The need to redefine genomic data sharing: A focus on data accessibility

A Blockchain-Based Dynamic Consent Architecture to Support Clinical Genomic Data Sharing (ConsentChain): Proof-of-Concept Study

Background

In clinical genomics, sharing of rare genetic disease information between genetic databases and laboratories is essential to determine the pathogenic significance of variants to enable the diagnosis of rare genetic diseases. Significant concerns regarding data governance and security have reduced this sharing in practice. Blockchain could provide a secure method for sharing genomic data between involved parties and thus help overcome some of these issues.

Objective

This study aims to contribute to the growing knowledge of the potential role of blockchain technology in supporting the sharing of clinical genomic data by describing blockchain-based dynamic consent architecture to support clinical genomic data sharing and provide a proof-of-concept implementation, called ConsentChain, for the architecture to explore its performance.

Methods

The ConsentChain requirements were captured from a patient forum to identify security and consent concerns. The ConsentChain was developed on the Ethereum platform, in which smart contracts were used to model the actions of patients, who may provide or withdraw consent to share their data; the data creator, who collects and stores patient data; and the data requester, who needs to query and access the patient data. A detailed analysis was undertaken of the ConsentChain performance as a function of the number of transactions processed by the system.

Results

We describe ConsentChain, a blockchain-based system that provides a web portal interface to support clinical genomic sharing. ConsentChain allows patients to grant or withdraw data requester access and allows data requesters to query and submit access to data stored in a secure off-chain database. We also developed an ontology model to represent patient consent elements into machine-readable codes to automate the consent and data access processes.

Conclusions

Blockchains and smart contracts can provide an efficient and scalable mechanism to support dynamic consent functionality and address some of the barriers that inhibit genomic data sharing. However, they are not a complete answer, and a number of issues still need to be addressed before such systems can be deployed in practice, particularly in relation to verifying user credentials.

Controlling my genome with my smartphone: first clinical experiences of the PROMISE system

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

Non-coding RNAs in endometriosis: a narrative review

BACKGROUND

Endometriosis is a benign gynaecological disorder, which affects 10% of reproductive-aged women and is characterized by endometrial cells from the lining of the uterus being found outside the uterine cavity. However, the pathophysiological mechanisms causing the development of this heterogeneous disease remain enigmatic, and a lack of effective biomarkers necessitates surgical intervention for diagnosis. There is international recognition that accurate non-invasive diagnostic tests and more effective therapies are urgently needed. Non-coding RNA (ncRNA) molecules, which are important regulators of cellular function, have been implicated in many chronic conditions. In endometriosis, transcriptome profiling of tissue samples and functional in vivo and in vitro studies demonstrate that ncRNAs are key contributors to the disease process.

OBJECTIVE AND RATIONALE

In this review, we outline the biogenesis of various ncRNAs relevant to endometriosis and then summarize the evidence indicating their roles in regulatory pathways that govern disease establishment and progression.

SEARCH METHODS

Articles from 2000 to 2016 were selected for relevance, validity and quality, from results obtained in PubMed, MEDLINE and Google Scholar using the following search terms: ncRNA and reproduction; ncRNA and endometriosis; miRNA and endometriosis; lncRNA and endometriosis; siRNA and endometriosis; endometriosis; endometrial; cervical; ovary; uterus; reproductive tract. All articles were independently screened for eligibility by the authors.

OUTCOMES

This review integrates extensive information from all relevant published studies focusing on microRNAs, long ncRNAs and short inhibitory RNAs in endometriosis. We outline the biological function and synthesis of microRNAs, long ncRNAs and short inhibitory RNAs and provide detailed findings from human research as well as functional studies carried out both in vitro and in vivo, including animal models. Although variability in findings between individual studies exists, collectively, the extant literature justifies the conclusion that dysregulated ncRNAs are a significant element of the endometriosis condition.

WIDER IMPLICATIONS

There is a compelling case that microRNAs, long non-coding RNAs and short inhibitory RNAs have the potential to influence endometriosis development and persistence through modulating inflammation, proliferation, angiogenesis and tissue remodelling. Rapid advances in ncRNA biomarker discovery and therapeutics relevant to endometriosis are emerging. Unravelling the significance of ncRNAs in endometriosis will pave the way for new diagnostic tests and identify new therapeutic targets and treatment approaches that have the potential to improve clinical options for women with this disabling condition.

Genes wide open: Data sharing and the social gradient of genomic privacy

This study reports on 13 semistructured in-depth interviews to qualitatively explore the experiences of individuals who publicly shared their direct-to-consumer genetic testing results on the platform openSNP. In particular, we focused on interviewees' understanding of privacy. Participants reported that the likelihood and the magnitude of privacy harms depend on gender, ethnicity, sexual orientation, the stigma associated with certain clinical conditions, the existence of adequate legislation, and the nature of national health care systems. Some participants expressed the view that those who enjoy higher socioeconomic status or are better protected by their country's legislation have a responsibility to share their genetic data. Our study shows that people who share their genetic data publicly online-far from being insensitive to privacy risks-have a complex understanding of the social, relational, and contextual nature of genetic privacy.

