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262 results on '"Kokkola, Tarja"'

1. Role of human plasma metabolites in prediabetes and type 2 diabetes from the IMI-DIRECT study

Author

Sharma, Sapna, Dong, Qiuling, Haid, Mark, Adam, Jonathan, Bizzotto, Roberto, Fernandez-Tajes, Juan J., Jones, Angus G., Tura, Andrea, Artati, Anna, Prehn, Cornelia, Kastenmüller, Gabi, Koivula, Robert W., Franks, Paul W., Walker, Mark, Forgie, Ian M., Giordano, Giuseppe, Pavo, Imre, Ruetten, Hartmut, Dermitzakis, Manolis, McCarthy, Mark I., Pedersen, Oluf, Schwenk, Jochen M., Tsirigos, Konstantinos D., De Masi, Federico, Brunak, Soren, Viñuela, Ana, Mari, Andrea, McDonald, Timothy J., Kokkola, Tarja, Adamski, Jerzy, Pearson, Ewan R., and Grallert, Harald

Published
2024
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3. 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, Adamski, Jerzy, Schwenk, Jochen M., Pearson, Ewan R., Dermitzakis, Emmanouil T., and Viñuela, Ana

Published
2023
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4. A FinnGen pilot clinical recall study for Alzheimer’s disease

Author

Julkunen, Valtteri, Schwarz, Claudia, Kalapudas, Juho, Hallikainen, Merja, Piironen, Aino-Kaisa, Mannermaa, Arto, Kujala, Hanna, Laitinen, Timo, Kosma, Veli-Matti, Paajanen, Teemu I., Kälviäinen, Reetta, Hiltunen, Mikko, Herukka, Sanna-Kaisa, Kärkkäinen, Sari, Kokkola, Tarja, Urjansson, Mia, Perola, Markus, Palotie, Aarno, Vuoksimaa, Eero, and Runz, Heiko

Published
2023
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5. 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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6. Protective Alzheimer's disease-associated APP A673T variant predominantly decreases sAPPβ levels in cerebrospinal fluid and 2D/3D cell culture models

Author

Wittrahm, Rebekka, Takalo, Mari, Kuulasmaa, Teemu, Mäkinen, Petra M., Mäkinen, Petri, Končarević, Saša, Fartzdinov, Vadim, Selzer, Stefan, Kokkola, Tarja, Antikainen, Leila, Martiskainen, Henna, Kemppainen, Susanna, Marttinen, Mikael, Jeskanen, Heli, Rostalski, Hannah, Rahunen, Eija, Kivipelto, Miia, Ngandu, Tiia, Natunen, Teemu, Lambert, Jean-Charles, Tanzi, Rudolph E., Kim, Doo Yeon, Rauramaa, Tuomas, Herukka, Sanna-Kaisa, Soininen, Hilkka, Laakso, Markku, Pike, Ian, Leinonen, Ville, Haapasalo, Annakaisa, and Hiltunen, Mikko

Published
2023
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7. 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. Serum total TDP-43 levels are decreased in frontotemporal dementia patients with C9orf72 repeat expansion or concomitant motoneuron disease phenotype

Author

Katisko, Kasper, Huber, Nadine, Kokkola, Tarja, Hartikainen, Päivi, Krüger, Johanna, Heikkinen, Anna-Leena, Paananen, Veera, Leinonen, Ville, Korhonen, Ville E., Helisalmi, Seppo, Herukka, Sanna-Kaisa, Cantoni, Valentina, Gadola, Yasmine, Archetti, Silvana, Remes, Anne M., Haapasalo, Annakaisa, Borroni, Barbara, and Solje, Eino

Published
2022
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9. TWINGEN: protocol for an observational clinical biobank recall and biomarker cohort study to identify Finnish individuals with high risk of Alzheimer’s disease

