Guidelines for genetic ancestry inference created through roundtable discussions
PMCID: PMC9926022
PMID:
Abstract
Summary The use of genetic and genomic technology to infer ancestry is commonplace in a variety of contexts, particularly in biomedical research and for direct-to-consumer genetic testing. In 2013 and 2015, two roundtables engaged a diverse group of stakeholders toward the development of guidelines for inferring genetic ancestry in academia and industry. This report shares the stakeholder groups’ work and provides an analysis of, commentary on, and views from the groundbreaking and sustained dialogue. We describe the engagement processes and the stakeholder groups’ resulting statements and proposed guidelines. The guidelines focus on five key areas: application of genetic ancestry inference, assumptions and confidence/laboratory and statistical methods, terminology and population identifiers, impact on individuals and groups, and communication or translation of genetic ancestry inferences. We delineate the terms and limitations of the guidelines and discuss their critical role in advancing the development and implementation of best practices for inferring genetic ancestry and reporting the results. These efforts should inform both governmental regulation and self-regulation. Two roundtables engaging a diverse group of stakeholders enabled the development of guidelines for inferring genetic ancestry in academia and industry. This report describes the engagement process and the resulting guidelines, which can inform continued improvement of practices and assist ongoing scholarly, industry, and policy discussions.
Full Text
Genetic ancestry inference is commonly used by researchers (e.g., to control for population stratification, explore population history, etc.), sought by individuals via direct-to-consumer (DTC) genetic testing companies to learn more about their genealogical history, geographic origins, and population affiliations, and contemplated by precision health initiatives as a means to “return value” or otherwise engage patient-participants. Both research findings and individual DTC results are often featured in the print and broadcast media. Genetic ancestry inference is thus used across a wide variety of settings, with different goals, assumptions, methods, and claims of accuracy and validity. It is therefore not surprising that there has been considerable disagreement among diverse stakeholders about the merits, limitations, utility, and impact of genetic ancestry inference. Consequently, efforts by any individual stakeholder group to advocate for standards or regulation have met with little success. The need for standards and other guidance has never been greater, as the popularity of DTC genetic ancestry testing continues to expand, members of Congress have expressed concern, controversial applications of genetic ancestry information continue to be explored (e.g., forensic or investigative genetic genealogy;,,,,, immigration decisions;, political posturing;, medical school admissions; entitlement eligibility;, and social identity and belonging,,,), and society has little choice but to confront whether, how, and when it is appropriate to rely upon anyone’s genetic ancestry information.
In 2008 the American Society of Human Genetics (ASHG) convened a task force to study issues emerging from genetic ancestry inference in academia and industry and to explore a constructive response to the need for more transparency and discussion about what genetic ancestry inference entails, as well as how it works and what it can and cannot do. The ASHG Board of Directors approved an ASHG position statement developed by the task force and the Society’s Social Issues Committee on ancestry inference that called attention to motivations, technical accuracy and reliability of results, health implications, societal and personal implications, proprietary databases, communication of limitations and potential impacts, public and personal education, interdisciplinary collaboration, and mechanisms for accountability (https://www.ashg.org/wp-content/uploads/2008/11/Statement-20081311-ASHGAncestryTesting.pdf) and approved an ASHG White Paper that provided recommendations aimed at addressing these issues.
One of the recommendations of the task force was to convene a diverse group of stakeholders and develop guidelines for genetic ancestry inference that would inform research and commercial applications of ancestry testing. The long-term goal was to develop the precursors to best practices for inferring genetic ancestry and guidelines for the uses and reporting of genetic ancestry testing results. A planning committee was formed consisting of two Chairpersons (C.D.R. and M.J.B.), representatives of human population geneticists, the DTC ancestry testing industry, scholars in ethical and social implications of human genetics, and consumers of ancestry testing (e.g., genetic genealogists), and it organized a “roundtable” to develop consensus statements and guidelines for genetic ancestry inference. A first meeting (i.e., Roundtable I) was held in Washington, DC in September 2013. There were 65 participants representing seven stakeholder groups: population geneticists, DTC ancestry testing companies, social and behavioral scientists, humanists, clinicians, community representatives, and consumer groups including genealogical associations/societies. The participants generated 22 “consensus” statements—defined as statements accepted by a majority but not all participants—about the uses, methods, and outcomes of genetic ancestry inference (Table 1). Critical dissent and constructive criticisms were encouraged to ensure that all stakeholders had a “voice” and that multiple perspectives—even those that were highly dissenting—were considered. Reports from those in the minority were solicited. Several statements were edited for clarity and grammar in subsequent email exchanges among participants. A second roundtable meeting (i.e., Roundtable II) was held in Durham, NC in May 2015 to compose, based upon these 22 consensus statements, a set of guidelines (Table 2) for ancestry inference that would serve as a template for the development of best practices. There were 49 participants in this second meeting, including 40 attendees from the first roundtable meeting.
