Adding dynamic consent to a longitudinal cohort study: A qualitative study of EXCEED participant perspectives.

BACKGROUND: Dynamic consent has been proposed as a process through which participants and patients can gain more control over how their data and samples, donated for biomedical research, are used, resulting in greater trust in researchers. It is also a way to respond to evolving data protection frameworks and new legislation. Others argue that the broad consent currently used in biobank research is ethically robust. Little empirical research with cohort study participants has been published. This research investigated the participants' opinions of adding a dynamic consent interface to their existing study. METHODS: Adult participants in the Extended Cohort for E-health, Environment and DNA (EXCEED) longitudinal cohort study who are members of the EXCEED Public and Participant Engagement Group were recruited. Four focus groups were conducted and analysed for thematic content. Discussion topics were derived from a review of the current literature on dynamic consent. RESULTS: Participants were in favour of many aspects of a dynamic consent interface, such as being able to update their information, add additional data to their records and choose withdrawal options. They were supportive provided it was simple to use and not intrusive. Participants expressed a markedly high level of trust in the study and its investigators and were unanimously happy with their current participation. No strong support was found for adding a dynamic consent interface to EXCEED. CONCLUSIONS: Trust in the study researchers was the strongest theme found. Openness and good data security were needed to retain their trust. While happy to discuss dynamic consent, participants were satisfied with the current study arrangements. There were indications that changing the study might unnecessarily disturb their trust. This raised the question of whether there are contexts where dynamic consent is more appropriate than others. This study was limited by the small number of participants who were committed to the study and biased towards it. More research is needed to fully understand the potential impact of adding a dynamic consent interface to an existing cohort study.

Data Safe Havens in health research and healthcare.

MOTIVATION: The data that put the 'evidence' into 'evidence-based medicine' are central to developments in public health, primary and hospital care. A fundamental challenge is to site such data in repositories that can easily be accessed under appropriate technical and governance controls which are effectively audited and are viewed as trustworthy by diverse stakeholders. This demands socio-technical solutions that may easily become enmeshed in protracted debate and controversy as they encounter the norms, values, expectations and concerns of diverse stakeholders. In this context, the development of what are called 'Data Safe Havens' has been crucial. Unfortunately, the origins and evolution of the term have led to a range of different definitions being assumed by different groups. There is, however, an intuitively meaningful interpretation that is often assumed by those who have not previously encountered the term: a repository in which useful but potentially sensitive data may be kept securely under governance and informatics systems that are fit-for-purpose and appropriately tailored to the nature of the data being maintained, and may be accessed and utilized by legitimate users undertaking work and research contributing to biomedicine, health and/or to ongoing development of healthcare systems. RESULTS: This review explores a fundamental question: 'what are the specific criteria that ought reasonably to be met by a data repository if it is to be seen as consistent with this interpretation and viewed as worthy of being accorded the status of 'Data Safe Haven' by key stakeholders'? We propose 12 such criteria. CONTACT: paul.burton@bristol.ac.uk.

Respecting Autonomy Over Time: Policy and Empirical Evidence on Re-Consent in Longitudinal Biomedical Research.

Re-consent in research, the asking for a new consent if there is a change in protocol or to confirm the expectations of participants in case of change, is an under-explored issue. There is little clarity as to what changes should trigger re-consent and what impact a re-consent exercise has on participants and the research project. This article examines applicable policy statements and literature for the prevailing arguments for and against re-consent in relation to longitudinal cohort studies, tissue banks and biobanks. Examples of re-consent exercises are presented, triggers and non-triggers for re-consent discussed and the conflicting attitudes of commentators, participants and researchers highlighted. We acknowledge current practice and argue for a greater emphasis on 'responsive autonomy,' that goes beyond a one-time consent and encourages greater communication between the parties involved. A balance is needed between respecting participants' wishes on how they want their data and samples used and enabling effective research to proceed.

"I don't mind damaging my own body" a qualitative study of the factors that motivate smokers to quit.

