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.

BACKGROUND: The online offer of commercial genetic tests, also called direct-to-consumer genetic tests (DTC-GTs), enables citizens to gain insight into their health and disease risk based on their genetic profiles. DTC-GT offers often consist of a combination of services or aspects, including advertisements, information, DNA analysis, and medical or lifestyle advice. The risks and benefits of DTC-GT services have been debated and studied extensively, but instruments that assess DTC-GT services and aid policy are lacking. This leads to uncertainty among policy makers, law enforcers, and regulators on how to ensure and balance both public safety and autonomy and about the responsibilities these 3 parties have toward the public.
OBJECTIVE: This study aimed to develop a framework that outlines aspects of DTC-GTs that lead to policy issues and to help provide policy guidance regarding DTC-GT services.
METHODS: We performed 3 steps: (1) an integrative literature review to identify risks and benefits of DTC-GT services for consumers and society in Embase and Medline (January 2014-June 2022), (2) structuring benefits and risks in different steps of the consumer journey, and (3) development of a checklist for policy guidance.
RESULTS: Potential risks and benefits of DTC-GT services were mapped from 134 papers and structured into 6 phases. In summary, these phases were called the consumer journey: (1) exposure, (2) pretest information, (3) DNA analysis, (4) data management, (5) posttest information, and (6) individual and societal impact. The checklist for evaluation of DTC-GT services consisted of 8 themes, covering 38 items that may raise policy issues in DTC-GT services. The themes included the following aspects: general service content, validity and quality assurance, potential data and privacy risks, scientific evidence and robustness, and quality of the provided information.
CONCLUSIONS: Both the consumer journey and the checklist break the DTC-GT offer down into key aspects that may impact and compromise individual and public health, safety, and autonomy. This framework helps policy makers, regulators, and law enforcers develop methods to interpret, assess, and act in the DTC-GT service market.

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.

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.

BACKGROUND: Genetic data are widely considered inherently identifiable. However, genetic data sets come in many shapes and sizes, and the feasibility of privacy attacks depends on their specific content. Assessing the reidentification risk of genetic data is complex, yet there is a lack of guidelines or recommendations that support data processors in performing such an evaluation.
OBJECTIVE: This study aims to gain a comprehensive understanding of the privacy vulnerabilities of genetic data and create a summary that can guide data processors in assessing the privacy risk of genetic data sets.
METHODS: We conducted a 2-step search, in which we first identified 21 reviews published between 2017 and 2023 on the topic of genomic privacy and then analyzed all references cited in the reviews (n=1645) to identify 42 unique original research studies that demonstrate a privacy attack on genetic data. We then evaluated the type and components of genetic data exploited for these attacks as well as the effort and resources needed for their implementation and their probability of success.
RESULTS: From our literature review, we derived 9 nonmutually exclusive features of genetic data that are both inherent to any genetic data set and informative about privacy risk: biological modality, experimental assay, data format or level of processing, germline versus somatic variation content, content of single nucleotide polymorphisms, short tandem repeats, aggregated sample measures, structural variants, and rare single nucleotide variants.
CONCLUSIONS: On the basis of our literature review, the evaluation of these 9 features covers the great majority of privacy-critical aspects of genetic data and thus provides a foundation and guidance for assessing genetic data risk.

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.

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.

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.

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.

Once someone is diagnosed with a genetic abnormality or disorder, that information can be extremely valuable to their biological relatives. It may allow them to access preventive treatment or make informed decisions, such as whether to have a biological child or not. However, when the original family member refuses to disclose that information to at-risk relatives, a conflict arises between their right to patient confidentiality and their relatives\' right to know. Aotearoa New Zealand lacks a specific, workable mechanism for disclosing genetic information to at-risk relatives. This article traverses the theoretical and practical issues involved in non-consensual disclosure of genetic information to suggest a new path for Aotearoa. It argues that the current, Western attitude of autonomy as an individual right free from obligations to others is no longer an appropriate justification for confidentiality over genetic information. Instead, patients diagnosed with a genetic abnormality or disorder should only be entitled to confidentiality where they have a reasonable expectation of privacy - determined by weighing the objective interests for and against disclosure. This approach recognises that we ought to consider our close relationships with others when we exercise autonomy over what is ultimately shared family information.