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4. Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models

Author

Allesøe, Rosa Lundbye, Lundgaard, Agnete Troen, Hernández Medina, Ricardo, Aguayo-Orozco, Alejandro, Johansen, Joachim, Nissen, Jakob Nybo, Brorsson, Caroline, Mazzoni, Gianluca, Niu, Lili, Biel, Jorge Hernansanz, Leal Rodríguez, Cristina, Brasas, Valentas, Webel, Henry, Benros, Michael Eriksen, Pedersen, Anders Gorm, Chmura, Piotr Jaroslaw, Jacobsen, Ulrik Plesner, Mari, Andrea, Koivula, Robert, Mahajan, Anubha, Vinuela, Ana, Tajes, Juan Fernandez, Sharma, Sapna, Haid, Mark, Hong, Mun-Gwan, Musholt, Petra B., De Masi, Federico, Vogt, Josef, Pedersen, Helle Krogh, Gudmundsdottir, Valborg, Jones, Angus, Kennedy, Gwen, Bell, Jimmy, Thomas, E. Louise, Frost, Gary, Thomsen, Henrik, Hansen, Elizaveta, Hansen, Tue Haldor, Vestergaard, Henrik, Muilwijk, Mirthe, Blom, Marieke T., ‘t Hart, Leen M., Pattou, Francois, Raverdy, Violeta, Brage, Soren, Kokkola, Tarja, Heggie, Alison, McEvoy, Donna, Mourby, Miranda, Kaye, Jane, Hattersley, Andrew, McDonald, Timothy, Ridderstråle, Martin, Walker, Mark, Forgie, Ian, Giordano, Giuseppe N., Pavo, Imre, Ruetten, Hartmut, Pedersen, Oluf, Hansen, Torben, Dermitzakis, Emmanouil, Franks, Paul W., Schwenk, Jochen M., Adamski, Jerzy, McCarthy, Mark I., Pearson, Ewan, Banasik, Karina, Rasmussen, Simon, and Brunak, Søren

Published
2023
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5. Gene expression signature predicts rate of type 1 diabetes progression

Author

Mathieu, Chantal, Gillard, Pieter, Casteels, Kristina, Overbergh, Lutgart, Dunger, David, Wallace, Chris, Evans, Mark, Thankamony, Ajay, Hendriks, Emile, Bruggraber, Sylvaine, Marcoveccchio, Loredana, Peakman, Mark, Tree, Timothy, Morgan, Noel G., Richardson, Sarah, Todd, John A., Wicker, Linda, Mander, Adrian, Dayan, Colin, Alhadj Ali, Mohammad, Pieber, Thomas, Eizirik, Decio L., Cnop, Myriam, Brunak, Søren, Pociot, Flemming, Johannesen, Jesper, Rossing, Peter, Quigley, Cristina Legido, Mallone, Roberto, Scharfmann, Raphael, Boitard, Christian, Knip, Mikael, Otonkoski, Timo, Veijola, Riitta, Lahesmaa, Riitta, Oresic, Matej, Toppari, Jorma, Danne, Thomas, Ziegler, Anette G., Achenbach, Peter, Rodriguez-Calvo, Teresa, Solimena, Michele, Bonifacio, Ezio E., Speier, Stephan, Holl, Reinhard, Dotta, Francesco, Chiarelli, Francesco, Marchetti, Piero, Bosi, Emanuele, Cianfarani, Stefano, Ciampalini, Paolo, De Beaufort, Carine, Dahl-Jørgensen, Knut, Skrivarhaug, Torild, Joner, Geir, Krogvold, Lars, Jarosz-Chobot, Przemka, Battelino, Tadej, Thorens, Bernard, Gotthardt, Martin, Roep, Bart O., Nikolic, Tanja, Zaldumbide, Arnaud, Lernmark, Ake, Lundgren, Marcus, Costacalde, Guillaume, Strube, Thorsten, Schulte, Anke M., Nitsche, Almut, Vela, Jose, Von Herrath, Matthias, Wesley, Johnna, Napolitano-Rosen, Antonella, Thomas, Melissa, Schloot, Nanette, Goldfine, Allison, Waldron-Lynch, Frank, Kompa, Jill, Vedala, Aruna, Hartmann, Nicole, Nicolas, Gwenaelle, van Rampelbergh, Jean, Bovy, Nicolas, Dutta, Sanjoy, Soderberg, Jeannette, Ahmed, Simi, Martin, Frank, Latres, Esther, Agiostratidou, Gina, Koralova, Anne, Willemsen, Ruben, Smith, Anne, Anand, Binu, Datta, Vipan, Puthi, Vijith, Zac-Varghese, Sagen, Dias, Renuka, Sundaram, Premkumar, Vaidya, Bijay, Patterson, Catherine, Owen, Katharine, Piel, Barbara, Heller, Simon, Randell, Tabitha, Gazis, Tasso, Reismen, Elise Bismuth, Carel, Jean-Claude, Riveline, Jean-Pierre, Gautier, Jean-Francoise, Andreelli, Fabrizion, Travert, Florence, Cosson, Emmanuel, Penfornis, Alfred, Petit, Catherine, Feve, Bruno, Lucidarme, Nadine, Beressi, Jean-Paul, Ajzenman, Catherina, Radu, Alina, Greteau-Hamoumou, Stephanie, Bibal, Cecile, Meissner, Thomas, Heidtmann, Bettina, Toni, Sonia, Rami-Merhar, Birgit, Eeckhout, Bart, Peene, Bernard, Vantongerloo, N., Maes, Toon, Gommers, Leen, Suomi, Tomi, Starskaia, Inna, Kalim, Ubaid Ullah, Rasool, Omid, Jaakkola, Maria K., Grönroos, Toni, Välikangas, Tommi, Brorsson, Caroline, Mazzoni, Gianluca, Overbergh, Lut, Chmura, Piotr, and Elo, Laura L.

