Life (Feb 2024)
A Federated Database for Obesity Research: An IMI-SOPHIA Study
- Carl Delfin,
- Iulian Dragan,
- Dmitry Kuznetsov,
- Juan Fernandez Tajes,
- Femke Smit,
- Daniel E. Coral,
- Ali Farzaneh,
- André Haugg,
- Andreas Hungele,
- Anne Niknejad,
- Christopher Hall,
- Daan Jacobs,
- Diana Marek,
- Diane P. Fraser,
- Dorothee Thuillier,
- Fariba Ahmadizar,
- Florence Mehl,
- Francois Pattou,
- Frederic Burdet,
- Gareth Hawkes,
- Ilja C. W. Arts,
- Jordi Blanch,
- Johan Van Soest,
- José-Manuel Fernández-Real,
- Juergen Boehl,
- Katharina Fink,
- Marleen M. J. van Greevenbroek,
- Maryam Kavousi,
- Michiel Minten,
- Nicole Prinz,
- Niels Ipsen,
- Paul W. Franks,
- Rafael Ramos,
- Reinhard W. Holl,
- Scott Horban,
- Talita Duarte-Salles,
- Van Du T. Tran,
- Violeta Raverdy,
- Yenny Leal,
- Adam Lenart,
- Ewan Pearson,
- Thomas Sparsø,
- Giuseppe N. Giordano,
- Vassilios Ioannidis,
- Keng Soh,
- Timothy M. Frayling,
- Carel W. Le Roux,
- Mark Ibberson
Affiliations
- Carl Delfin
- Novo Nordisk A/S, 2860 Søborg, Denmark
- Iulian Dragan
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
- Dmitry Kuznetsov
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
- Juan Fernandez Tajes
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre (CRC), Lund University, Jan Waldenströmsgata 35, SE-20502 Malmö, Sweden
- Femke Smit
- Maastricht Center for Systems Biology, Faculty of Science and Engineering, Maastricht University, Paul Henri Spaaklaan 1, 6229 EN Maastricht, The Netherlands
- Daniel E. Coral
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre (CRC), Lund University, Jan Waldenströmsgata 35, SE-20502 Malmö, Sweden
- Ali Farzaneh
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands
- André Haugg
- Global Biostatistics & Data Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, 88400 Biberach, Germany
- Andreas Hungele
- Institute of Epidemiology and Medical Biometry, CAQM, University of Ulm, 89081 Ulm, Germany
- Anne Niknejad
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
- Christopher Hall
- Division of Population Health and Genomics, Ninewells Hospital and School of Medicine, University of Dundee, Dundee DD1 4HN, UK
- Daan Jacobs
- Nederlandse Obesitas Kliniek, Huis Ter Heide, 3712 BA Utrecht, The Netherlands
- Diana Marek
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
- Diane P. Fraser
- University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK
- Dorothee Thuillier
- Univ Lille, Inserm, CHU Lille, Pasteur Institute Lille, U1190 Translational Research for Diabetes, European Genomic Institute of Diabetes, 59000 Lille, France
- Fariba Ahmadizar
- Data Science and Biostatistics Department, Julius Global Health, University Medical Center Utrecht, 3508 GA Utrecht, The Netherlands
- Florence Mehl
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
- Francois Pattou
- Univ Lille, Inserm, CHU Lille, Pasteur Institute Lille, U1190 Translational Research for Diabetes, European Genomic Institute of Diabetes, 59000 Lille, France
- Frederic Burdet
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
- Gareth Hawkes
- University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK
- Ilja C. W. Arts
- Maastricht Center for Systems Biology, Faculty of Science and Engineering, Maastricht University, Paul Henri Spaaklaan 1, 6229 EN Maastricht, The Netherlands
- Jordi Blanch
- Fundació Institut Universitari per a la Recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), 08007 Barcelona, Spain
- Johan Van Soest
- Brightlands Institute for Smart Society (BISS), Faculty of Science and Engineering, Maastricht University, 6229 EN Maastricht, The Netherlands
- José-Manuel Fernández-Real
- Nutrition, Eumetabolism and Health Group, Institut d’Investigació Biomèdica de Girona (IDIBGI-CERCA), Av. França 30, 17007 Girona, Spain
- Juergen Boehl
- Global Biostatistics & Data Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, 88400 Biberach, Germany
- Katharina Fink
- Institute of Epidemiology and Medical Biometry, CAQM, University of Ulm, 89081 Ulm, Germany
- Marleen M. J. van Greevenbroek
- Department of Internal Medicine and CARIM School of Cardiovascular Diseases, Maastricht University, 6229 EN Maastricht, The Netherlands
- Maryam Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, 3000 CA Rotterdam, The Netherlands
- Michiel Minten
- Maastricht Center for Systems Biology, Faculty of Science and Engineering, Maastricht University, Paul Henri Spaaklaan 1, 6229 EN Maastricht, The Netherlands
- Nicole Prinz
- Institute of Epidemiology and Medical Biometry, CAQM, University of Ulm, 89081 Ulm, Germany
- Niels Ipsen
- Novo Nordisk A/S, 2860 Søborg, Denmark
- Paul W. Franks
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre (CRC), Lund University, Jan Waldenströmsgata 35, SE-20502 Malmö, Sweden
- Rafael Ramos
- Fundació Institut Universitari per a la Recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), 08007 Barcelona, Spain
- Reinhard W. Holl
- Institute of Epidemiology and Medical Biometry, CAQM, University of Ulm, 89081 Ulm, Germany
- Scott Horban
- Division of Population Health and Genomics, Ninewells Hospital and School of Medicine, University of Dundee, Dundee DD1 4HN, UK
- Talita Duarte-Salles
- Fundació Institut Universitari per a la Recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), 08007 Barcelona, Spain
- Van Du T. Tran
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
- Violeta Raverdy
- Univ Lille, Inserm, CHU Lille, Pasteur Institute Lille, U1190 Translational Research for Diabetes, European Genomic Institute of Diabetes, 59000 Lille, France
- Yenny Leal
- Nutrition, Eumetabolism and Health Group, Institut d’Investigació Biomèdica de Girona (IDIBGI-CERCA), Av. França 30, 17007 Girona, Spain
- Adam Lenart
- Novo Nordisk A/S, 2860 Søborg, Denmark
- Ewan Pearson
- Division of Population Health and Genomics, Ninewells Hospital and School of Medicine, University of Dundee, Dundee DD1 4HN, UK
- Thomas Sparsø
- Novo Nordisk A/S, 2860 Søborg, Denmark
- Giuseppe N. Giordano
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Clinical Research Centre (CRC), Lund University, Jan Waldenströmsgata 35, SE-20502 Malmö, Sweden
- Vassilios Ioannidis
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
- Keng Soh
- Novo Nordisk A/S, 2860 Søborg, Denmark
- Timothy M. Frayling
- University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK
- Carel W. Le Roux
- Diabetes Complications Research Centre, University College Dublin, D04 V1W8 Dublin, Ireland
- Mark Ibberson
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
- DOI
- https://doi.org/10.3390/life14020262
- Journal volume & issue
-
Vol. 14,
no. 2
p. 262
Abstract
Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.
Keywords
