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Towards inclusive research: diverse datasets and cohort representation

Calvin Wai-Loon Ho

University of Hong Kong

Maili Raven-Adams

Nuffield Council on Bioethics, UK

Alham Saadat

Broad Institute, USA

Laura Arbour

Silent Genomes Project, Canada

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Considerations for How Genetic and Genomic Researchers Should Approach Thinking about Diversity in Data

Speaker: Maili Raven-Adams [former co-lead]

Regulatory and Ethics Work Stream

ga4gh.org

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Overview of Presentation

The Issue
The Policy

Thank you to Anna Lewis, Tina Hernandez-Boussard (co-leads), Beatrice Kaiser and Diya Uberoi and the entire Diversity in Datasets subgroup!!

ga4gh.org

In this presentation I will be representing the hard work that the ‘diversity in dataset’s’ subgroup of REWS has put in to develop their policy on ‘Considerations for How Genetic and Genomic Researchers Should Approach Thinking about Diversity in Data’

This has been a huge group effort, and has been led by Anna Lewis and Tina Hernandez-Boussard [who could not be here today], as well as myself before I moved jobs.

The policy itself has gone through multiple iterations due to being reviewed by the subgroup, REWS and wider public comment.

The current version which I have included as a QR on the screen went for REWS approval this week and passed, so will be looking for steering committee approval as an official GA4GH deliverable at the next meeting after Plenary has finished.

Before I get into the thick of things, I wanted to say a huge congrats to the group for pulling the policy together. I have not been as involved as I would have hoped recently and it has really come along since I have left!

Also a special thanks to Beatrice and Diya for their hard work picking up where I left off!

In the next slides I will aim to discuss the issue we outline in our policy, and how the policy proposes researchers can respond to this.

This will be quite high level, as I don’t have time to go into some of the examples we have provided, but you can find further info in the text itself!

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The Issue

Many calls for diversity

BUT

little clarity on what ‘diversity’ means and how to achieve it

Conflation of ‘diversity’ and ‘representation’

Multiple dimensions of diversity are important.

E.g. genetic ancestry, sex and/or geography.

Problems with putting people in categories

One size does not fit all -

especially not internationally

ga4gh.org

In our policy we spend some time outlining some of the background to the issue we are trying to address

Topic 1: Many Calls for Diversity

Firstly, we recognise there are many different calls for diversity in genomic datasets out there – all aiming to ensure that the benefits of genetics and genomics can be realised for everyone equitably and reliably, without perpetuating the health inequalities we have today.

For example, most of you will have heard the commonly cited statistic showing that 86% of genomic studies were conducted only in individuals of European descent in 2021.

However, despite the importance of these calls for increased diversity in genomic datasets, we recognise that there is a lack of specificity about what is meant by ‘diversity’ and how to achieve this.

The issue here is that this can leave a lack of clarity for researchers and others wanting to address the problem.

Topic 2: Conflation of ‘Diversity’ and ‘Representation’

In these calls, there often seems to be a conflation between terms like ‘diversity’ and ‘representation’

Although we agree that representation can be important, and we certainly don’t have enough of it now, we recognise that there may be good reasons for a lack of representation

For example, to maximise some genomic projects, over-sampling individuals from recent genetic ancestries from Africa, compared to the rest of the world may be needed.

Topic 3: Multiple Dimensions of Diversity are Important

Additionally, there are multiple dimensions of diversity that it may be important for researchers to consider.

These obviously include genetic ancestry, which is what many of the calls for diversity in datasets are focused on.

Other factors that researchers may want to consider are sex or environmental factors such as the social determinants of health, like geography, which can outweigh factors, including genetic predisposition.

In each case, it is really important to get the concept of diversity right for a given project.

Topic 4: Problems with Putting People in Categories

The concepts and terms we use matter and can have ramifications that we need to be aware of.

We need to remain aware that the birth of genomics was intertwined with eugenics and unfortunate efforts to try and justify racism.

When looking at increasing diversity in datasets there are dangers of reinforcing the false notion that humans come in distinct biological types.

Lots of the calls to increase diversity in datasets focus on increasing ‘ancestry.’ However, without further clarification, this suffers from ambiguity that can be harmful.

