmes, Bridget, Holst, Jens Juul, Hornbak, Malene, Hoyles, Lesley, Hulot, Jean-Sebastien, Jaqueminet, Sophie, Kerneis, Mathieu, Khemis, Jean, Kozlowski, Ruby, Pedersen, Helle Krogh, Kuhn, Michael, Mannerås-Holm, Louise, Marko, Lajos, Martinez-Gili Robin Massey, Laura, Maziers, Nicolas, Medina-Stamminger, Jonathan, Moitinho-Silva, Lucas, Montalescot, Gilles, Moutel, Sandrine, Neves, Ana Luisa, Olanipekun, Michael, Oppert, Jean-Michel, Poitou, Christine, Pousset, Francoise, Pouzoulet, Laurence, Rouault, Christine, Silvain, Johanne, Vestergaard, Henrik, Molinaro, Antonio, Nemet, Ina, Bel Lassen, Pierre, Chakaroun, Rima, Nielsen, Trine, Aron-Wisnewsky, Judith, Bergh, Per-Olof, Li, Lin, Henricsson, Marcus, Køber, Lars, Isnard, Richard, Helft, Gerard, Stumvoll, Michael, Pedersen, Oluf, Smith, J. Gustav, Tang, W.H. Wilson, Clément, Karine, Hazen, Stanley L., and Bäckhed, Fredrik
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- 2023
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6. Microbiome and metabolome features of the cardiometabolic disease spectrum
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Fromentin, Sebastien, Forslund, Sofia K., Chechi, Kanta, Aron-Wisnewsky, Judith, Chakaroun, Rima, Nielsen, Trine, Tremaroli, Valentina, Ji, Boyang, Prifti, Edi, Myridakis, Antonis, Chilloux, Julien, Andrikopoulos, Petros, Fan, Yong, Olanipekun, Michael T., Alves, Renato, Adiouch, Solia, Bar, Noam, Talmor-Barkan, Yeela, Belda, Eugeni, Caesar, Robert, Coelho, Luis Pedro, Falony, Gwen, Fellahi, Soraya, Galan, Pilar, Galleron, Nathalie, Helft, Gerard, Hoyles, Lesley, Isnard, Richard, Le Chatelier, Emmanuelle, Julienne, Hanna, Olsson, Lisa, Pedersen, Helle Krogh, Pons, Nicolas, Quinquis, Benoit, Rouault, Christine, Roume, Hugo, Salem, Joe-Elie, Schmidt, Thomas S. B., Vieira-Silva, Sara, Li, Peishun, Zimmermann-Kogadeeva, Maria, Lewinter, Christian, Søndertoft, Nadja B., Hansen, Tue H., Gauguier, Dominique, Gøtze, Jens Peter, Køber, Lars, Kornowski, Ran, Vestergaard, Henrik, Hansen, Torben, Zucker, Jean-Daniel, Hercberg, Serge, Letunic, Ivica, Bäckhed, Fredrik, Oppert, Jean-Michel, Nielsen, Jens, Raes, Jeroen, Bork, Peer, Stumvoll, Michael, Segal, Eran, Clément, Karine, Dumas, Marc-Emmanuel, Ehrlich, S. Dusko, and Pedersen, Oluf
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- 2022
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7. Combinatorial, additive and dose-dependent drug–microbiome associations
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Forslund, Sofia K., Chakaroun, Rima, Zimmermann-Kogadeeva, Maria, Markó, Lajos, Aron-Wisnewsky, Judith, Nielsen, Trine, Moitinho-Silva, Lucas, Schmidt, Thomas S. B., Falony, Gwen, Vieira-Silva, Sara, Adriouch, Solia, Alves, Renato J., Assmann, Karen, Bastard, Jean-Philippe, Birkner, Till, Caesar, Robert, Chilloux, Julien, Coelho, Luis Pedro, Fezeu, Leopold, Galleron, Nathalie, Helft, Gerard, Isnard, Richard, Ji, Boyang, Kuhn, Michael, Le Chatelier, Emmanuelle, Myridakis, Antonis, Olsson, Lisa, Pons, Nicolas, Prifti, Edi, Quinquis, Benoit, Roume, Hugo, Salem, Joe-Elie, Sokolovska, Nataliya, Tremaroli, Valentina, Valles-Colomer, Mireia, Lewinter, Christian, Søndertoft, Nadja B., Pedersen, Helle Krogh, Hansen, Tue H., Gøtze, Jens Peter, Køber, Lars, Vestergaard, Henrik, Hansen, Torben, Zucker, Jean-Daniel, Hercberg, Serge, Oppert, Jean-Michel, Letunic, Ivica, Nielsen, Jens, Bäckhed, Fredrik, Ehrlich, S. Dusko, Dumas, Marc-Emmanuel, Raes, Jeroen, Pedersen, Oluf, Clément, Karine, Stumvoll, Michael, and Bork, Peer
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- 2021
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8. The Association of Cardiometabolic, Diet and Lifestyle Parameters With Plasma Glucagon-like Peptide-1: An IMI DIRECT Study
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Eriksen, Rebeca, White, Margaret C, Dawed, Adem Y, Perez, Isabel Garcia, Posma, Joram M, Haid, Mark, Sharma, Sapna, Prehn, Cornelia, Thomas, E Louise, Koivula, Robert W, Bizzotto, Roberto, Mari, Andrea, Giordano, Giuseppe N, Pavo, Imre, Schwenk, Jochen M, De Masi, Federico, Tsirigos, Konstantinos D, Brunak, Søren, Viñuela, Ana, Mahajan, Anubha, McDonald, Timothy J, Kokkola, Tarja, Rutters, Femke, Beulens, Joline, Muilwijk, Mirthe, Blom, Marieke, Elders, Petra, Hansen, Tue H, Fernandez-Tajes, Juan, Jones, Angus, Jennison, Chris, Walker, Mark, McCarthy, Mark I, Pedersen, Oluf, Ruetten, Hartmut, Forgie, Ian, Holst, Jens J, Thomsen, Henrik S, Ridderstråle, Martin, Bell, Jimmy D, Adamski, Jerzy, Franks, Paul W, Hansen, Torben, Holmes, Elaine, Frost, Gary, and Pearson, Ewan R
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- 2024
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9. Gut microbiota profile and selected plasma metabolites in type 1 diabetes without and with stratification by albuminuria
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Winther, Signe A., Henriksen, Peter, Vogt, Josef K., Hansen, Tue H., Ahonen, Linda, Suvitaival, Tommi, Hein Zobel, Emilie, Frimodt-Møller, Marie, Hansen, Tine W., Hansen, Torben, Parving, Hans-Henrik, Legido-Quigley, Cristina, Rossing, Peter, and Pedersen, Oluf
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- 2020
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10. Conjugated C-6 hydroxylated bile acids in serum relate to human metabolic health and gut Clostridia species
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Petersen, Anders Ø, Julienne, Hanna, Hyötyläinen, Tuulia, Sen, Partho, Fan, Yong, Pedersen, Helle Krogh, Jäntti, Sirkku, Hansen, Tue H., Nielsen, Trine, Jørgensen, Torben, Hansen, Torben, Myers, Pernille Neve, Nielsen, H. Bjørn, Ehrlich, S. Dusko, Orešič, Matej, and Pedersen, Oluf
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- 2021
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11. Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: descriptive characteristics of the epidemiological studies within the IMI DIRECT Consortium
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Koivula, Robert W., Forgie, Ian M., Kurbasic, Azra, Viñuela, Ana, Heggie, Alison, Giordano, Giuseppe N., Hansen, Tue H., Hudson, Michelle, Koopman, Anitra D. M., Rutters, Femke, Siloaho, Maritta, Allin, Kristine H., Brage, Søren, Brorsson, Caroline A., Dawed, Adem Y., De Masi, Federico, Groves, Christopher J., Kokkola, Tarja, Mahajan, Anubha, Perry, Mandy H., Rauh, Simone P., Ridderstråle, Martin, Teare, Harriet J. A., Thomas, E. Louise, Tura, Andrea, Vestergaard, Henrik, White, Tom, Adamski, Jerzy, Bell, Jimmy D., Beulens, Joline W., Brunak, Søren, Dermitzakis, Emmanouil T., Froguel, Philippe, Frost, Gary, Gupta, Ramneek, Hansen, Torben, Hattersley, Andrew, Jablonka, Bernd, Kaye, Jane, Laakso, Markku, McDonald, Timothy J., Pedersen, Oluf, Schwenk, Jochen M., Pavo, Imre, Mari, Andrea, McCarthy, Mark I., Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, Franks, Paul W., and for the IMI DIRECT Consortium
