 Good afternoon and welcome to another episode of likeable science here on Think Tech Hawaii. I'm your host Ethan Allen. Thanks for joining us today. Likeable science is all about how science is a vital and interesting part of everyone's life. It's not something that just scientists do, it's something that matters to us all, and what scientists do really impacts our lives. And today I have coming from San Francisco joining us remotely is Dr. Kevin Keyes. Welcome Kevin. Kevin is a postdoctoral scholar at the University of California San Francisco Department of Medicine. And we are going to be talking about some of his work on asthma, genomics, and ancestry. So our show's subtitle is a breathtaking combination. So Kevin, perhaps you can talk a little bit though. This is actually the first of a series of shows that we're going to be doing over the next few months involving a group called SACNAS, which is Society for the Advancement of Chicano, Hispanics, and Native Americans in Science. And it's a large support organization that helps get various minority group representatives more involved in science, provides mentors, role models, all kinds of support. And Kevin, maybe you could start and tell us a little bit about sort of how SACNAS played a role in getting new involved in science. Sure. So I have been a member of SACNAS since attending my first conference in 2007. SACNAS is a group that that provides mentorship and support for people that are traditionally underrepresented in the sciences. Originally, it was founded by a group of Chicano's Native Americans, but it's actually grown in the intervening 45 years to become the largest multicultural and multidisciplinary science outreach organization in the United States. It's been an integral part of my development because when I first went there, I was able to see scientists like me. And it's been now, let's see now, about 12, 13 years later, I've stayed very close to organization. I like what they do. I like the people I meet there. And now that, of course, being that I started undergrad, I'm a postdoc and I can also give back to the undergrad so I can see myself and the students at these national conferences that they host. Excellent, excellent. And people may not know this, but as our upcoming graphic here will show, the SACNAS is having their annual conference here in Hawaii this year, coming up in the fall, the end of October, I think for 31st, right, 31st of November 2nd. I'll be here at the convention center, so and it's going to be a great gathering. They're going to, I guess, in part reaching out to sort of a new audience for them, the audience of Native Hawaiians and Pacific Islanders who have not traditionally, again, they've been very underrepresented in science. And this I think hope is by bringing the conference here, they'll raise awareness. And so that's part of what I want to do is help raise awareness of this group and all. And since you got were involved, your name was given to me as sort of a good member to talk to. We got John here. So let's let's move on then a little bit and tell me, tell us about your research. So you study pediatric asthma, that is asthma in kids. So sort of one, sort of what is this and why why is it important? The start from the basics, I guess, asthma is a it's a condition of the lungs. Most people know it involves the narrowing of the bronchial airways. And it affects a tremendous amount of people, actually, it's has a very high incidence in the United States. The I happen to be one of these people. Of course, I had asthma as a child. We traditionally focus on on a certain kind of asthma, right? So asthma can present itself in many forms. But the one that we care about is the the allergic type of asthma. And and here at UCSF, we study the the genomic basis of how we understand, we want to understand what component of of our genetics explains asthma incidents, right? Because different different groups sort of show asthma at sort of different differing rates of population. And this is sort of an intriguing phenomenon, right? It's not seen in all diseases. Some diseases are pretty much what you what you might call even handed they affect everyone, everyone around the world pretty equally. But asthma is not asthma apparently has your genes give you some predisposition for it or some protection against it one way or the other, right? Yeah, that's right. So it's asthma is is unusual in that it presents this ethnic disparity in in incidence and mortality. So in the United States, the the groups that will so here in the lab, I should clarify that we focus on four ethnic groups. We focus on Puerto Ricans, African Americans, Caucasians and Mexicans. Of course, these are other ethnic groups in the United States, but these happen to be the ones in in our study cohorts. And the breakdown of who suffers from asthma is a bit strange because it seems like the the Puerto Ricans, for example, suffered much higher than than the Mexican Americans. Now, in the United States, they're both considered Hispanics. This is long known as the Hispanic paradox in asthma. But but here in the lab, we understand that that genetically these two groups are actually distinct. Also, there's the African Americans seem to suffer it very and have a very high incidence as well. And so we we want to understand to which degree this the separation is genetic. Right. So we've got a graph, I think, that shows that basic incidence difference, right? That's right. Yeah. And so, yeah, you can see you go ahead and explain it out by. Yeah, so I was going to say that you can see that, you know, very clearly splits out by the four groups that I've mentioned, the four populations in the United States. And this is asthma prevalence in the United States. So we're saying that amongst Puerto Rican children at around 26 percent of them will suffer from asthma. It's pretty dramatic. It's almost two and a half times as high as yes, it's about a quarter, actually, two and a half times higher than the Mexican American children. But so prevalence is, of course, how many people have it. But there's there's also a similar situation with mortality. So for reasons that we don't fully understand, Puerto Rican children and African American children also die from asthma more