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45 results on '"Verkindt, Helene"'

1. Data-driven cluster analysis identifies distinct types of metabolic dysfunction-associated steatotic liver disease

Author

Raverdy, Violeta, Tavaglione, Federica, Chatelain, Estelle, Lassailly, Guillaume, De Vincentis, Antonio, Vespasiani-Gentilucci, Umberto, Qadri, Sami F., Caiazzo, Robert, Verkindt, Helene, Saponaro, Chiara, Kerr-Conte, Julie, Baud, Gregory, Marciniak, Camille, Chetboun, Mikael, Oukhouya-Daoud, Naima, Blanck, Samuel, Vandel, Jimmy, Olsson, Lisa, Chakaroun, Rima, Gnemmi, Viviane, Leteurtre, Emmanuelle, Lefebvre, Philippe, Haas, Joel T., Yki-Järvinen, Hannele, Francque, Sven, Staels, Bart, Le Roux, Carel W., Tremaroli, Valentina, Mathurin, Philippe, Marot, Guillemette, Romeo, Stefano, and Pattou, François

Published
2024
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2. Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study

Author

Saux, Patrick, Bauvin, Pierre, Raverdy, Violeta, Teigny, Julien, Verkindt, Hélène, Soumphonphakdy, Tomy, Debert, Maxence, Jacobs, Anne, Jacobs, Daan, Monpellier, Valerie, Lee, Phong Ching, Lim, Chin Hong, Andersson-Assarsson, Johanna C, Carlsson, Lena, Svensson, Per-Arne, Galtier, Florence, Dezfoulian, Guelareh, Moldovanu, Mihaela, Andrieux, Severine, Couster, Julien, Lepage, Marie, Lembo, Erminia, Verrastro, Ornella, Robert, Maud, Salminen, Paulina, Mingrone, Geltrude, Peterli, Ralph, Cohen, Ricardo V, Zerrweck, Carlos, Nocca, David, Roux, Carel W Le, Caiazzo, Robert, Preux, Philippe, and Pattou, François

Subjects
Computer Science - Machine Learning, Statistics - Applications
Abstract

Background Weight loss trajectories after bariatric surgery vary widely between individuals, and predicting weight loss before the operation remains challenging. We aimed to develop a model using machine learning to provide individual preoperative prediction of 5-year weight loss trajectories after surgery. Methods In this multinational retrospective observational study we enrolled adult participants (aged $\ge$18 years) from ten prospective cohorts (including ABOS [NCT01129297], BAREVAL [NCT02310178], the Swedish Obese Subjects study, and a large cohort from the Dutch Obesity Clinic [Nederlandse Obesitas Kliniek]) and two randomised trials (SleevePass [NCT00793143] and SM-BOSS [NCT00356213]) in Europe, the Americas, and Asia, with a 5 year followup after Roux-en-Y gastric bypass, sleeve gastrectomy, or gastric band. Patients with a previous history of bariatric surgery or large delays between scheduled and actual visits were excluded. The training cohort comprised patients from two centres in France (ABOS and BAREVAL). The primary outcome was BMI at 5 years. A model was developed using least absolute shrinkage and selection operator to select variables and the classification and regression trees algorithm to build interpretable regression trees. The performances of the model were assessed through the median absolute deviation (MAD) and root mean squared error (RMSE) of BMI. Findings10 231 patients from 12 centres in ten countries were included in the analysis, corresponding to 30 602 patient-years. Among participants in all 12 cohorts, 7701 (75$\bullet$3%) were female, 2530 (24$\bullet$7%) were male. Among 434 baseline attributes available in the training cohort, seven variables were selected: height, weight, intervention type, age, diabetes status, diabetes duration, and smoking status. At 5 years, across external testing cohorts the overall mean MAD BMI was 2$\bullet$8 kg/m${}^2$ (95% CI 2$\bullet$6-3$\bullet$0) and mean RMSE BMI was 4$\bullet$7 kg/m${}^2$ (4$\bullet$4-5$\bullet$0), and the mean difference between predicted and observed BMI was-0$\bullet$3 kg/m${}^2$ (SD 4$\bullet$7). This model is incorporated in an easy to use and interpretable web-based prediction tool to help inform clinical decision before surgery. InterpretationWe developed a machine learning-based model, which is internationally validated, for predicting individual 5-year weight loss trajectories after three common bariatric interventions., Comment: The Lancet Digital Health, 2023

