Health and Healthcare Systems

This is how to address genomic data abuse to achieve health equity

DNA samples on a tray: genomic research can save lives, but with no ethical frameworks in place, the practice could come with an inverse human cost.

Genomic research can save lives, but with few policies in place, the practice could come with a human cost. Image: National Cancer Institute

Elissa Prichep
Project Lead Precision Medicine, World Economic Forum
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Precision Medicine

This article is part of: Centre for Health and Healthcare
  • Due to longstanding gaps in population understanding, inclusion in research and access to targeted care, non-white minority populations may receive less accurate preventative screenings, less reliable diagnostics and less targeted treatments.
  • Two genomic research examples highlight the need for new tools to ensure equitable health outcomes globally.
  • A new framework calls for enhanced policy to balance ethical tensions around genomic research and its application.
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The disproportionately devastating impact of the COVID-19 pandemic on minority communities is alarming. Data from government offices in both the United States and United Kingdom show higher COVID-19 hospitalization and death rates for non-white minority populations compared to white populations.

American Indian and Alaska Native people, and black people, had a hospitalization rate approximately five times that of white people in the US. In the UK, a study reviewing National Health Service patient records also found that black and Asian people were about twice as likely to die from COVID-19 as white people, and a bulletin from the Office for National Statistics found men of Indian, Pakistani or Bangladeshi ethnicity were 1.5 times more likely to die than white men.

Image: Centers for Disease Control

Sadly, disparities in health outcomes are not unique to COVID-19. This data represents the latest consequence of longstanding gaps in population understanding, inclusion in research and access to targeted care. Unless addressed, these disparities will grow larger during the era of genomic medicine.

Disparities in genomic data

Genomic medicine refers to more precise disease screenings, diagnostics and treatments based on a deeper understanding of our DNA, the unique set of instructions that guides how each person’s body develops and functions. Most of the research informing genomic medicine has occurred in Caucasian populations. While over 99% of DNA is the same in all people, the differences can have important health implications.

The lack of diversity in research studies can lead to blind spots, like not knowing which disease-causing genetic “glitches” – such as those that increase one’s risk of breast cancer, sickle cell anaemia, or cystic fibrosis – appear more frequently in certain populations.

Translated to the clinic, this means non-white minority populations may receive less accurate preventative screenings, less reliable diagnostics and less targeted treatments.

In a 2019 study, researchers from the Broad Institute of MIT and Harvard and Massachusetts General Hospital found data from the UK Biobank had a 4.5 times higher prediction accuracy for polygenic risk scores (used to predict the risk of developing certain diseases) in people of European ancestry than those of African ancestry, and two times higher accuracy than those of East Asian ancestry. To address these issues, scientists, business leaders, civil society members and others are expanding genomic studies to include non-white populations globally; however, it is imperative they do so while proactively attending to the ethical and legal implications of collecting and using this highly sensitive information.

The accelerated collection and use of genomic data, the digitized record of a person’s DNA, is occurring in historically excluded and understudied populations, including in populations of low- and middle-income countries (LMICs) and emerging economies. While this data can be used to support scientific research leading to more population-relevant disease screening guidelines and more precise clinical care, collecting it under a lack of pertinent legal protections and ethical standards puts populations at risk of exploitation, harm and discrimination. Two cases below illustrate these opposing situations.

The promise and peril of genomic research: two examples

Genomic research on HIV infections provides an example of how more inclusive research can address existing disparities in genomic data, and the corresponding adverse impact on specific populations. HIV-1 represents 95% of global HIV infections for the virus across its subtypes or genetically distinct versions. Subtype HIV-1B represents about 12% of global infections and is predominant in the Americas, Western Europe and Australasia. Subtype HIV-1C accounts for about half of global HIV-1 infections and is commonly found in Africa and India.

Despite geographic differences in the prevalence of these two HIV-1 subtypes, most HIV research is done on Caucasian populations in the Americas or Western Europe, which can then inadvertently inform suboptimal approaches to public health and patient care for those in Africa or India.

More appropriate approaches are coming with more diversity in research studies. For example, a 2017 genome-wide association study with 556 HIV positive Botswanans revealed two genetic regions significantly associated with HIV-1C acquisition or progression in sub-Saharan African populations. This finding suggested new potential targets for HIV-1C prevention and treatment, as well as new markers for diagnostic testing, which would lead to earlier detection and more appropriate treatment.

While this research led to a beneficial discovery, genomic data collection is not without risk to participants. Insufficient genomic data policies expose countries and communities to the risk that certain actors will extract genetic and biologic information and use it for their own benefit rather than that of the population. There is also the less nefarious risk that actors will simply mishandle this highly sensitive data amid a lack of standards and policies to protect against such actions.

This was the case when members of the Havasupai Tribe, a native population in the Southwestern United States, consented to providing blood samples to university researchers to investigate a possible genetic link to the high rate of diabetes in their population. Other researchers at the university went beyond this consent, using the samples to research and publish papers on inbreeding, alcoholism, mental disorders and the tribe’s origin and migration from Asia. The Tribe was humiliated. The grievous nature of Havasupai’s experience prompted the Navajo Nation, the second largest recognized tribe in the United States, to ban genetic research on its members in 2002. The ban continues today.

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The consequences we face

The Havasupai case, and Navajo Nation reaction, show that backlash against the misuse of genomic data can be swift and severe. This would not only set back global advancements in genomic medicine, but will disproportionately harm the communities that are already suffering the greatest healthcare disparities.

These dire consequences can be preempted with ethical policy, regulations and standards. The World Economic Forum aims to support policy-makers, scientists, research participants and others in developing approaches that will lead to more inclusive genomic research while safeguarding against the devastating consequences of the abuse of genomic data.

New tools for equitable health outcomes globally

A set of tools, launched by the World Economic Forum, include a Genomic Data Policy Framework and Ethical Tensions whitepaper and case studies and lessons on Addressing Ethical Tensions in Genomic Data Policy. The whitepaper proposes 21 policy principles across the topics of consent, data privacy, data access and benefit sharing, such as autonomy, accountability, dignity and cooperation.

The documents explore six ethical tensions – such as the tension of balancing individual privacy and societal benefit – that highlight the competing ethical priorities surrounding genomic data. Policy should reflect a society’s ethical position on issues, and too often the two are divorced until conflict arises. To assist in thorough, diligent and nuanced discussion, the documents also provide a set of questions to guide ethical policy development.

Balancing the promise and perils of genomic data collection and use with the real-world practicalities of policy implementation and revision will remain a continuous challenge as the field of genomic medicine advances. Rising to this challenge is not an option. Developing genomic data policy that attends to the ethical norms within societies is necessary to foster further diversity in genomic research. This contribution to the growing set of work in the field supports those pursuing greater inclusivity of historically excluded and understudied populations, which will result in healthcare advances developed with, tailored to and accessible by these populations, thereby improving health outcomes globally.

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