BACKGROUND: Although smoking prevalence in England has declined, one in five adults smoke. Smokers are at increased risk of a number of diseases, including COPD which affects an estimated 1.5 million people in England alone. This study aimed to explore issues relating to smoking behaviour and intention to quit that might be used to inform the development of cessation interventions. Issues explored included knowledge of smoking related disease, with a particular emphasis on Chronic Obstructive Pulmonary Disease (COPD). Understanding around risk of disease, including genetic risk was explored, as were features of appropriate and accessible cessation materials and support. METHODS: Semi-structured interviews and focus groups were conducted with a total of 30 individuals of which 17 were smoking cessation clients and 13 were professionals working within health care settings relevant to supporting smokers to quit. A largely purposive approach was taken to sampling, and data were analysed using the constant comparative method. RESULTS: Knowledge of the smoking related disease COPD was limited. Smokers' concerns around risk of disease were influenced by their social context and were more focussed on how their smoking might impact on the health of their family and friends, rather than how it might impact on them as individuals. Participants felt the provision of genetic risk information may have a limited impact on motivation to quit. Genetic risk was considered to be a difficult concept to understand, particularly as increased risk does not mean an individual will definitely develop disease. In terms of cessation approaches, the use of visual media was consistently supported, as was the use of materials that linked directly with life experiences. Images of children inhaling second hand smoke for example, had a particular impact. CONCLUSIONS: Public health messages around the risks of smoking and approaches to quitting should continue to have an emphasis on the dangers that an individual's smoking has on the lives of the people around them. More work also needs to be done to raise awareness around both the risk of COPD in smokers and the impact this disease has on quality of life and life expectancy.

Family tree and ancestry inference: is there a need for a 'generational' consent?

BACKGROUND: Genealogical research and ancestry testing are popular recreational activities but little is known about the impact of the use of these services on clients' biological and social families. Ancestry databases are being enriched with self-reported data and data from deoxyribonucleic acid (DNA) analyses, but also are being linked to other direct-to-consumer genetic testing and research databases. As both family history data and DNA can provide information on more than just the individual, we asked whether companies, as a part of the consent process, were informing clients, and through them clients' relatives, of the potential implications of the use and linkage of their personal data. METHODS: We used content analysis to analyse publically-available consent and informational materials provided to potential clients of ancestry and direct-to-consumer genetic testing companies to determine what consent is required, what risks associated with participation were highlighted, and whether the consent or notification of third parties was suggested or required. RESULTS: We identified four categories of companies providing: 1) services based only on self-reported data, such as personal or family history; 2) services based only on DNA provided by the client; 3) services using both; and 4) services using both that also have a research component. The amount of information provided on the potential issues varied significantly across the categories of companies. 'Traditional' ancestry companies showed the greatest awareness of the implications for family members, while companies only asking for DNA focused solely on the client. While in some cases companies included text recommending clients inform their relatives, showing they recognised the issues, often it was located within lengthy terms and conditions or privacy statements that may not be read by potential clients. CONCLUSIONS: We recommend that companies should make it clearer that clients should inform third parties about their plans to participate, that third parties' data will be provided to companies, and that that data will be linked to other databases, thus raising privacy and issues on use of data. We also suggest investigating whether a 'generational consent' should be created that would include more than just the individual in decisions about participating in genetic investigations.

Returning findings within longitudinal cohort studies: the 1958 birth cohort as an exemplar.

Population-based, prospective longitudinal cohort studies are considering the issues surrounding returning findings to individuals as a result of genomic and other medical research studies. While guidance is being developed for clinical settings, the process is less clear for those conducting longitudinal research. This paper discusses work conducted on behalf of The UK Cohort and Longitudinal Study Enhancement Resource programme (CLOSER) to examine consent requirements, process considerations and specific examples of potential findings in the context of the 1958 British Birth cohort. Beyond deciding which findings to return, there are questions of whether re-consent is needed and the possible impact on the study, how the feedback process will be managed, and what resources are needed to support that process. Recommendations are made for actions a cohort study should consider taking when making vital decisions regarding returning findings. Any decisions need to be context-specific, arrived at transparently, communicated clearly, and in the best interests of both the participants and the study.

Genome-wide association study of thyroid-stimulating hormone highlights new genes, pathways and associations with thyroid disease.