Empirical work has shown some researchers use ‘ancestry’ as explicitly a biological term determined by genetic analysis while others understand ‘ancestry’ as a social phenomenon.

The problem with this, is that it can allow for the conflation of social and genetic categories, which can also lead to ignoring the impact of environmental ones

Researchers need to look at what they are actually interested in - for example, is it genetic similarity or is it ethnicity?

And so, we include that use of ‘genetic ancestry’ rather than just ‘ancestry’ should be adopted and researchers should be transparent about what is meant by the categories they adopt.

Topic 5: One Size Does Not Fit All

Lastly, providing one definition of ‘diversity’ will not work for everyone.

The contexts in which researchers are working vary substantially, for example, based on local cultural practices, the economy and whether research is embedded in healthcare or not

Because the goals of each research project will be different, the types of diversity that are important will vary for each research team.

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It is not enough to simply call for ‘diversity’ within datasets: There needs to be a way to understand what types of diversity matter (and why), and how to act on this understanding throughout the research process

ga4gh.org

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The Policy

Audience: Genetic and Genomic Researchers Type: A framework for addressing ‘diversity in datasets’

ga4gh.org

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Our Framing

There are complex reasons for the lack of diversity in data

Uphold a mandate for inclusive practices

Importance of data sharing

Equity often the most important concept

ga4gh.org

Throughout the policy we provide some key messages that frame our guidance.

Topic 1: Complex Reasons for Lack of Diversity

Firstly, we acknowledge that there are complex reasons for the lack of diversity in data.

This includes a well-founded lack of trust in genomics research based on instances of exploitation and cultural ignorance on the part of researchers, a fear of genetic discrimination and existing barriers to participating in research, such as language barriers and childcare and transport costs.

Helping researchers achieve the benefits of more diversity involves prioritising transparency, accountability, culturally appropriate behaviour, as well as recognition and respect for the role of marginalised communities participating in research.

Topic 2: Mandate for Inclusive Practices

Across the board we uphold there is a mandate for inclusive practices.

Researchers should make it as easy as they can for differently situated people to participate if they wish to do so - including respecting community practices and data governance, making considerate choices about language.

Topic 3: Importance of Data Sharing

We also highlight the importance of data sharing

Across genomic medicine, research results are optimized by integrating data from as many individuals as possible

This can be done by sharing data, which can in turn contribute to increasing the diversity researchers can access in available data.

However, data sharing needs to be done responsibly, recognizing human rights, other legislation and ethical guidelines which may limit what data can be shared.

Topic 4: Equity Most Important

We also recognise that equity will often be the most important concept when determining what dimensions of diversity are important and how to achieve it.

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What types of diversity are important?

Diversity in Data is a means to achieve ethical ends

Ethical norms:

Include public benefit, equity, justice and fairness, as well as fundamental human rights and the improvement of healthcare

Those who will be impacted by the researchers should be consulted, along with bioethicists and lawyers

ga4gh.org

The policy first outlines ways researchers can understand what types of diversity in data are important for their projects, keeping in mind that diversity in data is a means to achieve ethical ends.

Researchers should take the time to clarify the goal or goals of their project and consider how these align, or fail to align with ethical norms (such as public benefit, equity, justice and fairness), fundamental human rights and the improvement of healthcare.

To achieve this, we include that researchers should call on bioethicists, lawyers and local communities that will be impacted by their research, to support them

Researchers should then ask themselves, why is diversity in data important to achieve these goals. This should include considerations of who should be represented in the data, and what data points are most important to know about them.

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How to achieve diversity in data?

Benefit sharing is important and needs to be done responsibly

Find data

Collect data

Integrate data

Process and analyze data

Publish

Inform individual care

Store data

Share data

Concepts and Terminology

ga4gh.org

Secondly, the policy outlines a systematic way for how researchers can achieve the types of diversity they have identified as important for their project

Armed with some degree of clarity about the types of diversity in data needed to achieve the project goals, strategies will need to be consciously adopted throughout decision points along the data lifecycle

[Find lifecycle on the slide] Recognise in the policy that each stage of the lifecycle may not be relevant to each research project.

