1
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de Groot NF. A contextual integrity approach to genomic information: what bioethics can learn from big data ethics. MEDICINE, HEALTH CARE, AND PHILOSOPHY 2024:10.1007/s11019-024-10211-0. [PMID: 38865053 DOI: 10.1007/s11019-024-10211-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/27/2024] [Indexed: 06/13/2024]
Abstract
Genomic data is generated, processed and analysed at an increasingly rapid pace. This data is not limited to the medical context, but plays an important role in other contexts in society, such as commercial DNA testing, the forensic setting, archaeological research, and genetic surveillance. Genomic information also crosses the borders of these domains, e.g. forensic use of medical genetic information, insurance use of medical genomic information, or research use of commercial genomic data. This paper (1) argues that an informed consent approach for genomic information has limitations in many societal contexts, and (2) seeks to broaden the bioethical debate on genomic information by suggesting an approach that is applicable across multiple societal contexts. I argue that the contextual integrity framework, a theory rooted in information technology and big data ethics, is an effective tool to explore ethical challenges that arise from genomic information within a variety of different contexts. Rather than focusing on individual control over information, the contextual integrity approach holds that information should be shared and protected according to the norms that govern certain distinct social contexts. Several advantages of this contextual integrity approach will be discussed. The paper concludes that the contextual integrity framework helps to articulate and address a broad spectrum of ethical, social, and political factors in a variety of different societal contexts, while giving consideration to the interests of individuals, groups, and society at large.
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Affiliation(s)
- Nina F de Groot
- Department of Philosophy, Faculty of Humanities, VU University Amsterdam, Amsterdam, the Netherlands.
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2
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Maor M, Billig M. Women Who Perform Social Egg Freezing as Moral Pioneers: The Case of Ultra-Orthodox Communities in Israel. JOURNAL OF RELIGION AND HEALTH 2024:10.1007/s10943-024-02062-z. [PMID: 38782858 DOI: 10.1007/s10943-024-02062-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/13/2024] [Indexed: 05/25/2024]
Abstract
Social egg freezing (SEF) is a new reproductive technology that is increasingly used within ultra-Orthodox Jewish communities, stirring tensions between tradition and modernity. Based on in-depth semi-structured interviews, this study examined how ultra-Orthodox singles who employ SEF engage in social negotiations over gender- and body-related norms. Findings show that participants successfully assimilated SEF by establishing facts on the ground and discreetly spreading information while actively avoiding tensions that may threaten religious tradition. SEF did not push participants into modern individualism or dissolve their strong connection to the community. However they did modify social boundaries and articulated social criticism.
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Affiliation(s)
- Maya Maor
- Department of Sociology and Anthropology, Ariel University, Ariel, Israel.
| | - Miriam Billig
- Department of Sociology and Anthropology, Ariel University, Ariel, Israel
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3
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Nikolski M, Hovig E, Al-Shahrour F, Blomberg N, Scollen S, Valencia A, Saunders G. Roadmap for a European cancer data management and precision medicine infrastructure. NATURE CANCER 2024; 5:367-372. [PMID: 38321342 DOI: 10.1038/s43018-023-00717-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Affiliation(s)
- Macha Nikolski
- University of Bordeaux, CNRS-IBGC, UMR 5095, Bordeaux, France.
- University of Bordeaux, Bordeaux Bioinformatics Center CBiB, Bordeaux, France.
| | - Eivind Hovig
- Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Fatima Al-Shahrour
- Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | | | - Serena Scollen
- ELIXIR Hub, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Alfonso Valencia
- Life Sciences Department, Barcelona Supercomputing Center, Barcelona, Spain
- ICREA, Barcelona, Spain
| | - Gary Saunders
- ELIXIR Hub, Wellcome Genome Campus, Hinxton, Cambridge, UK
- EATRIS-ERIC, Amsterdam, the Netherlands
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4
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Deflaux N, Selvaraj MS, Condon HR, Mayo K, Haidermota S, Basford MA, Lunt C, Philippakis AA, Roden DM, Denny JC, Musick A, Collins R, Allen N, Effingham M, Glazer D, Natarajan P, Bick AG. Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis. Nat Commun 2023; 14:5419. [PMID: 37669985 PMCID: PMC10480504 DOI: 10.1038/s41467-023-41185-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 08/24/2023] [Indexed: 09/07/2023] Open
Abstract
Recently, large scale genomic projects such as All of Us and the UK Biobank have introduced a new research paradigm where data are stored centrally in cloud-based Trusted Research Environments (TREs). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conduct a Genome-Wide Association Study of standard lipid measures using two approaches: meta-analysis and pooled analysis. Comparison of full summary data from both approaches with an external study shows strong correlation of known loci with lipid levels (R2 ~ 83-97%). Importantly, 90 variants meet the significance threshold only in the meta-analysis and 64 variants are significant only in pooled analysis, with approximately 20% of variants in each of those groups being most prevalent in non-European, non-Asian ancestry individuals. These findings have important implications, as technical and policy choices lead to cross-cohort analyses generating similar, but not identical results, particularly for non-European ancestral populations.
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Affiliation(s)
| | - Margaret Sunitha Selvaraj
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Henry Robert Condon
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kelsey Mayo
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sara Haidermota
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
| | - Melissa A Basford
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Chris Lunt
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | | | - Dan M Roden
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Joshua C Denny
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Anjene Musick
- All of Us Research Program, National Institutes of Health, Bethesda, MD, USA
| | - Rory Collins
- Nuffield Department of Population Health, University of Oxford, Oxford, Oxfordshire, UK
- UK Biobank, Cheadle, Stockport, UK
| | - Naomi Allen
- Nuffield Department of Population Health, University of Oxford, Oxford, Oxfordshire, UK
- UK Biobank, Cheadle, Stockport, UK
| | | | | | - Pradeep Natarajan
- Program in Medical and Population Genetics and the Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Division of Cardiology, Massachusetts General Hospital, Boston, MA, USA
| | - Alexander G Bick
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
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Sanchini V, Marelli L, Monturano M, Bonizzi G, Peruzzotti G, Orecchia R, Pravettoni G. A comprehensive ethics and data governance framework for data-intensive health research: Lessons from an Italian cancer research institute. Account Res 2023:1-18. [PMID: 37608751 DOI: 10.1080/08989621.2023.2248884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/25/2023] [Accepted: 08/14/2023] [Indexed: 08/24/2023]
Affiliation(s)
- Virginia Sanchini
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
- Centre for Biomedical Ethics and Law, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
| | - Luca Marelli
- Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, Italy
- Centre for Sociological Research, KU Leuven, Leuven, Belgium
- European Institute of Oncology IRCCS, Milan, Italy
| | | | | | | | | | - Gabriella Pravettoni
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
- Applied Research Division for Cognitive and Psychological Science, European Institute of Oncology IRCCS, Milan, Italy
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Singh PP, Benayoun BA. Considerations for reproducible omics in aging research. NATURE AGING 2023; 3:921-930. [PMID: 37386258 PMCID: PMC10527412 DOI: 10.1038/s43587-023-00448-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 06/01/2023] [Indexed: 07/01/2023]
Abstract
Technical advancements over the past two decades have enabled the measurement of the panoply of molecules of cells and tissues including transcriptomes, epigenomes, metabolomes and proteomes at unprecedented resolution. Unbiased profiling of these molecular landscapes in the context of aging can reveal important details about mechanisms underlying age-related functional decline and age-related diseases. However, the high-throughput nature of these experiments creates unique analytical and design demands for robustness and reproducibility. In addition, 'omic' experiments are generally onerous, making it crucial to effectively design them to eliminate as many spurious sources of variation as possible as well as account for any biological or technical parameter that may influence such measures. In this Perspective, we provide general guidelines on best practices in the design and analysis of omic experiments in aging research from experimental design to data analysis and considerations for long-term reproducibility and validation of such studies.
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Affiliation(s)
- Param Priya Singh
- Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA.
- Bakar Aging Research Institute, University of California, San Francisco, San Francisco, CA, USA.
| | - Bérénice A Benayoun
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
- Molecular and Computational Biology Department, USC Dornsife College of Letters, Arts and Sciences, Los Angeles, CA, USA.
- Biochemistry and Molecular Medicine Department, USC Keck School of Medicine, Los Angeles, CA, USA.
- Epigenetics and Gene Regulation, USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA.
- USC Stem Cell Initiative, Los Angeles, CA, USA.
