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Lynch F, Meng Y, Best S, Goranitis I, Savulescu J, Gyngell C, Vears DF. Australian public perspectives on genomic data governance: responsibility, regulation, and logistical considerations. Eur J Hum Genet 2024; 32:295-301. [PMID: 37165103 PMCID: PMC10923910 DOI: 10.1038/s41431-023-01381-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 03/13/2023] [Accepted: 04/26/2023] [Indexed: 05/12/2023] Open
Abstract
Genomic sequencing generates huge volumes of data, which may be collected or donated to form large genomic databases. Such information can be stored for future use, either for the data donor themselves or by researchers to help improve our understanding of the genetic basis of disease. Creating datasets of this magnitude and diversity is only possible if patients, their families, and members of the public worldwide share their data. However, there is no consensus on the best technical approach to data sharing that also minimises risks to individuals and exploration of stakeholders' views on aspects of genomic data governance models-the ways genomic data is stored, managed, shared and used-has been minimal. To address this need, we conducted focus groups with 39 members of the Australian public exploring their views and preferences for different aspects of genomic data governance models. We found that consent and control were essential to participants, as they wanted the option to choose who had access to their data and for what purposes. Critically, participants wanted a trustworthy body to enforce regulation of data storage, sharing and usage. While participants recognised the importance of data accessibility, they also expressed a strong desire for data security. Finally, financial responsibility for data storage raised concerns for inequity as well as organisations and individuals using data in ethically contentious ways to generate profit. Our findings highlight some of the trade-offs that need to be considered in the development of genomic data governance systems.
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Affiliation(s)
- Fiona Lynch
- Murdoch Children's Research Institute, Parkville, VIC, 3052, Australia
- The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Yan Meng
- The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Stephanie Best
- The University of Melbourne, Parkville, VIC, 3052, Australia
- Peter MacCallum Cancer Centre, Parkville, VIC, 3052, Australia
- Victorian Comprehensive Cancer Centre, Parkville, VIC, 3052, Australia
- Australian Genomics Health Alliance, Parkville, VIC, Australia
| | - Ilias Goranitis
- Murdoch Children's Research Institute, Parkville, VIC, 3052, Australia
- The University of Melbourne, Parkville, VIC, 3052, Australia
- Australian Genomics Health Alliance, Parkville, VIC, Australia
| | - Julian Savulescu
- Murdoch Children's Research Institute, Parkville, VIC, 3052, Australia
- The University of Melbourne, Parkville, VIC, 3052, Australia
- Chen Su Lan Centennial Professor in Medical Ethics, Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Christopher Gyngell
- Murdoch Children's Research Institute, Parkville, VIC, 3052, Australia
- The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Danya F Vears
- Murdoch Children's Research Institute, Parkville, VIC, 3052, Australia.
- The University of Melbourne, Parkville, VIC, 3052, Australia.
- Center for Biomedical Ethics and Law, Department of Public Health and Primary Care, Leuven, 3000, Belgium.
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Schröder M, Muller SH, Vradi E, Mielke J, Lim YM, Couvelard F, Mostert M, Koudstaal S, Eijkemans MJ, Gerlinger C. Sharing Medical Big Data While Preserving Patient Confidentiality in Innovative Medicines Initiative: A Summary and Case Report from BigData@Heart. BIG DATA 2023; 11:399-407. [PMID: 37889577 PMCID: PMC10733752 DOI: 10.1089/big.2022.0178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/29/2023]
Abstract
Sharing individual patient data (IPD) is a simple concept but complex to achieve due to data privacy and data security concerns, underdeveloped guidelines, and legal barriers. Sharing IPD is additionally difficult in big data-driven collaborations such as Bigdata@Heart in the Innovative Medicines Initiative, due to competing interests between diverse consortium members. One project within BigData@Heart, case study 1, needed to pool data from seven heterogeneous data sets: five randomized controlled trials from three different industry partners, and two disease registries. Sharing IPD was not considered feasible due to legal requirements and the sensitive medical nature of these data. In addition, harmonizing the data sets for a federated data analysis was difficult due to capacity constraints and the heterogeneity of the data sets. An alternative option was to share summary statistics through contingency tables. Here it is demonstrated that this method along with anonymization methods to ensure patient anonymity had minimal loss of information. Although sharing IPD should continue to be encouraged and strived for, our approach achieved a good balance between data transparency while protecting patient privacy. It also allowed a successful collaboration between industry and academia.
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Affiliation(s)
- Megan Schröder
- The Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Ludwig-Maximilians-Universität München, Münich, Germany
| | - Sam H.A. Muller
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Eleni Vradi
- Biomedical Data Science II, Bayer AG, Berlin, Germany
| | - Johanna Mielke
- Research and Early Development, Bayer AG, Wuppertal, Germany
| | - Yvonne M.F. Lim
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Institute for Clinical Research, National Institutes of Health, Selangor, Malaysia
| | - Fabrice Couvelard
- Institut de Recherches Internationales SERVIER (I.R.I.S.), Suresnes, France
| | - Menno Mostert
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Stefan Koudstaal
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Division of Heart and Lungs, Department of Cardiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Department of Cardiology, Groene Hart Ziekenhuis, Gouda, The Netherlands
| | - Marinus J.C. Eijkemans
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Christoph Gerlinger
- Clinical Statistics and Data Insights, Bayer AG, Berlin, Germany
- Department of Gynecology, Obstetrics and Reproductive Medicine, University Medical School of Saarland, Homburg/Saar, Germany
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Bak MAR, Ploem MC, Tan HL, Blom MT, Willems DL. Towards trust-based governance of health data research. MEDICINE, HEALTH CARE, AND PHILOSOPHY 2023; 26:185-200. [PMID: 36633724 PMCID: PMC9835739 DOI: 10.1007/s11019-022-10134-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/12/2022] [Indexed: 05/13/2023]
Abstract
Developments in medical big data analytics may bring societal benefits but are also challenging privacy and other ethical values. At the same time, an overly restrictive data protection regime can form a serious threat to valuable observational studies. Discussions about whether data privacy or data solidarity should be the foundational value of research policies, have remained unresolved. We add to this debate with an empirically informed ethical analysis. First, experiences with the implementation of the General Data Protection Regulation (GDPR) within a European research consortium demonstrate a gap between the aims of the regulation and its effects in practice. Namely, strictly formalised data protection requirements may cause routinisation among researchers instead of substantive ethical reflection, and may crowd out trust between actors in the health data research ecosystem; while harmonisation across Europe and data sharing between countries is hampered by different interpretations of the law, which partly stem from different views about ethical values. Then, building on these observations, we use theory to argue that the concept of trust provides an escape from the privacy-solidarity debate. Lastly, the paper details three aspects of trust that can help to create a responsible research environment and to mitigate the encountered challenges: trust as multi-agent concept; trust as a rational and democratic value; and trust as method for priority setting. Mutual cooperation in research-among researchers and with data subjects-is grounded in trust, which should be more explicitly recognised in the governance of health data research.
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Affiliation(s)
- Marieke A R Bak
- Department of Ethics, Law and Humanities, Amsterdam UMC (Location AMC), University of Amsterdam, Meibergdreef 15, 1105 AZ, Amsterdam, The Netherlands.
| | - M Corrette Ploem
- Department of Ethics, Law and Humanities, Amsterdam UMC (Location AMC), University of Amsterdam, Meibergdreef 15, 1105 AZ, Amsterdam, The Netherlands
| | - Hanno L Tan
- Department of Cardiology, Amsterdam UMC (Location AMC), University of Amsterdam, Amsterdam, The Netherlands
- Netherlands Heart Institute, Utrecht, The Netherlands
| | - M T Blom
- Department of Cardiology, Amsterdam UMC (Location AMC), University of Amsterdam, Amsterdam, The Netherlands
| | - Dick L Willems
- Department of Ethics, Law and Humanities, Amsterdam UMC (Location AMC), University of Amsterdam, Meibergdreef 15, 1105 AZ, Amsterdam, The Netherlands
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Lynch F, Meng Y, Best S, Goranitis I, Savulescu J, Gyngell C, Vears DF. Australian public perspectives on genomic data storage and sharing: Benefits, concerns and access preferences. Eur J Med Genet 2023; 66:104676. [PMID: 36473622 DOI: 10.1016/j.ejmg.2022.104676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 11/15/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022]
Abstract
Diagnostic genomic sequencing generates unprecedented amounts of data. In addition to its primary use, this data could be used for a wide range of secondary purposes, including research and informing future healthcare for the data donor. These opportunities may require data to be shared with third parties. Although effective data sharing relies on public support, there are barriers which may prevent people from choosing to donate their genomic data and surprisingly few studies explore these barriers in depth. To address this need, this study aimed to qualitatively explore the Australian public's views and preferences for storing and sharing genomic data. Online focus groups were recorded, transcribed, and analysed using inductive content analysis. A total of 7 focus groups were conducted with 39 members of the Australian public ranging from 18 to 67 years of age. Participants were mostly supportive of genomic data being stored and shared for secondary purposes, recognising the potential benefits for individual health and wider medical research. However, some concerns were identified. Participants felt genomic data was particularly sensitive information, and raised the potential for discrimination, stigma, and other malicious uses of such data. Concerns for privacy and security of the data were also prevalent. Trustworthiness of data users was important when considering who genomic data should be shared with. Although participants were supportive of data being freely available to health professionals and researchers, they were opposed to insurance companies and employers accessing the data. There was greater controversy around sharing data with law enforcement and pharmaceutical companies. Participants recognised both benefits and harms to sharing with law enforcement. They were also cognizant of the dual purpose of pharmaceutical companies as both research and profit-driven organisations. Finally, participants expressed varying perspectives about sharing genomic data with family members, yet most agreed that explicit consent from the data donor should be required to share their information with relatives. This study highlighted several of the Australian public's perceived barriers and motivators for the storage and sharing of genomic data. Participants recognised both the benefits of collecting, storing and sharing such data widely but also the potential for harm from data misuse. While public acceptance of such endeavours is required to maximise the volume of data made available, the concerns around data access and security need to be addressed before this can occur. These findings also highlight the nuance and ethical complexity of decisions about who we should allow to access donated genomic data. These perspectives will be essential in helping to shape the way large-scale genomic data storage and sharing is developed and implemented in Australia, and internationally.
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Affiliation(s)
- Fiona Lynch
- Murdoch Children's Research Institute, Parkville, 3052, Australia; The University of Melbourne, Parkville, 3052, Australia
| | - Yan Meng
- The University of Melbourne, Parkville, 3052, Australia
| | - Stephanie Best
- The University of Melbourne, Parkville, 3052, Australia; Peter MacCallum Cancer Centre, Parkville, 3052, Australia; Victorian Comprehensive Cancer Centre, Parkville, 3052, Australia; Australian Genomics Health Alliance, Australia
| | - Ilias Goranitis
- Murdoch Children's Research Institute, Parkville, 3052, Australia; The University of Melbourne, Parkville, 3052, Australia; Australian Genomics Health Alliance, Australia
| | - Julian Savulescu
- Murdoch Children's Research Institute, Parkville, 3052, Australia; The University of Melbourne, Parkville, 3052, Australia; Chen Su Lan Centennial Professor in Medical Ethics, Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Christopher Gyngell
- Murdoch Children's Research Institute, Parkville, 3052, Australia; The University of Melbourne, Parkville, 3052, Australia
| | - Danya F Vears
- Murdoch Children's Research Institute, Parkville, 3052, Australia; The University of Melbourne, Parkville, 3052, Australia; Center for Biomedical Ethics and Law, Department of Public Health and Primary Care, Leuven, 3000, Belgium.