Published
2023
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6. Author Correction: Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models

Author

Allesøe, Rosa Lundbye, Lundgaard, Agnete Troen, Hernández Medina, Ricardo, Aguayo-Orozco, Alejandro, Johansen, Joachim, Nissen, Jakob Nybo, Brorsson, Caroline, Mazzoni, Gianluca, Niu, Lili, Biel, Jorge Hernansanz, Leal Rodríguez, Cristina, Brasas, Valentas, Webel, Henry, Benros, Michael Eriksen, Pedersen, Anders Gorm, Chmura, Piotr Jaroslaw, Jacobsen, Ulrik Plesner, Mari, Andrea, Koivula, Robert, Mahajan, Anubha, Vinuela, Ana, Tajes, Juan Fernandez, Sharma, Sapna, Haid, Mark, Hong, Mun-Gwan, Musholt, Petra B., De Masi, Federico, Vogt, Josef, Pedersen, Helle Krogh, Gudmundsdottir, Valborg, Jones, Angus, Kennedy, Gwen, Bell, Jimmy, Thomas, E. Louise, Frost, Gary, Thomsen, Henrik, Hansen, Elizaveta, Hansen, Tue Haldor, Vestergaard, Henrik, Muilwijk, Mirthe, Blom, Marieke T., ‘t Hart, Leen M., Pattou, Francois, Raverdy, Violeta, Brage, Soren, Kokkola, Tarja, Heggie, Alison, McEvoy, Donna, Mourby, Miranda, Kaye, Jane, Hattersley, Andrew, McDonald, Timothy, Ridderstråle, Martin, Walker, Mark, Forgie, Ian, Giordano, Giuseppe N., Pavo, Imre, Ruetten, Hartmut, Pedersen, Oluf, Hansen, Torben, Dermitzakis, Emmanouil, Franks, Paul W., Schwenk, Jochen M., Adamski, Jerzy, McCarthy, Mark I., Pearson, Ewan, Banasik, Karina, Rasmussen, Simon, and Brunak, Søren

Published
2023
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8. LBP-003 Semaglutide achieves resolution of metabolic dysfunction-associated steatohepatitis via modulation of multiple pathogenic pathways: insights from human and animal studies

Author

Jara, Maximilian Kurt, primary, Norlin, Jenny Egecioglu, additional, Kjaer, Mette, additional, Almholt, Kasper, additional, Bendtsen, Kristian, additional, Bugianesi, Elisabetta, additional, Cusi, Kenneth, additional, Galsgaard, Elisabeth, additional, Geybels, Milan, additional, Gluud, Lise Lotte, additional, Harder, Lea Mørch, additional, Loomba, Rohit, additional, Mazzoni, Gianluca, additional, Newsome, Philip N., additional, Nitze, Louise Maymann, additional, Palle, Mads Sundby, additional, Ratziu, Vlad, additional, Sejling, Anne-Sophie, additional, Wong, Vincent Wai-Sun, additional, Anstee, Quentin M., additional, and Knudsen, Lotte Bjerre, additional

Published
2024
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9. Identification of ligand and receptor interactions in CKD and MASH through the integration of single cell and spatial transcriptomics

Author

Moreno, Jaime, Gluud, Lise Lotte, Galsgaard, Elisabeth D., Hvid, Henning, Mazzoni, Gianluca, Das, Vivek, Moreno, Jaime, Gluud, Lise Lotte, Galsgaard, Elisabeth D., Hvid, Henning, Mazzoni, Gianluca, and Das, Vivek

Abstract

Background Chronic Kidney Disease (CKD) and Metabolic dysfunction-associated steatohepatitis (MASH) are metabolic fibroinflammatory diseases. Combining single-cell (scRNAseq) and spatial transcriptomics (ST) could give unprecedented molecular disease understanding at single-cell resolution. A more comprehensive analysis of the cell-specific ligand-receptor (L-R) interactions could provide pivotal information about signaling pathways in CKD and MASH. To achieve this, we created an integrative analysis framework in CKD and MASH from two available human cohorts. Results The analytical framework identified L-R pairs involved in cellular crosstalk in CKD and MASH. Interactions between cell types identified using scRNAseq data were validated by checking the spatial co-presence using the ST data and the co-expression of the communicating targets. Multiple L-R protein pairs identified are known key players in CKD and MASH, while others are novel potential targets previously observed only in animal models. Conclusion Our study highlights the importance of integrating different modalities of transcriptomic data for a better understanding of the molecular mechanisms. The combination of single-cell resolution from scRNAseq data, combined with tissue slide investigations and visualization of cell-cell interactions obtained through ST, paves the way for the identification of future potential therapeutic targets and developing effective therapies., Background Chronic Kidney Disease (CKD) and Metabolic dysfunction-associated steatohepatitis (MASH) are metabolic fibroinflammatory diseases. Combining single-cell (scRNAseq) and spatial transcriptomics (ST) could give unprecedented molecular disease understanding at single-cell resolution. A more comprehensive analysis of the cell-specific ligand-receptor (LR) interactions could provide pivotal information about signaling pathways in CKD and MASH. To achieve this, we created an integrative analysis framework in CKD and MASH from two available human cohorts. Results The analytical framework identified L-R pairs involved in cellular crosstalk in CKD and MASH. Interactions between cell types identified using scRNAseq data were validated by checking the spatial co-presence using the ST data and the co-expression of the communicating targets. Multiple L-R protein pairs identified are known key players in CKD and MASH, while others are novel potential targets previously observed only in animal models. Conclusion Our study highlights the importance of integrating different modalities of transcriptomic data for a better understanding of the molecular mechanisms. The combination of single-cell resolution from scRNAseq data, combined with tissue slide investigations and visualization of cell-cell interactions obtained through ST, paves the way for the identification of future potential therapeutic targets and developing effective therapies.

Published
2024

10. Multi‐omics analysis reveals drivers of loss of β‐cell function after newly diagnosed autoimmune type 1 diabetes: An INNODIA multicenter study.

