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1. Pharmacogene expression during progression of metabolic dysfunction-associated steatotic liver disease: Studies on mRNA and protein levels and their relevance to drug treatment

Author: Govaere, Olivier, Cockell, Simon J., Zatorska, Michalina, Wonders, Kristy, Tiniakos, Dina, Frey, Andrew M., Palmowksi, Pawel, Walker, Ruth, Porter, Andrew, Trost, Matthias, Anstee, Quentin M., and Daly, Ann K.
Published: 2024
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2. Liver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS): Assessment & validation of imaging modality performance across the NAFLD spectrum in a prospectively recruited cohort study (the LITMUS imaging study): Study protocol

Author: Pavlides, Michael, Mózes, Ferenc E., Akhtar, Salma, Wonders, Kristy, Cobbold, Jeremy, Tunnicliffe, Elizabeth M., Allison, Michael, Godfrey, Edmund M., Aithal, Guruprasad P., Francis, Susan, Romero-Gomez, Manuel, Castell, Javier, Fernandez-Lizaranzu, Isabel, Aller, Rocio, González, Rebeca Sigüenza, Agustin, Salvador, Pericàs, Juan M., Boursier, Jerome, Aube, Christophe, Ratziu, Vlad, Wagner, Mathilde, Petta, Salvatore, Antonucci, Michela, Bugianesi, Elisabetta, Faletti, Riccardo, Miele, Luca, Geier, Andreas, Schattenberg, Jörn M., Tilman, Emrich, Ekstedt, Mattias, Lundberg, Peter, Berzigotti, Annalisa, Huber, Adrian T., Papatheodoridis, George, Yki-Järvinen, Hannele, Porthan, Kimmo, Schneider, Moritz Jörg, Hockings, Paul, Shumbayawonda, Elizabeth, Banerjee, Rajarshi, Pepin, Kay, Kalutkiewicz, Mike, Ehman, Richard L., Trylesinksi, Aldo, Coxson, Harvey O., Martic, Miljen, Yunis, Carla, Tuthill, Theresa, Bossuyt, Patrick M., Anstee, Quentin M., Neubauer, Stefan, and Harrison, Stephen
Published: 2023
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3. Performance of non-invasive tests and histology for the prediction of clinical outcomes in patients with non-alcoholic fatty liver disease: an individual participant data meta-analysis

Author: 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, Ioannis, Petsalaki, Evangelia, Campbell, Mark, Lelliott, Chris J, Davies, Susan, Orešič, Matej, Hyötyläinen, Tuulia, McGlinchey, Aiden, Mato, Jose M, Millet, Óscar, Dufour, Jean-François, 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, Rasmussen, Daniel Guldager Kring, 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, Mattias, Kechagias, Stergios, 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, Andreas, Trautwein, Christian, Reißing, Johanna, Aithal, Guruprasad P, Francis, Susan, Palaniyappan, Naaventhan, Bradley, Christopher, 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 James, Ross, Trenton, Bernardo, Barbara, Schölch, Corinna, Ertle, Judith, Younes, Ramy, Oldenburger, Anouk, Coxson, Harvey, Ostroff, Rachel, Alexander, Leigh, Biegel, Hannah, Kjær, Mette Skalshøi, Harder, Lea Mørch, Davidsen, Peter, Ellegaard, Jens, Balp, Maria-Magdalena, Brass, Clifford, Jennings, Lori, Martic, Miljen, Löffler, Jürgen, Applegate, Douglas, Shankar, Sudha, Torstenson, Richard, Lindén, Daniel, 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, James, Thakker, Paresh, Derdak, Zoltan, Landgren, Henrik, Lackner, Carolin, Gouw, Annette, Hytiroglou, Prodromos, Mózes, Ferenc E, Lee, Jenny A, Alzoubi, Osama, Staufer, Katharina, Trauner, Michael, Paternostro, Rafael, Stauber, Rudolf E, van Dijk, Anne-Marieke, Mak, Anne Linde, de Saint Loup, Marc, Shima, Toshihide, Gaia, Silvia, Shalimar, Lupșor-Platon, Monica, Wong, Vincent Wai-Sun, Li, Guanlin, Wong, Grace Lai-Hung, Karlas, Thomas, Wiegand, Johannes, Sebastiani, Giada, Tsochatzis, Emmanuel, Liguori, Antonio, Yoneda, Masato, Nakajima, Atsushi, Hagström, Hannes, Akbari, Camilla, Hirooka, Masashi, Chan, Wah-Kheong, Mahadeva, Sanjiv, Rajaram, Ruveena, Zheng, Ming-Hua, George, Jacob, Eslam, Mohammed, Viganò, Mauro, Ridolfo, Sofia, Aithal, Guruprasad Padur, Lee, Dae Ho, Nasr, Patrik, Cassinotto, Christophe, de Lédinghen, Victor, Mendoza, Yuly P, Noureddin, Mazen, Truong, Emily, and Harrison, Stephen A
Published: 2023
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4. Biomarkers for staging fibrosis and non-alcoholic steatohepatitis in non-alcoholic fatty liver disease (the LITMUS project): a comparative diagnostic accuracy study

Author: Vali, Yasaman, Lee, Jenny, Boursier, Jerome, Petta, Salvatore, Wonders, Kristy, Tiniakos, Dina, Bedossa, Pierre, Geier, Andreas, Francque, Sven, Allison, Mike, Papatheodoridis, Georgios, Cortez-Pinto, Helena, Pais, Raluca, Dufour, Jean-Francois, Leeming, Diana Julie, Harrison, Stephen A, Chen, Yu, Cobbold, Jeremy F, Pavlides, Michael, Holleboom, Adriaan G, Yki-Jarvinen, Hannele, Crespo, Javier, Karsdal, Morten, Ostroff, Rachel, Zafarmand, Mohammad Hadi, Torstenson, Richard, Duffin, Kevin, Yunis, Carla, Brass, Clifford, Ekstedt, Mattias, Aithal, Guruprasad P, Schattenberg, Jörn M, Bugianesi, Elisabetta, Romero-Gomez, Manuel, Ratziu, Vlad, Anstee, Quentin M, and Bossuyt, Patrick M
Published: 2023
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5. 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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6. 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

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

Author: Lee, Jenny, Westphal, Max, Vali, Yasaman, Boursier, Jerome, Petta, Salvatorre, Ostroff, Rachel, Alexander, Leigh, Chen, Yu, Fournier, Celine, Geier, Andreas, Francque, Sven, Wonders, Kristy, Tiniakos, Dina, Bedossa, Pierre, Allison, Mike, Papatheodoridis, Georgios, Cortez-Pinto, Helena, Pais, Raluca, Dufour, Jean-Francois, Leeming, Diana Julie, Harrison, Stephen, Cobbold, Jeremy, Holleboom, Adriaan G., Yki-Jarvinen, Hannele, Crespo, Javier, Ekstedt, Mattias, Aithal, Guruprasad P., Bugianesi, Elisabetta, Romero-Gomez, Manuel, Torstenson, Richard, Karsdal, Morten, Yunis, Carla, Schattenberg, Joern M., Schuppan, Detlef, Ratziu, Vlad, Brass, Clifford, Duffin, Kevin, Zwinderman, Koos, Pavlides, Michael, Anstee, Quentin M., Bossuyt, Patrick M., LITMUS Investigators, Lee, Jenny, Westphal, Max, Vali, Yasaman, Boursier, Jerome, Petta, Salvatorre, Ostroff, Rachel, Alexander, Leigh, Chen, Yu, Fournier, Celine, Geier, Andreas, Francque, Sven, Wonders, Kristy, Tiniakos, Dina, Bedossa, Pierre, Allison, Mike, Papatheodoridis, Georgios, Cortez-Pinto, Helena, Pais, Raluca, Dufour, Jean-Francois, Leeming, Diana Julie, Harrison, Stephen, Cobbold, Jeremy, Holleboom, Adriaan G., Yki-Jarvinen, Hannele, Crespo, Javier, Ekstedt, Mattias, Aithal, Guruprasad P., Bugianesi, Elisabetta, Romero-Gomez, Manuel, Torstenson, Richard, Karsdal, Morten, Yunis, Carla, Schattenberg, Joern M., Schuppan, Detlef, Ratziu, Vlad, Brass, Clifford, Duffin, Kevin, Zwinderman, Koos, Pavlides, Michael, Anstee, Quentin M., Bossuyt, Patrick M., and LITMUS Investigators
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., Funding Agencies|Jenny Lee, Quentin M. Anstee, and Pierre Bedossa conceptualized and designed the study; Jerome Boursier, Salvatore Petta, Kristy Wonders, Dina Tiniakos, Pierre Bedossa, Andreas Geier, Sven Francque, Mike Allison, Georgios Papatheodoridis, Helena Cortez-Pin
Published: 2023
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8. Machine learning algorithm improves the detection of NASH (NAS-based) and at-risk NASH: A development and validation study