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Dahlquist JM, Nelson SC, Fullerton SM. Cloud-based biomedical data storage and analysis for genomic research: Landscape analysis of data governance in emerging NIH-supported platforms. HGG ADVANCES 2023; 4:100196. [PMID: 37181330 PMCID: PMC10173774 DOI: 10.1016/j.xhgg.2023.100196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 04/07/2023] [Indexed: 05/16/2023] Open
Abstract
The storage, sharing, and analysis of genomic data poses technical and logistical challenges that have precipitated the development of cloud-based computing platforms designed to facilitate collaboration and maximize the scientific utility of data. To understand cloud platforms' policies and procedures and the implications for different stakeholder groups, in summer 2021, we reviewed publicly available documents (N = 94) sourced from platform websites, scientific literature, and lay media for five NIH-funded cloud platforms (the All of Us Research Hub, NHGRI AnVIL, NHLBI BioData Catalyst, NCI Genomic Data Commons, and the Kids First Data Resource Center) and a pre-existing data sharing mechanism, dbGaP. Platform policies were compared across seven categories of data governance: data submission, data ingestion, user authentication and authorization, data security, data access, auditing, and sanctions. Our analysis finds similarities across the platforms, including reliance on a formal data ingestion process, multiple tiers of data access with varying user authentication and/or authorization requirements, platform and user data security measures, and auditing for inappropriate data use. Platforms differ in how data tiers are organized, as well as the specifics of user authentication and authorization across access tiers. Our analysis maps elements of data governance across emerging NIH-funded cloud platforms and as such provides a key resource for stakeholders seeking to understand and utilize data access and analysis options across platforms and to surface aspects of governance that may require harmonization to achieve the desired interoperability.
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Affiliation(s)
- Jacklyn M. Dahlquist
- Department of Bioethics and Humanities, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Sarah C. Nelson
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
- Corresponding author
| | - Stephanie M. Fullerton
- Department of Bioethics and Humanities, University of Washington School of Medicine, Seattle, WA 98195, USA
- Corresponding author
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Wagner JK, Yu JH, Fullwiley D, Moore C, Wilson JF, Bamshad MJ, Royal CD. Guidelines for genetic ancestry inference created through roundtable discussions. HGG ADVANCES 2023; 4:100178. [PMID: 36798092 PMCID: PMC9926022 DOI: 10.1016/j.xhgg.2023.100178] [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: 09/02/2022] [Accepted: 01/03/2023] [Indexed: 01/15/2023] Open
Abstract
The use of genetic and genomic technology to infer ancestry is commonplace in a variety of contexts, particularly in biomedical research and for direct-to-consumer genetic testing. In 2013 and 2015, two roundtables engaged a diverse group of stakeholders toward the development of guidelines for inferring genetic ancestry in academia and industry. This report shares the stakeholder groups' work and provides an analysis of, commentary on, and views from the groundbreaking and sustained dialogue. We describe the engagement processes and the stakeholder groups' resulting statements and proposed guidelines. The guidelines focus on five key areas: application of genetic ancestry inference, assumptions and confidence/laboratory and statistical methods, terminology and population identifiers, impact on individuals and groups, and communication or translation of genetic ancestry inferences. We delineate the terms and limitations of the guidelines and discuss their critical role in advancing the development and implementation of best practices for inferring genetic ancestry and reporting the results. These efforts should inform both governmental regulation and self-regulation.
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Affiliation(s)
- Jennifer K. Wagner
- School of Engineering Design and Innovation, Pennsylvania State University, University Park, PA 16802, USA
- Institute for Computational and Data Science, Pennsylvania State University, University Park, PA 16802, USA
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA 16802, USA
- Rock Ethics Institute, Pennsylvania State University, University Park, PA 16802, USA
- Penn State Law, University Park, PA 16802, USA
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA
| | - Joon-Ho Yu
- Department of Pediatrics and Institute for Public Health Genetics, University of Washington, Seattle, WA 98195, USA
- Treuman Katz Center for Pediatric Bioethics, Seattle Children’s Hospital and Research Institute, Seattle, WA 98101, USA
| | - Duana Fullwiley
- Department of Anthropology, Stanford University, Stanford, CA 94305, USA
| | | | - James F. Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh EH8 9AG, Scotland
| | - Michael J. Bamshad
- Department of Pediatrics and Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
- Division of Genetic Medicine, Seattle Children’s Hospital, Seattle, WA 98101, USA
| | - Charmaine D. Royal
- Departments of African and African American Studies, Biology, Global Health, and Family Medicine and Community Health, Duke University, Durham, NC 27708, USA
| | - Genetic Ancestry Inference Roundtable Participants
- School of Engineering Design and Innovation, Pennsylvania State University, University Park, PA 16802, USA
- Institute for Computational and Data Science, Pennsylvania State University, University Park, PA 16802, USA
- Department of Biomedical Engineering, Pennsylvania State University, University Park, PA 16802, USA
- Rock Ethics Institute, Pennsylvania State University, University Park, PA 16802, USA
- Penn State Law, University Park, PA 16802, USA
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA
- Department of Pediatrics and Institute for Public Health Genetics, University of Washington, Seattle, WA 98195, USA
- Treuman Katz Center for Pediatric Bioethics, Seattle Children’s Hospital and Research Institute, Seattle, WA 98101, USA
- Department of Anthropology, Stanford University, Stanford, CA 94305, USA
- The DNA Detectives, Dana Point, CA, USA
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh EH8 9AG, Scotland
- Department of Pediatrics and Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
- Division of Genetic Medicine, Seattle Children’s Hospital, Seattle, WA 98101, USA
- Departments of African and African American Studies, Biology, Global Health, and Family Medicine and Community Health, Duke University, Durham, NC 27708, USA
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Longstaff H, Flamenbaum J, Richer E, Egar J, McMaster CR, Zawati MH. Core elements of participant consent documents for Canadian human genomics research and the National Human Genome Library: guidance for policy. CMAJ 2022; 194:E1500-E1508. [PMID: 36379551 PMCID: PMC9828931 DOI: 10.1503/cmaj.212063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Affiliation(s)
- Holly Longstaff
- Provincial Health Services Authority of British Columbia (Longstaff); Faculty of Health Sciences (Longstaff), Simon Fraser University, Burnaby, BC; Ethics Office, Science and Policy Branch (Flamenbaum), Canadian Institutes of Health Research, Ottawa, Ont.; Institute of Genetics (Richer, Egar, McMaster) Canadian Institutes of Health Research, Halifax, NS; Centre of Genomics and Policy (Zawati), McGill University, Montréal, Que
| | - Jaime Flamenbaum
- Provincial Health Services Authority of British Columbia (Longstaff); Faculty of Health Sciences (Longstaff), Simon Fraser University, Burnaby, BC; Ethics Office, Science and Policy Branch (Flamenbaum), Canadian Institutes of Health Research, Ottawa, Ont.; Institute of Genetics (Richer, Egar, McMaster) Canadian Institutes of Health Research, Halifax, NS; Centre of Genomics and Policy (Zawati), McGill University, Montréal, Que
| | - Etienne Richer
- Provincial Health Services Authority of British Columbia (Longstaff); Faculty of Health Sciences (Longstaff), Simon Fraser University, Burnaby, BC; Ethics Office, Science and Policy Branch (Flamenbaum), Canadian Institutes of Health Research, Ottawa, Ont.; Institute of Genetics (Richer, Egar, McMaster) Canadian Institutes of Health Research, Halifax, NS; Centre of Genomics and Policy (Zawati), McGill University, Montréal, Que
| | - Jeanne Egar
- Provincial Health Services Authority of British Columbia (Longstaff); Faculty of Health Sciences (Longstaff), Simon Fraser University, Burnaby, BC; Ethics Office, Science and Policy Branch (Flamenbaum), Canadian Institutes of Health Research, Ottawa, Ont.; Institute of Genetics (Richer, Egar, McMaster) Canadian Institutes of Health Research, Halifax, NS; Centre of Genomics and Policy (Zawati), McGill University, Montréal, Que
| | - Christopher R McMaster
- Provincial Health Services Authority of British Columbia (Longstaff); Faculty of Health Sciences (Longstaff), Simon Fraser University, Burnaby, BC; Ethics Office, Science and Policy Branch (Flamenbaum), Canadian Institutes of Health Research, Ottawa, Ont.; Institute of Genetics (Richer, Egar, McMaster) Canadian Institutes of Health Research, Halifax, NS; Centre of Genomics and Policy (Zawati), McGill University, Montréal, Que.
