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Laboratories offering cell-free DNA often reserve the right to share prenatal genetic data for research or even commercial purposes, and obtain this permission on the patient consent form. Although it is known that nonpregnant patients are often reluctant to share their genetic data for research, pregnant patients' knowledge of, and opinions about, genetic data privacy are unknown.We investigated whether pregnant patients who had already undergone cell-free DNA screening were aware that genetic data derived from cell-free DNA may be shared for research. Furthermore, we examined whether pregnant patients exposed to video education about the Genetic Information Nondiscrimination Act-a federal law that mandates workplace and health insurance protections against genetic discrimination-were more willing to share cell-free DNA-related genetic data for research than pregnant patients who were unexposed.In this randomized controlled trial (ClinicalTrials.gov Identifier: NCT04420858), English-speaking patients with singleton pregnancies who underwent cell-free DNA and subsequently presented at 17 0/7 to 23 6/7 weeks of gestation for a detailed anatomy scan were randomized 1:1 to a control or intervention group. Both groups viewed an infographic about cell-free DNA. In addition, the intervention group viewed an educational video about the Genetic Information Nondiscrimination Act. The primary outcomes were knowledge about, and willingness to share, prenatal genetic data from cell-free DNA by commercial laboratories for nonclinical purposes, such as research. The secondary outcomes included knowledge about existing genetic privacy laws, knowledge about the potential for reidentification of anonymized genetic data, and acceptability of various use and sharing scenarios for prenatal genetic data. Eighty-one participants per group were required for 80% power to detect an increase in willingness to share data from 60% to 80% (α=0.05).A total of 747 pregnant patients were screened, and 213 patients were deemed eligible and approached for potential study participation. Of these patients, 163 (76.5%) consented and were randomized; one participant discontinued the intervention, and two participants were excluded from analysis after the intervention when it was discovered that they did not fulfill all eligibility criteria. Overall, 160 (75.1%) of those approached were included in the final analysis. Most patients in the control group (72 [90.0%]) and intervention (76 [97.4%]) group were either unsure about or incorrectly thought that cell-free DNA companies could not share prenatal genetic data for research. Participants in the intervention group were more likely to incorrectly believe that their prenatal genetic data would not be shared for nonclinical purposes than participants in the control group (28.8% in the control group vs 46.2% in the intervention; P=.03). However, video education did not increase participant willingness to share genetic data in multiple scenarios. Non-White participants were less willing than White participants to allow sharing of genetic data specifically for academic research (P.001).Most participants were unaware that their prenatal genetic data may be used for nonclinical purposes. Pregnant patients who were educated about the Genetic Information Nondiscrimination Act were not more willing to share genetic data than those who did not receive this education. Surprisingly, video education about the Genetic Information Nondiscrimination Act led patients to falsely believe that their data would not be shared for research, and participants who identified as racial minorities were less willing to share genetic data. New strategies are needed to improve pregnant patients' understanding of genetic privacy.

Background Estimation of genetic relatedness, or kinship, is used occasionally for recreational purposes and in forensic applications. While numerous methods were developed to estimate kinship, they suffer from high computational requirements and often make an untenable assumption of homogeneous population ancestry of the samples. Moreover, genetic privacy is generally overlooked in the usage of kinship estimation methods. There can be ethical concerns about finding unknown familial relationships in third-party databases. Similar ethical concerns may arise while estimating and reporting sensitive population-level statistics such as inbreeding coefficients for the concerns around marginalization and stigmatization. Results Here, we present SIGFRIED, which makes use of existing reference panels with a projection-based approach that simplifies kinship estimation in the admixed populations. We use simulated and real datasets to demonstrate the accuracy and efficiency of kinship estimation. We present a secure federated kinship estimation framework and implement a secure kinship estimator using homomorphic encryption-based primitives for computing relatedness between samples in two different sites while genotype data are kept confidential. Source code and documentation for our methods can be found at https://doi.org/10.5281/zenodo.7053352. Conclusions Analysis of relatedness is fundamentally important for identifying relatives, in association studies, and for estimation of population-level estimates of inbreeding. As the awareness of individual and group genomic privacy is growing, privacy-preserving methods for the estimation of relatedness are needed. Presented methods alleviate the ethical and privacy concerns in the analysis of relatedness in admixed, historically isolated and underrepresented populations. Short Abstract Genetic relatedness is a central quantity used for finding relatives in databases, correcting biases in genome wide association studies and for estimating population-level statistics. Methods for estimating genetic relatedness have high computational requirements, and occasionally do not consider individuals from admixed ancestries. Furthermore, the ethical concerns around using genetic data and calculating relatedness are not considered. We present a projection-based approach that can efficiently and accurately estimate kinship. We implement our method using encryption-based techniques that provide provable security guarantees to protect genetic data while kinship statistics are computed among multiple sites.