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- 2019
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12. Metformin-induced changes of the gut microbiota in healthy young men: results of a non-blinded, one-armed intervention study
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Bryrup, Thomas, Thomsen, Cæcilie W., Kern, Timo, Allin, Kristine H., Brandslund, Ivan, Jørgensen, Niklas R., Vestergaard, Henrik, Hansen, Torben, Hansen, Tue H., Pedersen, Oluf, and Nielsen, Trine
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- 2019
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13. Recovery of gut microbiota of healthy adults following antibiotic exposure
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Palleja, Albert, Mikkelsen, Kristian H., Forslund, Sofia K., Kashani, Alireza, Allin, Kristine H., Nielsen, Trine, Hansen, Tue H., Liang, Suisha, Feng, Qiang, Zhang, Chenchen, Pyl, Paul Theodor, Coelho, Luis Pedro, Yang, Huanming, Wang, Jian, Typas, Athanasios, Nielsen, Morten F., Nielsen, Henrik Bjorn, Bork, Peer, Wang, Jun, Vilsbøll, Tina, Hansen, Torben, Knop, Filip K., Arumugam, Manimozhiyan, and Pedersen, Oluf
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- 2018
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14. Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study
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Gudmundsdottir, Valborg, Pedersen, Helle Krogh, Mazzoni, Gianluca, Allin, Kristine H., Artati, Anna, Beulens, Joline W., Banasik, Karina, Brorsson, Caroline, Cederberg, Henna, Chabanova, Elizaveta, De Masi, Federico, Elders, Petra J., Forgie, Ian, Giordano, Giuseppe N., Grallert, Harald, Gupta, Ramneek, Haid, Mark, Hansen, Torben, Hansen, Tue H., Hattersley, Andrew T., Heggie, Alison, Hong, Mun-Gwan, Jones, Angus G., Koivula, Robert, Kokkola, Tarja, Laakso, Markku, Løngreen, Peter, Mahajan, Anubha, Mari, Andrea, McDonald, Timothy J., McEvoy, Donna, Musholt, Petra B., Pavo, Imre, Prehn, Cornelia, Ruetten, Hartmut, Ridderstråle, Martin, Rutters, Femke, Sharma, Sapna, Slieker, Roderick C., Syed, Ali, Tajes, Juan Fernandez, Thomas, Cecilia Engel, Thomsen, Henrik S., Vangipurapu, Jagadish, Vestergaard, Henrik, Viñuela, Ana, Wesolowska-Andersen, Agata, Walker, Mark, Adamski, Jerzy, Schwenk, Jochen M., McCarthy, Mark I., Pearson, Ewan, Dermitzakis, Emmanouil, Franks, Paul W., Pedersen, Oluf, and Brunak, Søren
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- 2020
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15. Objective assessment of dietary patterns by use of metabolic phenotyping: a randomised, controlled, crossover trial
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Garcia-Perez, Isabel, Posma, Joram M, Gibson, Rachel, Chambers, Edward S, Hansen, Tue H, Vestergaard, Henrik, Hansen, Torben, Beckmann, Manfred, Pedersen, Oluf, Elliott, Paul, Stamler, Jeremiah, Nicholson, Jeremy K, Draper, John, Mathers, John C, Holmes, Elaine, and Frost, Gary
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- 2017
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16. Gestational diabetes and the human salivary microbiota: a longitudinal study during pregnancy and postpartum
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Crusell, Mie K. W., Brink, Lærke R., Nielsen, Trine, Allin, Kristine H., Hansen, Torben, Damm, Peter, Lauenborg, Jeannet, Hansen, Tue H., and Pedersen, Oluf
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- 2020
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17. Bone turnover, calcium homeostasis, and vitamin D status in Danish vegans
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Hansen, Tue H., Madsen, Marie T. B., Jørgensen, Niklas R., Cohen, Arieh S., Hansen, Torben, Vestergaard, Henrik, Pedersen, Oluf, and Allin, Kristine H.
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- 2018
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18. Aberrant intestinal microbiota in individuals with prediabetes
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Allin, Kristine H., Tremaroli, Valentina, Caesar, Robert, Jensen, Benjamin A. H., Damgaard, Mads T. F., Bahl, Martin I., Licht, Tine R., Hansen, Tue H., Nielsen, Trine, Dantoft, Thomas M., Linneberg, Allan, Jørgensen, Torben, Vestergaard, Henrik, Kristiansen, Karsten, Franks, Paul W., Hansen, Torben, Bäckhed, Fredrik, Pedersen, Oluf, and the IMI-DIRECT consortium
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- 2018
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19. The effect of drinking water pH on the human gut microbiota and glucose regulation: results of a randomized controlled cross-over intervention
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Hansen, Tue H., Thomassen, Mette T., Madsen, Mia L., Kern, Timo, Bak, Emilie G., Kashani, Alireza, Allin, Kristine H., Hansen, Torben, and Pedersen, Oluf
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- 2018
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20. Microbially Produced Imidazole Propionate Is Associated With Heart Failure and Mortality
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Molinaro, Antonio, Nemet, Ina, Bel Lassen, Pierre, Chakaroun, Rima, Nielsen, Trine, Aron-Wisnewsky, Judith, Bergh, Per-Olof, Li, Lin, Henricsson, Marcus, Køber, Lars, Isnard, Richard, Helft, Gerard, Stumvoll, Michael, Pedersen, Oluf, Smith, J. Gustav, Tang, W.H. Wilson, Clément, Karine, Hazen, Stanley L., Bäckhed, Fredrik, Alves, Renato, Amouyal, Chloe, Andersson Galijatovic, Ehm Astrid, Andreelli, Fabrizio, Barthelemy, Olivier, Bastard, Jean-Philippe, Batisse, Jean-Paul, Berland, Magalie, Bittar, Randa, Blüher, Matthias, Bork, Peer, Bourron, Olivier, Camus, Mickael, Cassuto, Dominique, Ciangura, Cecile, Coelho, Luis Pedro, Collet, Jean-Philippe, Dumas, Marc-Emmanuel, Ehrlich, S. Dusko, Engelbrechtsen, Line, Fezeu, Leopold, Forslund, Sofia, Fromentin, Sebastien, Galan, Pilar, Giral, Philippe, Gøtze, Jens Peter, Hansen, Torben, Hansen, Tue H., Hartemann, Agnes, Hartmann, Bolette, Hercberg, Serge, Holmes, Bridget, Holst, Jens Juul, Hornbak, Malene, Hoyles, Lesley, Hulot, Jean-Sebastien, Jaqueminet, Sophie, Kerneis, Mathieu, Khemis, Jean, Kozlowski, Ruby, Pedersen, Helle Krogh, Kuhn, Michael, Mannerås-Holm, Louise, Marko, Lajos, Martinez-Gili Robin Massey, Laura, Maziers, Nicolas, Medina-Stamminger, Jonathan, Moitinho-Silva, Lucas, Montalescot, Gilles, Moutel, Sandrine, Neves, Ana Luisa, Olanipekun, Michael, Oppert, Jean-Michel, Poitou, Christine, Pousset, Francoise, Pouzoulet, Laurence, Rouault, Christine, Silvain, Johanne, and Vestergaard, Henrik
- Abstract
Over the past years, it has become clear that the microbial ecosystem in the gut has a profound capacity to interact with the host through the production of a wide range of bioactive metabolites. The microbially produced metabolite imidazole propionate (ImP) is clinically and mechanistically linked with insulin resistance and type 2 diabetes, but it is unclear how ImP is associated with heart failure.