Author

Armenteros, Jose Juan Almagro, Brorsson, Caroline, Johansen, Christian Holm, Banasik, Karina, Mazzoni, Gianluca, Moulder, Robert, Hirvonen, Karoliina, Suomi, Tomi, Rasool, Omid, Bruggraber, Sylvaine F. A., Marcovecchio, M. Loredana, Hendricks, Emile, Al‐Sari, Naba, Mattila, Ismo, Legido‐Quigley, Cristina, Suvitaival, Tommi, Chmura, Piotr J., Knip, Mikael, Schulte, Anke M., and Lee, Jeong Heon

Subjects
TYPE 1 diabetes, MULTIOMICS, G protein coupled receptors, KILLER cells, GENETIC translation, AUTOIMMUNE diseases
Abstract

Aims: Heterogeneity in the rate of β‐cell loss in newly diagnosed type 1 diabetes patients is poorly understood and creates a barrier to designing and interpreting disease‐modifying clinical trials. Integrative analyses of baseline multi‐omics data obtained after the diagnosis of type 1 diabetes may provide mechanistic insight into the diverse rates of disease progression after type 1 diabetes diagnosis. Methods: We collected samples in a pan‐European consortium that enabled the concerted analysis of five different omics modalities in data from 97 newly diagnosed patients. In this study, we used Multi‐Omics Factor Analysis to identify molecular signatures correlating with post‐diagnosis decline in β‐cell mass measured as fasting C‐peptide. Results: Two molecular signatures were significantly correlated with fasting C‐peptide levels. One signature showed a correlation to neutrophil degranulation, cytokine signalling, lymphoid and non‐lymphoid cell interactions and G‐protein coupled receptor signalling events that were inversely associated with a rapid decline in β‐cell function. The second signature was related to translation and viral infection was inversely associated with change in β‐cell function. In addition, the immunomics data revealed a Natural Killer cell signature associated with rapid β‐cell decline. Conclusions: Features that differ between individuals with slow and rapid decline in β‐cell mass could be valuable in staging and prediction of the rate of disease progression and thus enable smarter (shorter and smaller) trial designs for disease modifying therapies as well as offering biomarkers of therapeutic effect. [ABSTRACT FROM AUTHOR]

Published
2024
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13. Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration

Author

Jennison, Christopher, Ehrhardt, Beate, Baum, Patrick, Schoelsch, Corinna, Freijer, Jan, Grempler, Rolf, Graefe-Mody, Ulrike, Hennige, Anita, Dings, Christiane, Lehr, Thorsten, Scherer, Nina, Sihinecich, Iryna, Pattou, Francois, Raverdi, Violeta, Caiazzo, Robert, Torres, Fanelly, Verkindt, Helene, Mari, Andrea, Tura, Andrea, Giorgino, Toni, Bizzotto, Roberto, Froguel, Philippe, Bonneford, Amelie, Canouil, Mickael, Dhennin, Veronique, Brorsson, Caroline, Brunak, Soren, De Masi, Federico, Gudmundsdóttir, Valborg, Pedersen, Helle, Banasik, Karina, Thomas, Cecilia, Sackett, Peter, Staerfeldt, Hans-Henrik, Lundgaard, Agnete, Nilsson, Birgitte, Nielsen, Agnes, Mazzoni, Gianluca, Karaderi, Tugce, Rasmussen, Simon, Johansen, Joachim, Allesøe, Rosa, Fritsche, Andreas, Thorand, Barbara, Adamski, Jurek, Grallert, Harald, Haid, Mark, Sharma, Sapna, Troll, Martina, Adam, Jonathan, Ferrer, Jorge, Eriksen, Heather, Frost, Gary, Haussler, Ragna, Hong, Mun-gwan, Schwenk, Jochen, Uhlen, Mathias, Nicolay, Claudia, Pavo, Imre, Steckel-Hamann, Birgit, Thomas, Melissa, Adragni, Kofi, Wu, Han, Hart, Leen't, Roderick, Slieker, van Leeuwen, Nienke, Dekkers, Koen, Frau, Francesca, Gassenhuber, Johann, Jablonka, Bernd, Musholt, Petra, Ruetten, Hartmut, Tillner, Joachim, Baltauss, Tania, Bernard Poenaru, Oana, de Preville, Nathalie, Rodriquez, Marianne, Arumugam, Manimozhiyan, Allin, Kristine, Engelbrechtsen, Line, Hansen, Torben, Hansen, Tue, Forman, Annemette, Jonsson, Anna, Pedersen, Oluf, Dutta, Avirup, Vogt, Josef, Vestergaard, Henrik, Laakso, Markku, Kokkola, Tarja, Kuulasmaa, Teemu, Franks, Paul, Giordano, Nick, Pomares-Millan, Hugo, Fitipaldi, Hugo, Mutie, Pascal, Klintenberg, Maria, Bergstrom, Margit, Groop, Leif, Ridderstrale, Martin, Atabaki Pasdar, Naeimeh, Deshmukh, Harshal, Heggie, Alison, Wake, Dianne, McEvoy, Donna, McVittie, Ian, Walker, Mark, Hattersley, Andrew, Hill, Anita, Jones, Angus, McDonald, Timothy, Perry, Mandy, Nice, Rachel, Hudson, Michelle, Thorne, Claire, Dermitzakis, Emmanouil, Viñuela, Ana, Cabrelli, Louise, Loftus, Heather, Dawed, Adem, Donnelly, Louise, Forgie, Ian, Pearson, Ewan, Palmer, Colin, Brown, Andrew, Koivula, Robert, Wesolowska-Andersen, Agata, Abdalla, Moustafa, McRobert, Nicky, Fernandez, Juan, Jiao, Yunlong, Robertson, Neil, Gough, Stephen, Kaye, Jane, Mourby, Miranda, Mahajan, Anubha, McCarthy, Mark, Shah, Nisha, Teare, Harriet, Holl, Reinhard, Koopman, Anitra, Rutters, Femke, Beulens, Joline, Groeneveld, Lenka, Bell, Jimmy, Thomas, Louise, Whitcher, Brandon, Wilman, Henry R., Parisinos, Constantinos A., Atabaki-Pasdar, Naeimeh, Kelly, Matt, Thomas, E. Louise, Neubauer, Stefan, Hingorani, Aroon D., Patel, Riyaz S., Hemingway, Harry, Franks, Paul W., Bell, Jimmy D., Banerjee, Rajarshi, and Yaghootkar, Hanieh

Published
2019
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18. Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study

Author

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

Published
2020
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19. Laparoscopic Treatment of Perforated Peptic Ulcer: A Propensity Score-Matched Comparison of Interrupted Stitches Repair versus Knotless Barbed Suture.