Roundtable I resulted in an expansion of the eight draft consensus statements to 22 (Table 1), reflecting robust discussion and reactions to the questions that accompanied the draft statements. Clearly, it was often the case that discussion identified that original draft statements did not adequately capture the complexity of the questions posed and therefore required further elaboration. In several instances a consensus statement was deemed obvious, and therefore unnecessary, to one stakeholder group but was simultaneously judged by another stakeholder group to be unobvious and important. Eighty-five percent or more of attendees agreed with 15 statements, and no statement received less than 73% of positive votes (Table 1). Dissent from the consensus statements was captured by minority reports that were solicited from attendees at the conclusion of Roundtable I. In general, these reports reflected continued ambivalence about wording, technical accuracy, and necessity of a consensus statement.
Roundtable II was structured differently from Roundtable I to facilitate conversation both within and between the stakeholder groups (social scientists/humanists/community representatives, genetic genealogists, ancestry testing companies, and geneticists). Specifically, in Roundtable II there were four sessions of stakeholder group discussions followed by four sessions of mixed-stakeholder groups and then a review in a plenary session with all attendees. As with Roundtable I, groups were instructed to accept each guideline as is, edit the guideline, or develop a new guideline. Roundtable II resulted in reduction of the six draft guidelines to five. More than 80% of attendees agreed with four guidelines, and no guideline received less than 76% of positive votes (Table 2). To capture dissent from the guidelines, minority reports were solicited from attendees at the conclusion of Roundtable II. No minority reports were received. Below we present each guideline accompanied by a summary of comments concerning the importance of the guideline, our reasons for including the guideline, further explanations that are needed, limitations of the guideline, and suggestions for best practices relevant to the guideline.
This guideline is included to provide context to the changing nature of the field to consumers and researchers alike; to acknowledge the potential benefits and harms to individuals and groups; to emphasize the wide-ranging applications of genetic ancestry testing; and to stress that caution should be taken when any entity communicates results. Genetic ancestry inference affects the public’s confidence in genetic testing in general and vice versa, even if the methods, analysis, and resulting information gleaned for the analysis and application are quite different. As noted by Nelson (2016, at 81), “DNA spillover occurs when an individual’s experience with one domain of genetic analysis informs his or her understanding of other forms of it or authorizes its use in another domain.” So, it is important to make assumptions underlying genetic ancestry inference transparent and understandable upfront and to distinguish the features of this type of genetic test so that genetic ancestry inference does not unjustifiably undermine or, alternatively, unnecessarily bolster the public’s confidence in or willingness to consider or trust other types of genetic information (e.g., results of genetic testing for Mendelian conditions).
Further explanation is needed for this guidance, as it does not define validation or what specific measures are expected or steps to be taken. First, the guideline does not articulate how proficiency testing would best or most reasonably be achieved. Establishing an accepted proficiency testing approach would require substantial work (Box 1). Additionally, the guideline does not stipulate what information about reference populations is necessary for meaningful disclosure. At the very least, transparency about reference populations used should include their size, geographic location, level of population inclusivity, and how the markers used in genetic ancestry panels were selected, validated, and sometimes excluded to optimize a workable model of homogeneity in the reference populations being compared.