Debates surrounding genetic privacy have taken on different forms over the past 30 years. Taking genetic privacy to mean an interest that individuals, families, or even communities have with respect to genetic information, we examine the metaphors used in these debates to chronicle the development of genetic privacy. In 1990–2000, we examine claims for ownership and of ‘humanity’ spurred by the launch of the Human Genome Project and related endeavors. In 2000–2010, we analyze the interface of law and ethics with research infrastructures such as biobanks, for which notions of citizenship and ‘public goods’ were central. In 2010–2020, we detail the relational turn of genetic privacy in response of large international research consortia and big data. Although each decade had its leading conceptions of genetic privacy, the subject is neither strictly chronological nor static. We conclude with reflections on the nature of genetic privacy and the necessity to bring together the unique and private genetic self with the human other.

Maryland ’s new law provides a model for others

Data sharing was a core principle that led to the success of the Human Genome Project 20 years ago. Now scientists are struggling to keep information free. Data sharing was a core principle that led to the success of the Human Genome Project 20 years ago. Now scientists are struggling to keep information free.

Research in genetics relies heavily on voluntary contributions of personal data. We aimed to acquire insights into the differences between participants and refusers of participation in a Dutch population-based biobank. Accordingly, we assessed the demographic and prosocial intrapersonal characteristics of respondents who participated (n = 2615) or refused to participate (n = 404) in the Lifelines biobank and databank. Our results indicated that health-related values critically influence participation decisions. The participation threshold for Lifelines was determined by an absence of health-related values and of trust in government. Therefore, considering these factors in communication and recruitment strategies could enhance participation in biomedical research. No indications were found of a stronger general prosociality of participants or their trust in researchers beyond the context of biobanking. This emphasizes the contextual understanding of the decision of participation in biobanking. Our findings may contribute to improving recruitment strategies by incorporating relevant values and/or highlighting prosocial benefits. Moreover, they foreground the need to address trust issues in collaborations between data repositories and commercial companies. Future research should explore how prosocial intrapersonal characteristics drive participation and withdrawal decisions and relate to contextual attributes.

The complexities of the informed consent process for participating in research in genomic medicine are well-documented. Inspired by the potential for Dynamic Consent to increase participant choice and autonomy in decision-making, as well as the opportunities for ongoing participant engagement it affords, we wanted to trial Dynamic Consent and to do so developed our own web-based application (web app) called CTRL (control). This paper documents the design and development of CTRL, for use in the Australian Genomics study: a health services research project building evidence to inform the integration of genomic medicine into mainstream healthcare. Australian Genomics brought together a multi-disciplinary team to develop CTRL. The design and development process considered user experience; security and privacy; the application of international standards in data sharing; IT, operational and ethical issues. The CTRL tool is now being offered to participants in the study, who can use CTRL to keep personal and contact details up to date; make consent choices (including indicate preferences for return of results and future research use of biological samples, genomic and health data); follow their progress through the study; complete surveys, contact the researchers and access study news and information. While there are remaining challenges to implementing Dynamic Consent in genomic research, this study demonstrates the feasibility of building such a tool, and its ongoing use will provide evidence about the value of Dynamic Consent in large-scale genomic research programs.

Dynamic consent (DC) was originally developed in response to challenges to the informed consent process presented by participants agreeing to ‘future research’ in biobanking. In the past 12 years, it has been trialled in a number of different projects, and examined as a new approach for consent and to support patient engagement over time. There have been significant societal shifts during this time, namely in our reliance on digital tools and the use of social media, as well as a greater appreciation of the integral role of patients in biomedical research. This paper reflects on the development of DC to understand its importance in an age where digital health is becoming the norm and patients require greater oversight and control of how their data may be used in a range of settings. As well as looking back, it looks forwards to consider how DC could be further utilised to enhance the patient experience and address some of the inequalities caused by the digital divide in society.

