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

Autor: 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, 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, Brunak, S. ren, Froguel, Philippe, Thomas, Cecilia Engel, Haussler, Ragna, Beulens, Joline, Rutters, Femke, Nijpels, Giel, van Oort, Sabine, Groeneveld, Lenka, Elders, Petra, Giorgino, Toni, Rodriquez, Marianne, Nice, Rachel, Perry, Mandy, Bianzano, Susanna, Graefe-Mody, Ulrike, Hennige, Anita, Grempler, Rolf, Baum, Patrick, Stærfeldt, Hans-Henrik, Shah, Nisha, Teare, Harriet, Ehrhardt, Beate, Tillner, Joachim, Dings, Christiane, Lehr, Thorsten, Scherer, Nina, Sihinevich, Iryna, Cabrelli, Louise, Loftus, Heather, Bizzotto, Roberto, Tura, Andrea, Dekkers, Koen, van Leeuwen, Nienke, Groop, Leif, Slieker, Roderick, Ramisch, Anna, Jennison, Christopher, McVittie, Ian, Frau, Francesca, Steckel-Hamann, Birgit, Adragni, Kofi, Thomas, Melissa, Pasdar, Naeimeh Atabaki, Fitipaldi, Hugo, Kurbasic, Azra, Mutie, Pascal, Pomares-Millan, Hugo, Bonnefond, Amelie, Canouil, Mickael, Caiazzo, Robert, Verkindt, Helene, Holl, Reinhard, Kuulasmaa, Teemu, Deshmukh, Harshal, Cederberg, Henna, Laakso, Markku, Vangipurapu, Jagadish, Dale, Matilda, Thorand, Barbara, Nicolay, Claudia, Fritsche, Andreas, Hill, Anita, Hudson, Michelle, Thorne, Claire, Allin, Kristine, Arumugam, Manimozhiyan, Jonsson, Anna, Engelbrechtsen, Line, Forman, Annemette, Dutta, Avirup, Sondertoft, Nadja, Fan, Yong, Gough, Stephen, Robertson, Neil, McRobert, Nicky, Wesolowska-Andersen, Agata, Brown, Andrew, Davtian, David, Dawed, Adem, Donnelly, Louise, Palmer, Colin, White, Margaret, Ferrer, Jorge, Whitcher, Brandon, Artati, Anna, Prehn, Cornelia, Adam, Jonathan, Grallert, Harald, Gupta, Ramneek, Sackett, Peter Wad, Nilsson, Birgitte, Tsirigos, Konstantinos, Eriksen, Rebeca, Jablonka, Bernd, Uhlen, Mathias, Gassenhuber, Johann, Baltauss, Tania, de Preville, Nathalie, Klintenberg, Maria, Abdalla, Moustafa
Přispěvatelé: Lundgaard, Agnete Troen [0000-0001-7447-6560], Hernández Medina, Ricardo [0000-0001-6373-2362], Johansen, Joachim [0000-0001-7052-1870], Niu, Lili [0000-0003-4571-4368], Biel, Jorge Hernansanz [0000-0002-3125-2951], Benros, Michael Eriksen [0000-0003-4939-9465], Pedersen, Anders Gorm [0000-0001-9650-8965], Jacobsen, Ulrik Plesner [0000-0001-9181-6854], Koivula, Robert [0000-0002-1646-4163], Vinuela, Ana [0000-0003-3771-8537], Haid, Mark [0000-0001-6118-1333], Hong, Mun-Gwan [0000-0001-8603-8293], Kennedy, Gwen [0000-0002-9856-3236], Thomas, E Louise [0000-0003-4235-4694], Frost, Gary [0000-0003-0529-6325], Hansen, Tue Haldor [0000-0001-5948-8993], Kaye, Jane [0000-0002-7311-4725], Hattersley, Andrew [0000-0001-5620-473X], Ridderstråle, Martin [0000-0002-3270-9167], Pedersen, Oluf [0000-0002-3321-3972], Hansen, Torben [0000-0001-8748-3831], Schwenk, Jochen M [0000-0001-8141-8449], Rasmussen, Simon [0000-0001-6323-9041], Brunak, Søren [0000-0003-0316-5866], Apollo - University of Cambridge Repository, Epidemiology and Data Science, ACS - Diabetes & metabolism, APH - Health Behaviors & Chronic Diseases, General practice, ACS - Heart failure & arrhythmias, APH - Aging & Later Life, Graduate School, APH - Methodology
