Search

Your search keyword '"Ho, Gideon"' showing total 35 results
Start Over Author "Ho, Gideon"
35 results on '"Ho, Gideon"'

1. 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
Full Text
View/download PDF

2. Outcome prediction in metabolic dysfunction‐associated steatotic liver disease using stain‐free digital pathological assessment.

Author

Kendall, Timothy J., Chng, Elaine, Ren, Yayun, Tai, Dean, Ho, Gideon, and Fallowfield, Jonathan A.

Subjects
FATTY liver, PATHOLOGY, LIVER biopsy, LIVER diseases, IMAGE processing
Abstract

Computational quantification reduces observer‐related variability in histological assessment of metabolic dysfunction‐associated steatotic liver disease (MASLD). We undertook stain‐free imaging using the SteatoSITE resource to generate tools directly predictive of clinical outcomes. Unstained liver biopsy sections (n = 452) were imaged using second‐harmonic generation/two‐photon excitation fluorescence (TPEF) microscopy, and all‐cause mortality and hepatic decompensation indices constructed. The mortality index had greater predictive power for all‐cause mortality (index >.14 vs. .31 vs.

Published
2024
Full Text
View/download PDF

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
Full Text
View/download PDF

5. Combination therapy of TERN-501, a selective agonist of thyroid hormone receptor (THR) beta with TERN-101, a farnesoid X receptor (FXR) agonist improves non-alcoholic steatohepatitis (NASH) in a GAN diet-induced and biopsy-confirmed mouse model

Author

Jones, Christopher, primary, Nielsen, Malte H., additional, Oró, Denise, additional, Feigh, Michael, additional, Teng, Xiao, additional, Lie, Anthony, additional, Ho, Gideon, additional, and Jasper, Jeffrey, additional

Published
2023
Full Text
View/download PDF

7. 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

9. 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

10. 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
Full Text
View/download PDF

11. 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
Full Text
View/download PDF

18. Computer-Assisted Transurethral Laser Resection of the Prostate (CALRP): Theoretical and Experimental Motion Plan

Author

Ho, Gideon, Ng, Wan S., Teo, Ming Y., Kwoh, Chee K., and Cheng, Wai S. C.

Subjects
Robotics -- Usage, Lasers in surgery -- Innovations, Biological sciences, Business, Computers, Health care industry
Abstract

Computer-Assisted transurethral laser resection of the prostate (CALRP) is a treatment modality that was designed and developed based on an integrated system of computer, robotics and laser technology in association with a minimally invasive surgery known as laser transurethral resection of the prostate (LRP). CALRP possesses complementary capabilities that could remedy many of the problems faced by surgeons in conventional LRP by delivering a treatment with repeatability and reliability. The work deals primarily in determining the feasibility study of the computer-assisted lasing motion plan (planned motion sequence controlled by a program) for LRP. A theoretical motion plan that analyzes numerically the lasing motion of the fiber was designed by calculating the profile removal rate and in vitro experiments conducted on human cadaveric prostate to verify and validate the designed motion plan. The novel motion plan, which was executed experimentally using the LaserTrode lightguide, accomplished the objective of resecting the enlarged prostate with the aid of computer and robotics technology. Index Terms--BPH, laser resection, LaserTrode, medical robotics, Nd: YAG laser.

Published
2001

19. Computer-assisted laser resection of the prostate (CALRP)

Author

Ho, Gideon., Teo, Ming Yeong, School of Mechanical and Production Engineering, and Kwoh, Chee Keong

Subjects
Engineering::Mechanical engineering::Surgical assistive technology [DRNTU]
Abstract

Computer-Assisted Laser Resection of the Prostate (CALRP) is a treatment modality which was designed and developed based on an integrated system of computer, robotics and laser technology in association with a minimal invasive surgery known as Laser transurethral Resection of the Prostate (LRP). The objective of this project is to utilise the CALRP system to aid the treatment of Benign Prostatic Hyperplasia (BPH). The scope of this work deals primarily in the feasibility and effectiveness of the computer-assisted lasing motion plan (planned motion sequence controlled by a program) for LRP. Using a mathe-matical software program, a theoretical motion plan that manipulates the lasing motion of the fi-bre has been designed based on the optimisation of various modon sequences. In zxtm experi-ments were conducted on chicken breast tissue and human cadaveric prostate to verify and vali-date the designed motion plan. The finalised motion plan was implemented into the automated lasing program to resect a replica prostate made up of human cadaveric prostate tissue embedded in an anatomically-alike prostate phantom. Comparison of removal rate made with Transurethral Resection of the Prostate (TURP), the 'gold' standard of Minimally Invasive Surgery (MIS) treatment and Holmium Laser Resection of the Prostate (HoLRP) evinced equivalent results. It was concluded that the novel motion plan designed by the author and demonstrated experi-mentally using the Lasertrrxk lightguide, accomplished the objective of resecting the enlarged prostate effectively and efficiently with the aid of computer and robotics technology. Master of Engineering (MPE)

Published
2000

34. Molecular imaging reveals a correlation between 2′-CH3-MPTP-induced neonatal neurotoxicity and dopaminergic neurodegeneration in adult transgenic mice

Author

Ho, Gideon, Kumar, Saravana, Zhang, Chunyan, Kng, Yin Ling, and Zhuo, Lang

Subjects
*NEUROSCIENCES, *MEDICAL sciences, *NEUROTOXICOLOGY, *CELLS
Abstract

Abstract: We previously reported that a single subcutaneous (s.c.) injection of the neurotoxicant, 1-methyl-4-(2′-methylphenyl)-1,2,3,6-tetrahydropyridine or 2′-CH3-MPTP, to postnatal day 4 (PD4) mice caused acute and transient gliosis in the brain, which can be noninvasively monitored during a course of 8h immediately after the dosing [Ho, G., Zhang, C.Y., Zhuo, L., 2007. Non-invasive fluorescent imaging of gliosis in transgenic mice for profiling developmental neurotoxicity. Toxicol. Appl. Pharmacol. 221, 76–85]. In the current study, we examined the consequence of PD4 mice receiving multiple injections (4×8mg/kg, s.c. in 2h intervals) of the same neurotoxicant 24–72h after the last injection. Here we showed that the multiple dosing scheme (with a higher cumulative dose) triggered a severe gliosis not only in the striatum and substantia nigra pars compacta (SNpc), but also in hippocampus and cerebellum when examined by noninvasive in vivo imaging and by immunohistochemistry (IHC), respectively, in the PD5 to PD7 mice. When neonates treated with the neurotoxicant at PD4 were allowed to develop to 10 weeks of age and examined with IHC, a majority of the dopaminergic (DA) neurons were found to be permanently depleted from the adult SNpc. Our findings suggest that neurotoxicant-elicited neonatal gliosis can be used as an early molecular signature to predict the permanent loss of DA neurons in the developed brain. Since 2′-CH3-MPTP is an inducer of Parkinsonism in mice, the molecular imaging method described here is a relatively simple and powerful tool for longitudinally studying the developmental aspect of Parkinsonism. [Copyright &y& Elsevier]

Published
2008
Full Text
View/download PDF

35. 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
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results