Thyroid hormones play a critical role in regulation of multiple physiological functions and thyroid dysfunction is associated with substantial morbidity. Here, we use electronic health records to undertake a genome-wide association study of thyroid-stimulating hormone (TSH) levels, with a total sample size of 247,107. We identify 158 novel genetic associations, more than doubling the number of known associations with TSH, and implicate 112 putative causal genes, of which 76 are not previously implicated. A polygenic score for TSH is associated with TSH levels in African, South Asian, East Asian, Middle Eastern and admixed American ancestries, and associated with hypothyroidism and other thyroid disease in South Asians. In Europeans, the TSH polygenic score is associated with thyroid disease, including thyroid cancer and age-of-onset of hypothyroidism and hyperthyroidism. We develop pathway-specific genetic risk scores for TSH levels and use these in phenome-wide association studies to identify potential consequences of pathway perturbation. Together, these findings demonstrate the potential utility of genetic associations to inform future therapeutics and risk prediction for thyroid diseases.

Population biobanks and returning individual research results: mission impossible or new directions?

Historically, large-scale longitudinal genomic research studies have not returned individual research results to their participants, as these studies are not intended to find clinically significant information for individuals, but to produce 'generalisable' knowledge for future research. However, this stance is now changing. Commentators now argue that there is an ethical imperative to return clinically significant results and individuals are now expressing a desire to have them. This shift reflects societal changes, such as the rise of social networking and an increased desire to participate in medical decision-making, as well as a greater awareness of genetic information and the increasing ability of clinicians to use this information in health care treatment. This paper will discuss the changes that have prompted genomic research studies to reconsider their position and presents examples of projects that are actively engaged in returning individual research results.

How Can We Not Waste Legacy Genomic Research Data?

Enabling genomic and biomedical data to be shared for secondary research purposes is not always straightforward for existing "legacy" data sets. Researchers may not know whether their data meet ethical and regulatory requirements for sharing. As a result, these data, collected using public funds and the good will and efforts of the donors and investigators, may not be used beyond their original purpose. Single-use plastics are now being banned in many countries; single-use research should be avoided if possible. This paper describes a filter developed through the driver projects of the Global Alliance for Genomics and Health that can be used by researchers to help them determine the extent of sharing possible for their legacy data and actions to be taken to enable further sharing.

Potential for diagnosis of infectious disease from the 100,000 Genomes Project Metagenomic Dataset: Recommendations for reporting results.

The identification of microbiological infection is usually a diagnostic investigation, a complex process that is firstly initiated by clinical suspicion. With the emergence of high-throughput sequencing (HTS) technologies, metagenomic analysis has unveiled the power to identify microbial DNA/RNA from a diverse range of clinical samples (1). Metagenomic analysis of whole human genomes at the clinical/research interface bypasses the steps of clinical scrutiny and targeted testing and has the potential to generate unexpected findings relating to infectious and sometimes transmissible disease. There is no doubt that microbial findings that may have a significant impact on a patient's treatment and their close contacts should be reported to those with clinical responsibility for the sample-donating patient. There are no clear recommendations on how such findings that are incidental, or outside the original investigation, should be handled. Here we aim to provide an informed protocol for the management of incidental microbial findings as part of the 100,000 Genomes Project which may have broader application in this emerging field. As with any other clinical information, we aim to prioritise the reporting of data that are most likely to be of benefit to the patient and their close contacts. We also set out to minimize risks, costs and potential anxiety associated with the reporting of results that are unlikely to be of clinical significance. Our recommendations aim to support the practice of microbial metagenomics by providing a simplified pathway that can be applied to reporting the identification of potential pathogens from metagenomic datasets. Given that the ambition for UK sequenced human genomes over the next 5 years has been set to reach 5 million and the field of metagenomics is rapidly evolving, the guidance will be regularly reviewed and will likely adapt over time as experience develops.

What Does Anonymization Mean? DataSHIELD and the Need for Consensus on Anonymization Terminology.