Author

Costa, Gianluca, Garbarino, Giovanni Maria, Lepre, Luca, Liotta, Gianluca, Mazzoni, Gianluca, Gabrieli, Alice, Costa, Alessandro, Podda, Mauro, Sganga, Gabriele, and Fransvea, Pietro

Subjects
PEPTIC ulcer, LAPAROSCOPIC surgery, SUTURES, SUTURING, PROPENSITY score matching, PROTON pump inhibitors
Abstract

Background: Peptic ulcers result from imbalanced acid production, and in recent decades, proton pump inhibitors have proven effective in treating them. However, perforated peptic ulcers (PPU) continue to occur with a persistent high mortality rate when not managed properly. The advantages of the laparoscopic approach have been widely acknowledged. Nevertheless, concerning certain technical aspects of this method, such as the best gastrorrhaphy technique, the consensus remains elusive. Consequently, the choice tends to rely on individual surgical experiences. Our study aimed to compare interrupted stitches versus running barbed suture for laparoscopic PPU repair. Methods: We conducted a retrospective study utilizing propensity score matching analysis on patients who underwent laparoscopic PPU repair. Patients were categorised into two groups: Interrupted Stitches Suture (IStiS) and Knotless Suture (KnotS). We then compared the clinical and pathological characteristics of patients in both groups. Results: A total of 265 patients underwent laparoscopic PPU repair: 198 patients with interrupted stitches technique and 67 with barbed knotless suture. Following propensity score matching, each group (IStiS and KnotS) comprised 56 patients. The analysis revealed that operative time did not differ between groups: 87.9 ± 39.7 vs. 92.8 ± 42.6 min (p = 0.537). Postoperative morbidity (24.0% vs. 32.7%, p = 0.331) and Clavien–Dindo III (10.7% vs. 5.4%, p = 0.489) were more frequently observed in the KnotS group, without any significant difference. In contrast, we found a slightly higher mortality rate in the IStiS group (10.7% vs. 7.1%, p = 0.742). Concerning leaks, no differences emerged between groups (3.6% vs. 5.4%, p = 1.000). Conclusions: Laparoscopic PPU repair with knotless barbed sutures is a non-inferior alternative to interrupted stitches repair. Nevertheless, further research such as randomised trials, with a standardised treatment protocol according to ulcer size, are required to identify the best gastrorraphy technique. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Biomarkers identifying hepatic inflammation in non-alcoholic fatty liver disease (NAFLD)

Author

Werge, Mikkel, primary, Hoegl, Annabelle, additional, Therkelsen, Marie Louise, additional, Grønborg, Mads, additional, Mazzoni, Gianluca, additional, Harder, Lea Mørch, additional, Hvid, Henning, additional, Rashu, Elias, additional, Thing, Mira, additional, Hetland, Liv, additional, Junker, Anders, additional, Serizawa, Reza, additional, Vyberg, Mogens, additional, Galsgaard, Elisabeth, additional, and Gluud, Lise Lotte, additional

Published
2023
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22. Growth differentiation factor 15 in plasma and liver is associated with hepatic oxidative stress in non-alcoholic fatty liver disease

Author

Werge, Mikkel, primary, Grandt, Josephine, additional, Thing, Mira, additional, Hetland, Liv, additional, Rashu, Elias, additional, Jensen, Anne-Sofie Houlberg, additional, Junker, Anders, additional, Richter, Martin, additional, Møller, Søren, additional, Bendtsen, Flemming, additional, Harder, Lea Mørch, additional, Mazzoni, Gianluca, additional, Viuff, Birgitte, additional, Hvid, Henning, additional, Jørgensen, Sebastian, additional, Bendtsen, Kristian, additional, Kildegaard, Jonas, additional, Vyberg, Mogens, additional, Serizawa, Reza, additional, Galsgaard, Elisabeth, additional, Wewer Albrechtsen, Nicolai J, additional, and Gluud, Lise Lotte, additional

Published
2023
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23. Gene expression signature predicts rate of type 1 diabetes progression

