Multiomics unravels the complexity of male obesity: a prospective observational study
Abstract Background Obesity is associated with varying degrees of metabolic dysfunction. In this study, we aimed to discover markers of the severity of metabolic impairment in men with obesity via a multiomics approach. Methods Thirty-two morbidly men with obesity who were candidates for Roux-en-Y g...
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2025-01-01
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| author | Georgios E. Papadakis Lucie Favre Yassine Zouaghi Nathalie Vionnet Nicolas J. Niederländer Michela Adamo James S. Acierno Dassine Berdous Alexia Boizot Jenny Meylan Julijana Ivanisevic Emmanuelle Paccou Hector Gallart-Ayala Tim Reyns Elise Van Caeneghem Bruno Lapauw Jérôme Pasquier Yasser Aleman Styliani Mantziari Olivier Salamin Raul Nicoli Tiia Kuuranne Tom Fiers Patric Hagmann Federico Santoni Andrea Messina Nelly Pitteloud |
| author_facet | Georgios E. Papadakis Lucie Favre Yassine Zouaghi Nathalie Vionnet Nicolas J. Niederländer Michela Adamo James S. Acierno Dassine Berdous Alexia Boizot Jenny Meylan Julijana Ivanisevic Emmanuelle Paccou Hector Gallart-Ayala Tim Reyns Elise Van Caeneghem Bruno Lapauw Jérôme Pasquier Yasser Aleman Styliani Mantziari Olivier Salamin Raul Nicoli Tiia Kuuranne Tom Fiers Patric Hagmann Federico Santoni Andrea Messina Nelly Pitteloud |
| author_sort | Georgios E. Papadakis |
| collection | DOAJ |
| description | Abstract Background Obesity is associated with varying degrees of metabolic dysfunction. In this study, we aimed to discover markers of the severity of metabolic impairment in men with obesity via a multiomics approach. Methods Thirty-two morbidly men with obesity who were candidates for Roux-en-Y gastric bypass (RYGB) surgery were prospectively followed. Nine healthy adults served as controls. Deep phenotyping, including targeted metabolomics, transcriptomics, and brain magnetic resonance imaging (MRI), was performed. Results Testosterone emerged as a key contributor to phenotypic variability via principal component analysis and was therefore used to further categorize obese patients as having or not having hypogonadotropic hypogonadism (HH). Despite having comparable body mass indices, obese individuals with HH presented with worse metabolic defects than obese individuals without HH, including higher insulin resistance, as well as MRI signs of hypothalamic inflammation and a specific blood transcriptomics signature. The upregulated genes were involved mainly in inflammation, mitochondrial function, and protein translation. Integration of gene expression and clinical data revealed high FGF21 and low cortisol levels as the top markers correlated with the transcriptomic signature of metabolic risk. Following RYGB-induced substantial weight loss, testosterone levels markedly increased in both obese individuals with and without HH, challenging the current definition of hypogonadism. A longitudinal study in a subset of men with obesity following bariatric surgery revealed a unique FGF21 trajectory with a sharp peak at one month post-RYGB that correlated with metabolic and reproductive improvements. Conclusions Combining clinical, biochemical, and molecular markers allows adequate stratification of metabolic risk in men with obesity and provides novel tools for personalized care. |
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| institution | Kabale University |
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| language | English |
| publishDate | 2025-01-01 |
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| series | Journal of Translational Medicine |
| spelling | doaj-art-39113fb212cf4cf0bf630c0898ebe3832025-02-02T12:40:35ZengBMCJournal of Translational Medicine1479-58762025-01-0123111610.1186/s12967-024-06040-7Multiomics unravels the complexity of male obesity: a prospective observational studyGeorgios E. Papadakis0Lucie Favre1Yassine Zouaghi2Nathalie Vionnet3Nicolas J. Niederländer4Michela Adamo5James S. Acierno6Dassine Berdous7Alexia Boizot8Jenny Meylan9Julijana Ivanisevic10Emmanuelle Paccou11Hector Gallart-Ayala12Tim Reyns13Elise Van Caeneghem14Bruno Lapauw15Jérôme Pasquier16Yasser Aleman17Styliani Mantziari18Olivier Salamin19Raul Nicoli20Tiia Kuuranne21Tom Fiers22Patric Hagmann23Federico Santoni24Andrea Messina25Nelly Pitteloud26Department of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalMetabolomics Platform, Faculty of Biology and Medicine, University of LausanneDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalMetabolomics Platform, Faculty