Published
2023
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4. Time-of-day-dependent variation of the human liver transcriptome and metabolome is disrupted in MASLD

Author

Johanns, Manuel, Haas, Joel T., Raverdy, Violetta, Vandel, Jimmy, Chevalier-Dubois, Julie, Guille, Loic, Derudas, Bruno, Legendre, Benjamin, Caiazzo, Robert, Verkindt, Helene, Gnemmi, Viviane, Leteurtre, Emmanuelle, Derhourhi, Mehdi, Bonnefond, Amélie, Froguel, Philippe, Eeckhoute, Jérôme, Lassailly, Guillaume, Mathurin, Philippe, Pattou, François, Staels, Bart, and Lefebvre, Philippe

Published
2024
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5. Data-driven subgroups of type 2 diabetes, metabolic response, and renal risk profile after bariatric surgery: a retrospective cohort study

Author

Raverdy, Violeta, Cohen, Ricardo V, Caiazzo, Robert, Verkindt, Helene, Petry, Tarissa Beatrice Zanata, Marciniak, Camille, Legendre, Benjamin, Bauvin, Pierre, Chatelain, Estelle, Duhamel, Alain, Drumez, Elodie, Oukhouya-Daoud, Naima, Chetboun, Mikael, Baud, Gregory, Ahlqvist, Emma, Wierup, Niels, Asplund, Olof, Laferrère, Blandine, Groop, Leif, and Pattou, FranÇois

Published
2022
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7. NASH-related increases in plasma bile acid levels depend on insulin resistance

Author

Grzych, Guillaume, Chávez-Talavera, Oscar, Descat, Amandine, Thuillier, Dorothée, Verrijken, An, Kouach, Mostafa, Legry, Vanessa, Verkindt, Hélène, Raverdy, Violeta, Legendre, Benjamin, Caiazzo, Robert, Van Gaal, Luc, Goossens, Jean-Francois, Paumelle, Réjane, Francque, Sven, Pattou, François, Haas, Joel T., Tailleux, Anne, and Staels, Bart

Published
2021
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11. Genetic evidence of causal relation between intestinal glucose absorption and early postprandial glucose response: a Mendelian randomization study

Author

Peschard, Simon, primary, Raverdy, Violeta, primary, Bauvin, Pierre, primary, Goutchtat, Rebecca, primary, Touche, Veronique, primary, Derudas, Bruno, primary, Gheeraert, Celine, primary, Dubois-Chevalier, Julie, primary, Caiazzo, Robert, primary, Baud, Gregory, primary, Marciniak, Camille, primary, Verkindt, Helene, primary, Oukhouya Daoud, Naima, primary, W Le Roux, Carel, primary, Lefebvre, Philippe, primary, Staels, Bart, primary, Lestavel, Sophie, primary, and Pattou, François, primary

Published
2024
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12. 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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13. Genetic Evidence of Causal Relation Between Intestinal Glucose Absorption and Early Postprandial Glucose Response: A Mendelian Randomization Study.

Author

Peschard, Simon, Raverdy, Violeta, Bauvin, Pierre, Goutchtat, Rebecca, Touche, Veronique, Derudas, Bruno, Gheeraert, Celine, Dubois-Chevalier, Julie, Caiazzo, Robert, Baud, Gregory, Marciniak, Camille, Verkindt, Helene, Oukhouya Daoud, Naima, Le Roux, Carel W., Lefebvre, Philippe, Staels, Bart, Lestavel, Sophie, and Pattou, François

Subjects
HYPERGLYCEMIA, INTESTINAL absorption, GLUCOSE, GENE expression, GLUCOSE tolerance tests, TYPE 2 diabetes
Abstract