| | - Ma'n H Zawati
- Provincial Health Services Authority of British Columbia (Longstaff); Faculty of Health Sciences (Longstaff), Simon Fraser University, Burnaby, BC; Ethics Office, Science and Policy Branch (Flamenbaum), Canadian Institutes of Health Research, Ottawa, Ont.; Institute of Genetics (Richer, Egar, McMaster) Canadian Institutes of Health Research, Halifax, NS; Centre of Genomics and Policy (Zawati), McGill University, Montréal, Que
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Jeong JC, Hands I, Kolesar JM, Rao M, Davis B, Dobyns Y, Hurt-Mueller J, Levens J, Gregory J, Williams J, Witt L, Kim EM, Burton C, Elbiheary AA, Chang M, Durbin EB. Local data commons: the sleeping beauty in the community of data commons. BMC Bioinformatics 2022; 23:386. [PMID: 36151511 PMCID: PMC9502580 DOI: 10.1186/s12859-022-04922-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Accepted: 09/12/2022] [Indexed: 12/03/2022] Open
Abstract
Background Public Data Commons (PDC) have been highlighted in the scientific literature for their capacity to collect and harmonize big data. On the other hand, local data commons (LDC), located within an institution or organization, have been underrepresented in the scientific literature, even though they are a critical part of research infrastructure. Being closest to the sources of data, LDCs provide the ability to collect and maintain the most up-to-date, high-quality data within an organization, closest to the sources of the data. As a data provider, LDCs have many challenges in both collecting and standardizing data, moreover, as a consumer of PDC, they face problems of data harmonization stemming from the monolithic harmonization pipeline designs commonly adapted by many PDCs. Unfortunately, existing guidelines and resources for building and maintaining data commons exclusively focus on PDC and provide very little information on LDC. Results This article focuses on four important observations. First, there are three different types of LDC service models that are defined based on their roles and requirements. These can be used as guidelines for building new LDC or enhancing the services of existing LDC. Second, the seven core services of LDC are discussed, including cohort identification and facilitation of genomic sequencing, the management of molecular reports and associated infrastructure, quality control, data harmonization, data integration, data sharing, and data access control. Third, instead of commonly developed monolithic systems, we propose a new data sharing method for data harmonization that combines both divide-and-conquer and bottom-up approaches. Finally, an end-to-end LDC implementation is introduced with real-world examples. Conclusions Although LDCs are an optimal place to identify and address data quality issues, they have traditionally been relegated to the role of passive data provider for much larger PDC. Indeed, many LDCs limit their functions to only conducting routine data storage and transmission tasks due to a lack of information on how to design, develop, and improve their services using limited resources. We hope that this work will be the first small step in raising awareness among the LDCs of their expanded utility and to publicize to a wider audience the importance of LDC.
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Affiliation(s)
- Jong Cheol Jeong
- Division of Biomedical Informatics, College of Medicine, University of Kentucky, Lexington, KY, USA. .,Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA.
| | - Isaac Hands
- Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA.,Kentucky Cancer Registry, Lexington, KY, USA
| | - Jill M Kolesar
- Department of Pharmacy Practice and Science, College of Pharmacy, University of Kentucky, Lexington, KY, USA
| | - Mahadev Rao
- Department of Pharmacy Practice, Center for Translational Research, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Bront Davis
- Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA.,Kentucky Cancer Registry, Lexington, KY, USA
| | - York Dobyns
- Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA.,Kentucky Cancer Registry, Lexington, KY, USA
| | - Joseph Hurt-Mueller
- Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA.,Kentucky Cancer Registry, Lexington, KY, USA
| | - Justin Levens
- Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA.,Kentucky Cancer Registry, Lexington, KY, USA
| | - Jenny Gregory
- Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA.,Kentucky Cancer Registry, Lexington, KY, USA
| | - John Williams
- Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA.,Kentucky Cancer Registry, Lexington, KY, USA
| | - Lisa Witt
- Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA.,Kentucky Cancer Registry, Lexington, KY, USA
| | - Eun Mi Kim
- Department of Computer Science, Eastern Kentucky University, Richmond, KY, USA
| | - Carlee Burton
- Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA
| | - Amir A Elbiheary
- Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA
| | - Mingguang Chang
- Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA
| | - Eric B Durbin
- Division of Biomedical Informatics, College of Medicine, University of Kentucky, Lexington, KY, USA. .,Cancer Research Informatics Shared Resource Facility, Markey Cancer Center, Lexington, KY, USA. .,Kentucky Cancer Registry, Lexington, KY, USA.
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11
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Raj M, Ryan K, Nong P, Calhoun K, Trinidad MG, De Vries R, Creary M, Spector-Bagdady K, Kardia SLR, Platt J. Public Deliberation Process on Patient Perspectives on Health Information Sharing: Evaluative Descriptive Study. JMIR Cancer 2022; 8:e37793. [PMID: 36112409 PMCID: PMC9526123 DOI: 10.2196/37793] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 07/07/2022] [Accepted: 07/20/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Precision oncology is one of the fastest-developing domains of personalized medicine and is one of many data-intensive fields. Policy for health information sharing that is informed by patient perspectives can help organizations align practice with patient preferences and expectations, but many patients are largely unaware of the complexities of how and why clinical health information is shared. OBJECTIVE This paper evaluates the process of public deliberation as an approach to understanding the values and preferences of current and former patients with cancer regarding the use and sharing of health information collected in the context of precision oncology. METHODS We conducted public deliberations with patients who had a current or former cancer diagnosis. A total of 61 participants attended 1 of 2 deliberative sessions (session 1, n=28; session 2, n=33). Study team experts led two educational plenary sessions, and trained study team members then facilitated discussions with small groups of participants. Participants completed pre- and postdeliberation surveys measuring knowledge, attitudes, and beliefs about precision oncology and data sharing. Following informational sessions, participants discussed, ranked, and deliberated two policy-related scenarios in small groups and in a plenary session. In the analysis, we evaluate our process of developing the deliberative sessions, the knowledge gained by participants during the process, and the extent to which participants reasoned with complex information to identify policy preferences. RESULTS The deliberation process was rated highly by participants. Participants felt they were listened to by their group facilitator, that their opinions were respected by their group, and that the process that led to the group's decision was fair. Participants demonstrated improved knowledge of health data sharing policies between pre- and postdeliberation surveys, especially regarding the roles of physicians and health departments in health information sharing. Qualitative analysis of reasoning revealed that participants recognized complexity, made compromises, and engaged with trade-offs, considering both individual and societal perspectives related to health data sharing. CONCLUSIONS The deliberative approach can be valuable for soliciting the input of informed patients on complex issues such as health information sharing policy. Participants in our two public deliberations demonstrated that giving patients information about a complex topic like health data sharing and the opportunity to reason with others and discuss the information can help garner important insights into policy preferences and concerns. Data on public preferences, along with the rationale for information sharing, can help inform policy-making processes. Increasing transparency and patient engagement is critical to ensuring that data-driven health care respects patient autonomy and honors patient values and expectations.
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Affiliation(s)
- Minakshi Raj
- Department of Kinesiology and Community Health, University of Illinois at Urbana Champaign, Champaign, IL, United States
| | - Kerry Ryan
- Center for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Paige Nong
- School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Karen Calhoun
- Michigan Institute for Clinical & Health Research, Ann Arbor, MI, United States
| | - M Grace Trinidad
- National Hemophilia Program Coordinating Center, Ann Arbor, MI, United States
| | - Raymond De Vries
- Center for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor, MI, United States
- Department of Learning Health Sciences, University of Michigan, Ann Arbor, MI, United States
| | - Melissa Creary
- School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Kayte Spector-Bagdady
- Center for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor, MI, United States
- Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, United States
| | - Sharon L R Kardia
- School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Jodyn Platt
- Center for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor, MI, United States
- Department of Learning Health Sciences, University of Michigan, Ann Arbor, MI, United States
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12
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Milne R, Sheehan M, Barnes B, Kapper J, Lea N, N'Dow J, Singh G, Martín-Uranga A, Hughes N. A concentric circles view of health data relations facilitates understanding of sociotechnical challenges for learning health systems and the role of federated data networks. Front Big Data 2022; 5:945739. [PMID: 36238653 PMCID: PMC9552575 DOI: 10.3389/fdata.2022.945739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
The ability to use clinical and research data at scale is central to hopes for data-driven medicine. However, in using such data researchers often encounter hurdles–both technical, such as differing data security requirements, and social, such as the terms of informed consent, legal requirements and patient and public trust. Federated or distributed data networks have been proposed and adopted in response to these hurdles. However, to date there has been little consideration of how FDNs respond to both technical and social constraints on data use. In this Perspective we propose an approach to thinking about data in terms that make it easier to navigate the health data space and understand the value of differing approaches to data collection, storage and sharing. We set out a socio-technical model of data systems that we call the “Concentric Circles View” (CCV) of data-relationships. The aim is to enable a consistent understanding of the fit between the local relationships within which data are produced and the extended socio-technical systems that enable their use. The paper suggests this model can help understand and tackle challenges associated with the use of real-world data in the health setting. We use the model to understand not only how but why federated networks may be well placed to address emerging issues and adapt to the evolving needs of health research for patient benefit. We conclude that the CCV provides a useful model with broader application in mapping, understanding, and tackling the major challenges associated with using real world data in the health setting.