Author: Innovative Medicines Initiative, European Commission, Research Foundation - Flanders, Lee, Jenny, Westphal, Max, Vali, Yasaman, Boursier, Jerome, Petta, Salvatorre, Ostroff, Rachel, Alexander, Leigh, Chen, Yu, Fournier, Celine, Geier, Andreas, Francque, Sven, Wonders, Kristy, Tiniakos, Dina, Bedossa, Pierre, Allison, Mike, Papatheodoridis, Georgios, Cortez-Pinto, Helena, Pais, Raluca, Dufour, Jean-François, Leeming, Diana Julie, Harrison, Stephen, Cobbold, Jeremy, Holleboom, Adriaan G., Yki-Järvinen, Hannele, Crespo, Javier, Ekstedt, Mattias, Aithal, Guruprasad P., Bugianesi, Elisabetta, Romero-Gómez, Manuel, Torstenson, Richard, Karsdal, Morten, Yunis, Carla27, Schattenberg, Jörn M., Schuppan, Detlef, Ratziu, Vlad, Brass, Clifford, Duffin, Kevin, Zwinderman, Koos, Pavlides, Michael, Anstee, Quentin M., Bossuyt, Patrick M., LITMUS investigators, Innovative Medicines Initiative, European Commission, Research Foundation - Flanders, Lee, Jenny, Westphal, Max, Vali, Yasaman, Boursier, Jerome, Petta, Salvatorre, Ostroff, Rachel, Alexander, Leigh, Chen, Yu, Fournier, Celine, Geier, Andreas, Francque, Sven, Wonders, Kristy, Tiniakos, Dina, Bedossa, Pierre, Allison, Mike, Papatheodoridis, Georgios, Cortez-Pinto, Helena, Pais, Raluca, Dufour, Jean-François, Leeming, Diana Julie, Harrison, Stephen, Cobbold, Jeremy, Holleboom, Adriaan G., Yki-Järvinen, Hannele, Crespo, Javier, Ekstedt, Mattias, Aithal, Guruprasad P., Bugianesi, Elisabetta, Romero-Gómez, Manuel, Torstenson, Richard, Karsdal, Morten, Yunis, Carla27, Schattenberg, Jörn M., Schuppan, Detlef, Ratziu, Vlad, Brass, Clifford, Duffin, Kevin, Zwinderman, Koos, Pavlides, Michael, Anstee, Quentin M., Bossuyt, Patrick M., and LITMUS investigators
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

9. Biomarkers for staging fibrosis and non-alcoholic steatohepatitis in non-alcoholic fatty liver disease (the LITMUS project): a comparative diagnostic accuracy study

Author: Innovative Medicines Initiative, European Commission, Vali, Yasaman, Lee, Jenny, Boursier, Jerome, Petta, Salvatore, Wonders, Kristy, Tiniakos, Dina, Bedossa, Pierre, Geier, Andreas, Francque, Sven, Allison, Mike, Papatheodoridis, Georgios, Cortez-Pinto, Helena, Pais, Raluca, Dufour, Jean-François, Leeming, Diana Julie, Harrison, Stephen A., Chen, Yu, Cobbold, Jeremy F., Pavlides, Michael, Holleboom, Adriaan G., Yki-Jarvinen, Hannele, Crespo, Javier, Karsdal, Morten, Ostroff, Rachel, Zafarmand, Mohammad Hadi, Torstenson, Richard, Duffin, Kevin, Yunis, Carla, Brass, Clifford, Ekstedt, Mattias, Aithal, Guruprasad P., Schattenberg, Jörn M., Bugianesi, Elisabetta, Romero-Gómez, Manuel, Ratziu, Vlad, Anstee, Quentin M., Bossuyt, Patrick M., on behalf of theLiver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS) consortium investigators, Innovative Medicines Initiative, European Commission, Vali, Yasaman, Lee, Jenny, Boursier, Jerome, Petta, Salvatore, Wonders, Kristy, Tiniakos, Dina, Bedossa, Pierre, Geier, Andreas, Francque, Sven, Allison, Mike, Papatheodoridis, Georgios, Cortez-Pinto, Helena, Pais, Raluca, Dufour, Jean-François, Leeming, Diana Julie, Harrison, Stephen A., Chen, Yu, Cobbold, Jeremy F., Pavlides, Michael, Holleboom, Adriaan G., Yki-Jarvinen, Hannele, Crespo, Javier, Karsdal, Morten, Ostroff, Rachel, Zafarmand, Mohammad Hadi, Torstenson, Richard, Duffin, Kevin, Yunis, Carla, Brass, Clifford, Ekstedt, Mattias, Aithal, Guruprasad P., Schattenberg, Jörn M., Bugianesi, Elisabetta, Romero-Gómez, Manuel, Ratziu, Vlad, Anstee, Quentin M., Bossuyt, Patrick M., and on behalf of theLiver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS) consortium investigators
Abstract: [Background] The reference standard for detecting non-alcoholic steatohepatitis (NASH) and staging fibrosis—liver biopsy—is invasive and resource intensive. Non-invasive biomarkers are urgently needed, but few studies have compared these biomarkers in a single cohort. As part of the Liver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS) project, we aimed to evaluate the diagnostic accuracy of 17 biomarkers and multimarker scores in detecting NASH and clinically significant fibrosis in patients with non-alcoholic fatty liver disease (NAFLD) and identify their optimal cutoffs as screening tests in clinical trial recruitment., [Methods] This was a comparative diagnostic accuracy study in people with biopsy-confirmed NAFLD from 13 countries across Europe, recruited between Jan 6, 2010, and Dec 29, 2017, from the LITMUS metacohort of the prospective European NAFLD Registry. Adults (aged ≥18 years) with paired liver biopsy and serum samples were eligible; those with excessive alcohol consumption or evidence of other chronic liver diseases were excluded. The diagnostic accuracy of the biomarkers was expressed as the area under the receiver operating characteristic curve (AUC) with liver histology as the reference standard and compared with the Fibrosis-4 index for liver fibrosis (FIB-4) in the same subgroup. Target conditions were the presence of NASH with clinically significant fibrosis (ie, at-risk NASH; NAFLD Activity Score ≥4 and F≥2) or the presence of advanced fibrosis (F≥3), analysed in all participants with complete data. We identified thres holds for each biomarker for reducing the number of biopsy-based screen failures when recruiting people with both NASH and clinically significant fibrosis for future trials., [Findings] Of 1430 participants with NAFLD in the LITMUS metacohort with serum samples, 966 (403 women and 563 men) were included after all exclusion criteria had been applied. 335 (35%) of 966 participants had biopsy-confirmed NASH and clinically significant fibrosis and 271 (28%) had advanced fibrosis. For people with NASH and clinically significant fibrosis, no single biomarker or multimarker score significantly reached the predefined AUC 0·80 acceptability threshold (AUCs ranging from 0·61 [95% CI 0·54–0·67] for FibroScan controlled attenuation parameter to 0·81 [0·75–0·86] for SomaSignal), with accuracy mostly similar to FIB-4. Regarding detection of advanced fibrosis, SomaSignal (AUC 0·90 [95% CI 0·86–0·94]), ADAPT (0·85 [0·81–0·89]), and FibroScan liver stiffness measurement (0·83 [0·80–0·86]) reached acceptable accuracy. With 11 of 17 markers, histological screen failure rates could be reduced to 33% in trials if only people who were marker positive had a biopsy for evaluating eligibility. The best screening performance for NASH and clinically significant fibrosis was observed for SomaSignal (number needed to test [NNT] to find one true positive was four [95% CI 4–5]), then ADAPT (six [5–7]), MACK-3 (seven [6–8]), and PRO-C3 (nine [7–11])., [Interpretation] None of the single markers or multimarker scores achieved the predefined acceptable AUC for replacing biopsy in detecting people with both NASH and clinically significant fibrosis. However, several biomarkers could be applied in a prescreening strategy in clinical trial recruitment. The performance of promising markers will be further evaluated in the ongoing prospective LITMUS study cohort.
Published: 2023