The postprandial glucose response is an independent risk factor for type 2 diabetes. Observationally, early glucose response after an oral glucose challenge has been linked to intestinal glucose absorption, largely influenced by the expression of sodium–glucose cotransporter 1 (SGLT1). This study uses Mendelian randomization (MR) to estimate the causal effect of intestinal SGLT1 expression on early glucose response. Involving 1,547 subjects with class II/III obesity from the Atlas Biologique de l'Obésité Sévère cohort, the study uses SGLT1 genotyping, oral glucose tolerance tests, and jejunal biopsies to measure SGLT1 expression. A loss-of-function SGLT1 haplotype serves as the instrumental variable, with intestinal SGLT1 expression as the exposure and the change in 30-min postload glycemia from fasting glycemia (Δ30 glucose) as the outcome. Results show that 12.8% of the 1,342 genotyped patients carried the SGLT1 loss-of-function haplotype, associated with a mean Δ30 glucose reduction of −0.41 mmol/L and a significant decrease in intestinal SGLT1 expression. The observational study links a 1-SD decrease in SGLT1 expression to a Δ30 glucose reduction of −0.097 mmol/L. MR analysis parallels these findings, associating a statistically significant reduction in genetically instrumented intestinal SGLT1 expression with a Δ30 glucose decrease of −0.353. In conclusion, the MR analysis provides genetic evidence that reducing intestinal SGLT1 expression causally lowers early postload glucose response. This finding has a potential translational impact on managing early glucose response to prevent or treat type 2 diabetes Article Highlights: Loss-of-function variant of SGLT1 is associated with reduced intestinal SGLT1 expression and early postload glucose response. Mendelian randomization supports the causal relationship between intestinal glucose absorption and postprandial glucose. Modulating intestinal SGLT1 expression/function is a promising avenue for the prevention and treatment of type 2 diabetes. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Combining diabetes, sex, and menopause as meaningful clinical features associated with NASH and liver fibrosis in individuals with class II and III obesity: A retrospective cohort study

Author

Raverdy, Violeta, primary, Chatelain, Estelle, additional, Lasailly, Guillaume, additional, Caiazzo, Robert, additional, Vandel, Jimmy, additional, Verkindt, Helene, additional, Marciniak, Camille, additional, Legendre, Benjamin, additional, Bauvin, Pierre, additional, Oukhouya‐Daoud, Naima, additional, Baud, Gregory, additional, Chetboun, Mikael, additional, Vantyghem, Marie‐Christine, additional, Gnemmi, Viviane, additional, Leteurtre, Emmanuelle, additional, Staels, Bart, additional, Lefebvre, Philippe, additional, Mathurin, Philippe, additional, Marot, Guillemette, additional, and Pattou, Francois, additional

Published
2023
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15. Time-of-day-dependent variation of the human liver transcriptome and metabolome is disrupted in MASLD

Author

Johanns, Manuel, primary, Haas, Joel T., additional, Raverdy, Violetta, additional, Vandel, Jimmy, additional, Chevalier-Dubois, Julie, additional, Guille, Loic, additional, Derudas, Bruno, additional, Legendre, Benjamin, additional, Caiazzo, Robert, additional, Verkindt, Helene, additional, Gnemmi, Viviane, additional, Leteurtre, Emmanuelle, additional, Derhourhi, Mehdi, additional, Bonnefond, Amélie, additional, Froguel, Philippe, additional, Eeckhoute, Jérôme, additional, Lassailly, Guillaume, additional, Mathurin, Philippe, additional, Pattou, François, additional, Staels, Bart, additional, and Lefebvre, Philippe, additional

Published
2023
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19. Time-of-day-dependent variation of the hepatic transcriptome and metabolome is disrupted in non-alcoholic fatty liver disease patients

Author

JOHANNS, MANUEL, primary, HAAS, JOEL T, additional, RAVERDY, VIOLETA, additional, VANDEL, JIMMY, additional, CHEVALIER-DUBOIS, Julie, additional, GUILLE, LOIC, additional, DERUDAS, BRUNO, additional, LEGENDRE, BENJAMIN, additional, CAIAZZO, ROBERT, additional, VERKINDT, HELENE, additional, GNEMMI, VIVIANE, additional, LETEURTRE, EMMANUELLE, additional, DERHOUDI, MEDHI, additional, BONNEFOND, AMELIE, additional, FROGUEL, PHILIPPE, additional, Eeckhoute, Jerome, additional, LASSAILLY, GUILLAUME, additional, MATHURIN, PHILIPPE, additional, PATTOU, FRANCOIS, additional, Staels, Bart, additional, and LEFEBVRE, PHILIPPE, additional

Published
2023
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20. 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

21. Hepatic transcriptomic signatures of statin treatment are associated with impaired glucose homeostasis in severely obese patients