Author

Vuoksimaa, Eero, primary, Saari, Toni T, additional, Aaltonen, Aino, additional, Aaltonen, Sari, additional, Herukka, Sanna-Kaisa, additional, Iso-Markku, Paula, additional, Kokkola, Tarja, additional, Kyttälä, Aija, additional, Kärkkäinen, Sari, additional, Liedes, Hilkka, additional, Ollikainen, Miina, additional, Palviainen, Teemu, additional, Ruotsalainen, Ilona, additional, Toivola, Auli, additional, Urjansson, Mia, additional, Vasankari, Tommi, additional, Vähä-Ypyä, Henri, additional, Forsberg, Markus M, additional, Hiltunen, Mikko, additional, Jalanko, Anu, additional, Kälviäinen, Reetta, additional, Kuopio, Teijo, additional, Lähteenmäki, Jaakko, additional, Nyberg, Pia, additional, Männikkö, Minna, additional, Serpi, Raisa, additional, Siltanen, Sanna, additional, Palotie, Aarno, additional, Kaprio, Jaakko, additional, Runz, Heiko, additional, and Julkunen, Valtteri, additional

Published
2024
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11. Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study

Author

Eriksen, Rebeca, Perez, Isabel Garcia, Posma, Joram M., Haid, Mark, Sharma, Sapna, Prehn, Cornelia, Thomas, Louise E., 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, Rutter, Femke, Teare, Harriet, Hansen, Tue H., Fernandez, Juan, Jones, Angus, Jennison, Chris, Walker, Mark, McCarthy, Mark I., Pedersen, Oluf, Ruetten, Hartmut, Forgie, Ian, Bell, Jimmy D., Pearson, Ewan R., Franks, Paul W., Adamski, Jerzy, Holmes, Elaine, and Frost, Gary

Published
2020
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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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14. The Association of Cardiometabolic, Diet and Lifestyle Parameters With Plasma Glucagon-like Peptide-1: An IMI DIRECT Study

Author

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

Published
2024
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15. 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

Author

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

Published
2019
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16. Cerebrospinal Fluid Diagnostics of Alzheimer’s Disease in Patients with Idiopathic Normal Pressure Hydrocephalus

Author

Vanninen, Aleksi, primary, Lukkarinen, Heikki, additional, Kokkola, Tarja, additional, Koivisto, Anne M., additional, Kokki, Merja, additional, Musialowicz, Tadeusz, additional, Hiltunen, Mikko, additional, Zetterberg, Henrik, additional, Leinonen, Ville, additional, Herukka, Sanna-Kaisa, additional, and Rauramaa, Tuomas, additional

Published
2023
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17. 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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18. Novel cerebrospinal fluid biomarkers correlating with shunt responsiveness in patients with idiopathic normal pressure hydrocephalus

Author

Weiner, Sophia, primary, Junkkari, Antti, additional, Sauer, Mathias, additional, Luikku, Antti, additional, Rauramaa, Tuomas, additional, Kokkola, Tarja, additional, Herukka, Sanna-Kaisa, additional, Blennow, Kaj, additional, Zetterberg, Henrik, additional, Leinonen, Ville, additional, and Gobom, Johan, additional

Published
2023
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19. Serum Cathepsin S Levels Do Not Show Alterations in Different Clinical, Neuropathological, or Genetic Subtypes of Frontotemporal Dementia Patients nor in Comparison to Healthy Control Individuals

Author

Heikkinen, Sami, primary, Huber, Nadine, additional, Katisko, Kasper, additional, Kokkola, Tarja, additional, Hartikainen, Päivi, additional, Krüger, Johanna, additional, Leinonen, Ville, additional, Korhonen, Ville E., additional, Herukka, Sanna-Kaisa, additional, Remes, Anne M., additional, Borroni, Barbara, additional, Alberici, Antonella, additional, Libri, Ilenia, additional, Solje, Eino, additional, and Haapasalo, Annakaisa, additional

Published
2023
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21. A FinnGen pilot clinical recall study for Alzheimer’s disease

Author

Julkunen, Valtteri, primary, Schwarz, Claudia, additional, Kalapudas, Juho, additional, Hallikainen, Merja, additional, Piironen, Aino-Kaisa, additional, Mannermaa, Arto, additional, Kujala, Hanna, additional, Laitinen, Timo, additional, Kosma, Veli-Matti, additional, Paajanen, Teemu I., additional, Kälviäinen, Reetta, additional, Hiltunen, Mikko, additional, Herukka, Sanna-Kaisa, additional, Kärkkäinen, Sari, additional, Kokkola, Tarja, additional, Urjansson, Mia, additional, Gen, Finn, additional, Perola, Markus, additional, Palotie, Aarno, additional, Vuoksimaa, Eero, additional, and Runz, Heiko, additional