Identifiers are not uniform across geopolitical boundaries and do not remain constant over time. The instability of identifiers in the United States Census is well known, and common practices to aggregate and disaggregate distinct concepts of ethnicity, country of origin, and nationality into one or more Office of Management and Budget (OMB) race categories or to synthesize global data further complicate the matter (e.g., OMB,, Institute of Medicine,,,,,,, Morning,,,,,,, Villarroel et al.,,,,,,, Popejoy et al.,,,,,,, Byeon et al.,,,,,,). Terminology used with genetic ancestry inference must be as clear, accurate, and precise as possible to promote understanding. For example, rather than describing a DNA sample or data with merely a regional geographic descriptor (e.g., West African), it might be useful to have additional information such as self-identification (e.g., Yoruba), place of collection (e.g., Ibadan, Nigeria), and language or dialect. It would also be helpful if, to the extent practicable, samples and reference populations were accompanied by a researched description providing further reading for users on the historical emergence of each reference population. This step would help to preclude tendencies that “fossilize” groups as static, which is especially needed to broaden conceptions of non-Western and marginalized peoples. Such descriptions might include dynamics that have shaped groups’ complex histories and current social practices. This is to emphasize Ogundiran’s point regarding the history of the Yoruba: that identity making is a process (see, e.g., Ogundiran,,, Law,,, and Matory,,). This guideline is included to ensure that consumers can make informed choices about different genetic ancestry tests and better understand why test results might differ between platforms. Moreover, its inclusion reflects the roundtable participants’ recognition that misinterpretation and overgeneralizations, enabled by loose and inconsistent terminology unmoored from history, can contribute to misunderstandings of other people, social discrimination, and racism that must be acknowledged, prevented, and mitigated.
Subsequent to the roundtable discussions, the National Academies of Sciences, Engineering, and Medicine (NASEM) took steps toward developing and recommending best practices for use of population descriptors not only in genetic ancestry inferences but also in human genetics and genomics research more broadly. In 2021, NASEM established an ad hoc committee tasked with examining population descriptors (such as race, ethnicity, and genetic ancestry) in genomics research and offering “best practices” including recommendations for “culturally responsive methods and common data elements” that could enable the harmonization of population descriptors used in genomics research within and beyond the United States.
This guideline’s importance is to protect consumers and study participants from the complex web of third-party interests and varying regulations that intersect with genetic ancestry testing and information. It is intended to enable consumers to make informed decisions about genetic ancestry tests and sharing their data directly with others, whether within an ancestry testing company’s website or more broadly through online publication elsewhere. The guideline also is important in its recognition that there are potential benefits and risks of harm that can occur at the individual level and at familial, community, or broader social levels. For example, for groups in the United States that have been oppressed and had their “roots,” cultures, and actual ancestors purposefully eradicated, actively erased, or historically concealed from them, the acquisition of genetic ancestry information could affect not only the connections that individuals make with the past but also the viability of connections that individuals pursue in the present and future. Unexpected outcomes from DTC genetic testing are not infrequent, and, in most cases, these outcomes involve kinship rather than ancestral origins (e.g., Law). Additionally, this guideline is important because ancestry inference results might be unexpected or disruptive to an individual’s or group’s understanding of themselves. Individuals and families should be aware of the limitations to genetic privacy and understand that their DNA samples or data might be used in other contexts, such as law enforcement or other governmental agencies (e.g., Guerrini et al.). (While law enforcement agencies’ use of resources made available by DTC genetic ancestry testing was a possibility at the time the roundtables were held, it was not until years after the roundtables that news of investigative genetic genealogy to catch California’s Golden State Killer brought widespread media attention to the issue [e.g., Zhang,, Speakers et al.,)
This guideline reflects the roundtable participants’ recognition (1) of variation in perceived and potential benefits and risks associated with genetic ancestry testing that might impact either individuals or socially-ascribed groups and (2) that it is an ethical responsibility to communicate these possibilities to the potential test-takers prior to the DNA collection and analysis. The issue of third-party uses of ancestry data and the variation in regulations governing data security and privacy increase the potential risk of harm to consumers and the need for protections. Related to this is the pervasive commercial interest in the digital age that requires consumer confidence in mechanisms for privacy and consensual use of data perceived as personal information. Following the roundtables of 2013 and 2015, considerable privacy law scholarship and data protection policy developments have materialized in the genetics community,,,,,,,,,,,,,,, and society more broadly. These developments, discussed further below, have ongoing implications for the responsible collection, storage, and use of genetic and genomic data.