10. 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

11. Performance of non-invasive tests and histology for the prediction of clinical outcomes in patients with non-alcoholic fatty liver disease: an individual participant data meta-analysis

Author: Mózes, Ferenc E, Lee, Jenny A, Vali, Yasaman, Alzoubi, Osama, Staufer, Katharina, Trauner, Michael, Paternostro, Rafael, Stauber, Rudolf E, Holleboom, Adriaan G, van Dijk, Anne-Marieke, Mak, Anne Linde, Boursier, Jérôme, de Saint Loup, Marc, Shima, Toshihide, Bugianesi, Elisabetta, Gaia, Silvia, Armandi, Angelo, Shalimar, Lupșor-Platon, Monica, Wong, Vincent Wai-Sun, Li, Guanlin, Wong, Grace Lai-Hung, Cobbold, Jeremy, Karlas, Thomas, Wiegand, Johannes, Sebastiani, Giada, Tsochatzis, Emmanuel, Liguori, Antonio, Yoneda, Masato, Nakajima, Atsushi, Hagström, Hannes, Akbari, Camilla, Hirooka, Masashi, Chan, Wah-Kheong, Mahadeva, Sanjiv, Rajaram, Ruveena, Zheng, Ming-Hua, George, Jacob, Eslam, Mohammed, Petta, Salvatore, Pennisi, Grazia, Viganò, Mauro, Ridolfo, Sofia, Aithal, Guruprasad Padur, Palaniyappan, Naaventhan, Lee, Dae Ho, Ekstedt, Mattias, Nasr, Patrik, Cassinotto, Christophe, de Lédinghen, Victor, Berzigotti, Annalisa, Mendoza, Yuly P, Noureddin, Mazen, Truong, Emily, Fournier-Poizat, Céline, Geier, Andreas, Martic, Miljen, Tuthill, Theresa, Anstee, Quentin M, Harrison, Stephen A, Bossuyt, Patrick M, Pavlides, Michael, 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, Ioannis, Petsalaki, Evangelia, Campbell, Mark, Lelliott, Chris J, Davies, Susan, Orešič, Matej, Hyötyläinen, Tuulia, McGlinchey, Aiden, Mato, Jose M, Millet, Óscar, Dufour, Jean-François, 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, Rasmussen, Daniel Guldager Kring, 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, Mattias, Kechagias, Stergios, 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, Andreas, Trautwein, Christian, Reißing, Johanna, Aithal, Guruprasad P, Francis, Susan, Palaniyappan, Naaventhan, Bradley, Christopher, 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 James, Ross, Trenton, Bernardo, Barbara, Schölch, Corinna, Ertle, Judith, Younes, Ramy, Oldenburger, Anouk, Coxson, Harvey, Ostroff, Rachel, Alexander, Leigh, Biegel, Hannah, Kjær, Mette Skalshøi, Harder, Lea Mørch, Davidsen, Peter, Ellegaard, Jens, Balp, Maria-Magdalena, Brass, Clifford, Jennings, Lori, Martic, Miljen, Löffler, Jürgen, Applegate, Douglas, Shankar, Sudha, Torstenson, Richard, Lindén, Daniel, 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, James, Thakker, Paresh, Derdak, Zoltan, Landgren, Henrik, Lackner, Carolin, Gouw, Annette, and Hytiroglou, Prodromos
Abstract: Histologically assessed liver fibrosis stage has prognostic significance in patients with non-alcoholic fatty liver disease (NAFLD) and is accepted as a surrogate endpoint in clinical trials for non-cirrhotic NAFLD. Our aim was to compare the prognostic performance of non-invasive tests with liver histology in patients with NAFLD.
Published: 2023
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12. Diagnostic accuracy of elastography and magnetic resonance imaging in patients with NAFLD: A systematic review and meta-analysis

Author: Selvaraj, Emmanuel Anandraj, primary, Mózes, Ferenc Emil, additional, Jayaswal, Arjun Narayan Ajmer, additional, Zafarmand, Mohammad Hadi, additional, Vali, Yasaman, additional, Lee, Jenny A., additional, Levick, Christina Kim, additional, Young, Liam Arnold Joseph, additional, Palaniyappan, Naaventhan, additional, Liu, Chang-Hai, additional, Aithal, Guruprasad Padur, additional, Romero-Gómez, Manuel, additional, Brosnan, M. Julia, additional, Tuthill, Theresa A., additional, Anstee, Quentin M., additional, Neubauer, Stefan, additional, Harrison, Stephen A., additional, Bossuyt, Patrick M., additional, Pavlides, Michael, additional, Anstee, Quentin, additional, Daly, Ann, additional, Johnson, Katherine, additional, Govaere, Olivier, additional, Cockell, Simon, additional, Tiniakos, Dina, additional, Bedossa, Pierre, additional, Oakley, Fiona, additional, Cordell, Heather, additional, Day, Chris, additional, Wonders, Kristy, additional, Bossuyt, Patrick, additional, Zafarmand, Hadi, additional, Lee, Jenny, additional, Ratziu, Vlad, additional, Clement, Karine, additional, Pais, Raluca, additional, Schuppan, Detlef, additional, Schattenberg, Jörn, additional, Vidal-Puig, Toni, additional, Vacca, Michele, additional, Rodrigues-Cuenca, Sergio, additional, Allison, Mike, additional, Kamzolas, Ioannis, additional, Petsalaki, Evangelia, additional, Oresic, Matej, additional, Hyötyläinen, Tuulia, additional, McGlinchey, Aiden, additional, Mato, Jose M., additional, Millet, Oscar, additional, Dufour, Jean-François, additional, Berzigotti, Annalisa, additional, Harrison, Stephen, additional, Cobbold, Jeremy, additional, Mozes, Ferenc, additional, Akhtar, Salma, additional, Banerjee, Rajarshi, additional, Kelly, Matt, additional, Shumbayawonda, Elizabeth, additional, Dennis, Andrea, additional, Erpicum, Charlotte, additional, Gómez-González, Emilio, additional, Ampuero, Javier, additional, Castell, Javier, additional, Gallego-Durán, Rocío, additional, Fernández, Isabel, additional, Montero-Vallejo, Rocío, additional, Karsdal, Morten, additional, Erhardtsen, Elisabeth, additional, Rasmussen, Daniel, additional, Leeming, Diana Julie, additional, Fisker, Mette Juul, additional, Sinisi, Antonia, additional, Musa, Kishwar, additional, Betsou, Fay, additional, Sandt, Estelle, additional, Tonini, Manuela, additional, Bugianesi, Elisabetta, additional, Rosso, Chiara, additional, Armandi, Angelo, additional, Marra, Fabio, additional, Gastaldelli, Amalia, additional, Svegliati, Gianluca, additional, Boursier, Jérôme, additional, Francque, Sven, additional, Vonghia, Luisa, additional, Ekstedt, Mattias, additional, Kechagias, Stergios, additional, Yki-Jarvinen, Hannele, additional, Luukkonen, Panu, additional, van Mil, Saskia, additional, Papatheodoridis, George, additional, Cortez-Pinto, Helena, additional, Valenti, Luca, additional, Petta, Salvatore, additional, Miele, Luca, additional, Geier, Andreas, additional, Trautwein, Christian, additional, Aithal, Guru, additional, Hockings, Paul, additional, Newsome, Philip, additional, Wenn, David, additional, Pereira Rodrigues, Cecília Maria, additional, Chaumat, Pierre, additional, Hanf, Rémy, additional, Trylesinski, Aldo, additional, Ortiz, Pablo, additional, Duffin, Kevin, additional, Brosnan, Julia, additional, Tuthill, Theresa, additional, McLeod, Euan, additional, Ertle, Judith, additional, Younes, Ramy, additional, Ostroff, Rachel, additional, Alexander, Leigh, additional, Kjær, Mette Skalshøi, additional, Mikkelsen, Lars Friis, additional, Balp, Maria-Magdalena, additional, Brass, Clifford, additional, Jennings, Lori, additional, Martic, Miljen, additional, Loeffler, Juergen, additional, Hanauer, Guido, additional, Shankar, Sudha, additional, Fournier, Céline, additional, Pepin, Kay, additional, Ehman, Richard, additional, Myers, Joel, additional, Ho, Gideon, additional, Torstenson, Richard, additional, Myers, Rob, additional, and Doward, Lynda, additional
Published: 2021
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13. The European NAFLD Registry: A real-world longitudinal cohort study of nonalcoholic fatty liver disease