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- 2023
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21. Impairment of gut microbial biotin metabolism and host biotin status in severe obesity:effect of biotin and prebiotic supplementation on improved metabolism
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Belda, Eugeni, Voland, Lise, Tremaroli, Valentina, Falony, Gwen, Adriouch, Solia, Assmann, Karen E., Prifiti, Edi, Aron-Wisnewsky, Judith, Debedat, Jean, Le Roy, Tiphaine, Nielsen, Trine, Amouyal, Chloe, Andre, Sebastien, Andreelli, Fabrizio, Blueher, Matthias, Chakaroun, Rima, Chilloux, Julien, Coelho, Luis Pedro, Dao, Maria Carlota, Das, Promi, Fellahi, Soraya, Forslund, Sofia, Galleron, Nathalie, Hansen, Tue H., Holmes, Bridget, Ji, Boyang, Pedersen, Helle Krogh, Phuong Le, Le Chatelier, Emmanuelle, Lewinter, Christian, Manneras-Holm, Louise, Marquet, Florian, Myridakis, Antonis, Pelloux, Veronique, Pons, Nicolas, Quinquis, Benoit, Rouault, Christine, Roume, Hugo, Salem, Joe-Elie, Sokolovska, Nataliya, Søndertoft, Nadja B., Touch, Sothea, Vieira-Silva, Sara, Galan, Pilar, Holst, Jens, Gøtze, Jens Peter, Køber, Lars, Vestergaard, Henrik, Hansen, Torben, Hercberg, Serge, Oppert, Jean-Michel, Nielsen, Jens, Letunic, Ivica, Dumas, Marc-Emmanuel, Stumvoll, Michael, Pedersen, Oluf Borbye, Bork, Peer, Ehrlich, Stanislav Dusko, Zucker, Jean-Daniel, Baeckhed, Fredrik, Raes, Jeroen, Clement, Karine, Commission of the European Communities, Medical Research Council (MRC), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases [IHU ICAN], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut de Cardiométabolisme et Nutrition = Institute of Cardiometabolism and Nutrition [CHU Pitié Salpêtrière] (IHU ICAN), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Nutrition et obésités: approches systémiques (UMR-S 1269) (Nutriomics), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Inst Med, Dept Mol & Clin Med, Wallenberg Lab, University of Gothenburg (GU), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Sorbonne Paris Cité (COMUE) (USPC), MetaGenoPolis, Institut National de la Recherche Agronomique (INRA), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Université Pierre et Marie Curie - Paris 6 (UPMC)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Service de Nutrition [CHU Pitié-Salpétrière], Institut E3M [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Université de Bordeaux (UB), Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR), Faculty of Health and Medical Sciences, University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH), Service de Diabétologie [CHU Pitié-Salpétrière], Laboratoire de chimie Macromoléculaire (CNRS UMR 5076), Ecole Nationale Supérieure de Chimie de Montpellier (ENSCM), Institut Cochin (IC UM3 (UMR 8104 / U1016)), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Universität Leipzig [Leipzig], Keck School of Medicine [Los Angeles], University of Southern California (USC), Nutrition et cerveau (U1213, U855), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM), Instituto de Medicina Molecular, Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (EGENODIA (GI3M)), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Imperial College London - National Heart and Lung Institute, and Division of Computational and Systems Medicine, Imperial College London, London, SW7 2AZ, UK
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EXPRESSION ,[SDV]Life Sciences [q-bio] ,Biotin ,Endocrinology and Diabetes ,Microbiology ,DIET ,Mice ,Humans ,Animals ,Obesity ,CHROMIUM PICOLINATE ,Inflammation ,Science & Technology ,OVERWEIGHT ,Gastroenterology & Hepatology ,Gastroenterology ,1103 Clinical Sciences ,Gastrointestinal Microbiome ,Obesity, Morbid ,MetaCardis Consortium ,Mice, Inbred C57BL ,nutrition ,Prebiotics ,Diabetes Mellitus, Type 2 ,Cardiovascular and Metabolic Diseases ,micronutrients ,Other Clinical Medicine ,diabetes mellitus ,Vitamin B Complex ,1114 Paediatrics and Reproductive Medicine ,intestinal bacteria ,HEALTH ,Life Sciences & Biomedicine - Abstract
ObjectivesGut microbiota is a key component in obesity and type 2 diabetes, yet mechanisms and metabolites central to this interaction remain unclear. We examined the human gut microbiome’s functional composition in healthy metabolic state and the most severe states of obesity and type 2 diabetes within the MetaCardis cohort. We focused on the role of B vitamins and B7/B8 biotin for regulation of host metabolic state, as these vitamins influence both microbial function and host metabolism and inflammation.DesignWe performed metagenomic analyses in 1545 subjects from the MetaCardis cohorts and different murine experiments, including germ-free and antibiotic treated animals, faecal microbiota transfer, bariatric surgery and supplementation with biotin and prebiotics in mice.ResultsSevere obesity is associated with an absolute deficiency in bacterial biotin producers and transporters, whose abundances correlate with host metabolic and inflammatory phenotypes. We found suboptimal circulating biotin levels in severe obesity and altered expression of biotin-associated genes in human adipose tissue. In mice, the absence or depletion of gut microbiota by antibiotics confirmed the microbial contribution to host biotin levels. Bariatric surgery, which improves metabolism and inflammation, associates with increased bacterial biotin producers and improved host systemic biotin in humans and mice. Finally, supplementing high-fat diet-fed mice with fructo-oligosaccharides and biotin improves not only the microbiome diversity, but also the potential of bacterial production of biotin and B vitamins, while limiting weight gain and glycaemic deterioration.ConclusionStrategies combining biotin and prebiotic supplementation could help prevent the deterioration of metabolic states in severe obesity.Trial registration numberNCT02059538.