MONTRA: An agile architecture for data publishing and discovery

BACKGROUND AND OBJECTIVE

Data catalogues are a common form of capturing and presenting information about a specific kind of entity (e.g. products, services, professionals, datasets, etc.). However, the construction of a web-based catalogue for a particular scenario normally implies the development of a specific and dedicated solution. In this paper, we present MONTRA, a rapid-application development framework designed to facilitate the integration and discovery of heterogeneous objects, which may be characterized by distinct data structures.

METHODS

MONTRA was developed following a plugin-based architecture to allow dynamic composition of services over represented datasets. The core of MONTRA's functionalities resides in a flexible data skeleton used to characterize data entities, and from which a fully-fledged web data catalogue is automatically generated, ensuring access control and data privacy.

RESULTS

MONTRA is being successfully used by several European projects to collect and manage biomedical databases. In this paper, we describe three of these applications scenarios.

CONCLUSIONS

This work was motivated by the plethora of geographically scattered biomedical repositories, and by the role they can play altogether for the understanding of diseases and of the real-world effectiveness of treatments. Using metadata to expose datasets' characteristics, MONTRA greatly simplifies the task of building data catalogues. The source code is publicly available at https://github.com/bioinformatics-ua/montra.

Society and personal genome data

Genomic data offer a goldmine of information for understanding the contribution of genetic variation makes to health and disease. The potential of genomic medicine, to predict, diagnose, manage and treat genetic disease, is underpinned by accurate variant interpretation. This in itself hinges on the ability to access large and varied genomic databases. There is now recognition that international collaboration between research and healthcare systems are paramount to delivering the scale of genomic data required. No single research group, institute or country will liberate our understanding, it is only through global cooperation, together with super computing power, will we truly make sense of how genotype and phenotype correlate. Whilst it is logistically possible to create computing systems that talk to each other and aggregate datasets ready to reveal novel correlations, the bottom line is that this will only happen if people (whether they be scientists, clinicians, patients, research participants, policy makers, politicians, law makers) support the principle that we should be donating, accessing and sharing our DNA data in this way. And in order to make the most sense of genomics, given the geographical and ancestral variation between us, such people are likely to be the majority of society. Within this review, a perspective is proffered on the human story that underpins genomic 'big data' access and how we are at a tipping point as a society-we need to decide collectively, are we in? and if so, what needs to be in place to protect us? or are we out?

A FAIR guide for data providers to maximise sharing of human genomic data

It is generally acknowledged that, for reproducibility and progress of human genomic research, data sharing is critical. For every sharing transaction, a successful data exchange is produced between a data consumer and a data provider. Providers of human genomic data (e.g., publicly or privately funded repositories and data archives) fulfil their social contract with data donors when their shareable data conforms to FAIR (findable, accessible, interoperable, reusable) principles. Based on our experiences via Repositive (https://repositive.io), a leading discovery platform cataloguing all shared human genomic datasets, we propose guidelines for data providers wishing to maximise their shared data's FAIRness.

Extending TCGA queries to automatically identify analogous genomic data from dbGaP

Data sharing is critical to advance genomic research by reducing the demand to collect new data by reusing and combining existing data and by promoting reproducible research. The Cancer Genome Atlas (TCGA) is a popular resource for individual-level genotype-phenotype cancer related data. The Database of Genotypes and Phenotypes (dbGaP) contains many datasets similar to those in TCGA. We have created a software pipeline that will allow researchers to discover relevant genomic data from dbGaP, based on matching TCGA metadata. The resulting research provides an easy to use tool to connect these two data sources.

Moral Duties of Genomics Researchers: Why Personalized Medicine Requires a Collective Approach

Advances in genome sequencing together with the introduction of personalized medicine offer promising new avenues for research and precision treatment, particularly in the field of oncology. At the same time, the convergence of genomics, bioinformatics, and the collection of human tissues and patient data creates novel moral duties for researchers. After all, unprecedented amounts of potentially sensitive information are being generated. Over time, traditional research ethics principles aimed at protecting individual participants have become supplemented with social obligations related to the interests of society and the research enterprise at large, illustrating that genomic medicine is also a social endeavor. In this review we provide a comprehensive assembly of moral duties that have been attributed to genomics researchers and offer suggestions for responsible advancement of personalized genomic cancer care.

DNAdigest and Repositive: Connecting the World of Genomic Data

There is no unified place where genomics researchers can search through all available raw genomic data in a way similar to OMIM for genes or Uniprot for proteins. With the recent increase in the amount of genomic data that is being produced and the ever-growing promises of precision medicine, this is becoming more and more of a problem. DNAdigest is a charity working to promote efficient sharing of human genomic data to improve the outcome of genomic research and diagnostics for the benefit of patients. Repositive, a social enterprise spin-out of DNAdigest, is building an online platform that indexes genomic data stored in repositories and thus enables researchers to search for and access a range of human genomic data sources through a single, easy-to-use interface, free of charge.

This Community Page article introduces the charity DNAdigest, which aims to promote best practices for ethical and efficient genomic data sharing, and the free online community platform Repositive, for easy search and access to genomic datasets.

Between Openness and Privacy in Genomics

With the prospect of genomic data becoming ever more easily available, Effy Vayena and Urs Gasser discuss how we could balance making the most of its benefits with reducing its risks to privacy.

Principle of proportionality in genomic data sharing

We propose that a principle of proportionality be applied to genomic data that weighs the depth of data (what is shared) against the breadth of sharing (with whom).