The Key Features of a Genetic Nondiscrimination Policy: A Delphi Consensus Statement.

Importance: Governments worldwide have become increasingly cognizant of the spread of genetic discrimination (negative treatment or harm on the basis of actual or presumed genetic characteristics). Despite efforts by a number of governments to establish regulations addressing this phenomenon, public concern about genetic discrimination persists. Objective: To identify key elements of an optimal genetic nondiscrimination policy and inform policymakers as they seek to allay genetic nondiscrimination and related public anxieties. Evidence Review: Sixty multidisciplinary experts from 20 jurisdictions worldwide were consulted to understand their views on effective genetic nondiscrimination policies. Following standard requirements of the Delphi method, 3 rounds of surveys over the course of 1.5 years were conducted. Round 1 focused on assessing participants' understanding of the intricacies of existing genetic nondiscrimination policies, while rounds 2 and 3 invited participants to reflect on specific means of implementing a more effective regime. A total of 60 respondents participated in the first round, 53 participated in round 2, and 43 participated in round 3. Findings: While responses varied across disciplines, there was consensus that binding regulations that reach across various sectors are most useful in preventing genetic discrimination. Overall, experts agreed that human rights-based approaches are well suited to preventing genetic discrimination. Experts also agreed that explicit prohibition of genetic discrimination within nondiscrimination policies can highlight the importance of genetic nondiscrimination as a fundamental right and ensure robust protection at a national level. While most participants believed the international harmonization of genetic nondiscrimination laws would facilitate data sharing worldwide, they also recognized that regulations must reflect the sociocultural differences that exist among regions. Conclusions and Relevance: As the reach of genetic discrimination continues to evolve alongside developments in genomics, strategic policy responses that are harmonious at the international and state levels will be critical to address this phenomenon. In seeking to establish comprehensive frameworks, policymakers will need to be mindful of regional and local circumstances that influence the need for and efficacy of unique genetic nondiscrimination approaches across diverse contexts.

Analysis of the privacy-performance tradeoff of reference testing in Forensic Investigative Genetic Genealogy.

During an investigation using Forensic Investigative Genetic Genealogy, which is a novel approach for solving violent crimes and identifying human remains, reference testing-when law enforcement requests a DNA sample from a person in a partially constructed family tree-is sometimes used when an investigation has stalled. Because the people considered for a reference test have not opted in to allow law enforcement to use their DNA profile in this way, reference testing is viewed by many as an invasion of privacy and by some as unethical. We generalize an existing mathematical optimization model of the genealogy process by incorporating the option of reference testing. Using simulated versions of 17 DNA Doe Project cases, we find that reference testing can solve cases more quickly (although many reference tests are required to substantially hasten the investigative process), but only rarely (<1%) solves cases that cannot otherwise be solved. Through a mixture of mathematical and computational analysis, we find that the most desirable people to test are at the bottom of a path descending from an ancestral couple that is most likely to be related to the target. We also characterize the rare cases where reference testing is necessary for solving the case: when there is only one descending path from an ancestral couple, which precludes the possibility of identifying an intersection (e.g., marriage) between two descendants of two different ancestral couples.

Genomic privacy preservation in genome-wide association studies: taxonomy, limitations, challenges, and vision.

Genome-wide association studies (GWAS) serve as a crucial tool for identifying genetic factors associated with specific traits. However, ethical constraints prevent the direct exchange of genetic information, prompting the need for privacy preservation solutions. To address these issues, earlier works are based on cryptographic mechanisms such as homomorphic encryption, secure multi-party computing, and differential privacy. Very recently, federated learning has emerged as a promising solution for enabling secure and collaborative GWAS computations. This work provides an extensive overview of existing methods for GWAS privacy preserving, with the main focus on collaborative and distributed approaches. This survey provides a comprehensive analysis of the challenges faced by existing methods, their limitations, and insights into designing efficient solutions.

The Legal Status and Improvement Path of Human Genetic Data in Gene Therapy in China.