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5
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Smart SE, Agbedjro D, Pardiñas AF, Ajnakina O, Alameda L, Andreassen OA, Barnes TRE, Berardi D, Camporesi S, Cleusix M, Conus P, Crespo-Facorro B, D'Andrea G, Demjaha A, Di Forti M, Do K, Doody G, Eap CB, Ferchiou A, Guidi L, Homman L, Jenni R, Joyce E, Kassoumeri L, Lastrina O, Melle I, Morgan C, O'Neill FA, Pignon B, Restellini R, Richard JR, Simonsen C, Španiel F, Szöke A, Tarricone I, Tortelli A, Üçok A, Vázquez-Bourgon J, Murray RM, Walters JTR, Stahl D, MacCabe JH. Clinical predictors of antipsychotic treatment resistance: Development and internal validation of a prognostic prediction model by the STRATA-G consortium. Schizophr Res 2022; 250:1-9. [PMID: 36242784 PMCID: PMC9834064 DOI: 10.1016/j.schres.2022.09.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 08/03/2022] [Accepted: 09/04/2022] [Indexed: 11/06/2022]
Abstract
INTRODUCTION Our aim was to, firstly, identify characteristics at first-episode of psychosis that are associated with later antipsychotic treatment resistance (TR) and, secondly, to develop a parsimonious prediction model for TR. METHODS We combined data from ten prospective, first-episode psychosis cohorts from across Europe and categorised patients as TR or non-treatment resistant (NTR) after a mean follow up of 4.18 years (s.d. = 3.20) for secondary data analysis. We identified a list of potential predictors from clinical and demographic data recorded at first-episode. These potential predictors were entered in two models: a multivariable logistic regression to identify which were independently associated with TR and a penalised logistic regression, which performed variable selection, to produce a parsimonious prediction model. This model was internally validated using a 5-fold, 50-repeat cross-validation optimism-correction. RESULTS Our sample consisted of N = 2216 participants of which 385 (17 %) developed TR. Younger age of psychosis onset and fewer years in education were independently associated with increased odds of developing TR. The prediction model selected 7 out of 17 variables that, when combined, could quantify the risk of being TR better than chance. These included age of onset, years in education, gender, BMI, relationship status, alcohol use, and positive symptoms. The optimism-corrected area under the curve was 0.59 (accuracy = 64 %, sensitivity = 48 %, and specificity = 76 %). IMPLICATIONS Our findings show that treatment resistance can be predicted, at first-episode of psychosis. Pending a model update and external validation, we demonstrate the potential value of prediction models for TR.
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Affiliation(s)
- Sophie E Smart
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK; Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
| | - Deborah Agbedjro
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Antonio F Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Olesya Ajnakina
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; Department of Behavioural Science and Health, Institute of Epidemiology and Health Care, University College London, London, UK
| | - Luis Alameda
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; Centro de Investigacion en Red Salud Mental (CIBERSAM), Sevilla, Spain; Department of Psychiatry, Hospital Universitario Virgen del Rocio, IBiS, Universidad de Sevilla, Spain; TIPP (Treatment and Early Intervention in Psychosis Program), Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | | | - Domenico Berardi
- Department of Biomedical and Neuro-motor Sciences, Psychiatry Unit, Alma Mater Studiorum Università di Bologna, Bologna, Italy
| | - Sara Camporesi
- TIPP (Treatment and Early Intervention in Psychosis Program), Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland; Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Martine Cleusix
- Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Philippe Conus
- TIPP (Treatment and Early Intervention in Psychosis Program), Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Benedicto Crespo-Facorro
- Centro de Investigacion en Red Salud Mental (CIBERSAM), Sevilla, Spain; Department of Psychiatry, Hospital Universitario Virgen del Rocio, IBiS, Universidad de Sevilla, Spain
| | - Giuseppe D'Andrea
- Department of Biomedical and Neuro-motor Sciences, Psychiatry Unit, Alma Mater Studiorum Università di Bologna, Bologna, Italy
| | - Arsime Demjaha
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Marta Di Forti
- Social Genetics and Developmental Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; South London and Maudsley NHS Foundation Trust, London, UK
| | - Kim Do
- Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Gillian Doody
- Department of Medical Education, University of Nottingham Faculty of Medicine and Health Sciences, Nottingham, UK
| | - Chin B Eap
- Unit of Pharmacogenetics and Clinical Psychopharmacology, Centre for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland; School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland; Center for Research and Innovation in Clinical Pharmaceutical Sciences, University of Lausanne, Switzerland; Institute of Pharmaceutical Sciences of Western, Switzerland, University of Geneva, University of Lausanne
| | - Aziz Ferchiou
- Univ Paris Est Creteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Creteil, France; AP-HP, Hôpitaux Universitaires H. Mondor, DMU IMPACT, FHU ADAPT, Creteil, France
| | - Lorenzo Guidi
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team (BoTPT), Alma Mater Studiorum - University of Bologna, Bologna, Italy
| | - Lina Homman
- Disability Research Division (FuSa), Department of Behavioural Sciences and Learning, Linköping University, Linköping, Sweden
| | - Raoul Jenni
- Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Eileen Joyce
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Laura Kassoumeri
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Ornella Lastrina
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team (BoTPT), Alma Mater Studiorum - University of Bologna, Bologna, Italy
| | - Ingrid Melle
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Craig Morgan
- Health Service and Population Research, King's College London, London, UK; Centre for Society and Mental Health, King's College London, London, UK
| | - Francis A O'Neill
- Centre for Public Health, Institute of Clinical Sciences, Queens University Belfast, Belfast, UK
| | - Baptiste Pignon
- Univ Paris Est Creteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Creteil, France; AP-HP, Hôpitaux Universitaires H. Mondor, DMU IMPACT, FHU ADAPT, Creteil, France
| | - Romeo Restellini
- TIPP (Treatment and Early Intervention in Psychosis Program), Service of General Psychiatry, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland; Unit for Research in Schizophrenia, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Jean-Romain Richard
- Univ Paris Est Creteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Creteil, France
| | - Carmen Simonsen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway; Early Intervention in Psychosis Advisory Unit for South East Norway (TIPS Sør-Øst), Division of Mental Health and Addiction, Oslo University Hospital, Norway
| | - Filip Španiel
- Department of Applied Neuroscience and Neuroimaging, National Institute of Mental Health, Klecany, Czechia; Department of Psychiatry and Medical Psychology, Third Faculty of Medicine, Charles University, Prague, Czechia
| | - Andrei Szöke
- Univ Paris Est Creteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Creteil, France; AP-HP, Hôpitaux Universitaires H. Mondor, DMU IMPACT, FHU ADAPT, Creteil, France
| | - Ilaria Tarricone
- Department of Medical and Surgical Sciences, Bologna Transcultural Psychosomatic Team (BoTPT), Alma Mater Studiorum - University of Bologna, Bologna, Italy
| | - Andrea Tortelli
- Univ Paris Est Creteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Creteil, France; Groupe Hospitalier Universitaire Psychiatrie Neurosciences Paris, Pôle Psychiatrie Précarité, Paris, France
| | - Alp Üçok
- Istanbul University, Istanbul Faculty of Medicine, Department of Psychiatry, Istanbul, Turkey
| | - Javier Vázquez-Bourgon
- Centro de Investigacion en Red Salud Mental (CIBERSAM), Sevilla, Spain; Department of Psychiatry, University Hospital Marques de Valdecilla - Instituto de Investigación Marques de Valdecilla (IDIVAL), Santander, Spain; Department of Medicine and Psychiatry, School of Medicine, University of Cantabria, Santander, Spain
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - James T R Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Daniel Stahl
- Department of Biostatistics & Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - James H MacCabe
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK; South London and Maudsley NHS Foundation Trust, London, UK
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Pan H, Bakalov V, Cox L, Engle ML, Erickson SW, Feolo M, Guo Y, Huggins W, Hwang S, Kimura M, Krzyzanowski M, Levy J, Phillips M, Qin Y, Williams D, Ramos EM, Hamilton CM. Identifying Datasets for Cross-Study Analysis in dbGaP using PhenX. Sci Data 2022; 9:532. [PMID: 36050327 PMCID: PMC9434066 DOI: 10.1038/s41597-022-01660-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 08/23/2022] [Indexed: 11/09/2022] Open
Abstract
Identifying relevant studies and harmonizing datasets are major hurdles for data reuse. Common Data Elements (CDEs) can help identify comparable study datasets and reduce the burden of retrospective data harmonization, but they have not been required, historically. The collaborative team at PhenX and dbGaP developed an approach to use PhenX variables as a set of CDEs to link phenotypic data and identify comparable studies in dbGaP. Variables were identified as either comparable or related, based on the data collection mode used to harmonize data across mapped datasets. We further added a CDE data field in the dbGaP data submission packet to indicate use of PhenX and annotate linkages in the future. Some 13,653 dbGaP variables from 521 studies were linked through PhenX variable mapping. These variable linkages have been made accessible for browsing and searching in the repository through dbGaP CDE-faceted search filter and the PhenX variable search tool. New features in dbGaP and PhenX enable investigators to identify variable linkages among dbGaP studies and reveal opportunities for cross-study analysis.
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Affiliation(s)
- Huaqin Pan
- RTI International, Research Triangle Park, NC, USA.
| | | | - Lisa Cox
- RTI International, Research Triangle Park, NC, USA
| | | | | | - Michael Feolo
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Yuelong Guo
- GeneCentric Therapeutics Inc., Durham, NC, USA
| | | | | | - Masato Kimura
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | | | - Josh Levy
- Levy Informatics, Chapel Hill, NC, USA
| | | | - Ying Qin
- RTI International, Research Triangle Park, NC, USA
| | | | - Erin M Ramos
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
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7
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Belbasis L, Panagiotou OA. Reproducibility of prediction models in health services research. BMC Res Notes 2022; 15:204. [PMID: 35690767 PMCID: PMC9188254 DOI: 10.1186/s13104-022-06082-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 05/18/2022] [Indexed: 12/23/2022] Open
Abstract
The field of health services research studies the health care system by examining outcomes relevant to patients and clinicians but also health economists and policy makers. Such outcomes often include health care spending, and utilization of care services. Building accurate prediction models using reproducible research practices for health services research is important for evidence-based decision making. Several systematic reviews have summarized prediction models for outcomes relevant to health services research, but these systematic reviews do not present a thorough assessment of reproducibility and research quality of the prediction modelling studies. In the present commentary, we discuss how recent advances in prediction modelling in other medical fields can be applied to health services research. We also describe the current status of prediction modelling in health services research, and we summarize available methodological guidance for the development, update, external validation and systematic appraisal of prediction models.
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Affiliation(s)
- Lazaros Belbasis
- Meta-Research Innovation Center Berlin, QUEST Center, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, Berlin, Germany.
| | - Orestis A Panagiotou
- Center for Evidence Synthesis in Health, School of Public Health, Brown University, Providence, RI, USA.,Department of Health Services, Policy and Practice, School of Public Health, Brown University, Providence, RI, USA.,Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA
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8
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Weissbrod O, Kanai M, Shi H, Gazal S, Peyrot WJ, Khera AV, Okada Y, Martin AR, Finucane HK, Price AL. Leveraging fine-mapping and multipopulation training data to improve cross-population polygenic risk scores. Nat Genet 2022; 54:450-458. [PMID: 35393596 PMCID: PMC9009299 DOI: 10.1038/s41588-022-01036-9] [Citation(s) in RCA: 108] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 02/25/2022] [Indexed: 01/25/2023]
Abstract
Polygenic risk scores suffer reduced accuracy in non-European populations, exacerbating health disparities. We propose PolyPred, a method that improves cross-population polygenic risk scores by combining two predictors: a new predictor that leverages functionally informed fine-mapping to estimate causal effects (instead of tagging effects), addressing linkage disequilibrium differences, and BOLT-LMM, a published predictor. When a large training sample is available in the non-European target population, we propose PolyPred+, which further incorporates the non-European training data. We applied PolyPred to 49 diseases/traits in four UK Biobank populations using UK Biobank British training data, and observed relative improvements versus BOLT-LMM ranging from +7% in south Asians to +32% in Africans, consistent with simulations. We applied PolyPred+ to 23 diseases/traits in UK Biobank east Asians using both UK Biobank British and Biobank Japan training data, and observed improvements of +24% versus BOLT-LMM and +12% versus PolyPred. Summary statistics-based analogs of PolyPred and PolyPred+ attained similar improvements.
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Affiliation(s)
- Omer Weissbrod
- Epidemiology Department, Harvard School of Public Health, Boston, MA, USA.
| | - Masahiro Kanai
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Huwenbo Shi
- Epidemiology Department, Harvard School of Public Health, Boston, MA, USA
- OMNI Bioinformatics, San Francisco, CA, USA
| | - Steven Gazal
- Epidemiology Department, Harvard School of Public Health, Boston, MA, USA
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Wouter J Peyrot
- Epidemiology Department, Harvard School of Public Health, Boston, MA, USA
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands
| | - Amit V Khera
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Verve Therapeutics, Cambridge, MA, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | - Hilary K Finucane
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alkes L Price
- Epidemiology Department, Harvard School of Public Health, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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9
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Lacey JV, Benbow JL. Invited Commentary: Standards, Inputs, and Outputs-Strategies for Improving Data-Sharing and Consortia-Based Epidemiologic Research. Am J Epidemiol 2022; 191:159-162. [PMID: 34435200 DOI: 10.1093/aje/kwab217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 06/16/2021] [Accepted: 06/21/2021] [Indexed: 11/14/2022] Open
Abstract
Data-sharing improves epidemiologic research, but the sharing of data frustrates epidemiologic researchers. The inefficiencies of current methods and options for data-sharing are increasingly documented and easily understood by any study group that has shared its data and any researcher who has received shared data. In this issue of the Journal, Temprosa et al. (Am J Epidemiol. 2021;191(1):147-158) describe how the Consortium of Metabolomics Studies (COMETS) developed and deployed a flexible analytical platform to eliminate key pain points in large-scale metabolomics research. COMETS Analytics includes an online tool, but its cloud computing and technology are the supporting rather than the leading actors in this script. The COMETS team identified the need to standardize diverse and inconsistent metabolomics and covariate data and models across its many participating cohort studies, and then developed a flexible tool that gave its member studies choices about how they wanted to meet the consortium's analytical requirements. Different specialties will have different specific research needs and will probably continue to use and develop an array of diverse analytical and technical solutions for their projects. COMETS Analytics shows how important-and enabling-the upstream attention to data standards and data consistency is to producing high-quality metabolomics, consortia-based, and large-scale epidemiology research.
