Maili Raven-Adams, Niharika Batra, Trupti Patel and Naimah Callachand: How can we ensure equitable access to genomic medicine?

Digital consent models, language barriers, and cultural
differences are just a few factors that can exclude people from
participating in genomic research. In this episode, our guests
discuss these issues, and explore alternative methods such as
in-person discussions and the use of trusted community figures to
engage with their communities to increase awareness of genomic
research. They also highlight the importance of communicating
consent in ways that respect cultural dynamics, such as family
involvement in decision-making.


Our host, Naimah Callachand is joined by Maili Raven-Adams,
researcher in bioethics and policy at Nuffield Council on
Bioethics, Niharika Batra, Community Projects Manager at Southall
Community Alliance and Trupti Patel, Policy Manager at Genomics
England.


 


"I think it is about finding language to involve people, and
figure out how the benefits of them donating data can relate to
them and their community"


 


You can download the transcript or read it below.


Niharika: People are usually comfortable giving their data when
they feel that there is transparency from the data collector,
they’re being completely transparent, they come with you with
clear benefits, how it’s going to benefit the community. 
And you are equally sort of agent of your own data and you feel
involved in the research and you feel that you have power to give
out your data and have control over the journey of that research.


Naimah: My name is Naimah Callachand, and I’m the Head of Product
Engagement and Growth at Genomics England. On today’s episode,
I’m joined by Maili Raven-Adams, researcher in bioethics and
policy at Nuffield Council on Bioethics, Niharika Batra,
Community Projects Manager for Southall Community Alliance, and
Trupti Patel, Policy Manager at Genomics England.  Today,
we’re going to be discussing some of the ethical, legal and
social implications of genomics research for diverse communities,
and how we might overcome them to address the challenge of
diverse communities health needs.  If you enjoy today’s
episode, we’d love your support, please like, share and rate us
on wherever you listen to your podcasts.  First of all, I’m
going to ask each of our guests to briefly introduce themselves.


Maili: I’m Maili Raven-Adams, I lead on work at the Nuffield
Council on Bioethics to do with genomics.  This has
predominantly been looking at how to develop a best practice
approach for genomics, and looking at the ethical implications of
AI and genomics when they’re used together in healthcare. 
Before here, I worked at the Global Alliance for Genomics and
Health, where I developed policies related to diversity in
datasets and genomic discrimination, so I have a particular
interest in this area.


Naimah: Niharika, can we come to you?


Niharika: Hello, everyone, I’m Niharika Batra, I’m the Community
Projects Manager at Southall Community Alliance.  We are a
charity based in Southall.  Prior to joining the charity, I
was working as a Youth Community Engagement Assistant in United
Nations Development Programme in India, and I have a background
in gender and development.  I also bring with me lived
experience of being a South Asian immigrant woman, and I’m really
passionate about working with the immigrant communities in the
UK.


Naimah: It’s lovely to have you.  And Trupti, can we come to
you?


Trupti: Hi, I’m Trupti Patel, I’m a Policy Manager at Genomics
England.  I work primarily within the diverse data
initiative and I lead the equity in health research
workstream.  My background is in responsible research and
innovation, as well as co-production, and more ethical ways in
which members of the public can shape the direction of scientific
advancements.


Naimah: So, first of all, Trupti, can we talk about the
challenges around equity in data, and what this means for diverse
groups in the context of genomics?


Trupti: Yes, as I mentioned, I lead the equity in health research
workstream.  Now we talk very specifically about equity in
health data.  As Genomics England, we are a biobank, and we
hold health data on individuals who have consented to be a part
of genomic research. When we talk about equity, primarily we’re
talking about those of non-European ancestry, and there are very
specific reasons as to why that is.  So firstly, there’s a
wider issue about representativeness within health datasets more
widely.  We know that across all health data sets that are
located within Global North countries, the data held within them
tends to not be representative of their populations. And what I
mean by that is that they tend to overrepresent those of European
ancestry, and underrepresent anyone who is not of European
ancestry.  The consequences of this is that healthcare
innovation might stand to leave these population groups behind.