The recommendations regarding communication and translation in this guideline stem from a fundamental difference of opinion regarding the impact of genetic ancestry inference/estimation. One area of agreement among the roundtables’ diverse stakeholders was the need for greater transparency and education, which hopefully will enable consumers and prospective study participants (whom researchers might offer opportunities to receive genetic ancestry information as a study benefit) to make informed decisions about whether to obtain an ancestry test. Communication and education are shared responsibilities that can be fulfilled in several ways but are dependent upon available resources. This guideline underscores the importance of ongoing efforts to improve communication and education while acknowledging the tensions commonly observed between those in marketing departments seeking to puff products and services with colorful commentary to increase sales and interest and the perceived “dull” or black-and-white scientific state of knowledge. Table 3 provides a comprehensive, but not necessarily exhaustive, list of various types of information that can be learned from genetic ancestry testing, which could inform the development or enhancement of educational tools for consumers and other users of genetic ancestry information.
Since the roundtable discussions, scholarly work examining genetic ancestry inference, descriptions of human variation, and impacts of genetic ancestry testing have continued;,,,,,,,,,,,,,,, industry practices for DTC genetic ancestry inference have changed (for a list of active and inactive DTC companies offering genetic ancestry testing, see https://isogg.org/wiki/List_of_DNA_testing_companies); and some genetic genealogy standards have emerged. Policy and scholarly developments—for example, regarding privacy harms, data justice and dataveillance concerns, attention brought to Indigenous data sovereignty, and calls in the United States for comprehensive (rather than sector-specific) approaches to personal data protection as well as modernized rules for data access and increased interoperability,,,—have substantial implications for the refinement and implementation of guidelines for genetic ancestry inference and addressing matters of genetic privacy. In addition to the changing state laws for genetic information privacy specifically (e.g., Florida’s Protecting DNA Privacy Act, H.B. 1189, enacted in 2021; Utah’s Genetic Information Privacy Act, S.B. 227, enacted in 2021; Wyoming’s Genetic Data Privacy Act, H.B. 86, enacted in 2022; and Kentucky’s Genetic Information Privacy Act, H.B. 502, enacted in 2022) and personal data protection generally (e.g., the California Privacy Rights Act, Proposition 24, approved by CA voters in 2020; the Colorado Privacy Act, S.B. 21-1980, enacted in 2021; and the Virginia Consumer Data Protection Act, H.B. 2307/S.B. 1392, enacted in 2021), agencies such as the Federal Trade Commission have been increasingly active in ensuring that data practices are not unfair or deceptive or unreasonably lax with regard to privacy and security measures. Those engaged in genetic ancestry inference—whether as members of the DTC industry or academic research—will need to pay careful attention to shifting data governance expectations of individuals and obligations imposed implicitly or explicitly by policymakers.
Sections
"[{\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"bib1\", \"bib2\", \"bib3\", \"bib4\", \"bib5\", \"bib6\", \"bib7\", \"bib8\", \"bib9\", \"bib10\", \"bib11\", \"bib12\", \"bib13\", \"bib14\", \"bib15\", \"bib16\", \"bib17\", \"bib18\", \"bib19\"], \"section\": \"Introduction\", \"text\": \"Genetic ancestry inference is commonly used by researchers (e.g., to control for population stratification, explore population history, etc.), sought by individuals via direct-to-consumer (DTC) genetic testing companies to learn more about their genealogical history, geographic origins, and population affiliations, and contemplated by precision health initiatives as a means to \\u201creturn value\\u201d or otherwise engage patient-participants. Both research findings and individual DTC results are often featured in the print and broadcast media. Genetic ancestry inference is thus used across a wide variety of settings, with different goals, assumptions, methods, and claims of accuracy and validity. It is therefore not surprising that there has been considerable disagreement among diverse stakeholders about the merits, limitations, utility, and impact of genetic ancestry inference. Consequently, efforts by any individual stakeholder group to advocate for standards or regulation have met with little success. The need for standards and other guidance has never been greater, as the popularity of DTC genetic ancestry testing continues to expand, members of Congress have expressed concern, controversial applications of genetic ancestry information continue to be explored (e.g., forensic or investigative genetic genealogy;,,,,, immigration decisions;, political posturing;, medical school admissions; entitlement eligibility;, and social identity and belonging,,,), and society has little choice but to confront whether, how, and when it is appropriate to rely upon anyone\\u2019s genetic ancestry information.