Published
2023
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22. Concordance of Alzheimer’s Disease-Related Biomarkers Between Intraventricular and Lumbar Cerebrospinal Fluid in Idiopathic Normal Pressure Hydrocephalus

Author

Lukkarinen, Heikki, primary, Vanninen, Aleksi, additional, Tesseur, Ina, additional, Pemberton, Darrel, additional, Van Der Ark, Peter, additional, Kokkola, Tarja, additional, Herukka, Sanna-Kaisa, additional, Rauramaa, Tuomas, additional, Hiltunen, Mikko, additional, Blennow, Kaj, additional, Zetterberg, Henrik, additional, and Leinonen, Ville, additional

Published
2023
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24. Protective Alzheimer’s disease-associated APP A673T variant predominantly decreases sAPPβ levels in cerebrospinal fluid and 2D/3D cell culture models

Author

Wittrahm, Rebekka, primary, Takalo, Mari, additional, Kuulasmaa, Teemu, additional, Mäkinen, Petra M, additional, Mäkinen, Petri, additional, Končarević, Saša, additional, Fartzdinov, Vadim, additional, Selzer, Stefan, additional, Kokkola, Tarja, additional, Antikainen, Leila, additional, Martiskainen, Henna, additional, Kemppainen, Susanna, additional, Marttinen, Mikael, additional, Jeskanen, Heli, additional, Rostalski, Hannah, additional, Rahunen, Eija, additional, Kivipelto, Miia, additional, Ngandu, Tiia, additional, Natunen, Teemu, additional, Lambert, Jean-Charles, additional, Tanzi, Rudolph E, additional, Kim, Doo Yeon, additional, Rauramaa, Tuomas, additional, Herukka, Sanna-Kaisa, additional, Soininen, Hilkka, additional, Laakso, Markku, additional, Pike, Ian, additional, Leinonen, Ville, additional, Haapasalo, Annakaisa, additional, and Hiltunen, Mikko, additional

Published
2022
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27. Four groups of type 2 diabetes contribute to the etiological and clinical heterogeneity in newly diagnosed individuals: An IMI DIRECT study

Author

Wesolowska-Andersen, Agata, primary, Brorsson, Caroline A., additional, Bizzotto, Roberto, additional, Mari, Andrea, additional, Tura, Andrea, additional, Koivula, Robert, additional, Mahajan, Anubha, additional, Vinuela, Ana, additional, Tajes, Juan Fernandez, additional, Sharma, Sapna, additional, Haid, Mark, additional, Prehn, Cornelia, additional, Artati, Anna, additional, Hong, Mun-Gwan, additional, Musholt, Petra B., additional, Kurbasic, Azra, additional, De Masi, Federico, additional, Tsirigos, Kostas, additional, Pedersen, Helle Krogh, additional, Gudmundsdottir, Valborg, additional, Thomas, Cecilia Engel, additional, Banasik, Karina, additional, Jennison, Chrisopher, additional, Jones, Angus, additional, Kennedy, Gwen, additional, Bell, Jimmy, additional, Thomas, Louise, additional, Frost, Gary, additional, Thomsen, Henrik, additional, Allin, Kristine, additional, Hansen, Tue Haldor, additional, Vestergaard, Henrik, additional, Hansen, Torben, additional, Rutters, Femke, additional, Elders, Petra, additional, t’Hart, Leen, additional, Bonnefond, Amelie, additional, Canouil, Mickaël, additional, Brage, Soren, additional, Kokkola, Tarja, additional, Heggie, Alison, additional, McEvoy, Donna, additional, Hattersley, Andrew, additional, McDonald, Timothy, additional, Teare, Harriet, additional, Ridderstrale, Martin, additional, Walker, Mark, additional, Forgie, Ian, additional, Giordano, Giuseppe N., additional, Froguel, Philippe, additional, Pavo, Imre, additional, Ruetten, Hartmut, additional, Pedersen, Oluf, additional, Dermitzakis, Emmanouil, additional, Franks, Paul W., additional, Schwenk, Jochen M., additional, Adamski, Jerzy, additional, Pearson, Ewan, additional, McCarthy, Mark I., additional, and Brunak, Søren, additional