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Affiliation(s)
- Richard Milne
- Wellcome Connecting Science, Cambridge, United Kingdom
- Kavli Centre for Ethics, Science and the Public, Faculty of Education, University of Cambridge, Cambridge, United Kingdom
| | - Mark Sheehan
- Ethox Centre, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Oxford National Institute for Health and Care Research (NIHR) Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, United Kingdom
| | - Brendan Barnes
- European Federation of Pharmaceutical Industries and Associations, Brussels, Belgium
| | - Janek Kapper
- Estonian Chamber of Disabled People/European Patients Forum, The Estonian Inflammatory Bowel Disease Society, Tallinn, Estonia
| | - Nathan Lea
- Institute for Innovation Through Health Data (i-HD), Gent, Belgium
| | - James N'Dow
- Academic Urology Unit, University of Aberdeen, Aberdeen, United Kingdom
| | | | | | - Nigel Hughes
- Janssen Research and Development, Beerse, Belgium
- *Correspondence: Nigel Hughes
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13
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Buchbinder M, Juengst E, Rennie S, Blue C, Rosen DL. Advancing a Data Justice Framework for Public Health Surveillance. AJOB Empir Bioeth 2022; 13:205-213. [PMID: 35442141 PMCID: PMC10777676 DOI: 10.1080/23294515.2022.2063997] [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] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
BACKGROUND Bioethical debates about privacy, big data, and public health surveillance have not sufficiently engaged the perspectives of those being surveilled. The data justice framework suggests that big data applications have the potential to create disproportionate harm for socially marginalized groups. Using examples from our research on HIV surveillance for individuals incarcerated in jails, we analyze ethical issues in deploying big data in public health surveillance. METHODS We conducted qualitative, semi-structured interviews with 24 people living with HIV who had been previously incarcerated in county jails about their perspectives on and experiences with HIV surveillance, as part of a larger study to characterize ethical considerations in leveraging big data techniques to enhance continuity of care for incarcerated people living with HIV. RESULTS Most participants expressed support for the state health department tracking HIV testing results and viral load data. Several viewed HIV surveillance as a violation of privacy, and several had actively avoided contact from state public health outreach workers. Participants were most likely to express reservations about surveillance when they viewed the state's motives as self-interested. Perspectives highlight the mistrust that structurally vulnerable people may have in the state's capacity to act as an agent of welfare. Findings suggest that adopting a nuanced, context-sensitive view on surveillance is essential. CONCLUSIONS Establishing trustworthiness through interpersonal interactions with public health personnel is important to reversing historical legacies of harm to racial minorities and structurally vulnerable groups. Empowering stakeholders to participate in the design and implementation of data infrastructure and governance is critical for advancing a data justice agenda, and can offset privacy concerns. The next steps in advancing the data justice framework in public health surveillance will be to innovate ways to represent the voices of structurally vulnerable groups in the design and governance of big data initiatives.
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Affiliation(s)
- Mara Buchbinder
- Department of Social Medicine, Center for Bioethics, UNC—Chapel Hill
| | - Eric Juengst
- Department of Social Medicine, Center for Bioethics, UNC—Chapel Hill
| | - Stuart Rennie
- Department of Social Medicine, Center for Bioethics, UNC—Chapel Hill
| | - Colleen Blue
- Institute for Global Health and Infectious Diseases, UNC—Chapel Hill
| | - David L. Rosen
- Division of Infectious Diseases, Department of Medicine, UNC—Chapel Hill
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14
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Genomic health data generation in the UK: a 360 view. Eur J Hum Genet 2022; 30:782-789. [PMID: 34663916 PMCID: PMC8523282 DOI: 10.1038/s41431-021-00976-w] [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: 05/27/2021] [Revised: 08/25/2021] [Accepted: 09/27/2021] [Indexed: 12/24/2022] Open
Abstract
In the UK, genomic health data is being generated in three major contexts: the healthcare system (based on clinical indication), in large scale research programmes, and for purchasers of direct-to-consumer genetic tests. The recently delivered hybrid clinical/research programme, 100,000 Genomes Project set the scene for a new Genomic Medicine Service, through which the National Health Service aims to deliver consistent and equitable care informed by genomics, while providing data to inform academic and industry research and development. In parallel, a large scale research study, Our Future Health, has UK Government and Industry investment and aims to recruit 5 million volunteers to support research intended to improve early detection, risk stratification, and early intervention for chronic diseases. To explore how current models of genomic health data generation intersect, and to understand clinical, ethical, legal, policy and social issues arising from this intersection, we conducted a series of five multidisciplinary panel discussions attended by 28 invited stakeholders. Meetings were recorded and transcribed. We present a summary of issues identified: genomic test attributes; reasons for generating genomic health data; individuals' motivation to seek genomic data; health service impacts; role of genetic counseling; equity; data uses and security; consent; governance and regulation. We conclude with some suggestions for policy consideration.
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15
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Rahimzadeh V, Lawson J, Rushton G, Dove ES. Leveraging Algorithms to Improve Decision-Making Workflows for Genomic Data Access and Management. Biopreserv Biobank 2022; 20:429-435. [PMID: 35772014 PMCID: PMC9603251 DOI: 10.1089/bio.2022.0042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Studies on the ethics of automating clinical or research decision making using artificial intelligence and other algorithmic tools abound. Less attention has been paid, however, to the scope for, and ethics of, automating decision making within regulatory apparatuses governing the access, use, and exchange of data involving humans for research. In this article, we map how the binary logic flows and real-time capabilities of automated decision support (ADS) systems may be leveraged to accelerate one rate-limiting step in scientific discovery: data access management. We contend that improved auditability, consistency, and efficiency of the data access request process using ADS systems have the potential to yield fairer outcomes in requests for data largely sourced from biospecimens and biobanked samples. This procedural justice rationale reinforces a broader set of participant and data subject rights that data access committees (DACs) indirectly protect. DACs protect the rights of citizens to benefit from science by bringing researchers closer to the data they need to advance that science. DACs also protect the informational dignities of individuals and communities by ensuring the data being accessed are used in ways consistent with participant values. We discuss the development of the Global Alliance for Genomics and Health Data Use Ontology standard as a test case of ADS for genomic data access management specifically, and we synthesize relevant ethical, legal, and social challenges to its implementation in practice. We conclude with an agenda of future research needed to thoughtfully advance strategies for computational governance that endeavor to instill public trust in, and maximize the scientific value of, health-related human data across data types, environments, and user communities.
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Affiliation(s)
- Vasiliki Rahimzadeh
- Stanford Center for Biomedical Ethics, Stanford University, Stanford, California, USA
| | - Jonathan Lawson
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Greg Rushton
- Stanford Center for Biomedical Ethics, Stanford University, Stanford, California, USA
| | - Edward S Dove
- School of Law, University of Edinburgh, Edinburgh, United Kingdom
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16
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Appelbaum PS, Burke W, Parens E, Zeevi DA, Arbour L, Garrison NA, Bonham VL, Chung WK. Is there a way to reduce the inequity in variant interpretation on the basis of ancestry? Am J Hum Genet 2022; 109:981-988. [PMID: 35659933 PMCID: PMC9247826 DOI: 10.1016/j.ajhg.2022.04.012] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
The underrepresentation of non-European ancestry groups in current genomic databases complicates interpretation of their genetic test results, yielding a much higher prevalence of variants of uncertain significance (VUSs). Such VUS findings can frustrate the goals of genetic testing, create anxiety in patients, and lead to unnecessary medical interventions. Approaches to addressing underrepresentation of people with genetic ancestries other than European are being undertaken by broad-based recruitment efforts. However, some underrepresented groups have concerns that might preclude participation in such efforts. We describe here two initiatives aimed at meeting the needs of underrepresented ancestry groups in genomic datasets. The two communities, the Sephardi Jewish community in New York and First Peoples of Canada, have very different concerns about contributing to genomic research and datasets. Sephardi concerns focus on the possible negative effects of genetic findings on the marriage prospects of family members. Canadian Indigenous populations seek control over the research uses to which their genetic data would be put. Both cases involve targeted efforts to respond to the groups' concerns; these efforts include governance models aimed at ensuring that the data are used primarily to inform clinical test analyses and at achieving successful engagement and participation of community members. We suggest that these initiatives could provide models for other ancestral groups seeking to improve the accuracy and utility of clinical genetic testing while respecting the underlying preferences and values of community members with regard to the use of their genetic data.