Author

Suomi, Tomi, primary, Starskaia, Inna, additional, Kalim, Ubaid Ullah, additional, Rasool, Omid, additional, Jaakkola, Maria K., additional, Grönroos, Toni, additional, Välikangas, Tommi, additional, Brorsson, Caroline, additional, Mazzoni, Gianluca, additional, Bruggraber, Sylvaine, additional, Overbergh, Lut, additional, Dunger, David, additional, Peakman, Mark, additional, Chmura, Piotr, additional, Brunak, Søren, additional, Schulte, Anke M., additional, Mathieu, Chantal, additional, Knip, Mikael, additional, Lahesmaa, Riitta, additional, Elo, Laura L., additional, Gillard, Pieter, additional, Casteels, Kristina, additional, Overbergh, Lutgart, additional, Wallace, Chris, additional, Evans, Mark, additional, Thankamony, Ajay, additional, Hendriks, Emile, additional, Marcoveccchio, Loredana, additional, Tree, Timothy, additional, Morgan, Noel G., additional, Richardson, Sarah, additional, Todd, John A., additional, Wicker, Linda, additional, Mander, Adrian, additional, Dayan, Colin, additional, Alhadj Ali, Mohammad, additional, Pieber, Thomas, additional, Eizirik, Decio L., additional, Cnop, Myriam, additional, Pociot, Flemming, additional, Johannesen, Jesper, additional, Rossing, Peter, additional, Quigley, Cristina Legido, additional, Mallone, Roberto, additional, Scharfmann, Raphael, additional, Boitard, Christian, additional, Otonkoski, Timo, additional, Veijola, Riitta, additional, Oresic, Matej, additional, Toppari, Jorma, additional, Danne, Thomas, additional, Ziegler, Anette G., additional, Achenbach, Peter, additional, Rodriguez-Calvo, Teresa, additional, Solimena, Michele, additional, Bonifacio, Ezio E., additional, Speier, Stephan, additional, Holl, Reinhard, additional, Dotta, Francesco, additional, Chiarelli, Francesco, additional, Marchetti, Piero, additional, Bosi, Emanuele, additional, Cianfarani, Stefano, additional, Ciampalini, Paolo, additional, De Beaufort, Carine, additional, Dahl-Jørgensen, Knut, additional, Skrivarhaug, Torild, additional, Joner, Geir, additional, Krogvold, Lars, additional, Jarosz-Chobot, Przemka, additional, Battelino, Tadej, additional, Thorens, Bernard, additional, Gotthardt, Martin, additional, Roep, Bart O., additional, Nikolic, Tanja, additional, Zaldumbide, Arnaud, additional, Lernmark, Ake, additional, Lundgren, Marcus, additional, Costacalde, Guillaume, additional, Strube, Thorsten, additional, Nitsche, Almut, additional, Vela, Jose, additional, Von Herrath, Matthias, additional, Wesley, Johnna, additional, Napolitano-Rosen, Antonella, additional, Thomas, Melissa, additional, Schloot, Nanette, additional, Goldfine, Allison, additional, Waldron-Lynch, Frank, additional, Kompa, Jill, additional, Vedala, Aruna, additional, Hartmann, Nicole, additional, Nicolas, Gwenaelle, additional, van Rampelbergh, Jean, additional, Bovy, Nicolas, additional, Dutta, Sanjoy, additional, Soderberg, Jeannette, additional, Ahmed, Simi, additional, Martin, Frank, additional, Latres, Esther, additional, Agiostratidou, Gina, additional, Koralova, Anne, additional, Willemsen, Ruben, additional, Smith, Anne, additional, Anand, Binu, additional, Datta, Vipan, additional, Puthi, Vijith, additional, Zac-Varghese, Sagen, additional, Dias, Renuka, additional, Sundaram, Premkumar, additional, Vaidya, Bijay, additional, Patterson, Catherine, additional, Owen, Katharine, additional, Piel, Barbara, additional, Heller, Simon, additional, Randell, Tabitha, additional, Gazis, Tasso, additional, Reismen, Elise Bismuth, additional, Carel, Jean-Claude, additional, Riveline, Jean-Pierre, additional, Gautier, Jean-Francoise, additional, Andreelli, Fabrizion, additional, Travert, Florence, additional, Cosson, Emmanuel, additional, Penfornis, Alfred, additional, Petit, Catherine, additional, Feve, Bruno, additional, Lucidarme, Nadine, additional, Beressi, Jean-Paul, additional, Ajzenman, Catherina, additional, Radu, Alina, additional, Greteau-Hamoumou, Stephanie, additional, Bibal, Cecile, additional, Meissner, Thomas, additional, Heidtmann, Bettina, additional, Toni, Sonia, additional, Rami-Merhar, Birgit, additional, Eeckhout, Bart, additional, Peene, Bernard, additional, Vantongerloo, N., additional, Maes, Toon, additional, and Gommers, Leen, additional

Published
2023
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24. Gene expression signature predicts rate of type 1 diabetes progression.

Author

Suomi, Tomi, Starskaia, Inna, Kalim, Ubaid Ullah, Rasool, Omid, Jaakkola, Maria K, Grönroos, Toni, Välikangas, Tommi, Brorsson, Caroline, Mazzoni, Gianluca, Bruggraber, Sylvaine, Overbergh, Lut, Dunger, David B, Peakman, Mark, Chmura, Piotr, Brunak, Søren, Cnop, Miriam, Schulte, Anke M, Mathieu, Chantal, Knip, Mikael, Lahesmaa, Riitta, Elo, Laura L, INNODIA Consortium, Suomi, Tomi, Starskaia, Inna, Kalim, Ubaid Ullah, Rasool, Omid, Jaakkola, Maria K, Grönroos, Toni, Välikangas, Tommi, Brorsson, Caroline, Mazzoni, Gianluca, Bruggraber, Sylvaine, Overbergh, Lut, Dunger, David B, Peakman, Mark, Chmura, Piotr, Brunak, Søren, Cnop, Miriam, Schulte, Anke M, Mathieu, Chantal, Knip, Mikael, Lahesmaa, Riitta, Elo, Laura L, and INNODIA Consortium

Abstract

Type 1 diabetes is a complex heterogenous autoimmune disease without therapeutic interventions available to prevent or reverse the disease. This study aimed to identify transcriptional changes associated with the disease progression in patients with recent-onset type 1 diabetes., 0, Miriam Cnop is in the author list as part of the INNODIA Consortium, info:eu-repo/semantics/published

