Translating genomic research into public health benefits is a central aim of public health genomics [1]. Rapid technological advancements are transforming the field and its approaches to clinical practice and disease prevention. As the genome becomes an avenue through which to understand health risk, disease progression, and treatment response, researchers, policy-makers, patients, members of the public, and members of industry are all increasingly interested in identifying whether and how genomics can be used to personalize clinical services and enhance public health.

In this commentary, we examine what it means to practically translate genomic research into public health benefits and challenges to doing so. As Koehly and colleagues point out, understanding genomics is “an inescapable part of fully understanding human behavior and social systems” and thus critical for implementing successful public health policies [2]. Yet genomic research and applications must navigate the tension between personalizing for the individual and optimizing for public health. This tension has long existed within public health – well before the integration of molecular genetic data into the field [3]. However, the personal nature of genomic information can make it particularly tempting to focus on individual, rather than public, health metrics. As such, we argue that public health genomics must vigilantly evaluate whether and how its genomic research prioritizes public health. Furthermore, public health genomics ought to identify the public health impacts, both positive and negative, of genomic research as defined by the societies and communities where that health care is delivered. This involves working to interrogate the current public/expert binary that exists in many public health responses and empowering communities to assist with defining and securing public health benefits.

We begin by introducing one of the latest genomic tools to make inroads into public health: polygenic scores (PGS). Then, we present some of the dangers of forgetting to prioritize publics in public health. Finally, we offer some practical ways to prioritize these collective-level goals so that public health can justly and equitably benefit from genomic advances.

In recent years, significant attention has been devoted to exploring whether and how to integrate genomic data into public health. PGS – also known as polygenic risk scores, genome-wide PGS, or polygenic indices – are an emerging tool that many hope will help to improve preventive public health. Derived from genome-wide association studies, PGS aggregate the small effects of thousands of genetic variants spread out across the human genome to provide an estimate of an individual’s genetic risk for traits such as heart disease or type II diabetes.

PGS raise potential benefits and risks for public health broadly and preventive public health approaches specifically. On the one hand, US federal agencies like the Centers for Disease Control (CDC) are optimistic that PGS, in combination with other risk factors (e.g., family history, diet), can enhance prediction of disease progression and treatment response [4]. With this information, clinicians may be able to target proactive interventions to those who need them most by, for instance, implementing heightened monitoring protocols for patients with high PGS for heart disease or proactively administering statins to them. Furthermore, researchers have argued that genomic data may allow the medical community to move beyond treatment on the basis of problematic social constructs such as race and toward a system of care that views each individual as a unique constellation of genetic and environmental factors [5].

On the other hand, however, the vast majority of samples available for PGS generation come from individuals whose ancestors may have originated from the European continent. Although initiatives such as the US-based National Institutes of Health (NIH) All of Us research program endeavor to increase biobank diversity, the current overrepresentation of a relatively narrow subset of the global population limits the accuracy with which PGS can be used to estimate genetic risk for the vast majority of people in the world. An implication of this limitation is that any implementation of PGS in clinical settings today risks exacerbating existing health disparities – thereby producing population-level harms [6]. In addition, the focus on enhancing biobank diversity through the recruitment of underrepresented racial/ethnic groups risks reinforcing false perceptions of race as biological, and in and of itself, this does not guarantee that more accurate PGS will result in concrete benefit to minoritized communities [7].

Despite the current limitations and uncertainties about PGS [8], efforts to integrate this technology into preventive public health are already underway. The National Health Service in the UK, for example, recently launched a pilot study to integrate PGS for heart disease into clinics [9]. Moreover, large clinical research institutes in the USA are beginning to explore the design of clinical programs that integrate PGS into routine preventive health screenings for heart disease and cancer in adults [9] and type I diabetes in newborns [10]. These efforts are further supported by the recent development of reporting standards for PGS to help ease the translational process [11].

Outside the academic enterprise, industries are beginning to market PGS information to consumers. Direct-to-consumer companies like 23andMe [12] and SelfDecode [13] are offering consumers the opportunity to learn their PGS for disease conditions that adversely impact individual and public health such as Alzheimer’s disease and type II diabetes. In addition, companies such as Orchid Health [14] and Genomic Prediction [15] have begun using PGS to screen embryos for a host of clinical phenotypes, including heart disease – one of the leading causes of death in the US. Industry applications of PGS – especially in embryo selection – have been loudly criticized by some scientific experts [16, 17]. Regardless, regulation of direct-to-consumer genetic testing is sparse [18], and the commercial appeal of PGS applications appears to be strong among consumers [19]. For example, the parents of the first baby born via polygenic embryo selection selected the embryo with the lowest PGSs for heart disease, diabetes, and cancer [20]. As genomic technologies like PGS become increasingly available and accessible, their implications for public health will grow in number.