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- 2022
22. Sustained influence of metformin therapy on circulating glucagon‐like peptide‐1 levels in individuals with and without type 2 diabetes
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Preiss, David, Dawed, Adem, Welsh, Paul, Heggie, Alison, Jones, Angus G., Dekker, Jacqueline, Koivula, Robert, Hansen, Tue H., Stewart, Caitlin, Holman, Rury R., Franks, Paul W., Walker, Mark, Pearson, Ewan R., and Sattar, Naveed
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- 2017
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23. Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: rationale and design of the epidemiological studies within the IMI DIRECT Consortium
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Koivula, Robert W., Heggie, Alison, Barnett, Anna, Cederberg, Henna, Hansen, Tue H., Koopman, Anitra D., Ridderstråle, Martin, Rutters, Femke, Vestergaard, Henrik, Gupta, Ramneek, Herrgård, Sanna, Heymans, Martijn W., Perry, Mandy H., Rauh, Simone, Siloaho, Maritta, Teare, Harriet J. A., Thorand, Barbara, Bell, Jimmy, Brunak, Søren, Frost, Gary, Jablonka, Bernd, Mari, Andrea, McDonald, Tim J., Dekker, Jacqueline M., Hansen, Torben, Hattersley, Andrew, Laakso, Markku, Pedersen, Oluf, Koivisto, Veikko, Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, Franks, Paul W., and for the DIRECT Consortium
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- 2014
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24. Inferring causal pathways between metabolic processes and liver fat accumulation: an IMI DIRECT study
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Atabaki-Pasdar, Naeimeh, primary, Pomares-Millan, Hugo, additional, Koivula, Robert W, additional, Tura, Andrea, additional, Brown, Andrew, additional, Viñuela, Ana, additional, Agudelo, Leandro, additional, Coral, Daniel, additional, van Oort, Sabine, additional, Allin, Kristine, additional, Chabanova, Elizaveta, additional, Cederberg, Henna, additional, De Masi, Federico, additional, Elders, Petra, additional, Tajes, Juan Fernandez, additional, Forgie, Ian M, additional, Hansen, Tue H, additional, Heggie, Alison, additional, Jones, Angus, additional, Kokkola, Tarja, additional, Mahajan, Anubha, additional, McDonald, Timothy J, additional, McEvoy, Donna, additional, Tsirigos, Konstantinos, additional, Teare, Harriet, additional, Vangipurapu, Jagadish, additional, Vestergaard, Henrik, additional, Adamski, Jerzy, additional, Beulens, Joline WJ, additional, Brunak, Søren, additional, Dermitzakis, Emmanouil, additional, Hansen, Torben, additional, Hattersley, Andrew T, additional, Laakso, Markku, additional, Pedersen, Oluf, additional, Ridderstråle, Martin, additional, Ruetten, Hartmut, additional, Rutters, Femke, additional, Schwenk, Jochen M, additional, Walker, Mark, additional, Giordano, Giuseppe N, additional, Ohlsson, Mattias, additional, Gupta, Ramneek, additional, Mari, Andrea, additional, McCarthy, Mark I, additional, Thomas, E Louise, additional, Bell, Jimmy D, additional, Pavo, Imre, additional, Pearson, Ewan R, additional, and Franks, Paul W, additional
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- 2021
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25. Profiles of Glucose Metabolism in Different Prediabetes Phenotypes, Classified by Fasting Glycemia, 2-Hour OGTT, Glycated Hemoglobin, and 1-hour OGTT: An IMI DIRECT Study
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Tura, Andrea, primary, Grespan, Eleonora, primary, Göbl, Christian S., primary, Koivula, Robert W., primary, Franks, Paul W., primary, Pearson, Ewan R., primary, Walker, Mark, primary, Forgie, Ian M., primary, Giordano, Giuseppe N., primary, Pavo, Imre, primary, Ruetten, Hartmut, primary, Dermitzakis, Emmanouil T., primary, McCarthy, Mark I., primary, Pedersen, Oluf, primary, Schwenk, Jochen M., primary, Adamski, Jerzy, primary, Masi, Federico De, primary, Tsirigos, Konstantinos D., primary, Brunak, Søren, primary, Viñuela, Ana, primary, Mahajan, Anubha, primary, McDonald, Timothy J., primary, Kokkola, Tarja, primary, Vangipurapu, Jagadish, primary, Cederberg, Henna, primary, Laakso, Markku, primary, Rutters, Femke, primary, Elders, Petra J.M., primary, Koopman, Anitra D.M., primary, Beulens, Joline W., primary, Ridderstråle, Martin, primary, Hansen, Tue H., primary, Allin, Kristine H., primary, Hansen, Torben, primary, Vestergaard, Henrik, primary, Mari, Andrea, primary, and Consortium, IMI DIRECT, primary
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- 2021
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26. Correction to: The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes: an IMI DIRECT study (Diabetologia, (2020), 63, 4, (744-756), 10.1007/s00125-019-05083-6)
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Koivula, Robert W., Atabaki-Pasdar, Naeimeh, Giordano, Giuseppe N., White, Tom, Adamski, Jerzy, Bell, Jimmy D., Beulens, Joline, Brage, S. ren, Brunak, S. ren, de Masi, Federico, Dermitzakis, Emmanouil T., Forgie, Ian M., Frost, Gary, Hansen, Torben, Hansen, Tue H., Hattersley, Andrew, Kokkola, Tarja, Kurbasic, Azra, Laakso, Markku, Mari, Andrea, McDonald, Timothy J., Pedersen, Oluf, Rutters, Femke, Schwenk, Jochen M., Teare, Harriet J. A., Thomas, E. Louise, Vinuela, Ana, Mahajan, Anubha, McCarthy, Mark I., Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, Pavo, Imre, Franks, Paul W., Epidemiology and Data Science, ACS - Diabetes & metabolism, APH - Health Behaviors & Chronic Diseases, APH - Aging & Later Life, and ACS - Heart failure & arrhythmias
- Abstract
Unfortunately, ‘Present address’ was omitted from one of the addresses provided for Mark I. McCarthy (#26). The corrected address details are given on the following page.
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- 2021
27. Serum Short-Chain Fatty Acids and Associations With Inflammation in Newly Diagnosed Patients With Multiple Sclerosis and Healthy Controls
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Olsson, Anna, primary, Gustavsen, Stefan, additional, Nguyen, Thao Duy, additional, Nyman, Margareta, additional, Langkilde, Annika R., additional, Hansen, Tue H., additional, Sellebjerg, Finn, additional, Oturai, Annette B., additional, and Bach Søndergaard, Helle, additional
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- 2021
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28. The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes: an IMI DIRECT study
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Koivula, Robert W, Atabaki-Pasdar, Naeimeh, Giordano, Giuseppe N, White, Tom, Adamski, Jerzy, Bell, Jimmy D, Beulens, Joline, Brage, Søren, Brunak, Søren, De Masi, Federico, Dermitzakis, Emmanouil T, Forgie, Ian M, Frost, Gary, Hansen, Torben, Hansen, Tue H, Hattersley, Andrew, Kokkola, Tarja, Kurbasic, Azra, Laakso, Markku, Mari, Andrea, McDonald, Timothy J, Pedersen, Oluf, Rutters, Femke, Schwenk, Jochen M, Teare, Harriet JA, Thomas, E Louise, Vinuela, Ana, Mahajan, Anubha, McCarthy, Mark I, Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, Pavo, Imre, Franks, Paul W, IMI DIRECT Consortium, Koivula, Robert W [0000-0002-1646-4163], and Apollo - University of Cambridge Repository
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Blood Glucose ,Male ,Denmark ,Glycemic Control ,Ectopic fat ,Cohort Studies ,Glycaemic control ,Homeostasis ,Humans ,Exercise ,Finland ,Aged ,Netherlands ,Sweden ,Physical activity ,Beta cell function ,Type 2 diabetes ,Glucose Tolerance Test ,Middle Aged ,Insulin sensitivity ,Cross-Sectional Studies ,Diabetes Mellitus, Type 2 ,Structural equation modelling ,Female ,Insulin Resistance ,Energy Metabolism ,Prediabetes - Abstract
AIMS/HYPOTHESIS: It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435). METHODS: We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively. RESULTS: The TC and TC-PA models showed better fit than null models (TC: χ2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle. CONCLUSIONS/INTERPRETATION: These analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.
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- 2020
29. Additional file 1 of Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study
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Gudmundsdottir, Valborg, Pedersen, Helle Krogh, Mazzoni, Gianluca, Allin, Kristine H., Artati, Anna, Beulens, Joline W., Banasik, Karina, Brorsson, Caroline, Cederberg, Henna, Chabanova, Elizaveta, Masi, Federico De, Elders, Petra J., Forgie, Ian, Giordano, Giuseppe N., Grallert, Harald, Ramneek Gupta, Haid, Mark, Hansen, Torben, Hansen, Tue H., Hattersley, Andrew T., Heggie, Alison, Mun-Gwan Hong, Jones, Angus G., Koivula, Robert, Kokkola, Tarja, Laakso, Markku, Løngreen, Peter, Anubha Mahajan, Mari, Andrea, McDonald, Timothy J., McEvoy, Donna, Musholt, Petra B., Pavo, Imre, Prehn, Cornelia, Ruetten, Hartmut, Ridderstråle, Martin, Rutters, Femke, Sharma, Sapna, Slieker, Roderick C., Syed, Ali, Tajes, Juan Fernandez, Thomas, Cecilia Engel, Thomsen, Henrik S., Jagadish Vangipurapu, Vestergaard, Henrik, Viñuela, Ana, Wesolowska-Andersen, Agata, Walker, Mark, Adamski, Jerzy, Schwenk, Jochen M., McCarthy, Mark I., Pearson, Ewan, Dermitzakis, Emmanouil, Franks, Paul W., Pedersen, Oluf, and Brunak, Søren
- Abstract
Additional file 1. Supplementary Figures. This file contains Fig. S1 – S13.
