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2. PPARγ lipodystrophy mutants reveal intermolecular interactions required for enhancer activation

Author

Madsen, Maria Stahl, Broekema, Marjoleine F., Madsen, Martin Rønn, Koppen, Arjen, Borgman, Anouska, Gräwe, Cathrin, Thomsen, Elisabeth G. K., Westland, Denise, Kranendonk, Mariette E. G., Koerkamp, Marian Groot, Hamers, Nicole, Bonvin, Alexandre M. J. J., Pittol, José M. Ramos, Natarajan, Kedar Nath, Kersten, Sander, Holstege, Frank C. P., Monajemi, Houshang, van Mil, Saskia W. C., Vermeulen, Michiel, Kragelund, Birthe B., Cassiman, David, Mandrup, Susanne, and Kalkhoven, Eric

Published
2022
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3. Increased serum miR-193a-5p during non-alcoholic fatty liver disease progression: Diagnostic and mechanistic relevance

Author

Clark, James, Cordell, Heather J., Darlay, Rebecca, Day, Christopher P., Hardy, Tim, Liu, Yang-Lin, Oakley, Fiona, Palmer, Jeremy, Queen, Rachel, Wonders, Kristy, Bossuyt, Patrick M., Holleboom, Adriaan G., Zafarmand, Hadi, Vali, Yasaman, Lee, Jenny, Clement, Karine, Pais, Raluca, Schuppan, Detlef, Allison, Michael, Cuenca, Sergio Rodriguez, Pellegrinelli, Vanessa, Vacca, Michele, Vidal-Puig, Antonio, Hyötyläinen, Tuulia, McGlinchey, Aidan, Orešič, Matej, Sen, Partho, Mato, Jose, Millet, Óscar, Dufour, Jean-Francois, Harrison, Stephen, Neubauer, Stefan, Pavlides, Michael, Mozes, Ferenc, Akhtar, Salma, Banerjee, Rajarshi, Kelly, Matt, Shumbayawonda, Elizabeth, Dennis, Andrea, Erpicum, Charlotte, Romero-Gomez, Manuel, Gallego-Durán, Rocío, Fernández, Isabel, Karsdal, Morten, Leeming, Diana, Fisker, Mette Juul, Erhardtsen, Elisabeth, Rasmussen, Daniel, Qvist, Per, Sinisi, Antonia, Sandt, Estelle, Tonini, Maria Manuela, Parola, Maurizio, Rosso, Chiara, Marra, Fabio, Gastaldelli, Amalia, Francque, Sven, Kechagias, Stergios, Yki-Järvinen, Hannele, Porthan, Kimmo, van Mil, Saskia, Papatheodoridis, George, Cortez-Pinto, Helena, Valenti, Luca, Petta, Salvatore, Miele, Luca, Geier, Andreas, Trautwein, Christian, Hockings, Paul, Newsome, Phil, Wenn, David, Pereira Rodrigues, Cecília Maria, Hanf, Rémy, Chaumat, Pierre, Rosenquist, Christian, Trylesinski, Aldo, Ortiz, Pablo, Duffin, Kevin, Yunis, Carla, Miller, Melissa, Tuthill, Theresa, Ertle, Judith, Younes, Ramy, Alexander, Leigh, Ostroff, Rachel, Kjær, Mette Skalshøi, Mikkelsen, Lars Friis, Brass, Clifford, Jennings, Lori, Balp, Maria-Magdalena, Martic, Miljen, Hanauer, Guido, Shankar, Sudha, Torstenson, Richard, Fournier, Céline, Ehman, Richard, Kalutkiewicz, Michael, Pepin, Kay, Myers, Joel, Shevell, Diane, Ho, Gideon, Landgren, Henrik, Myers, Rob, Doward, Lynda, Whalley, Diane, Twiss, James, Johnson, Katherine, Leary, Peter J., Govaere, Olivier, Barter, Matthew J., Charlton, Sarah H., Cockell, Simon J., Tiniakos, Dina, Zatorska, Michalina, Bedossa, Pierre, Brosnan, M. Julia, Cobbold, Jeremy F., Ekstedt, Mattias, Aithal, Guruprasad P., Clément, Karine, Schattenberg, Jörn M., Boursier, Jerome, Ratziu, Vlad, Bugianesi, Elisabetta, Anstee, Quentin M., and Daly, Ann K.

Published
2022
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7. Dietary cystine restriction increases the proliferative capacity of the small intestine of mice

Author

CMM, CMM Groep Van Mil, Cancer, CMM Groep Burgering, MMB Research line 2, Infection & Immunity, CMM Groep Vercoulen, Child Health, de Jong, Judith C.W., van Rooijen, Kristel S., Stigter, Edwin C.A., Gülersönmez, M. Can, de Zoete, Marcel R., Top, Janetta, Baars, Matthijs J.D., Vercoulen, Yvonne, Kuipers, Folkert, Van Mil, Saskia W.C., Ijssennagger, Noortje, CMM, CMM Groep Van Mil, Cancer, CMM Groep Burgering, MMB Research line 2, Infection & Immunity, CMM Groep Vercoulen, Child Health, de Jong, Judith C.W., van Rooijen, Kristel S., Stigter, Edwin C.A., Gülersönmez, M. Can, de Zoete, Marcel R., Top, Janetta, Baars, Matthijs J.D., Vercoulen, Yvonne, Kuipers, Folkert, Van Mil, Saskia W.C., and Ijssennagger, Noortje

Published
2024

8. Dietary cystine restriction increases the proliferative capacity of the small intestine of mice

Author

de Jong, Judith C. W., primary, van Rooijen, Kristel S., additional, Stigter, Edwin C. A., additional, Gülersönmez, M. Can, additional, de Zoete, Marcel R., additional, Top, Janetta, additional, Baars, Matthijs J. D., additional, Vercoulen, Yvonne, additional, Kuipers, Folkert, additional, van Mil, Saskia W. C., additional, and Ijssennagger, Noortje, additional

Published
2024
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9. Farnesoid X receptor (FXR) activation and FXR genetic variation in inflammatory bowel disease.