Published
2023

25. Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits

Author

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, Adragni, Kofi, Allesøe, Rosa Lundbye L., Artati, Anna A., Arumugam, Manimozhiyan, Atabaki-Pasdar, Naeimeh, Baltauss, Tania, Banasik, Karina, Barnett, Anna L., Baum, Patrick, Bell, Jimmy D., Beulens, Joline W., Bianzano, Susanna B., Bizzotto, Roberto, Bonnefond, Amelie, Cabrelli, Louise, Dale, Matilda, Dawed, Adem Y., de Preville, Nathalie, Dekkers, Koen F., Deshmukh, Harshal A., Dings, Christiane, Donnelly, Louise, Dutta, Avirup, Ehrhardt, Beate, Engelbrechtsen, Line, Eriksen, Rebeca, Fan, Yong, Ferrer, Jorge, Fitipaldi, Hugo, Forman, Annemette, Fritsche, Andreas, Froguel, Philippe, Gassenhuber, Johann, Gough, Stephen, Graefe-Mody, Ulrike, Grempler, Rolf, Groeneveld, Lenka, Groop, Leif, Gudmundsdóttir, Valborg, Gupta, Ramneek, Hennige, Anita M.H., Hill, Anita V., Holl, Reinhard W., Hudson, Michelle, Jacobsen, Ulrik Plesner, Jennison, Christopher, Johansen, Joachim, Jonsson, Anna, Karaderi, Tugce, Kaye, Jane, Kennedy, Gwen, Klintenberg, Maria, Kuulasmaa, Teemu, Lehr, Thorsten, Loftus, Heather, Lundgaard, Agnete Troen T., Mazzoni, Gianluca, McRobert, Nicky, McVittie, Ian, Nice, Rachel, Nicolay, Claudia, Nijpels, Giel, Palmer, Colin N., Pedersen, Helle K., Perry, Mandy H., Pomares-Millan, Hugo, Prehn, Cornelia P., Ramisch, Anna, Rasmussen, Simon, Robertson, Neil, Rodriquez, Marianne, Sackett, Peter, Scherer, Nina, Shah, Nisha, Sihinevich, Iryna, Slieker, Roderick C., Sondertoft, Nadja B., Steckel-Hamann, Birgit, Thomas, Melissa K., Thomas, Cecilia Engel E., Thomas, Elizabeth Louise L., Thorand, Barbara, Thorne, Claire E., Tillner, Joachim, Tura, Andrea, Uhlen, Mathias, van Leeuwen, Nienke, van Oort, Sabine, Verkindt, Helene, Vogt, Josef, Wad Sackett, Peter W., Wesolowska-Andersen, Agata, Whitcher, Brandon, White, Margaret W., Adamski, Jerzy, Schwenk, Jochen M., Pearson, Ewan R., Dermitzakis, Emmanouil T., Viñuela, Ana, 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, Adragni, Kofi, Allesøe, Rosa Lundbye L., Artati, Anna A., Arumugam, Manimozhiyan, Atabaki-Pasdar, Naeimeh, Baltauss, Tania, Banasik, Karina, Barnett, Anna L., Baum, Patrick, Bell, Jimmy D., Beulens, Joline W., Bianzano, Susanna B., Bizzotto, Roberto, Bonnefond, Amelie, Cabrelli, Louise, Dale, Matilda, Dawed, Adem Y., de Preville, Nathalie, Dekkers, Koen F., Deshmukh, Harshal A., Dings, Christiane, Donnelly, Louise, Dutta, Avirup, Ehrhardt, Beate, Engelbrechtsen, Line, Eriksen, Rebeca, Fan, Yong, Ferrer, Jorge, Fitipaldi, Hugo, Forman, Annemette, Fritsche, Andreas, Froguel, Philippe, Gassenhuber, Johann, Gough, Stephen, Graefe-Mody, Ulrike, Grempler, Rolf, Groeneveld, Lenka, Groop, Leif, Gudmundsdóttir, Valborg, Gupta, Ramneek, Hennige, Anita M.H., Hill, Anita V., Holl, Reinhard W., Hudson, Michelle, Jacobsen, Ulrik Plesner, Jennison, Christopher, Johansen, Joachim, Jonsson, Anna, Karaderi, Tugce, Kaye, Jane, Kennedy, Gwen, Klintenberg, Maria, Kuulasmaa, Teemu, Lehr, Thorsten, Loftus, Heather, Lundgaard, Agnete Troen T., Mazzoni, Gianluca, McRobert, Nicky, McVittie, Ian, Nice, Rachel, Nicolay, Claudia, Nijpels, Giel, Palmer, Colin N., Pedersen, Helle K., Perry, Mandy H., Pomares-Millan, Hugo, Prehn, Cornelia P., Ramisch, Anna, Rasmussen, Simon, Robertson, Neil, Rodriquez, Marianne, Sackett, Peter, Scherer, Nina, Shah, Nisha, Sihinevich, Iryna, Slieker, Roderick C., Sondertoft, Nadja B., Steckel-Hamann, Birgit, Thomas, Melissa K., Thomas, Cecilia Engel E., Thomas, Elizabeth Louise L., Thorand, Barbara, Thorne, Claire E., Tillner, Joachim, Tura, Andrea, Uhlen, Mathias, van Leeuwen, Nienke, van Oort, Sabine, Verkindt, Helene, Vogt, Josef, Wad Sackett, Peter W., Wesolowska-Andersen, Agata, Whitcher, Brandon, White, Margaret W., Adamski, Jerzy, Schwenk, Jochen M., Pearson, Ewan R., Dermitzakis, Emmanouil T., and Viñuela, Ana

Abstract

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Published
2023

26. Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models:[with Author Correction]