Author

Margerie, Daniel, Lefebvre, Philippe, Raverdy, Violeta, Schwahn, Uwe, Ruetten, Hartmut, Larsen, Philip, Duhamel, Alain, Labreuche, Julien, Thuillier, Dorothée, Derudas, Bruno, Gheeraert, Céline, Dehondt, Hélène, Dhalluin, Quentin, Alexandre, Jérémy, Caiazzo, Robert, Nesslany, Pamela, Verkindt, Helene, Pattou, François, and Staels, Bart

Published
2019
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24. 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, 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, 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, and APH - Methodology

Subjects
Biomedical Engineering, Type 2 diabetes, Bioengineering, Applied Microbiology and Biotechnology, Deep Learning, SDG 3 - Good Health and Well-being, Diabetes Mellitus, Type 2, Machine learning, Molecular Medicine, Humans, Data integration, IMI DIRECT Consortium, Systems biology, Algorithms, Biotechnology
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
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30. JVS-1105; No. of Pages 11

Author

D Quilliot, M Coupaye, C Ciangura, S Czernichow, A Sallé, B Gaborit, M Alligier, P.-L Nguyen-Thi, J Dargent, S Msika, L Brunaud, Bernard, Céline, Coueffe, Xaviera, Verkindt, Helene, Topart, Philippe, Thibault, Ronan, Thereaux, Jérémie, Sallé, Agnes, Roussel, Anne-Marie, Ritz, Patrick, Pradignac, Alain, Piguel, Xavier, Matussiere, Yann, Ledoux, Séverine, Moullec, Nathalie Le, Laville, Martine, Marie-Laure Lalanne-Mistrih, Krempf, Michel, Johanet, Hubert, Gugenheim, Jean, Guedeney, Alexandra, Brunaud, Laurent, Marie-Claude Brindisi, Anne-Laure Borel, Avignon, Antoine, Anduze-Acher, Yves, and Andrieux, Séverine

Published
2020
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31. 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, 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, Koopman, Anitra, Rutters, Femke, Beulens, Joline, Groeneveld, Lenka, Thomas, Louise, Whitcher, Brandon, Mahajan, Anubha, Hingorani, Aroon D., Patel, Riyaz S., Hemingway, Harry, Franks, Paul W., Bell, Jimmy D., Banerjee, Rajarshi, Yaghootkar, Hanieh, Epidemiology and Data Science, APH - Health Behaviors & Chronic Diseases, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, and APH - Aging & Later Life

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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33. A452 Differential Unfolded Protein Response expression in skeletal muscle from patients with obesity with normal or impaired glucose tolerance before and after bariatric surgery

Author

Marciniak, Camille, primary, Duhem, Christian, additional, Boulinguiez, Alexis, additional, Raverdy, Violeta, additional, Baud, Gregory, additional, Verkindt, Helene, additional, Caiazzo, Robert, additional, Staels, Bart, additional, Duez, Helene, additional, Pattou, Francois, additional, and Lancel, Steve, additional

Published
2019
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34. A314 Impact of Bariatric Surgery on Sexual Function, sex hormones serum profile and semen quality in men with class 3 obesity: preliminary one-year result from a prospective study

Author

Marciniak, Camille, primary, Leroy, Clara, additional, Prasivoravong, Julie, additional, Barbotin, Anne Laure, additional, Raverdy, Violeta, additional, Nesslany, Pamela, additional, Daoud, Naima Oukhouya, additional, Verkindt, Helene, additional, Marcelli, Francois, additional, Pattou, Francois, additional, and Caiazzo, Robert, additional

Published
2019
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37. Collaborateurs