To achieve diversity, it is not just about who is in the sample.

Considerations include thinking about both the implication of choices and how to encourage benefit sharing, including building research capacity, equitable partnerships and avoiding helicopter science.

This benefit sharing needs to be done responsibly, developed with research participants and local communities and with awareness of where some forms of benefit sharing may be illegal.

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Consideration Examples

Concept and Terminology	Avoid reference just to “ancestry”, and instead refer to “genetic ancestry” if this is in fact what is meant.
Find Data	Attempt to identify datasets that adequately capture the different dimensions of diversity identified as important.
Collect Data	Identify culturally and contextually appropriate ways to recognize the value provided by participants, to the extent that this is allowed by the relevant local legal framework
Publish	Carefully state how results are expected to generalize or fail to generalize

ga4gh.org

We provide considerations required for all research projects. Some examples can be found on the slide.

This includes avoiding reference to just ‘ancestry’ and ensuring there are attempts to identify datasets that adequately capture the different dimensions of diversity identified as important.

Data should also be collected in a way that is culturally and contextually appropriate, with barriers to participation being identified and reduced – recognising the value provided by participants.

Another example is that care is needed when reporting results at publication.

Research that centres diversity in data can bring too much attention to the small amount of genetic variation that divides us. It can be used to tell over simplified stories about human groups and can contribute to stigmatisation of already marginalised groups.

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Two Examples

We use two examples to demonstrate how these considerations might work in practice:

Example 1: Minimising Reporting False Positive Pathogenic Variants [e.g. rare disease]

Example 2: The Clinical Impact of Differential Predictive Performance of Polygenic Scores

ga4gh.org

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Thank you

Contact us!

Maili: mraven-adams@nuffieldbioethics.org

Anna: acflewis@gmail.com

REWS: rews-coordinator@ga4gh.org

ga4gh.org

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Towards inclusive research: diverse datasets and cohort representation

Calvin Wai-Loon Ho

University of Hong Kong

Maili Raven-Adams

Nuffield Council on Bioethics, UK

Alham Saadat

Broad Institute, USA

Laura Arbour

Silent Genomes Project, Canada

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A Multi-dimensional Approach Towards Inclusion and Equity Biomedical Research

Alham Saadat

21 September 2023

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Inclusion, Diversity, Equity and Allyship (IDEA) Office

Scientific Equity:

(Alham Saadat)

Develop and implement strategies to make our science inclusive and equitable - ensuring that the benefits of biomedical research are shared by all.

Inclusive Culture & Community:

(Ana Foley)

Build an inclusive culture, where everyone feels that they belong and can reach their full potential.

Scientific Workforce Diversity:

(Gisselle Vélez-Ruiz)

Develop and implement pathways to expand and accelerate the diversity of future scientists.

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Scientific Equity

Scientific Equity:

Develop and implement strategies to make our science inclusive and equitable - ensuring that the benefits of biomedical research are shared by all.

Increase understanding of how decisions we make at all stages of research will impact health outcomes for people - particularly those that have been historically excluded, under-served, or harmed.

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Scientific Equity: four focus areas

Foster learning and discussions
Develop new bioethical capabilities and increase bioethical engagement
Develop and share educational resources, good practices and tool kits
Build collaborations with organizations engaged in similar work

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Fostering learning and discussions: EBM Series

Thoughtful Use of “Population Descriptors” in Genomics Research

Nasa Sinnott-Armstrong

Fred Hutch Cancer Center

Sex and Gender Minority Inclusion in Research

Katrina Claw

University of Colorado

Genevieve Wojcik

John Hopkins

Anna Lewis

Brigham and Women’s Hospital, Harvard, and Broad Institute

Past EBM seminars:

Genomics Research in African Diaspora Populations

Shawneequa Callier

George Washington University

Research as Relational: Community Engagement for Equity in Precision Medicine Research

Sandra Soo-Jin Lee

Colombia University

Recordings available on the Equity in Biomedicine YouTube channel!