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- 2020
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30. Predicting and elucidating the etiology of fatty liver disease:A machine learning modeling and validation study in the IMI DIRECT cohorts
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Atabaki-Pasdar, Naeimeh, Ohlsson, Mattias, Viñuela, Ana, Frau, Francesca, Pomares-Millan, Hugo, Haid, Mark, Jones, Angus G, Thomas, E Louise, Koivula, Robert W, Kurbasic, Azra, Mutie, Pascal M, Fitipaldi, Hugo, Fernandez, Juan, Dawed, Adem Y, Giordano, Giuseppe N, Forgie, Ian M, McDonald, Timothy J, Rutters, Femke, Cederberg, Henna, Chabanova, Elizaveta, Dale, Matilda, Masi, Federico De, Thomas, Cecilia Engel, Allin, Kristine H., Hansen, Tue H, Heggie, Alison, Hong, Mun-Gwan, Elders, Petra J M, Kennedy, Gwen, Kokkola, Tarja, Pedersen, Helle Krogh, Mahajan, Anubha, McEvoy, Donna, Pattou, Francois, Raverdy, Violeta, Häussler, Ragna S, Sharma, Sapna, Thomsen, Henrik S, Vangipurapu, Jagadish, Vestergaard, Henrik, Adamski, Jerzy, Musholt, Petra B, Brage, Søren, Brunak, Søren, Dermitzakis, Emmanouil, Frost, Gary, Hansen, Torben, Laakso, Markku, and Pedersen, Oluf
- Abstract
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning.METHODS AND FINDINGS: We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (CONCLUSIONS: In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community.TRIAL REGISTRATION: ClinicalTrials.gov NCT03814915.
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- 2020
31. Additional file 2 of Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study
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Gudmundsdottir, Valborg, Pedersen, Helle Krogh, Mazzoni, Gianluca, Allin, Kristine H., Artati, Anna, Beulens, Joline W., Banasik, Karina, Brorsson, Caroline, Cederberg, Henna, Chabanova, Elizaveta, Masi, Federico De, Elders, Petra J., Forgie, Ian, Giordano, Giuseppe N., Grallert, Harald, Ramneek Gupta, Haid, Mark, Hansen, Torben, Hansen, Tue H., Hattersley, Andrew T., Heggie, Alison, Mun-Gwan Hong, Jones, Angus G., Koivula, Robert, Kokkola, Tarja, Laakso, Markku, Løngreen, Peter, Anubha Mahajan, Mari, Andrea, McDonald, Timothy J., McEvoy, Donna, Musholt, Petra B., Pavo, Imre, Prehn, Cornelia, Ruetten, Hartmut, Ridderstråle, Martin, Rutters, Femke, Sharma, Sapna, Slieker, Roderick C., Syed, Ali, Tajes, Juan Fernandez, Thomas, Cecilia Engel, Thomsen, Henrik S., Jagadish Vangipurapu, Vestergaard, Henrik, Viñuela, Ana, Wesolowska-Andersen, Agata, Walker, Mark, Adamski, Jerzy, Schwenk, Jochen M., McCarthy, Mark I., Pearson, Ewan, Dermitzakis, Emmanouil, Franks, Paul W., Pedersen, Oluf, and Brunak, Søren
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Data_FILES - Abstract
Additional file 2. Supplementary Methods. This file contains methods descriptions for omics data generation and preprocessing.
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- 2020
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32. Processes Underlying Glycemic Deterioration in Type 2 Diabetes: An IMI DIRECT Study
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Bizzotto, Roberto, primary, Jennison, Christopher, primary, Jones, Angus G, primary, Kurbasic, Azra, primary, Tura, Andrea, primary, Kennedy, Gwen, primary, Bell, Jimmy D, primary, Thomas, Elizabeth L, primary, Frost, Gary, primary, Eriksen, Rebeca, primary, Koivula, Robert W, primary, Brage, Soren, primary, Kaye, Jane, primary, Hattersley, Andrew T, primary, Heggie, Alison, primary, McEvoy, Donna, primary, Hart, Leen M ’t, primary, Beulens, Joline W, primary, Elders, Petra, primary, Musholt, Petra B, primary, Ridderstråle, Martin, primary, Hansen, Tue H, primary, Allin, Kristine H, primary, Hansen, Torben, primary, Vestergaard, Henrik, primary, Lundgaard, Agnete T, primary, Thomsen, Henrik S, primary, Masi, Federico De, primary, Tsirigos, Konstantinos D, primary, Brunak, Søren, primary, Viñuela, Ana, primary, Mahajan, Anubha, primary, McDonald, Timothy J, primary, Kokkola, Tarja, primary, Forgie, Ian M, primary, Giordano, Giuseppe N, primary, Pavo, Imre, primary, Ruetten, Hartmut, primary, Dermitzakis, Emmanouil, primary, McCarthy, Mark I, primary, Pedersen, Oluf, primary, Schwenk, Jochen M, primary, Adamski, Jerzy, primary, Franks, Paul W, primary, Walker, Mark, primary, Pearson, Ewan R, primary, Mari, Andrea, primary, and consortium, the IMI DIRECT, primary
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- 2020
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33. The intestinal microbiome is a co-determinant of the postprandial plasma glucose response
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Søndertoft, Nadja B., primary, Vogt, Josef K., additional, Arumugam, Manimozhiyan, additional, Kristensen, Mette, additional, Gøbel, Rikke J., additional, Fan, Yong, additional, Lyu, Liwei, additional, Bahl, Martin I., additional, Eriksen, Carsten, additional, Ängquist, Lars, additional, Frøkiær, Hanne, additional, Hansen, Tue H., additional, Brix, Susanne, additional, Nielsen, H. Bjørn, additional, Hansen, Torben, additional, Vestergaard, Henrik, additional, Gupta, Ramneek, additional, Licht, Tine R., additional, Lauritzen, Lotte, additional, and Pedersen, Oluf, additional
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- 2020
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34. Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study
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Eriksen, Rebeca, primary, Perez, Isabel Garcia, additional, Posma, Joram M., additional, Haid, Mark, additional, Sharma, Sapna, additional, Prehn, Cornelia, additional, Thomas, Louise E., additional, Koivula, Robert W., additional, Bizzotto, Roberto, additional, Mari, Andrea, additional, Giordano, Giuseppe N., additional, Pavo, Imre, additional, Schwenk, Jochen M., additional, De Masi, Federico, additional, Tsirigos, Konstantinos D., additional, Brunak, Søren, additional, Viñuela, Ana, additional, Mahajan, Anubha, additional, McDonald, Timothy J., additional, Kokkola, Tarja, additional, Rutter, Femke, additional, Teare, Harriet, additional, Hansen, Tue H., additional, Fernandez, Juan, additional, Jones, Angus, additional, Jennison, Chris, additional, Walker, Mark, additional, McCarthy, Mark I., additional, Pedersen, Oluf, additional, Ruetten, Hartmut, additional, Forgie, Ian, additional, Bell, Jimmy D., additional, Pearson, Ewan R., additional, Franks, Paul W., additional, Adamski, Jerzy, additional, Holmes, Elaine, additional, and Frost, Gary, additional
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- 2020
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35. Large-scale association analyses identify host factors influencing human gut microbiome composition
