Marta Guasch-Ferré1,2,3,4, Miguel Ruiz-Canela3,5,6, Jun Li1,7, Yan Zheng8, Mònica Bulló2,3, Dong D Wang1, Estefanía Toledo3,5,6, Clary Clish9, Dolores Corella3,10, Ramon Estruch3,11, Emilio Ros3,12, Montserrat Fitó3,13, Fernando Arós3,14, Miquel Fiol3,15, José Lapetra3,16, Lluís Serra-Majem3,17, Liming Liang7,18, Christopher Papandreou2,3, Courtney Dennis9, Miguel A Martínez-González1,3,5,6, Frank B Hu1,4,7, Jordi Salas-Salvadó2,3. 1. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. 2. Human Nutrition Unit, Faculty of Medicine and Health Sciences, Pere Virgili Health Research Institute, Rovira i Virgili University, Reus, Spain. 3. CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain. 4. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts. 5. University of Navarra, Department of Preventive Medicine and Public Health, Pamplona, Spain. 6. Health Research Institute of Navarra, Pamplona, Spain. 7. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. 8. State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China. 9. Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts. 10. Department of Preventive Medicine, University of Valencia, Valencia, Spain. 11. Department of Internal Medicine, Hospital Clinic, August Pi Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain. 12. Lipid Clinic, Department of Endocrinology and Nutrition, Hospital Clinic, University of Barcelona, Barcelona, Spain. 13. Cardiovascular and Nutrition Research Group (REGICOR Study Group), Hospital del Mar Research Institute, Barcelona, Spain. 14. Department of Cardiology, Organización Sanitaria Integrada (OSI) ARABA, Universidad del País Vasco/Euskal Herriko Univertsitatea (UPV/EHU), Vitoria-Gasteiz, Spain. 15. Institute of Health Sciences (Institut Universitari d'Investigació en Ciències de la Salut-IUNICS), University of Balearic Islands and Hospital Son Espases, Palma de Mallorca, Spain. 16. Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Sevilla, Spain. 17. Research Institute of Biomedical and Health Sciences, University of Las Palmas de Gran Canaria and Service of Preventive Medicine, Complejo Hospitalario Universitario Insular Materno Infantil (CHUIMI), Canary Health Service, Las Palmas de Gran Canaria, Spain. 18. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Abstract
CONTEXT: The potential associations between acylcarnitine profiles and incidence of type 2 diabetes (T2D) and whether acylcarnitines can be used to improve diabetes prediction remain unclear. OBJECTIVE: To evaluate the associations between baseline and 1-year changes in acylcarnitines and their diabetes predictive ability beyond traditional risk factors. DESIGN, SETTING, AND PARTICIPANTS: We designed a case-cohort study within the PREDIMED Study including all incident cases of T2D (n = 251) and 694 randomly selected participants at baseline (follow-up, 3.8 years). Plasma acylcarnitines were measured using a targeted approach by liquid chromatography-tandem mass spectrometry. We tested the associations between baseline and 1-year changes in individual acylcarnitines and T2D risk using weighted Cox regression models. We used elastic net regressions to select acylcarnitines for T2D prediction and compute a weighted score using a cross-validation approach. RESULTS: An acylcarnitine profile, especially including short- and long-chain acylcarnitines, was significantly associated with a higher risk of T2D independent of traditional risk factors. The relative risks of T2D per SD increment of the predictive model scores were 4.03 (95% CI, 3.00 to 5.42; P < 0.001) for the conventional model and 4.85 (95% CI, 3.65 to 6.45; P < 0.001) for the model including acylcarnitines, with a hazard ratio of 1.33 (95% CI, 1.08 to 1.63; P < 0.001) attributed to the acylcarnitines. Including the acylcarnitines into the model did not significantly improve the area under the receiver operator characteristic curve (0.86 to 0.88, P = 0.61). A 1-year increase in C4OH-carnitine was associated with higher risk of T2D [per SD increment, 1.44 (1.03 to 2.01)]. CONCLUSIONS: An acylcarnitine profile, mainly including short- and long-chain acylcarnitines, was significantly associated with higher T2D risk in participants at high cardiovascular risk. The inclusion of acylcarnitines into the model did not significantly improve the T2D prediction C-statistics beyond traditional risk factors, including fasting glucose.