Author

Nijmeijer, Rian M, Gadaleta, Raffaella M, van Mil, Saskia WC, van Bodegraven, Adriaan A, Crusius, J Bart A, Dijkstra, Gerard, Hommes, Daan W, de Jong, Dirk J, Stokkers, Pieter CF, Verspaget, Hein W, Weersma, Rinse K, van der Woude, C Janneke, Stapelbroek, Janneke M, Schipper, Marguerite EI, Wijmenga, Cisca, van Erpecum, Karel J, Oldenburg, Bas, and Dutch Initiative on Crohn, Colitis (ICC)

Subjects
Dutch Initiative on Crohn, Colitis, Colon, Ileum, Humans, Colitis, Ulcerative, Inflammatory Bowel Diseases, Receptors, Cytoplasmic and Nuclear, RNA, Messenger, Case-Control Studies, Gene Expression, Polymorphism, Single Nucleotide, Female, Male, Genetic Variation, General Science & Technology
Abstract

BackgroundWe previously showed that activation of the bile salt nuclear receptor Farnesoid X Receptor (FXR) protects against intestinal inflammation in mice. Reciprocally, these inflammatory mediators may decrease FXR activation. We investigated whether FXR activation is repressed in the ileum and colon of inflammatory bowel disease (IBD) patients in remission. Additionally, we evaluated whether genetic variation in FXR is associated with IBD.MethodsmRNA expression of FXR and FXR target gene SHP was determined in ileal and colonic biopsies of patients with Crohn's colitis (n = 15) and ulcerative colitis (UC; n = 12), all in clinical remission, and healthy controls (n = 17). Seven common tagging SNPs and two functional SNPs in FXR were genotyped in 2355 Dutch IBD patients (1162 Crohn's disease (CD) and 1193 UC) and in 853 healthy controls.ResultsmRNA expression of SHP in the ileum is reduced in patients with Crohn's colitis but not in patients with UC compared to controls. mRNA expression of villus marker Villin was correlated with FXR and SHP in healthy controls, a correlation that was weaker in UC patients and absent in CD patients. None of the SNPs was associated with IBD, UC or CD, nor with clinical subgroups of CD.ConclusionsFXR activation in the ileum is decreased in patients with Crohn's colitis. This may be secondary to altered enterohepatic circulation of bile salts or transrepression by inflammatory signals but does not seem to be caused by the studied SNPs in FXR. Increasing FXR activity by synthetic FXR agonists may have benefit in CD patients.

Published
2011

13. Machine learning algorithm improves the detection of NASH (NAS-based) and at-risk NASH: A development and validation study