of Biology and Medicine, University of LausanneDepartment of Clinical Chemistry, Ghent University HospitalDepartment of Clinical Chemistry, Ghent University HospitalDepartment of Clinical Chemistry, Ghent University HospitalCenter for Primary Care and Public Health, University of LausanneDivision of Radio-Diagnostics and Interventional Radiology, Lausanne University HospitalFaculty of Biology and Medicine, University of LausanneSwiss Laboratory for Doping Analyses, University Center of Legal Medicine, Lausanne University Hospital and University of GenevaSwiss Laboratory for Doping Analyses, University Center of Legal Medicine, Lausanne University Hospital and University of GenevaSwiss Laboratory for Doping Analyses, University Center of Legal Medicine, Lausanne University Hospital and University of GenevaDepartment of Clinical Chemistry, Ghent University HospitalFaculty of Biology and Medicine, University of LausanneDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalDepartment of Endocrinology, Diabetology and Metabolism, Lausanne University HospitalAbstract Background Obesity is associated with varying degrees of metabolic dysfunction. In this study, we aimed to discover markers of the severity of metabolic impairment in men with obesity via a multiomics approach. Methods Thirty-two morbidly men with obesity who were candidates for Roux-en-Y gastric bypass (RYGB) surgery were prospectively followed. Nine healthy adults served as controls. Deep phenotyping, including targeted metabolomics, transcriptomics, and brain magnetic resonance imaging (MRI), was performed. Results Testosterone emerged as a key contributor to phenotypic variability via principal component analysis and was therefore used to further categorize obese patients as having or not having hypogonadotropic hypogonadism (HH). Despite having comparable body mass indices, obese individuals with HH presented with worse metabolic defects than obese individuals without HH, including higher insulin resistance, as well as MRI signs of hypothalamic inflammation and a specific blood transcriptomics signature. The upregulated genes were involved mainly in inflammation, mitochondrial function, and protein translation. Integration of gene expression and clinical data revealed high FGF21 and low cortisol levels as the top markers correlated with the transcriptomic signature of metabolic risk. Following RYGB-induced substantial weight loss, testosterone levels markedly increased in both obese individuals with and without HH, challenging the current definition of hypogonadism. A longitudinal study in a subset of men with obesity following bariatric surgery revealed a unique FGF21 trajectory with a sharp peak at one month post-RYGB that correlated with metabolic and reproductive improvements. Conclusions Combining clinical, biochemical, and molecular markers allows adequate stratification of metabolic risk in men with obesity and provides novel tools for personalized care.https://doi.org/10.1186/s12967-024-06040-7Male obesityMetabolic risk stratificationHypogonadismBariatric surgeryTranscriptomics |
| spellingShingle | Georgios E. Papadakis Lucie Favre Yassine Zouaghi Nathalie Vionnet Nicolas J. Niederländer Michela Adamo James S. Acierno Dassine Berdous Alexia Boizot Jenny Meylan Julijana Ivanisevic Emmanuelle Paccou Hector Gallart-Ayala Tim Reyns Elise Van Caeneghem Bruno Lapauw Jérôme Pasquier Yasser Aleman Styliani Mantziari Olivier Salamin Raul Nicoli Tiia Kuuranne Tom Fiers Patric Hagmann Federico Santoni Andrea Messina Nelly Pitteloud Multiomics unravels the complexity of male obesity: a prospective observational study Journal of Translational Medicine Male obesity Metabolic risk stratification Hypogonadism Bariatric surgery Transcriptomics |
| title | Multiomics unravels the complexity of male obesity: a prospective observational study |
| title_full | Multiomics unravels the complexity of male obesity: a prospective observational study |
| title_fullStr | Multiomics unravels the complexity of male obesity: a prospective observational study |
| title_full_unstemmed | Multiomics unravels the complexity of male obesity: a prospective observational study |
| title_short | Multiomics unravels the complexity of male obesity: a prospective observational study |
| title_sort | multiomics unravels the complexity of male obesity a prospective observational study |
| topic | Male obesity Metabolic risk stratification Hypogonadism Bariatric surgery Transcriptomics |
| url | https://doi.org/10.1186/s12967-024-06040-7 |
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