CONTEXT: The potential associations between acylcarnitine profiles and incidence of type 2 diabetes (T2D) and whether acylcarnitines can be used to improve diabetes prediction remain unclear. OBJECTIVE: To evaluate the associations between baseline and 1-year changes in acylcarnitines and their diabetes predictive ability beyond traditional risk factors. DESIGN, SETTING, AND PARTICIPANTS: We designed a case-cohort study within the PREDIMED Study including all incident cases of T2D (n = 251) and 694 randomly selected participants at baseline (follow-up, 3.8 years). Plasma acylcarnitines were measured using a targeted approach by liquid chromatography-tandem mass spectrometry. We tested the associations between baseline and 1-year changes in individual acylcarnitines and T2D risk using weighted Cox regression models. We used elastic net regressions to select acylcarnitines for T2D prediction and compute a weighted score using a cross-validation approach. RESULTS: An acylcarnitine profile, especially including short- and long-chain acylcarnitines, was significantly associated with a higher risk of T2D independent of traditional risk factors. The relative risks of T2D per SD increment of the predictive model scores were 4.03 (95% CI, 3.00 to 5.42; P < 0.001) for the conventional model and 4.85 (95% CI, 3.65 to 6.45; P < 0.001) for the model including acylcarnitines, with a hazard ratio of 1.33 (95% CI, 1.08 to 1.63; P < 0.001) attributed to the acylcarnitines. Including the acylcarnitines into the model did not significantly improve the area under the receiver operator characteristic curve (0.86 to 0.88, P = 0.61). A 1-year increase in C4OH-carnitine was associated with higher risk of T2D [per SD increment, 1.44 (1.03 to 2.01)]. CONCLUSIONS: An acylcarnitine profile, mainly including short- and long-chain acylcarnitines, was significantly associated with higher T2D risk in participants at high cardiovascular risk. The inclusion of acylcarnitines into the model did not significantly improve the T2D prediction C-statistics beyond traditional risk factors, including fasting glucose.
Authors: Sara Violante; Lodewijk Ijlst; Heleen Te Brinke; Janet Koster; Isabel Tavares de Almeida; Ronald J A Wanders; Fátima V Ventura; Sander M Houten Journal: Biochim Biophys Acta Date: 2013-07-10
Authors: Jordi Salas-Salvadó; Mònica Bulló; Ramón Estruch; Emilio Ros; Maria-Isabel Covas; Núria Ibarrola-Jurado; Dolores Corella; Fernando Arós; Enrique Gómez-Gracia; Valentina Ruiz-Gutiérrez; Dora Romaguera; José Lapetra; Rosa Maria Lamuela-Raventós; Lluís Serra-Majem; Xavier Pintó; Josep Basora; Miguel Angel Muñoz; José V Sorlí; Miguel A Martínez-González Journal: Ann Intern Med Date: 2014-01-07 Impact factor: 25.391
Authors: Marta Guasch-Ferré; Yan Zheng; Miguel Ruiz-Canela; Adela Hruby; Miguel A Martínez-González; Clary B Clish; Dolores Corella; Ramon Estruch; Emilio Ros; Montserrat Fitó; Courtney Dennis; Isabel M Morales-Gil; Fernando Arós; Miquel Fiol; José Lapetra; Lluís Serra-Majem; Frank B Hu; Jordi Salas-Salvadó Journal: Am J Clin Nutr Date: 2016-04-20 Impact factor: 7.045