Author

Jenny, Lee, Max, Westphal, Yasaman, Vali, Jerome, Boursier, Salvatorre, Petta, Rachel, Ostroff, Leigh, Alexander, Yu, Chen, Celine, Fournier, Andreas, Geier, Sven, Francque, Kristy, Wonder, Dina, Tiniako, Pierre, Bedossa, Mike, Allison, Georgios, Papatheodoridi, Helena, Cortez-Pinto, Raluca, Pai, Jean-Francois, Dufour, Diana Julie, Leeming, Stephen, Harrison, Jeremy, Cobbold, Adriaan G, Holleboom, Hannele, Yki-Järvinen, Javier, Crespo, Mattias, Ekstedt, Guruprasad P, Aithal, Elisabetta, Bugianesi, Manuel, Romero-Gomez, Richard, Torstenson, Morten, Karsdal, Carla, Yuni, Jörn M, Schattenberg, Detlef, Schuppan, Vlad, Ratziu, Clifford, Bra, Kevin, Duffin, Koos, Zwinderman, Michael, Pavlide, Quentin M, Anstee, Patrick M, Bossuyt, Anstee, Quentin M., Daly, Ann K., Govaere, Olivier, Cockell, Simon, Tiniakos, Dina, Bedossa, Pierre, Burt, Alastair, Oakley, Fiona, Cordell, Heather J., Day, Christopher P., Wonders, Kristy, Missier, Paolo, Mcteer, Matthew, Vale, Luke, Oluboyede, Yemi, Breckons, Matt, Bossuyt, Patrick M., Zafarmand, Hadi, Vali, Yasaman, Lee, Jenny, Nieuwdorp, Max, Holleboom, Adriaan G., Verheij, Joanne, Ratziu, Vlad, Clément, Karine, Patino-Navarrete, Rafael, Pais, Raluca, Paradis, Valerie, Schuppan, Detlef, Schattenberg, Jörn M., Surabattula, Rambabu, Myneni, Sudha, Straub, Beate K., Vidal-Puig, Toni, Vacca, Michele, Rodrigues-Cuenca, Sergio, Allison, Mike, Kamzolas, Ioanni, Petsalaki, Evangelia, Campbell, Mark, Lelliott, Chris J., Davies, Susan, Orešič, Matej, Hyötyläinen, Tuulia, Mcglinchey, Aiden, Mato, Jose M., Millet, Óscar, Dufour, Jean-Françoi, Berzigotti, Annalisa, Masoodi, Mojgan, Pavlides, Michael, Harrison, Stephen, Neubauer, Stefan, Cobbold, Jeremy, Mozes, Ferenc, Akhtar, Salma, Olodo-Atitebi, Seliat, Banerjee, Rajarshi, Kelly, Matt, Shumbayawonda, Elizabeth, Dennis, Andrea, Andersson, Anneli, Wigley, Ioan, Romero-Gómez, Manuel, Gómez-González, Emilio, Ampuero, Javier, Castell, Javier, Gallego-Durán, Rocío, Fernández, Isabel, Montero-Vallejo, Rocío, Karsdal, Morten, Guldager Kring Rasmussen, Daniel, Leeming, Diana Julie, Sinisi, Antonia, Musa, Kishwar, Sandt, Estelle, Tonini, Manuela, Bugianesi, Elisabetta, Rosso, Chiara, Armandi, Angelo, Marra, Fabio, Gastaldelli, Amalia, Svegliati, Gianluca, Boursier, Jérôme, Francque, Sven, Vonghia, Luisa, Driessen, Ann, Ekstedt, Mattia, Kechagias, Stergio, Yki-Järvinen, Hannele, Porthan, Kimmo, Arola, Johanna, van Mil, Saskia, Papatheodoridis, George, Cortez-Pinto, Helena, Rodrigues, Cecilia M. P., Valenti, Luca, Pelusi, Serena, Petta, Salvatore, Pennisi, Grazia, Miele, Luca, Geier, Andrea, Trautwein, Christian, Aithal, Guruprasad P., Francis, Susan, Hockings, Paul, Schneider, Moritz, Newsome, Philip, Hübscher, Stefan, Wenn, David, Rosenquist, Christian, Trylesinski, Aldo, Mayo, Rebeca, Alonso, Cristina, Duffin, Kevin, Perfield, James W., Chen, Yu, Yunis, Carla, Tuthill, Theresa, Harrington, Magdalena Alicia, Miller, Melissa, Chen, Yan, Mcleod, Euan Jame, Ross, Trenton, Bernardo, Barbara, Schölch, Corinna, Ertle, Judith, Younes, Ramy, Oldenburger, Anouk, Ostroff, Rachel, Alexander, Leigh, Biegel, Hannah, Skalshøi Kjær, Mette, Mørch Harder, Lea, Davidsen, Peter, Mikkelsen, Lars Frii, Balp, Maria-Magdalena, Brass, Clifford, Jennings, Lori, Martic, Miljen, Löffler, Jürgen, Applegate, Dougla, Shankar, Sudha, Torstenson, Richard, Fournier-Poizat, Céline, Llorca, Anne, Kalutkiewicz, Michael, Pepin, Kay, Ehman, Richard, Horan, Gerald, Ho, Gideon, Tai, Dean, Chng, Elaine, Patterson, Scott D., Billin, Andrew, Doward, Lynda, Twiss, Jame, Thakker, Paresh, Landgren, Henrik, Lackner, Carolin, Gouw, Annette, Hytiroglou, Prodromos, Luca, Miele (ORCID:0000-0003-3464-0068), Jenny, Lee, Max, Westphal, Yasaman, Vali, Jerome, Boursier, Salvatorre, Petta, Rachel, Ostroff, Leigh, Alexander, Yu, Chen, Celine, Fournier, Andreas, Geier, Sven, Francque, Kristy, Wonder, Dina, Tiniako, Pierre, Bedossa, Mike, Allison, Georgios, Papatheodoridi, Helena, Cortez-Pinto, Raluca, Pai, Jean-Francois, Dufour, Diana Julie, Leeming, Stephen, Harrison, Jeremy, Cobbold, Adriaan G, Holleboom, Hannele, Yki-Järvinen, Javier, Crespo, Mattias, Ekstedt, Guruprasad P, Aithal, Elisabetta, Bugianesi, Manuel, Romero-Gomez, Richard, Torstenson, Morten, Karsdal, Carla, Yuni, Jörn M, Schattenberg, Detlef, Schuppan, Vlad, Ratziu, Clifford, Bra, Kevin, Duffin, Koos, Zwinderman, Michael, Pavlide, Quentin M, Anstee, Patrick M, Bossuyt, Anstee, Quentin M., Daly, Ann K., Govaere, Olivier, Cockell, Simon, Tiniakos, Dina, Bedossa, Pierre, Burt, Alastair, Oakley, Fiona, Cordell, Heather J., Day, Christopher P., Wonders, Kristy, Missier, Paolo, Mcteer, Matthew, Vale, Luke, Oluboyede, Yemi, Breckons, Matt, Bossuyt, Patrick M., Zafarmand, Hadi, Vali, Yasaman, Lee, Jenny, Nieuwdorp, Max, Holleboom, Adriaan G., Verheij, Joanne, Ratziu, Vlad, Clément, Karine, Patino-Navarrete, Rafael, Pais, Raluca, Paradis, Valerie, Schuppan, Detlef, Schattenberg, Jörn M., Surabattula, Rambabu, Myneni, Sudha, Straub, Beate K., Vidal-Puig, Toni, Vacca, Michele, Rodrigues-Cuenca, Sergio, Allison, Mike, Kamzolas, Ioanni, Petsalaki, Evangelia, Campbell, Mark, Lelliott, Chris J., Davies, Susan, Orešič, Matej, Hyötyläinen, Tuulia, Mcglinchey, Aiden, Mato, Jose M., Millet, Óscar, Dufour, Jean-Françoi, Berzigotti, Annalisa, Masoodi, Mojgan, Pavlides, Michael, Harrison, Stephen, Neubauer, Stefan, Cobbold, Jeremy, Mozes, Ferenc, Akhtar, Salma, Olodo-Atitebi, Seliat, Banerjee, Rajarshi, Kelly, Matt, Shumbayawonda, Elizabeth, Dennis, Andrea, Andersson, Anneli, Wigley, Ioan, Romero-Gómez, Manuel, Gómez-González, Emilio, Ampuero, Javier, Castell, Javier, Gallego-Durán, Rocío, Fernández, Isabel, Montero-Vallejo, Rocío, Karsdal, Morten, Guldager Kring Rasmussen, Daniel, Leeming, Diana Julie, Sinisi, Antonia, Musa, Kishwar, Sandt, Estelle, Tonini, Manuela, Bugianesi, Elisabetta, Rosso, Chiara, Armandi, Angelo, Marra, Fabio, Gastaldelli, Amalia, Svegliati, Gianluca, Boursier, Jérôme, Francque, Sven, Vonghia, Luisa, Driessen, Ann, Ekstedt, Mattia, Kechagias, Stergio, Yki-Järvinen, Hannele, Porthan, Kimmo, Arola, Johanna, van Mil, Saskia, Papatheodoridis, George, Cortez-Pinto, Helena, Rodrigues, Cecilia M. P., Valenti, Luca, Pelusi, Serena, Petta, Salvatore, Pennisi, Grazia, Miele, Luca, Geier, Andrea, Trautwein, Christian, Aithal, Guruprasad P., Francis, Susan, Hockings, Paul, Schneider, Moritz, Newsome, Philip, Hübscher, Stefan, Wenn, David, Rosenquist, Christian, Trylesinski, Aldo, Mayo, Rebeca, Alonso, Cristina, Duffin, Kevin, Perfield, James W., Chen, Yu, Yunis, Carla, Tuthill, Theresa, Harrington, Magdalena Alicia, Miller, Melissa, Chen, Yan, Mcleod, Euan Jame, Ross, Trenton, Bernardo, Barbara, Schölch, Corinna, Ertle, Judith, Younes, Ramy, Oldenburger, Anouk, Ostroff, Rachel, Alexander, Leigh, Biegel, Hannah, Skalshøi Kjær, Mette, Mørch Harder, Lea, Davidsen, Peter, Mikkelsen, Lars Frii, Balp, Maria-Magdalena, Brass, Clifford, Jennings, Lori, Martic, Miljen, Löffler, Jürgen, Applegate, Dougla, Shankar, Sudha, Torstenson, Richard, Fournier-Poizat, Céline, Llorca, Anne, Kalutkiewicz, Michael, Pepin, Kay, Ehman, Richard, Horan, Gerald, Ho, Gideon, Tai, Dean, Chng, Elaine, Patterson, Scott D., Billin, Andrew, Doward, Lynda, Twiss, Jame, Thakker, Paresh, Landgren, Henrik, Lackner, Carolin, Gouw, Annette, Hytiroglou, Prodromos, and Luca, Miele (ORCID:0000-0003-3464-0068)