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10
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Shishegar R, Cox T, Rolls D, Bourgeat P, Doré V, Lamb F, Robertson J, Laws SM, Porter T, Fripp J, Tosun D, Maruff P, Savage G, Rowe CC, Masters CL, Weiner MW, Villemagne VL, Burnham SC. Using imputation to provide harmonized longitudinal measures of cognition across AIBL and ADNI. Sci Rep 2021; 11:23788. [PMID: 34893624 PMCID: PMC8664816 DOI: 10.1038/s41598-021-02827-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 11/12/2021] [Indexed: 12/12/2022] Open
Abstract
To improve understanding of Alzheimer’s disease, large observational studies are needed to increase power for more nuanced analyses. Combining data across existing observational studies represents one solution. However, the disparity of such datasets makes this a non-trivial task. Here, a machine learning approach was applied to impute longitudinal neuropsychological test scores across two observational studies, namely the Australian Imaging, Biomarkers and Lifestyle Study (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) providing an overall harmonised dataset. MissForest, a machine learning algorithm, capitalises on the underlying structure and relationships of data to impute test scores not measured in one study aligning it to the other study. Results demonstrated that simulated missing values from one dataset could be accurately imputed, and that imputation of actual missing data in one dataset showed comparable discrimination (p < 0.001) for clinical classification to measured data in the other dataset. Further, the increased power of the overall harmonised dataset was demonstrated by observing a significant association between CVLT-II test scores (imputed for ADNI) with PET Amyloid-β in MCI APOE-ε4 homozygotes in the imputed data (N = 65) but not for the original AIBL dataset (N = 11). These results suggest that MissForest can provide a practical solution for data harmonization using imputation across studies to improve power for more nuanced analyses.
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Affiliation(s)
- Rosita Shishegar
- The Australian e-Health Research Centre, CSIRO, Melbourne, Australia. .,School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia.
| | - Timothy Cox
- The Australian e-Health Research Centre, CSIRO, Melbourne, Australia
| | - David Rolls
- The Australian e-Health Research Centre, CSIRO, Melbourne, Australia
| | - Pierrick Bourgeat
- The Australian e-Health Research Centre, CSIRO, Melbourne, Australia
| | - Vincent Doré
- The Australian e-Health Research Centre, CSIRO, Melbourne, Australia.,Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, VIC, Australia
| | - Fiona Lamb
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, VIC, Australia
| | - Joanne Robertson
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Simon M Laws
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia.,Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.,School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, WA, Australia
| | - Tenielle Porter
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia.,Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia.,School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, WA, Australia
| | - Jurgen Fripp
- The Australian e-Health Research Centre, CSIRO, Melbourne, Australia
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA, USA
| | | | - Greg Savage
- Department of Psychology, Macquarie University, Sydney, NSW, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, VIC, Australia.,Department of Medicine, The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Colin L Masters
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Michael W Weiner
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, CA, USA
| | - Victor L Villemagne
- Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, VIC, Australia.,Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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11
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Vesteghem C, Brøndum RF, Sønderkær M, Sommer M, Schmitz A, Bødker JS, Dybkær K, El-Galaly TC, Bøgsted M. Implementing the FAIR Data Principles in precision oncology: review of supporting initiatives. Brief Bioinform 2021; 21:936-945. [PMID: 31263868 PMCID: PMC7299292 DOI: 10.1093/bib/bbz044] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Revised: 03/13/2019] [Accepted: 03/21/2019] [Indexed: 12/26/2022] Open
Abstract
Compelling research has recently shown that cancer is so heterogeneous that single research centres cannot produce enough data to fit prognostic and predictive models of sufficient accuracy. Data sharing in precision oncology is therefore of utmost importance. The Findable, Accessible, Interoperable and Reusable (FAIR) Data Principles have been developed to define good practices in data sharing. Motivated by the ambition of applying the FAIR Data Principles to our own clinical precision oncology implementations and research, we have performed a systematic literature review of potentially relevant initiatives. For clinical data, we suggest using the Genomic Data Commons model as a reference as it provides a field-tested and well-documented solution. Regarding classification of diagnosis, morphology and topography and drugs, we chose to follow the World Health Organization standards, i.e. ICD10, ICD-O-3 and Anatomical Therapeutic Chemical classifications, respectively. For the bioinformatics pipeline, the Genome Analysis ToolKit Best Practices using Docker containers offer a coherent solution and have therefore been selected. Regarding the naming of variants, we follow the Human Genome Variation Society's standard. For the IT infrastructure, we have built a centralized solution to participate in data sharing through federated solutions such as the Beacon Networks.
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Affiliation(s)
- Charles Vesteghem
- Department of Clinical Medicine, Aalborg University, Denmark.,Department of Haematology, Aalborg University Hospital, Denmark
| | | | - Mads Sønderkær
- Department of Haematology, Aalborg University Hospital, Denmark
| | - Mia Sommer
- Department of Clinical Medicine, Aalborg University, Denmark.,Department of Haematology, Aalborg University Hospital, Denmark
| | | | | | - Karen Dybkær
- Department of Clinical Medicine, Aalborg University, Denmark.,Department of Haematology, Aalborg University Hospital, Denmark.,Clinical Cancer Research Center, Aalborg University Hospital, Denmark
| | - Tarec Christoffer El-Galaly
- Department of Clinical Medicine, Aalborg University, Denmark.,Department of Haematology, Aalborg University Hospital, Denmark.,Clinical Cancer Research Center, Aalborg University Hospital, Denmark
| | - Martin Bøgsted
- Department of Clinical Medicine, Aalborg University, Denmark.,Department of Haematology, Aalborg University Hospital, Denmark.,Clinical Cancer Research Center, Aalborg University Hospital, Denmark
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12
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Campos MLM, Silva E, Cerceau R, da Cruz SMS, Silva FAB, Gouveia FC, Jardim R, Kotowski N, Lopes GR, Dávila AMR. Towards Machine-Readable (Meta) Data and the FAIR Value for Artificial Intelligence Exploration of COVID-19 and Cancer Research Data. Front Big Data 2021; 4:656553. [PMID: 34527943 PMCID: PMC8437372 DOI: 10.3389/fdata.2021.656553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 07/14/2021] [Indexed: 11/24/2022] Open
Affiliation(s)
- Maria Luiza. M. Campos
- Instituto de Computação, Universidade Federal do Rio de Janeiro, UFRJ, Rio de Janeiro, Brazil
| | - Eugênio Silva
- Unidade de Computação (Ucomp), Centro Universitario Estadual da Zona Oeste (UEZO), Rio de Janeiro, Brazil
| | - Renato Cerceau
- Instituto Nacional de Cardiologia, INC, Rio de Janeiro, Brazil
- Universidade do Estado do Rio de Janeiro, UERJ, Rio de Janeiro, Brazil
| | - Sérgio Manuel Serra da Cruz
- Instituto de Computação, Universidade Federal do Rio de Janeiro, UFRJ, Rio de Janeiro, Brazil
- Departamento de Ciências da Computação, Universidade Federal Rural do Rio de Janeiro, UFRRJ, Seropédica, Brazil
| | | | | | - Rodrigo Jardim
- Laboratório de Biologia Computacional e Sistemas, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - Nelson Kotowski
- Laboratório de Biologia Computacional e Sistemas, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - Giseli Rabello Lopes
- Instituto de Computação, Universidade Federal do Rio de Janeiro, UFRJ, Rio de Janeiro, Brazil
| | - Alberto. M. R. Dávila
- Laboratório de Biologia Computacional e Sistemas, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
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13
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Wilde EA, Dennis EL, Tate DF. The ENIGMA Brain Injury working group: approach, challenges, and potential benefits. Brain Imaging Behav 2021; 15:465-474. [PMID: 33506440 PMCID: PMC8035294 DOI: 10.1007/s11682-021-00450-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Revised: 12/29/2020] [Accepted: 01/03/2021] [Indexed: 12/26/2022]
Abstract
The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium brings together researchers from around the world to try to identify the genetic underpinnings of brain structure and function, along with robust, generalizable effects of neurological and psychiatric disorders. The recently-formed ENIGMA Brain Injury working group includes 10 subgroups, based largely on injury mechanism and patient population. This introduction to the special issue summarizes the history, organization, and objectives of ENIGMA Brain Injury, and includes a discussion of strategies, challenges, opportunities and goals common across 6 of the subgroups under the umbrella of ENIGMA Brain Injury. The following articles in this special issue, including 6 articles from different subgroups, will detail the challenges and opportunities specific to each subgroup.
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Affiliation(s)
- Elisabeth A Wilde
- TBICC, Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
- George E. Wahlen VA Medical Center, Salt Lake City, UT, USA
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA
| | - Emily L Dennis
- TBICC, Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA.
- George E. Wahlen VA Medical Center, Salt Lake City, UT, USA.
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, Los Angeles, CA, USA.
| | - David F Tate
- TBICC, Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
- George E. Wahlen VA Medical Center, Salt Lake City, UT, USA
- Missouri Institute of Mental Health, University of Missouri, St. Louis, MO, USA
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14
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Morrison M, Mourby M, Gowans H, Coy S, Kaye J. Governance of research consortia: challenges of implementing Responsible Research and Innovation within Europe. LIFE SCIENCES, SOCIETY AND POLICY 2020; 16:13. [PMID: 33190636 PMCID: PMC7667809 DOI: 10.1186/s40504-020-00109-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 10/27/2020] [Indexed: 06/11/2023]
Abstract
Responsible Research and Innovation ('RRI') is a cross-cutting priority for scientific research in the European Union and beyond. This paper considers whether the way such research is organised and delivered lends itself to the aims of RRI. We focus particularly on international consortia, which have emerged as a common model to organise large-scale, multi-disciplinary research in contemporary biomedical science. Typically, these consortia operate through fixed-term contracts, and employ governance frameworks consisting of reasonably standard, modular components such as management committees, advisory boards, and data access committees, to co-ordinate the activities of partner institutions and align them with funding agency priorities. These have advantages for organisation and management of the research, but can actively inhibit researchers seeking to implement RRI activities. Conventional consortia governance structures pose specific problems for meaningful public and participant involvement, data sharing, transparency, and 'legacy' planning to deal with societal commitments that persist beyond the duration of the original project. In particular, the 'upstream' negotiation of contractual terms between funders and the institutions employing researchers can undermine the ability for those researchers to subsequently make decisions about data, or participant remuneration, or indeed what happens to consortia outputs after the project is finished, and can inhibit attempts to make project activities and goals responsive to input from ongoing dialogue with various stakeholders. Having explored these challenges, we make some recommendations for alternative consortia governance structures to better support RRI in future.