Published
2022
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28. Oxygen-18 and carbon-13 isotopes in eCO(2) and erythrocytes carbonic anhydrase activity of Finnish prediabetic population

Author

Kårlund, Anna, Kääriäinen, Teemu, Kostamo, Vili M., Kokkola, Tarja, Kolehmainen, Marjukka, Lakka, Timo A., Pihlajamäki, Jussi, Manninen, Albert, Faculty of Medicine, and University of Helsinki

Subjects
breath, INSULIN-RESISTANCE, Carbonic anhydrase, Prediabets, Breath, carbonic anhydrase, Carbon-13, oxygen-18, prediabetes, SDG 3 - Good Health and Well-being, TheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITY, carbon-13, 3121 General medicine, internal medicine and other clinical medicine, SDG 13 - Climate Action, 1182 Biochemistry, cell and molecular biology, isotope ratio, Isotope ratio, Oxygen-18
Abstract

Complex human physiological processes create the stable isotopic composition of exhaled carbon dioxide (eCO 2), measurable with noninvasive breath tests. Recently, isotope-selective breath tests utilizing natural fluctuation in 18O/ 16O isotope ratio in eCO 2 have been proposed for screening prediabetic (PD) individuals. It has been suggested that 18O/ 16O fractionation patterns reflect shifts in the activity of carbonic anhydrase (CA), an enzyme involved in the metabolic changes in the PD state. To evaluate the applicability of the breath sampling method in Finnish PD individuals, breath delta values (BDVs, %) of 18O/ 16O (δ 18O) were monitored for 120 min in real-time with a high-precision optical isotope ratio spectrometer, both in the fasting state and during a 2 h oral glucose tolerance test (2 h OGTT) with non-labeled glucose. In addition, the BDV of 13C/ 12C (δ 13C) was measured, and total erythrocyte CA activity was determined. δ 18O and CA did not demonstrate any statistically significant differences between PD and non-diabetic control (NDC) participants. Instead, δ 13C was significantly lower in PD patients in comparison to NDCs in the fasting state and at time points 90 and 120 min of the 2 h OGTT, thus indicating slightly better potential in identifying Finnish PD individuals. However, overlapping values were measured in PD participants and NDCs, and therefore, δ 13C cannot be applied as a sole measure in screening prediabetes at an individual level. Thus, because the combination of environmental and lifestyle factors and anthropometric parameters has a greater effect on glucose metabolism and CA activity in comparison to the PD state, 18O/ 16O and 13C/ 12C fractionations or CA activity did not prove to be reliable biomarkers for impaired glucose tolerance in Finnish subjects. This study was conducted under the clinicaltrials.gov ID NCT03156478.

Published
2021
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29. Inferring causal pathways between metabolic processes and liver fat accumulation: an IMI DIRECT study

Author

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

Published
2021
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30. 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

Author

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

Published
2021
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31. 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)

Author

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.

Published
2021
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32. 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

Author

Tura, Andrea, Grespan, Eleonora, Göbl, Christian S, Koivula, Robert W, Franks, Paul W, Pearson, Ewan R, Walker, Mark, Forgie, Ian M, Giordano, Giuseppe N, Pavo, Imre, Ruetten, Hartmut, Dermitzakis, Emmanouil T, McCarthy, Mark I, Pedersen, Oluf, Schwenk, Jochen M, Adamski, Jerzy, De Masi, Federico, Tsirigos, Konstantinos D, Brunak, Søren, Viñuela, Ana, Mahajan, Anubha, McDonald, Timothy J, Kokkola, Tarja, Vangipurapu, Jagadish, Cederberg, Henna, Laakso, Markku, Rutters, Femke, Elders, Petra J M, Koopman, Anitra D M, Beulens, Joline W, Ridderstråle, Martin, Hansen, Tue H, Allin, Kristine H, Hansen, Torben, Vestergaard, Henrik, Mari, Andrea, Tura, Andrea, Grespan, Eleonora, Göbl, Christian S, Koivula, Robert W, Franks, Paul W, Pearson, Ewan R, Walker, Mark, Forgie, Ian M, Giordano, Giuseppe N, Pavo, Imre, Ruetten, Hartmut, Dermitzakis, Emmanouil T, McCarthy, Mark I, Pedersen, Oluf, Schwenk, Jochen M, Adamski, Jerzy, De Masi, Federico, Tsirigos, Konstantinos D, Brunak, Søren, Viñuela, Ana, Mahajan, Anubha, McDonald, Timothy J, Kokkola, Tarja, Vangipurapu, Jagadish, Cederberg, Henna, Laakso, Markku, Rutters, Femke, Elders, Petra J M, Koopman, Anitra D M, Beulens, Joline W, Ridderstråle, Martin, Hansen, Tue H, Allin, Kristine H, Hansen, Torben, Vestergaard, Henrik, and Mari, Andrea