Anonymization is a recognized process by which identifiers can be removed from identifiable data to protect an individual's confidentiality and is used as a standard practice when sharing data in biomedical research. However, a plethora of terms, such as coding, pseudonymization, unlinked, and deidentified, have been and continue to be used, leading to confusion and uncertainty. This article shows that this is a historic problem and argues that such continuing uncertainty regarding the levels of protection given to data risks damaging initiatives designed to assist researchers conducting cross-national studies and sharing data internationally. DataSHIELD and the creation of a legal template are used as examples of initiatives that rely on anonymization, but where the inconsistency in terminology could hinder progress. More broadly, this article argues that there is a real possibility that there could be possible damage to the public's trust in research and the institutions that carry it out by relying on vague notions of the anonymization process. Research participants whose lack of clear understanding of the research process is compensated for by trusting those carrying out the research may have that trust damaged if the level of protection given to their data does not match their expectations. One step toward ensuring understanding between parties would be consistent use of clearly defined terminology used internationally, so that all those involved are clear on the level of identifiability of any particular set of data and, therefore, how that data can be accessed and shared.

Compare and contrast: a cross-national study across UK, USA and Greek experts regarding return of incidental findings from clinical sequencing.

Return of incidental findings (IFs) from clinical sequencing has become a hotly debated topic over the past year. Efforts are being made by several bodies to provide guidance at both national and international levels; however, no studies comparing attitudes of experts across different countries have been published so far. Our goal was to investigate attitudes towards return of IFs from clinical sequencing across UK, USA and Greek experts. Thirty in-depth interviews were conducted with genetics and genomic experts with different backgrounds. Our study revealed more differences when experts were compared according to their professional background than their country. General principles guiding the decision-making and the feedback process were common across all experts but the details of integrating these tests might vary as different professionals reported different needs and attitudes.

A decision tool to guide the ethics review of a challenging breed of emerging genomic projects.

Recent projects conducted by the International Cancer Genome Consortium (ICGC) have raised the important issue of distinguishing quality assurance (QA) activities from research in the context of genomics. Research was historically defined as a systematic effort to expand a shared body of knowledge, whereas QA was defined as an effort to ascertain whether a specific project met desired standards. However, the two categories increasingly overlap due to advances in bioinformatics and the shift toward open science. As few ethics review policies take these changes into account, it is often difficult to determine the appropriate level of review. Mislabeling can result in unnecessary burdens for the investigators or, conversely, in underestimation of the risks to participants. Therefore, it is important to develop a consistent method of selecting the review process for genomics and bioinformatics projects. This paper begins by discussing two case studies from the ICGC, followed by a literature review on the distinction between QA and research and a comparative analysis of ethics review policies from Canada, the United States, the United Kingdom, and Australia. These results are synthesized into a novel two-step decision tool for researchers and policymakers, which uses traditional criteria to sort clearly defined activities while requiring the use of actual risk levels to decide more complex cases.

Protecting personal data in epidemiological research: DataSHIELD and UK law.

BACKGROUND: Data from individual collections, such as biobanks and cohort studies, are now being shared in order to create combined datasets which can be queried to ask complex scientific questions. But this sharing must be done with due regard for data protection principles. DataSHIELD is a new technology that queries nonaggregated, individual-level data in situ but returns query data in an anonymous format. This raises questions of the ability of DataSHIELD to adequately protect participant confidentiality. METHODS: An ethico-legal analysis was conducted that examined each step of the DataSHIELD process from the perspective of UK case law, regulations, and guidance. RESULTS: DataSHIELD reaches agreed UK standards of protection for the sharing of biomedical data. All direct processing of personal data is conducted within the protected environment of the contributing study; participating studies have scientific, ethics, and data access approvals in place prior to the analysis; studies are clear that their consents conform with this use of data, and participants are informed that anonymisation for further disclosure will take place. CONCLUSION: DataSHIELD can provide a flexible means of interrogating data while protecting the participants' confidentiality in accordance with applicable legislation and guidance.

DataSHIELD: taking the analysis to the data, not the data to the analysis.