One of the other reasons that we talk about equity specifically,
as opposed to things like equality, is that we’re also aware that
if we look at research on a global level, the majority of
research funding is given out through grant bodies located in
Global North countries.  So we already know that research
portfolios can actually be quite skewed towards population groups
who live in those countries themselves.  We know that
there’s a lack of financial investment as well within developing
economies.  So it’s natural to assume that health innovation
projects which address the needs of these communities are more
likely to be conducted by researchers who are based in developing
economies.  However, their access to funding is very
limited, and on top of that they tend to have much smaller life
sciences sectors, so their access for private funding, as well as
opportunities to collaborate with industry can actually be quite
limited in itself as well.


Another reason that we care about equity is that we actually know
that there are some sub-populations that are very diverse within
themselves.  So a good example is the genetic diversity of
Africa as a whole is much larger than those who live outside of
Africa itself.  And for that reason there tends to be a
focus on actually oversampling from people who are of these
ancestries.  And another example being South East Asians as
well.  The final challenge when it comes to equity is that
we also know that there has to be a need for medical innovation
for these population groups, and a desire for people to actually
buy this type of innovation.  So there’s a need for demand
for these therapies and medications.  Now if we already know
that developing economies might be less likely to be able to
afford these medications, then the demand will always be lower
for these population groups.  And therefore the demand for
innovation might also be lower population groups.  But as a
country, because we would want to make sure that we’re able to
provide medication to everyone equally, we need to take an
equitable approach.


So one thing about the lack of diversity within datasets actually
means that we can’t always accurately predict whether or not
someone does or doesn’t have a condition.  So we’re still at
the stage where accuracy is not as good for these population
groups as it is for others, and it leads to things that we call
false positives and false negatives.  So where we think that
someone does or doesn’t have a condition, and in fact, they might
or they might now.  The incidence rates of that happening
for anyone of non-European ancestry are higher.  That’s one
of the tensions that we’re playing with at the moment, especially
when it comes to providing genomic healthcare via a healthcare
service.  Understanding people’s cultural background and
nuances I think is really important.  For example, a lot of
those cultural practices can actually play into whether or not
someone decides to receive or not receive a form of
healthcare.  And it’s also important to understand things
like timing, so the decision around whether or not someone
decides whether or not they’re going to take a preventative
medication might be based upon cultural timings around things
like giving birth or something.


Naimah: How can we ensure equitable access to genomic medicine
for all of these communities?


Maili: So I think we need to understand that there are several
understandable reasons that people might not have been involved
in genomic research to date.  Efforts have been made to
engage with different communities, but this has sort of been
piecemeal and we need to see how that engagement can feed into
research practices. So that people feel as if their information
that they’ve given has been taken on board, and that those
research practices have been co-developed, and they feel more
willing to engage so that that representation can increase. 
There’s also been examples where research has been actively
untrustworthy in the past.  You know, there’s well known
stories of Henrietta Lacks, whose cancer cells were taken without
her consent, and then used to develop research.  And there’s
different examples across the globe that kind of mirror that sort
of exploitation.  So we kind of need to take note of these,
and understand why people aren’t there, and then allow that to
inform engagement practices.  So that research practice can
change over time and be more inclusive and encourage people to
get involved and give good reason for them to get involved in
that.


Niharika: Also, to add on to what Trupti and Maili
mentioned.  First of all, why this data gap exists, why is
there inequity in genomic data?  It’s because historically
South Asian communities or the marginalised communities have been
used to extract a lot of data, be it social research or medicine
research.  So when a researcher approached them or a data
collector approaches them, they feel that they’re just going to
collect the data and there will be no feedback process, or it
might not benefit the community.  The communities do not
understand what the clear benefits of these researches are. 
And in terms of genomics, when we talk about medicine research,
historically these communities have been exploited.  There
has been information asymmetry, and we have observed a case in
1960s where in Coventry Punjabi women, or South Asian women, were
given radioactive rotis, and they weren’t even aware what they
were consuming.  And it was in the name of research. 
So there’s always this hesitancy when it comes to medicine
research.