Making routine clinical-care-data available for medical research requires adequate consent to legitimize use and exchange. While, public interest in supporting medical research is increasing, individuals often find it difficult to actively enable researchers to access their data. In addition to broad consent, the idea of (consent-free) data donation has been brought into play as another way to legitimize secondary research use of medial data. However, flanking the implementation of broad consent policies or data donation, the attitude of patients, and the general public toward different aspects of these approaches needs to be assessed. We conducted two empirical studies to this end among Dutch patients (n = 7430) and representative German citizens (n = 1006). Wide acceptance of broad consent was observed among Dutch patients (92.3%), corroborating previous findings among German patients (93.0%). Moreover, 28.8% of the Dutch patients generally approved secondary data-use for non-academic research, 42.3% would make their decision dependent upon the type of institution in question. In the German survey addressing the general population, 78.8% approved data donation without explicit consent as an alternative model of legitimization, the majority of those who approved (96.7%) would allow donated data to be used by universities and public research institutions. This willingness to support contrasted sharply with the fact that only 16.6% would allow access to the data by industry. Our findings thus not only add empirical evidence to the debate about broad consent and data donation, but also suggest that widespread public discussion and education about the role of industry in medical research is necessary in that context.

Parabon Nanolabs shot to fame using DNA and genealogy analysis to solve cold cases. Then it hit a setback. Parabon Nanolabs shot to fame using DNA and genealogy analysis to solve cold cases. Then it hit a setback.

There is growing evidence that human genetics plays a significant role in shaping human responses to infectious diseases. For instance, individuals' genetic susceptibility or resistance to infectious disease is likely to affect disease transmission. Yet little attention has been paid to the ethical, legal, and social implications of research in genomics and infectious disease, despite the unique ethical issues that arise in this arena. This article presents results from a pilot study exploring ethics in research on human genetics and response to HIV and other infectious diseases and is focused on perspectives from expert stakeholders. Whereas chairs of institutional review boards, biobank directors, and researchers in genomics and infectious disease expressed similar views about research privacy in the context of a public health emergency, they expressed different perspectives about the role that public health considerations ought to play in the return of individual results to research participants. These perspectives highlight the need to emphasize the importance of broad dialogue for helping various parties navigate the ethically complex current and future challenges of genomics and infectious disease research.

Communicating results from genomic sequencing to family members can play an essential role allowing access to surveillance, prevention, treatment or prophylactic measures. Yet, many patients struggle with communication of these results and it is unclear to what extent this is discussed during the consent process. We conducted an online systematic search and used content analysis to explore how consent forms for genomic sequencing address communication of genetic information to family members. Our search yielded 68 consent forms from 11 countries. Although 57 forms alluded to the familial nature of results, forms varied in their discussion of the potential familial implications of results. Only 11 addressed communication of genetic information with family members, with differences in who would be responsible for this process. Several forms offered patients options regarding communication, even in countries where national guidelines and legislation allow for the disclosure of results in the absence of patient consent. These findings are concerning because they show how forms may potentially mislead patients and health care professionals about whether communication is permissible in cases where the patient does not consent. We suggest that providers and health care professionals reconsider how consent forms address communicating genetic information to family members. ispartof: EUROPEAN JOURNAL OF HUMAN GENETICS vol:28 issue:9 pages:1160-1167 ispartof: location:England status: published

Rapid advances in technologies in the field of genomics such as high throughput DNA sequencing, big data processing by machine learning algorithms and gene-editing techniques are expected to make precision medicine and gene-therapy a greater reality. However, this development will raise many important new issues, including ethical, moral, social and privacy issues. The field of exercise genomics has also advanced by incorporating these innovative technologies. There is therefore an urgent need for guiding references for sport and exercise genomics to allow the necessary advancements in this field of sport and exercise medicine, while protecting athletes from any invasion of privacy and misuse of their genomic information. Here, we update a previous consensus and develop a guiding reference for sport and exercise genomics based on a SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis. This SWOT analysis and the developed guiding reference highlight the need for scientists/clinicians to be well-versed in ethics and data protection policy to advance sport and exercise genomics without compromising the privacy of athletes and the efforts of international sports federations. Conducting research based on the present guiding reference will mitigate to a great extent the risks brought about by inappropriate use of genomic information and allow further development of sport and exercise genomics in accordance with best ethical standards and international data protection principles and policies. This guiding reference should regularly be updated on the basis of new information emerging from the area of sport and exercise medicine as well as from the developments and challenges in genomics of health and disease in general in order to best protect the athletes, patients and all other relevant stakeholders.