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Kurilshikov, Alexander, primary, Medina-Gomez, Carolina, additional, Bacigalupe, Rodrigo, additional, Radjabzadeh, Djawad, additional, Wang, Jun, additional, Demirkan, Ayse, additional, Roy, Caroline I. Le, additional, Raygoza Garay, Juan Antonio, additional, Finnicum, Casey T., additional, Liu, Xingrong, additional, Zhernakova, Daria V., additional, Bonder, Marc Jan, additional, Hansen, Tue H., additional, Frost, Fabian, additional, Rühlemann, Malte C., additional, Turpin, Williams, additional, Moon, Jee-Young, additional, Kim, Han-Na, additional, Lüll, Kreete, additional, Barkan, Elad, additional, Shah, Shiraz A., additional, Fornage, Myriam, additional, Szopinska-Tokov, Joanna, additional, Wallen, Zachary D., additional, Borisevich, Dmitrii, additional, Agreus, Lars, additional, Andreasson, Anna, additional, Bang, Corinna, additional, Bedrani, Larbi, additional, Bell, Jordana T., additional, Bisgaard, Hans, additional, Boehnke, Michael, additional, Boomsma, Dorret I., additional, Burk, Robert D., additional, Claringbould, Annique, additional, Croitoru, Kenneth, additional, Davies, Gareth E., additional, van Duijn, Cornelia M., additional, Duijts, Liesbeth, additional, Falony, Gwen, additional, Fu, Jingyuan, additional, van der Graaf, Adriaan, additional, Hansen, Torben, additional, Homuth, Georg, additional, Hughes, David A., additional, Ijzerman, Richard G., additional, Jackson, Matthew A., additional, Jaddoe, Vincent W.V., additional, Joossens, Marie, additional, Jørgensen, Torben, additional, Keszthelyi, Daniel, additional, Knight, Rob, additional, Laakso, Markku, additional, Laudes, Matthias, additional, Launer, Lenore J., additional, Lieb, Wolfgang, additional, Lusis, Aldons J., additional, Masclee, Ad A.M., additional, Moll, Henriette A., additional, Mujagic, Zlatan, additional, Qibin, Qi, additional, Rothschild, Daphna, additional, Shin, Hocheol, additional, Sørensen, Søren J., additional, Steves, Claire J., additional, Thorsen, Jonathan, additional, Timpson, Nicholas J., additional, Tito, Raul Y., additional, Vieira-Silva, Sara, additional, Völker, Uwe, additional, Völzke, Henry, additional, Võsa, Urmo, additional, Wade, Kaitlin H., additional, Walter, Susanna, additional, Watanabe, Kyoko, additional, Weiss, Stefan, additional, Weiss, Frank U., additional, Weissbrod, Omer, additional, Westra, Harm-Jan, additional, Willemsen, Gonneke, additional, Payami, Haydeh, additional, Jonkers, Daisy M.A.E., additional, Vasquez, Alejandro Arias, additional, de Geus, Eco J.C., additional, Meyer, Katie A., additional, Stokholm, Jakob, additional, Segal, Eran, additional, Org, Elin, additional, Wijmenga, Cisca, additional, Kim, Hyung-Lae, additional, Kaplan, Robert C., additional, Spector, Tim D., additional, Uitterlinden, Andre G., additional, Rivadeneira, Fernando, additional, Franke, Andre, additional, Lerch, Markus M., additional, Franke, Lude, additional, Sanna, Serena, additional, D’Amato, Mauro, additional, Pedersen, Oluf, additional, Paterson, Andrew D., additional, Kraaij, Robert, additional, Raes, Jeroen, additional, and Zhernakova, Alexandra, additional
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- 2020
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36. Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts
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Atabaki-Pasdar, Naeimeh, primary, Ohlsson, Mattias, additional, Viñuela, Ana, additional, Frau, Francesca, additional, Pomares-Millan, Hugo, additional, Haid, Mark, additional, Jones, Angus G., additional, Thomas, E. Louise, additional, Koivula, Robert W., additional, Kurbasic, Azra, additional, Mutie, Pascal M., additional, Fitipaldi, Hugo, additional, Fernandez, Juan, additional, Dawed, Adem Y., additional, Giordano, Giuseppe N., additional, Forgie, Ian M., additional, McDonald, Timothy J., additional, Rutters, Femke, additional, Cederberg, Henna, additional, Chabanova, Elizaveta, additional, Dale, Matilda, additional, Masi, Federico De, additional, Thomas, Cecilia Engel, additional, Allin, Kristine H., additional, Hansen, Tue H., additional, Heggie, Alison, additional, Hong, Mun-Gwan, additional, Elders, Petra J. M., additional, Kennedy, Gwen, additional, Kokkola, Tarja, additional, Pedersen, Helle Krogh, additional, Mahajan, Anubha, additional, McEvoy, Donna, additional, Pattou, Francois, additional, Raverdy, Violeta, additional, Häussler, Ragna S., additional, Sharma, Sapna, additional, Thomsen, Henrik S., additional, Vangipurapu, Jagadish, additional, Vestergaard, Henrik, additional, ‘t Hart, Leen M., additional, Adamski, Jerzy, additional, Musholt, Petra B., additional, Brage, Soren, additional, Brunak, Søren, additional, Dermitzakis, Emmanouil, additional, Frost, Gary, additional, Hansen, Torben, additional, Laakso, Markku, additional, Pedersen, Oluf, additional, Ridderstråle, Martin, additional, Ruetten, Hartmut, additional, Hattersley, Andrew T., additional, Walker, Mark, additional, Beulens, Joline W. J., additional, Mari, Andrea, additional, Schwenk, Jochen M., additional, Gupta, Ramneek, additional, McCarthy, Mark I., additional, Pearson, Ewan R., additional, Bell, Jimmy D., additional, Pavo, Imre, additional, and Franks, Paul W., additional
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- 2020
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37. Predicting and elucidating the etiology of fatty liver disease using a machine learning-based approach: an IMI DIRECT study
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Atabaki-Pasdar, Naeimeh, primary, Ohlsson, Mattias, additional, Viñuela, Ana, additional, Frau, Francesca, additional, Pomares-Millan, Hugo, additional, Haid, Mark, additional, Jones, Angus G, additional, Thomas, E Louise, additional, Koivula, Robert W, additional, Kurbasic, Azra, additional, Mutie, Pascal M, additional, Fitipaldi, Hugo, additional, Fernandez, Juan, additional, Dawed, Adem Y, additional, Giordano, Giuseppe N, additional, Forgie, Ian M, additional, McDonald, Timothy J, additional, Rutters, Femke, additional, Cederberg, Henna, additional, Chabanova, Elizaveta, additional, Dale, Matilda, additional, De Masi, Federico, additional, Thomas, Cecilia Engel, additional, Allin, Kristine H, additional, Hansen, Tue H, additional, Heggie, Alison, additional, Hong, Mun-Gwan, additional, Elders, Petra JM, additional, Kennedy, Gwen, additional, Kokkola, Tarja, additional, Pedersen, Helle Krogh, additional, Mahajan, Anubha, additional, McEvoy, Donna, additional, Pattou, Francois, additional, Raverdy, Violeta, additional, Häussler, Ragna S, additional, Sharma, Sapna, additional, Thomsen, Henrik S, additional, Vangipurapu, Jagadish, additional, Vestergaard, Henrik, additional, ‘t Hart, Leen M, additional, Adamski, Jerzy, additional, Musholt, Petra B, additional, Brage, Soren, additional, Brunak, Søren, additional, Dermitzakis, Emmanouil, additional, Frost, Gary, additional, Hansen, Torben, additional, Laakso, Markku, additional, Pedersen, Oluf, additional, Ridderstråle, Martin, additional, Ruetten, Hartmut, additional, Hattersley, Andrew T, additional, Walker, Mark, additional, Beulens, Joline WJ, additional, Mari, Andrea, additional, Schwenk, Jochen M, additional, Gupta, Ramneek, additional, McCarthy, Mark I, additional, Pearson, Ewan R, additional, Bell, Jimmy D, additional, Pavo, Imre, additional, and Franks, Paul W, additional
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- 2020
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38. Impairment of gut microbial biotin metabolism and host biotin status in severe obesity: effect of biotin and prebiotic supplementation on improved metabolism