One way to tackle the problem of the data gap in genomic research
is by co-production . So when you're approaching the communities,
it sort of helps who is collecting the data, there is no skewed
power dynamic involved.  People are usually comfortable
giving their data when they feel that there is transparency from
the data collector, they are being completely transparent, they
come with you with clear benefits, how it’s going to benefit the
community.  And you are equally sort of agent of your own
data, and you feel involved in the research, and you feel that
you have power to give out your data and have control over the
journey of that research.


So it is also important how you frame the message when you're
collecting the data.  In our communities, the idea of sevā
or Kismet is very embedded in the communities, which mean either
giving out your services or your time for the benefit of the
communities.  So it’s not just donation, but it’s just
spending more time or just working with the communities for a
common or a collective benefit.  So when the message is
framed in such a manner that you are doing a sevā or you are
helping your communities bridge the health inequalities and there
might be a collective benefit for the communities, people are
more motivated to give their data.  But when the word
donating data is used, then it puts a sort of emotional burden on
the participant.  So it all depends on the messaging, how
you frame your messages when you're collecting the data, and it’s
important to be cognisant of the cultural sort of ideas. 
And this is something that can be used with South Asian
communities, sevā and giving back to the communities.


Maili: I was just going to say, I completely agree with that,
like 100%, it’s really important as well that the global majority
don’t feel pressurised into giving that data because of the
language that’s being used.  You know, the global majority
are not represented in these datasets, so it could be that the
language used might put pressure on people to donate that data to
fill that gap, but that’s not the right language.  I think
it is about finding language to involve people, and figure out
how the benefits of them donating data can relate to them and
their community, so it just wanted to say that.  And also,
it’s important when we’re using language like genetic ancestry
that those aren’t conflated with things like race or ethnicity,
which are social uses of that language.  So I think this is
just another area where it is really important to think about
language and work with communities, to figure out what the right
language to use it, and understand the benefits of using certain
types of language.


Naimah: And it just kind of highlights how many different nuances
there is, and areas that need to be considered.


Maili: Yes, I was just going to say, within that, we need to
think about barriers to participation as well that might affect
certain communities.  You know, there might be some language
barriers, to making sure that we’ve got translators, or there’s
investment in making sure that the resources are there to make
the engagement and also the research accessible to people. 
There’s things like people have lives, they have childcare, they
have jobs, so making sure that they can donate data if they want
to, at times that work for them and environments that work for
them.  And things like transport costs and that sort of
thing might be covered by a research organisation, so that people
are empowered to get involved, and there’s not too many barriers
to become involved if they want to be.  I think that’s
really important to address as well.


Naimah: Trupti, did you have something to add?


Trupti: Yes, I was just going to say, I think it was really
interesting that Niharika actually framed the benefit around
community benefit.  Because within the policy sphere, and
actually even within wider conversations on data and health,
people use frame benefit in terms of patient benefit
specifically.  And what we find is that when we engage with
diverse communities, most of their concerns around harms are
actually not harms necessarily to themselves specifically, but
harms around their whole community.  And I do wonder whether
there needs to be a slight reframing in how we talk about benefit
when it comes to genomics in particular.  Because most
people when they donate their data they know that it has
consequences for those who are related to them.


Naimah: So I wanted to talk about research governance as
well.  And in the context of history of medical racism, with
medical innovation now heading towards personalised healthcare,
what are they key considerations we should have when it comes to
rules around access to data?


Trupti: So, I mean, one of the rules that we have within our
biobank, when it comes to access to data, is that we don’t want
it to lead to any discrimination, and we won't allow access for
things, for research projects, that do lead to
discrimination.  However, we already know that there are
lots of unintended consequences when it comes to research in
general.  And when it comes to medical research in
particular, and thinking about genomics in particular, lots of
communities are aware that because in the past there has been a
lot of research outputs have been used in ways that actually
don’t benefit these communities, and actually have negative
consequences for these community groups, it means that the
barrier to encourage people to take part is actually quite
high.  When it comes to genomics in particular, obviously
there’s been a history of eugenics, and at the moment, that’s
quite a big area that lots of universities, especially in the UK,
are going through eugenics inquiries.  It has effects upon
people’s perceptions of genomics as an area, and whether or not
people can be confident that those types of research won't be
repeated, and the types of research that will happen will
actually benefit them.