\"}, {\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"bib20\"], \"section\": \"Introduction\", \"text\": \"In 2008 the American Society of Human Genetics (ASHG) convened a task force to study issues emerging from genetic ancestry inference in academia and industry and to explore a constructive response to the need for more transparency and discussion about what genetic ancestry inference entails, as well as how it works and what it can and cannot do. The ASHG Board of Directors approved an ASHG position statement developed by the task force and the Society\\u2019s Social Issues Committee on ancestry inference that called attention to motivations, technical accuracy and reliability of results, health implications, societal and personal implications, proprietary databases, communication of limitations and potential impacts, public and personal education, interdisciplinary collaboration, and mechanisms for accountability (https://www.ashg.org/wp-content/uploads/2008/11/Statement-20081311-ASHGAncestryTesting.pdf) and approved an ASHG White Paper that provided recommendations aimed at addressing these issues.\"}, {\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"tbl1\", \"tbl2\"], \"section\": \"Introduction\", \"text\": \"One of the recommendations of the task force was to convene a diverse group of stakeholders and develop guidelines for genetic ancestry inference that would inform research and commercial applications of ancestry testing. The long-term goal was to develop the precursors to best practices for inferring genetic ancestry and guidelines for the uses and reporting of genetic ancestry testing results. A planning committee was formed consisting of two Chairpersons (C.D.R. and M.J.B.), representatives of human population geneticists, the DTC ancestry testing industry, scholars in ethical and social implications of human genetics, and consumers of ancestry testing (e.g., genetic genealogists), and it organized a \\u201croundtable\\u201d to develop consensus statements and guidelines for genetic ancestry inference. A first meeting (i.e., Roundtable I) was held in Washington, DC in September 2013. There were 65 participants representing seven stakeholder groups: population geneticists, DTC ancestry testing companies, social and behavioral scientists, humanists, clinicians, community representatives, and consumer groups including genealogical associations/societies. The participants generated 22 \\u201cconsensus\\u201d statements\\u2014defined as statements accepted by a majority but not all participants\\u2014about the uses, methods, and outcomes of genetic ancestry inference (Table\\u00a01). Critical dissent and constructive criticisms were encouraged to ensure that all stakeholders had a \\u201cvoice\\u201d and that multiple perspectives\\u2014even those that were highly dissenting\\u2014were considered. Reports from those in the minority were solicited. Several statements were edited for clarity and grammar in subsequent email exchanges among participants. A second roundtable meeting (i.e., Roundtable II) was held in Durham, NC in May 2015 to compose, based upon these 22 consensus statements, a set of guidelines (Table\\u00a02) for ancestry inference that would serve as a template for the development of best practices. There were 49 participants in this second meeting, including 40 attendees from the first roundtable meeting.\"}, {\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"tbl1\", \"tbl1\"], \"section\": \"\\u201cConsensus\\u201d statements (Roundtable I)\", \"text\": \"Roundtable I resulted in an expansion of the eight draft consensus statements to 22 (Table\\u00a01), reflecting robust discussion and reactions to the questions that accompanied the draft statements. Clearly, it was often the case that discussion identified that original draft statements did not adequately capture the complexity of the questions posed and therefore required further elaboration. In several instances a consensus statement was deemed obvious, and therefore unnecessary, to one stakeholder group but was simultaneously judged by another stakeholder group to be unobvious and important. Eighty-five percent or more of attendees agreed with 15 statements, and no statement received less than 73% of positive votes (Table\\u00a01). Dissent from the consensus statements was captured by minority reports that were solicited from attendees at the conclusion of Roundtable I. In general, these reports reflected continued ambivalence about wording, technical accuracy, and necessity of a consensus statement.