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Belda, Eugeni, Voland, Lise, Tremaroli, Valentina, Falony, Gwen, Adriouch, Solia, Assmann, Karen E, Prifti, Edi, Aron-Wisnewsky, Judith, Debédat, Jean, Le Roy, Tiphaine, Nielsen, Trine, Amouyal, Chloé, André, Sébastien, Andreelli, Fabrizio, Blu¨her, Matthias, Chakaroun, Rima, Chilloux, Julien, Coelho, Luis Pedro, Dao, Maria Carlota, Das, Promi, Fellahi, Soraya, Forslund, Sofia, Galleron, Nathalie, Hansen, Tue H, Holmes, Bridget, Ji, Boyang, Krogh Pedersen, Helle, Le, Phuong, Le Chatelier, Emmanuelle, Lewinter, Christian, Mannerås-Holm, Louise, Marquet, Florian, Myridakis, Antonis, Pelloux, Veronique, Pons, Nicolas, Quinquis, Benoit, Rouault, Christine, Roume, Hugo, Salem, Joe-Elie, Sokolovska, Nataliya, Søndertoft, Nadja B, Touch, Sothea, Vieira-Silva, Sara, Galan, Pilar, Holst, Jens, Gøtze, Jens Peter, Køber, Lars, Vestergaard, Henrik, Hansen, Torben, Hercberg, Serge, Oppert, Jean-Michel, Nielsen, Jens, Letunic, Ivica, Dumas, Marc-Emmanuel, Stumvoll, Michael, Pedersen, Oluf Borbye, Bork, Peer, Ehrlich, Stanislav Dusko, Zucker, Jean-Daniel, Ba¨ckhed, Fredrik, Raes, Jeroen, and Clément, Karine
- Abstract
ObjectivesGut microbiota is a key component in obesity and type 2 diabetes, yet mechanisms and metabolites central to this interaction remain unclear. We examined the human gut microbiome’s functional composition in healthy metabolic state and the most severe states of obesity and type 2 diabetes within the MetaCardis cohort. We focused on the role of B vitamins and B7/B8 biotin for regulation of host metabolic state, as these vitamins influence both microbial function and host metabolism and inflammation.DesignWe performed metagenomic analyses in 1545 subjects from the MetaCardis cohorts and different murine experiments, including germ-free and antibiotic treated animals, faecal microbiota transfer, bariatric surgery and supplementation with biotin and prebiotics in mice.ResultsSevere obesity is associated with an absolute deficiency in bacterial biotin producers and transporters, whose abundances correlate with host metabolic and inflammatory phenotypes. We found suboptimal circulating biotin levels in severe obesity and altered expression of biotin-associated genes in human adipose tissue. In mice, the absence or depletion of gut microbiota by antibiotics confirmed the microbial contribution to host biotin levels. Bariatric surgery, which improves metabolism and inflammation, associates with increased bacterial biotin producers and improved host systemic biotin in humans and mice. Finally, supplementing high-fat diet-fed mice with fructo-oligosaccharides and biotin improves not only the microbiome diversity, but also the potential of bacterial production of biotin and B vitamins, while limiting weight gain and glycaemic deterioration.ConclusionStrategies combining biotin and prebiotic supplementation could help prevent the deterioration of metabolic states in severe obesity.Trial registration numberNCT02059538.
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- 2022
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39. 1845-P: Divergent Effects on T2D of Alleles Associated with Increased Liver Fat Reflect Differential Impact on Hepatic Glucose and Lipid Output: An IMI DIRECT Study
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KOIVULA, ROBERT W., primary, CONSORTIUM, IMI-DIRECT, additional, FRANKS, PAUL W., additional, HANSEN, TUE H., additional, LAAKSO, MARKKU, additional, PEARSON, EWAN, additional, RUTTERS, FEMKE, additional, KARPE, FREDRIK, additional, TOMLINSON, JEREMY W., additional, MAHAJAN, ANUBHA, additional, and MCCARTHY, MARK, additional
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- 2019
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40. Short-chain fatty acids and gut microbiota in multiple sclerosis
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Melbye, Pernille, primary, Olsson, Anna, additional, Hansen, Tue H., additional, Søndergaard, Helle B., additional, and Bang Oturai, Annette, additional
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- 2018
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41. Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes: An IMI-DIRECT study.
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Obura, Morgan, Beulens, Joline W. J., Slieker, Roderick, Koopman, Anitra D. M., Hoekstra, Trynke, Nijpels, Giel, Elders, Petra, Koivula, Robert W., Kurbasic, Azra, Laakso, Markku, Hansen, Tue H., Ridderstråle, Martin, Hansen, Torben, Pavo, Imre, Forgie, Ian, Jablonka, Bernd, Ruetten, Hartmut, Mari, Andrea, McCarthy, Mark I., and Walker, Mark
- Subjects
TYPE 2 diabetes ,GLUCOSE ,GLYCEMIC index ,GLYCOSYLATED hemoglobin ,BETA (Finance) - Abstract
Aim: Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D. Methods: The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders. Results: At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1–3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18–1.92) for subgroup 2 and 1.88 (-0.08–3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose. Conclusions: Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk. [ABSTRACT FROM AUTHOR]
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- 2020
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42. The sustained influence of metformin therapy on circulating GLP-1 levels in individuals with and without type 2 diabetes
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Preiss, David, Dawed, Adem, Welsh, Paul, Heggie, Alison, Jones, Angus G, Dekker, Jacqueline, Koivula, Robert, Hansen, Tue H, Stewart, Caitlin, Holman, Rury R, Franks, Paul W, Walker, Mark, Pearson, Ewan R, and Sattar, Naveed
- Subjects
Adult ,Blood Glucose ,Glycated Hemoglobin ,Male ,Body Weight ,Fasting ,Middle Aged ,Postprandial Period ,Article ,Metformin ,Diabetes Mellitus, Type 2 ,Double-Blind Method ,Glucagon-Like Peptide 1 ,Case-Control Studies ,Humans ,Hypoglycemic Agents ,Intercellular Signaling Peptides and Proteins ,Female ,Peptides ,Aged - Abstract
To investigate, in the Carotid Atherosclerosis: Metformin for Insulin Resistance (CAMERA) trial (NCT00723307), whether the influence of metformin on the glucagon-like peptide (GLP)-1 axis in individuals with and without type 2 diabetes (T2DM) is sustained and related to changes in glycaemia or weight, and to investigate basal and post-meal GLP-1 levels in patients with T2DM in the cross-sectional Diabetes Research on Patient Stratification (DIRECT) study.CAMERA was a double-blind randomized placebo-controlled trial of metformin in 173 participants without diabetes. Using 6-monthly fasted total GLP-1 levels over 18 months, we evaluated metformin's effect on total GLP-1 with repeated-measures analysis and analysis of covariance. In the DIRECT study, we examined active and total fasting and 60-minute post-meal GLP-1 levels in 775 people recently diagnosed with T2DM treated with metformin or diet, using Student's t-tests and linear regression.In CAMERA, metformin increased total GLP-1 at 6 (+20.7%, 95% confidence interval [CI] 4.7-39.0), 12 (+26.7%, 95% CI 10.3-45.6) and 18 months (+18.7%, 95% CI 3.8-35.7), an overall increase of 23.4% (95% CI 11.2-36.9; P.0001) vs placebo. Adjustment for changes in glycaemia and adiposity, individually or combined, did not attenuate this effect. In the DIRECT study, metformin was associated with higher fasting active (39.1%, 95% CI 21.3-56.4) and total GLP-1 (14.1%, 95% CI 1.2-25.9) but not post-meal incremental GLP-1. These changes were independent of potential confounders including age, sex, adiposity and glycated haemoglobin.In people without diabetes, metformin increases total GLP-1 in a sustained manner and independently of changes in weight or glycaemia. Metformin-treated patients with T2DM also have higher fasted GLP-1 levels, independently of weight and glycaemia.