I mean, there’s a good example that one of the community members
gave, not directly to do with genomics, but actually they knew
that if you're first name is Mohammed, your car insurance is
actually much higher, your premiums are much higher.  And so
they were concerned that if you were grouping people within
genomic ancestries, or genetic ancestries, what consequences that
has for them can be quite nuanced in the first instance. 
But in the long-term it would actually mean that people might be
grouped within these ancestries and policies and things that are
created as a consequence were quite concerning for them.


Naimah: And Maili, I wonder if you could tell me how people might
feel more comfortable in the ways in which their data is being
used?


Maili: I guess if there’s transparent governance mechanisms in
place and they can understand how their data is being protected,
you know, that goes right through data access committees. 
There’s one at Genomics England that as Trupti said reviews
data.  So if they can understand what sorts of
considerations that committee are thinking about in respect to
genetic discrimination, and they can understand that certain
considerations have been taken into account when their data is
being used, that’s one thing.  Another could be through
consent processes.  So there’s different sorts of consent
models that could be explored with communities to figure out
which one they’d be more comfortable with.  So broad consent
I think is the one that’s used at Genomics England at the
moment.  So that means that people give their consent once,
and then that data can kind of be used for a broad range of
purposes.  But it’s not always clear to people what those
purposes are, or where that might be used over time.


So there’s different sorts of mechanisms that could be explored,
like dynamic consent, where people are updated over time about
what their data is being used for, and they can either opt out or
opt in to those research practices.  Or forms like things
like granular consent, where when people give their consent
there’s different options of people that they’d be happy for
their data to be shared with.  So we know that people are
less trusting of private companies, for example, so people might
be able to say, “Yes, my data can be shared with nonprofit
organisations or research organisations affiliated with
universities or the government, but I don’t want my data to be
shared with private companies.”  And that might make people
feel more comfortable in donating their data, because they might
feel like they have some more control over where that is ending
up.  And I think transparency there is really important, so
people can understand when they give their data or they donate
their data, they can understand what benefit might be coming from
that.  And that might encourage people to get involved as
well.


Trupti: I was just going to add to that comment about dynamic
consent.  So actually an interesting thing that Niharika
mentioned earlier was this feeling that the people that we engage
with actually really wanted a sense of control over their own
data still.  Obviously when you give broad consent, your
giving your consent, as Maili said, to a wide range of research
that will happen or can happen in the future.  But
interestingly, dynamic consent, I think culturally it is really
valuable for some population groups, partly because it fits in
very nicely with the idea that your biological data is actually a
part of who you are. And that cultural philosophy can still exist
within a lot of these communities that we’re engaging with and a
lot of these communities that we’re trying to encourage to
actually provide us with data.  Do you ever think that there
could be like a medium position, where it was actually dynamic
withdrawal?


Maili: Yes, I guess that is something that could be explored, and
I think that’s one of the models that sometimes is talked about
in academia or in these sorts of forums.  I think if people
were dynamically kind of withdrawing, it might be interesting to
understand why they’re withdrawing and their reasons for that, so
that research practice can change and take account of why people
maybe no longer want to get involved in a certain type of
research.  And I know that’s something that you’ve spoken
about in your community engagement groups.


Naimah: Niharika, do you have something you want to add?


Niharika: Yes, so when we were engaging with our communities, we
primarily engaged with Hindi speaking people from Indian origin,
Punjabi speaking people from Indian origin, and Urdu speaking
people from Indian origin, and we spoke to them about genomic
research.  We also spoke to them about the branches of
genomic research and how their data could be used.  So while
their data could be used for innovation in pharmacogenomics,
which seemed to be more palatable for the people as this is an
extension for treatments they’ve already been using.  For
example, treatment for a chronic condition like hypertension or
diabetes.  Whereas they were quite reluctant when it came to
their data being used for gene editing.  So in Hindu
religion, humans are considered the creation of Brahma, who is
one of our main Gods.  And similarly in Islam, humans are
called (Islamic term), which means God’s greatest creation. 
So when it comes to gene editing, some people believe that it
means you are playing God, it means that you're tampering with
the DNA, you're tampering with God’s creation.  So they were
really reluctant in providing their data for an innovation that
entails gene editing or genetic screening or gene therapy.