In the legal context of Chinese law, genetic data are an object of complex rights. At the level of private law, genetic data contain personal information, thus being protected by the Civil Code and the Personal Information Protection Law. At the level of public law, genetic data are important genetic resource that embody both public and national interests, which should also be regulated by public laws such as the Biosecurity Law and the Data Security Law. The recently issued Regulation on the Administration of Human Genetic Resources have refined the approval and record procedure, in order to promote the utilization of genetic data in China. At present, China still lacks sufficient protection for genetic data privacy, and the "informed consent" and "anonymization" system cannot work effectively. On the path of improvement, we should break constraints of individualism and start from the following three levels to strengthen genetic data privacy protection: formulating specialized legislation and leveraging the functions of group organizations and public interest litigation systems.

Moving Genomics into the Clinic: Platforms for Implementing Clinical Genomic Data-Sharing in Ways That Address Ethical, Legal and Social Implications.

This section explores the challenges involved in translating genomic research into genomic medicine. A number of priorities have been identified in the Australian National Health Genomics Framework for addressing these challenges. Responsible collection, storage, use and management of genomic data is one of these priorities, and is the primary theme of this section. The recent release of Genomical, an Australian data-sharing platform, is used as a case study to illustrate the type of assistance that can be provided to the health care sector in addressing this priority. The section first describes the National Framework and other drivers involved in the move towards genomic medicine. The section then examines key ethical, legal and social factors at play in genomics, with particular focus on privacy and consent. Finally, the section examines how Genomical is being used to help ensure that the move towards genomic medicine is ethically, legally and socially sound and that it optimises advances in both genomic and information technology.

Revealing misattributed parentage through the integration of genetic information into the electronic health record.

The integration of genetic information (GI) into the electronic health record (EHR) seems inevitable as the mainstreaming of genomics continues. Such newly provided accessibility to GI could be beneficial for improving health care, as well as for supporting clinical decision-making and health management. Notwithstanding these promising benefits, the automatic integration of GI into the EHR, allowing unrestricted access to one's GI through patient portals, carries various knowledge-related risks for patients. This article is focused on the potential case of inadvertently revealing misattributed parentage through such practice. The article aims to identify key clinical and ethical implications of such revelation for adult patients. Clinical implications include, for example, altering the physician-patient interaction and the need to enhance physician's genetic literacy to improve genetic-information-specific communication skills. Ethical implications yield arguments supporting disclosure of MP, such as autonomy, individuals' right to know medical information pertaining to them, and the right to know one's genetic origins. Arguments opposing disclosure of MP centre on the right not to know GI and concerns for post-disclosure family relationships. Following the clinical and ethical analyses of these respective implications, we consider how such integration of GI into the EHR ought to be carried out, ethically. We therefore suggest a solution, featuring an autonomy-based approach, built around EHR users' right not to know. Our solution of nuanced consent options (including a 'genetic ignorance option') is designed to enable patients' informed exposure to GI through the EHR, allowing them some control over their self- and familial narrative.

A proposal for an inclusive working definition of genetic discrimination to promote a more coherent debate.

Genetic discrimination is an evolving phenomenon that impacts fundamental human rights such as dignity, justice and equity. Although, in the past, various definitions to better conceptualize genetic discrimination have been proposed, these have been unable to capture several key facets of the phenomenon. In this Perspective, we explore definitions of genetic discrimination across disciplines, consider criticisms of such definitions and show how other forms of discrimination and stigmatization can compound genetic discrimination in a way that affects individuals, groups and systems. We propose a nuanced and inclusive definition of genetic discrimination, which reflects its multifaceted impact that should remain relevant in the face of an evolving social context and advancing science. We argue that our definition should be adopted as a guiding academic framework to facilitate scientific and policy discussions about genetic discrimination and support the development of laws and industry policies seeking to address the phenomenon.

Legal aspects of privacy-enhancing technologies in genome-wide association studies and their impact on performance and feasibility.

Genomic data holds huge potential for medical progress but requires strict safety measures due to its sensitive nature to comply with data protection laws. This conflict is especially pronounced in genome-wide association studies (GWAS) which rely on vast amounts of genomic data to improve medical diagnoses. To ensure both their benefits and sufficient data security, we propose a federated approach in combination with privacy-enhancing technologies utilising the findings from a systematic review on federated learning and legal regulations in general and applying these to GWAS.