Abstract

Background and aims: Detecting NASH remains challenging, while at-risk NASH (steatohepatitis and F≥ 2) tends to progress and is of interest for drug development and clinical application. We developed prediction models by supervised machine learning techniques, with clinical data and biomarkers to stage and grade patients with NAFLD. Approach and results: Learning data were collected in the Liver Investigation: Testing Marker Utility in Steatohepatitis metacohort (966 biopsy-proven NAFLD adults), staged and graded according to NASH CRN. Conditions of interest were the clinical trial definition of NASH (NAS ≥ 4;53%), at-risk NASH (NASH with F ≥ 2;35%), significant (F ≥ 2;47%), and advanced fibrosis (F ≥ 3;28%). Thirty-five predictors were included. Missing data were handled by multiple imputations. Data were randomly split into training/validation (75/25) sets. A gradient boosting machine was applied to develop 2 models for each condition: clinical versus extended (clinical and biomarkers). Two variants of the NASH and at-risk NASH models were constructed: direct and composite models.Clinical gradient boosting machine models for steatosis/inflammation/ballooning had AUCs of 0.94/0.79/0.72. There were no improvements when biomarkers were included. The direct NASH model produced AUCs (clinical/extended) of 0.61/0.65. The composite NASH model performed significantly better (0.71) for both variants. The composite at-risk NASH model had an AUC of 0.83 (clinical and extended), an improvement over the direct model. Significant fibrosis models had AUCs (clinical/extended) of 0.76/0.78. The extended advanced fibrosis model (0.86) performed significantly better than the clinical version (0.82). Conclusions: Detection of NASH and at-risk NASH can be improved by constructing independent machine learning models for each component, using only clinical predictors. Adding biomarkers only improved the accuracy of fibrosis.

Published
2023

14. Multi-country metabolic signature discovery for chicken health classification

Author

Wolthuis, Joanna C., Magnúsdóttir, Stefanía, Stigter, Edwin, Tang, Yuen Fung, Jans, Judith, Gilbert, Myrthe, van der Hee, Bart, Langhout, Pim, Gerrits, Walter, Kies, Arie, de Ridder, Jeroen, van Mil, Saskia, Wolthuis, Joanna C., Magnúsdóttir, Stefanía, Stigter, Edwin, Tang, Yuen Fung, Jans, Judith, Gilbert, Myrthe, van der Hee, Bart, Langhout, Pim, Gerrits, Walter, Kies, Arie, de Ridder, Jeroen, and van Mil, Saskia

Abstract

Introduction: To decrease antibiotic resistance, their use as growth promoters in the agricultural sector has been largely abandoned. This may lead to decreased health due to infectious disease or microbiome changes leading to gut inflammation. Objectives: We aimed to generate a m/z signature classifying chicken health in blood, and obtain biological insights from the resulting m/z signature. Methods: We used direct infusion mass-spectrometry to determine a machine-learned metabolomics signature that classifies chicken health from a blood sample. We then challenged the resulting models by investigating the classification capability of the signature on novel data obtained at poultry houses in previously unseen countries using a Leave-One-Country-Out (LOCO) cross-validation strategy. Additionally, we optimised the number of mass/charge (m/z) values required to maximise the classification capability of Random Forest models, by developing a novel ranking system based on combined univariate t-test and fold-change analyses and building models based on this ranking through forward and reverse feature selection. Results: The multi-country and LOCO models could classify chicken health. Both resulting 25-m/z and 3784-m/z signatures reliably classified chicken health in multiple countries. Through mummichog enrichment analysis on the large m/z signature, we found changes in amino acid metabolism, including branched chain amino acids and polyamines. Conclusion: We reliably classified chicken health from blood, independent of genetic-, farm-, feed- and country-specific confounding factors. The 25-m/z signature can be used to aid development of a per-metabolite panel. The extended 3784-m/z version can be used to gain a deeper understanding of the metabolic causes and consequences of low chicken health. Together, they may facilitate future treatment, prevention and intervention.