EBM is an institute-wide interactive meeting that focuses on critical issues related to equity and representation in biomedical research, especially as it applies to genomics research and precision medicine. Speakers dive into the equal or unequal social implications of their work: Who is affected? How are they affected? Why? The overall goal of this series is to foster discussions about equity and inspire Broad scientists and trainees to reflect on the social impact of their own research.

The next discussion will take place later this month and focuses on Thougthful Use of Population Descriptors in Genetics and Genomics Research. Panelists include members of the NASEM working group, Katrina Claw and Gen Wojcik, that were charged with providing guidance on how to use of terms like race, ethnicity, and genetic ancestry precisely and how to avoid problematic essentialist links to biology that propagate incorrect and racist notions that discrete genetic groups exist. Anna Lewis, who has written extensively on topic, will be leading the discussion.

Previous speakers for this semester included statistical geneticist Nasa Sinnott-Armstrong presenting on how we can move towards Sex and Gender Minoroty Inclusion in Research. Recording for these and other EBM talks can be found on the EBM Youtube page.

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Fostering learning and discussions: EBM Series

Upcoming EBM Seminars:

Increased Genetic Diversity Needed in Cell Models and CRISPR Experimental Tools

Jesse Boehm, Lindy Barrett, Ralda Nehme (Broad Institute)

Nov 30th, 2023

12:00 pm - 1:00 pm EST

Population Genetics and the Responsibility to Counter Nefarious Use of Research

Sohini Ramachandran (Brown University)

Feb 8, 2024

9:30-11:00am EST

Minority Health and Health Disparities Research

Eliseo J. Pérez-Stable, Director National Institute on Minority Health and Health Disparities, NIH

Feb 22, 2024

3:00-4:00pm EST

Upcoming seminars will be open to the public!

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New bioethical capabilities and increased bioethical engagement: Broad Bioethics Initiative (BBI)

Idea that with the privilege to work on cutting-edge research comes responsibility

Bioethical engagement at the Broad can:

Support bioethics domains beyond regulatory domains that require collaborative problem solving among administrative compliance functions, ethicists, and scientists.

Help produce better scientific research, through e.g. clarifying which concepts can help align both scientific needs and ethical ends.

Produce leading and impactful bioethical scholarship: Broad leads in science and technology development, it has the opportunity to also play a role in leading considerations of how these developments can and should impact people’s lives.

Co-led with Broad colleagues

Anna Lewis and Rosy Hosking

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BBI: examples of bioethics domains for the work

Return of results and benefit to research participants and their communities
Bioethical considerations when increasing research participation from underrepresented groups in under-resourced settings
Consideration of what types of diversity matter for which types of genetic research
Responsible data sharing beyond regulatory
Bioethical issues surrounding Artificial Intelligence/Machine Learning

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Vision for the BBI: three strands of work

A bioethics consultancy service, available to all Broadies, aimed at providing useful and practical advice on the issue raised.

Educational offerings, aimed at 1) providing an overview of how to identify and engage with bioethical issues in their work, 2) deep dives into particular topic areas (e.g. scientific racism).

Projects, initiated by Broad scientists in collaboration with bioethicists, aimed at producing state-of-the-art, and practical, bioethics advice and scholarship.

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IDEA approach: inclusive and equitable biomedical research requires multi-dimensional approaches

Scientific Equity:

Develop and implement strategies to make our science inclusive, representative, and equitable - ensuring that the benefits of biomedical research are shared by all.

Inclusive Culture & Community:

Build an inclusive culture, where everyone feels that they belong and can reach their full potential.

Scientific Workforce Diversity:

Develop and implement pathways to expand and accelerate the diversity of future scientists.