How Indigenous communities in New Zealand are protecting their data.

Concerns about the ethical use of data, privacy, and data harms are front of mind in many jurisdictions as regulators move to impose tighter controls on data privacy and protection, and the use of artificial intelligence (AI). Although efforts to hold corporations to account for their deployment of data and data-driven technologies have been largely welcomed by academics and civil society, there is a growing recognition of the limits to individual data rights, given the capacity of tech giants to link, surveil, target, and make inferences about groups. Questions about whether collective data rights exist, and how they can be recognized and protected, have provided fertile ground for researchers but have yet to penetrate the broader discourse on data rights and regulation.

IGG in the trenches: Results of an in-depth interview study on the practice, politics, and future of investigative genetic genealogy.

Investigative genetic genealogy (IGG) is a new technique for identifying criminal suspects and unidentified deceased and living persons that has sparked controversy. In a criminal case, the technique involves uploading genetic information left by a putative perpetrator at the crime scene to one or more direct-to-consumer genetic genealogy databases with the intention of identifying the perpetrator's genetic relatives and, eventually, locating the perpetrator on the family tree. In 2018, IGG helped to identify the Golden State Killer, and it has since been used in hundreds of investigations in the United States. Here, we report findings from in-depth interviews with 24 U.S.-based individuals involved in IGG that are relevant to the technique's current practice and predicted future. Key findings include: an emphasis on restricting IGG as a conceptual and technical matter to lead generation; the rapid growth of a private and largely self-regulating industry to support IGG; general recognition of three categories of cases associated with distinct practical, ethical, and policy questions, as well as varying degrees of controversy; and the significant influence of perceived public opinion on IGG practice. The experiences and perspectives of individuals in the IGG trenches related to these and other issues are potentially useful inputs to ongoing efforts to regulate the technique.

Returning personal genetic information on susceptibility to arsenic toxicity to research participants in Bangladesh.

BACKGROUND: There is growing consensus that researchers should offer to return genetic results to participants, but returning results in lower-resource countries has received little attention. In this study, we return results on genetic susceptibility to arsenic toxicity to participants in a Bangladeshi cohort exposed to arsenic through naturally-contaminated drinking water. We examine the impact on behavioral changes related to exposure reduction. METHODS: We enrolled participants from the Health Effects of Arsenic Longitudinal Study who had (1) high arsenic (≥150 µg/g creatinine) in a recent urine sample and (2) existing data on genetic variants impacting arsenic metabolism efficiency (AS3MT and FTCD). We used genetic data to recruit three study groups, each with n = 103: (1) efficient metabolizers (low-risk), (2) inefficient metabolizers (high-risk), and (3) a randomly-selected control group (NCT05072132). At baseline, all participants received information on the effects of arsenic and how to reduce exposure by switching to a low arsenic well. The two intervention groups also received their arsenic metabolism efficiency status (based on their genetic results). Changes in behavior and arsenic exposure were assessed using questionnaires and urine arsenic measures after six months. RESULTS: Clear decreases in urine arsenic after six months were observed for all three groups. The inefficient group self-reported higher levels of attempted switching to lower arsenic wells than the other groups; however, there was no detectable difference in urine arsenic reduction among the three groups. Participants showed strong interest in receiving genetic results and found them useful. The inefficient group experienced higher levels of anxiety than the other groups. Among the efficient group, that receiving genetic results did not appear to hinder behavioral change. CONCLUSION: Returning genetic results increased self-reported exposure-reducing behaviors but did not have a detectable impact on reducing urine arsenic over and above a one-on-one educational intervention.

Assessing and mitigating privacy risks of sparse, noisy genotypes by local alignment to haplotype databases.