Author

Allesøe, Rosa Lundbye, Lundgaard, Agnete Troen, Hernández Medina, Ricardo, Aguayo-Orozco, Alejandro, Johansen, Joachim, Nissen, Jakob Nybo, Brorsson, Caroline, Mazzoni, Gianluca, Niu, Lili, Biel, Jorge Hernansanz, Brasas, Valentas, Webel, Henry, Benros, Michael Eriksen, Pedersen, Anders Gorm, Chmura, Piotr Jaroslaw, Jacobsen, Ulrik Plesner, Mari, Andrea, Koivula, Robert, Mahajan, Anubha, Vinuela, Ana, Tajes, Juan Fernandez, Sharma, Sapna, Haid, Mark, Hong, Mun-Gwan, Musholt, Petra B, De Masi, Federico, Vogt, Josef, Pedersen, Helle Krogh, Gudmundsdottir, Valborg, Jones, Angus, Kennedy, Gwen, Bell, Jimmy, Thomas, E Louise, Frost, Gary, Thomsen, Henrik, Hansen, Elizaveta, Hansen, Tue Haldor, Vestergaard, Henrik, Muilwijk, Mirthe, Blom, Marieke T, 't Hart, Leen M, Pattou, Francois, Raverdy, Violeta, Brage, Soren, Ridderstråle, Martin, Pedersen, Oluf, Hansen, Torben, Banasik, Karina, Rasmussen, Simon, Brunak, Søren, Allesøe, Rosa Lundbye, Lundgaard, Agnete Troen, Hernández Medina, Ricardo, Aguayo-Orozco, Alejandro, Johansen, Joachim, Nissen, Jakob Nybo, Brorsson, Caroline, Mazzoni, Gianluca, Niu, Lili, Biel, Jorge Hernansanz, Brasas, Valentas, Webel, Henry, Benros, Michael Eriksen, Pedersen, Anders Gorm, Chmura, Piotr Jaroslaw, Jacobsen, Ulrik Plesner, Mari, Andrea, Koivula, Robert, Mahajan, Anubha, Vinuela, Ana, Tajes, Juan Fernandez, Sharma, Sapna, Haid, Mark, Hong, Mun-Gwan, Musholt, Petra B, De Masi, Federico, Vogt, Josef, Pedersen, Helle Krogh, Gudmundsdottir, Valborg, Jones, Angus, Kennedy, Gwen, Bell, Jimmy, Thomas, E Louise, Frost, Gary, Thomsen, Henrik, Hansen, Elizaveta, Hansen, Tue Haldor, Vestergaard, Henrik, Muilwijk, Mirthe, Blom, Marieke T, 't Hart, Leen M, Pattou, Francois, Raverdy, Violeta, Brage, Soren, Ridderstråle, Martin, Pedersen, Oluf, Hansen, Torben, Banasik, Karina, Rasmussen, Simon, and Brunak, Søren

Abstract

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug-omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug-drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.

Published
2023

27. Drug dosage modifications in 24 million in-patient prescriptions covering eight years:A Danish population-wide study of polypharmacy

Author

Leal Rodríguez, Cristina, Haue, Amalie Dahl, Mazzoni, Gianluca, Eriksson, Robert, Hernansanz Biel, Jorge, Cantwell, Lisa, Westergaard, David, Belling, Kirstine G., Brunak, Søren, Leal Rodríguez, Cristina, Haue, Amalie Dahl, Mazzoni, Gianluca, Eriksson, Robert, Hernansanz Biel, Jorge, Cantwell, Lisa, Westergaard, David, Belling, Kirstine G., and Brunak, Søren

Abstract

Author summary Polypharmacy continues to grow in importance because of multimorbid, aging populations. In healthcare, polypharmacy is well-known for its detrimental consequences related to adverse events. Polypharmacy is also a key challenge included in the precision medicine agenda. So-called precision dosing is important for addressing concomitant diseases and medications, and their impact on treatment responses. In this work, we present a study aiming at investigating this problem using real-world data from ~185 million treatment episodes leading to significant statistical power across drug-cocktails. We introduce a comprehensive analysis of dosage changes aiming to identify those significant pairs that may influence each other. More than half of the identified drug pairs were associated with readmission, mortality or longer stays and we also observed major differences in relation to disease and laboratory tests. Under the premise that drug-drug interactions are manageable through patient monitoring and dosage adjustments, we collected and cross-referenced information from a wide range of clinical and bioinformatics drug-drug interaction databases that could be related to pairs associated with dosage changes. Overall, this work shows how distinct, changing dosage patterns can facilitate the identification of drug-drug interactions in the context of polypharmacy complementing longitudinal analyses of disease progression.

Published
2023

29. Multi-omics analysis reveals drivers of loss of β-cell function after newly diagnosed autoimmune type 1 diabetes: An INNODIA‡multicenter study

Author

Armenteros, Jose Juan Almagro, primary, Brorsson, Caroline, additional, Johansen, Christian Holm, additional, Banasik, Karina, additional, Mazzoni, Gianluca, additional, Moulder, Robert, additional, Hirvonen, Karoliina, additional, Suomi, Tomi, additional, Rasool, Omid, additional, Bruggraber, Sylvaine FA, additional, Marcovecchio, M Loredana, additional, Hendricks, Emile, additional, Al-Sari, Naba, additional, Mattila, Ismo, additional, Legido-Quigley, Cristina, additional, Suvitaival, Tommi, additional, Chmura, Piotr J, additional, Knip, Mikael, additional, Schulte, Anke M, additional, Lee, Jeong Heon, additional, Sebastiani, Guido, additional, Grieco, Giuseppina Emanuela, additional, Elo, Laura L, additional, Kaur, Simranjeet, additional, Pociot, Flemming, additional, Dotta, Francesco, additional, Tree, Tim, additional, Lahesmaa, Riitta, additional, Overbergh, Lut, additional, Mathieu, Chantal, additional, Peakman, Mark, additional, and Brunak, Søren, additional

Published
2023
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31. Multi-omics to predict changes during cold pressor test

Author

Kogelman, Lisette J.A., Ernst, Madeleine, Falkenberg, Katrine, Mazzoni, Gianluca, Courraud, Julie, Lundgren, Li Peng, Laursen, Susan Svane, Cohen, Arieh, Olesen, Jes, Hansen, Thomas Folkmann, Kogelman, Lisette J.A., Ernst, Madeleine, Falkenberg, Katrine, Mazzoni, Gianluca, Courraud, Julie, Lundgren, Li Peng, Laursen, Susan Svane, Cohen, Arieh, Olesen, Jes, and Hansen, Thomas Folkmann

Abstract

Background: The cold pressor test (CPT) is a widely used pain provocation test to investigate both pain tolerance and cardiovascular responses. We hypothesize, that performing multi-omic analyses during CPT gives the opportunity to home in on molecular mechanisms involved. Twenty-two females were phenotypically assessed before and after a CPT, and blood samples were taken. RNA-Sequencing, steroid profiling and untargeted metabolomics were performed. Each ‘omic level was analyzed separately at both single-feature and systems-level (principal component [PCA] and partial least squares [PLS] regression analysis) and all ‘omic levels were combined using an integrative multi-omics approach, all using the paired-sample design. Results: We showed that PCA was not able to discriminate time points, while PLS did significantly distinguish time points using metabolomics and/or transcriptomic data, but not using conventional physiological measures. Transcriptomic and metabolomic data revealed at feature-, systems- and integrative- level biologically relevant processes involved during CPT, e.g. lipid metabolism and stress response. Conclusion: Multi-omics strategies have a great potential in pain research, both at feature- and systems- level. Therefore, they should be exploited in intervention studies, such as pain provocation tests, to gain knowledge on the biological mechanisms involved in complex traits.