Abstract

Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants (N=2111) underwent 2h-75g OGTT at baseline and 48 months. HbA1c was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose, IFG; impaired glucose tolerance, IGT; HbA1c-prediabetes, IA1c), two defects (IFG+IGT, IFG+IA1c, IGT+IA1c), or all defects (IFG+IGT+IA1c). Beta-cell function (BCF) and insulin sensitivity (IS) were assessed from OGTT. At baseline, when pooling participants with isolated defects, they showed impairment in both BCF and IS compared to healthy controls. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, IGT showed lower IS, insulin secretion at reference glucose (ISRr), and insulin secretion potentiation (p<0.002). Conversely, IA1c showed higher IS and ISRr (p<0.0001). Among groups with two defects, we similarly found differences in both BCF and IS. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio >2, p<0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared to the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.

Published
2021

33. Processes Underlying Glycemic Deterioration in Type 2 Diabetes:An IMI DIRECT Study

Author

Bizzotto, Roberto, Jennison, Christopher, Jones, Angus G., Kurbasic, Azra, Tura, Andrea, Kennedy, Gwen, Bell, Jimmy D., Thomas, E. Louise, Frost, Gary, Eriksen, Rebeca, Koivula, Robert W., Brage, Soren, Kaye, Jane, Hattersley, Andrew T., Heggie, Alison, McEvoy, Donna, 't Hart, Leen M., Beulens, Joline W., Elders, Petra, Musholt, Petra B., Ridderstrale, Martin, Hansen, Tue H., Allin, Kristine H., Hansen, Torben, Vestergaard, Henrik, Lundgaard, Agnete T., Thomsen, Henrik S., De Masi, Federico, Tsirigos, Konstantinos D., Brunak, Søren, Vinuela, Ana, Mahajan, Anubha, McDonald, Timothy J., Kokkola, Tarja, Forgie, Ian M., Giordano, Giuseppe N., Pavo, Imre, Ruetten, Hartmut, Dermitzakis, Emmanouil, McCarthy, Mark I., Pedersen, Oluf, Schwenk, Jochen M., Adamski, Jerzy, Franks, Paul W., Walker, Mark, Pearson, Ewan R., Mari, Andrea, Bizzotto, Roberto, Jennison, Christopher, Jones, Angus G., Kurbasic, Azra, Tura, Andrea, Kennedy, Gwen, Bell, Jimmy D., Thomas, E. Louise, Frost, Gary, Eriksen, Rebeca, Koivula, Robert W., Brage, Soren, Kaye, Jane, Hattersley, Andrew T., Heggie, Alison, McEvoy, Donna, 't Hart, Leen M., Beulens, Joline W., Elders, Petra, Musholt, Petra B., Ridderstrale, Martin, Hansen, Tue H., Allin, Kristine H., Hansen, Torben, Vestergaard, Henrik, Lundgaard, Agnete T., Thomsen, Henrik S., De Masi, Federico, Tsirigos, Konstantinos D., Brunak, Søren, Vinuela, Ana, Mahajan, Anubha, McDonald, Timothy J., Kokkola, Tarja, Forgie, Ian M., Giordano, Giuseppe N., Pavo, Imre, Ruetten, Hartmut, Dermitzakis, Emmanouil, McCarthy, Mark I., Pedersen, Oluf, Schwenk, Jochen M., Adamski, Jerzy, Franks, Paul W., Walker, Mark, Pearson, Ewan R., and Mari, Andrea