Regulatory policy for genomic testing may be subject to biases that favor reliance on existing regulatory frameworks even when those frameworks carry unintended legal consequences or may be poorly tailored to the challenges genomic testing presents. This article explores three examples drawn from genetic privacy regulation, oversight of clinical uses of genomic information, and regulation of genomic software. Overreliance on expedient regulatory approaches has a potential to undercut complete and durable solutions.

New technologies, including genomics and precision medicine, are expanding the range of predictive health information. Employers interested in assessing the future health risks of prospective or current employees can gain access to information in an individual’s clinical record or can use algorithms to make their own predictions. When individuals have sub-clinical markers of future serious impairments, neither of the two main laws prohibiting discrimination in employment based on health status, the Americans with Disabilities Act (ADA) nor the Genetic Information Nondiscrimination Act (GINA) applies. The ADA does not apply to physical or mental impairments that are not currently a substantial limitation of a major life activity. GINA does not apply to conditions that have “manifested,” including physical changes detectable by a trained professional. Both statutes should be amended to prohibit forms of discrimination that were not contemplated when the legislation was enacted.

This commentary proposes the need for greater normative debate about when, if ever, it is appropriate for insurers to access genetic information of insureds to combat anti-selection.

Effective management of complex pancreatic diseases demands precision medicine. While this new approach is technically feasible, many barriers to implementation impede realization of its promised benefits. Barriers exist in the acquisition and utilization of high quality, accurate, specific and quantitative information from both the clinical records and basic sciences. Barriers exist in integrating various domains of knowledge. Barriers exist in translating new insights from the bench to the bedside. Logistical barriers prevent seamless connection and interpretation of the necessary data elements. Barriers also exist with acceptance and application of precision medicine by major institutions and payers. Overcome these barriers will require high-level planning, clarity of vision into short and long term steps, and the commitment of innovative leaders, representing all stakeholders, to work together to reach a common goal.

Next-generation sequencing produces large amounts of data. The complexity and data management issues associated with next-generation sequencing have led many laboratories to turn to cloud services, especially when internal information technology infrastructure is inadequate to support data requirements. In addition, public cloud repositories of variants are being increasingly utilized, and their data sets are being populated through crowdsourcing submissions of human genetic variation identified within laboratories. The purpose of this review is to describe the challenges of managing genomic data in the cloud and to discuss potential strategies to surmount these challenges in a compliant manner. The definitions and advantages of cloud systems are outlined. Special regulatory considerations for laboratories are included, and strategies for compliance in the US regulatory environment for genetic information in clinical patient care as well as in research and public databases are also discussed.

Optimistic predictions that genetic and genomic testing will provide health benefits have been tempered by the concern that individuals who receive their results may experience negative psychosocial outcomes. This potential ethical and clinical concern has prompted extensive conversations between policy-makers, health researchers, ethicists, and the general public. Fortunately, the psychosocial consequences of such testing are subject to empirical investigation, and over the past quarter century, research that clarifies some of the types, likelihood, and severity of potential harms from learning the results of the testing has accumulated. I aim to provide an overview of the findings of this research by looking at selected systematic reviews. This will convey the gist of the literature's quality and coverage, reveal gaps in existing knowledge, and highlight promising areas for future scholarship.

In the last third of the twentieth century, humanists and social scientists argued that attention to genetics would heighten already-existing genetic determinism, which in turn would intensify negative social outcomes, especially sexism, racism, ableism, and harshness to criminals. They assumed that laypeople are at risk of becoming genetic essentialists. I will call this the "laypeople are genetic essentialists model." This model has not accurately predicted psychosocial impacts of findings from genetics research. I will be arguing that the failure of the model can be traced to its inability to recognize the complexity of laypeople's attitudes; its incorrect theory of how beliefs, attitudes, and discourse function; and its blindness to how academics' own interests can override the available evidence. More specifically, I suggest that the substantial data about laypeople's deployment of genetics supports what I will call the "laypeople are strategic essentialists model" better than the "laypeople are genetic essentialists model." The strategic essentialists model holds that people tend to store multiple categories, including multiple causal forces, that they deploy "strategically" to serve context-dependent goals. It will be difficult for academics to reorient ourselves to model laypeople as sophisticated strategic essentialists rather than as naïve genetic essentialists. Perhaps a little shift, however, will be of value.