And when it comes to consent, I know Genomics England takes a
broad consent, and there’s scope of dynamic consent.  Where
people are constantly engaged on where their data is being used,
how their data is being used, which innovation their data is
being used for, which research their data is being used
for.  And they have an opportunity to withdraw their data if
they’re uncomfortable with any aspect of research.


Maili: I was just going to say something else about consent
models.  When we’re thinking about different forms of
consent, like dynamic consent, it’s also important to consider
the accessibility of those, lots of those models would rely on
the internet and people having access to laptops or phones. 
And so when we’re exploring those models, we need to make sure
that people have access, and if they don’t have access that
there’s other ways that that sort of consent model might be able
to be replicated, or there is an alternative way, so that people
aren’t excluded through that.


Naimah: Is there a question around language barriers as well with
the consent models?


Maili: Yes, when verbal consent is taking place, the same
problems of language barriers are there within the online
version.  You know, how do you make sure that things that
are translated, and translated well as well?  Because
genomics is a complicated area with lots of jargon and complex
language.  So how can we make sure that we translate that
language in a way that’s done, where the meaning is kind of
translated as well.


Trupti: The language thing was something that came up within some
of our community workshops.  And I think one of the things
that really came out was that genomics research itself has so
much technical language that often you simply cannot translate
the word into other languages.  And different ways in which
you can convey information, so that you're still making sure that
you're getting informed consent from participants I think is
really important for these groups, beyond simply translating
written material.  Whether that’s through analogies or
visuals that convey information, I think that’s quite an
underexplored area actually, within research more generally, but
as a starting point genomics.


Naimah: And did any of those community groups identify any
preferences for what way they wanted to be communicated with, for
consent and things like that?


Trupti: I mean, certainly having online consent was a huge
barrier.  So the idea that you log into a platform online in
order to provide your consent to something wasn’t something that
people were that comfortable with.  Especially since these
participants are often very reluctant to take part in the first
place, so you're almost creating a barrier to them as well, it’s
an extra thing that they have to do.  They did feel that
consent should really be in person.  They also preferred the
idea of being able to discuss genomics widely within less formal
settings, so outside of healthcare settings, or outside of
research settings.  Because it meant that they felt that
they were primed for the questions that they might have.


One of the things that I was going to add is actually for
genomics in particular, I mean, I mentioned before about when
people decide whether or not they would like to consent to take
part in genomic research..  They feel like they’re not just
consenting for themselves, they’re also consenting for people
within their network.  And so these are people that they
would consult probably as to whether or not they should or
shouldn’t take part.  And so when you are making that
decision and you're having those consenting conversations,
whether that be within a research setting or a healthcare
setting, it’s important I think for people to understand that
those decisions have been taken not just by an individual, they
are actually reaching out to a much wider range of people within
their own communities.


Naimah: And is there something around that these decisions are
often made with family members as well?


Trupti: Yes.  So in situations where there are people from
some cultures who are much more likely to take part in cousin
marriages, these particular populations have scientifically been
shown to have much higher likelihood to develop genetic
conditions.  Now if that is the case, that can lead to a lot
of stigmatisation, and it can proliferate a lot of discrimination
that these population groups might be facing already.  So I
think that’s something to be considerate of.  And it might
influence their decision making as to whether or not they or
their family members should or shouldn’t take part.


Niharika: Yes, just to add onto what Trupti and Maili actually
said, while language plays a very important role in terms of
consent, how consent is being taken, it also depends on the
setting.  In our areas where we engage with communities,
usually the consent, or consent regarding medical research or
genomic research is taken via the GPs.  And the GP services
here in our areas are so overwhelmed at the moment, there are
long waiting lists, like three months.  And when people
actually get through the waiting list and go to their GP, they’re
so done with the process of waiting that when their GPs ask them
for consent, they just either feel that they need to succumb to
the pressure of, okay, giving the consent.  Because there’s
this skewed power dynamic over them as their white man or white
doctor asking for the consent.  But also, they don’t know
what exactly to do in that moment, they’re very frustrating from
the long waiting line.  And they feel they’re okay, they
might need a little time to sort of cool down, go back home, look
at the consent form, what is it about?   