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Affiliation(s)
- Michael Morrison
- Centre for Health, Law, and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, UK
| | - Miranda Mourby
- Centre for Health, Law, and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, UK
| | - Heather Gowans
- Centre for Health, Law, and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, UK
| | - Sarah Coy
- Centre for Health, Law, and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, UK
| | - Jane Kaye
- Centre for Health, Law, and Emerging Technologies (HeLEX), Faculty of Law, University of Oxford, Oxford, UK
- Melbourne Law School, University of Melbourne, Melbourne, Australia
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15
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Luningham JM, Hendriks AM, Krapohl E, Ip HF, van Beijsterveldt CE, Lundström S, Vuoksimaa E, Korhonen T, Lichtenstein P, Plomin R, Pulkkinen L, Rose RJ, Kaprio J, Bartels M, Boomsma DI, Lubke GH. Harmonizing behavioral outcomes across studies, raters, and countries: application to the genetic analysis of aggression in the ACTION Consortium. J Child Psychol Psychiatry 2020; 61:807-817. [PMID: 31950512 PMCID: PMC7363537 DOI: 10.1111/jcpp.13188] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/25/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Aggression in children has genetic and environmental causes. Studies of aggression can pool existing datasets to include more complex models of social effects. Such analyses require large datasets with harmonized outcome measures. Here, we made use of a reference panel for phenotype data to harmonize multiple aggression measures in school-aged children to jointly analyze data from five large twin cohorts. METHODS Individual level aggression data on 86,559 children (42,468 twin pairs) were available in five European twin cohorts measured by different instruments. A phenotypic reference panel was collected which enabled a model-based phenotype harmonization approach. A bi-factor integration model in the integrative data analysis framework was developed to model aggression across studies while adjusting for rater, age, and sex. Finally, harmonized aggression scores were analyzed to estimate contributions of genes, environment, and social interaction to aggression. The large sample size allowed adequate power to test for sibling interaction effects, with unique dynamics permitted for opposite-sex twins. RESULTS The best-fitting model found a high level of overall heritability of aggression (~60%). Different heritability rates of aggression across sex were marginally significant, with heritability estimates in boys of ~64% and ~58% in girls. Sibling interaction effects were only significant in the opposite-sex twin pairs: the interaction effect of males on their female co-twin differed from the effect of females on their male co-twin. An aggressive female had a positive effect on male co-twin aggression, whereas more aggression in males had a negative influence on a female co-twin. CONCLUSIONS Opposite-sex twins displayed unique social dynamics of aggressive behaviors in a joint analysis of a large, multinational dataset. The integrative data analysis framework, applied in combination with a reference panel, has the potential to elucidate broad, generalizable results in the investigation of common psychological traits in children.
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Affiliation(s)
- Justin M. Luningham
- Department of Psychology, University of Notre Dame, Notre
Dame, IN;,Department of Population Health Sciences, School of Public
Health, Georgia State University, Atlanta, GA, USA
| | - Anne M. Hendriks
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands
| | - Eva Krapohl
- Medical Research Council Social, Genetic, and Developmental
Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, UK
| | - Hill Fung Ip
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands
| | - Catharina E.M. van Beijsterveldt
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands
| | - Sebastian Lundström
- Gillberg Neuropsychiatry Centre, University of Gothenburg,
Gothenburg;,Centre for Ethics, Law and Mental Health (CELAM),
University of Gothenburg, Gothenburg, Sweden
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland, University of
Helsinki, Helsinki, Finland
| | - Tellervo Korhonen
- Institute for Molecular Medicine Finland, University of
Helsinki, Helsinki, Finland
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics,
Karolinska Institutet, Stockholm, Sweden
| | - Robert Plomin
- Medical Research Council Social, Genetic, and Developmental
Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, UK
| | - Lea Pulkkinen
- Department of Psychology, University of Jyvaskyla,
Jyvaskyla, Finland
| | - Richard J. Rose
- Department of Psychological and Brain Sciences, Indiana
University, Bloomington, IN, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of
Helsinki, Helsinki, Finland;,Department of Public Health, University of Helsinki,
Helsinki, Finland
| | - Meike Bartels
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands;,Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Dorret I. Boomsma
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands;,Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Gitta H. Lubke
- Department of Psychology, University of Notre Dame, Notre
Dame, IN
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16
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Bonilla C, Novaes Baccarini L. Genetic Epidemiology in Latin America: Identifying Strong Genetic Proxies for Complex Disease Risk Factors. Genes (Basel) 2020; 11:E507. [PMID: 32375401 PMCID: PMC7288659 DOI: 10.3390/genes11050507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 04/24/2020] [Accepted: 04/28/2020] [Indexed: 11/16/2022] Open
Abstract
Epidemiology seeks to determine the causal effects of exposures on outcomes related to the health and wellbeing of populations. Observational studies, one of the most commonly used designs in epidemiology, can be biased due to confounding and reverse causation, which makes it difficult to establish causal relationships. In recent times, genetically informed methods, like Mendelian randomization (MR), have been developed in an attempt to overcome these disadvantages. MR relies on the association of genetic variants with outcomes of interest, where the genetic variants are proxies or instruments for modifiable exposures. Because genotypes are sorted independently and at random at the time of conception, they are less prone to confounding and reverse causation. Implementation of MR depends on, among other things, a strong association of the genetic variants with the exposure, which has usually been defined via genome-wide association studies (GWAS). Because GWAS have been most often carried out in European populations, the limited identification of strong instruments in other populations poses a major problem for the application of MR in Latin America. We suggest potential solutions that can be realized with the resources at hand and others that will have to wait for increased funding and access to technology.
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Affiliation(s)
- Carolina Bonilla
- Departamento de Medicina Preventiva, Faculdade de Medicina, Universidade de São Paulo, São Paulo 01246, Brazil
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17
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Picache J, May JC, McLean JA. Crowd-Sourced Chemistry: Considerations for Building a Standardized Database to Improve Omic Analyses. ACS OMEGA 2020; 5:980-985. [PMID: 31984253 PMCID: PMC6977078 DOI: 10.1021/acsomega.9b03708] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 12/24/2019] [Indexed: 05/09/2023]
Abstract
Mass spectrometry (MS) is used in multiple omics disciplines to generate large collections of data. This data enables advancements in biomedical research by providing global profiles of a given system. One of the main barriers to generating these profiles is the inability to accurately annotate omics data, especially small molecules. To complement pre-existing large databases that are not quite complete, research groups devote efforts to generating personal libraries to annotate their data. Scientific progress is impeded during the generation of these personal libraries because the data contained within them is often redundant and/or incompatible with other databases. To overcome these redundancies and incompatibilities, we propose that communal, crowd-sourced databases be curated in a standardized fashion. A small number of groups have shown this model is feasible and successful. While the needs of a specific field will dictate the functionality of a communal database, we discuss some features to consider during database development. Special emphasis is made on standardization of terminology, documentation, format, reference materials, and quality assurance practices. These standardization procedures enable a field to have higher confidence in the quality of the data within a given database. We also discuss the three conceptual pillars of database design as well as how crowd-sourcing is practiced. Generating open-source databases requires front-end effort, but the result is a well curated, high quality data set that all can use. Having a resource such as this fosters collaboration and scientific advancement.
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Affiliation(s)
- Jaqueline
A. Picache
- Department of Chemistry,
Center for Innovative Technology, Vanderbilt Institute of Chemical
Biology, Vanderbilt Institute for Integrative Biosystems Research
and Education, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - Jody C. May
- Department of Chemistry,
Center for Innovative Technology, Vanderbilt Institute of Chemical
Biology, Vanderbilt Institute for Integrative Biosystems Research
and Education, Vanderbilt University, Nashville, Tennessee 37235, United States
| | - John A. McLean
- Department of Chemistry,
Center for Innovative Technology, Vanderbilt Institute of Chemical
Biology, Vanderbilt Institute for Integrative Biosystems Research
and Education, Vanderbilt University, Nashville, Tennessee 37235, United States
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18
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Kuntz RE, Antman EM, Califf RM, Ingelfinger JR, Krumholz HM, Ommaya A, Peterson ED, Ross JS, Waldstreicher J, Wang SV, Zarin DA, Whicher DM, Siddiqi SM, Lopez MH. Individual Patient-Level Data Sharing for Continuous Learning: A Strategy for Trial Data Sharing. NAM Perspect 2019; 2019:201906b. [PMID: 34532668 DOI: 10.31478/201906b] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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19
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Middleton A, Milne R, Thorogood A, Kleiderman E, Niemiec E, Prainsack B, Farley L, Bevan P, Steed C, Smith J, Vears D, Atutornu J, Howard HC, Morley KI. Attitudes of publics who are unwilling to donate DNA data for research. Eur J Med Genet 2019; 62:316-323. [PMID: 30476628 PMCID: PMC6582635 DOI: 10.1016/j.ejmg.2018.11.014] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Revised: 11/20/2018] [Accepted: 11/22/2018] [Indexed: 12/17/2022]
Abstract
With the use of genetic technology, researchers have the potential to inform medical diagnoses and treatment in actionable ways. Accurate variant interpretation is a necessary condition for the utility of genetic technology to unfold. This relies on the ability to access large genomic datasets so that comparisons can be made between variants of interest. This can only be successful if DNA and medical data are donated by large numbers of people to 'research', including clinical, non-profit and for-profit research initiatives, in order to be accessed by scientists and clinicians worldwide. The objective of the 'Your DNA, Your Say' global survey is to explore public attitudes, values and opinions towards willingness to donate and concerns regarding the donation of one's personal data for use by others. Using a representative sample of 8967 English-speaking publics from the UK, the USA, Canada and Australia, we explore the characteristics of people who are unwilling (n = 1426) to donate their DNA and medical information, together with an exploration of their reasons. Understanding this perspective is important for making sense of the interaction between science and society. It also helps to focus engagement initiatives on the issues of concern to some publics.
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Affiliation(s)
- Anna Middleton
- Society and Ethics Research, Connecting Science, Wellcome Genome Campus, Cambridge, UK; Faculty of Education, University of Cambridge, Cambridge, UK.
| | - Richard Milne
- Society and Ethics Research, Connecting Science, Wellcome Genome Campus, Cambridge, UK; Institute of Public Health, University of Cambridge, Cambridge, UK
| | - Adrian Thorogood
- Centre of Genomics and Policy, McGill University, Montreal, Quebec, Canada
| | - Erika Kleiderman
- Centre of Genomics and Policy, McGill University, Montreal, Quebec, Canada
| | - Emilia Niemiec
- Centre for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden
| | - Barbara Prainsack
- Department of Political Science, University of Vienna, Austria; Department of Global Health & Social Medicine, King's College London, UK
| | - Lauren Farley
- Society and Ethics Research, Connecting Science, Wellcome Genome Campus, Cambridge, UK
| | - Paul Bevan
- Web Team, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Claire Steed
- Web Team, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - James Smith
- Web Team, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Danya Vears
- Center for Biomedical Ethics and Law, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium; Melbourne Law School, The University of Melbourne, Melbourne, Australia; Biomedical Ethics Research Group, Murdoch Children's Research Institute, Parkville, Australia
| | - Jerome Atutornu
- Society and Ethics Research, Connecting Science, Wellcome Genome Campus, Cambridge, UK; Faculty of Education, University of Cambridge, Cambridge, UK; School of Health Sciences, University of Suffolk, Ipswich, UK
| | - Heidi C Howard
- Society and Ethics Research, Connecting Science, Wellcome Genome Campus, Cambridge, UK; Centre for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden
| | - Katherine I Morley
- Society and Ethics Research, Connecting Science, Wellcome Genome Campus, Cambridge, UK; Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK; Centre for Epidemiology and Biostatistics, Melbourne School of Global and Population Health, The University of Melbourne, Melbourne, Australia
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20
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Teare HJA, de Masi F, Banasik K, Barnett A, Herrgard S, Jablonka B, Postma JWM, McDonald TJ, Forgie I, Chmura PJ, Rydzka EK, Gupta R, Brunak S, Pearson E, Kaye J. The governance structure for data access in the DIRECT consortium: an innovative medicines initiative (IMI) project. LIFE SCIENCES, SOCIETY AND POLICY 2018; 14:20. [PMID: 30182269 PMCID: PMC6123336 DOI: 10.1186/s40504-018-0083-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 07/23/2018] [Indexed: 06/08/2023]
Abstract
Biomedical research projects involving multiple partners from public and private sectors require coherent internal governance mechanisms to engender good working relationships. The DIRECT project is an example of such a venture, funded by the Innovative Medicines Initiative Joint Undertaking (IMI JU). This paper describes the data access policy that was developed within DIRECT to support data access and sharing, via the establishment of a 3-tiered Data Access Committee. The process was intended to allow quick access to data, whilst enabling strong oversight of how data were being accessed and by whom, and any subsequent analyses, to contribute to the overall objectives of the consortium.
