48 research outputs found
Sociotechnical Safeguards for Genomic Data Privacy
Recent developments in a variety of sectors, including health care, research and the direct-to-consumer industry, have led to a dramatic increase in the amount of genomic data that are collected, used and shared. This state of affairs raises new and challenging concerns for personal privacy, both legally and technically. This Review appraises existing and emerging threats to genomic data privacy and discusses how well current legal frameworks and technical safeguards mitigate these concerns. It concludes with a discussion of remaining and emerging challenges and illustrates possible solutions that can balance protecting privacy and realizing the benefits that result from the sharing of genetic information
Open sharing of genomic data: Who does it and why?
We explored the characteristics and motivations of people who, having obtained their genetic or genomic data from Direct-To-Consumer genetic testing (DTC-GT) companies, voluntarily decide to share them on the publicly accessible web platform openSNP. The study is the first attempt to describe open data sharing activities undertaken by individuals without institutional oversight. In the paper we provide a detailed overview of the distribution of the demographic characteristics and motivations of people engaged in genetic or genomic open data sharing. The geographical distribution of the respondents showed the USA as dominant. There was no significant gender divide, the age distribution was broad, educational background varied and respondents with and without children were equally represented. Health, even though prominent, was not the respondents' primary or only motivation to be tested. As to their motivations to openly share their data, 86.05% indicated wanting to learn about themselves as relevant, followed by contributing to the advancement of medical research (80.30%), improving the predictability of genetic testing (76.02%) and considering it fun to explore genotype and phenotype data (75.51%). Whereas most respondents were well aware of the privacy risks of their involvement in open genetic data sharing and considered the possibility of direct, personal repercussions troubling, they estimated the risk of this happening to be negligible. Our findings highlight the diversity of DTC-GT consumers who decide to openly share their data. Instead of focusing exclusively on health-related aspects of genetic testing and data sharing, our study emphasizes the importance of taking into account benefits and risks that stretch beyond the health spectrum. Our results thus lend further support to the call for a broader and multi-faceted conceptualization of genomic utility
Digital Phenotyping and Sensitive Health Data: Implications for Data Governance
Mobile and wearable devices, such as smartwatches and fitness trackers, increasingly enable
the continuous collection of physiological and behavioural data that permit inferences about
users’ physical and mental health. Growing consumer adoption of these technologies has
reduced the cost of generating clinically meaningful data. This can help reduce medical
research costs and aid large-scale studies. However, the collection, processing, and storage of
data comes with significant ethical, security, and data governance considerations. A complex
ecosystem is developing, with the need for collaboration among researchers, healthcare
providers, and a broad range of entities across public and private sectors, some of which are
not traditionally associated with healthcare. This has raised important questions in the literature
regarding the role of the individual as a patient, customer, research participant, researcher, and
user when consenting to data processing in this ecosystem. Here, we use the emerging
concept of “digital phenotyping” to highlight key lessons for data governance which draw
on parallels with the history of genomics research, while highlighting areas where digital
phenotyping will require novel governance frameworks.I.P.P. work is supported by GlaxoSmithKline and EPSRC through an iCase fellowship
(17100053); D.S. work is supported by the Embiricos Trust Scholarship of Jesus College
Cambridge, and EPSRC through Grant DTP (EP/N509620/1); J.C. is the recipient of a doctoral
scholarship from The Alan Turing Institute and J.M. is supported by the Wellcome Trust
Privacy in the Genomic Era
Genome sequencing technology has advanced at a rapid pace and it is now
possible to generate highly-detailed genotypes inexpensively. The collection
and analysis of such data has the potential to support various applications,
including personalized medical services. While the benefits of the genomics
revolution are trumpeted by the biomedical community, the increased
availability of such data has major implications for personal privacy; notably
because the genome has certain essential features, which include (but are not
limited to) (i) an association with traits and certain diseases, (ii)
identification capability (e.g., forensics), and (iii) revelation of family
relationships. Moreover, direct-to-consumer DNA testing increases the
likelihood that genome data will be made available in less regulated
environments, such as the Internet and for-profit companies. The problem of
genome data privacy thus resides at the crossroads of computer science,
medicine, and public policy. While the computer scientists have addressed data
privacy for various data types, there has been less attention dedicated to
genomic data. Thus, the goal of this paper is to provide a systematization of
knowledge for the computer science community. In doing so, we address some of
the (sometimes erroneous) beliefs of this field and we report on a survey we