 


And in South Asian settings usually the decision making is done
in family setting, where you consult your families.  And
when we spoke to older South Asian women and asked them how would
they give their data and why would they give data, they mentioned
that they would give data because their children or husbands have
advised them to do so.  So yes, it’s important to see the
setting of where the consent is being taken, who is taking the
consent, and if they have enough time to think about it and go
back and give their consent.  Also, it came up during the
workshops that it helps if the consent is being taken by someone
the communities already trust.  So having accredited
community champions seek the consent.  So once they’re
trained, once they have enough knowledge about genomic research
and how it can benefit their communities, they’re able to better
bridge the gap between the researchers or the research
organisations and the communities. 


 


Maili: Yes, I completely agree.  And I was just going to add
that it’s important that healthcare professionals are properly
informed and open and aware of those different cultural or
contextual dynamics within those consenting conversations. 
So that they can properly listen and understand where people are
coming from and give that time.  And I get that that’s
difficult in pressurised situations, where healthcare
professionals are under a lot of time pressure.  But that
needs to really be built into that healthcare professional
training over time so that carries on and people can talk about
genomics in a really accessible way.  And that carries
through as well to genetic counsellors who give results to
families, they need to be able to do that in the right sort of
way.  And they need to ask the right questions and
understand the patient that they’re talking with so that that
information can be translated or got across in the best possible
way.   


 


And that’s even more important I think where there is a lack of
diverse data that’s informing research and informing healthcare
outcomes.  I think healthcare professionals should be
transparent with patients about some of the accuracy of certain
things or how different results might mean different things for
different people.  And it’s really important that those
conversations are had very openly and for that to happen,
healthcare professionals also need to get the training to be able
to do that. 


 


Naimah: Okay.  So we’re going to move on to talk a bit about
developing countries.  Niharika, I wanted to come to you for
this question.  Why would diverse communities benefit from
research being more collaborative with developing
countries? 


 


Niharika: So in recent times, we have witnessed growing diaspora
in the UK.  And when it comes to collaboration with
developing countries, there’s increased collaboration with these
developing countries.  It can be a win-win situation for
both the countries, for example, there can be increased
innovation for these developing countries in exchange of
information.  And at the same time, people in the developing
countries, if they provide their data, they have the sense that
they are helping their own communities who are living
abroad. 


 


Naimah: You’ve touched on a few points already, but, Trupti, I
wonder if you could talk about the considerations we should have
when considering international partnerships? 


 


Trupti: Yes.  So one of the things that Genomics England has
tried to do in the past and is still trying to do is increase the
number of international academics that can have access to our
biobank.  Now we already know that internationally,
especially in developing economies, there’s often a lack of data
purely because the resource to do things like whole genome
sequencing is so expensive.  The resource to even have or
host a biobank itself is so costly that the barrier to even
developing the infrastructure is so high.  So one way that
we’re looking to encourage innovation within those settings is
actually to allow access through particular partnership
agreements to academics who are based abroad.  Now obviously
that means that there’s a benefit for them in terms of being able
to do the research in the first place.  But one of the
things is that as a biobank we’re also known for being a very
highly secure biobank, compared to others.  So that’s
something that as a data store people actually highly respect,
and in particular, a lot of the data regulation within the UK is
highly respected by other countries.   


 


One of the things that we have seen happening recently is that
essentially some of our data security laws and data protection
regulations are being reproduced in other countries as a way to
ease working with research datasets across geographic political
boundaries.  When it came to engaging members of local
primary communities they have three primary asks when it came to
the international partnerships that we might be developing in the
future.  One of them was that at the very least there would
be tiered pricing.  If we ever came to a situation where we
were charging for access to our data, that pricing should be
tiered to address the fact that if you are someone based in a
developing economy, your access to financial resource to do
research is much lower.   