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Affiliation(s)
- Harriet J. A. Teare
- HeLEX Centre, University of Oxford, Ewert House, Banbury Road, Oxford, OX2 7DD UK
- Melbourne Law School, University of Melbourne, 185 Pelham Street, Carlton, VIC 3053 Australia
| | - Federico de Masi
- Center for Biological Sequence Analysis, Department of Bio and Health Informatics, Technical University of Denmark, Building 208, DK-2800 Lyngby, Denmark
| | - Karina Banasik
- Translational Disease Systems Biology, NNF Center for Protein Research, University of Copenhagen, Faculty of Health and Medical Sciences, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark
| | - Anna Barnett
- Division of Molecular & Clinical Medicine, School of Medicine, University of Dundee, Ninewells Hospital & Medical School, Dundee, UK
| | - Sanna Herrgard
- Center for Biological Sequence Analysis, Department of Bio and Health Informatics, Technical University of Denmark, Building 208, DK-2800 Lyngby, Denmark
| | - Bernd Jablonka
- Sanofi-Aventis Deutschland GmbH, Industriepark Höchst, 65926 Frankfurt, Germany
| | - Jacqueline W. M. Postma
- Clinical Research Centre, Lund University Diabetes Centre, Box 50332, SE-202 13 Malmö, Sweden
| | - Timothy J. McDonald
- Blood Sciences, Template A2, Royal Devon and Exeter Hospital, Barrack Road, Exeter, EX2 5DW UK
| | - Ian Forgie
- Division of Molecular & Clinical Medicine, School of Medicine, University of Dundee, Ninewells Hospital & Medical School, Dundee, UK
| | - Piotr J. Chmura
- Center for Biological Sequence Analysis, Department of Bio and Health Informatics, Technical University of Denmark, Building 208, DK-2800 Lyngby, Denmark
| | - Emil K. Rydzka
- Center for Biological Sequence Analysis, Department of Bio and Health Informatics, Technical University of Denmark, Building 208, DK-2800 Lyngby, Denmark
| | - Ramneek Gupta
- Center for Biological Sequence Analysis, Department of Bio and Health Informatics, Technical University of Denmark, Building 208, DK-2800 Lyngby, Denmark
| | - Soren Brunak
- Center for Biological Sequence Analysis, Department of Bio and Health Informatics, Technical University of Denmark, Building 208, DK-2800 Lyngby, Denmark
- Translational Disease Systems Biology, NNF Center for Protein Research, University of Copenhagen, Faculty of Health and Medical Sciences, Blegdamsvej 3B, DK-2200 Copenhagen, Denmark
| | - Ewan Pearson
- Division of Molecular & Clinical Medicine, School of Medicine, University of Dundee, Ninewells Hospital & Medical School, Dundee, UK
| | - Jane Kaye
- HeLEX Centre, University of Oxford, Ewert House, Banbury Road, Oxford, OX2 7DD UK
- Melbourne Law School, University of Melbourne, 185 Pelham Street, Carlton, VIC 3053 Australia
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21
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Bastião Silva L, Trifan A, Luís Oliveira J. MONTRA: An agile architecture for data publishing and discovery. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2018; 160:33-42. [PMID: 29728244 DOI: 10.1016/j.cmpb.2018.03.024] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2017] [Revised: 02/26/2018] [Accepted: 03/27/2018] [Indexed: 06/08/2023]
Abstract
BACKGROUND AND OBJECTIVE Data catalogues are a common form of capturing and presenting information about a specific kind of entity (e.g. products, services, professionals, datasets, etc.). However, the construction of a web-based catalogue for a particular scenario normally implies the development of a specific and dedicated solution. In this paper, we present MONTRA, a rapid-application development framework designed to facilitate the integration and discovery of heterogeneous objects, which may be characterized by distinct data structures. METHODS MONTRA was developed following a plugin-based architecture to allow dynamic composition of services over represented datasets. The core of MONTRA's functionalities resides in a flexible data skeleton used to characterize data entities, and from which a fully-fledged web data catalogue is automatically generated, ensuring access control and data privacy. RESULTS MONTRA is being successfully used by several European projects to collect and manage biomedical databases. In this paper, we describe three of these applications scenarios. CONCLUSIONS This work was motivated by the plethora of geographically scattered biomedical repositories, and by the role they can play altogether for the understanding of diseases and of the real-world effectiveness of treatments. Using metadata to expose datasets' characteristics, MONTRA greatly simplifies the task of building data catalogues. The source code is publicly available at https://github.com/bioinformatics-ua/montra.
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22
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Takashima K, Maru Y, Mori S, Mano H, Noda T, Muto K. Ethical concerns on sharing genomic data including patients' family members. BMC Med Ethics 2018; 19:61. [PMID: 29914459 PMCID: PMC6006763 DOI: 10.1186/s12910-018-0310-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Accepted: 06/07/2018] [Indexed: 12/28/2022] Open
Abstract
Background Platforms for sharing genomic and phenotype data have been developed to promote genomic research, while maximizing the utility of existing datasets and minimizing the burden on participants. The value of genomic analysis of trios or family members has increased, especially in rare diseases and cancers. This article aims to argue the necessity of protection when sharing data from both patients and family members. Main text Sharing patients’ and family members’ data collectively raises an ethical tension between the value of datasets and the rights of participants, and increases the risk of re-identification. However, current data-sharing policies have no specific safeguards or provisions for familial data sharing. A quantitative survey conducted on 10,881 general adults in Japan indicated that they expected stronger protection mechanisms when their family members’ clinical and/or genomic data were shared together, as compared to when only their data were shared. A framework that respects decision-making and the right of withdrawal of participants, including family members, along with ensuring usefulness and security of data is needed. To enable this, we propose recommendations on ancillary safeguards for familial data sharing according to the stakeholders, namely, initial researchers, genomic researchers, data submitters, database operators, institutional review boards, and the public and participants. Conclusions Families have played significant roles in genetic research, and its value is re-illuminated in the era of genomic medicine. It is important to make progress in data sharing while simultaneously protecting the privacy and interests of patients and families, and return its benefits to them.
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Affiliation(s)
- Kyoko Takashima
- Department of Public Policy, The Institute of Medical Science, The University of Tokyo, Shirokanedai 4-6-1, Minato-ku, Tokyo, 108-8639, Japan. .,Medical Genomics Center, National Center for Global Health and Medicine, 1-21-1 Toyama, Shinjuku-ku, Tokyo, 162-8655, Japan.
| | - Yuichi Maru
- Department of Regional Policy, Faculty of Regional Sciences, Tottori University, 4-101 Koyama-cho Minami, Tottori, 680-8551, Japan
| | - Seiichi Mori
- Cancer Precision Medicine Center, Japanese Foundation for Cancer Research, 3-8-31, Ariake, Koto-ku, Tokyo, 135-8550, Japan
| | - Hiroyuki Mano
- National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Tetsuo Noda
- Cancer Institute, Japanese Foundation for Cancer Research, 3-8-31, Ariake, Koto-ku, Tokyo, 135-8550, Japan
| | - Kaori Muto
- Department of Public Policy, The Institute of Medical Science, The University of Tokyo, Shirokanedai 4-6-1, Minato-ku, Tokyo, 108-8639, Japan
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23
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Middleton A. Society and personal genome data. Hum Mol Genet 2018; 27:R8-R13. [PMID: 29522190 PMCID: PMC5946868 DOI: 10.1093/hmg/ddy084] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Revised: 03/05/2018] [Accepted: 03/06/2018] [Indexed: 12/18/2022] Open
Abstract
Genomic data offer a goldmine of information for understanding the contribution of genetic variation makes to health and disease. The potential of genomic medicine, to predict, diagnose, manage and treat genetic disease, is underpinned by accurate variant interpretation. This in itself hinges on the ability to access large and varied genomic databases. There is now recognition that international collaboration between research and healthcare systems are paramount to delivering the scale of genomic data required. No single research group, institute or country will liberate our understanding, it is only through global cooperation, together with super computing power, will we truly make sense of how genotype and phenotype correlate. Whilst it is logistically possible to create computing systems that talk to each other and aggregate datasets ready to reveal novel correlations, the bottom line is that this will only happen if people (whether they be scientists, clinicians, patients, research participants, policy makers, politicians, law makers) support the principle that we should be donating, accessing and sharing our DNA data in this way. And in order to make the most sense of genomics, given the geographical and ancestral variation between us, such people are likely to be the majority of society. Within this review, a perspective is proffered on the human story that underpins genomic 'big data' access and how we are at a tipping point as a society-we need to decide collectively, are we in? and if so, what needs to be in place to protect us? or are we out?
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Affiliation(s)
- Anna Middleton
- Society and Ethics Research Group, Connecting Science, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Faculty of Education, University of Cambridge, UK
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24
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Borry P, Bentzen HB, Budin-Ljøsne I, Cornel MC, Howard HC, Feeney O, Jackson L, Mascalzoni D, Mendes Á, Peterlin B, Riso B, Shabani M, Skirton H, Sterckx S, Vears D, Wjst M, Felzmann H. The challenges of the expanded availability of genomic information: an agenda-setting paper. J Community Genet 2018; 9:103-116. [PMID: 28952070 PMCID: PMC5849701 DOI: 10.1007/s12687-017-0331-7] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Accepted: 09/03/2017] [Indexed: 01/20/2023] Open
Abstract
Rapid advances in microarray and sequencing technologies are making genotyping and genome sequencing more affordable and readily available. There is an expectation that genomic sequencing technologies improve personalized diagnosis and personalized drug therapy. Concurrently, provision of direct-to-consumer genetic testing by commercial providers has enabled individuals' direct access to their genomic data. The expanded availability of genomic data is perceived as influencing the relationship between the various parties involved including healthcare professionals, researchers, patients, individuals, families, industry, and government. This results in a need to revisit their roles and responsibilities. In a 1-day agenda-setting meeting organized by the COST Action IS1303 "Citizen's Health through public-private Initiatives: Public health, Market and Ethical perspectives," participants discussed the main challenges associated with the expanded availability of genomic information, with a specific focus on public-private partnerships, and provided an outline from which to discuss in detail the identified challenges. This paper summarizes the points raised at this meeting in five main parts and highlights the key cross-cutting themes. In light of the increasing availability of genomic information, it is expected that this paper will provide timely direction for future research and policy making in this area.
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Affiliation(s)
- Pascal Borry
- Centre for Biomedical Ethics and Law, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium.
- Leuven Institute for Human Genomics and Society, 3000, Leuven, Belgium.
- Faculty of Medicine, University of Leuven, Leuven, Belgium.
| | - Heidi Beate Bentzen
- Centre for Medical Ethics, Faculty of Medicine, University of Oslo, Oslo, Norway
- Norwegian Research Center for Computers and Law, Faculty of Law, University of Oslo, Oslo, Norway
- Norwegian Cancer Genomics Consortium, Oslo, Norway
| | - Isabelle Budin-Ljøsne
- Norwegian Cancer Genomics Consortium, Oslo, Norway
- Centre for Medical Ethics, Institute of Health and Society, University of Oslo, P.O Box 1130, Blindern, 0318, Oslo, Norway
- Cohort Studies, Norwegian Institute of Public Health, Oslo, Norway
| | - Martina C Cornel
- Department of Clinical Genetics, Section of Community Genetics, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, the Netherlands
| | - Heidi Carmen Howard
- Centre for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden
| | - Oliver Feeney
- Centre of Bioethical Research and Analysis (COBRA), National University of Ireland (Galway), Galway, Republic of Ireland
| | - Leigh Jackson
- RILD Building, Royal Devon and Exeter Hospital, University of Exeter Medical School, Exeter, UK
| | - Deborah Mascalzoni
- Centre for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden
- EURAC Research, Bolzano, Italy
| | - Álvaro Mendes
- i3S, Instituto de Investigação e Inovação em Saúde, IBMC-UnIGENe and Centre for Predictive and Preventive Genetics, Universidade do Porto, Porto, Portugal
| | - Borut Peterlin
- Clinical Institute of Medical Genetics, University Medical Center Ljubljana, Šlajmerjeva 4, 1000, Ljubljana, Slovenia
| | - Brigida Riso
- Instituto Universitário de Lisboa (ISCTE-IUL), CIES-IUL, Lisbon, Portugal
| | - Mahsa Shabani
- Centre for Biomedical Ethics and Law, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
- Leuven Institute for Human Genomics and Society, 3000, Leuven, Belgium
| | - Heather Skirton
- Faculty of Health and Human Sciences, University of Plymouth, Drake Circus, Plymouth, PL4 8AA, UK
| | - Sigrid Sterckx
- Bioethics Institute Ghent, Ghent University, Blandijnberg 2, 9000, Ghent, Belgium
| | - Danya Vears
- Centre for Biomedical Ethics and Law, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
- Leuven Institute for Human Genomics and Society, 3000, Leuven, Belgium
| | - Matthias Wjst
- Helmholtz Center Munich, National Research Centre for Environmental Health, Institute of Lung Biology and Disease, Munich, Germany
- Institute of Medical Statistics, Epidemiology and Medical Informatics, Technical University Munich, Munich, Germany
| | - Heike Felzmann
- Centre of Bioethical Research and Analysis (COBRA), National University of Ireland (Galway), Galway, Republic of Ireland
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25
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Dashevsky BZ, Bercu ZL, Bhosale PR, Burton KR, Chatterjee AR, Frigini LAR, Heacock L, Herskovits EH, Lee JT, Subhas N, Wasnik AP, Gyftopoulos S. Multicenter Research Studies in Radiology. Acad Radiol 2018; 25:18-25. [PMID: 28927579 DOI: 10.1016/j.acra.2017.05.019] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2017] [Revised: 05/02/2017] [Accepted: 05/03/2017] [Indexed: 12/27/2022]
Abstract
RATIONALE AND OBJECTIVES Here we review the current state of multicenter radiology research (MRR), and utilize a survey of experienced researchers to identify common advantages, barriers, and resources to guide future investigators. MATERIALS AND METHODS The Association of University Radiologists established a Radiology Research Alliance task force, Multi-center Research Studies in Radiology, composed of 12 society members to review MRR. A REDCap survey was designed to gain more insight from experienced researchers. Recipients were authors identified from a PubMed database search, utilizing search terms "multicenter" or "multisite" and "radiology." The survey included investigator background information, reasons why, barriers to, and resources that investigators found helpful in conducting or participating in MRR. RESULTS The survey was completed by 23 of 80 recipients (29%), the majority (76%) of whom served as a primary investigator on at least one MRR project. Respondents reported meeting collaborators at national or international (74%) and society (39%) meetings. The most common perceived advantages of MRR were increased sample size (100%) and improved generalizability (91%). External funding was considered the most significant barrier to MRR, reported by 26% of respondents. Institutional funding, setting up a central picture archiving and communication system, and setting up a central database were considered a significant barrier by 30%, 22%, and 22% of respondents, respectively. Resources for overcoming barriers included motivated staff (74%), strong leadership (70%), regular conference calls (57%), and at least one face-to-face meeting (57%). CONCLUSIONS Barriers to MRR include funding and establishing a central database and a picture archiving and communication system. Upon embarking on an MRR project, forming a motivated team who meets and speaks regularly is essential.