Public health is largely concerned with collective effort and informed choice at the societal or population level. That is, public health is about securing public benefits such as decreased rates of diabetes or heart disease in a society. To secure such benefits, public health officials might choose to develop school nutrition programs that support healthy eating or run widely accessible anti-smoking campaigns that point out the relationship between smoking and heart disease. Integrating genomic research into public health offers additional potential approaches. PGS, for instance, could support diabetes prevention efforts by helping allocate scarce resources to those who might benefit most.

However, a key goal of genomic research is to support personalization through precision health, and such a goal may be in tension with the goals of public health. For instance, the All of Us precision health research program presents itself as a foil to the “one size fits all” approach to health care, stating that “treatments meant for the “average” patients may not work well for individual people” [21]. Whether intentionally or not, genomic research initiatives can present themselves as primarily focused on conferring potential benefits to individuals, like connecting “people with the right clinical studies for their needs” [21]. Indeed, All of Us defines precision medicine as being “based on you as an individual” [21].

While it may be tempting to flock to the latest genomic advances for answers, public health researchers must continue to hold a holistic view of public health. This means navigating the tension between the individual and the population that genomic research can invite and recognizing the importance of other non-genetic factors like the social determinants of health. For instance, any use of PGS in public health should be done in combination with other risk factors (e.g., diet, environmental toxins, poverty) as a combined approach stands to improve both individual and public health measures more than any one factor in isolation. The genome is more than just genetic information and reactions on a cellular level; it is a dynamic system whose greatest strength is its ability to adapt to the immediate environment [22]. And, the environments in which people are born, live, and work affect their health, quality of life, and life outcomes.

In short, when integrating genomic technologies like PGS into public health, it is necessary to consider whether public benefits are being optimized over individual benefits. This requires asking and answering questions like: Has the health and well-being of society improved as a function of PGS? Do all those who stand to benefit from PGS applications have access to them? Are the outputs of the technology actionable? For whom? As we discuss next, an important component to effectively answering these questions is including the public.

One of the most difficult parts of developing a comprehensive list of benefits, burdens, concerns, fears, and hopes about the future of public health genomics is gathering honest, legitimate input from the public itself. But the use of the term “public” can disguise the diversity of perspectives and lived experiences captured in a society. Thus, we use the plural term “publics” to account for these heterogeneities.

Individuals often belong to several different publics. For example, consider an individual like Alex (pronouns they/them), who lives in a rural environment with limited health care resources, speaks a language other than English at home, and identifies as African American and LGBTQIA+. Each of these identities brings different definitions, challenges, and perspectives to public health issues.

In recent years, researchers have begun to realize the importance of gathering the input of publics on an array of issues when designing and conducting public health research (e.g., what defines consent) [23]. One reason for this shift is the growing recognition that ignoring or neglecting public considerations produces policies and interventions that are less likely to be successful. For instance, without community feedback, researchers may be unable to identify barriers that make accessing testing and care difficult for some communities, especially marginalized ones, such as those that are rural or low-income [24]. A recent study by Crocker and colleagues (2017) found that community members who participated in public health research felt that their involvement resulted in research findings of a higher caliber that were more relevant to their lives (as compared to researcher-only projects) [25]. Allowing publics to serve as equal partners in research priority setting can help foster research agendas that result in the more just and equitable distribution of benefits that communities want.

As researchers and clinicians seek to understand the role and relevance of PGS for public health, devoting specific attention to gathering input, facilitating discussion, and seeking the approval of the publics that will encounter PGS applications will be critical. For example, Alex and their family may be concerned about a PGS-informed newborn screening program in their community. The privacy concerns in their small rural town will differ from those that someone living in New York City may have, and their newborn child’s access to preventive, specialized, and timely care could pose geographical and technological access challenges. Thus, there may be both group and individual harms that are overlooked without input from publics.

Restricting discussion and decision-making during the scientific process to members of the academic community could also reduce publics’ trust in those who conduct research. When institutions or governments lack an understanding of publics’ views on genomic medicine and the potential harms and benefits of it, they may find that people are less inclined to trust recommendations or buy into behaviors that could reduce individual genetic risk [26]. Genomic research specifically has been critiqued for failing to incorporate patient and public concerns, expectations, and goals [27, 28]. Research agendas are often set by non-interdisciplinary teams of researchers and based on scientific or funding priorities [29]. When this happens, institutional and public concerns may not overlap. For example, in a study about genetic testing for post-traumatic stress disorder (PTSD) and addiction, Lent and colleagues (2017) were surprised to find that ELSI (ethical, legal, and social implications) concerns identified by academic scholars (e.g., privacy, discrimination, insurance coverage) were not concerns raised by potential consumers and patients who were surveyed [30]. Lent et al. [30] also found that the majority of participants surveyed were not even interested in genetic testing for PTSD (61.7%) or for addiction (68.7%). If unaware of potential differences in values like these, researchers could overlook what is important to those they are trying to help. Lent et al. [30] provide a case study of scientists focusing their efforts on developing services using genomics that consumers do not want and that do not align with community health goals. Finally, failure to present tangible, actionable, and requested information or services to communities could further add to the perception that academic research is a self-serving industry; this, in turn, could stymy efforts to enhance the trustworthiness of research institutions [31] and adversely affect public health measures, which necessarily require publics to buy-in.