Personalized genetic information is not widely utilized as a resource in learning environments, in part because of concerns about data privacy and the treatment of sensitive personal information. Here we describe the implementation of a curriculum centered on analyzing personalized genetic-ancestry test results during two-week science summer camps for middle-school-aged youth. Our research focused on how the examination of personalized DNA results affected learners’ subsequent perceptions and performance, as measured by in-camp pre- and post-tests and surveys, analysis of voluntary student talk captured by audio and video recordings, and periodic one-on-one post-camp follow-ups. The curriculum was grounded in Next Generation Science Standards (NGSS) and focused around the central question of “Who am I?” Campers approached this question via guided lessons designed to shed light on their genetic uniqueness, the many attributes of their genotype and phenotype shared with others, their more distant genetic and evolutionary ancestries, and their roles as active agents in the healthy continuation of their lives. Data relevant to these questions came from edited subsets of ancestry-informative single-nucleotide polymorphisms (SNPs) and phenotype-related SNPs from the campers’ genotype results, which their parents had received from a direct-to-consumer vendor. Our approaches to data privacy and the discovery, disclosure, and discussion of sensitive information on paternity, carrier status, and ancestry can be usefully applied and modified for many educational contexts. On the basis of our pilot implementations, we recommend additional and expanded research on how to incorporate personalized genetic ancestry information in a variety of learning contexts.

As genomic science has evolved, so have policy and practice debates about how to describe and evaluate the ways in which genomic information is treated for individuals, institutions, and society. The term genetic exceptionalism, describing the concept that genetic information is special or unique, and specifically different from other kinds of medical information, has been utilized widely, but often counterproductively in these debates. We offer genomic contextualism as a new term to frame the characteristics of genomic science in the debates. Using stasis theory to draw out the important connection between definitional issues and resulting policies, we argue that the framework of genomic contextualism is better suited to evaluating genomics and its policy-relevant features to arrive at more productive discussion and resolve policy debates.

The proliferation of sequencing technologies in biomedical research has raised many new privacy concerns. These include concerns over the publication of aggregate data at a genomic scale (e.g. minor allele frequencies, regression coefficients). Methods such as differential privacy can overcome these concerns by providing strong privacy guarantees, but come at the cost of greatly perturbing the results of the analysis of interest. Here we investigate an alternative approach for achieving privacy-preserving aggregate genomic data sharing without the high cost to accuracy of differentially private methods. In particular, we demonstrate how other ideas from the statistical disclosure control literature (in particular, the idea of disclosure risk) can be applied to aggregate data to help ensure privacy. This is achieved by combining minimal amounts of perturbation with Bayesian statistics and Markov Chain Monte Carlo techniques. We test our technique on a GWAS dataset to demonstrate its utility in practice.

BACKGROUND: Genomic analysis may reveal both primary and secondary findings with direct relevance to the health of probands’ biological relatives. Researchers question their obligations to return findings not only to participants but also to family members. Given the social value of privacy protection, should researchers offer a proband’s results to family members, including after the proband’s death? METHODS: Preferences were elicited using interviews and a survey. Respondents included probands from two pancreatic cancer research resources, plus biological and non-biological family members. Hypothetical scenarios based on actual research findings from the two cancer research resources were presented; participants were asked return of results preferences and justifications. Interview transcripts were coded and analyzed; survey data were analyzed descriptively. RESULTS: 51 individuals (17 probands, 21 biological relatives, 13 spouses/partners) were interviewed. Subsequently, a mailed survey was returned by 464 probands, 1,040 biological family members, and 399 spouses/partners. This analysis highlights the interviews, augmented by survey findings. Probands and family members attribute great predictive power and life-saving potential to genomic information. A majority hold that a proband’s genomic results relevant to family members’ health ought to be offered. While informants endorse each individual’s choice whether to learn results, most express a strong moral responsibility to know and to share, particularly with the younger generation. Most have few concerns about sharing genetic information within the family; rather, their concerns focus on the health consequences of not sharing. CONCLUSIONS: Although additional studies in diverse populations are needed, policies governing return of genomic results should consider how families understand genomic data, how they value confidentiality within the family, and whether they endorse an ethics of sharing. A focus on respect for individual privacy—without attention to how the broad social and cultural context shapes preferences within families—cannot be the sole foundation of policy.

