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8 results on '"Torres, Fanelly"'

1. Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration

Author

Jennison, Christopher, Ehrhardt, Beate, Baum, Patrick, Schoelsch, Corinna, Freijer, Jan, Grempler, Rolf, Graefe-Mody, Ulrike, Hennige, Anita, Dings, Christiane, Lehr, Thorsten, Scherer, Nina, Sihinecich, Iryna, Pattou, Francois, Raverdi, Violeta, Caiazzo, Robert, Torres, Fanelly, Verkindt, Helene, Mari, Andrea, Tura, Andrea, Giorgino, Toni, Bizzotto, Roberto, Froguel, Philippe, Bonneford, Amelie, Canouil, Mickael, Dhennin, Veronique, Brorsson, Caroline, Brunak, Soren, De Masi, Federico, Gudmundsdóttir, Valborg, Pedersen, Helle, Banasik, Karina, Thomas, Cecilia, Sackett, Peter, Staerfeldt, Hans-Henrik, Lundgaard, Agnete, Nilsson, Birgitte, Nielsen, Agnes, Mazzoni, Gianluca, Karaderi, Tugce, Rasmussen, Simon, Johansen, Joachim, Allesøe, Rosa, Fritsche, Andreas, Thorand, Barbara, Adamski, Jurek, Grallert, Harald, Haid, Mark, Sharma, Sapna, Troll, Martina, Adam, Jonathan, Ferrer, Jorge, Eriksen, Heather, Frost, Gary, Haussler, Ragna, Hong, Mun-gwan, Schwenk, Jochen, Uhlen, Mathias, Nicolay, Claudia, Pavo, Imre, Steckel-Hamann, Birgit, Thomas, Melissa, Adragni, Kofi, Wu, Han, Hart, Leen't, Roderick, Slieker, van Leeuwen, Nienke, Dekkers, Koen, Frau, Francesca, Gassenhuber, Johann, Jablonka, Bernd, Musholt, Petra, Ruetten, Hartmut, Tillner, Joachim, Baltauss, Tania, Bernard Poenaru, Oana, de Preville, Nathalie, Rodriquez, Marianne, Arumugam, Manimozhiyan, Allin, Kristine, Engelbrechtsen, Line, Hansen, Torben, Hansen, Tue, Forman, Annemette, Jonsson, Anna, Pedersen, Oluf, Dutta, Avirup, Vogt, Josef, Vestergaard, Henrik, Laakso, Markku, Kokkola, Tarja, Kuulasmaa, Teemu, Franks, Paul, Giordano, Nick, Pomares-Millan, Hugo, Fitipaldi, Hugo, Mutie, Pascal, Klintenberg, Maria, Bergstrom, Margit, Groop, Leif, Ridderstrale, Martin, Atabaki Pasdar, Naeimeh, Deshmukh, Harshal, Heggie, Alison, Wake, Dianne, McEvoy, Donna, McVittie, Ian, Walker, Mark, Hattersley, Andrew, Hill, Anita, Jones, Angus, McDonald, Timothy, Perry, Mandy, Nice, Rachel, Hudson, Michelle, Thorne, Claire, Dermitzakis, Emmanouil, Viñuela, Ana, Cabrelli, Louise, Loftus, Heather, Dawed, Adem, Donnelly, Louise, Forgie, Ian, Pearson, Ewan, Palmer, Colin, Brown, Andrew, Koivula, Robert, Wesolowska-Andersen, Agata, Abdalla, Moustafa, McRobert, Nicky, Fernandez, Juan, Jiao, Yunlong, Robertson, Neil, Gough, Stephen, Kaye, Jane, Mourby, Miranda, Mahajan, Anubha, McCarthy, Mark, Shah, Nisha, Teare, Harriet, Holl, Reinhard, Koopman, Anitra, Rutters, Femke, Beulens, Joline, Groeneveld, Lenka, Bell, Jimmy, Thomas, Louise, Whitcher, Brandon, Wilman, Henry R., Parisinos, Constantinos A., Atabaki-Pasdar, Naeimeh, Kelly, Matt, Thomas, E. Louise, Neubauer, Stefan, Hingorani, Aroon D., Patel, Riyaz S., Hemingway, Harry, Franks, Paul W., Bell, Jimmy D., Banerjee, Rajarshi, and Yaghootkar, Hanieh