\"}, {\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"tbl2\"], \"section\": \"Guidelines (Roundtable II)\", \"text\": \"Roundtable II was structured differently from Roundtable I to facilitate conversation both within and between the stakeholder groups (social scientists/humanists/community representatives, genetic genealogists, ancestry testing companies, and geneticists). Specifically, in Roundtable II there were four sessions of stakeholder group discussions followed by four sessions of mixed-stakeholder groups and then a review in a plenary session with all attendees. As with Roundtable I, groups were instructed to accept each guideline as is, edit the guideline, or develop a new guideline. Roundtable II resulted in reduction of the six draft guidelines to five. More than 80% of attendees agreed with four guidelines, and no guideline received less than 76% of positive votes (Table\\u00a02). To capture dissent from the guidelines, minority reports were solicited from attendees at the conclusion of Roundtable II. No minority reports were received. Below we present each guideline accompanied by a summary of comments concerning the importance of the guideline, our reasons for including the guideline, further explanations that are needed, limitations of the guideline, and suggestions for best practices relevant to the guideline.\"}, {\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"bib21\"], \"section\": \"GUIDELINE\", \"text\": \"This guideline is included to provide context to the changing nature of the field to consumers and researchers alike; to acknowledge the potential benefits and harms to individuals and groups; to emphasize the wide-ranging applications of genetic ancestry testing; and to stress that caution should be taken when any entity communicates results. Genetic ancestry inference affects the public\\u2019s confidence in genetic testing in general and vice versa, even if the methods, analysis, and resulting information gleaned for the analysis and application are quite different. As noted by Nelson (2016, at 81), \\u201cDNA spillover occurs when an individual\\u2019s experience with one domain of genetic analysis informs his or her understanding of other forms of it or authorizes its use in another domain.\\u201d So, it is important to make assumptions underlying genetic ancestry inference transparent and understandable upfront and to distinguish the features of this type of genetic test so that genetic ancestry inference does not unjustifiably undermine or, alternatively, unnecessarily bolster the public\\u2019s confidence in or willingness to consider or trust other types of genetic information (e.g., results of genetic testing for Mendelian conditions).\"}, {\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"tbox1\"], \"section\": \"GUIDELINE\", \"text\": \"Further explanation is needed for this guidance, as it does not define validation or what specific measures are expected or steps to be taken. First, the guideline does not articulate how proficiency testing would best or most reasonably be achieved. Establishing an accepted proficiency testing approach would require substantial work (Box 1). Additionally, the guideline does not stipulate what information about reference populations is necessary for meaningful disclosure. At the very least, transparency about reference populations used should include their size, geographic location, level of population inclusivity, and how the markers used in genetic ancestry panels were selected, validated, and sometimes excluded to optimize a workable model of homogeneity in the reference populations being compared.\"}, {\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"bib22\", \"bib23\", \"bib22\", \"bib23\", \"bib24\", \"bib25\", \"bib26\", \"bib27\", \"bib28\", \"bib22\", \"bib23\", \"bib24\", \"bib25\", \"bib26\", \"bib27\", \"bib28\", \"bib22\", \"bib23\", \"bib24\", \"bib25\", \"bib26\", \"bib27\", \"bib28\", \"bib22\", \"bib23\", \"bib24\", \"bib25\", \"bib26\", \"bib27\", \"bib28\", \"bib22\", \"bib23\", \"bib24\", \"bib25\", \"bib26\", \"bib27\", \"bib28\", \"bib29\", \"bib30\", \"bib31\", \"bib29\", \"bib30\", \"bib31\", \"bib29\", \"bib30\", \"bib31\"], \"section\": \"GUIDELINE\", \"text\": \"Identifiers are not uniform across geopolitical boundaries and do not remain constant over time. The instability of identifiers in the United States Census is well known, and common practices to aggregate and disaggregate distinct concepts of ethnicity, country of origin, and nationality into one or more Office of Management and Budget (OMB) race categories or to synthesize global data further complicate the matter (e.g., OMB,, Institute of Medicine,,,,,,, Morning,,,,,,, Villarroel et\\u00a0al.,,,,,,, Popejoy et\\u00a0al.,,,,,,, Byeon et\\u00a0al.,,,,,,). Terminology used with genetic ancestry inference must be as clear, accurate, and precise as possible to promote understanding. For example, rather than describing a DNA sample or data with merely a regional