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Affiliation(s)
- Brittany Z Dashevsky
- Department of Radiology, University of Chicago Medical Center, MC2026, 5841 South Maryland Ave., Chicago, IL 60637.
| | - Zachary L Bercu
- School of Medicine, Department of Radiology, EmoryUniversity, Atlanta, Georgia
| | - Priya R Bhosale
- MD Anderson Cancer Center, Department of Radiology, University of Texas, Houston, Texas
| | | | - Arindam R Chatterjee
- Department of Radiology, Medical University of South Carolina, Charleston, South Carolina
| | | | - Laura Heacock
- Department of Radiology, NYU Langone Medical Center, New York, New York
| | - Edward H Herskovits
- School of Medicine, Department of Radiology, University of Maryland, Baltimore, Maryland
| | - James T Lee
- College of Medicine, Department of Radiology, University of Kentucky, Lexington, Kentucky
| | - Naveen Subhas
- Department of Radiology, Cleveland Clinic, Cleveland, Ohio
| | - Ashish P Wasnik
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
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26
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Piciocchi C, Ducato R, Martinelli L, Perra S, Tomasi M, Zuddas C, Mascalzoni D. Legal issues in governing genetic biobanks: the Italian framework as a case study for the implications for citizen's health through public-private initiatives. J Community Genet 2017; 9:177-190. [PMID: 28921376 PMCID: PMC5849700 DOI: 10.1007/s12687-017-0328-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 09/03/2017] [Indexed: 11/10/2022] Open
Abstract
This paper outlines some of the challenges faced by regulation of genetic biobanking, using case studies coming from the Italian legal system. The governance of genetic resources in the context of genetic biobanks in Italy is discussed, as an example of the stratification of different inputs and rules: EU law, national law, orders made by authorities and soft law, which need to be integrated with ethical principles, technological strategies and solutions. After providing an overview of the Italian legal regulation of genetic data processing, it considers the fate of genetic material and IP rights in the event of a biobank’s insolvency. To this end, it analyses two case studies: a controversial bankruptcy case which occurred in Sardinia, one of the first examples of private and public partnership biobanks. Another case study considered is the Chris project: an example of partnership between a research institute in Bolzano and the South Tyrolean Health System. Both cases seem to point in the same direction, suggesting expediency of promoting and improving public-private partnerships to manage biological tissues and biotrust to conciliate patent law and public interest.
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Affiliation(s)
| | - Rossana Ducato
- Faculty of Law, University of Trento, Trento, Italy.,Institut pour la recherche interdisciplinaire en sciences juridiques, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
| | | | - Silvia Perra
- Faculty of Economics, Law and Political Sciences, Department of Law, University of Cagliari, Cagliari, Italy
| | - Marta Tomasi
- Faculty of Economics, Free University of Bozen-Bolzano, Bolzano, Italy
| | - Carla Zuddas
- Faculty of Economics, Law and Political Sciences, Department of Law, University of Cagliari, Cagliari, Italy
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27
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Abstract
The rising demand to use genetic data for research goes hand in hand with an increased awareness of privacy issues related to its use. Using human genetic data in a legally compliant way requires an examination of the legal basis as well as an assessment of potential disclosure risks. Focusing on the relevant legal framework in the European Union, we discuss open questions and uncertainties around the handling of genetic data in research, which can result in the introduction of unnecessary hurdles for data sharing. First, we discuss defining features and relative disclosure risks of some DNA-related biomarkers, distinguishing between the risk for disclosure of (1) the identity of an individual, (2) information about an individual's health and behavior, including previously unknown phenotypes, and (3) information about an individual's blood relatives. Second, we discuss the European legal framework applicable to the use of DNA-related biomarkers in research, the implications of including both inherited and acquired traits in the legal definition, as well as the issue of “genetic exceptionalism”—the notion that genetic information has inherent characteristics that require different considerations than other health and medical information. Finally, by mapping the legal to specific technical definitions, we draw some initial conclusions concerning how sensitive different types of “genetic data” may actually be. We argue that whole genome sequences may justifiably be considered “exceptional” and require special protection, whereas other genetic data that do not fulfill the same criteria should be treated in a similar manner to other clinical data. This kind of differentiation should be reflected by the law and/or other governance frameworks as well as agreed Codes of Conduct when using the term “genetic data.”
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Affiliation(s)
- Murat Sariyar
- 1 Institute of Medical Informatics, Bern University of Applied Sciences , Bienne, Switzerland
| | | | - Irene Schlünder
- 3 TMF-Technologie- und Methodenplattform e.V. , Berlin, Germany .,4 BBMRI-ERIC , Graz, Austria
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28
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Brennan P, Perola M, van Ommen GJ, Riboli E. Chronic disease research in Europe and the need for integrated population cohorts. Eur J Epidemiol 2017; 32:741-749. [PMID: 28986739 PMCID: PMC5662668 DOI: 10.1007/s10654-017-0315-2] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2017] [Accepted: 09/11/2017] [Indexed: 12/14/2022]
Affiliation(s)
- Paul Brennan
- Genetics Section, International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69372, Lyon Cedex 08, France.
| | - Markus Perola
- National Institute for Health and Welfare, Helsinki, Finland
| | - Gert-Jan van Ommen
- Department of Human Genetics, Leiden University Medical Center (LUMC), Leiden, The Netherlands
- Biobanking and Biomolecular Research Resources Infrastructure (BBMRI-ERIC), Graz, Austria
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29
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Abstract
PURPOSE OF REVIEW Increasingly, there is a need for examining exposure disease associations in large, diverse datasets to understand the complex determinants of pediatric disease and disability. Recognizing that children's health research consortia will be important sources of big data, it is crucial for the pediatric research community to be knowledgeable about the challenges and opportunities that they will face. The present review will provide examples of existing children's health consortia, highlight recent pooled analyses conducted by children's health research consortia, address common challenges of pooled analyses, and provide recommendations to advance collective research efforts in pediatric research. RECENT FINDINGS Formal consortia and other collective-science initiatives are increasingly being created to share individual data from a set of relevant epidemiological studies to address a common research topic under the concept that the joint effort of many individual groups can accomplish far more than working alone. There are practical challenges to the participation of investigators within consortia that need to be addressed in order for them to work. SUMMARY Researchers who access consortia with data centers will be able to go far beyond their initial hypotheses and potentially accomplish research that was previously thought infeasible or too costly.
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30
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Gainotti S, Turner C, Woods S, Kole A, McCormack P, Lochmüller H, Riess O, Straub V, Posada M, Taruscio D, Mascalzoni D. Improving the informed consent process in international collaborative rare disease research: effective consent for effective research. Eur J Hum Genet 2016; 24:1248-54. [PMID: 26860059 PMCID: PMC4989211 DOI: 10.1038/ejhg.2016.2] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2015] [Revised: 11/23/2015] [Accepted: 12/08/2015] [Indexed: 01/03/2023] Open
Abstract
The increased international sharing of data in research consortia and the introduction of new technologies for sequencing challenge the informed consent (IC) process, adding complexities that require coordination between research centres worldwide. Rare disease consortia present special challenges since available data and samples may be very limited. Thus, it is especially relevant to ensure the best use of available resources but at the same time protect patients' right to integrity. To achieve this aim, there is an ethical duty to plan in advance the best possible consent procedure in order to address possible ethical and legal hurdles that could hamper research in the future. Therefore, it is especially important to identify key core elements (CEs) to be addressed in the IC documents for international collaborative research in two different situations: (1) new research collections (biobanks and registries) for which information documents can be created according to current guidelines and (2) established collections obtained without IC or with a previous consent that does not cover all CEs. We propose here a strategy to deal with consent in these situations. The principles have been applied and are in current practice within the RD-Connect consortia - a global research infrastructure funded by the European Commission Seventh Framework program but forward looking in terms of issues addressed. However, the principles established, the lessons learned and the implications for future research are of direct relevance to all internationally collaborative rare-disease projects.
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Affiliation(s)
- Sabina Gainotti
- National Centre for Rare Diseases, Istituto Superiore di Sanità, Rome, Italy
| | - Cathy Turner
- Institute of Genetic Medicine, Newcastle University International Centre for Life, Newcastle upon Tyne, UK
| | - Simon Woods
- PEALS (Policy, Ethics and Life Sciences) Research Centre, Newcastle University, Newcastle upon Tyne, UK
| | - Anna Kole
- EURORDIS, Rare Disease Europe, Paris, France
| | - Pauline McCormack
- PEALS (Policy, Ethics and Life Sciences) Research Centre, Newcastle University, Newcastle upon Tyne, UK
| | - Hanns Lochmüller
- Institute of Genetic Medicine, Newcastle University International Centre for Life, Newcastle upon Tyne, UK
| | - Olaf Riess
- Institute of Human Genetics and Applied Genomics, University of Tubingen, Tubingen, Germany
| | - Volker Straub
- Institute of Genetic Medicine, Newcastle University International Centre for Life, Newcastle upon Tyne, UK
| | - Manuel Posada
- Institute of Rare Diseases Research, SpainRDR & CIBERER, ISCIII, Madrid, Spain
| | - Domenica Taruscio
- National Centre for Rare Diseases, Istituto Superiore di Sanità, Rome, Italy
| | - Deborah Mascalzoni
- Center for Research Ethics and Bioethics, Uppsala University, Uppsala, Sweden
- Center for Biomedicine, EURAC Research, Bolzano, Italy
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31
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Abstract
This paper makes the case for implementing an internal governance framework for sharing materials and data in stem cell research consortia. A governance framework can facilitate a transparent and accountable system while building trust among partner institutions. However, avoiding excessive bureaucracy is essential. The development and implementation of a governance framework for materials and data access in the Stem cells for Biological Assays of Novel drugs and prediCtive toxiCology (StemBANCC) consortium is presented as a practical example. The StemBANCC project is a multi-partner European research consortium, which aims to build a resource of 1,500 well characterised induced pluripotent stem cell (iPSC) lines for in vitro disease modelling and toxicology studies. The project governance framework was developed in two stages. A small working group identified key components of a framework and translated the project legal agreements into a draft policy document. The second phase allowed input from all consortium partners to shape the iterative development of a final policy document that could be agreed by all parties. Careful time management strategies were needed to manage the duration of this component. This part of the process also served as an exploratory space where different options could be proposed, potential gaps in planning identified, and project co-ordination activities specified.
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32
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Hate K, Meherally S, Shah More N, Jayaraman A, Bull S, Parker M, Osrin D. Sweat, Skepticism, and Uncharted Territory: A Qualitative Study of Opinions on Data Sharing Among Public Health Researchers and Research Participants in Mumbai, India. J Empir Res Hum Res Ethics 2016; 10:239-50. [PMID: 26297746 PMCID: PMC4547203 DOI: 10.1177/1556264615592383] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Efforts to internalize data sharing in research practice have been driven largely by developing international norms that have not incorporated opinions from researchers in low- and middle-income countries. We sought to identify the issues around ethical data sharing in the context of research involving women and children in urban India. We interviewed researchers, managers, and research participants associated with a Mumbai non-governmental organization, as well as researchers from other organizations and members of ethics committees. We conducted 22 individual semi-structured interviews and involved 44 research participants in focus group discussions. We used framework analysis to examine ideas about data and data sharing in general; its potential benefits or harms, barriers, obligations, and governance; and the requirements for consent. Both researchers and participants were generally in favor of data sharing, although limited experience amplified their reservations. We identified three themes: concerns that the work of data producers may not receive appropriate acknowledgment, skepticism about the process of sharing, and the fact that the terrain of data sharing was essentially uncharted and confusing. To increase data sharing in India, we need to provide guidelines, protocols, and examples of good practice in terms of consent, data preparation, screening of applications, and what individuals and organizations can expect in terms of validation, acknowledgment, and authorship.