Published
2023

15. Multi-country metabolic signature discovery for chicken health classification

Author

CMM, CMM Groep Van Mil, Cancer, CMM Groep Burgering, Genetica Sectie Metabole Diagnostiek, Brain, Child Health, CMM Groep De Ridder, Wolthuis, Joanna C., Magnúsdóttir, Stefanía, Stigter, Edwin, Tang, Yuen Fung, Jans, Judith, Gilbert, Myrthe, van der Hee, Bart, Langhout, Pim, Gerrits, Walter, Kies, Arie, de Ridder, Jeroen, van Mil, Saskia, CMM, CMM Groep Van Mil, Cancer, CMM Groep Burgering, Genetica Sectie Metabole Diagnostiek, Brain, Child Health, CMM Groep De Ridder, Wolthuis, Joanna C., Magnúsdóttir, Stefanía, Stigter, Edwin, Tang, Yuen Fung, Jans, Judith, Gilbert, Myrthe, van der Hee, Bart, Langhout, Pim, Gerrits, Walter, Kies, Arie, de Ridder, Jeroen, and van Mil, Saskia

Published
2023

16. Rifaximin stimulates nitrogen detoxification by PXR-independent mechanisms in human small intestinal organoids

Author

CMM Groep Van Mil, Cancer, CMM Groep Burgering, Child Health, Regenerative Medicine and Stem Cells, CMM, de Wit, Koos, Beuers, Ulrich, Mukha, Anna, Stigter, Edwin, Gulersonmez, M Can, Ramos Pittol, Jose M, Middendorp, Sabine, Takkenberg, R Bart, van Mil, Saskia W C, CMM Groep Van Mil, Cancer, CMM Groep Burgering, Child Health, Regenerative Medicine and Stem Cells, CMM, de Wit, Koos, Beuers, Ulrich, Mukha, Anna, Stigter, Edwin, Gulersonmez, M Can, Ramos Pittol, Jose M, Middendorp, Sabine, Takkenberg, R Bart, and van Mil, Saskia W C

Published
2023

19. Increased serum miR-193a-5p during non-alcoholic fatty liver disease progression: Diagnostic and mechanistic relevance

Author

Johnson, Katherine, Leary, Peter J., Govaere, Olivier, Barter, Matthew J., Charlton, Sarah H., Cockell, Simon J., Tiniakos, Dina, Zatorska, Michalina, Bedossa, Pierre, Brosnan, M. Julia, Cobbold, Jeremy F., Ekstedt, Mattias, Aithal, Guruprasad P., Boursier, Jerome, Ratziu, Vlad, Bugianesi, Elisabetta, Anstee, Quentin M., Daly, Ann K., Clark, James, Cockell, Simon, Cordell, Heather J., Darlay, Rebecca, Day, Christopher P., Hardy, Tim, Liu, Yang-Lin, Oakley, Fiona, Palmer, Jeremy, Queen, Rachel, Wonders, Kristy, Bossuyt, Patrick M., Holleboom, Adriaan G., Zafarmand, Hadi, Vali, Yasaman, Lee, Jenny, Clement, Karine, Pais, Raluca, Schuppan, Detlef, Allison, Michael, Cuenca, Sergio Rodriguez, Pellegrinelli, Vanessa, Vacca, Michele, Vidal-Puig, Antonio, McGlinchey, Aidan, Sen, Partho, Mato, Jose, Dufour, Jean-Francois, Harrison, Stephen, Neubauer, Stefan, Pavlides, Michael, Mozes, Ferenc, Akhtar, Salma, Banerjee, Rajarshi, Kelly, Matt, Shumbayawonda, Elizabeth, Dennis, Andrea, Erpicum, Charlotte, Romero-Gomez, Manuel, Karsdal, Morten, Leeming, Diana, Fisker, Mette Juul, Erhardtsen, Elisabeth, Rasmussen, Daniel, Qvist, Per, Sinisi, Antonia, Sandt, Estelle, Tonini, Maria Manuela, Parola, Maurizio, Rosso, Chiara, Marra, Fabio, Gastaldelli, Amalia, Francque, Sven, Kechagias, Stergios, Porthan, Kimmo, van Mil, Saskia, Papatheodoridis, George, Cortez-Pinto, Helena, Valenti, Luca, Petta, Salvatore, Miele, Luca, Geier, Andreas, Trautwein, Christian, Hockings, Paul, Newsome, Phil, Wenn, David, Chaumat, Pierre, Rosenquist, Christian, Trylesinski, Aldo, Ortiz, Pablo, Duffin, Kevin, Yunis, Carla, Miller, Melissa, Tuthill, Theresa, Ertle, Judith, Younes, Ramy, Alexander, Leigh, Ostroff, Rachel, Mikkelsen, Lars Friis, Brass, Clifford, Jennings, Lori, Balp, Maria-Magdalena, Martic, Miljen, Hanauer, Guido, Shankar, Sudha, Torstenson, Richard, Ehman, Richard, Kalutkiewicz, Michael, Pepin, Kay, Myers, Joel, Shevell, Diane, Ho, Gideon, Landgren, Henrik, Myers, Rob, Doward, Lynda, Whalley, Diane, and Twiss, James

Subjects
Hepatology, Gastroenterology, Internal Medicine, Immunology and Allergy, digestive system diseases
Abstract