Author

Abderrhamani, Amar, Achamrah, Najate, Allès, Benjamin, Alligier, Maud, Amouyal, Chloé, André, Sébastien, Andreelli, Fabrizio, Antuna-Puente, Barbara, Apfeldorfer, Gérard, Arienzo, Roberto, Arnulf, Isabelle, Aron-Wisnewski, Judith, Aubry, Estelle, Avignon, Antoine, Bachelot, Anne, Barat, Pascal, Barouki, Robert, Bastard, Jean-Philippe, Bastin, Marie, Batisse, Thibaut, Bauduceau, Bernard, Bauters, Catherine, Lassen, Pierre Bel, Bellicha, Alice, Bergouignan, Audrey, Bienvenot, Rebecca, Böhme, Philip, Bonnefond, Amélie, Bordier, Lyse, Boirie, Yves, Borel, Anne-Laure, Bouchard, Philippe, Bouillot, Jean-Luc, Boutron-Ruault, Marie-Christine, Brot-Laroche, Édith, Caiazzo, Robert, Carette, Claire, Carriere, Caroline, Carriere-Pazat, Audrey, Casteilla, Louis, Cassuto, Dominique-Adèle, Charles, Marie-Aline, Chapelot, Didier, Charreire, Hélène, Chevalier, Nicolas, Chevallier, Jean-Marc, Ciangura, Cécile, Clément, Karine, Coëffier, Moïse, Cornet, Philippe, Cortet, Christine, Coupaye, Muriel, Czernichow, Sébastien, Dargent, Jérôme, Delzenne, Nathalie, Deruelle, Philippe, Desport, Jean-Claude, Desseigne, Magalie, Detournay, Bruno, Dharancy, Sébastien, Disse, Emmanuel, Donadille, Bruno, Douillard, Claire, Dubern, Béatrice, Dubreuil, Sophie, Duclos, Martine, Duez, Hélène, Dunoyer, Sophie, Dupont, Charlotte, Durlach, Vincent, Durrer-Schutz, Dominique, Duverne, Sophie, Eburdery, Harold, Espiard, Stéphanie, Esser, Nathalie, Everard, Amandine, Faucher, Pauline, Fayemendy, Philippe, Fellahi, Soraya, Fève, Bruno, Fillon, Alicia, Folope, Vanessa, Fontanille, Isabelle, Frelut, Marie-Laure, Froguel, Philippe, Gaborit, Bénédicte, Gatta-Cherifi, Blandine, Guillet, Christelle, Grange, Laurent, Grangeard, Catherine, Gueorguieva, Iva, Halimi, Serge, Hanaire, Hélène, Heide, Solveig, Heude, Barbara, Iceta, Sylvain, Janmaat, Sonja, Jéru, Isabelle, Jésus, Pierre, Joly, Anne-Sophie, Jouret, Béatrice, Julia, Chantal, Julien-Sweerts, Sabrina, Kim, Min Ji, Ladsous, Miriam, Lalau, Jean-Daniel, Langin, Dominique, Lascols, Olivier, Lassailly, Guillaume, de La Serre, Claire, Laville, Martine, Laye, Sophie, Lecerf, Jean-Michel, Leturque, Armelle, Lévy, Rachel, Lienard, Yasmine, Losserand, Guillaume, Maghroudi, Aïcha, Magnan, Christophe, Marcelin, Geneviève, Marciniak, Camille, Marre, Philippe, Marty, Lucile, Mathurin, Philippe, Matta, Joane, Mencia-Huerta, Matthieu, Michaud, Andréanne, Miramont, Vincent, Mocquot, Caroline, Monnery-Patris, Sandrine, Montastier, Émilie, Morigny, Pauline, Mosbah, Héléna, Negro, Nathalie, Neyrinck, Audrey, Oppert, Jean-Michel, Daoud, Naïma Oukhouya, Pacini, Filippo, Paccou, Julien, Paquot, Nicolas, Pattou, François, Péron-Le Lay, Soazig, Peuteuil, Pierre, Poghosyan, Tigran, Poitou, Christine, Poulain, Jean-Pierre, Pourcher, Guillaume, Quilliot, Didier, Raison, Jocelyne, Raucoules-Aimé, Marc, Ribes, Gérard, Rigal, Nathalie, Ritz, Patrick, Rives-Lange, Claire, Riviere, Pauline, Robert, Maud, Rodriguez, Julie, Romon, Monique, Rose, Cindy, Rozier, Romain, de Saint Pol, Thibault, Sanguignol, Frédéric, Scheen, André, Schlienger, Jean-Louis, Sermondade, Nathalie, Sebti, Yasmine, Simon, Chantal, Tappy, Luc, Tauber, Maïté, Thibault, Hélène, Thivel, David, Valet, Philippe, Vantyghem, Marie-Christine, Vatier, Camille, Verges, Bruno, Verkindt, Hélène, Vialettes, Bernard, Vigouroux, Corinne, Walrand, Stéphane, Waysfeld, Bernard, Zammouri, Jamila, Zermati, Jean-Philippe, Ziegler, Olivier, and Zucker, Jean-Daniel