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Affiliation(s)
- Ketaki Hate
- Society for Nutrition, Education and Health Action, Mumbai, India
| | - Sanna Meherally
- Society for Nutrition, Education and Health Action, Mumbai, India
| | - Neena Shah More
- Society for Nutrition, Education and Health Action, Mumbai, India
| | - Anuja Jayaraman
- Society for Nutrition, Education and Health Action, Mumbai, India
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33
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Tassé AM, Kirby E, Fortier I. Developing an Ethical and Legal Interoperability Assessment Process for Retrospective Studies. Biopreserv Biobank 2016; 14:249-55. [PMID: 27115199 DOI: 10.1089/bio.2015.0122] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The past decade has witnessed the creation of major international research consortia, aiming to facilitate the sharing of data from different studies to maximize health benefits. However, combining heterogeneous data across existing studies requires addressing issues related to both data harmonization and ethical and legal interoperability. This article proposes a rigorous interoperability assessment process to assess whether different data sets are sufficiently ethically and legally interoperable to allow for a given proposed research use. The methodology used to develop this process is based on a comprehensive analysis of the international ethical and legal framework governing the use of retrospective data in research, and includes the following steps: (I) finding existing processes; (II) comparing processes to identify similarities and differences and determining the limits of the "consistent whole"; (III) establishing common principles and procedures; and, (IV) changing or removing processes that do not contribute to the consistent whole. Each of these four steps were examined using step-specific methodologies, including (a) literature and policy reviews; (b) consultations with international ethical, legal and social implications (ELSI) experts; and (c) a case study piloting the proposed framework in an actual international research consortium. This assessment process takes into account key legal and ethical components such as consent, recontact, and waiver of consent. As a result, this analysis allows the development of a comprehensive filter used to verify the legal and ethical restrictions pertaining to a data set. This in turns helps in determining whether the given data set can to be used for a proposed research project, or is ethically and legally interoperable for use in research collaborations. By integrating this filter to the regular data access processes used by cohorts, not only will researchers be able to create virtual "mega-cohorts" of research participants, but it will also ensure that these cohorts respect basic legal and ethical precepts.
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Affiliation(s)
- Anne-Marie Tassé
- 1 Public Population Project in Genomics and Society, McGill University and Genome Quebec Innovation Centre , Montreal, Quebec, Canada
| | - Emily Kirby
- 1 Public Population Project in Genomics and Society, McGill University and Genome Quebec Innovation Centre , Montreal, Quebec, Canada
| | - Isabel Fortier
- 2 Maelstrom Research, Research Institute of the McGill University Health Centre , Montreal, Quebec, Canada
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34
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Improving the informed consent process in international collaborative rare disease research: effective consent for effective research. Eur J Hum Genet 2016. [PMID: 26860059 DOI: 10.1038/ejhg.2016.2;] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
The increased international sharing of data in research consortia and the introduction of new technologies for sequencing challenge the informed consent (IC) process, adding complexities that require coordination between research centres worldwide. Rare disease consortia present special challenges since available data and samples may be very limited. Thus, it is especially relevant to ensure the best use of available resources but at the same time protect patients' right to integrity. To achieve this aim, there is an ethical duty to plan in advance the best possible consent procedure in order to address possible ethical and legal hurdles that could hamper research in the future. Therefore, it is especially important to identify key core elements (CEs) to be addressed in the IC documents for international collaborative research in two different situations: (1) new research collections (biobanks and registries) for which information documents can be created according to current guidelines and (2) established collections obtained without IC or with a previous consent that does not cover all CEs. We propose here a strategy to deal with consent in these situations. The principles have been applied and are in current practice within the RD-Connect consortia - a global research infrastructure funded by the European Commission Seventh Framework program but forward looking in terms of issues addressed. However, the principles established, the lessons learned and the implications for future research are of direct relevance to all internationally collaborative rare-disease projects.
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35
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Spjuth O, Krestyaninova M, Hastings J, Shen HY, Heikkinen J, Waldenberger M, Langhammer A, Ladenvall C, Esko T, Persson MÅ, Heggland J, Dietrich J, Ose S, Gieger C, Ried JS, Peters A, Fortier I, de Geus EJC, Klovins J, Zaharenko L, Willemsen G, Hottenga JJ, Litton JE, Karvanen J, Boomsma DI, Groop L, Rung J, Palmgren J, Pedersen NL, McCarthy MI, van Duijn CM, Hveem K, Metspalu A, Ripatti S, Prokopenko I, Harris JR. Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research. Eur J Hum Genet 2015; 24:521-8. [PMID: 26306643 PMCID: PMC4929882 DOI: 10.1038/ejhg.2015.165] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Revised: 05/18/2015] [Accepted: 06/18/2015] [Indexed: 12/04/2022] Open
Abstract
A wealth of biospecimen samples are stored in modern globally distributed biobanks.
Biomedical researchers worldwide need to be able to combine the available resources
to improve the power of large-scale studies. A prerequisite for this effort is to be
able to search and access phenotypic, clinical and other information about samples
that are currently stored at biobanks in an integrated manner. However, privacy
issues together with heterogeneous information systems and the lack of agreed-upon
vocabularies have made specimen searching across multiple biobanks extremely
challenging. We describe three case studies where we have linked samples and sample
descriptions in order to facilitate global searching of available samples for
research. The use cases include the ENGAGE (European Network for Genetic and Genomic
Epidemiology) consortium comprising at least 39 cohorts, the SUMMIT (surrogate
markers for micro- and macro-vascular hard endpoints for innovative diabetes tools)
consortium and a pilot for data integration between a Swedish clinical health
registry and a biobank. We used the Sample avAILability (SAIL) method for data
linking: first, created harmonised variables and then annotated and made searchable
information on the number of specimens available in individual biobanks for various
phenotypic categories. By operating on this categorised availability data we sidestep
many obstacles related to privacy that arise when handling real values and show that
harmonised and annotated records about data availability across disparate biomedical
archives provide a key methodological advance in pre-analysis exchange of information
between biobanks, that is, during the project planning phase.
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Affiliation(s)
- Ola Spjuth
- Department of Medical Epidemiology and Biostatistics, Swedish e-Science Research Centre, Karolinska Institutet, Stockholm, Sweden.,Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Maria Krestyaninova
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, UK.,Uniquer Sarl, rue de la Mercerie, Lausanne, Switzerland
| | - Janna Hastings
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, UK
| | - Huei-Yi Shen
- Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Biomedicum Helsinki 2U, Helsinki, Finland
| | - Jani Heikkinen
- Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Biomedicum Helsinki 2U, Helsinki, Finland
| | - Melanie Waldenberger
- Institute of Epidemiology II, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany.,Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany
| | - Arnulf Langhammer
- Department of Public Health and General Practice, HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway
| | - Claes Ladenvall
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Lund, Sweden.,Lund University Diabetes Centre, CRC at Skåne University Hospital, Malmö, Sweden
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Mats-Åke Persson
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Lund, Sweden.,Lund University Diabetes Centre, CRC at Skåne University Hospital, Malmö, Sweden
| | - Jon Heggland
- Department of Public Health and General Practice, HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway
| | - Joern Dietrich
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, UK
| | - Sandra Ose
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, UK
| | - Christian Gieger
- Institute of Epidemiology II, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany.,Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany
| | - Janina S Ried
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany.,Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany
| | - Isabel Fortier
- McGill University Health Centre, Montreal, Quebec, Canada
| | - Eco J C de Geus
- Department of Biological Psychology, FGB, VU University, Amsterdam, The Netherlands
| | - Janis Klovins
- Latvian Genome Data Base (LGDB), Latvian Biomedical Research and Study Centre, Ratsupites 1 k-1, Riga, Latvia
| | - Linda Zaharenko
- Latvian Genome Data Base (LGDB), Latvian Biomedical Research and Study Centre, Ratsupites 1 k-1, Riga, Latvia
| | - Gonneke Willemsen
- Department of Biological Psychology, FGB, VU University, Amsterdam, The Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, FGB, VU University, Amsterdam, The Netherlands
| | - Jan-Eric Litton
- Department of Medical Epidemiology and Biostatistics, Swedish e-Science Research Centre, Karolinska Institutet, Stockholm, Sweden.,BBMRI-ERIC, Neue Stiftingtalstrasse 2/B/6, Graz, Austria
| | - Juha Karvanen
- National Institute for Health and Welfare, Helsinki, Finland.,University of Jyvaskyla, Jyväskylä, Finland
| | - Dorret I Boomsma
- Department of Biological Psychology, FGB, VU University, Amsterdam, The Netherlands
| | - Leif Groop
- Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Biomedicum Helsinki 2U, Helsinki, Finland.,Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Lund, Sweden
| | - Johan Rung
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, UK.,Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Juni Palmgren
- Department of Medical Epidemiology and Biostatistics, Swedish e-Science Research Centre, Karolinska Institutet, Stockholm, Sweden.,Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Biomedicum Helsinki 2U, Helsinki, Finland
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Swedish e-Science Research Centre, Karolinska Institutet, Stockholm, Sweden
| | - Mark I McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, UK.,Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.,Oxford NIHR Biomedical Research Centre, Churchill Hospital, Headington, Oxford, UK
| | | | - Kristian Hveem
- Department of Public Health and General Practice, HUNT Research Centre, Norwegian University of Science and Technology, Levanger, Norway
| | | | - Samuli Ripatti
- Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Biomedicum Helsinki 2U, Helsinki, Finland.,Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
| | - Inga Prokopenko
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, UK.,Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.,Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, UK
| | - Jennifer R Harris
- Division of Epidemiology, Department of Genes and Environment, The Norwegian Institute of Public Health, Oslo, Norway
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36
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Sariyar M, Schluender I, Smee C, Suhr S. Sharing and Reuse of Sensitive Data and Samples: Supporting Researchers in Identifying Ethical and Legal Requirements. Biopreserv Biobank 2015; 13:263-70. [PMID: 26186169 PMCID: PMC4559154 DOI: 10.1089/bio.2015.0014] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Availability of and access to data and biosamples are essential in medical and translational research, where their reuse and repurposing by the wider research community can maximize their value and accelerate discovery. However, sharing human-related data or samples is complicated by ethical, legal, and social sensitivities. The specific ethical and legal requirements linked to sensitive data are often unfamiliar to life science researchers who, faced with vast amounts of complex, fragmented, and sometimes even contradictory information, may not feel competent to navigate through it. In this case, the impulse may be not to share the data in order to safeguard against unintentional misuse. Consequently, helping data providers to identify relevant ethical and legal requirements and how they might address them is an essential and frequently neglected step in removing possible hurdles to data and sample sharing in the life sciences. Here, we describe the complex regulatory context and discuss relevant online tools-one which the authors co-developed-targeted at assisting providers of sensitive data or biosamples with ethical and legal questions. The main results are (1) that the different approaches of the tools assume different user needs and prior knowledge of ethical and legal requirements, affecting how a service is designed and its usefulness, (2) that there is much potential for collaboration between tool providers, and (3) that enriched annotations of services (e.g., update status, completeness of information, and disclaimers) would increase their value and facilitate quick assessment by users. Further, there is still work to do with respect to providing researchers using sensitive data or samples with truly 'useful' tools that do not require pre-existing, in-depth knowledge of legal and ethical requirements or time to delve into the details. Ultimately, separate resources, maintained by experts familiar with the respective fields of research, may be needed while-in the longer term-harmonization and increase in ease of use will be very desirable.