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- 2016
43. Statin therapy is associated with lower prevalence of gut microbiota dysbiosis.
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Vieira-Silva, Sara, Falony, Gwen, Belda, Eugeni, Nielsen, Trine, Aron-Wisnewsky, Judith, Chakaroun, Rima, Forslund, Sofia K., Assmann, Karen, Valles-Colomer, Mireia, Nguyen, Thi Thuy Duyen, Proost, Sebastian, Prifti, Edi, Tremaroli, Valentina, Pons, Nicolas, Le Chatelier, Emmanuelle, Andreelli, Fabrizio, Bastard, Jean-Phillippe, Coelho, Luis Pedro, Galleron, Nathalie, and Hansen, Tue H.
- Abstract
Microbiome community typing analyses have recently identified the Bacteroides2 (Bact2) enterotype, an intestinal microbiota configuration that is associated with systemic inflammation and has a high prevalence in loose stools in humans1,2. Bact2 is characterized by a high proportion of Bacteroides, a low proportion of Faecalibacterium and low microbial cell densities1,2, and its prevalence varies from 13% in a general population cohort to as high as 78% in patients with inflammatory bowel disease2. Reported changes in stool consistency3 and inflammation status4 during the progression towards obesity and metabolic comorbidities led us to propose that these developments might similarly correlate with an increased prevalence of the potentially dysbiotic Bact2 enterotype. Here, by exploring obesity-associated microbiota alterations in the quantitative faecal metagenomes of the cross-sectional MetaCardis Body Mass Index Spectrum cohort (n = 888), we identify statin therapy as a key covariate of microbiome diversification. By focusing on a subcohort of participants that are not medicated with statins, we find that the prevalence of Bact2 correlates with body mass index, increasing from 3.90% in lean or overweight participants to 17.73% in obese participants. Systemic inflammation levels in Bact2-enterotyped individuals are higher than predicted on the basis of their obesity status, indicative of Bact2 as a dysbiotic microbiome constellation. We also observe that obesity-associated microbiota dysbiosis is negatively associated with statin treatment, resulting in a lower Bact2 prevalence of 5.88% in statin-medicated obese participants. This finding is validated in both the accompanying MetaCardis cardiovascular disease dataset (n = 282) and the independent Flemish Gut Flora Project population cohort (n = 2,345). The potential benefits of statins in this context will require further evaluation in a prospective clinical trial to ascertain whether the effect is reproducible in a randomized population and before considering their application as microbiota-modulating therapeutics. A cross-sectional analysis of participants in the MetaCardis Body Mass Index Spectrum cohort finds that the higher prevalence of gut microbiota dysbiosis in individuals with obesity is not observed in those who take statin drugs. [ABSTRACT FROM AUTHOR]
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- 2020
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44. The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes: an IMI DIRECT study.
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Koivula, Robert W., Atabaki-Pasdar, Naeimeh, Giordano, Giuseppe N., White, Tom, Adamski, Jerzy, Bell, Jimmy D., Beulens, Joline, Brage, Søren, Brunak, Søren, De Masi, Federico, Dermitzakis, Emmanouil T., Forgie, Ian M., Frost, Gary, Hansen, Torben, Hansen, Tue H., Hattersley, Andrew, Kokkola, Tarja, Kurbasic, Azra, Laakso, Markku, and Mari, Andrea
- Abstract
Aims/hypothesis: It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435). Methods: We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively. Results: The TC and TC-PA models showed better fit than null models (TC: χ
2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle. Conclusions/interpretation: These analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control. [ABSTRACT FROM AUTHOR]- Published
- 2020
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45. Impact of a vegan diet on the human salivary microbiota
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Hansen, Tue H., primary, Kern, Timo, additional, Bak, Emilie G., additional, Kashani, Alireza, additional, Allin, Kristine H., additional, Nielsen, Trine, additional, Hansen, Torben, additional, and Pedersen, Oluf, additional
- Published
- 2018
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46. Short‐chain fatty acids and gut microbiota in multiple sclerosis.
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Melbye, Pernille, Olsson, Anna, Hansen, Tue H., Søndergaard, Helle B., and Bang Oturai, Annette
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SHORT-chain fatty acids ,MULTIPLE sclerosis ,GUT microbiome ,ENCEPHALOMYELITIS ,AUTOIMMUNE diseases - Abstract
Background: Multiple Sclerosis (MS) is a chronic immune‐mediated neurological disease of the central nervous system with a complex and still not fully understood aetiology. In recent years, the gut microbiota and fermentative metabolites like short‐chain fatty acids (SCFAs) have received increased attention in relation to the development and disease course of MS. This systematic review highlights and summarizes the existing literature within this field. Methods: A systematic search in PubMed was conducted on 12 October 2017, to find published original studies on SCFAs and their impact on MS and the animal model of MS experimental autoimmune encephalomyelitis (EAE). Furthermore, all studies analysing the gut microbiota in MS patients were included. A total of 14 studies were eligible for this review. Results: Short‐chain fatty acids have been shown to ameliorate the disease course in EAE, but no studies specifically addressing the role of SCFAs in human MS patients were identified. However, some investigations have shown that the microbiota of MS patients is characterized by a reduction in SCFA‐producing bacteria. Conclusions: Studies of EAE in mice suggest that SCFAs may play a role in the development and progression of EAE, but so far this has not been confirmed in humans. An aberrant gut microbiota in MS patients has been reported to be differentially abundant compared with healthy controls, although with little consistency in the bacterial taxa. Further investigations are required to elucidate the involvement of the gut microbiota and its metabolites, including potential beneficial effects of SCFAs, in the development and course of MS. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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47. Alterations in fecal microbiota composition by probiotic supplementation in healthy adults: a systematic review of randomized controlled trials
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Kristensen, Nadja B., primary, Bryrup, Thomas, additional, Allin, Kristine H., additional, Nielsen, Trine, additional, Hansen, Tue H., additional, and Pedersen, Oluf, additional
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- 2016
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48. Erratum to: ‘Intake of Macro- and Micronutrients in Danish Vegans’
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Kristensen, Nadja B., primary, Madsen, Mia L., additional, Hansen, Tue H., additional, Allin, Kristine H., additional, Hoppe, Camilla, additional, Fagt, Sisse, additional, Lausten, Mia S., additional, Gøbel, Rikke J., additional, Vestergaard, Henrik, additional, Hansen, Torben, additional, and Pedersen, Oluf, additional
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- 2015
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49. Intake of macro- and micronutrients in Danish vegans
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Kristensen, Nadja B., primary, Madsen, Mia L., additional, Hansen, Tue H., additional, Allin, Kristine H., additional, Hoppe, Camilla, additional, Fagt, Sisse, additional, Lausten, Mia S., additional, Gøbel, Rikke J., additional, Vestergaard, Henrik, additional, Hansen, Torben, additional, and Pedersen, Oluf, additional
- Published
- 2015
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50. The gut microbiome in cardio-metabolic health
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Hansen, Tue H, primary, Gøbel, Rikke J, additional, Hansen, Torben, additional, and Pedersen, Oluf, additional
- Published
- 2015
- Full Text
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