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Affiliation(s)
- Paul S Appelbaum
- Department of Psychiatry, Columbia University Irving Medical Center, and New York State Psychiatric Institute, New York, NY 10032, USA.
| | - Wylie Burke
- Department of Bioethics and Humanities, University of Washington, Seattle, WA 98195, USA
| | - Erik Parens
- The Hastings Center, Garrison, NY 10524, USA
| | - David A Zeevi
- Dor Yeshorim, The Committee for the Prevention of Jewish Genetic Diseases, Jerusalem, Israel
| | - Laura Arbour
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada; Division of Medical Sciences, University of Victoria, Victoria, BC V8P 5C2, Canada; BC Children's Hospital Research Institute, Victoria, BC V8P 5C2, Canada
| | - Nanibaa' A Garrison
- Institute for Society and Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA; Institute for Precision Health, University of California Los Angeles, Los Angeles, CA 90095; Division of General Internal Medicine and Health Services Research, University of California, Los Angeles, Los Angeles, CA 9009, USA5
| | - Vence L Bonham
- Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD 20892, USA
| | - Wendy K Chung
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY 10032, USA; Department of Medicine, Columbia University Irving Medical Center, New York, NY 10032, USA
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17
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El-Attar EA, Helmy Elkaffas RM, Aglan SA, Naga IS, Nabil A, Abdallah HY. Genomics in Egypt: Current Status and Future Aspects. Front Genet 2022; 13:797465. [PMID: 35664315 PMCID: PMC9157251 DOI: 10.3389/fgene.2022.797465] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 04/04/2022] [Indexed: 11/13/2022] Open
Abstract
Egypt is the third most densely inhabited African country. Due to the economic burden and healthcare costs of overpopulation, genomic and genetic testing is a huge challenge. However, in the era of precision medicine, Egypt is taking a shift in approach from “one-size-fits all” to more personalized healthcare via advancing the practice of medical genetics and genomics across the country. This shift necessitates concrete knowledge of the Egyptian genome and related diseases to direct effective preventive, diagnostic and counseling services of prevalent genetic diseases in Egypt. Understanding disease molecular mechanisms will enhance the capacity for personalized interventions. From this perspective, we highlight research efforts and available services for rare genetic diseases, communicable diseases including the coronavirus 2019 disease (COVID19), and cancer. The current state of genetic services in Egypt including availability and access to genetic services is described. Drivers for applying genomics in Egypt are illustrated with a SWOT analysis of the current genetic/genomic services. Barriers to genetic service development in Egypt, whether economic, geographic, cultural or educational are discussed as well. The sensitive topic of communicating genomic results and its ethical considerations is also tackled. To understand disease pathogenesis, much can be gained through the advancement and integration of genomic technologies via clinical applications and research efforts in Egypt. Three main pillars of multidisciplinary collaboration for advancing genomics in Egypt are envisaged: resources, infrastructure and training. Finally, we highlight the recent national plan to establish a genome center that will aim to prepare a map of the Egyptian human genome to discover and accurately determine the genetic characteristics of various diseases. The Reference Genome Project for Egyptians and Ancient Egyptians will initialize a new genomics era in Egypt. We propose a multidisciplinary governance system in Egypt to support genomic medicine research efforts and integrate into the healthcare system whilst ensuring ethical conduct of data.
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Affiliation(s)
- Eman Ahmed El-Attar
- Chemical Pathology Department, Medical Research Institute, Alexandria University, Alexandria, Egypt
- *Correspondence: Eman Ahmed El-Attar,
| | | | - Sarah Ahmed Aglan
- Chemical Pathology Department, Medical Research Institute, Alexandria University, Alexandria, Egypt
| | - Iman S. Naga
- Department of Microbiology, Medical Research Institute, Alexandria University, Alexandria, Egypt
| | - Amira Nabil
- Department of Human Genetics, Medical Research Institute, Alexandria University, Alexandria, Egypt
| | - Hoda Y. Abdallah
- Medical Genetics Unit, Histology and Cell Biology Department, Faculty of Medicine, Suez Canal University, Ismailia, Egypt
- Center of Excellence in Molecular and Cellular Medicine, Faculty of Medicine, Suez Canal University, Ismailia, Egypt
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18
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Muenzen KD, Amendola LM, Kauffman TL, Mittendorf KF, Bensen JT, Chen F, Green R, Powell BC, Kvale M, Angelo F, Farnan L, Fullerton SM, Robinson JO, Li T, Murali P, Lawlor JM, Ou J, Hindorff LA, Jarvik GP, Crosslin DR. Lessons learned and recommendations for data coordination in collaborative research: The CSER consortium experience. HGG ADVANCES 2022; 3:100120. [PMID: 35707062 PMCID: PMC9190054 DOI: 10.1016/j.xhgg.2022.100120] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 05/16/2022] [Indexed: 11/18/2022] Open
Abstract
Integrating data across heterogeneous research environments is a key challenge in multi-site, collaborative research projects. While it is important to allow for natural variation in data collection protocols across research sites, it is also important to achieve interoperability between datasets in order to reap the full benefits of collaborative work. However, there are few standards to guide the data coordination process from project conception to completion. In this paper, we describe the experiences of the Clinical Sequence Evidence-Generating Research (CSER) consortium Data Coordinating Center (DCC), which coordinated harmonized survey and genomic sequencing data from seven clinical research sites from 2020 to 2022. Using input from multiple consortium working groups and from CSER leadership, we first identify 14 lessons learned from CSER in the categories of communication, harmonization, informatics, compliance, and analytics. We then distill these lessons learned into 11 recommendations for future research consortia in the areas of planning, communication, informatics, and analytics. We recommend that planning and budgeting for data coordination activities occur as early as possible during consortium conceptualization and development to minimize downstream complications. We also find that clear, reciprocal, and continuous communication between consortium stakeholders and the DCC is equally important to maintaining a secure and centralized informatics ecosystem for pooling data. Finally, we discuss the importance of actively interrogating current approaches to data governance, particularly for research studies that straddle the research-clinical divide.
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19
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McCormick JB, Hopkins M, Lehman EB, Green MJ. Mining the Data: Exploring Rural Patients' Attitudes about the Use of Their Personal Information in Research. AJOB Empir Bioeth 2022; 13:89-106. [PMID: 35271430 PMCID: PMC10038193 DOI: 10.1080/23294515.2022.2040644] [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] [Indexed: 10/18/2022]
Abstract
BACKGROUND This study examines rural patients' perceived importance of knowing or being consulted about researchers' access and use of their personal data (identifiable and de-identified health information, and identifiable and de-identified non-health information) across five scenarios. This study also examines their views on stewardship or governance of their personal information by researchers in their healthcare systems. METHODS We conducted a survey by mail. Data were analyzed using descriptive statistics. Multivariable regression analyses were conducted across each scenario and type of personal data with the same variables included in each model. RESULTS The majority of participants said it was "very important/absolutely essential" to know the purpose of the study, to be asked every time, and to know the policies governing researcher access and use of their identifiable health information. Just over two-thirds of respondents thought it "very important/absolutely essential" to know who serves on the data governance committee and to have a community member serve. Distrust in healthcare organizations was positively correlated with the scenarios while willingness to give permission to donate leftover biological specimens was negatively correlated. CONCLUSION Our study findings indicate that the type of personal information being accessed and used generally matters to 1,407 patients living in rural Pennsylvania. We also demonstrate that knowing their healthcare organizations' governance policies and practices for managing their personal data is important to many rural Pennsylvania patients. Biomedical researchers need to recognize and attend to those differences as much as possible in order to expand opportunities for and participation in research by residents of these rural communities. Supplemental data for this article is available online at.
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Affiliation(s)
- Jennifer B McCormick
- Department of Humanities, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Margaret Hopkins
- Department of Humanities, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Erik B Lehman
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Michael J Green
- Department of Humanities, Pennsylvania State University College of Medicine, Hershey, PA, USA
- Department of Medicine, Pennsylvania State University College of Medicine, Hershey, PA, USA
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20
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Abstract
Questions of consent and public interest research loom large.