often, right? This is taken in, I think it's per 100,000 patients. You'll see the African Americans and Puerto Ricans die much more often than the other two groups. Yeah, even even in greater proportions than there than that first figure would have reflected, right? I mean, well, yeah, wow. That's right. So this is a very sort of, in a sense, a very selective disease. Yeah, and you could think about it one way, because so there's if you look at, for example, the drug response, right? So one of the characteristics of having asthma or controlling asthma, especially with children, is that they have inhalers. So I having had asthma as a child, I had these inhalers, right? And it turns out that the inhalers don't seem to work as well in all populations, right? So this is the third component of this, is that the Puerto Rican and African American children show a different drug response to the corticosteroids that they inhale to control their asthma. And they're not getting as much benefit out of the drug you're saying. That's correct. So the corticosteroid is supposed to reverse the constriction of the airways. And imagine it's opening up the airways in your lungs, right? It's exactly. And so it seems like the drugs, the standard drugs that are used to do this don't seem to work quite as well in these populations. You have you have a higher incidence, a higher mortality and a worse drug response, right? Right. So the one thing to keep in mind, though, is that asthma actually afflicts everyone. It can afflict everyone. But for some reason, right, it's there's this ethnic breakdown that we think is explained by very small genetic differences, right? We human beings are mostly alike. We're over 99.99 percent alike at the genetic level, right? But maybe maybe that tiny, tiny portion of our genomes that vary, right? That might explain why these drugs aren't working. Right. That's quite intriguing that we see this this kind of differences in, as you say, in the frequency, in the mortality and in the response to treatments. And given given the, as you point out, the overwhelming similarity of people to one another, that's interesting to see. So in some sense, I don't want to make too much too light of it, but your task should be simple because there's very little of the genome left. It's different, right? Right. It always seems like that. But remember, the genome is three billion bases long. So if we are even a 99.999 percent alike, there are going to be several thousands of bases that are different. Right. And then you've got to, yeah, you've got to find that. You've got to look at large population samples. Right. Exactly. Try to see what where those differences pop up where consistently you're seeing that. Ideally, you want to do that in the people who are actually suffering from asthma versus those who aren't in their same ethnic group, right? Right. Exactly. Wow. So that's got to be quite a quite an undertaking. But but asthma is if you've got several types of it and the allergic type you refer to. So it people get something triggers an asthma attack, right? And some tip typically something maybe inhaled or some environmental factor. Yeah. So you can you can induce asthma from an allergen, obviously, but also from pollution. There is there are people hypothesize that there is actually an exercise induced asthma for people who do really strenuous amounts of exercise. There is another hypothesis that there might be an asthma subtype related to obesity that for some reason people who who have very high BMI's suffer a very different kind of bronchial constriction that's not the same as the allergic form of asthma. Interesting. Interesting. So there are there are a lot of subtleties to this then. So that's that's pretty pretty pretty amazing. So how do you how do you go out doing or what sort of what do what do you do to look at this stuff in simple, non-technical terms? Sure. So we here in the lab do what are called genetic association tests. And in simple terms, what we want to do is compare the the differences, the genetic differences between two groups. You grab your children who have asthma and your children who do not have asthma. We called this left group, the control group that doesn't have asthma. And then we gather the genotypes where we sequence the genomes of each of these subjects. And then we simply compare the the genotypes, right? We have to align these genomes and we compare down the line and say, you know, this group has asthma and this does not do any of the genotypes differ. Does the variance between the genotypes differ? And we can statistically determine to which extent the the differences in these genotypes actually affect the the outcome, which would be disease status of asthma. OK, OK. So it's a fairly sophisticated process involving a lot of sort of bioengineering, but also very very high level mathematical algorithms. So some some people do it that way. But actually, this is this is a beautiful part about this particular field that these particular analyses are fundamentally very simple, right? So the statistical mechanics of them are quite simple. The complications come from the data itself, right? You have to have an understanding of genetic inheritance, the population genetics behind how humans arose. And those those details actually matter a lot. They can dramatically change the outcome of the association test. So it is it's beautiful in that some of your statistics one on one. If you if you take that one on one, you can actually understand the statistical process of how we get here, right? But then you have to remember that the reason that we, you know, have scientists still doing this is that the data, the nuances, the data end up being very, very important in this field. Yeah, data often are messy with the real world data. And we're going to look into a bit more of that aspect. When we come back right now, I'm told we need to go off to a brief break. Kevin Keyes from the University of California, San Francisco Department of Medicine is with me today. Virtually here in likeable science. I'm your host, Ethan Allen, and we'll be back in one minute. Hey, loha, my name is Andrew Lanning. I'm the host of Security Matters Hawaii airing every Wednesday here on Think Tech Hawaii live from