Background & Aims: Serum microRNA (miRNA) levels are known to change in non-alcoholic fatty liver disease (NAFLD) and may serve as useful biomarkers. This study aimed to profile miRNAs comprehensively at all NAFLD stages. Methods: We profiled 2,083 serum miRNAs in a discovery cohort (183 cases with NAFLD representing the complete NAFLD spectrum and 10 population controls). miRNA libraries generated by HTG EdgeSeq were sequenced by Illumina NextSeq. Selected serum miRNAs were profiled in 372 additional cases with NAFLD and 15 population controls by quantitative reverse transcriptase PCR. Results: Levels of 275 miRNAs differed between cases and population controls. Fewer differences were seen within individual NAFLD stages, but miR-193a-5p consistently showed increased levels in all comparisons. Relative to NAFL/non-alcoholic steatohepatitis (NASH) with mild fibrosis (stage 0/1), 3 miRNAs (miR-193a-5p, miR-378d, and miR378d) were increased in cases with NASH and clinically significant fibrosis (stages 2–4), 7 (miR193a-5p, miR-378d, miR-378e, miR-320b, miR-320c, miR-320d, and miR-320e) increased in cases with NAFLD activity score (NAS) 5–8 compared with lower NAS, and 3 (miR-193a-5p, miR-378d, and miR-378e) increased but 1 (miR-19b-3p) decreased in steatosis, activity, and fibrosis (SAF) activity score 2–4 compared with lower SAF activity. The significant findings for miR-193a-5p were replicated in the additional cohort with NAFLD. Studies in Hep G2 cells showed that following palmitic acid treatment, miR-193a-5p expression decreased significantly. Gene targets for miR-193a-5p were investigated in liver RNAseq data for a case subgroup (n = 80); liver GPX8 levels correlated positively with serum miR-193a-5p. Conclusions: Serum miR-193a-5p levels correlate strongly with NAFLD activity grade and fibrosis stage. MiR-193a-5p may have a role in the hepatic response to oxidative stress and is a potential clinically tractable circulating biomarker for progressive NAFLD. Lay summary: MicroRNAs (miRNAs) are small pieces of nucleic acid that may turn expression of genes on or off. These molecules can be detected in the blood circulation, and their levels in blood may change in liver disease including non-alcoholic fatty liver disease (NAFLD). To see if we could detect specific miRNA associated with advanced stages of NAFLD, we carried out miRNA sequencing in a group of 183 patients with NAFLD of varying severity together with 10 population controls. We found that a number of miRNAs showed changes, mainly increases, in serum levels but that 1 particular miRNA miR-193a-5p consistently increased. We confirmed this increase in a second group of cases with NAFLD. Measuring this miRNA in a blood sample may be a useful way to determine whether a patient has advanced NAFLD without an invasive liver biopsy.

Published
2022

23. Proper genomic profiling of (BRCA1-mutated) basal-like breast carcinomas requires prior removal of tumor infiltrating lymphocytes

Author

Massink, Maarten P.G., Kooi, Irsan E., van Mil, Saskia E., Jordanova, Ekaterina S., Ameziane, Najim, Dorsman, Josephine C., van Beek, Daphne M., van der Voorn, Patrick J., Sie, Daoud, Ylstra, Bauke, van Deurzen, Carolien H.M., Martens, John W., Smid, Marcel, Sieuwerts, Anieta M., de Weerd, Vanja, Foekens, John A., van den Ouweland, Ans M.W., van Dyk, Ewald, Nederlof, Petra M., Waisfisz, Quinten, and Meijers-Heijboer, Hanne

Published
2015
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24. Ablation of liver Fxr results in an increased colonic mucus barrier in mice.

Author

dI&I I&I-2, Dep Biomolecular Health Sciences, Pathobiologie, dPB RMSC, Ijssennagger, Noortje, van Rooijen, Kristel S., Magnúsdóttir, Stefanía, Ramos Pittol, José M., Willemsen, Ellen C.L., de Zoete, Marcel R., Baars, Matthijs J.D., Stege, Paul B., Colliva, Carolina, Pellicciari, Roberto, Youssef, Sameh A., de Bruin, Alain, Vercoulen, Yvonne, Kuipers, Folkert, van Mil, Saskia W.C., dI&I I&I-2, Dep Biomolecular Health Sciences, Pathobiologie, dPB RMSC, Ijssennagger, Noortje, van Rooijen, Kristel S., Magnúsdóttir, Stefanía, Ramos Pittol, José M., Willemsen, Ellen C.L., de Zoete, Marcel R., Baars, Matthijs J.D., Stege, Paul B., Colliva, Carolina, Pellicciari, Roberto, Youssef, Sameh A., de Bruin, Alain, Vercoulen, Yvonne, Kuipers, Folkert, and van Mil, Saskia W.C.

Published
2021

26. Ablation of liver Fxr results in an increased colonic mucus barrier in mice

Author

CMM Groep Van Mil, Cancer, DBG Metabole en Endocriene Ziekten, MMB Research line 2, Infection & Immunity, CMM Groep Vercoulen, CMM, Child Health, Ijssennagger, Noortje, van Rooijen, Kristel S., Magnúsdóttir, Stefanía, Ramos Pittol, José M., Willemsen, Ellen C.L., de Zoete, Marcel R., Baars, Matthijs J.D., Stege, Paul B., Colliva, Carolina, Pellicciari, Roberto, Youssef, Sameh A., de Bruin, Alain, Vercoulen, Yvonne, Kuipers, Folkert, van Mil, Saskia W.C., CMM Groep Van Mil, Cancer, DBG Metabole en Endocriene Ziekten, MMB Research line 2, Infection & Immunity, CMM Groep Vercoulen, CMM, Child Health, Ijssennagger, Noortje, van Rooijen, Kristel S., Magnúsdóttir, Stefanía, Ramos Pittol, José M., Willemsen, Ellen C.L., de Zoete, Marcel R., Baars, Matthijs J.D., Stege, Paul B., Colliva, Carolina, Pellicciari, Roberto, Youssef, Sameh A., de Bruin, Alain, Vercoulen, Yvonne, Kuipers, Folkert, and van Mil, Saskia W.C.