conducted about genome data privacy with biomedical specialists. Then, after
characterizing the genome privacy problem, we review the state-of-the-art
regarding privacy attacks on genomic data and strategies for mitigating such
attacks, as well as contextualizing these attacks from the perspective of
medicine and public policy. This paper concludes with an enumeration of the
challenges for genome data privacy and presents a framework to systematize the
analysis of threats and the design of countermeasures as the field moves
forward
DyPS: Dynamic, Private and Secure GWAS (Summary)
International audienceGenome-Wide Association Studies (GWAS) identify the genomic variations that are statistically associated with a particular phenotype (e.g., a disease). GWAS results, i.e., statistics, benefit research and personalized medicine. The confidence in GWAS increases with the number of genomes analyzed, which encourages federated computations where biocenters periodically include newly sequenced genomes. However, for legal and economical reasons, this collaboration can only happen if a release of GWAS results never jeopardizes the genomic privacy of data donors, if biocenters retain ownership and cannot learn each others' data. Therefore, two challenges need to be simultaneously addressed to enable federated GWAS: (i) the computation of GWAS statistics must rely on secure and privacy-preserving methods; and (ii) GWAS results that are publicly released should not allow any form of privacy attack. In this talk, we will introduce the problem we consider in more details and present DyPS [1], the framework we have designed and recently presented at the Privacy Enhancing Technologies Symposium (PETS). We refer the reader to the full paper 1 for the details we cannot cover in this short version
Blockchain for Genomics:A Systematic Literature Review
Human genomic data carry unique information about an individual and offer
unprecedented opportunities for healthcare. The clinical interpretations
derived from large genomic datasets can greatly improve healthcare and pave the
way for personalized medicine. Sharing genomic datasets, however, pose major
challenges, as genomic data is different from traditional medical data,
indirectly revealing information about descendants and relatives of the data
owner and carrying valid information even after the owner passes away.
Therefore, stringent data ownership and control measures are required when
dealing with genomic data. In order to provide secure and accountable
infrastructure, blockchain technologies offer a promising alternative to
traditional distributed systems. Indeed, the research on blockchain-based
infrastructures tailored to genomics is on the rise. However, there is a lack
of a comprehensive literature review that summarizes the current
state-of-the-art methods in the applications of blockchain in genomics. In this
paper, we systematically look at the existing work both commercial and
academic, and discuss the major opportunities and challenges. Our study is
driven by five research questions that we aim to answer in our review. We also
present our projections of future research directions which we hope the
researchers interested in the area can benefit from
Blockchain for Genomics:A Systematic Literature Review
Human genomic data carry unique information about an individual and offer
unprecedented opportunities for healthcare. The clinical interpretations
derived from large genomic datasets can greatly improve healthcare and pave the
way for personalized medicine. Sharing genomic datasets, however, pose major
challenges, as genomic data is different from traditional medical data,
indirectly revealing information about descendants and relatives of the data
owner and carrying valid information even after the owner passes away.
Therefore, stringent data ownership and control measures are required when
dealing with genomic data. In order to provide secure and accountable
infrastructure, blockchain technologies offer a promising alternative to
traditional distributed systems. Indeed, the research on blockchain-based
infrastructures tailored to genomics is on the rise. However, there is a lack
of a comprehensive literature review that summarizes the current
state-of-the-art methods in the applications of blockchain in genomics. In this
paper, we systematically look at the existing work both commercial and
academic, and discuss the major opportunities and challenges. Our study is
driven by five research questions that we aim to answer in our review. We also
present our projections of future research directions which we hope the
researchers interested in the area can benefit from
Forensic DNA phenotyping: Developing a model privacy impact assessment
© 2018 Elsevier B.V. Forensic scientists around the world are adopting new technology platforms capable of efficiently analysing a larger proportion of the human genome. Undertaking this analysis could provide significant operational benefits, particularly in giving investigators more information about the donor of genetic material, a particularly useful investigative lead. Such information could include predicting externally visible characteristics such as eye and hair colour, as well as biogeographical ancestry. This article looks at the adoption of this new technology from a privacy perspective, using this to inform and critique the application of a Privacy Impact Assessment to this emerging technology. Noting the benefits and limitations, the article develops a number of themes that would influence a model Privacy Impact Assessment as a contextual framework for forensic laboratories and law enforcement agencies considering implementing forensic DNA phenotyping for operational use