BACKGROUND Genetic information is unique among all laboratory data because it not only informs the current health of the specific person tested but may also be predictive of the future health of the individual and, to varying degrees, all biological relatives. CONTENT As DNA sequencing has become ubiquitous with decreasing cost, large repositories of genomic data have emerged from the domains of research, healthcare, law enforcement, international security, and recreational consumer interest (i.e., genealogy). Broadly shared genomic data are believed to be a key element for future discoveries in human disease. For example, the National Cancer Institute's Genomic Data Commons is designed to promote cancer research discoveries by providing free access to the genome data sets of 12000 cancer patients. However, in parallel with the promise of curing diseases, genomic data also have the potential for harm. Genomic data that are deidentified by standard healthcare practices (e.g., removal of name, date of birth) can be reidentified by methods that combine genomic software with publicly available demographic databases (e.g., phone book). Recent law enforcement cases (i.e., Bear Brook Murders, Golden State Killer) in the US have demonstrated the power of combining DNA profiles with genealogy databases. SUMMARY We examine the current environment of genomic privacy and confidentiality in the US and describe current and future risks to genomic privacy. Reidentification and inference of genetic information of biological relatives will become more important as larger databases of clinical, criminal, and recreational genomic information are developed over the next decade.

Recent advances in metagenomic technology and computational prediction may inadvertently weaken an individual’s reasonable expectation of privacy. Through cross-kingdom genetic and metagenomic forensics, we can already predict at least a dozen human phenotypes with varying degrees of accuracy. There is also growing potential to detect a “molecular echo” of an individual’s microbiome from cells deposited on public surfaces. At present, host genetic data from somatic or germ cells provide more reliable information than microbiome samples. However, the emerging ability to infer personal details from different microscopic biological materials left behind on surfaces requires in-depth ethical and legal scrutiny. There is potential to identify and track individuals, along with new, surreptitious means of genetic discrimination. This commentary underscores the need to update legal and policy frameworks for genetic privacy with additional considerations for the information that could be acquired from microbiome-derived data. The article also aims to stimulate ubiquitous discourse to ensure the protection of genetic rights and liberties in the post-genomic era. Video abstract Supplementary Information The online version contains supplementary material available at 10.1186/s40168-021-01076-z.

Health-related genetic testing, once exclusively within the medical space, is now available within the commercial space. This paradigm shift from medical to consumer presents challenges to regulators, health care professionals and individuals. This section reports on pathways, processes and protections afforded to Australians whether genetic test results are provided by medical professionals or commercial players. While a complex web of protections is available within Australia's medical space, those accessing commercial testing rely on the same protections afforded all consumers in all marketplace transactions. There is also potential for these two initially bifurcated pathways to merge, either by business model or individual choice. Individuals pursuing commercial options obtain personal genetic information, which they self-interpret and, if they choose, share with family, medical professionals and online. While this section focuses on health-related genetic testing, it gives insight into what will undoubtedly be continued incursions into the medical space by commercial players.

Nowadays, the purpose of human genomics is widely emerging in health-related problems and also to achieve time and cost-efficient healthcare. Due to advancement in genomics and its research, development in privacy concerns is needed regarding querying, accessing and, storage and computation of the genomic data. While the genomic data is widely accessible, the privacy issues may emerge due to the untrusted third party (adversaries/researchers), they may reveal the information or strategy plans regarding the genome data of an individual when it is requested for research purposes. To mitigate this problem many privacy-preserving techniques are used along with cryptographic methods are briefly discussed. Furthermore, efficiency and accuracy in a secure and private genomic data computation are needed to be researched in future.