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Affiliation(s)
- Mahsa Shabani
- Metamedica, Faculty of Law and Criminology, Ghent University, Campus Aula, Ghent, Belgium
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21
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Voisin C, Linden M, Dyke SO, Bowers SR, Alper P, Barkley MP, Bernick D, Chao J, Courtot M, Jeanson F, Konopko MA, Kuba M, Lawson J, Leinonen J, Li S, Ota Wang V, Philippakis AA, Reinold K, Rushton GA, Spalding JD, Törnroos J, Tulchinsky I, Guidry Auvil JM, Nyrönen TH. GA4GH Passport standard for digital identity and access permissions. CELL GENOMICS 2021; 1:None. [PMID: 34820660 PMCID: PMC8591913 DOI: 10.1016/j.xgen.2021.100030] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 07/08/2021] [Accepted: 09/02/2021] [Indexed: 12/21/2022]
Abstract
The Global Alliance for Genomics and Health (GA4GH) supports international standards that enable a federated data sharing model for the research community while respecting data security, ethical and regulatory frameworks, and data authorization and access processes for sensitive data. The GA4GH Passport standard (Passport) defines a machine-readable digital identity that conveys roles and data access permissions (called "visas") for individual users. Visas are issued by data stewards, including data access committees (DACs) working with public databases, the entities responsible for the quality, integrity, and access arrangements for the datasets in the management of human biomedical data. Passports streamline management of data access rights across data systems by using visas that present a data user's digital identity and permissions across organizations, tools, environments, and services. We describe real-world implementations of the GA4GH Passport standard in use cases from ELIXIR Europe, National Institutes of Health, and the Autism Sharing Initiative. These implementations demonstrate that the Passport standard has provided transparent mechanisms for establishing permissions and authorizing data access across platforms.
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Affiliation(s)
- Craig Voisin
- Google LLC, Kitchener, ON N2H 5G5, Canada,Corresponding author
| | - Mikael Linden
- CSC–IT Center for Science, Espoo 02101, Finland,ELIXIR Finland, Espoo 02101, Finland
| | - Stephanie O.M. Dyke
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, QC H3A 2B4, Canada
| | | | - Pinar Alper
- ELIXIR Luxembourg, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4367 Belvaux, Luxembourg
| | | | - David Bernick
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Mélanie Courtot
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire CB10 1SD, UK
| | | | - Melissa A. Konopko
- Wellcome Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, UK,Global Alliance for Genomics and Health, Toronto, ON M5G 0A3, Canada
| | - Martin Kuba
- Masaryk University, Brno 602 00, Czech Republic
| | - Jonathan Lawson
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Stephanie Li
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA,Global Alliance for Genomics and Health, Toronto, ON M5G 0A3, Canada
| | - Vivian Ota Wang
- National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - Kathy Reinold
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - J. Dylan Spalding
- CSC–IT Center for Science, Espoo 02101, Finland,ELIXIR Finland, Espoo 02101, Finland
| | - Juha Törnroos
- CSC–IT Center for Science, Espoo 02101, Finland,ELIXIR Finland, Espoo 02101, Finland
| | | | | | - Tommi H. Nyrönen
- CSC–IT Center for Science, Espoo 02101, Finland,ELIXIR Finland, Espoo 02101, Finland,Corresponding author
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22
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Rehm HL, Page AJ, Smith L, Adams JB, Alterovitz G, Babb LJ, Barkley MP, Baudis M, Beauvais MJ, Beck T, Beckmann JS, Beltran S, Bernick D, Bernier A, Bonfield JK, Boughtwood TF, Bourque G, Bowers SR, Brookes AJ, Brudno M, Brush MH, Bujold D, Burdett T, Buske OJ, Cabili MN, Cameron DL, Carroll RJ, Casas-Silva E, Chakravarty D, Chaudhari BP, Chen SH, Cherry JM, Chung J, Cline M, Clissold HL, Cook-Deegan RM, Courtot M, Cunningham F, Cupak M, Davies RM, Denisko D, Doerr MJ, Dolman LI, Dove ES, Dursi LJ, Dyke SO, Eddy JA, Eilbeck K, Ellrott KP, Fairley S, Fakhro KA, Firth HV, Fitzsimons MS, Fiume M, Flicek P, Fore IM, Freeberg MA, Freimuth RR, Fromont LA, Fuerth J, Gaff CL, Gan W, Ghanaim EM, Glazer D, Green RC, Griffith M, Griffith OL, Grossman RL, Groza T, Guidry Auvil JM, Guigó R, Gupta D, Haendel MA, Hamosh A, Hansen DP, Hart RK, Hartley DM, Haussler D, Hendricks-Sturrup RM, Ho CW, Hobb AE, Hoffman MM, Hofmann OM, Holub P, Hsu JS, Hubaux JP, Hunt SE, Husami A, Jacobsen JO, Jamuar SS, Janes EL, Jeanson F, Jené A, Johns AL, Joly Y, Jones SJ, Kanitz A, Kato K, Keane TM, Kekesi-Lafrance K, Kelleher J, Kerry G, Khor SS, Knoppers BM, Konopko MA, Kosaki K, Kuba M, Lawson J, Leinonen R, Li S, Lin MF, Linden M, Liu X, Liyanage IU, Lopez J, Lucassen AM, Lukowski M, Mann AL, Marshall J, Mattioni M, Metke-Jimenez A, Middleton A, Milne RJ, Molnár-Gábor F, Mulder N, Munoz-Torres MC, Nag R, Nakagawa H, Nasir J, Navarro A, Nelson TH, Niewielska A, Nisselle A, Niu J, Nyrönen TH, O’Connor BD, Oesterle S, Ogishima S, Ota Wang V, Paglione LA, Palumbo E, Parkinson HE, Philippakis AA, Pizarro AD, Prlic A, Rambla J, Rendon A, Rider RA, Robinson PN, Rodarmer KW, Rodriguez LL, Rubin AF, Rueda M, Rushton GA, Ryan RS, Saunders GI, Schuilenburg H, Schwede T, Scollen S, Senf A, Sheffield NC, Skantharajah N, Smith AV, Sofia HJ, Spalding D, Spurdle AB, Stark Z, Stein LD, Suematsu M, Tan P, Tedds JA, Thomson AA, Thorogood A, Tickle TL, Tokunaga K, Törnroos J, Torrents D, Upchurch S, Valencia A, Guimera RV, Vamathevan J, Varma S, Vears DF, Viner C, Voisin C, Wagner AH, Wallace SE, Walsh BP, Williams MS, Winkler EC, Wold BJ, Wood GM, Woolley JP, Yamasaki C, Yates AD, Yung CK, Zass LJ, Zaytseva K, Zhang J, Goodhand P, North K, Birney E. GA4GH: International policies and standards for data sharing across genomic research and healthcare. CELL GENOMICS 2021; 1:100029. [PMID: 35072136 PMCID: PMC8774288 DOI: 10.1016/j.xgen.2021.100029] [Citation(s) in RCA: 75] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.