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Acknowledgements

Chief Equity Officer

René Salazar (1960-2022)

Chief Equity Officer

Kedrick Perry

Associate Director,

Scientific Workforce Diversity

Gisselle Vélez-Ruiz

IDEA Team

Broad Bioethics Initiative

BWH, GA4GH, Broad

Anna Lewis

Broad, Biology of Trauma

Rosy Hosking

Reach out if you would like to learn

more or collaborate!

asaadat@broadinstitute.org

Associate Director,

Culture and Community

Ana Foley

Senior Administrator,

IDEA Office

Lois Doolittle

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Towards inclusive research: diverse datasets and cohort representation

Calvin Wai-Loon Ho

University of Hong Kong

Maili Raven-Adams

Nuffield Council on Bioethics, UK

Alham Saadat

Broad Institute, USA

Laura Arbour

Silent Genomes Project, Canada

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PUTTING EPISTEMIC JUSTICE AS INCLUSIVITY AT THE HEART OF GENOMIC RESEARCH��11^TH PLENARY OF THE GLOBAL ALLIANCE OF GENOMICS & HEALTH�SAN FRANCISCO, 21 SEPTEMBER 2023

Calvin W.L. Ho

Associate Professor of Law & Co-Director,

HKU Centre for Medical Ethics & Law

cwlho@hku.hk - @CalvinWLHo

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Epistemic Justice

Concern with obstruction to generation of knowledge by social inequality

Timely discussion by GA4GH REWS on the need to look beyond “ancestral diversity” in thinking about diversity in data
Approach proposed by REWS’s proposed policy on data diversity:

Identifies what types of diversity are important in data by considering the outcome that this diversity is designed to deliver (insight: diversity is linked to achieving equity and not only about representativeness)
Proposes a way for researcher to achieve the benefits that the identified diversity is designed to enable
Adopts a data lifecycle approach in engaging with complex reasons for the lack of diversity present in current data

Epistemic injustice arises when participation in / influence over knowledge generating processes are not fairly / equitably distributed among members of the “genomics community” (Query: who counts as a member of this epistemic community?).

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Testimonial Epistemic Justice

Epistemic injustice arises when the credibility of a speaker’s testimony being discounted by her interlocutor due to prejudice against her social identity
Testimonial nature: The speaker is harmed in her capacity as a knower or a valid source of knowledge. The speaker could lose self-confidence or the intellectual capacity of forming beliefs.
Example (Boaz Miller & Meital Pinto (2022)): Differences in epistemic standards

Treating experience of dominant groups as universal vs. experience of disempowered groups as restricted.
Elevating certain academic education and official accreditation vs. Marginalizing uncredited experts.

Illustration (Julian Go (2020)): Scientific preference for universal generalizability could marginalize disempowered members of the scientific community. E.g. African American sociologists were not considered to have made substantial contributions to the field as their study of African American communities offered particularistic insights rather than universally generalizable ones.

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Hermeneutic Epistemic Justice

Testimonial epistemic injustice may become structural when institutional arrangements or practices continue to give effect to such exclusions.
Hermeneutic epistemic injustice:

Always structural
Points to the interpretive resources that a society lacks in order to make sense of important aspects of a speaker’s experience because she belongs to a social group that has been unfairly marginalised in meaning-making activities.
Includes differential access to the markers of credibility, ethnocentrism and shared reality biases.

As knowledge is social, social / power inequalities shape participation in, and influence over, genomic science as a knowledge-generating discourse.
Social diversity tends to improve collective epistemic performance, but measures are needed to mitigate obstacles like inter-group friction (Scott Page 2017).
Social diversity Cognitive diversity Multiple types of data / evidence Theoretical and evidential robustness

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Shared Reality Bias

Tendency for certain viewpoints or perspectives to converge based on groups of individuals who tend to interact frequently together.
When such groups of individuals and their viewpoints or perceptions are segregated along the same lines that define group inequalities, the shared reality bias tends to insulate members of advantaged groups from those who are systematically disadvantaged.
The viewpoint or perspective of the disadvantaged makes no sense to the advantaged because the interpretive resources developed by the latter are inadequate for understanding the experiences of those from whom they have been set apart.
Public health workers is not immune to prejudicial forms of reasoning, since they are social agents whose beliefs and worldviews are embedded in wider social and experiential contexts.

