Race & Genetics in America
Transcript for Student Voices
Sohini Ramachandran/Enyonam Odoom
You’re listening to Student Voices, a podcast featuring student-led interviews of Brown University faculty based on the Race & in America panel discussion series, curated by the Center for the Study of Race and Ethnicity in America in partnership with the Office of the Provost.
Enyonam Odoom: I’m Enyonam Odoom, I'm a graduate student in the School of Public Health, and I'm speaking with Professor Sohini Ramachandran about the recent panel discussion on Race & Genetics in America. Hi, Dr. Ramachandran, how are you doing today?
Professor Sohini Ramachandran: I'm doing great. It's such a pleasure to be here with you virtually! Thank you so much for spending time with me.
Enyonam Odoom: Of course. I'm really excited about our conversation today and I really enjoyed hearing you and Dr. [Lorin] Crawford and Dr. [Brandon] Ogbunu speak a couple of weeks ago about contemporary genetics research and all the work that you guys are all doing within that. And I'm just excited to learn more about your perspectives as a population geneticist. So I found all your conversations really thought-provoking and I just had a couple of followup questions for you about your panel discussion. So the first question I have for you is during the panel discussion you spoke a little bit about the protection of genetic data in the Genetic Information Nondiscrimination Act or “The GINA Act” and I'm really interested in hearing more about that, what that could look like and just following that trail a little bit more. What do the current protections look like and how do you think those should be expanded?
Professor Sohini Ramachandran: The most important feature of GINA, with respect to the way we structure healthcare in this country where we don't have universal health care, is that the protection that's most important that GINA puts in place is that insurance companies cannot change offers of coverage or premia for individuals based on results from genetic tests. That information is kind of kept separate because if you think about the way that an insurance company operates in terms of premia or a life insurance company, if there's a known preexisting condition that an individual has that might influence their health outcomes in a negative way, then they might have to pay more to get coverage. Or if a company knows that they're going to require more care over time in a sort of market based insurance situation, that might be taken into account when evaluating how much someone should pay for healthcare.
So currently under both GINA and the Affordable Care Act we all have that protection in America where our genetic information cannot be used to discriminate against us in the way we receive healthcare and the way we're covered, but it's actually not an ironclad rule as it is. So in fact, small employers are employers who only have less than 50 individuals, if for some reason they got access to genetic testing results [they] could in fact deny coverage legally to employees. However, the Affordable Care Act also adds additional protection so, especially under the Trump presidency when there was so much rhetoric about dismantling the Affordable Care Act, this was a concern of mine and other geneticists. What would happen to GINA? How would it continue to exist without the Affordable Care Act? Which was protecting so many individuals who worked for small employers and might, by proxy of the Affordable Care Act potentially getting revoked, it was unclear that anyone was going to pay attention to this.
There are also a number of kind of interesting and horrifying medical questions that emerge when you talk about genetic testing results because so much of the phenotypes that we experience as adults involve our environment, they aren't necessarily totally prescribed by genetics, diseases that can require very long term care like Alzheimer's disease, or there's some potential genetic risk factors but there are other risk factors, and you can't a hundred percent predict who's going to experience these outcomes that then lead to needs for long-term care and high hospital bills. Wired, I think a couple of years ago had a really interesting article that was very thought-provoking for me in terms of a disease that has some genetic risk, when does a preexisting condition become existing? Is it when you’re born, even though you might not experience the deleterious effect of the disease-associated mutation until you're much older? So these are all questions that we haven't really grappled with as a society, both from the scientific standpoint, but then when it goes into affecting you as an agent in terms of getting health care or your behavior in a healthcare market or how you’re perceived as an investment, that becomes a real problem. I think universal healthcare would be a wonderful step forward obviously for many, many, many reasons, both medical and public health, but I think it's also important to think about increasingly that genetic information is something that needs to be protected, that should be divorced from medical coverage. And also that we need to make sure that it's secure from employers and that people know that it's information they should be able to keep private.
I'll just tell you another angle of this, which is kind of unrelated, but related technically, even though genetic data, if I deposit my genetic data in a database or I take a direct to consumer test, that database, that company, they have some information about all my relatives, some amount, right? Depending on how closely related someone is to me, they have some information about their genetic data as well. And it turns out that also we do not have any rights to our genetic data and nor do our heirs when we die. If I’ve deposited my DNA with 23andMe, when I pass away my children can't write to them and say, “Please take our mother's data out of your dataset.”
But there's similar issues around social media like removing a Facebook profile when someone passes away or something like that. But this is kind of an interesting question again that we haven't really grappled with as a society. So there are some, I think genomic privacy and genomic security are really interesting questions for us to think about. In part because, as I mentioned in the panel, unlike credit history or purchase history or even aspects of one's own identity, you can change them, but you can't change your genetic data. So those are some of the challenges that we face with GINA in this country and it's important for people to think about that and talk to their representatives about it if we ever get into a situation where it looks like some of these protections might go away.