As an example of one approach to integrate publics into public health, Wand and colleagues [32] (2023) engaged in a community empowerment co-design process. The team, comprised of patients, caregivers, researchers, and clinicians, sought to integrate community and patient concerns, and hopes, into the design of a new clinical genetics service incorporating PGS for heart disease into routine preventive health screening. Throughout the process, their team highlighted the importance of co-learning, where the expertise of each person – whether community member, researcher, or clinician – was recognized and honored as an essential ingredient for creating and establishing a successful program. Reciprocal relationships and true partnerships among all members of the team, and shared, transparent decision-making, were also necessary and supported by active facilitation, participation, and the development of dynamic group norms [32]. One of the biggest lessons learned was the importance of being mindful of and adapting to a specific context, cognizant of political climates and attitudes, social conditions, and community norms and expectations – all of which ultimately require a “hyper contextual and localized approach” [32].

In this section, we offer four recommendations for moving toward more just and equitable public health genomics.

Interrogate Who Is Considered an “Expert”

Terms like “public engagement” and “community engagement” have become buzzword as researchers and academics increasingly recognize the value of collaboration with a wide variety of communities [24]. However, scholars have shown that there is uncertainty about what it means to engage publics or a community and what the goals of such engagements should be [33, 34]. Considering the perspectives, values, and epistemologies of publics (i.e., viewing publics as experts in their lived experiences) is often seen as non-essential to the scientific process, treated as an afterthought, or acted upon because funders require it [31].

In a recent article, Conley and colleagues (2023) questioned whether current efforts to engage non-researchers simply result in the regurgitation of government recommendations – giving superficial authenticity to institutions who can now say they have gathered public input [33]. Work remains to identify the best ways to recognize and meaningfully incorporate publics’ desires, perspectives, and experiences into scientific and translational processes; this includes questioning the paradigms that exist that position the expertise of publics as secondary to that of researchers and policymakers.

Public health response has at times been critiqued for the one-way transmission of expert-led decisions to “the public” [35]. As polarization over vaccines and mask-wearing in the face of COVID-19 has illustrated, the recommendations of experts are not always readily accepted by everyone: what seemed like a straight-forward public health recommendation was interpreted as curtailing personal liberties in some communities [36]. Interrogating the “expert”/public binary such that publics feel more empowered and are given greater agency in decision-making processes about their health could better prioritize and promote public benefits and minimize public harms.

Evaluate Public Benefits and Harms

Once the “expertise” of publics is recognized, public health genomics will need to understand and evaluate the public benefits and harms of research by actually taking into account the knowledge and perspectives of a diverse set of publics – those who are affected by and may affect the research. Opinions about who decides which research and implementation outcomes to evaluate and which methods should be used for doing so can vary among different groups [25]. Furthermore, publics may identify, define, and prioritize benefits and harms differently than researchers [34]. Thus, research and any resulting research applications (e.g., the introduction of PGS into preventive health screenings) that are intended to support public health will need to be implemented in partnership with publics.

In addition, public benefits need to be considered relative to public harms. In the USA, few incentives or policies exist to encourage researchers to consider the broad downstream implications of research – especially the social harms. Yet, history is replete with examples of large-scale public health projects that produced real harms to both individuals and communities (e.g., the Tuskegee study [37], the Johns Hopkins Kennedy Krieger Institute (KKI) lead paint study [38], and the Havasupai tribe genetics study [23]). Each of these cases was conceived without any community involvement and claims about who the study benefitted were specious at best. Theoretically, knowledge that could be used to improve public health could be gleaned from each study; however, the devastation these studies left behind in each community means that many groups are rightfully skeptical of claims from institutions to be conducting research for the greater good. These cases demonstrate the need to consider and, where possible, mitigate against broad social harms so as to maximize potential benefits for all, not just some, publics.

As such, new scientific and academic knowledge must be presented and operationalized to communities using culturally appropriate frameworks. LorrieAnn Santos, former co-project director of `Imi Hale – Native Hawaiian Cancer Network, explains that “If academic generated research undermines the cultural fabric and beliefs of a group, it is tantamount to stripping them of traditions and practices that have also served as protective factors for generations” [23]. Having a big-picture awareness of culturally important issues and values is a vital component to mitigating against the harms of, and successfully realizing the benefits of, genomics for different communities. The Native BioData Consortium is an example of one such effort; the nonprofit research institute seeks to secure health research benefits for Indigenous people by (1) keeping samples and data under tribal jurisdiction; (2) building the STEM capacity of tribal communities via economic opportunities and educational; (3) supporting Indigenous scientists and trained academics to foster trust in research; and (4) creating datasets that encompass biological, cultural, and socioeconomic factors that affect the health outcomes of Indigenous people [39].