Published
2021

30. FXR Isoforms Control Different Metabolic Functions in Liver Cells via Binding to Specific DNA Motifs

Author

CMM Groep Van Mil, Cancer, CMM Groep Kalkhoven, DBG Metabole en Endocriene Ziekten, Staf Onderwijs en Opleidingen, Child Health, Ramos Pittol, Jose Miguel, Milona, Alexandra, Morris, Imogen, Willemsen, Ellen C L, van der Veen, Suzanne W, Kalkhoven, Eric, van Mil, Saskia W C, CMM Groep Van Mil, Cancer, CMM Groep Kalkhoven, DBG Metabole en Endocriene Ziekten, Staf Onderwijs en Opleidingen, Child Health, Ramos Pittol, Jose Miguel, Milona, Alexandra, Morris, Imogen, Willemsen, Ellen C L, van der Veen, Suzanne W, Kalkhoven, Eric, and van Mil, Saskia W C

Published
2020

31. MetaboShiny: interactive analysis and metabolite annotation of mass spectrometry-based metabolomics data

Author

CMM Groep Van Mil, Cancer, Genetica Sectie Metabole Diagnostiek, Child Health, CMM Sectie Molecular Cancer Research, CMM Groep De Ridder, Wolthuis, Joanna C, Magnusdottir, Stefania, Pras-Raves, Mia, Moshiri, Maryam, Jans, Judith J M, Burgering, Boudewijn, van Mil, Saskia, de Ridder, Jeroen, CMM Groep Van Mil, Cancer, Genetica Sectie Metabole Diagnostiek, Child Health, CMM Sectie Molecular Cancer Research, CMM Groep De Ridder, Wolthuis, Joanna C, Magnusdottir, Stefania, Pras-Raves, Mia, Moshiri, Maryam, Jans, Judith J M, Burgering, Boudewijn, van Mil, Saskia, and de Ridder, Jeroen

Published
2020

33. Steroidogenic control of liver metabolism through a nuclear receptor-network

Author

Milona, Alexandra, Massafra, Vittoria, Vos, Harmjan, Naik, Jyoti, Artigas, Natalia, Paterson, Helen A.B., Bijsmans, Ingrid T.G.W., Willemsen, Ellen C.L., Ramos Pittol, Jose M., Miguel-Aliaga, Irene, Bosma, Piter, Burgering, Boudewijn M.T., Williamson, Catherine, Vernia, Santiago, Dhillo, Waljit S., van Mil, Saskia W.C., and Owen, Bryn M.

Published
2019
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34. Loss of FLCN-FNIP1/2 induces a non-canonical interferon response in human renal tubular epithelial cells

Author

Glykofridis, Iris E, primary, Knol, Jaco C, additional, Balk, Jesper A, additional, Westland, Denise, additional, Pham, Thang V, additional, Piersma, Sander R, additional, Lougheed, Sinéad M, additional, Derakhshan, Sepide, additional, Veen, Puck, additional, Rooimans, Martin A, additional, van Mil, Saskia E, additional, Böttger, Franziska, additional, Poddighe, Pino J, additional, van de Beek, Irma, additional, Drost, Jarno, additional, Zwartkruis, Fried JT, additional, de Menezes, Renee X, additional, Meijers-Heijboer, Hanne EJ, additional, Houweling, Arjan C, additional, Jimenez, Connie R, additional, and Wolthuis, Rob MF, additional

Published
2021
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37. MetaboShiny - interactive processing, analysis and identification of untargeted metabolomics data

Author

Wolthuis, Joanna C., Magnusdottir, Stefania, Pras-Raves, Mia, Jans, Judith J.M., Burgering, Boudewijn, van Mil, Saskia, and de Ridder, Jeroen

Abstract

Untargeted metabolomics by mass spectrometry in the form of mass over charge and intensity of ions, provides insight into the metabolic activity in a sample and is therefore essential to understand regulation and expression at the protein and transcription level. Problematically, it is often challenging to analyze untargeted metabolomics data as many m/z values are detected per sample and it is difficult to identify what compound they represent. We aimed to facilitate the process of finding m/z biomarkers through statistical analysis, machine learning and searching for their putative identities. To address this challenge, we developed MetaboShiny, a novel R and RShiny based metabolomics data analysis package. MetaboShiny features bi/multivariate and temporal statistics, an extensive machine learning module, interactive plotting and result exploration, and compound identification through a variety of chemical databases. As a result, MetaboShiny enables rapid and rigorous analysis of untargeted metabolomics data as well as target identification at unprecedented scale. To demonstrate its efficacy and ease-of-use, we apply MetaboShiny to a publicly accessible metabolomics dataset generated from the urine of smokers and non-smokers. Replication of the main results of the original publication, which includes importing, normalization and several statistical analyses, is achieved within minutes. Moreover, MetaboShiny enables deeper exploration of the data thereby revealing novel putative biomarkers and hypotheses. For instance, by using MetaboShiny’s subsetting feature, iodine is found to be significantly increased in non-smoking lung cancer patients. Furthermore, by allowing for custom adducts, MetaboShiny reveals a putative identification for an m/z value which could not be identified by the original authors. This validates MetaboShiny as a flexible and customizable data analysis package that greatly enhances metabolomics biomarker discovery.