Author: Hardy, Timothy, Wonders, Kristy, Younes, Ramy, Aithal, Guruprasad P, Aller, Rocio, Allison, Michael, Bedossa, Pierre, Betsou, Fay, Boursier, Jerome, Brosnan, M Julia, Burt, Alastair, Cobbold, Jeremy, Cortez-Pinto, Helena, Day, Chris P, Dufour, Jean-Francois, Ekstedt, Mattias, Francque, Sven, Harrison, Stephen, Miele, Luca, Nasr, Patrik, Papatheodoridis, George, Petta, Salvatore, Tiniakos, Dina, Torstenson, Richard, Valenti, Luca, Holleboom, Adriaan G, Yki-Jarvinen, Hannele, Geier, Andreas, Romero-Gomez, Manuel, Ratziu, Vlad, Bugianesi, Elisabetta, Schattenberg, Jörn M, Anstee, Quentin M, LITMUS Consortium, Newcastle University [Newcastle], Università degli studi di Torino (UNITO), University of Nottingham, UK (UON), Universidad de Valladolid [Valladolid] (UVa), Cambridge University Hospitals - NHS (CUH), University of Cambridge [UK] (CAM), Integrated BioBank of Luxembourg (IBBL), Hémodynamique, Interaction Fibrose et Invasivité tumorales Hépatiques (HIFIH), Université d'Angers (UA), Pfizer, Oxford University Hospitals NHS Trust, University of Oxford [Oxford], Universidade de Lisboa (ULISBOA), University of Bern, Linköping University (LIU), University of Antwerp (UA), Università cattolica del Sacro Cuore [Roma] (Unicatt), National and Kapodistrian University of Athens (NKUA), Università degli studi di Palermo - University of Palermo, University of Milan, University of Helsinki, University of Würzburg, Hospital Universitario Virgen del Rocío [Sevilla], Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), University Medical Center [Mainz], Newcastle Upon Tyne Hospitals NHS Foundation Trust, Vascular Medicine, ACS - Diabetes & metabolism, ACS - Amsterdam Cardiovascular Sciences, AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, LITMUS Consortium, Innovative Medicines Initiative, European Commission, Department of Medicine, HUS Internal Medicine and Rehabilitation, Helsinki University Hospital Area, Hardy T., Wonders K., Younes R., Aithal G.P., Aller R., Allison M., Bedossa P., Betsou F., Boursier J., Brosnan M.J., Burt A., Cobbold J., Cortez-Pinto H., Day C.P., Dufour J.-F., Ekstedt M., Francque S., Harrison S., Miele L., Nasr P., Papatheodoridis G., Petta S., Tiniakos D., Torstenson R., Valenti L., Holleboom A.G., Yki-Jarvinen H., Geier A., Romero-Gomez M., Ratziu V., Bugianesi E., Schattenberg J.M., Anstee Q.M., Harrison, Seamus Conor [0000-0003-1480-1143], and Apollo - University of Cambridge Repository
Subjects: Liver Cirrhosis, PROGNOSIS, Cirrhosis, SCORING SYSTEM, [SDV]Life Sciences [q-bio], PROGRESSION, Disease, Biomarker, Cirrhosis, NAFLD, NASH, STEATOHEPATITIS, DEFINITIONS, Cohort Studies, 0302 clinical medicine, Non-alcoholic Fatty Liver Disease, Nonalcoholic fatty liver disease, Pharmacology (medical), 030212 general & internal medicine, Longitudinal Studies, Registries, ComputingMilieux_MISCELLANEOUS, media_common, Pharmacology. Therapy, Fatty liver, Liver Neoplasms, NASH, General Medicine, 3. Good health, Liver, 317 Pharmacy, Cohort, 0305 other medical science, Cohort study, medicine.medical_specialty, Settore MED/12 - GASTROENTEROLOGIA, Geriatrik, QUESTIONNAIRE, NAFLD, Biomarker, 610 Medicine & health, 03 medical and health sciences, medicine, STEATOSIS, media_common.cataloged_instance, Humans, ALGORITHM, European union, Intensive care medicine, 030505 public health, business.industry, CONSUMPTION, STAGING SYSTEM, medicine.disease, Diabetes Mellitus, Type 2, Geriatrics, 3121 General medicine, internal medicine and other clinical medicine, 3111 Biomedicine, Human medicine, Steatohepatitis, business
Abstract: © 2020 The Author(s)., Non-Alcoholic Fatty Liver Disease (NAFLD), a progressive liver disease that is closely associated with obesity, type 2 diabetes, hypertension and dyslipidaemia, represents an increasing global public health challenge. There is significant variability in the disease course: the majority exhibit only fat accumulation in the liver but a significant minority develop a necroinflammatory form of the disease (non-alcoholic steatohepatitis, NASH) that may progress to cirrhosis and hepatocellular carcinoma. At present our understanding of pathogenesis, disease natural history and long-term outcomes remain incomplete. There is a need for large, well characterised patient cohorts that may be used to address these knowledge gaps and to support the development of better biomarkers and novel therapies. The European NAFLD Registry is an international, prospectively recruited observational cohort study that aims to establish a large, highly-phenotyped patient cohort and linked bioresource. Here we describe the infrastructure, data management and monitoring plans, and the standard operating procedures implemented to ensure the timely and systematic collection of high-quality data and samples. Already recruiting subjects at secondary/tertiary care centres across Europe, the Registry is supporting the European Union IMI2-funded LITMUS ‘Liver Investigation: Testing Marker Utility in Steatohepatitis’ consortium, which is a major international effort to robustly validate biomarkers that diagnose, risk stratify and/or monitor NAFLD progression and liver fibrosis stage. The European NAFLD Registry has the demonstrable capacity to support research and biomarker development at scale and pace., The European NAFLD Registry is supported by the LITMUS (Liver Investigation: Testing Biomarker Utility in Steatohepatitis) consortium funded by the European Union Innovative Medicines Initiative 2 (IMI2) Joint Undertaking under grant agreement 777377, which receives support from the Horizon 2020 Framework Program of European Union and EFPIA. It has also received support from the EPoS (Elucidating Pathways of Steatohepatitis) consortium funded by the Horizon 2020 Framework Program of the European Union under Grant Agreement 634413, the FLIP consortium funded by the Framework Program 7 of the European Union under grant agreement 241762, and an EASL Registry Grant from the European Association for the Study of the Liver.
Published: 2020
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14. The European NAFLD Registry: A real-world longitudinal cohort study of nonalcoholic fatty liver disease