Enyonam Odoom: Interesting. Yeah, it's scary when you put it like that. I didn't know all of that, but that's really worrisome. I might call my Senator today. I know there's an interest in expanding that protection, what might that look like? What other protections could exist to save consumers who take these either direct to consumer tests or other genetic tests and want more protection around their privacy?
Professor Sohini Ramachandran: It's a really good question. I think one thing is to share with relatives, to the extent one's comfortable, that one has taken these tests. And I think this question of if one isn't in a position to advocate for oneself and wants to take back genetic information, having other people know like, oh, you deposited your information somewhere and I can help advocate for that.
I do think, just like social media websites, there's a lot of information provided when you do a direct consumer test about privacy, but it’s just educating people to think about their data, what it means to contribute to a database, what it could mean. I mean, I'm not trying to completely knock direct to consumer tests, I've done them, but it's more about understanding is this a database that secure? Is this a database that could potentially sell my information to a third party, to a pharmaceutical company? That information is there and I think all of us and especially young people growing up today really need to take control of our own data and make decisions really intentionally when we participate in creating online accounts or social media type things. Yeah, I think just educating ourselves on privacy and understand that our genome is something that could be private if we wanted it to would be really important. In terms of expanding GINA, I think expanding it to include all employers would be huge in this country because small employers, small businesses make up so much of -- especially in the hospitality industry which we’ve seen hit by COVID -- make up so much of the source of jobs in this country. And I think it's really important for people to feel if something about their medical history gets revealed to their employer that they're not going to end up losing access to the healthcare that they need as a result of that.
Enyonam Odoom: That’s a really great point. Yeah, like I said, I'll be calling my Senator. You've convinced me. Okay, and then shifting gears a little bit, I know you also spoke about the importance of breaking down silos in working with researchers outside of your direct field. I'm just interested in hearing a little bit about any interdisciplinary projects that you've worked on and how those turned out and what made them successful.
Professor Sohini Ramachandran: Thank you for asking. I would actually say my whole career has been very interdisciplinary and that, you know, I was an applied math major in college and I started working in a lab that was interested in genomics and biology in my field, population genetics, which is a pretty young field so it was begun just over a hundred years ago. What is interesting about it is that two of the three founders who are regarded as the three founders of population genetics were also seminal statisticians. So that the field has had a history from the beginning of bringing folks from statistics, mathematics, then physics into biology. It's kind of where the first theoretical mathematical computational biologist sort of came from into the field. That and molecular modeling, I would say.
But sort of to answer your question more directly, my philosophy about collaboration has always been to collaborate with my friends so I think my favorite collaborations are with people I've known for a long time and sometimes it takes a long time for us to find points of intersection. So one example I'll give is a friend of mine who, we actually went to college together and we're both population geneticists, but she was trained as an anthropologist and her name is Brenna Henn. She's now an Associate Professor at UC Davis in biological anthropology. So we had known each other for about 14 years probably before we really wrote a paper together and part of it is that we would see each other at conferences or we'd see each other socially and we'd always be talking about our science in kind of different ways. Then finally she approached me with a really interesting dataset from her field sites in South Africa. She works with ‡Khomani San individuals and was really interested in identifying adapted mutations in their genomes and I was developing computational methods to identify adopted mutations in any genome. So we said let's collaborate. And it was just so much fun because it was so easy for us to talk about the logistics of the collaboration like authorship and where we wanted to submit and what conferences, and to bounce ideas off each other in a way that, because we knew each other so well, we knew it was all constructive and for the project. And so that's something I talk a lot about with my own trainees is that the best collaborations are less about identifying somebody who has a particular dataset or a particular resource that would be useful for the project and it's really more about personality, I think. Finding people where you vibe together and over time find more and more stuff to work on.
And actually you mentioned Dr. Crawford, who was on the panel with me and who's a very close collaborator of mine now, and that's very much how we've approached things. He's a statistician by training and ever since he's come to Brown we've just ended up co-advising three or four lab members together and we sort of have this understanding about alternating who's going to lead things. And we talk a lot about how to make the project match the strength of the first author and it's just very easy for us to talk with each other. And so I think an exciting thing about being an academic and being in a university environment -- and it's probably true in any industry, but this is what I know -- is that over time you get influenced by the people that you're around and so I think being open to those opportunities is really helpful. I feel like now I have some close friends who are sociologists where I can imagine that over time, especially if we had a postdoc or something that we shared, that we might end up doing some work around joint interests. So yeah, I think just being open to cool conversations with your friends, which I'm sure you've experienced, and noticing when they're really influencing you and kind of pulling you in a new direction can be really fruitful.
Enyonam Odoom: That is really great advice, I'm definitely going to keep that one close. Thank you for talking to me today, Professor Ramachandran.
Professor Sohini Ramachandran: Thank you so much for taking the time. I really appreciate your interest.
Student Voices is a feature of the Race & in America digital publication series developed by the Brown University Library. Our theme music is “see the unseen” by Butter. Explore the series at DigitalPublications.Brown.edu