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Ten Hagen, K.G., Wolinetz, C., Clayton, J.A. et al. Community voices: NIH working toward inclusive excellence by promoting and supporting women in science. Nat Commun 13, 1682 (2022). https://doi.org/10.1038/s41467-022-28665-2

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Inclusiveness

Full & active engagement and participation of representatives of communities and relevant stakeholders across all levels
Essential to mobilize social capital, resources and adherence to public health and social measures
Essential to gain trust in governments and partners supporting pandemic prevention, preparedness, response and health systems recovery

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Article 9 (on R&D) in Pandemic Accord

Provisions relating to R&D highlight concerns with epistemic justice:

Build, strengthen and sustain capacities and institutions for R&D
Promoting greater sharing of knowledge and transparency of information
Encourage the participation of relevant stakeholders, including community-led and cross-sector collaboration
Promote, cooperate and strengthen knowledge translation and evidence-based communication tools and strategies
Develop strong, resilient national, regional and international, appropriately resourced research ecosystems, including national and global clinical research networks

See also provisions on access and benefit sharing (Article 12); regulatory strengthening (Article 14) and international collaboration and cooperation (Article 15)

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Conclusion: Putting Epistemic Justice at the Heart of Genomic Research

Link between data diversity and social diversity.
Inclusivity as a concern with epistemic justice in genomic research

What should count as an epistemic community in genomics?
Who are the putative members?
How does data represent (a) and (b), as well as link the two up?

Inclusiveness is also a bridging point to rights-based initiatives
Gives Expression to Progressive Realization

Equity-promoting moral institutions
Human rights core principles (Accountability; Equality and non-discrimination; Participation) & Human rights core elements (Progressive realisation using maximum available resources; Non-retrogression)

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Argument: Putting Epistemic Justice at the Heart of Genomic Research

Epistemic justice as an ethical concept – fair and equitable means by which certain claims acquire the status of ‘knowledge’ that sets them apart from opinion, speculation or informed guesses.
Inclusivity as a concern with epistemic justice in genomic research
Inclusiveness is also a bridging point to rights-based initiatives, including the one that is considered for the WHO-led pandemic accord that is under negotiation
Gives expression to progressive realization

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THANK YOU!

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Towards inclusive research: diverse datasets and cohort representation

Calvin Wai-Loon Ho

University of Hong Kong

Maili Raven-Adams

Nuffield Council on Bioethics, UK

Alham Saadat

Broad Institute, USA

Laura Arbour

Silent Genomes Project, Canada

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The Silent Genomes Project:

Addressing genomic inequity for, and with, Indigenous populations of Canada. �

Laura Arbour MD

Professor, UBC Dept of Medical Genetics

September 21, 2023

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THE ROAD TO INCLUSION-AN EXAMPLE FROM CANADA

Justifying inclusive genomics for Indigenous people of Canada
Operationalizing Indigenous involvement/partnership in the Silent Genomes project
Indigenous guidance and governance for a sustainable Indigenous background Variant library

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I acknowledge with respect the Songhees, Esquimalt, W̱SÁNEĆ and Coast Salish peoples on whose traditional territories I have the privilege to live, work, and play, and whose historical relationships with the land continue to this day.

I appreciate that we are currently on the unceded Ancestral homeland of the Ramaytush Ohlone peoples, who are the original inhabitants of the San Francisco Peninsula.

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Inuit:

53 communities

N=70,545

First Nations:

634 communities N=1,048,405

Métis:

N=624,220

5 % of the Canadian population are Indigenous.

There is great diversity within and between Indigenous groups

But in common there are challenges to access to health care, including genetic care

Statistics Canada 2021 census

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Geographic barriers: Remoteness of many communities
Poor access to clinical expertise at point of care to recognize genetic diseases and refer to medical genetics
Additional barriers

Racism in healthcare system
Long history of research transgressions
Indigenous populations not represented in variant reference databases

BARRIERS TO GENOMIC DIAGNOSIS & HEALTHCARE

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FOR INDIGENOUS PEOPLES, GENOMIC REFERENCE DATA IS ABSENT OR UNIDENTIFIED

(WHY IS THAT?)