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Affiliation(s)
- Murat Sariyar
- Institute of Pathology, Charite—University Medicine Berlin, Berlin, Germany
- TMF—Technologie und Methodenplattform e. V., Berlin, Germany
| | | | - Carol Smee
- The Wellcome Trust Sanger Institute, UK ELIXER Hub, Hinxton, Cambridge, United Kingdom
| | - Stephanie Suhr
- European Molecular Biology Laboratory–European Bioinformatics Institute, UK ELIXER Hub, Hinxton, Cambridge, United Kingdom
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Baur J, Moreno-Villanueva M, Kötter T, Sindlinger T, Bürkle A, Berthold MR, Junk M. MARK-AGE data management: Cleaning, exploration and visualization of data. Mech Ageing Dev 2015; 151:38-44. [PMID: 26004801 DOI: 10.1016/j.mad.2015.05.007] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2015] [Revised: 05/13/2015] [Accepted: 05/18/2015] [Indexed: 11/18/2022]
Abstract
Databases are an organized collection of data and necessary to investigate a wide spectrum of research questions. For data evaluation analyzers should be aware of possible data quality problems that can compromise results validity. Therefore data cleaning is an essential part of the data management process, which deals with the identification and correction of errors in order to improve data quality. In our cross-sectional study, biomarkers of ageing, analytical, anthropometric and demographic data from about 3000 volunteers have been collected in the MARK-AGE database. Although several preventive strategies were applied before data entry, errors like miscoding, missing values, batch problems etc., could not be avoided completely. Such errors can result in misleading information and affect the validity of the performed data analysis. Here we present an overview of the methods we applied for dealing with errors in the MARK-AGE database. We especially describe our strategies for the detection of missing values, outliers and batch effects and explain how they can be handled to improve data quality. Finally we report about the tools used for data exploration and data sharing between MARK-AGE collaborators.
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Affiliation(s)
- Jennifer Baur
- Chair for Molecular Toxicology, University of Konstanz, 78457 Konstanz, Germany
| | | | - Tobias Kötter
- Chair for Bioinformatics and Information Mining, University of Konstanz, 78457 Konstanz, Germany
| | - Thilo Sindlinger
- Chair for Molecular Toxicology, University of Konstanz, 78457 Konstanz, Germany
| | - Alexander Bürkle
- Chair for Molecular Toxicology, University of Konstanz, 78457 Konstanz, Germany.
| | - Michael R Berthold
- Chair for Bioinformatics and Information Mining, University of Konstanz, 78457 Konstanz, Germany
| | - Michael Junk
- Department for Mathematics and Statistics,University of Konstanz, 78457 Konstanz, Germany
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38
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Budin-Ljøsne I, Burton P, Isaeva J, Gaye A, Turner A, Murtagh MJ, Wallace S, Ferretti V, Harris JR. DataSHIELD: an ethically robust solution to multiple-site individual-level data analysis. Public Health Genomics 2014; 18:87-96. [PMID: 25532061 DOI: 10.1159/000368959] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2014] [Accepted: 10/08/2014] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND DataSHIELD (Data Aggregation Through Anonymous Summary-statistics from Harmonised Individual levEL Databases) has been proposed to facilitate the co-analysis of individual-level data from multiple studies without physically sharing the data. In a previous paper, we investigated whether DataSHIELD could protect participant confidentiality in accordance with UK law. In this follow-up paper, we investigate whether DataSHIELD addresses a broader range of ethics-related data-sharing concerns. METHODS Ethics-related data-sharing concerns of Institutional Review Boards, ethics experts, international research consortia and research participants were identified through a literature search and systematically examined at a multidisciplinary workshop to determine whether DataSHIELD proposes mechanisms which can address these concerns. RESULTS DataSHIELD addresses several ethics-related data-sharing concerns related to privacy, confidentiality, and the protection of the research participant's rights while sharing data and after the data have been shared. The data remain entirely under the direct management of the study that collected them. Data processing commands are strictly supervised, and the data are queried in a protected environment. Issues related to the return of individual research results when data are shared are eliminated; the responsibility for return remains at the study of origin. CONCLUSION DataSHIELD can provide an innovative and robust solution for addressing commonly encountered ethics-related data-sharing concerns.
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Affiliation(s)
- Isabelle Budin-Ljøsne
- Division of Epidemiology, Department of Genes and Environment, Norwegian Institute of Public Health, Oslo, Norway
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39
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Kosseim P, Dove ES, Baggaley C, Meslin EM, Cate FH, Kaye J, Harris JR, Knoppers BM. Building a data sharing model for global genomic research. Genome Biol 2014; 15:430. [PMID: 25221857 PMCID: PMC4282015 DOI: 10.1186/s13059-014-0430-2] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
Data sharing models designed to facilitate global business provide insights for improving transborder genomic data sharing. We argue that a flexible, externally endorsed, multilateral arrangement, combined with an objective third-party assurance mechanism, can effectively balance privacy with the need to share genomic data globally.
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Affiliation(s)
- Patricia Kosseim
- />Office of the Privacy Commissioner of Canada, Ottawa, Ontario K1A 1H3 Canada
| | - Edward S Dove
- />Centre of Genomics and Policy, McGill University, Montreal, Quebec H3A 0G1 Canada
| | - Carman Baggaley
- />Office of the Privacy Commissioner of Canada, Ottawa, Ontario K1A 1H3 Canada
| | - Eric M Meslin
- />IU Center for Bioethics, Indiana University, Indianapolis, IN 46202 USA
- />Center for Law, Ethics, and Applied Research in Health Information, Bloomington, IN 47408 USA
| | - Fred H Cate
- />Center for Law, Ethics, and Applied Research in Health Information, Bloomington, IN 47408 USA
- />Maurer School of Law, Indiana University, Bloomington, IN 47405 USA
| | - Jane Kaye
- />HeLEX-Centre for Health, Law and Emerging Technologies, University of Oxford, Old Road Campus, Oxford, OX3 7LF UK
| | - Jennifer R Harris
- />Division of Epidemiology, Department of Genes and Environment, Norwegian Institute of Public Health, PO Box 4404, Nydalen, Oslo 0403 Norway
| | - Bartha M Knoppers
- />Centre of Genomics and Policy, McGill University, Montreal, Quebec H3A 0G1 Canada
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40
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Knoppers BM, Harris JR, Budin-Ljøsne I, Dove ES. A human rights approach to an international code of conduct for genomic and clinical data sharing. Hum Genet 2014; 133:895-903. [PMID: 24573176 PMCID: PMC4053599 DOI: 10.1007/s00439-014-1432-6] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2013] [Accepted: 02/16/2014] [Indexed: 11/30/2022]
Abstract
Fostering data sharing is a scientific and ethical imperative. Health gains can be achieved more comprehensively and quickly by combining large, information-rich datasets from across conventionally siloed disciplines and geographic areas. While collaboration for data sharing is increasingly embraced by policymakers and the international biomedical community, we lack a common ethical and legal framework to connect regulators, funders, consortia, and research projects so as to facilitate genomic and clinical data linkage, global science collaboration, and responsible research conduct. Governance tools can be used to responsibly steer the sharing of data for proper stewardship of research discovery, genomics research resources, and their clinical applications. In this article, we propose that an international code of conduct be designed to enable global genomic and clinical data sharing for biomedical research. To give this proposed code universal application and accountability, however, we propose to position it within a human rights framework. This proposition is not without precedent: international treaties have long recognized that everyone has a right to the benefits of scientific progress and its applications, and a right to the protection of the moral and material interests resulting from scientific productions. It is time to apply these twin rights to internationally collaborative genomic and clinical data sharing.
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Affiliation(s)
- Bartha M. Knoppers
- Centre of Genomics and Policy, McGill University, 740 Dr. Penfield Avenue, Suite 5200, Montreal, H3A 0G1 Canada
| | - Jennifer R. Harris
- Division of Epidemiology, Department of Genes and Environment, Norwegian Institute of Public Health, PO Box 4404, Nydalen, 0403 Oslo Norway
| | - Isabelle Budin-Ljøsne
- Division of Epidemiology, Department of Genes and Environment, Norwegian Institute of Public Health, PO Box 4404, Nydalen, 0403 Oslo Norway
| | - Edward S. Dove
- Centre of Genomics and Policy, McGill University, 740 Dr. Penfield Avenue, Suite 5200, Montreal, H3A 0G1 Canada
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Choudhury S, Fishman JR, McGowan ML, Juengst ET. Big data, open science and the brain: lessons learned from genomics. Front Hum Neurosci 2014; 8:239. [PMID: 24904347 PMCID: PMC4032989 DOI: 10.3389/fnhum.2014.00239] [Citation(s) in RCA: 89] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2014] [Accepted: 04/02/2014] [Indexed: 12/14/2022] Open
Abstract
The BRAIN Initiative aims to break new ground in the scale and speed of data collection in neuroscience, requiring tools to handle data in the magnitude of yottabytes (1024). The scale, investment and organization of it are being compared to the Human Genome Project (HGP), which has exemplified “big science” for biology. In line with the trend towards Big Data in genomic research, the promise of the BRAIN Initiative, as well as the European Human Brain Project, rests on the possibility to amass vast quantities of data to model the complex interactions between the brain and behavior and inform the diagnosis and prevention of neurological disorders and psychiatric disease. Advocates of this “data driven” paradigm in neuroscience argue that harnessing the large quantities of data generated across laboratories worldwide has numerous methodological, ethical and economic advantages, but it requires the neuroscience community to adopt a culture of data sharing and open access to benefit from them. In this article, we examine the rationale for data sharing among advocates and briefly exemplify these in terms of new “open neuroscience” projects. Then, drawing on the frequently invoked model of data sharing in genomics, we go on to demonstrate the complexities of data sharing, shedding light on the sociological and ethical challenges within the realms of institutions, researchers and participants, namely dilemmas around public/private interests in data, (lack of) motivation to share in the academic community, and potential loss of participant anonymity. Our paper serves to highlight some foreseeable tensions around data sharing relevant to the emergent “open neuroscience” movement.
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Affiliation(s)
- Suparna Choudhury
- Division of Social and Transcultural Psychiatry, McGill University and Lady Davis Institute, Jewish General Hospital Montreal, QC, Canada
| | - Jennifer R Fishman
- Biomedical Ethics Unit, Social Studies of Medicine Department, McGill University Montreal, QC, Canada
| | - Michelle L McGowan
- Department of Bioethics, Case Western Reserve University School of Medicine Cleveland, Ohio, USA
| | - Eric T Juengst
- Center for Bioethics, University of North Carolina Chapel Hill, NC, USA
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Dove ES, Knoppers BM, Zawati MH. An ethics safe harbor for international genomics research? Genome Med 2013; 5:99. [PMID: 24267880 PMCID: PMC3978721 DOI: 10.1186/gm503] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2013] [Accepted: 11/04/2013] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Genomics research is becoming increasingly globally connected and collaborative, contesting traditional ethical and legal boundaries between global and local research practice. As well, global data-driven genomics research holds great promise for health discoveries. Yet, paradoxically, current research ethics review systems around the world challenge potential improvements in human health from such research and thus undermine respect for research participants. Case reports illustrate that the current system is costly, fragmented, inefficient, inadequate, and inconsistent. There is an urgent need to improve the governance system of ethics review to enable secure and seamless genomic and clinical data sharing across jurisdictions. DISCUSSION Building on the international privacy 'safe harbor' model that was developed following the adoption of the European Privacy Directive, we propose an international infrastructure. The goal is to create a streamlined and harmonized ethics governance system for international, data-driven genomics research projects. The proposed 'Safe Harbor Framework for International Ethics Equivalency' would consist in part of an agency supporting an International Federation for Ethics Review (IFER), formed by a voluntary agreement among countries, granting agencies, philanthropies, institutions, and healthcare, patient advocacy, and research organizations. IFER would be both a central ethics review body and also a forum for review and follow-up of policies concerning ethics norms for international genomics research projects. It would be built on five principle elements: (1) registration; (2) compliance review; (3) recognition; (4) monitoring and enforcement; and (5) public participation. SUMMARY A Safe Harbor Framework for International Ethics Equivalency would create many benefits for researchers, countries, and the general public, and may eventually have application beyond genomics to other areas of biomedical research that increasingly engage in secondary use of data and present only negligible risks. Among the benefits, research participants and patients would have uniform adequate protection, while researchers would be ensured expert ethics review with a reduction in cost, time, administrative hassle, and redundant regulatory hurdles. Most importantly, society would enjoy the maximization of the potential benefits of genomics research.
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Affiliation(s)
- Edward S Dove
- Centre of Genomics and Policy, McGill University, 740 Dr. Penfield Avenue, Suite 5200, Montreal H3A 0G1, Canada
| | - Bartha M Knoppers
- Centre of Genomics and Policy, McGill University, 740 Dr. Penfield Avenue, Suite 5200, Montreal H3A 0G1, Canada
| | - Ma’n H Zawati
- Centre of Genomics and Policy, McGill University, 740 Dr. Penfield Avenue, Suite 5200, Montreal H3A 0G1, Canada
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Data harmonization and federated analysis of population-based studies: the BioSHaRE project. Emerg Themes Epidemiol 2013; 10:12. [PMID: 24257327 PMCID: PMC4175511 DOI: 10.1186/1742-7622-10-12] [Citation(s) in RCA: 90] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2013] [Accepted: 11/11/2013] [Indexed: 01/08/2023] Open
Abstract
Abstracts
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