Abstract

OBJECTIVEWe investigated the processes underlying glycemic deterioration in type 2 diabetes (T2D).RESEARCH DESIGN AND METHODSA total of 732 recently diagnosed patients with T2D from the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) study were extensively phenotyped over 3 years, including measures of insulin sensitivity (OGIS), beta-cell glucose sensitivity (GS), and insulin clearance (CLIm) from mixed meal tests, liver enzymes, lipid profiles, and baseline regional fat from MRI. The associations between the longitudinal metabolic patterns and HbA(1c) deterioration, adjusted for changes in BMI and in diabetes medications, were assessed via stepwise multivariable linear and logistic regression.RESULTSFaster HbA(1c) progression was independently associated with faster deterioration of OGIS and GS and increasing CLIm; visceral or liver fat, HDL-cholesterol, and triglycerides had further independent, though weaker, roles (R-2 = 0.38). A subgroup of patients with a markedly higher progression rate (fast progressors) was clearly distinguishable considering these variables only (discrimination capacity from area under the receiver operating characteristic = 0.94). The proportion of fast progressors was reduced from 56% to 8-10% in subgroups in which only one trait among OGIS, GS, and CLIm was relatively stable (odds ratios 0.07-0.09). T2D polygenic risk score and baseline pancreatic fat, glucagon-like peptide 1, glucagon, diet, and physical activity did not show an independent role.CONCLUSIONSDeteriorating insulin sensitivity and beta-cell function, increasing insulin clearance, high visceral or liver fat, and worsening of the lipid profile are the crucial factors mediating glycemic deterioration of patients with T2D in the initial phase of the disease. Stabilization of a single trait among insulin sensitivity, beta-cell function, and insulin clearance may be relevant to prevent

Published
2021

35. GFAP as a biomarker in frontotemporal dementia and primary psychiatric disorders: diagnostic and prognostic performance

Author

Katisko, Kasper, primary, Cajanus, Antti, additional, Huber, Nadine, additional, Jääskeläinen, Olli, additional, Kokkola, Tarja, additional, Kärkkäinen, Virve, additional, Rostalski, Hannah, additional, Hartikainen, Paivi, additional, Koivisto, Anne M, additional, Hannonen, Sanna, additional, Lehtola, Juha-Matti, additional, Korhonen, Ville E, additional, Helisalmi, Seppo, additional, Koivumaa-Honkanen, Heli, additional, Herukka, Sanna-Kaisa, additional, Remes, Anne M, additional, Solje, Eino, additional, and Haapasalo, Annakaisa, additional

Published
2021
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36. The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes: an IMI DIRECT study

Author

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

Subjects
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.

Published
2020

37. Predicting and elucidating the etiology of fatty liver disease:A machine learning modeling and validation study in the IMI DIRECT cohorts

Author

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.

Published
2020
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38. 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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39. 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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40. Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk:An IMI DIRECT study

Author

Eriksen, Rebeca, Perez, Isabel Garcia, Posma, Joram M, Haid, Mark, Sharma, Sapna, Prehn, Cornelia, Thomas, Louise E, 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, Rutter, Femke, Teare, Harriet, Hansen, Tue H, Fernandez, Juan, Jones, Angus, Jennison, Chris, Walker, Mark, McCarthy, Mark I, Pedersen, Oluf, Ruetten, Hartmut, Forgie, Ian, Bell, Jimmy D, Pearson, Ewan R, Franks, Paul W, Adamski, Jerzy, Holmes, Elaine, Frost, Gary, Eriksen, Rebeca, Perez, Isabel Garcia, Posma, Joram M, Haid, Mark, Sharma, Sapna, Prehn, Cornelia, Thomas, Louise E, 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, Rutter, Femke, Teare, Harriet, Hansen, Tue H, Fernandez, Juan, Jones, Angus, Jennison, Chris, Walker, Mark, McCarthy, Mark I, Pedersen, Oluf, Ruetten, Hartmut, Forgie, Ian, Bell, Jimmy D, Pearson, Ewan R, Franks, Paul W, Adamski, Jerzy, Holmes, Elaine, and Frost, Gary