Modern prenatal genetic screening techniques such as cell-free fetal DNA and expanded carrier screening genotype substantial amounts of maternal and fetoplacental DNA. Although DNA can be deidentified by stripping protected health information from genetic data, anonymized DNA can be reidentified using genetic databases, raising long-term genetic privacy concerns for both mother and fetus. In this commentary, we explore the evolution of prenatal genetic screening and how modern screening techniques may pose unanticipated privacy risks. We highlight knowledge gaps and outline steps to improve patient awareness of and control over their genetic privacy, including specific recommendations for laboratories and prenatal care practitioners who offer screening. We also encourage our colleagues who provide prenatal care to be well informed about the privacy implications of the genetic tests we order and to be vocal advocates for our patients' genetic privacy, both with the laboratories that perform these tests and in the public sphere.

Genomic data is growing in importance as scientific knowledge and technology develop, and in availability, as direct‐to‐consumer genomic health testing and recreational genealogy services become more widely utilized. Access to genomic data needs to be considered in light of individual privacy. Cross‐sector use of genomic health and ancestry data, and by law enforcement in particular, raises ethical questions and requires appropriate regulation. This article discusses the significance of genomic data and focuses on investigative genetic genealogy, namely the use of genomic health and ancestry data to advance law enforcement, as an example of cross‐sector use. An ethical framework is developed that contributes to a more principled approach to genomic data access.

Investigative genetic genealogy (IGG) has emerged as a new, rapidly growing field of forensic science. We describe the process whereby dense SNP data, commonly comprising more than half a million markers, are employed to infer distant relationships. By distant we refer to degrees of relatedness exceeding that of first cousins. We review how methods of relationship matching and SNP analysis on an enlarged scale are used in a forensic setting to identify a suspect in a criminal investigation or a missing person. There is currently a strong need in forensic genetics not only to understand the underlying models to infer relatedness but also to fully explore the DNA technologies and data used in IGG. This review brings together many of the topics and examines their effectiveness and operational limits, while suggesting future directions for their forensic validation. We further investigated the methods used by the major direct-to-consumer (DTC) genetic ancestry testing companies as well as submitting a questionnaire where providers of forensic genetic genealogy summarized their operation/ services. Although most of the DTC market, and genetic genealogy in general, has undisclosed, proprietary algorithms we review the current knowledge where information has been discussed and published more openly.

Background Privacy-related concerns can prevent equitable participation in health research by US Indigenous communities. However, studies focused on these communities' views regarding health data privacy, including systematic reviews, are lacking. Methods We conducted a systematic literature review analyzing empirical, US-based studies involving American Indian/Alaska Native (AI/AN) and Native Hawaiian or other Pacific Islander (NHPI) perspectives on health data privacy, which we define as the practice of maintaining the security and confidentiality of an individual’s personal health records and/or biological samples (including data derived from biological specimens, such as personal genetic information), as well as the secure and approved use of those data. Results Twenty-one studies involving 3234 AI/AN and NHPI participants were eligible for review. The results of this review suggest that concerns about the privacy of health data are both prevalent and complex in AI/AN and NHPI communities. Many respondents raised concerns about the potential for misuse of their health data, including discrimination or stigma, confidentiality breaches, and undesirable or unknown uses of biological specimens. Conclusions Participants cited a variety of individual and community-level concerns about the privacy of their health data, and indicated that these deter their willingness to participate in health research. Future investigations should explore in more depth which health data privacy concerns are most salient to specific AI/AN and NHPI communities, and identify the practices that will make the collection and use of health data more trustworthy and transparent for participants.

Funder: State Government of Victoria (Victorian Government); doi: https://doi.org/10.13039/501100004752, Funder: Victorian State Government, Public acceptance is critical for sharing of genomic data at scale. This paper examines how acceptance of data sharing pertains to the perceived similarities and differences between DNA and other forms of personal data. It explores the perceptions of representative publics from the USA, Canada, the UK and Australia (n = 8967) towards the donation of DNA and health data. Fifty-two percent of this public held ‘exceptionalist’ views about genetics (i.e., believed DNA is different or ‘special’ compared to other types of medical information). This group was more likely to be familiar with or have had personal experience with genomics and to perceive DNA information as having personal as well as clinical and scientific value. Those with personal experience with genetics and genetic exceptionalist views were nearly six times more likely to be willing to donate their anonymous DNA and medical information for research than other respondents. Perceived harms from re-identification did not appear to dissuade publics from being willing to participate in research. The interplay between exceptionalist views about genetics and the personal, scientific and clinical value attributed to data would be a valuable focus for future research.