geographic descriptor (e.g., West African), it might be useful to have additional information such as self-identification (e.g., Yoruba), place of collection (e.g., Ibadan, Nigeria), and language or dialect. It would also be helpful if, to the extent practicable, samples and reference populations were accompanied by a researched description providing further reading for users on the historical emergence of each reference population. This step would help to preclude tendencies that \\u201cfossilize\\u201d groups as static, which is especially needed to broaden conceptions of non-Western and marginalized peoples. Such descriptions might include dynamics that have shaped groups\\u2019 complex histories and current social practices. This is to emphasize Ogundiran\\u2019s point regarding the history of the Yoruba: that identity making is a process (see, e.g., Ogundiran,,, Law,,, and Matory,,). This guideline is included to ensure that consumers can make informed choices about different genetic ancestry tests and better understand why test results might differ between platforms. Moreover, its inclusion reflects the roundtable participants\\u2019 recognition that misinterpretation and overgeneralizations, enabled by loose and inconsistent terminology unmoored from history, can contribute to misunderstandings of other people, social discrimination, and racism that must be acknowledged, prevented, and mitigated.\"}, {\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"bib32\"], \"section\": \"GUIDELINE\", \"text\": \"Subsequent to the roundtable discussions, the National Academies of Sciences, Engineering, and Medicine (NASEM) took steps toward developing and recommending best practices for use of population descriptors not only in genetic ancestry inferences but also in human genetics and genomics research more broadly. In 2021, NASEM established an ad hoc committee tasked with examining population descriptors (such as race, ethnicity, and genetic ancestry) in genomics research and offering \\u201cbest practices\\u201d including recommendations for \\u201cculturally responsive methods and common data elements\\u201d that could enable the harmonization of population descriptors used in genomics research within and beyond the United States.\"}, {\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"bib30\", \"bib3\", \"bib33\", \"bib34\", \"bib33\", \"bib34\"], \"section\": \"GUIDELINE\", \"text\": \"This guideline\\u2019s importance is to protect consumers and study participants from the complex web of third-party interests and varying regulations that intersect with genetic ancestry testing and information. It is intended to enable consumers to make informed decisions about genetic ancestry tests and sharing their data directly with others, whether within an ancestry testing company\\u2019s website or more broadly through online publication elsewhere. The guideline also is important in its recognition that there are potential benefits and risks of harm that can occur at the individual level and at familial, community, or broader social levels. For example, for groups in the United States that have been oppressed and had their \\u201croots,\\u201d cultures, and actual ancestors purposefully eradicated, actively erased, or historically concealed from them, the acquisition of genetic ancestry information could affect not only the connections that individuals make with the past but also the viability of connections that individuals pursue in the present and future. Unexpected outcomes from DTC genetic testing are not infrequent, and, in most cases, these outcomes involve kinship rather than ancestral origins (e.g.,\\u00a0Law). Additionally, this guideline is important because ancestry inference results might be unexpected or disruptive to an individual\\u2019s or group\\u2019s understanding of themselves. Individuals and families should be aware of the limitations to genetic privacy and understand that their DNA samples or data might be used in other contexts, such as law enforcement or other governmental agencies (e.g.,\\u00a0Guerrini et\\u00a0al.). (While law enforcement agencies\\u2019 use of resources made available by DTC genetic ancestry testing was a possibility at the time the roundtables were held, it was not until years after the roundtables that news of investigative genetic genealogy to catch California\\u2019s Golden State Killer brought widespread media attention to the issue [e.g., Zhang,, Speakers et\\u00a0al.,)\"}, {\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"bib35\", \"bib36\", \"bib37\", \"bib38\", \"bib39\", \"bib40\", \"bib41\", \"bib42\", \"bib43\", \"bib44\", \"bib45\", \"bib46\", \"bib47\", \"bib48\", \"bib49\", \"bib50\"], \"section\": \"GUIDELINE\", \"text\": \"This guideline reflects the roundtable participants\\u2019 recognition (1) of variation in perceived and potential benefits and risks associated with genetic ancestry testing that might impact either