Author: Universidad de Sevilla. Departamento de Medicina, Universidad de Sevilla. CTS-532: Unidad de Hepatología, Hardy, Timothy, Wonders, Kristy, Younes, Ramy, Aithal, Guruprasad P., Aller, Rocio, Allison, Michael, Romero Gómez, Manuel, Anstee, Quentin M., Universidad de Sevilla. Departamento de Medicina, Universidad de Sevilla. CTS-532: Unidad de Hepatología, Hardy, Timothy, Wonders, Kristy, Younes, Ramy, Aithal, Guruprasad P., Aller, Rocio, Allison, Michael, Romero Gómez, Manuel, and Anstee, Quentin M.
Abstract: Non-Alcoholic Fatty Liver Disease (NAFLD), a progressive liver disease that is closely associated with obesity, type 2 diabetes, hypertension and dyslipidaemia, represents an increasing global public health challenge. There is significant variability in the disease course: the majority exhibit only fat accumulation in the liver but a significant minority develop a necroinflammatory form of the disease (non-alcoholic steatohepatitis, NASH) that may progress to cirrhosis and hepatocellular carcinoma. At present our understanding of pathogenesis, disease natural history and long-term outcomes remain incomplete. There is a need for large, well characterised patient cohorts that may be used to address these knowledge gaps and to support the development of better biomarkers and novel therapies. The European NAFLD Registry is an international, prospectively recruited observational cohort study that aims to establish a large, highly-phenotyped patient cohort and linked bioresource. Here we describe the infrastructure, data management and monitoring plans, and the standard operating procedures implemented to ensure the timely and systematic collection of high-quality data and samples. Already recruiting subjects at secondary/tertiary care centres across Europe, the Registry is supporting the European Union IMI2-funded LITMUS ‘Liver Investigation: Testing Marker Utility in Steatohepatitis’ consortium, which is a major international effort to robustly validate biomarkers that diagnose, risk stratify and/or monitor NAFLD progression and liver fibrosis stage. The European NAFLD Registry has the demonstrable capacity to support research and biomarker development at scale and pace.
Published: 2020

15. The European NAFLD Registry: A real-world longitudinal cohort study of nonalcoholic fatty liver disease

Author: Innovative Medicines Initiative, European Commission, Hardy, Timothy, Wonders, Kristy, Younes, Ramy, Aithal, Guruprasad P., Aller, Rocío, Allison, Michael, Bedossa, Pierre, Betsou, Fay, Boursier, Jerome, Brosnan, M. Julia, Burt, Alastair, Cobbold, Jeremy, Cortez-Pinto, Helena, Day, Chris P., Dufour, Jean-François, Ekstedt, Mattias, Francque, Sven, Harrison, Stephen A., Miele, Luca, Nasr, Patrik, Papatheodoridis, George, Petta, Salvatore, Tiniakos, Dina, Torstenson, Richard, Valenti, Luca, Holleboom, Adriaan G., Yki-Järvinen, Hannele, Geier, Andreas, Romero-Gómez, Manuel, Ratziu, Vlad, Bugianesi, Elisabetta, Schattenberg, Jörn M., Anstee, Quentin M., Innovative Medicines Initiative, European Commission, Hardy, Timothy, Wonders, Kristy, Younes, Ramy, Aithal, Guruprasad P., Aller, Rocío, Allison, Michael, Bedossa, Pierre, Betsou, Fay, Boursier, Jerome, Brosnan, M. Julia, Burt, Alastair, Cobbold, Jeremy, Cortez-Pinto, Helena, Day, Chris P., Dufour, Jean-François, Ekstedt, Mattias, Francque, Sven, Harrison, Stephen A., Miele, Luca, Nasr, Patrik, Papatheodoridis, George, Petta, Salvatore, Tiniakos, Dina, Torstenson, Richard, Valenti, Luca, Holleboom, Adriaan G., Yki-Järvinen, Hannele, Geier, Andreas, Romero-Gómez, Manuel, Ratziu, Vlad, Bugianesi, Elisabetta, Schattenberg, Jörn M., and Anstee, Quentin M.
Abstract: Non-Alcoholic Fatty Liver Disease (NAFLD), a progressive liver disease that is closely associated with obesity, type 2 diabetes, hypertension and dyslipidaemia, represents an increasing global public health challenge. There is significant variability in the disease course: the majority exhibit only fat accumulation in the liver but a significant minority develop a necroinflammatory form of the disease (non-alcoholic steatohepatitis, NASH) that may progress to cirrhosis and hepatocellular carcinoma. At present our understanding of pathogenesis, disease natural history and long-term outcomes remain incomplete. There is a need for large, well characterised patient cohorts that may be used to address these knowledge gaps and to support the development of better biomarkers and novel therapies. The European NAFLD Registry is an international, prospectively recruited observational cohort study that aims to establish a large, highly-phenotyped patient cohort and linked bioresource. Here we describe the infrastructure, data management and monitoring plans, and the standard operating procedures implemented to ensure the timely and systematic collection of high-quality data and samples. Already recruiting subjects at secondary/tertiary care centres across Europe, the Registry is supporting the European Union IMI2-funded LITMUS ‘Liver Investigation: Testing Marker Utility in Steatohepatitis’ consortium, which is a major international effort to robustly validate biomarkers that diagnose, risk stratify and/or monitor NAFLD progression and liver fibrosis stage. The European NAFLD Registry has the demonstrable capacity to support research and biomarker development at scale and pace.
Published: 2020

16. Transcriptomic profiling across the nonalcoholic fatty liver disease spectrum reveals gene signatures for steatohepatitis and fibrosis