Published
2019
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2. Islet transplantation versus insulin therapy in patients with type 1 diabetes with severe hypoglycaemia or poorly controlled glycaemia after kidney transplantation (TRIMECO): a multicentre, randomised controlled trial

Author

Malvezzi, Paolo, Tauveron, Igor, Roche, Béatrice, Noel, Christian, Frimat, Luc, Guerci, Bruno, Pernin, Nadine, Moisan, Anaick, Persoons, Virginie, Ezzouaoui, Rimed, Gmyr, Valery, Thony, Frédéric, Bricault, Yvan, Rodière, Mathieu, Sengel, Christian, Greget, Michel, Enescu, Iulian, Hazzan, Marc, Caiazzo, Robert, Torres, Fanelly, Le Mapihan, Kristel, Raverdy, Violetta, Pierredon, Marie-Ange, Valette, Pierre-Jean, Muller, Arnaud, Champagnac, Jean, Chaillous, Lucy, Dantal, Jacques, Cattan, Pierre, Riveline, Jean-Pierre, Moreau, François, Baltzinger, Philippe, Bahoune, Thibault, Lablanche, Sandrine, Vantyghem, Marie-Christine, Kessler, Laurence, Wojtusciszyn, Anne, Borot, Sophie, Thivolet, Charles, Girerd, Sophie, Bosco, Domenico, Bosson, Jean-Luc, Colin, Cyrille, Tetaz, Rachel, Logerot, Sophie, Kerr-Conte, Julie, Renard, Eric, Penfornis, Alfred, Morelon, Emmanuel, Buron, Fanny, Skaare, Kristina, Grguric, Gwen, Camillo-Brault, Coralie, Egelhofer, Harald, Benomar, Kanza, Badet, Lionel, Berney, Thierry, Pattou, François, and Benhamou, Pierre-Yves

Published
2018
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6. Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration

Author

Wilman, Henry R., Parisinos, Constantinos A., Atabaki-Pasdar, Naeimeh, Kelly, Matt, Thomas, E. Louise, Neubauer, Stefan, Jennison, Christopher, Ehrhardt, Beate, Baum, Patrick, Schoelsch, Corinna, Freijer, Jan, Grempler, Rolf, Graefe-Mody, Ulrike, Hennige, Anita, Dings, Christiane, Lehr, Thorsten, Scherer, Nina, Sihinecich, Iryna, Pattou, Francois, Raverdi, Violeta, Caiazzo, Robert, Torres, Fanelly, Verkindt, Helene, Mari, Andrea, Tura, Andrea, Giorgino, Toni, Bizzotto, Froguel, Philippe, Bonneford, Amelie, Canouil, Mickael, Dhennin, Veronique, Brorsson, Caroline, Brunak, Soren, de Masi, Federico, Gudmundsdóttir, Valborg, Pedersen, Helle, Banasik, Karina, Thomas, Cecilia, Sackett, Peter, Staerfeldt, Hans-Henrik, Lundgaard, Agnete, Koopman, Anitra, Rutters, Femke, Beulens, Joline, Groeneveld, Lenka, Thomas, Louise, Whitcher, Brandon, Mahajan, Anubha, Hingorani, Aroon D., Patel, Riyaz S., Hemingway, Harry, Franks, Paul W., Bell, Jimmy D., Banerjee, Rajarshi, Yaghootkar, Hanieh, Epidemiology and Data Science, APH - Health Behaviors & Chronic Diseases, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, and APH - Aging & Later Life

Abstract

Background & Aims: Excess liver iron content is common and is linked to the risk of hepatic and extrahepatic diseases. We aimed to identify genetic variants influencing liver iron content and use genetics to understand its link to other traits and diseases. Methods: First, we performed a genome-wide association study (GWAS) in 8,289 individuals from UK Biobank, whose liver iron level had been quantified by magnetic resonance imaging, before validating our findings in an independent cohort (n = 1,513 from IMI DIRECT). Second, we used Mendelian randomisation to test the causal effects of 25 predominantly metabolic traits on liver iron content. Third, we tested phenome-wide associations between liver iron variants and 770 traits and disease outcomes. Results: We identified 3 independent genetic variants (rs1800562 [C282Y] and rs1799945 [H63D] in HFE and rs855791 [V736A] in TMPRSS6) associated with liver iron content that reached the GWAS significance threshold (p

Published
2019
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7. Incidence and Predictive Factors of Postprandial Hyperinsulinemic Hypoglycemia After Roux-en-Y Gastric Bypass.