individuals or socially-ascribed groups and (2) that it is an ethical responsibility to communicate these possibilities to the potential test-takers prior to the DNA collection and analysis. The issue of third-party uses of ancestry data and the variation in regulations governing data security and privacy increase the potential risk of harm to consumers and the need for protections. Related to this is the pervasive commercial interest in the digital age that requires consumer confidence in mechanisms for privacy and consensual use of data perceived as personal information. Following the roundtables of 2013 and 2015, considerable privacy law scholarship and data protection policy developments have materialized in the genetics community,,,,,,,,,,,,,,, and society more broadly. These developments, discussed further below, have ongoing implications for the responsible collection, storage, and use of genetic and genomic data.\"}, {\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"tbl3\"], \"section\": \"GUIDELINE\", \"text\": \"The recommendations regarding communication and translation in this guideline stem from a fundamental difference of opinion regarding the impact of genetic ancestry inference/estimation. One area of agreement among the roundtables\\u2019 diverse stakeholders was the need for greater transparency and education, which hopefully will enable consumers and prospective study participants (whom researchers might offer opportunities to receive genetic ancestry information as a study benefit) to make informed decisions about whether to obtain an ancestry test. Communication and education are shared responsibilities that can be fulfilled in several ways but are dependent upon available resources. This guideline underscores the\\u00a0importance of ongoing efforts to improve communication and education while acknowledging the tensions commonly observed between those in marketing departments seeking to puff products and services with colorful commentary to increase sales and interest and the perceived \\u201cdull\\u201d or black-and-white scientific state of knowledge. Table\\u00a03 provides a comprehensive, but not necessarily exhaustive, list of various types of information that can be learned from genetic ancestry testing, which could inform the development or enhancement of educational tools for consumers and other users of genetic ancestry information.\"}, {\"pmc\": \"PMC9926022\", \"pmid\": \"\", \"reference_ids\": [\"bib79\", \"bib80\", \"bib81\", \"bib82\", \"bib83\", \"bib84\", \"bib85\", \"bib86\", \"bib87\", \"bib88\", \"bib89\", \"bib90\", \"bib91\", \"bib92\", \"bib93\", \"bib94\", \"bib95\", \"bib96\", \"bib97\", \"bib44\", \"bib98\", \"bib99\", \"bib100\", \"bib101\", \"bib102\"], \"section\": \"Discussion\", \"text\": \"Since the roundtable discussions, scholarly work examining genetic ancestry inference, descriptions of human variation, and impacts of genetic ancestry testing have continued;,,,,,,,,,,,,,,, industry practices for DTC genetic ancestry inference have changed (for a list of active and inactive DTC\\u00a0companies offering genetic ancestry testing, see https://isogg.org/wiki/List_of_DNA_testing_companies); and some genetic genealogy standards have emerged. Policy and scholarly developments\\u2014for example, regarding privacy harms, data justice and dataveillance concerns, attention brought to Indigenous data sovereignty, and calls in the United States for comprehensive (rather than sector-specific) approaches to personal data protection as well as modernized rules for data access and increased interoperability,,,\\u2014have substantial implications for the refinement and implementation of guidelines for genetic ancestry inference and addressing matters of genetic privacy. In addition to the changing state laws for genetic information privacy specifically (e.g., Florida\\u2019s Protecting DNA Privacy Act, H.B. 1189, enacted in 2021; Utah\\u2019s Genetic Information Privacy Act, S.B. 227, enacted in 2021; Wyoming\\u2019s Genetic Data Privacy Act, H.B. 86, enacted in 2022; and Kentucky\\u2019s Genetic Information Privacy Act, H.B. 502, enacted in 2022) and personal data protection generally (e.g., the California Privacy Rights Act, Proposition 24, approved by CA voters in 2020; the Colorado Privacy Act, S.B. 21-1980, enacted in 2021; and the Virginia Consumer Data Protection Act, H.B. 2307/S.B. 1392, enacted in 2021), agencies such as the Federal Trade Commission have been increasingly active in ensuring that data practices are not unfair or deceptive or unreasonably lax with regard to privacy and security measures. Those engaged in genetic ancestry inference\\u2014whether as members of the DTC industry or academic research\\u2014will need to pay careful attention to shifting data governance expectations of individuals and obligations imposed implicitly or explicitly by policymakers.\"}]"
Metadata
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