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Allesøe, R L, Lundgaard, A T, Hernández Medina, R, Aguayo-Orozco, A, Johansen, J, Nissen, J N, Brorsson, C, Mazzoni, G, Niu, L, Biel, J H, Brasas, V, Webel, H, Benros, M E, Pedersen, A G, Chmura, P J, Jacobsen, U P, Mari, A, Koivula, R, Mahajan, A, Vinuela, A, Tajes, J F, Sharma, S, Haid, M, Hong, M-G, Musholt, P B, de Masi, F, Vogt, J, Pedersen, H K, Gudmundsdottir, V, Jones, A, Kennedy, G, Bell, J, Thomas, E L, Frost, G, Thomsen, H, Hansen, E, Hansen, T H, Vestergaard, H, Muilwijk, M, Blom, M T, ‘t Hart, L M, Pattou, F, Raverdy, V, Brage, S, Kokkola, T, Heggie, A, McEvoy, D, Mourby, M, Kaye, J, Hattersley, A, McDonald, T, Ridderstråle, M, Walker, M, Forgie, I, Giordano, G N, Pavo, I, Ruetten, H, Pedersen, O, Hansen, T, Dermitzakis, E, Franks, P W, Schwenk, J M, Adamski, J, McCarthy, M I, Pearson, E, Banasik, K, Rasmussen, S, Brunak, S R, Froguel, P, Thomas, C E, Haussler, R, Beulens, J, Rutters, F, Nijpels, G, van Oort, S, Groeneveld, L, Elders, P, Giorgino, T, Rodriquez, M, Nice, R, Perry, M, Bianzano, S, Graefe-Mody, U, Hennige, A, Grempler, R, Baum, P, Stærfeldt, H-H, Shah, N, Teare, H, Ehrhardt, B, Tillner, J, Dings, C, Lehr, T, Scherer, N, Sihinevich, I, Cabrelli, L, Loftus, H, Bizzotto, R, Tura, A, Dekkers, K, van Leeuwen, N, Groop, L, Slieker, R, Ramisch, A, Jennison, C, McVittie, I, Frau, F, Steckel-Hamann, B, Adragni, K, Thomas, M, Pasdar, N A, Fitipaldi, H, Kurbasic, A, Mutie, P, Pomares-Millan, H, Bonnefond, A, Canouil, M, Caiazzo, R, Verkindt, H, Holl, R, Kuulasmaa, T, Deshmukh, H, Cederberg, H, Laakso, M, Vangipurapu, J, Dale, M, Thorand, B, Nicolay, C, Fritsche, A, Hill, A, Hudson, M, Thorne, C, Allin, K, Arumugam, M, Jonsson, A, Engelbrechtsen, L, Forman, A, Dutta, A, Sondertoft, N, Fan, Y, Gough, S, Robertson, N, McRobert, N, Wesolowska-Andersen, A, Brown, A, Davtian, D, Dawed, A, Donnelly, L, Palmer, C, White, M, Ferrer, J, Whitcher, B, Artati, A, Prehn, C, Adam, J, Grallert, H, Gupta, R, Sackett, P W, Nilsson, B, Tsirigos, K, Eriksen, R, Jablonka, B, Uhlen, M, Gassenhuber, J, IMI DIRECT Consortium, Baltauss, T, de Preville, N, Klintenberg, M & Abdalla, M 2023, ' Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models ', Nature Biotechnology, vol. 41, no. 3, pp. 399-408 . https://doi.org/10.1038/s41587-022-01520-x
Nature Biotechnology, 41(3), 399-408. Nature Publishing Group
Allesøe, R L, Lundgaard, A T, Hernández Medina, R, Aguayo-Orozco, A, Johansen, J, Nissen, J N, Brorsson, C, Mazzoni, G, Niu, L, Biel, J H, Brasas, V, Webel, H, Benros, M E, Pedersen, A G, Chmura, P J, Jacobsen, U P, Mari, A, Koivula, R, Mahajan, A, Vinuela, A, Tajes, J F, Sharma, S, Haid, M, Hong, M G, Musholt, P B, De Masi, F, Vogt, J, Pedersen, H K, Gudmundsdottir, V, Jones, A, Kennedy, G, Bell, J, Thomas, E L, Frost, G, Thomsen, H, Hansen, E, Hansen, T H, Vestergaard, H, Muilwijk, M, Blom, M T, ‘t Hart, L M, Hansen, T, Schwenk, J M, Adamski, J, McCarthy, M I, Pearson, E, Banasik, K, Rasmussen, S, Brunak, S & Franks, P W 2023, ' Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models ', Nature Biotechnology, vol. 41, no. 3, pp. 399-408 . https://doi.org/10.1038/s41587-022-01520-x
Nature Biotechnology, 41, 399-408. NATURE PORTFOLIO
Nature biotechnology, 41(3), 399-408. Nature Publishing Group
ISSN: 1087-0156
Popis: 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.
Databáze: OpenAIRE
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