Abstract

BACKGROUND: Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D.METHODS: We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (Tpred) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous Tpred score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models.FINDINGS: A higher Tpred score was associated with healthier diets high in wholegrain (β=3.36 g, 95% CI 0.31, 6.40 and β=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (β=-75.53 kcal, 95% CI -144.71, -2.35 and β=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (β=-0.92 g, 95% CI -1.56, -0.28 and β=-0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher Tpred score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (β=0.07 mmol/L, 95% CI 0.03, 0.1), (β=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (β=-0.1 mmol/L, 95% CI -0.2, -0.03), (β=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the Tpred score was negatively associated with liver fat (β=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (β=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (β=-0.2 mmol/L, 95% CI -0.4, -0.05) an

Published
2020

41. The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes:an IMI DIRECT study

Author

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 J A, Thomas, E Louise, Vinuela, Ana, Mahajan, Anubha, McCarthy, Mark I, Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, Pavo, Imre, Franks, Paul W, 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 J A, Thomas, E Louise, Vinuela, Ana, Mahajan, Anubha, McCarthy, Mark I, Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, Pavo, Imre, and Franks, Paul W

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

Published
2020

42. The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes: an IMI DIRECT study

Author

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 J.A., Thomas, E. Louise, Vinuela, Ana, Mahajan, Anubha, McCarthy, Mark I., Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, Pavo, Imre, Franks, Paul W., 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 J.A., Thomas, E. Louise, Vinuela, Ana, Mahajan, Anubha, McCarthy, Mark I., Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, Pavo, Imre, and Franks, Paul W.

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 suppo

Published
2020

43. 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

44. Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes:An IMI-DIRECT study

Author

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., Walker, Mark, Heggie, Alison, McDonald, Timothy J., Perry, Mandy H., de Masi, Federico, Brunak, Søren, Mahajan, Anubha, Giordano, Giuseppe N., Kokkola, Tarja, Dermitzakis, Emmanouil, Viñuela, Ana, Pedersen, Oluf, Schwenk, Jochen M., Adamski, Jurek, Teare, Harriet J.A., Pearson, Ewan R., Franks, Paul W., Hart, Leen M.t., Rutters, Femke, 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., Walker, Mark, Heggie, Alison, McDonald, Timothy J., Perry, Mandy H., de Masi, Federico, Brunak, Søren, Mahajan, Anubha, Giordano, Giuseppe N., Kokkola, Tarja, Dermitzakis, Emmanouil, Viñuela, Ana, Pedersen, Oluf, Schwenk, Jochen M., Adamski, Jurek, Teare, Harriet J.A., Pearson, Ewan R., Franks, Paul W., Hart, Leen M.t., and Rutters, Femke

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.

Published
2020

46. Processes Underlying Glycemic Deterioration in Type 2 Diabetes: An IMI DIRECT Study

Author

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

Published
2020
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47. Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts

Author

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

Published
2020
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49. Predicting and elucidating the etiology of fatty liver disease using a machine learning-based approach: an IMI DIRECT study

Author

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

Published
2020
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50. Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration

Author

Wilman, Henry R., Parisinos, Constantinos A., Atabaki-Pasdar, Naeimeh, Kelly, Matt, Thomas, E. Louise, Neubauer, Stefan, 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, and Pomares-Millan, Hugo

Subjects
Genome-wide association study, Magnetic resonance imaging, Metabolism, Iron, Genetics, Metabolic syndrome
Abstract

Background & Aims: Excess liver iron content is common and is linked to the risk of hepatic and extrahepatic diseases. We aimed to identify genetic variants influencing liver iron content and use genetics to understand its link to other traits and diseases. Methods: First, we performed a genome-wide association study (GWAS) in 8,289 individuals from UK Biobank, whose liver iron level had been quantified by magnetic resonance imaging, before validating our findings in an independent cohort (n = 1,513 from IMI DIRECT). Second, we used Mendelian randomisation to test the causal effects of 25 predominantly metabolic traits on liver iron content. Third, we tested phenome-wide associations between liver iron variants and 770 traits and disease outcomes. Results: We identified 3 independent genetic variants (rs1800562 [C282Y] and rs1799945 [H63D] in HFE and rs855791 [V736A] in TMPRSS6) associated with liver iron content that reached the GWAS significance threshold (p

Published
2019
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