the studios. I'll bring you guests. I'll bring you information about the things in security that matter to keeping you safe, your co-workers safe, your family safe, to keep our community safe. We want to teach you about those things in our industry that, you know, may be a little outside of your experience. So please join me because Security Matters, aloha. Hi, my boohai. My name is Amy Ortega Anderson, inviting you to join us every Tuesday here on Pinoy Power Hawaii with Think Tech Hawaii. We come to your home at 12 noon every Tuesday. We invite you to listen, watch for our mission of empowerment. We aim to enrich, enlighten, educate, entertain, and we hope to empower. Again, maraming, salamat po, mabuhai, and aloha. And welcome back to likeable science here on Think Tech Hawaii. You've joined us for a show on asthma, genomics and ancestry. And Kevin, Dr. Kevin Keyes is joining us here remotely from the University of California, San Francisco, in the Department of Medicine here. Welcome back, Kevin. Hello. Good to see you again. And in the first part of the show, we were talking a little bit about the sort of the different groups, different ethnic groups and their different proclivities for getting asthma, the different sort of mortality rates they suffer from asthma and the different responses they have to asthma drugs. And I wouldn't maybe take a look at our next next image because I think that might help people understand a little bit. Not quite as cut and dried as we were talking about, right? That is, we talk about those groups as if they're sort of uniform groups, but they really aren't. All of us basically have genes from a bunch of different people and ancestors, but certain groups can prevently to have more ancestry from certain other certain ancestral groups, right? That's right. So in that image, I showed you the four populations that we study here in the lab at UCSF. I made a side note, by the way, because for your Pacific Islander viewers that we don't happen to study Pacific Islanders, but the story behind Asian Americans and Pacific Islanders in the United States, it's a very large diverse group. So there's a lot of the same principles will apply, but the story, the details are different. In that image, though, you can see that we model these particular four ethnic groups as having come from three ancestral populations, right? And if you think about your world history and American history, it sort of makes sense how this pans out. We have some European ancestors, some African ancestors, and some Native American ancestors. And depending on how many ancestors you have in your lineage, it will determine roughly what kind of global genetic ancestry you have in your genome. So on the left over here, we'll have the Caucasians that are mostly European. Mexican Americans are strongly mixed between European Native American with a tiny bit of African. There actually are some Afromexicans. I don't know if it's not a very large population, but they exist. There are African Americans that are mostly European and African with some Native American ancestry. And then there are the Puerto Ricans who actually have a substantial mixture of all three ancestries. Right. And even within, as that chart show, within those groups, people can vary tremendously in terms of their percentages and sort of who their ancestors were. So. And one of the things that you were talking about in some of our earlier conversations is that, of course, this, I guess it shouldn't surprise us, but this propensity to get asthma more frequently in some of these groups, to get asthma apparently worse and to be less responsive to good asthma drugs, means that certainly these groups, like African Americans, typically suffer more from impaired lung function, basically, or impaired eyes and bronchial function. And yet we see lots and lots of examples of great athletes among these populations. Is there anything sort of discordant about that? Or is this understandable? So there actually isn't anything discordant about it. It depends on a couple of things, actually. So one thing to remember is that asthma is actually very common amongst all these ethnic groups. Right. So I've shown the prevalence is a little different, but asthma is a very widely common disease in the United States. It's actually, I think there's, I provided another figure for you that it afflicts, I think, well over 20 million people in the United States. Now, to give you an idea, one of the more prevalent diseases might be, for example, obesity, right? But asthma is on par with things like cardiovascular disease or type two diabetes, right? In terms of actual the number of people that suffer in the United States. So within such a large group, you're actually likely to get a lot of variation. So asthma is not, I guess I would call it an obstacle, but it's not an insurmountable barrier to becoming an athlete. The other thing to remember is that, you know, it's not just for African-American athletes, there actually are many non-African athletes that also suffer from asthma. Right. Yeah. And that figure you were referring to, I think that's, I think that's the next figure in that series, right? So can you just explain this to the audience a little bit, what that vertical axis represents? Yeah. So we actually compiled this in our lab. This is something that our lab has produced. On the X, you have the number of affected people in millions, right? You can see, for example, that there are adult obesity is very prevalent. Things like asthma, coronary heart disease and type two diabetes run around maybe 25 to 28 million people and a little less slower are things like childhood obesity and COPD. Right. But the Y axis is actually very interesting, right? Because we wanted to measure the what we called the disparity ratio. If you take the ratio of the largest incidence of the disease versus the smallest incidence of disease, right? And you've done this split these incidences by ethnicity, then asthma seems unusually high, right? At the disparity between those who suffer at the most, in this case, Puerto Ricans, and those who suffer at the least, in this case, the Mexican Americans, is remarkably high compared to other diseases. So asthma is it affects all people, right? But it