Author: Govaere, Olivier, Cockell, Simon, Tiniakos, Dina, Queen, Rachel, Younes, Ramy, Vacca, Michele, Alexander, Leigh, Ravaioli, Federico, Palmer, Jeremy, Petta, Salvatore, Boursier, Jerome, Rosso, Chiara, Johnson, Katherine, Wonders, Kristy, Day, Christopher P., Ekstedt, Mattias, Oresic, Matej, Darlay, Rebecca, Cordell, Heather J., Marra, Fabio, Vidal-Puig, Antonio, Bedossa, Pierre, Schattenberg, Jörn M., Clément, Karine, Allison, Michael, Bugianesi, Elisabetta, Ratziu, Vlad, Daly, Ann K., Anstee, Quentin M., Govaere, Olivier, Cockell, Simon, Tiniakos, Dina, Queen, Rachel, Younes, Ramy, Vacca, Michele, Alexander, Leigh, Ravaioli, Federico, Palmer, Jeremy, Petta, Salvatore, Boursier, Jerome, Rosso, Chiara, Johnson, Katherine, Wonders, Kristy, Day, Christopher P., Ekstedt, Mattias, Oresic, Matej, Darlay, Rebecca, Cordell, Heather J., Marra, Fabio, Vidal-Puig, Antonio, Bedossa, Pierre, Schattenberg, Jörn M., Clément, Karine, Allison, Michael, Bugianesi, Elisabetta, Ratziu, Vlad, Daly, Ann K., and Anstee, Quentin M.
Abstract: The mechanisms that drive nonalcoholic fatty liver disease (NAFLD) remain incompletely understood. This large multicenter study characterized the transcriptional changes that occur in liver tissue across the NAFLD spectrum as disease progresses to cirrhosis to identify potential circulating markers. We performed high-throughput RNA sequencing on a discovery cohort comprising histologically characterized NAFLD samples from 206 patients. Unsupervised clustering stratified NAFLD on the basis of disease activity and fibrosis stage with differences in age, aspartate aminotransferase (AST), type 2 diabetes mellitus, and carriage of PNPLA3 rs738409, a genetic variant associated with NAFLD. Relative to early disease, we consistently identified 25 differentially expressed genes as fibrosing steatohepatitis progressed through stages F2 to F4. This 25-gene signature was independently validated by logistic modeling in a separate replication cohort (n = 175), and an integrative analysis with publicly available single-cell RNA sequencing data elucidated the likely relative contribution of specific intrahepatic cell populations. Translating these findings to the protein level, SomaScan analysis in more than 300 NAFLD serum samples confirmed that circulating concentrations of proteins AKR1B10 and GDF15 were strongly associated with disease activity and fibrosis stage. Supporting the biological plausibility of these data, in vitro functional studies determined that endoplasmic reticulum stress up-regulated expression of AKR1B10, GDF15, and PDGFA, whereas GDF15 supplementation tempered the inflammatory response in macrophages upon lipid loading and lipopolysaccharide stimulation. This study provides insights into the pathophysiology of progressive fibrosing steatohepatitis, and proof of principle that transcriptomic changes represent potentially tractable and clinically relevant markers of disease progression., Funding Agencies:EPoS consortium - Horizon 2020 Framework Program of the European Union 634413Innovative Medicines Initiative (IMI2) Program of the European Union 777377
Published: 2020
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17. Transcriptomic profiling across the nonalcoholic fatty liver disease spectrum reveals gene signatures for steatohepatitis and fibrosis

Author: Govaere, Olivier, primary, Cockell, Simon, additional, Tiniakos, Dina, additional, Queen, Rachel, additional, Younes, Ramy, additional, Vacca, Michele, additional, Alexander, Leigh, additional, Ravaioli, Federico, additional, Palmer, Jeremy, additional, Petta, Salvatore, additional, Boursier, Jerome, additional, Rosso, Chiara, additional, Johnson, Katherine, additional, Wonders, Kristy, additional, Day, Christopher P., additional, Ekstedt, Mattias, additional, Orešič, Matej, additional, Darlay, Rebecca, additional, Cordell, Heather J., additional, Marra, Fabio, additional, Vidal-Puig, Antonio, additional, Bedossa, Pierre, additional, Schattenberg, Jörn M., additional, Clément, Karine, additional, Allison, Michael, additional, Bugianesi, Elisabetta, additional, Ratziu, Vlad, additional, Daly, Ann K., additional, and Anstee, Quentin M., additional
Published: 2020
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18. The European NAFLD Registry: A real-world longitudinal cohort study of nonalcoholic fatty liver disease

Author: Hardy, Timothy, Wonders, Kristy, Younes, Ramy, Aithal, Guruprasad P, Aller, Rocio, Allison, Michael, Bedossa, Pierre, Betsou, Fay, Boursier, Jerome, Brosnan, M Julia, Burt, Alastair, Cobbold, Jeremy, Cortez-Pinto, Helena, Day, Chris P, Dufour, Jean-François, Ekstedt, Mattias, Francque, Sven, Harrison, Stephen, Miele, Luca, Nasr, Patrik, Papatheodoridis, George, Petta, Salvatore, Tiniakos, Dina, Torstenson, Richard, Valenti, Luca, Holleboom, Adriaan G, Yki-Jarvinen, Hannele, Geier, Andreas, Romero-Gomez, Manuel, Ratziu, Vlad, Bugianesi, Elisabetta, Schattenberg, Jörn M, and Anstee, Quentin M
Subjects: 610 Medicine & health, 3. Good health
Abstract: Non-Alcoholic Fatty Liver Disease (NAFLD), a progressive liver disease that is closely associated with obesity, type 2 diabetes, hypertension and dyslipidaemia, represents an increasing global public health challenge. There is significant variability in the disease course: the majority exhibit only fat accumulation in the liver but a significant minority develop a necroinflammatory form of the disease (non-alcoholic steatohepatitis, NASH) that may progress to cirrhosis and hepatocellular carcinoma. At present our understanding of pathogenesis, disease natural history and long-term outcomes remain incomplete. There is a need for large, well characterised patient cohorts that may be used to address these knowledge gaps and to support the development of better biomarkers and novel therapies. The European NAFLD Registry is an international, prospectively recruited observational cohort study that aims to establish a large, highly-phenotyped patient cohort and linked bioresource. Here we describe the infrastructure, data management and monitoring plans, and the standard operating procedures implemented to ensure the timely and systematic collection of high-quality data and samples. Already recruiting subjects at secondary/tertiary care centres across Europe, the Registry is supporting the European Union IMI2-funded LITMUS 'Liver Investigation: Testing Marker Utility in Steatohepatitis' consortium, which is a major international effort to robustly validate biomarkers that diagnose, risk stratify and/or monitor NAFLD progression and liver fibrosis stage. The European NAFLD Registry has the demonstrable capacity to support research and biomarker development at scale and pace.