Authors: Nina P Paynter; Raji Balasubramanian; Franco Giulianini; Dong D Wang; Lesley F Tinker; Shuba Gopal; Amy A Deik; Kevin Bullock; Kerry A Pierce; Justin Scott; Miguel A Martínez-González; Ramon Estruch; JoAnn E Manson; Nancy R Cook; Christine M Albert; Clary B Clish; Kathryn M Rexrode Journal: Circulation Date: 2018-02-20 Impact factor: 29.690
Authors: Ramón Estruch; Emilio Ros; Jordi Salas-Salvadó; Maria-Isabel Covas; Dolores Corella; Fernando Arós; Enrique Gómez-Gracia; Valentina Ruiz-Gutiérrez; Miquel Fiol; José Lapetra; Rosa M Lamuela-Raventos; Lluís Serra-Majem; Xavier Pintó; Josep Basora; Miguel A Muñoz; José V Sorlí; J Alfredo Martínez; Montserrat Fitó; Alfredo Gea; Miguel A Hernán; Miguel A Martínez-González Journal: N Engl J Med Date: 2018-06-13 Impact factor: 91.245
Authors: Oliver Fiehn; W Timothy Garvey; John W Newman; Kerry H Lok; Charles L Hoppel; Sean H Adams Journal: PLoS One Date: 2010-12-10 Impact factor: 3.240
Authors: Samantha Molsberry; Kjetil Bjornevik; Katherine C Hughes; Zhongli Joel Zhang; Sarah Jeanfavre; Clary Clish; Brian Healy; Michael Schwarzschild; Alberto Ascherio Journal: J Parkinsons Dis Date: 2020 Impact factor: 5.568
Authors: Marta Guasch-Ferré; Miguel Ruiz-Canela; Jun Li; Yan Zheng; Mònica Bulló; Dong D Wang; Estefanía Toledo; Clary Clish; Dolores Corella; Ramon Estruch; Emilio Ros; Montserrat Fitó; Fernando Arós; Miquel Fiol; José Lapetra; Lluís Serra-Majem; Liming Liang; Christopher Papandreou; Courtney Dennis; Miguel A Martínez-González; Frank B Hu; Jordi Salas-Salvadó Journal: J Clin Endocrinol Metab Date: 2019-05-01 Impact factor: 5.958
Authors: Miguel Ruiz-Canela; Marta Guasch-Ferré; Cristina Razquin; Estefanía Toledo; Pablo Hernández-Alonso; Clary B Clish; Jun Li; Clemens Wittenbecher; Courtney Dennis; Ángel Alonso-Gómez; Enrique Almanza-Aguilera; Liming Liang; Dolores Corella; Enrique Gómez-Gracia; Ramón Estruch; Miguel Fiol; José Lapetra; Lluis Serra-Majem; Emilio Ros; Fernando Arós; Jordi Salas-Salvadó; Frank B Hu; Miguel Ángel Martínez-González Journal: Rev Esp Cardiol (Engl Ed) Date: 2021-12-02
Authors: Meghana D Gadgil; Alka M Kanaya; Caroline Sands; Matthew R Lewis; Namratha R Kandula; David M Herrington Journal: Diabet Med Date: 2020-12-25 Impact factor: 4.359
Authors: Pablo Hernández-Alonso; Nerea Becerra-Tomás; Christopher Papandreou; Mònica Bulló; Marta Guasch-Ferré; Estefanía Toledo; Miguel Ruiz-Canela; Clary B Clish; Dolores Corella; Courtney Dennis; Amy Deik; Dong D Wang; Cristina Razquin; Jean-Philippe Drouin-Chartier; Ramon Estruch; Emilio Ros; Montserrat Fitó; Fernando Arós; Miquel Fiol; Lluís Serra-Majem; Liming Liang; Miguel A Martínez-González; Frank B Hu; Jordi Salas-Salvadó Journal: Mol Nutr Food Res Date: 2020-05-25 Impact factor: 6.575
Authors: Dan Ziegler; Alexander Strom; Klaus Straßburger; Birgit Knebel; Gidon J Bönhof; Jörg Kotzka; Julia Szendroedi; Michael Roden Journal: Diabetologia Date: 2020-10-21 Impact factor: 10.122