Single nucleotide polymorphisms (SNPs) from omics data create a reidentification risk for individuals and their relatives. Although the ability of thousands of SNPs (especially rare ones) to identify individuals has been repeatedly shown, the availability of small sets of noisy genotypes, from environmental DNA samples or functional genomics data, motivated us to quantify their informativeness. We present a computational tool suite, termed Privacy Leakage by Inference across Genotypic HMM Trajectories (PLIGHT), using population-genetics-based hidden Markov models (HMMs) of recombination and mutation to find piecewise alignment of small, noisy SNP sets to reference haplotype databases. We explore cases in which query individuals are either known to be in the database, or not, and consider several genotype queries, including those from environmental sample swabs from known individuals and from simulated "mosaics" (two-individual composites). Using PLIGHT on a database with ∼5000 haplotypes, we find for common, noise-free SNPs that only ten are sufficient to identify individuals, ∼20 can identify both components in two-individual mosaics, and 20-30 can identify first-order relatives. Using noisy environmental-sample-derived SNPs, PLIGHT identifies individuals in a database using ∼30 SNPs. Even when the individuals are not in the database, local genotype matches allow for some phenotypic information leakage based on coarse-grained SNP imputation. Finally, by quantifying privacy leakage from sparse SNP sets, PLIGHT helps determine the value of selectively sanitizing released SNPs without explicit assumptions about population membership or allele frequency. To make this practical, we provide a sanitization tool to remove the most identifying SNPs from genomic data.

[DNA everywhere]. / Notre ADN est partout !

Advanced analysis of environmental DNA for diversity monitoring using deep sequencing reveals the presence of human DNA in many samples connected to human activity.Moreover, this DNA is in relatively good condition and can be used for genetic survey of populations and even individuals. This opens many interesting scientific opportunities but also raises serious privacy issues.

The Genetic Information Privacy Act: Drawbacks and Limitations.

This Viewpoint discusses proposed and enacted state legislation to protect genetic privacy for those participating in direct-to-consumer genetic testing and ensuring genetic antidiscrimination for life, health, long-term care, and disability insurance.

DisVar: an R library for identifying variants associated with diseases using large-scale personal genetic information.

Background: Genetic variants may potentially play a contributing factor in the development of diseases. Several genetic disease databases are used in medical research and diagnosis but the web applications used to search these databases for disease-associated variants have limitations. The application may not be able to search for large-scale genetic variants, the results of searches may be difficult to interpret and variants mapped from the latest reference genome (GRCH38/hg38) may not be supported. Methods: In this study, we developed a novel R library called "DisVar" to identify disease-associated genetic variants in large-scale individual genomic data. This R library is compatible with variants from the latest reference genome version. DisVar uses five databases of disease-associated variants. Over 100 million variants can be simultaneously searched for specific associated diseases. Results: The package was evaluated using 24 Variant Call Format (VCF) files (215,054 to 11,346,899 sites) from the 1000 Genomes Project. Disease-associated variants were detected in 298,227 hits across all the VCF files, taking a total of 63.58 m to complete. The package was also tested on ClinVar's VCF file (2,120,558 variants), where 20,657 hits associated with diseases were identified with an estimated elapsed time of 45.98 s. Conclusions: DisVar can overcome the limitations of existing tools and is a fast and effective diagnostic and preventive tool that identifies disease-associated variations from large-scale genetic variants against the latest reference genome.

The reuse of genetic information in research and informed consent.

Important advances in genetics research have been made in recent years. Such advances have facilitated the availability of huge amounts of genetic information that could potentially be reused beyond the original purpose for which such information was obtained. Any such reuse must meet certain ethical criteria to ensure that the dignity, integrity, and autonomy of the individual from whom that information was obtained are protected. The aim of this paper is to reflect on these criteria through a critical analysis of the literature. To guarantee these values, ethical criteria need to be established in several respects. For instance, the question must be posed whether the information requires special attention and protection (so-called genetic exceptionalism). Another aspect to bear in mind is the most appropriate type of consent to be given by the person involved, on the one hand favouring research and the reuse of genetic information while on the other protecting the autonomy of that person. Finally, there is a need to determine what protection such reuse should have in order to avoid detrimental consequences and protect the rights of the individual. The main conclusions are that genetic information requires special care and protection (genetic exceptionalism) and that broad consent is the most practical and trustworthy type of consent for the reuse of genetic information.