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

Author: Raluca Pais, Rachel Ostroff, Stephen Harrison, Lars Friis Mikkelsen, Elisabeth Erhardtsen, Sudha Shankar, Kimmo Porthan, Jérôme Boursier, Antonia Sinisi, Michael Kalutkiewicz, Sven Francque, Miljen Martic, Vanessa Pellegrinelli, Phil N. Newsome, Guido Hanauer, Hannele Yki-Järvinen, Rebecca Darlay, Joel Myers, Carla Yunis, Salvatore Petta, Mette Skalshøi Kjær, Pablo Ortiz, Ann K. Daly, James H. Clark, Dina Tiniakos, Yasaman Vali, Hadi Zafarmand, Matej Orešič, Maurizio Parola, Estelle Sandt, Lori L. Jennings, Matt Kelly, Tuulia Hyötyläinen, Detlef Schuppan, Céline Fournier, Chiara Rosso, Diane E. Shevell, Maria Manuela Tonini, Paul Hockings, Aidan McGlinchey, Salma Akhtar, Mette Juul Fisker, Morten A. Karsdal, Diane Whalley, Melissa R. Miller, Aldo Trylesinski, Mattias Ekstedt, Stefan Neubauer, Jeremy M. Palmer, Partho Sen, Michael Pavlides, Per Qvist, Isabel Fernández, Luca Miele, Fabio Marra, Stergios Kechagias, Richard Torstenson, Katherine Johnson, Jean-François Dufour, Elisabetta Bugianesi, M. Julia Brosnan, George V. Papatheodoridis, Kay M. Pepin, Daniel Guldager Kring Rasmussen, Henrik Landgren, Rachel Queen, Simon Cockell, Michael Allison, Patrick M.M. Bossuyt, Rocío Gallego-Durán, Christian Rosenquist, Leigh Alexander, Elizabeth Shumbayawonda, Michele Vacca, Antonio Vidal-Puig, David Wenn, Rémy Hanf, Oscar Millet, Michalina Zatorska, R. Myers, José M. Mato, Jenny Lee, Theresa Tuthill, James Twiss, Ramy Younes, Peter Leary, Lynda Doward, Kristy Wonders, Guruprasad P. Aithal, Sarah Charlton, Vlad Ratziu, Cecília M. P. Rodrigues, Christian Trautwein, Helena Cortez-Pinto, Gideon Ho, Matt J. Barter, Judith Ertle, Jörn M. Schattenberg, Maria-Magdalena Balp, Yang-Lin Liu, Clifford A. Brass, Olivier Govaere, Amalia Gastaldelli, Sergio Rodriguez Cuenca, Pierre Chaumat, Fiona Oakley, Luca Valenti, Simon J. Cockell, Saskia W.C. van Mil, Ferenc E. Mózes, Andreas Geier, Timothy Hardy, Pierre Bedossa, Andrea Dennis, Richard L. Ehman, Charlotte Erpicum, Karine Clément, Jeremy F. L. Cobbold, Christopher P. Day, Rajarshi Banerjee, Manuel Romero-Gómez, Quentin M. Anstee, Adriaan G. Holleboom, Heather J. Cordell, Kevin L. Duffin, Diana Julie Leeming, Epidemiology and Data Science, APH - Methodology, APH - Personalized Medicine, Vascular Medicine, ACS - Diabetes & metabolism, AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, APH - Aging & Later Life, ARD - Amsterdam Reproduction and Development, Graduate School, Investigators, LITMUS Consortium, Johnson K., Leary P.J., Govaere O., Barter M.J., Charlton S.H., Cockell S.J., Tiniakos D., Zatorska M., Bedossa P., Brosnan M.J., Cobbold J.F., Ekstedt M., Aithal G.P., Clement K., Schattenberg J.M., Boursier J., Ratziu V., Bugianesi E., Anstee Q.M., Daly A.K., Clark J., Cordell H.J., Darlay R., Day C.P., Hardy T., Liu Y.-L., Oakley F., Palmer J., Queen R., Wonders K., Bossuyt P.M., Holleboom A.G., Zafarmand H., Vali Y., Lee J., Pais R., Schuppan D., Allison M., Cuenca S.R., Pellegrinelli V., Vacca M., Vidal-Puig A., Hyotylainen T., McGlinchey A., Oresic M., Sen P., Mato J., Millet O., Dufour J.-F., Harrison S., Neubauer S., Pavlides M., Mozes F., Akhtar S., Banerjee R., Kelly M., Shumbayawonda E., Dennis A., Erpicum C., Romero-Gomez M., Gallego-Duran R., Fernandez I., Karsdal M., Leeming D., Fisker M.J., Erhardtsen E., Rasmussen D., Qvist P., Sinisi A., Sandt E., Tonini M.M., Parola M., Rosso C., Marra F., Gastaldelli A., Francque S., Kechagias S., Yki-Jarvinen H., Porthan K., van Mil S., Papatheodoridis G., Cortez-Pinto H., Valenti L., Petta S., Miele L., Geier A., Trautwein C., Hockings P., Newsome P., Wenn D., Pereira Rodrigues C.M., Hanf R., Chaumat P., Rosenquist C., Trylesinski A., Ortiz P., Duffin K., Yunis C., Miller M., Tuthill T., Ertle J., Younes R., Alexander L., Ostroff R., Kjaer M.S., Mikkelsen L.F., Brass C., Jennings L., Balp M.-M., Martic M., Hanauer G., Shankar S., Torstenson R., Fournier C., Ehman R., Kalutkiewicz M., Pepin K., Myers J., Shevell D., Ho G., Landgren H., Myers R., Doward L., Whalley D., Twiss J., 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, 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, and Yunis, Carla
Subjects: SCORING SYSTEM, CPM, counts per million, AUROC, area under the receiver operating characteristic, RC799-869, AST, aspartate aminotransferase, MicroRNA, Non-alcoholic fatty liver disease, Biomarker, Sequencing, TGF-β, transforming growth factor-beta, Gastroenterology, STEATOHEPATITIS, Liver disease, 0302 clinical medicine, Fibrosis, miRNA, microRNA, logFC, log2 fold change, FIBROSIS, Immunology and Allergy, 0303 health sciences, education.field_of_study, NAS, NAFLD activity score, medicine.diagnostic_test, Fatty liver, GTEx, Genotype-Tissue Expression, Diseases of the digestive system. Gastroenterology, 3. Good health, Real-time polymerase chain reaction, Biomarker, MicroRNA, Non-alcoholic fatty liver disease, Sequencing, Liver biopsy, ACID, Biomarker (medicine), 030211 gastroenterology & hepatology, Life Sciences & Biomedicine, Research Article, EXPRESSION, medicine.medical_specialty, NAFLD, non-alcoholic fatty liver disease, NASH, non-alcoholic steatohepatitis, Population, Gastroenterology and Hepatology, SAF, steatosis–activity–fibrosis, VALIDATION, ER, endoplasmic reticulum, 03 medical and health sciences, cDNA, complementary DNA, Internal medicine, ALT, alanine aminotransferase, Gastroenterologi, Internal Medicine, medicine, NAFL, non-alcoholic fatty liver, ALGORITHM, FIB-4, fibrosis-4, education, 030304 developmental biology, PCA, principal component analysis, Science & Technology, Gastroenterology & Hepatology, Hepatology, business.industry, FC, fold change, medicine.disease, digestive system diseases, FLIP, fatty liver inhibition of progression, Ct, cycle threshold, Steatosis, qPCR, quantitative PCR, business
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., Graphical abstract, Highlights • Serum miRNA was sequenced in 183 NAFLD cases of varying severity and 10 population controls. • Plasma levels of miR-193a-5p were significantly increased in patients with advanced fibrosis, high NAS scores, or high SAF scores. • Other miRNAs including miR378d and miR378e were also significantly increased in certain comparisons. • The findings for miR-193a-5p were replicated in a cohort of 372 additional NAFLD cases.
Published: 2022
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20. Scientific Business Abstracts.