does not affect all people equally. Right, whereas your chronic pulmonary obstructive disease there and adult obesity on that chart are equal opportunity diseases. In fact, all groups pretty much equally. Yeah, that's an intriguing finding. And it speaks well to the kind of science that we're able to do now that we're able to tease apart those sorts of relationships, right? And able to understand that there are subtle genomic factors that are playing on in. Mm-hmm, so maybe you take this in a more practical direction, what impact does this have then on people in terms of sort of their lives? Well, so it's not unique to asthma, but let's say, for example, that we think about the term of genomic precision medicine. Precision medicine is a growing field. There's a lot of interest in making medicine very personalized to each individual subject. And so an asthma happens to be one case where this might be a very important thing to think about. But of course, it's still developing a field. So we can see those of us here who work at UCSF, we foresee in the future, maybe not necessarily tomorrow, but sometime in the near future in which the ability to understand your genetic ancestry and your genetic information might end up being very useful in the clinic. So if you went to 23 and me or something and got a breakdown of your ancestry, this might be a useful thing to take in and show to your doctor and say, hey, here's who I am. And then they could say, you should take drug X instead of drug Y then, right? Yeah, so 23 and me happens to be one very large player in this field. There are other companies, Ancestry comes to mind. I think there are groups like Helix, many of these companies that are trying to figure out if they can use your ancestry profile to better inform how you'll respond to your disease risk and how you respond to drugs, right? So this is a very plausible thing to happen in the future. Right, and we've seen some examples. You were quoting me, the story of Plavix as sort of almost a cautionary tale in this, right? Maybe I suspect about it probably doesn't know it. You give us a brief version of that. Yes, Plavix is a blood thinner. It was produced by, I guess the region produced by Sanofi, but the producer in the United States was Bristol Myers Squibb. Now, Plavix was a very profitable drug for them. Used a lot in the clinic and potentially, you know, to relieve an emergency blood clot. However, over time, people started to notice that Plavix wasn't working the same in all groups. And in fact, in this case for Asian Americans and Pacific Islanders, for I think it's about 30% or 40%, right? Between in that range, Plavix and that group work like a placebo. So you can imagine that if you're in an emergency situation where you need to unclog a critical blood vessel and this patient, an Asian American patient is administered Plavix, there's a very high chance that the drug will not work. Now this ended up becoming such a scandal that the state of California, and I believe the state of Hawaii actually sued the drug manufacturers, right? Because they contested that the drug manufacturers had distributed and marketed this drug without fully understanding how it would impact the people of their state. Interesting, interesting. But I don't think from what I heard, if I understood you correctly, these lawsuits are still pending or in process. Nothing has been resolved, right? They aren't fully resolved yet. I think that these lawsuits started, well, many years ago actually, at least 2014, it's not earlier. Right, but you can see this brings up all kinds of interesting issues, right? Here is a drug that may work perfectly well for some people. Some percentage of patients are still on quite well to it. It's a valuable product for them. It shouldn't be, they should not be denied that, but as a physician, you certainly don't want to be giving that drug to somebody who's in a group where they have good odds that they won't respond well to it, they'll respond badly or not at all, right? Mm-hmm. Especially in an emergency situation, right? These physicians, they want to know that the drugs that they rely on will actually work for all the patients that come to their hospitals. Right, now, it's a great example that there are no guarantees. And we're finding now, as you so nicely point out, these subtle differences that are turning out to be very important, of course, for some people, life and death literally matters. But only now we're coming to light about this and how the drug companies are going to deal with this in the future going forward is an intriguing question, right? They just need to make sure that they study their drugs on everyone. Yeah, I mean, they'll have to presumably start attaching warnings to these and making it better known that these drugs only work better for certain groups and are less of a good bet for other groups, right? That's actually, I think that some of the drugs already do this. There might be, in the near future, some push to actually have these drugs tested in clinical trials on more than just one population. Typically, for many reasons, these drugs are only tested on one population group, right? They want to control the genetic variation in some sense, right? So there might be, it's entirely plausible in the future after the field really realizes that in the drug companies too, they realize that, oh, this is a thing we must care about genetic ancestry when we develop our drugs, that the clinical trials themselves will become much more diverse. Interesting, interesting. That sort of reflects this issue that I run into as an educator, I've got equity now and this is sort of equity in medicine, yeah. Excellent. Yes. Hey, well, this is exciting stuff. It's great to learn about this. Wonderful that you take your time here to come and talk with us. I appreciate it. And let me just remind our audience again, the SACNAS International Conference is gonna be here in Honolulu on October 31st, November 2nd, this is coming fall. A wonderful event, it's sure to be. Thank you so much, Kevin. I appreciate your being here and good luck to you in your future endeavors. And to those of you watching us here, I hope you'll come back next week and see us again on the next episode of Likeable Science.