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Affiliation(s)
- Heidi L. Rehm
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Angela J.H. Page
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Global Alliance for Genomics and Health, Toronto, ON, Canada
| | - Lindsay Smith
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Jeremy B. Adams
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Gil Alterovitz
- Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | | | | | - Michael Baudis
- University of Zurich, Zurich, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Michael J.S. Beauvais
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- McGill University, Montreal, QC, Canada
| | - Tim Beck
- University of Leicester, Leicester, UK
| | | | - Sergi Beltran
- CNAG-CRG, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Universitat de Barcelona, Barcelona, Spain
| | - David Bernick
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | | | - Tiffany F. Boughtwood
- Australian Genomics, Parkville, VIC, Australia
- Murdoch Children’s Research Institute, Parkville, VIC, Australia
| | - Guillaume Bourque
- McGill University, Montreal, QC, Canada
- Canadian Center for Computational Genomics, Montreal, QC, Canada
| | | | | | - Michael Brudno
- Canadian Center for Computational Genomics, Montreal, QC, Canada
- University of Toronto, Toronto, ON, Canada
- University Health Network, Toronto, ON, Canada
- Vector Institute, Toronto, ON, Canada
- Canadian Distributed Infrastructure for Genomics (CanDIG), Toronto, ON, Canada
| | | | - David Bujold
- McGill University, Montreal, QC, Canada
- Canadian Center for Computational Genomics, Montreal, QC, Canada
- Canadian Distributed Infrastructure for Genomics (CanDIG), Toronto, ON, Canada
| | - Tony Burdett
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | | | | | - Daniel L. Cameron
- Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- University of Melbourne, Melbourne, VIC, Australia
| | | | | | | | - Bimal P. Chaudhari
- Nationwide Children’s Hospital, Columbus, OH, USA
- The Ohio State University, Columbus, OH, USA
| | - Shu Hui Chen
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Justina Chung
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Melissa Cline
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
| | | | | | - Mélanie Courtot
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Fiona Cunningham
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | | | | | | | | | | | | | - L. Jonathan Dursi
- University Health Network, Toronto, ON, Canada
- Canadian Distributed Infrastructure for Genomics (CanDIG), Toronto, ON, Canada
| | | | | | | | | | - Susan Fairley
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Khalid A. Fakhro
- Sidra Medicine, Doha, Qatar
- Weill Cornell Medicine - Qatar, Doha, Qatar
| | - Helen V. Firth
- Wellcome Sanger Institute, Hinxton, UK
- Addenbrooke’s Hospital, Cambridge, UK
| | | | | | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Ian M. Fore
- National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Mallory A. Freeberg
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | | | - Lauren A. Fromont
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | | | - Clara L. Gaff
- Australian Genomics, Parkville, VIC, Australia
- Murdoch Children’s Research Institute, Parkville, VIC, Australia
- Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- University of Melbourne, Melbourne, VIC, Australia
| | - Weiniu Gan
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Elena M. Ghanaim
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - David Glazer
- Verily Life Sciences, South San Francisco, CA, USA
| | - Robert C. Green
- Brigham and Women’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Malachi Griffith
- Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Obi L. Griffith
- Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | | | | | | | - Roderic Guigó
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Dipayan Gupta
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | | | - Ada Hamosh
- Johns Hopkins University, Baltimore, MD, USA
| | - David P. Hansen
- Australian Genomics, Parkville, VIC, Australia
- The Australian e-Health Research Centre, CSIRO, Herston, QLD, Australia
| | - Reece K. Hart
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Invitae, San Francisco, CA, USA
- MyOme, Inc, San Bruno, CA, USA
| | | | - David Haussler
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, University of California, Santa Cruz, CA, USA
| | | | | | | | - Michael M. Hoffman
- University of Toronto, Toronto, ON, Canada
- University Health Network, Toronto, ON, Canada
- Vector Institute, Toronto, ON, Canada
| | - Oliver M. Hofmann
- University of Toronto, Toronto, ON, Canada
- University of Melbourne, Melbourne, VIC, Australia
| | - Petr Holub
- BBMRI-ERIC, Graz, Austria
- Masaryk University, Brno, Czech Republic
| | | | | | - Sarah E. Hunt
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Ammar Husami
- Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
| | | | - Saumya S. Jamuar
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Republic of Singapore
- SingHealth Duke-NUS Institute of Precision Medicine, Singapore, Republic of Singapore
| | - Elizabeth L. Janes
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- University of Waterloo, Waterloo, ON, Canada
| | | | - Aina Jené
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Amber L. Johns
- Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Yann Joly
- McGill University, Montreal, QC, Canada
| | - Steven J.M. Jones
- Canada’s Michael Smith Genome Sciences Centre, BC Cancer, Vancouver, BC, Canada
| | - Alexander Kanitz
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University of Basel, Basel, Switzerland
| | | | - Thomas M. Keane
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
- University of Nottingham, Nottingham, UK
| | - Kristina Kekesi-Lafrance
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- McGill University, Montreal, QC, Canada
| | | | - Giselle Kerry
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Seik-Soon Khor
- National Center for Global Health and Medicine Hospital, Tokyo, Japan
- University of Tokyo, Tokyo, Japan
| | | | | | | | | | | | - Rasko Leinonen
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Stephanie Li
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Global Alliance for Genomics and Health, Toronto, ON, Canada
| | | | - Mikael Linden
- CSC–IT Center for Science, Espoo, Finland
- ELIXIR Finland, Espoo, Finland
| | | | - Isuru Udara Liyanage
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | | | | | | | - Alice L. Mann
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- Wellcome Sanger Institute, Hinxton, UK
| | | | | | | | - Anna Middleton
- Wellcome Connecting Science, Hinxton, UK
- University of Cambridge, Cambridge, UK
| | - Richard J. Milne
- Wellcome Connecting Science, Hinxton, UK
- University of Cambridge, Cambridge, UK
| | | | - Nicola Mulder
- H3ABioNet, Computational Biology Division, IDM, Faculty of Health Sciences, Cape Town, South Africa
| | | | - Rishi Nag
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Hidewaki Nakagawa
- Japan Agency for Medical Research & Development (AMED), Tokyo, Japan
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | - Arcadi Navarro
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | | | - Ania Niewielska
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Amy Nisselle
- Murdoch Children’s Research Institute, Parkville, VIC, Australia
- University of Melbourne, Melbourne, VIC, Australia
- Human Genetics Society of Australasia Education, Ethics & Social Issues Committee, Alexandria, NSW, Australia
| | - Jeffrey Niu
- University Health Network, Toronto, ON, Canada
| | - Tommi H. Nyrönen
- CSC–IT Center for Science, Espoo, Finland
- ELIXIR Finland, Espoo, Finland
| | | | - Sabine Oesterle
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | - Vivian Ota Wang
- National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Emilio Palumbo
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Helen E. Parkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | | | | | | | - Jordi Rambla
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | | | - Renee A. Rider
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Peter N. Robinson
- The Jackson Laboratory, Farmington, CT, USA
- University of Connecticut, Farmington, CT, USA
| | - Kurt W. Rodarmer
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | | | - Alan F. Rubin
- Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- University of Melbourne, Melbourne, VIC, Australia
| | - Manuel Rueda
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | | | | | | | - Helen Schuilenburg
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Torsten Schwede
- SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University of Basel, Basel, Switzerland
| | | | | | | | - Neerjah Skantharajah
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | | | - Heidi J. Sofia
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Dylan Spalding
- CSC–IT Center for Science, Espoo, Finland
- ELIXIR Finland, Espoo, Finland
| | | | - Zornitza Stark
- Australian Genomics, Parkville, VIC, Australia
- Murdoch Children’s Research Institute, Parkville, VIC, Australia
- University of Melbourne, Melbourne, VIC, Australia
| | - Lincoln D. Stein
- Ontario Institute for Cancer Research, Toronto, ON, Canada
- University of Toronto, Toronto, ON, Canada
| | | | - Patrick Tan
- SingHealth Duke-NUS Genomic Medicine Centre, Singapore, Republic of Singapore
- Precision Health Research Singapore, Singapore, Republic of Singapore
- Genome Institute of Singapore, Singapore, Republic of Singapore
| | | | - Alastair A. Thomson
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Adrian Thorogood
- McGill University, Montreal, QC, Canada
- University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | | | - Katsushi Tokunaga
- University of Tokyo, Tokyo, Japan
- National Center for Global Health and Medicine, Tokyo, Japan
| | - Juha Törnroos
- CSC–IT Center for Science, Espoo, Finland
- ELIXIR Finland, Espoo, Finland
| | - David Torrents
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
- Barcelona Supercomputing Center, Barcelona, Spain
| | - Sean Upchurch
- California Institute of Technology, Pasadena, CA, USA
| | - Alfonso Valencia
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
- Barcelona Supercomputing Center, Barcelona, Spain
| | | | - Jessica Vamathevan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Susheel Varma
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
- Health Data Research UK, London, UK
| | - Danya F. Vears
- Murdoch Children’s Research Institute, Parkville, VIC, Australia
- University of Melbourne, Melbourne, VIC, Australia