Author: Cooles F, Vidal-Pedrola G, Naamane N, Pratt A, Barron-Millar B, Anderson A, Hilkens C, Casement J, Bondet V, Duffy D, Zhang F, Shukla R, Isaacs J, Little M, Payne M, Coupe N, Fairfax B, Taylor CA, Mackay S, Milotay G, Bos S, Hunter B, Mcdonald D, Merces G, Sheldon G, Pradère P, Majo J, Pulle J, Vanstapel A, Vanaudenaerde BM, Vos R, Filby AJ, Fisher AJ, Collier J, Lambton J, Suomi F, Prigent M, Guissart C, Erskine D, Rozanska A, Mccorvie T, Trimouille A, Imam A, Hobson E, Mccullagh H, Frengen E, Misceo D, Bjerre A, Smeland M, Klingenberg C, Alkuraya F, Mcfarland R, Alston C, Yue W, Legouis R, Koenig M, Lako M, Mcwilliams T, Oláhová M, Taylor R, Newman W, Harkness R, McDermott J, Metcalfe K, Khan N, Macken W, Pitceathly R, Record C, Maroofian R, Sabir A, Santra S, Urquhart J, Demain L, Byers H, Beaman G, Yue W, Taylor R, Durmusalioglu E, Atik T, Isik E, Cogulu O, Reunert J, Marquardt T, Ryba L, Buchert-Lo R, Haack T, Lassuthova P, Polavarapu K, Lochmuller H, Horvath R, Jamieson P, Reilly M, O'Keefe R, Boggan R, Ng YS, Franklin I, Alston C, Blakely E, Büchner B, Bugiardini E, Colclough K, Feeney C, Hanna M, Hattersley A, Klopstock T, Kornblum C, Mancuso M, Patel K, Pitceathly R, Pizzamiglio C, Prokisch H, Schäfer J, Schaefer A, Shepherd M, Thaele A, Thomas R, Turnbull D, Gorman G, Woodward C, McFarland R, Taylor R, Cordell H, Pickett S, Tsilifis C, Pearce M, Gennery A, Daly A, Darlay R, Zatorska M, Worthington S, Anstee Q, Cordell H, Reeves H, Nizami S, Mauricio-Muir J, McCain M, Singh R, Wordsworth J, Kadharusman M, Watson R, Masson S, McPherson S, Burt A, Tiniakos D, Littler P, Nsengimana J, Zhang S, Mann D, Jamieson D, Leslie J, Shukla R, Wilson C, Betts J, Croall I, Hoggard N, Bennett J, Naamane N, Hollingsworth KG, Pratt AG, Egail M, Feeney C, Di Leo V, Taylor RW, Dodds R, Anderson AE, Sayer AA, Isaacs JD, McCracken C, Condurache DG, Szabo L, Elghazaly H, Walter F, Meade A, Chakraverty R, Harvey N, Manisty C, Petersen S, Neubauer S, Raisi-Estabragh Z, Allen L, Taylor P, Carlsson A, Hagopian W, Hedlund E, Hill A, Jones A, Ludvigsson J, Onengut-Gumuscu S, Redondo M, Rich S, Gillespie K, Dayan C, Oram R, Resteu A, Wonders K, Schattenberg J, Straub B, Ekstedt M, Berzigotti A, Geier A, Francque S, Driessen A, Boursier J, Yki-Jarvinen H, Arola J, Aithal G, Holleboom A, Verheij J, Yunis C, Trylesinski A, Papatheodoridis G, Petta S, Romero-Gomez M, Bugianesi E, Paradis V, Ratziu V, Tiniakos D, Anstee Q, Burton J, Ciminata G, Geue C, Quinn T, Glover E, Morais M, Reynolds G, Denby L, Ali S, Lennon R, Sheerin N, Yang F, Zounemat-Kermani N, Dixey P, Adcock IM, Bloom CI, Chung KF, Govaere O, Hasoon M, Alexander L, Cockell S, Tiniakos D, Ekstedt M, Schattenberg JM, Boursier J, Bugianesi E, Ratziu V, Daly AK, and Anstee QM
Published: 2024
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21. Machine learning algorithm improves the detection of NASH (NAS-based) and at-risk NASH: A development and validation study.

Author: Lee J, Westphal M, Vali Y, Boursier J, Petta S, Ostroff R, Alexander L, Chen Y, Fournier C, Geier A, Francque S, Wonders K, Tiniakos D, Bedossa P, Allison M, Papatheodoridis G, Cortez-Pinto H, Pais R, Dufour JF, Leeming DJ, Harrison S, Cobbold J, Holleboom AG, Yki-Järvinen H, Crespo J, Ekstedt M, Aithal GP, Bugianesi E, Romero-Gomez M, Torstenson R, Karsdal M, Yunis C, Schattenberg JM, Schuppan D, Ratziu V, Brass C, Duffin K, Zwinderman K, Pavlides M, Anstee QM, and Bossuyt PM
Subjects: Adult, Humans, Liver pathology, Fibrosis, Algorithms, Biomarkers, Machine Learning, Biopsy, Liver Cirrhosis diagnosis, Liver Cirrhosis pathology, Non-alcoholic Fatty Liver Disease diagnosis, Non-alcoholic Fatty Liver Disease pathology
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., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)
Published: 2023
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22. The European NAFLD Registry: A real-world longitudinal cohort study of nonalcoholic fatty liver disease.

Author: Hardy T, Wonders K, Younes R, Aithal GP, Aller R, Allison M, Bedossa P, Betsou F, Boursier J, Brosnan MJ, Burt A, Cobbold J, Cortez-Pinto H, Day CP, Dufour JF, Ekstedt M, Francque S, Harrison S, Miele L, Nasr P, Papatheodoridis G, Petta S, Tiniakos D, Torstenson R, Valenti L, Holleboom AG, Yki-Jarvinen H, Geier A, Romero-Gomez M, Ratziu V, Bugianesi E, Schattenberg JM, and Anstee QM
Subjects: Cohort Studies, Humans, Liver pathology, Liver Cirrhosis diagnosis, Liver Cirrhosis epidemiology, Liver Cirrhosis pathology, Longitudinal Studies, Registries, Diabetes Mellitus, Type 2, Liver Neoplasms pathology, Non-alcoholic Fatty Liver Disease diagnosis, Non-alcoholic Fatty Liver Disease epidemiology, Non-alcoholic Fatty Liver Disease therapy
Abstract: Non-Alcoholic Fatty Liver Disease (NAFLD), a progressive liver disease that is closely associated with obesity, type 2 diabetes, hypertension and dyslipidaemia, represents an increasing global public health challenge. There is significant variability in the disease course: the majority exhibit only fat accumulation in the liver but a significant minority develop a necroinflammatory form of the disease (non-alcoholic steatohepatitis, NASH) that may progress to cirrhosis and hepatocellular carcinoma. At present our understanding of pathogenesis, disease natural history and long-term outcomes remain incomplete. There is a need for large, well characterised patient cohorts that may be used to address these knowledge gaps and to support the development of better biomarkers and novel therapies. The European NAFLD Registry is an international, prospectively recruited observational cohort study that aims to establish a large, highly-phenotyped patient cohort and linked bioresource. Here we describe the infrastructure, data management and monitoring plans, and the standard operating procedures implemented to ensure the timely and systematic collection of high-quality data and samples. Already recruiting subjects at secondary/tertiary care centres across Europe, the Registry is supporting the European Union IMI2-funded LITMUS 'Liver Investigation: Testing Marker Utility in Steatohepatitis' consortium, which is a major international effort to robustly validate biomarkers that diagnose, risk stratify and/or monitor NAFLD progression and liver fibrosis stage. The European NAFLD Registry has the demonstrable capacity to support research and biomarker development at scale and pace., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)
Published: 2020
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22 results on '"Wonders, Kristy"'

1. Pharmacogene expression during progression of metabolic dysfunction-associated steatotic liver disease: Studies on mRNA and protein levels and their relevance to drug treatment

2. Liver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS): Assessment & validation of imaging modality performance across the NAFLD spectrum in a prospectively recruited cohort study (the LITMUS imaging study): Study protocol

3. Performance of non-invasive tests and histology for the prediction of clinical outcomes in patients with non-alcoholic fatty liver disease: an individual participant data meta-analysis

4. Biomarkers for staging fibrosis and non-alcoholic steatohepatitis in non-alcoholic fatty liver disease (the LITMUS project): a comparative diagnostic accuracy study

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

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

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

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

9. Biomarkers for staging fibrosis and non-alcoholic steatohepatitis in non-alcoholic fatty liver disease (the LITMUS project): a comparative diagnostic accuracy study

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

11. Performance of non-invasive tests and histology for the prediction of clinical outcomes in patients with non-alcoholic fatty liver disease: an individual participant data meta-analysis

12. Diagnostic accuracy of elastography and magnetic resonance imaging in patients with NAFLD: A systematic review and meta-analysis

13. The European NAFLD Registry: A real-world longitudinal cohort study of nonalcoholic fatty liver disease

14. The European NAFLD Registry: A real-world longitudinal cohort study of nonalcoholic fatty liver disease

15. The European NAFLD Registry: A real-world longitudinal cohort study of nonalcoholic fatty liver disease

16. Transcriptomic profiling across the nonalcoholic fatty liver disease spectrum reveals gene signatures for steatohepatitis and fibrosis

17. Transcriptomic profiling across the nonalcoholic fatty liver disease spectrum reveals gene signatures for steatohepatitis and fibrosis

18. The European NAFLD Registry: A real-world longitudinal cohort study of nonalcoholic fatty liver disease

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

20. Scientific Business Abstracts.

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

22. The European NAFLD Registry: A real-world longitudinal cohort study of nonalcoholic fatty liver disease.

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