Cultivate Trust and Mutual Respect

As Wand and colleagues (2023) point out, genuine partnerships, nourished with trust and mutual respect, are critical for the successful future of public health genomics [32]. Researchers and public health officials on their own are incapable of anticipating the range of potential harms and benefits that may arise in public health genomics; they are also unable, without soliciting publics’ input, to know about the concerns held by various publics about said research. When institutions or governments lack an understanding about different publics’ views on genomic technologies, their translation into public health, and the potential harms and benefits, the individuals who comprise publics may be less inclined to trust recommendations or buy into behaviors that could reduce individual genetic risk [26]. As public health can sometimes require public interests to trump personal desires or convenience, gathering input and perspectives from publics can help frame this negotiation in ways that may be more palatable to diverse communities.

Communication among and between publics, in common language, is critical for cultivating trust and mutual respect. Researchers are already aware that there are challenges to communication with the public, including how best to gather social concerns from a variety of audiences [40, 41]. Some publics may find it hard to draw connections between factors that clearly indicate health (rates of depression) and amenities that increase one’s health but are not strictly “health improvements” (like safe community spaces to reduce isolation among individuals). Using a dynamic system model [22] to explain interactions among health determinants could help more publics understand the importance of public health by attending to macro-level effects rather than just individualized health statuses like a PGS. Importantly, education should not flow unidirectionally from expert to publics. Researchers and policy-makers mutually have learning to do about the values, goals, and preferences of those they aim to help.

Move beyond Data Representation

Lastly, truly securing public health benefits means moving beyond the development of more representative datasets – as has been the primary focus of genomic research lately [42] – to providing adequate access to care, appropriate insurance coverage, and expanding cutting-edge clinical service delivery outside the ivory towers of large medical centers. Diverse representation in genomics should not be limited to sample donations. It should also include a 360° evaluation of whether health benefits are, in practice, being actualized and for whom. For example, the introduction of PGS into public health measures via preventive health screenings could incentivize additional medical evaluations that benefit private health care institutions and test developers. However, this extra involvement with the health care system could also subject patients to undue stress and/or produce unactionable results. It remains an open question whether the integration of PGS into preventive health will, in fact, improve public health. Answering this question will require consistent monitoring and regular evaluation. Therefore, priority should be given to researching delivery models and evaluating the sustainability of public health interventions that incorporate genomics. In particular, public health needs robust evidence on how to implement genomic measures in communities that are adversely affected by social determinants of health and what the impacts of implementation are [24]. This will require many strands of research, as local, regional, or even neighborhood differences can impact delivery and sustainability.

Public health genomics is a rapidly developing field, making it challenging to predict what genomic technologies will be developed, how they will be implemented, and the consequences of their implementation. As such, it is an area in which the views of both scientifically trained researchers and the publics that genomic technologies will impact are required. Otherwise, important concerns or potential harms could be missed, and the harms that are articulated by researchers, whether intentionally or not, may infantilize minoritized groups – generating unforeseen consequences that are not visible from an institutional standpoint or that suppress real-life consequences for vulnerable individuals and communities [43].

The translation of genomic data into public health (e.g., through PGS-informed preventive health screenings) will be neither fair nor just and will fail to produce collective health benefits, if broad social harms and benefits are unaccounted for and a collective response is neglected. Public health genomics needs to regularly ask itself: Who are the intended beneficiaries of incorporating genomic data into public health? Who actually benefits in practice? Are the benefits of public health genomic research amassing among members of industry who have found ways to make it profitable? Are the benefits concentrated among researchers driven to secure their own tenure and promotion? Public health genomics will need to ask the publics that make up “the public” whether they perceive the anticipated benefits of public health genomics as benefits. Without answers to these questions, without bringing questions of public benefit to the forefront of genomic personalization, without more thoughtful integration of publics into discussions about public health, the just and equitable translation of genomic research into public health benefits will remain elusive.

An ethics statement was not required for this study type; no human or animal subjects or materials were used.

This manuscript is comprised of original material that is not under review elsewhere, and the subject on which the research is based has been subject to appropriate ethical review. The authors declare there are no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Effort for B.M.F. was supported by the Stanford Training Program in ELSI Research (NHGRI Grant T32HG008953).

Brandy M. Fox and Daphne Oluwaseun Martschenko contributed to the paper conception, writing, and editing and read and approved the final manuscript.

No data were generated or analyzed during this study. Further inquiries can be directed to the corresponding author.

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