BACKGROUND: Research in modern biomedicine and social science requires sample sizes so large that they can often only be achieved through a pooled co-analysis of data from several studies. But the pooling of information from individuals in a central database that may be queried by researchers raises important ethico-legal questions and can be controversial. In the UK this has been highlighted by recent debate and controversy relating to the UK's proposed 'care.data' initiative, and these issues reflect important societal and professional concerns about privacy, confidentiality and intellectual property. DataSHIELD provides a novel technological solution that can circumvent some of the most basic challenges in facilitating the access of researchers and other healthcare professionals to individual-level data. METHODS: Commands are sent from a central analysis computer (AC) to several data computers (DCs) storing the data to be co-analysed. The data sets are analysed simultaneously but in parallel. The separate parallelized analyses are linked by non-disclosive summary statistics and commands transmitted back and forth between the DCs and the AC. This paper describes the technical implementation of DataSHIELD using a modified R statistical environment linked to an Opal database deployed behind the computer firewall of each DC. Analysis is controlled through a standard R environment at the AC. RESULTS: Based on this Opal/R implementation, DataSHIELD is currently used by the Healthy Obese Project and the Environmental Core Project (BioSHaRE-EU) for the federated analysis of 10 data sets across eight European countries, and this illustrates the opportunities and challenges presented by the DataSHIELD approach. CONCLUSIONS: DataSHIELD facilitates important research in settings where: (i) a co-analysis of individual-level data from several studies is scientifically necessary but governance restrictions prohibit the release or sharing of some of the required data, and/or render data access unacceptably slow; (ii) a research group (e.g. in a developing nation) is particularly vulnerable to loss of intellectual property-the researchers want to fully share the information held in their data with national and international collaborators, but do not wish to hand over the physical data themselves; and (iii) a data set is to be included in an individual-level co-analysis but the physical size of the data precludes direct transfer to a new site for analysis.

Legal aspects of genetic databases for international biomedical research: the example of the International Cancer Genome Consortium (ICGC).

There is a noticeable lack of international regulation on personal data exchange and management in research. This article sheds light in this area by describing how the International Cancer Genome Consortium is developing policies and procedures to address the ethical and legal issues raised by the international transfer of data and results. These policies and procedures aim, first and most importantly, to safeguard the interests of the research participants and other involved stakeholders and, secondly, to facilitate the sharing of data and results to realize greater benefits from this kind of internationally collaborative genetic research.

The needle in the haystack: international consortia and the return of individual research results.

Returning individual results to participants in research studies is gaining acceptance and policy guidance is now available for investigators to develop a plan for returning results at the local level. However, returning results discovered through the work of an international scientific research consortium presents additional ethical and procedural difficulties. No general guidance is available for international consortia that wish to consider this issue, but there are examples of internal policies that are being used by consortia such as the International Cancer Genome Consortium (ICGC) and the Type 1 Diabetes Genetics Consortium (T1DGC). This paper presents the policy stance these studies have adopted regarding returning individual research results and their reasons behind it, and gives specific examples from their policy documents and project consent materials. Finally, it suggests an oversight mechanism these and other international consortia can use to ensure that this important issue is addressed appropriately.

DataSHIELD: resolving a conflict in contemporary bioscience--performing a pooled analysis of individual-level data without sharing the data.

BACKGROUND: Contemporary bioscience sometimes demands vast sample sizes and there is often then no choice but to synthesize data across several studies and to undertake an appropriate pooled analysis. This same need is also faced in health-services and socio-economic research. When a pooled analysis is required, analytic efficiency and flexibility are often best served by combining the individual-level data from all sources and analysing them as a single large data set. But ethico-legal constraints, including the wording of consent forms and privacy legislation, often prohibit or discourage the sharing of individual-level data, particularly across national or other jurisdictional boundaries. This leads to a fundamental conflict in competing public goods: individual-level analysis is desirable from a scientific perspective, but is prevented by ethico-legal considerations that are entirely valid. METHODS: Data aggregation through anonymous summary-statistics from harmonized individual-level databases (DataSHIELD), provides a simple approach to analysing pooled data that circumvents this conflict. This is achieved via parallelized analysis and modern distributed computing and, in one key setting, takes advantage of the properties of the updating algorithm for generalized linear models (GLMs). RESULTS: The conceptual use of DataSHIELD is illustrated in two different settings. CONCLUSIONS: As the study of the aetiological architecture of chronic diseases advances to encompass more complex causal pathways-e.g. to include the joint effects of genes, lifestyle and environment-sample size requirements will increase further and the analysis of pooled individual-level data will become ever more important. An aim of this conceptual article is to encourage others to address the challenges and opportunities that DataSHIELD presents, and to explore potential extensions, for example to its use when different data sources hold different data on the same individuals.