Published
2019
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41. Farnesoid X receptor and bile acids regulate vitamin A storage

Author

CMM Groep Van Mil, Child Health, Cancer, Saeed, Ali, Yang, Jing, Heegsma, Janette, Groen, Albert K., van Mil, Saskia W.C., Paulusma, Coen C., Zhou, Lu, Wang, Bangmao, Faber, Klaas Nico, CMM Groep Van Mil, Child Health, Cancer, Saeed, Ali, Yang, Jing, Heegsma, Janette, Groen, Albert K., van Mil, Saskia W.C., Paulusma, Coen C., Zhou, Lu, Wang, Bangmao, and Faber, Klaas Nico

Published
2019

42. Steroidogenic control of liver metabolism through a nuclear receptor-network

Author

Child Health, CMM, CMM Groep Van Mil, CMM Groep Burgering, Cancer, DBG Metabole en Endocriene Ziekten, CMM Sectie Molecular Cancer Research, Milona, Alexandra, Massafra, Vittoria, Vos, Harmjan, Naik, Jyoti, Artigas, Natalia, Paterson, Helen A.B., Bijsmans, Ingrid T.G.W., Willemsen, Ellen C.L., Ramos Pittol, Jose M., Miguel-Aliaga, Irene, Bosma, Piter, Burgering, Boudewijn M.T., Williamson, Catherine, Vernia, Santiago, Dhillo, Waljit S., van Mil, Saskia W.C., Owen, Bryn M., Child Health, CMM, CMM Groep Van Mil, CMM Groep Burgering, Cancer, DBG Metabole en Endocriene Ziekten, CMM Sectie Molecular Cancer Research, Milona, Alexandra, Massafra, Vittoria, Vos, Harmjan, Naik, Jyoti, Artigas, Natalia, Paterson, Helen A.B., Bijsmans, Ingrid T.G.W., Willemsen, Ellen C.L., Ramos Pittol, Jose M., Miguel-Aliaga, Irene, Bosma, Piter, Burgering, Boudewijn M.T., Williamson, Catherine, Vernia, Santiago, Dhillo, Waljit S., van Mil, Saskia W.C., and Owen, Bryn M.

Published
2019

43. Identification of FDA-approved drugs targeting the Farnesoid X Receptor

Author

CMM Groep Van Mil, Cancer, Child Health, van de Wiel, Sandra M W, Bijsmans, Ingrid T G W, van Mil, Saskia W C, van de Graaf, Stan F J, CMM Groep Van Mil, Cancer, Child Health, van de Wiel, Sandra M W, Bijsmans, Ingrid T G W, van Mil, Saskia W C, and van de Graaf, Stan F J

Published
2019

47. Farnesoid X Receptor Activation Promotes Hepatic Amino Acid Catabolism and Ammonium Clearance in Mice

Author

Massafra, Vittoria, Milona, Alexandra, Vos, Harmjan R, Ramos, Rúben J J, Gerrits, Johan, Willemsen, Ellen C L, Ramos Pittol, José M, Ijssennagger, Noortje, Houweling, Martin, Prinsen, Hubertus C M T, Verhoeven-Duif, Nanda M, Burgering, Boudewijn M T, van Mil, Saskia W C, dB&C FR-RMSC FR, and dB&C FR-RMSC FR

Subjects
Male, 0301 basic medicine, Glutamine Synthetase, Proteome, Cytoplasmic and Nuclear, Glutamine, Wistar, Gene Expression, Receptors, Cytoplasmic and Nuclear, Inbred C57BL, Mice, chemistry.chemical_compound, INT-747, Chenodeoxycholic acid, Receptors, Urea, Mice, Knockout, Bile acid, Gastroenterology, Obeticholic acid, Liver Proteome, Liver, Biochemistry, Urea cycle, Metabolome, Dietary Proteins, medicine.medical_specialty, medicine.drug_class, Knockout, Cps1, Biology, Chenodeoxycholic Acid, Bile Acids and Salts, 03 medical and health sciences, Ammonia, Internal medicine, medicine, Journal Article, Animals, Rats, Wistar, Liver X receptor, Hepatology, Catabolism, Rats, Mice, Inbred C57BL, 030104 developmental biology, Endocrinology, chemistry, Hepatocytes, Farnesoid X receptor
Abstract

Background & Aims The nuclear receptor subfamily 1 group H member 4 (NR1H4 or farnesoid X receptor [FXR]) regulates bile acid synthesis, transport, and catabolism. FXR also regulates postprandial lipid and glucose metabolism. We performed quantitative proteomic analyses of liver tissues from mice to evaluate these functions and investigate whether FXR regulates amino acid metabolism. Methods To study the role of FXR in mouse liver, we used mice with a disruption of Nr1h4 (FXR-knockout mice) and compared them with floxed control mice. Mice were gavaged with the FXR agonist obeticholic acid or vehicle for 11 days. Proteome analyses, as well as targeted metabolomics and chromatin immunoprecipitation, were performed on the livers of these mice. Primary rat hepatocytes were used to validate the role of FXR in amino acid catabolism by gene expression and metabolomics studies. Finally, control mice and mice with liver-specific disruption of Nr1h4 (liver FXR-knockout mice) were re-fed with a high-protein diet after 6 hours fasting and gavaged a 15 NH 4 Cl tracer. Gene expression and the metabolome were studied in the livers and plasma from these mice. Results In livers of control mice and primary rat hepatocytes, activation of FXR with obeticholic acid increased expression of proteins that regulate amino acid degradation, ureagenesis, and glutamine synthesis. We found FXR to bind to regulatory sites of genes encoding these proteins in control livers. Liver tissues from FXR-knockout mice had reduced expression of urea cycle proteins, and accumulated precursors of ureagenesis, compared with control mice. In liver FXR-knockout mice on a high-protein diet, the plasma concentration of newly formed urea was significantly decreased compared with controls. In addition, liver FXR-knockout mice had reduced hepatic expression of enzymes that regulate ammonium detoxification compared with controls. In contrast, obeticholic acid increased expression of genes encoding enzymes involved in ureagenesis compared with vehicle in C57Bl/6 mice. Conclusions In livers of mice, FXR regulates amino acid catabolism and detoxification of ammonium via ureagenesis and glutamine synthesis. Failure of the urea cycle and hyperammonemia are common in patients with acute and chronic liver diseases; compounds that activate FXR might promote ammonium clearance in these patients.

Published
2017

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