Author

Raverdy, Violeta, Baud, Gregory, Pigeyre, Marie, Verkindt, Helene, Torres, Fanelly, Preda, Cristian, Thuillier, Dorothee, Gélé, Patrick, Vantyghem, Marie-Christine, Caiazzo, Robert, and Pattou, François

Abstract

Background: Postprandial hyperinsulinemic hypoglycemia (PHH) is often reported after Roux-en-Y gastric bypass (RYGB). In the absence of a prospective study, the clinical and biological determinants of PHH remain unclear. Objective: To determine the incidence and predictive factors of PHH after RYGB. Methods: Participants were 957 RYGB patients enrolled in an ongoing longitudinal cohort study. We analyzed the results of an oral glucose tolerance test (OGTT) routinely performed before surgery and 1 and/or 5 years after. PHH was defined as blood glucose < 50 mg/dL AND plasma insulin > 3 mU/L at 120 minutes post glucose challenge. Validated indices of insulin sensitivity (Matsuda index), beta-cell function (Insulinogenic index), and beta-cell mass (fasting C-peptide: glucose ratio) were calculated, from glucose, insulin, and c-peptide values measured during OGTT. Results: OGTT results were available in all patients at baseline, in 85.6% at 12 months and 52.8% at 60 months. The incidence of PHH was 0.5% at baseline, 9.1% * and 7.9%* at 12 months and 60 months following RYGB (*: P < 0.001). In multivariate logistic regression analysis, PHH after RYGB was independently associated with lower age (P=0.005), greater weight loss (P= 0.031), as well as higher beta-cell function (P = 0.002) and insulin sensitivity (P < 0.001), but not with beta-cell mass (P = 0.381). A preoperative elevated beta-cell function was an independent predictor of PHH after RYGB (receiver operating characteristics curve area under the curve 0.68, P = 0.04). Conclusions: : The incidence of PHH significantly increased after RYGB but remained stable between 1 and 5 years. The estimation of beta-cell function with an OGTT before surgery can identify patients at risk for developing PHH after RYGB. [ABSTRACT FROM AUTHOR]

Published
2016
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8. Impact of Surgical Technique on Long-term Complication Rate After Laparoscopic Adjustable Gastric Banding (LAGB).

Author

Le Coq, Benjamin, Frering, Vincent, Ghunaim, Mohammed, Campan, Pierre, Dabrowski, André, Mulliez, Emmanuel, Loridan, Eric, Combemale, Frédéric, Denimal, Franck, Torres, Fanelly, Baud, Gregory, Thibault, Camille, Dezfoulian, Guelareh, Arnalsteen, Laurent, Duhamel, Alain, Pattou, François, and Caiazzo, Robert

Abstract

Objective: The aim of the study was to explore the impact of the absence of band fixation on the reoperation rate and to identify other risk factors for longterm complications. Background: Laparoscopic adjustable gastric banding has been demonstrated to permit important weight loss and comorbidity improvement, but some bands will have to be removed mainly for failure or in case of planned 2- step surgery. Then, the absence of a gastro-gastric suture (GGS) would allow easier band removal. There are insufficient data to conclude that GGS should be abandoned, as the associated risk of band slippage has not been prospectively assessed. Methods: The ANOSEAN study was a randomized controlled single-blind trial (CPP 2009-A00346-51). Primary outcome was reintervention rate for band removal or repositioning at 3 years. It included 706 patients in 17 bariatric centers. Patients in group 1 received a gastric band with GGS. Inclusion criteria were adapted from National Institutes of Health recommendations. Surgical technique was standardized among all surgeons. Results: At 3 years, the reintervention rate for band retrieval or repositioning was significantly higher in the absence of band fixation (19.4% vs11.3%; P = 0.013), partly because of the slippage rate (10.3% vs 3.6%; P = 0.005). Body mass index <40 kg/m² at baseline was also an independent risk factor of slippage (odds ratio 2.769, 95% confidence interval 1.373, 5.581). Conclusions: GGS prevents band slippage and lower reintervention rate at 3 years. Fixation could be discussed for patients with high BMI who are scheduled to undergo 2-step surgery, but it needs to be specifically assessed. [ABSTRACT FROM AUTHOR]

Published
2016
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