 


The second ask was that there’d be some way for us to foster
collaborations.  Now, whether that be led by an academic who
is based abroad or an academic based in the UK was up for
debate.  It was more that those collaborations have to
continue and have to be enabled in some capacity.  And then
the third thing that was a big ask was actually around IP
sharing.  So what happens to the financial benefits of doing
this type of research?  And also, more equitable basically
knowledge sharing across these regions was what was asked. 
So what we’re looking at in the near future is whether or not
these principles could be used in order to guide some of our
international partnerships’ work. 


 


Naimah: And I think just on that point you raised about fostering
collaborations, Maili, I wonder if you could comment on how we
could foster collaborations between the researchers and the
communities that they serve? 


 


Maili: Yes.  I think here is when engagement is really
important, and we need to get researchers and communities
speaking to each other, to have some sort of meaningful dialogue
that doesn’t just happen once but is embedded into whole research
practices.  So there’s many different opportunities to feed
in and that practice is shaped based on the feedback the
researchers receive.  I think engagement is a really amazing
thing, but it does need to be done well, and there needs to be
clear outcomes from that engagement.  So people need to feel
that the information that they’re giving and the time that
they’re giving is respected, and that those practices do change
as a result of that.  So I think we really need to make sure
that engagement and practices are done well.  And I was just
going to say something on collaboration between different
researchers.  When researches are happening across borders,
it’s really important that that’s done in a really equitable way,
and that those conversations are had between different
researchers to figure out what’s going to work
well.   


 


We need to avoid instances of things like helicopter science, and
sometimes it’s called other things.  Where researchers for
example from the UK would go into a developing country and
undertake research and then leave, taking all the benefits with
them and not sharing them.  And that’s something that we
really need to avoid, especially in the UK, we don’t want to
exacerbate colonial pasts.  And I think it's really
important in this context that those benefits are shared with
communities.  And again, we can do that through engagement
and understanding that relationship and making sure that
collaboration really is collaboration, and that we can provide
things that maybe others need or want in the right sort of
way. 


 


Niharika: Just to reiterate our communities are still haunted by
the colonial pasts.  There’s always this constant fear that
our data might be misused, there might be data breaches and we
won't be protected.  And your DNA data contains a lot of
personal information, so there’s constant anxiety around your DNA
or genetic data.  So it’s important that the researchers
maintain utmost transparency.  There’s a constant focus on
flattening the hierarchies, where you sort of bridge the power
gap between the researchers and the communities.  And it can
be done through, again, as I mentioned before, having community
champions on board who understand the communities better, who are
constantly in touch with the communities.  And they provide
that sort of semi-formal settings, where they know that where
they’re in constant touch with the authorities or the GPs or NHS,
but also at the same time have very good relationship with the
communities.  So this is something that should be taken into
consideration.  And then just be cognisant of the cultural
values, and not have very imperial ideas when you sort of
approach communities. 


 


Maili: I think this becomes even more important as genomics
continues to evolve and new genomic techniques are
developing.  For example, with things like polygenic scores,
where we can look at people’s genomic data and predict how
susceptible someone might be to developing a certain disease or
trait or outcome, in relation to the rest of the
population.  Those are developing, and people are interested
in them, but the data that they’re based off again is that
European genetic ancestry data, and therefore is not accurate or
applicable to lots of communities.  And it’s not just genes
that we need to be aware of, it’s people’s environments, and that
data is really important to integrate with things like polygenic
scores.  I think we need to really address these issues now
and make sure that as genomics develops that these things aren’t
perpetuated and existing health inequalities aren’t continued to
be exacerbated. 


 


Naimah: Okay, we’ll wrap up there.  Thank you to our guests,
Maili Raven-Adams, Niharika Batra and Trupti Patel, for joining
me today as we discussed the ethical, legal and social
implications of genomics research for diverse communities. 
If you’d like to hear more like this, please subscribe to Behind
the Genes on your favourite podcast app.  Thank you for
listening.  I’ve been your host and producer, Naimah
Callachand, and this podcast was edited by Bill Griffin at
Ventoux Digital.