Published
2021
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45. Hepatic transcriptomic signatures of statin treatment are associated with impaired glucose homeostasis in severely obese patients

Author

Margerie, Daniel, Lefebvre, Philippe, Raverdy, Violeta, Schwahn, Uwe, Ruetten, Hartmut, Larsen, Philip, Duhamel, Alain, Labreuche, Julien, Thuillier, Dorothée, Derudas, Bruno, Gheeraert, Céline, Dehondt, Hélène, Dhalluin, Quentin, Alexandre, Jérémy, Caiazzo, Robert, Nesslany, Pamela, Verkindt, Helene, Pattou, François, Staels, Bart, Research & Development [Sanofi Avantis], Sanofi-Aventis Deutschland GmbH, Récepteurs nucléaires, maladies cardiovasculaires et diabète - U 1011 (RNMCD), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Institut National de la Santé et de la Recherche Médicale (INSERM), Recherche translationnelle sur le diabète - U 1190 (RTD), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille, Service de biostatistiques [CHU Lille], Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Chirurgie générale et endocrinienne [CHU Lille], his work was supported by grants from the European Genomic Institute for Diabetes (ANR-10-LABX-46), and «Fonds hospitalier d’aide à l’émergence et à la structuration des activités et des équipes de recherche» (CHU Lille, France). Bart Staels is a holder of an ERC Advanced Grant (694717). Bart Staels and Francois Pattou received funding for this project from Sanofi Aventis Deutschland GmbH. B.S. is supported by the European Research Council (ERC Grant Immunobile, contract 694717)., European Project: 694717,H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) ,ImmunoBile(2016), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Service de Biostatistiques [CHRU Lille], Derudas, Marie-Hélène, and Bile acid, immune-metabolism, lipid and glucose homeostasis - ImmunoBile - - H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) 2016-09-01 - 2021-08-31 - 694717 - VALID

Subjects
Adult, Male, lcsh:Internal medicine, lcsh:QH426-470, Gene networks, Statin, lcsh:Genetics, Cholesterol, Glucose, Liver, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Homeostasis, Humans, [SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Female, Iatrogenic diabetes, Obesity, Gene expression, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Propensity Score, Sterol Regulatory Element Binding Protein 1, Transcriptome, lcsh:RC31-1245, Research Article, Human
Abstract

Background Clinical data identified an association between the use of HMG-CoA reductase inhibitors (statins) and incident diabetes in patients with underlying diabetes risk factors such as obesity, hypertension and dyslipidemia. The molecular mechanisms however are unknown. Methods An observational cross-sectional study included 910 severely obese patients, mean (SD) body mass index (BMI) 46.7 (8.7), treated with or without statins (ABOS cohort: a biological atlas of severe obesity). Data and sample collection took place in France between 2006 and 2016. Transcriptomic signatures of statin treatment in human liver obtained from genome-wide transcriptomic profiling of five different statin drugs using microarrays were correlated to clinico-biological phenotypes and also assigned to biological pathways and mechanisms. Patients from the non-statin-users group were matched to patients in the statin users group by propensity score analysis to minimize confounding effects from age, gender, parental familial history of diabetes, BMI, waist circumference, systolic and diastolic blood pressure and use of anti-hypertensive drugs as pre-specified covariates. Results We determined the hepatic, statin-related gene signature from genome-wide transcriptomic profiling in severely obese patients with varying degrees of glucose tolerance and cardio-metabolic comorbidities. One hundred and fifty seven patients on statin treatment in the matched cohort showed higher diabetes prevalence (OR = 2.67; 95%CI, 1.60–4.45; P = 0.0002) and impairment of glucose homeostasis. This phenotype was associated with molecular signatures of increased hepatic de novo lipogenesis (DNL) via activation of sterol regulatory element-binding protein 1 (SREBP1) and concomitant upregulation of the expression of key genes in both fatty acid and triglyceride metabolism. Conclusions A DNL gene activation profile in response to statins is associated with insulin resistance and the diabetic status of the patients. Identified molecular signatures thus suggest that statin treatment increases the risk for diabetes in humans at least in part via induction of DNL. Trial registration NCT01129297. Registered May 242,010 (retrospectively registered). Electronic supplementary material The online version of this article (10.1186/s12920-019-0536-1) contains supplementary material, which is available to authorized users.

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