Published
2022

32. Multi-Omics To Predict Changes During Cold Pressor Test

Author

Kogelman, Lisette J.A., primary, Ernst, Madeleine, additional, Falkenberg, Katrine, additional, Mazzoni, Gianluca, additional, Courraud, Julie, additional, Lundgren, Li Peng, additional, Laursen, Susan Svane, additional, Cohen, Arieh, additional, Olesen, Jes, additional, and Hansen, Thomas Folkmann, additional

Published
2022
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39. Additional file 1 of Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study

Author

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.

Published
2020
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40. Additional file 2 of Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study

Author

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

Subjects
Data_FILES
Abstract

Additional file 2. Supplementary Methods. This file contains methods descriptions for omics data generation and preprocessing.

Published
2020
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41. Characterization of the endometrial transcriptome in early diestrus influencing pregnancy status in dairy cattle after transfer of in vitro-produced embryos

Author

Mazzoni, Gianluca, Pedersen, Hanne S., Rabaglino, Maria B., Hyttel, Poul, Callesen, Henrik, Kadarmideen, Haja N., Mazzoni, Gianluca, Pedersen, Hanne S., Rabaglino, Maria B., Hyttel, Poul, Callesen, Henrik, and Kadarmideen, Haja N.

Abstract

Modifications of the endometrial transcriptome at day 7 of the estrus cycle are crucial to maintain gestation after transfer of in vitro-produced (IVP) embryos, although these changes are still largely unknown. The aim of this study was to identify genes, and their related biological mechanisms, important for pregnancy establishment based on the endometrial transcriptome of recipient lactating dairy cows that become pregnant in the subsequent estrus cycle, upon transfer of IVP embryos. Endometrial biopsies were taken from Holstein Friesian cows on day 6–8 of the estrus cycle followed by embryo transfer in the following cycle. Animals were classified retrospectively as pregnant (PR, n = 8) or nonpregnant (non-PR, n = 11) cows, according to pregnancy status at 26–47 days. Extracted mRNAs from endometrial samples were sequenced with an Illumina platform to determine differentially expressed genes (DEG) between the endometrial transcriptome from PR and non-PR cows. There were 111 DEG (false discovery rate < 0.05), which were mainly related to extracellular matrix interaction, histotroph metabolic composition, prostaglandin synthesis, transforming growth factor-β signaling as well as inflammation and leukocyte activation. Comparison of these DEG with DEG identified in two public external data sets confirmed the more fertile endometrial molecular profile of PR cows. In conclusion, this study provides insights into the key early endometrial mechanisms for pregnancy establishment, after IVP embryo transfer in dairy cows.

Published
2020

42. Whole blood co-expression modules associate with metabolic traits and type 2 diabetes:an IMI-DIRECT study

Author

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, Brunak, Søren, 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

Abstract

Background: The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D. Methods: Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts. Results: We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic sig

Published
2020

43. Bovine in-vitro produced embryos:Development of embryo proper and associated membranes from day 26 to 47 of gestation

Author

Pedersen, Hanne Skovsgaard, Mazzoni, Gianluca, Pihl, Maria, Kadarmideen, Haja N., Hyttel, Poul, Callesen, Henrik, Pedersen, Hanne Skovsgaard, Mazzoni, Gianluca, Pihl, Maria, Kadarmideen, Haja N., Hyttel, Poul, and Callesen, Henrik

Abstract

Based on in-vitro produced (IVP) bovine embryos, embryo proper and embryonic/fetal membranes were studied in 12 pregnancies from day 26 to 47. The embryos/fetuses displayed external as well as internal development of organs and structures according to the expectations from comparable in-vivo studies. However, the embryonic/fetal membranes were shorter than those reported for in-vivo-derived embryos/fetuses on days 26–35 of calculated age, whereas on days 41–47 they were of comparable lengths.

Published
2020

47. WED-421 - Growth differentiation factor 15 in plasma and liver is associated with hepatic oxidative stress in non-alcoholic fatty liver disease

Author

Werge, Mikkel, Grandt, Josephine, Thing, Mira, Hetland, Liv, Rashu, Elias, Jensen, Anne-Sofie Houlberg, Junker, Anders, Richter, Martin, Møller, Søren, Bendtsen, Flemming, Harder, Lea Mørch, Mazzoni, Gianluca, Viuff, Birgitte, Hvid, Henning, Jørgensen, Sebastian, Bendtsen, Kristian, Kildegaard, Jonas, Vyberg, Mogens, Serizawa, Reza, Galsgaard, Elisabeth, Wewer Albrechtsen, Nicolai J, and Gluud, Lise Lotte

Published
2023
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50. The Dynamic Nature of Vanadyl Pyrophosphate, Catalyst for the Selective Oxidation of n-Butane to Maleic Anhydride

Author

Cortelli, Carlotta, primary, Bordes-Richard, Elisabeth, additional, Luciani, Silvia, additional, Cavani, Fabrizio, additional, Leanza, Roberto, additional, Trifirò, Ferruccio, additional, Degli Esposti, Elisa, additional, Ballarini, Nicola, additional, Mazzoni, Gianluca, additional, Brückner, Angelika, additional, and De Santi, Davide, additional

Published
2008
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