Source : gnomAD

S. Correard-Derived from gnomAD 2022

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Indian (Havasupai) Tribe Wins Fight to Limit Research of Its DNA - THE NEW YORK TIMES, April 2010

GENETIC RESEARCHER USES NUU-CHAH-NULTH BLOOD FOR UNAPPROVED STUDIES IN GENETIC ANTHROPOLOGY- Ha-Shilth-Sa newspaper, Sept 2000

Pediatr Child Health Vol 19 No 2 February 2014

Trust

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INDIGENOUS CONCERNS ABOUT GENETICS/GENOMICS

Genetic cause may be considered stigmatizing
A specific genetic variant may identify a community
Data may be used for exploitative purposes (secondary research without consent, commercial/mainstream benefit while health disparities continue)

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ACCESS TO RARE DISEASE DIAGNOSIS IN INDIGENOUS POPULATIONS:�WHERE DO WE START? �

1 in 14 people have a rare disease, and a large proportion (~80%) of those will have a genetic basis. Based on population estimates, >100,000 Indigenous people in Canada will be affected

Frederiksen, S.D., Avramović, V., Maroilley, T. et al. Rare disorders have many faces: in silico characterization of rare disorder spectrum. Orphanet J Rare Dis 17, 76 (2022). https://ojrd.biomedcentral.com/articles/10.1186/s13023-022-02217-9

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GOALS: SILENT GENOMES

With Indigenous partners we are:

building a governance model for use of Indigenous genomic data
offered genomic diagnosis to Indigenous Children across Canada;
planning together, and building an Indigenous Background Variant Library (IBVL);
assessing the acceptance and effectiveness of the IBVL and the cost to the system, with and without.

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Funding awarded through Genome Canada’s Large-Scale Applied Research Project Competition

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ACTIVITY 1:

First Nations, Inuit And Métis Engagement, Governance, and Capacity Building

ACTIVITY 3:

Build an Indigenous

Background Variant Library

ACTIVITY 2:

Precision Diagnosis of Indigenous Children with Genetic Disorders

ACTIVITY 4: Economics of Genomic Diagnosis in Indigenous Populations

SILENT GENOMES PROJECT – 4 ACTIVITIES

www.bcchr.ca/silent-genomes-project

Dr. Nadine Caron

Dr. Wyeth Wasserman

Dr. Dean Regier

Dr. Anna

Lehman

Dr. Maja

Tarailo-Graovac

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Maile Tauali‘i, Ph.D.

Chairperson

Native Hawaiian

Kim Tallbear, Ph.D.

Sisseton-Wahpeton Oyate, SD

Nanibaa’ Garrison, PhD Navajo

Maui Hudson, Ph.D., Maori, New Zealand

Ngiare Brown M.D.,

Yuin Nation, Australia

Keolu Fox, Ph.D.,

Kanaka Maoli, Hawaii

Phil Wilcox, Ph.D.

Maori, New Zealand

OPPORTUNITIES: INTERNATIONAL INDIGENOUS GENOMICS ADVISORY COMMITTEE

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Silent Genomes team, including community members, Indigenous organizations

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ACTIVITY 1:

First Nations, Inuit And Métis Engagement, Governance, and Capacity Building

ACTIVITY 3:

Build an Indigenous

Background Variant Library

ACTIVITY 2:

Precision Diagnosis of Indigenous Children with Genetic Disorders

ACTIVITY 4: Economics of Genomic Diagnosis in Indigenous Populations

SILENT GENOMES PROJECT – 4 ACTIVITIES

www.bcchr.ca/silent-genomes-project

Dr. Nadine Caron

Dr. Wyeth Wasserman

Dr. Dean Regier

Dr. Anna

Lehman

Dr. Maja

Tarailo-Graovac

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ACTIVITY 3: IBVL DEVELOPMENT

Solenne Correard

Brittany Hewitson

Mohammed Abdallah

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Variant Catalogue Pipeline-Solenne Correard

Fastq 🡪 Allele frequencies (annotated)

4 independent modules :

Mapping
Mitochondrial variants
SNV/indels
Structural variants (inc. STR, MEI)

Tested on 100 WGS publicly available

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Origin	Number of Participants
Alliance – biobank	900
BC coastal participants	200
TOTAL	1,100

Julia Hwang, Laurie Montour and Brittany Morgan

Community Engagement Co-ordinators

Proposed DNA Samples for the IBVL:

2018

April 2019

May 2019

July 2019

Oct 2019

Nov 2019

Sept 2020

Gathering Ceremony:

Victoria BC

#1: Health Board and Chief and Council

#2:

Community gathering

#3: Health Advisory Board

#1:

Community gathering

Statistics Training Workshop: Hamilton (all Alliance communities)

#4: local physician committee- Act 2 focused

#5: REB members and Health Board

#4: Executive Director and local PI

#6:

Health Board and Chief and council

CAHHM FN Data Analysis:

All Alliance communities

COMMUNITY ENGAGEMENT AND GOVERNANCE

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Educate and inform (project)

Community interest

Establish governance process

Educate and inform (process)

Educate and inform (governance)

Transfer of biobank samples (DNA on Loan)

Sequencing

Variant analysis

IBVL (data storage)

Community Discussion

IBVL Governance

COMMUNITY ENGAGEMENT PROCESS

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S-GIRDD STEERING COMMITTEE MISSION STATEMENT

Established to provide cultural oversight & strategic advice in support of the collaborative creation, implementation, and utilization of the IBVL including respectful, culturally safe policies regarding access to data for clinical diagnoses [and related research]

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Tri-council Policy Statement (TCPS2)- Chapter 9: Research Involving the First Nations, Inuit and Métis Peoples of Canada

United Nations Declaration of the Rights of Indigenous Peoples (UNDRIP):

Article 4, 18, 19, 24, 31 (focus on self determination, decision making, and FPI consent)

Ownership, Control, Access, and Possession (OCAP):

The First Nations principles of OCAP® are a set of standards that establish how First Nations data should be collected, protected, used, or shared.

DNA on Loan

Considering DNA to be ‘on loan’ to the researcher for the purpose of the research for which consent was obtained

RIGHTS AND SAFE GOVERNANCE TOOLS�

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How can Indigenous Data Sovereignty co-exist with clinician and patient access to genomic variant frequencies and distribution across the country?

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First steering Committee meeting

Intro to SG

TOR Review

TOR revisions

Initiation of process for clinical release of variants

Initiation of process for requests for research and publications

Initiation of process of publication review

Building of IBVL and establish governance

STEERING COMMITTEE TIMELINE

TOR Approval

Discussion on the extent of clinical research

Oct

2020

Nov 2020

Dec 2020

Jan 2021

Feb 2021

Mar 2021

Spring

2021

Fall

2021

Winter

2022

Ongoing

Establish writing team

S-GIRDD Steering Committee Meetings

Oct 1, 2020 Oct 21, 2020 Nov 2020 Jan 2021 Feb 2021 Mar 2021 Apr 2021 May 14, 2021 May 28, 2021 June 2021 Sept 2021 Oct 2021 Nov 2021 Dec 2021 spring 2022

Finalizing release of variants process

Mission statement complete

Intro to SG

Choosing Chair

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Variant release : A spectrum of options

Accessibility

Time

Unregistered

- No account required

- No monitoring

- Immediate access

- Unlimited queries

Registration automatically approved

- Account required

- Active monitoring

- Almost immediate access

- Limited queries

Registration manually reviewed for approval

- Account required

- Active monitoring

- Delayed access

- Limited queries

Registration and variant queries manually reviewed

- Account required

- Active monitoring

- delayed access

- reviewed queries

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Restricted Variant Release Process

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Educate and inform (project)

Community interest

Establish governance process

Educate and inform (process)

Educate and inform (governance)

Transfer of biobank samples (DNA on Loan)

Sequencing

Variant analysis

IBVL (data storage)

Community Discussion

IBVL Governance

-Governance is now in place, leading to transfer of 600 samples.

-Sequencing and processing is underway.

-Aiming for first trials in 2024.

-This is a START---Sustainability is essential.

-Expanding is essential.

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1. Patient

2. Health care provider

3. Rare disease diagnosis

IBVL

Indigenous Genomic Reference data

EQUITY-ACCESS

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Summer Internship for

INdigenous Genomics

SING USA (2011-2021)

SING Aotearoa (New Zealand) (2016-2021)

SING Canada (2018-2023)

OPPORTUNITIES:

9 Silent Genomes Scholarships

per year

Dr. Kim Tallbear,

University of Alberta