- Human Genetics Society of Australasia Education, Ethics & Social Issues Committee, Alexandria, NSW, Australia
- Melbourne Law School, University of Melbourne, Parkville, VIC, Australia
| | - Coby Viner
- University of Toronto, Toronto, ON, Canada
- University Health Network, Toronto, ON, Canada
| | | | - Alex H. Wagner
- Nationwide Children’s Hospital, Columbus, OH, USA
- The Ohio State University, Columbus, OH, USA
| | | | | | | | - Eva C. Winkler
- Section of Translational Medical Ethics, University Hospital Heidelberg, Heidelberg, Germany
| | | | | | | | | | - Andrew D. Yates
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
| | - Christina K. Yung
- Ontario Institute for Cancer Research, Toronto, ON, Canada
- Indoc Research, Toronto, ON, Canada
| | - Lyndon J. Zass
- H3ABioNet, Computational Biology Division, IDM, Faculty of Health Sciences, Cape Town, South Africa
| | - Ksenia Zaytseva
- McGill University, Montreal, QC, Canada
- Canadian Centre for Computational Genomics, Montreal, QC, Canada
| | - Junjun Zhang
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Peter Goodhand
- Global Alliance for Genomics and Health, Toronto, ON, Canada
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Kathryn North
- Murdoch Children’s Research Institute, Parkville, VIC, Australia
- University of Toronto, Toronto, ON, Canada
- University of Melbourne, Melbourne, VIC, Australia
| | - Ewan Birney
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Hinxton, UK
- European Molecular Biology Laboratory, Heidelberg, Germany
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23
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Amr A, Hinderer M, Griebel L, Deuber D, Egger C, Sedaghat-Hamedani F, Kayvanpour E, Huhn D, Haas J, Frese K, Schweig M, Marnau N, Krämer A, Durand C, Battke F, Prokosch HU, Backes M, Keller A, Schröder D, Katus HA, Frey N, Meder B. Controlling my genome with my smartphone: first clinical experiences of the PROMISE system. Clin Res Cardiol 2021; 111:638-650. [PMID: 34694434 PMCID: PMC9151530 DOI: 10.1007/s00392-021-01942-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 09/13/2021] [Indexed: 12/01/2022]
Abstract
Background The development of Precision Medicine strategies requires high-dimensional phenotypic and genomic data, both of which are highly privacy-sensitive data types. Conventional data management systems lack the capabilities to sufficiently handle the expected large quantities of such sensitive data in a secure manner. PROMISE is a genetic data management concept that implements a highly secure platform for data exchange while preserving patient interests, privacy, and autonomy. Methods The concept of PROMISE to democratize genetic data was developed by an interdisciplinary team. It integrates a sophisticated cryptographic concept that allows only the patient to grant selective access to defined parts of his genetic information with single DNA base-pair resolution cryptography. The PROMISE system was developed for research purposes to evaluate the concept in a pilot study with nineteen cardiomyopathy patients undergoing genotyping, questionnaires, and longitudinal follow-up. Results The safety of genetic data was very important to 79%, and patients generally regarded the data as highly sensitive. More than half the patients reported that their attitude towards the handling of genetic data has changed after using the PROMISE app for 4 months (median). The patients reported higher confidence in data security and willingness to share their data with commercial third parties, including pharmaceutical companies (increase from 5 to 32%). Conclusion PROMISE democratizes genomic data by a transparent, secure, and patient-centric approach. This clinical pilot study evaluating a genetic data infrastructure is unique and shows that patient’s acceptance of data sharing can be increased by patient-centric decision-making. Graphic abstract ![]()
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Affiliation(s)
- Ali Amr
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany.,DZHK (German Centre for Cardiovascular Research), 69120, Heidelberg, Germany
| | - Marc Hinderer
- Chair of Medical Informatics, Friedrich Alexander University Erlangen-Nürnberg, 91058, Erlangen, Germany
| | - Lena Griebel
- Chair of Medical Informatics, Friedrich Alexander University Erlangen-Nürnberg, 91058, Erlangen, Germany
| | - Dominic Deuber
- Chair for Applied Cryptography, Friedrich-Alexander University Erlangen-Nürnberg, 90429, Erlangen, Germany
| | - Christoph Egger
- Chair for Applied Cryptography, Friedrich-Alexander University Erlangen-Nürnberg, 90429, Erlangen, Germany
| | - Farbod Sedaghat-Hamedani
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany.,DZHK (German Centre for Cardiovascular Research), 69120, Heidelberg, Germany
| | - Elham Kayvanpour
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany.,DZHK (German Centre for Cardiovascular Research), 69120, Heidelberg, Germany
| | - Daniel Huhn
- Department of General Internal Medicine and Psychosomatic, University Hospital Heidelberg, 69120, Heidelberg, Germany
| | - Jan Haas
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany.,DZHK (German Centre for Cardiovascular Research), 69120, Heidelberg, Germany
| | - Karen Frese
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany.,DZHK (German Centre for Cardiovascular Research), 69120, Heidelberg, Germany
| | | | - Ninja Marnau
- CISPA Helmholtz Center for Information Security, 66123, Saarbrücken, Germany
| | - Annika Krämer
- Chair for Information Security and Cryptography, Saarland University, 66123, Saarbrücken, Germany
| | - Claudia Durand
- CeGaT GmbH, Center for Genomics and Transcriptomics, 72076, Tübingen, Germany
| | - Florian Battke
- CeGaT GmbH, Center for Genomics and Transcriptomics, 72076, Tübingen, Germany
| | - Hans-Ulrich Prokosch
- Chair of Medical Informatics, Friedrich Alexander University Erlangen-Nürnberg, 91058, Erlangen, Germany
| | - Michael Backes
- CISPA Helmholtz Center for Information Security, 66123, Saarbrücken, Germany.,Chair for Information Security and Cryptography, Saarland University, 66123, Saarbrücken, Germany
| | - Andreas Keller
- Chair for Clinical Bioinformatics, Saarland University, 66123, Saarbrücken, Germany
| | - Dominique Schröder
- Chair for Applied Cryptography, Friedrich-Alexander University Erlangen-Nürnberg, 90429, Erlangen, Germany
| | - Hugo A Katus
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany.,DZHK (German Centre for Cardiovascular Research), 69120, Heidelberg, Germany
| | - Norbert Frey
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany.,DZHK (German Centre for Cardiovascular Research), 69120, Heidelberg, Germany
| | - Benjamin Meder
- Institute for Cardiomyopathies, Department of Medicine III, University of Heidelberg, Im Neuenheimer Feld 410, 69120, Heidelberg, Germany. .,DZHK (German Centre for Cardiovascular Research), 69120, Heidelberg, Germany. .,Stanford Genome Technology Center, Stanford University School of Medicine, Palo Alto, CA, 94305, USA.
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24
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Arshad S, Arshad J, Khan MM, Parkinson S. Analysis of security and privacy challenges for DNA-genomics applications and databases. J Biomed Inform 2021; 119:103815. [PMID: 34022422 DOI: 10.1016/j.jbi.2021.103815] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 05/07/2021] [Accepted: 05/08/2021] [Indexed: 02/06/2023]
Abstract
DNA technology is rapidly moving towards digitization. Scientists use software tools and applications for sequencing, synthesizing, analyzing and sharing of DNA and genomic data, operate lab equipment and store genetic information in shared datastores. Using cutting-edge computing methods and techniques, researchers have decoded human genome, created organisms with new capabilities, automated drug development and transformed food safety. Such software applications are typically developed to progress scientific understanding and as such cyber security is never a concern for these applications. However, with the increasing commercialisation of DNA technologies, coupled with the sensitivity of DNA data, there is a need to adopt a security-by-design approach. In this paper we investigate bio-cyber security threats to genomic-DNA data and software applications making use of such data to advance scientific research. Specifically, we adopt an empirical approach to analyse and identify vulnerabilities within genomic-DNA databases and bioinformatics software applications that can lead to cyber-attacks affecting the confidentiality, integrity and availability of such sensitive data. We present a detailed analysis of these threats and highlight potential protection mechanisms to help researchers pursue these research directions.
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Affiliation(s)
- Saadia Arshad
- Department of Computer Science & IT, NED University of Engineering and Technology, Karachi, Pakistan
| | - Junaid Arshad
- School of Computing and Digital Technology, Birmingham City University, Birmingham, UK.
| | - Muhammad Mubashir Khan
- Department of Computer Science & IT, NED University of Engineering and Technology, Karachi, Pakistan
| | - Simon Parkinson
- Department of Computer Science, University of Huddersfield, Huddersfield, UK
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25
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Constraints in Clinical Cardiology and Personalized Medicine: Interrelated Concepts in Clinical Cardiology. CARDIOGENETICS 2021. [DOI: 10.3390/cardiogenetics11020007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Systems biology is established as an integrative computational analysis methodology with practical and theoretical applications in clinical cardiology. The integration of genetic and molecular components of a disease produces interacting networks, modules and phenotypes with clinical applications in complex cardiovascular entities. With the holistic principle of systems biology, some of the features of complexity and natural progression of cardiac diseases are approached and explained. Two important interrelated holistic concepts of systems biology are described; the emerging field of personalized medicine and the constraint-based thinking with downward causation. Constraints in cardiovascular diseases embrace three scientific fields related to clinical cardiology: biological and medical constraints; constraints due to limitations of current technology; and constraints of general resources for better medical coverage. Systems healthcare and personalized medicine are connected to the related scientific fields of: ethics and legal status; data integration; taxonomic revisions; policy decisions; and organization of human genomic data.
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