Hannah Went (00:04.877)
Welcome to the Everything Epigenetics podcast. Dr. Schmitz excited to have you today. Thanks for joining.
Lauren Schmitz (00:06.45)
Thank you.
Lauren Schmitz (00:10.821)
Thanks so much for having me, Hannah.
Hannah Went (00:13.137)
Yeah, so, you know, without further ado, we’re going to just hop right into it. You know, I gave our listeners a brief introduction about what we’ll be chatting about today and your history and background, but tell me your story. I’d love to know more about your journey and your upbringing about how you got to where you are now.
Lauren Schmitz (00:30.31)
Yeah, I had a very atypical kind of windy road into science. I grew up in Colorado in Denver and I was actually a professional ballet dancer until my early 20s when it became apparent that I wasn’t gonna move up from the core in the ranks and to principles. So I decided to pursue my education full time. And at the time I had been going to school at night to get my bachelor
Hannah Went (00:48.299)
Mm-hmm.
Lauren Schmitz (01:00.01)
And I ended up majoring in economics and just really loved kind of how I could bring together my right brain and my left brain to study social problems in the world. And then I went on to get my PhD in economics at the new school for social research, which is in New York City. And there, I think, my interest for social inequality and how that impacts health disparities really began to develop
and more. I always say that, you know, I lived in kind of a, it was an area in Brooklyn that was fast becoming gentrified, but it was still very diverse. And, you know, very much a low income neighborhood. That was basically all I could afford for rent. And I would, you know, get on the subway and ride all the way and, you know, to, into Manhattan and pop out, you know, on Fifth
Hannah Went (01:38.757)
Mm-hmm.
Hannah Went (01:45.064)
Thank you.
Lauren Schmitz (01:59.91)
of riding the subway every day, it was like, you know, riding the entire socioeconomic distribution. You know, you saw everything and everyone and, you know, how they were going to work, what they were doing. You were really, you know, you saw people in a way that I think you don’t often in areas of the country where we’re kind of more separated. And so, you know, I really became
Hannah Went (02:06.46)
Oh wow.
Hannah Went (02:17.683)
Mm-hmm.
Lauren Schmitz (02:30.11)
these disparities in health and mortality that we see that are so well documented and linked to socioeconomic differences in the population. And at the time, I wasn’t using any biological data. I was just getting my degree in economics, but I was very interested in health economics. So I was really interested in looking at health outcomes. And I began working with the Health and Retirement Study, which is the,
Hannah Went (02:41.357)
Yeah.
Thank you. Bye.
Lauren Schmitz (02:59.87)
just aging study in the world. It started here in the United States back in 1992, when Congress said, hey, we need a study to start looking at aging in the United States, because there was a realization that our population was aging, that the baby boomers were getting older, and we needed to understand more about not just health and aging, but also things like retirement and savings
and how these factors impact people’s livelihood at older ages. And so that was a really groundbreaking study that still continues to this day. So they have collected data on over 30,000 people, and it is population representative of the United States of people over the age of 50. And this will become important later because it’s going to feed into all the data that I am using in the studies that I’ll be talking about today.
Hannah Went (03:51.357)
Mm-hmm.
Lauren Schmitz (04:00.07)
most of the data that I’ll be using and talking about today comes from the health and retirement study. So I had started working with the health and retirement study really early in my PhD. And in 2006, 2008, it became cheap enough to begin genotyping these people. So they had, you know, a ton of information on these individuals, and then they began collecting genetic data. And I started working with a sociologist at New York University,
Hannah Went (04:05.519)
Mm-hmm.
Lauren Schmitz (04:30.03)
Dalton Conley, who integrates genetic data into his work as a sociologist to study inequality and just became really interested in using genetic data to look at how our social world and our biological world are both coming together to kind of produce these disparities in health that we see in the population. So I started working with genetic data because that was what was
Lauren Schmitz (04:59.91)
work with in these large population studies. And then, luckily in 2016, the HRS started to collect epigenetic data. And that was really groundbreaking in the sense that they were able to get a population representative sample of epigenetics in the United States. So across all states and regions of the country, and they were actually able to collect this from whole blood.
Hannah Went (05:10.057)
Thank you.
Hannah Went (05:18.519)
Mm-hmm.
Lauren Schmitz (05:30.05)
and interview people, you know, while they were doing their regular two-year interviews for the health and retirement study, they began collecting blood on these individuals. And so that has then kind of really helped me get more into studying epigenetics. And so, because in other words, the data were finally available to where I could study it and integrate it into the social models of health disparities that I was using as a social scientist. And I don’t know if I said earlier,
Hannah Went (05:59.457)
Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you.
Lauren Schmitz (05:59.87)
retirement study, they start interviewing people around age 50. They interview them every two years until they pass away. And then even after they pass away, they interview their next of kin. So it’s this really great population representative longitudinal study of older individuals in the United States. And it’s since replicated and been replicated in other parts of the world. There’s now a lot of other aging studies in the world that have kind of modeled themselves after the health and retirement study. They’re called kind of sister studies of aging.
Hannah Went (06:04.039)
Mm-hmm.
Hannah Went (06:08.318)
Mm-hmm.
Hannah Went (06:17.818)
Perfect.
Lauren Schmitz (06:31.33)
So that’s the background in terms of the data. And after I graduated from the new school, I went and did a postdoc at the University of Michigan where I worked directly with the Health and Retirement Study. And there I wrote an NIH grant that funded my time and also allowed me to get additional education in genetics. So I got my masters in human genetics from the University of Michigan.
and allowed me to start to understand the biological side of things and really begin to integrate it, I think in a way that continues to drive my work today. And then I was lucky to, when I went on the market, to get a job as a professor. There was a position that opened up here at the University of Wisconsin-Madison in social genomics.
is one of the leaders there and starting to bring together researchers that have expertise both in the social sciences and in the biological sciences. And that’s been very exciting. So that’s kind of a short short but not so short windy road that has gotten me to this topic. Yeah.
Hannah Went (07:42.178)
Yeah.
Yeah.
Hannah Went (07:49.817)
No. That’s awesome. And it seems, you know, where you are now is a perfect fit for kind of everything you’ve learned throughout your journey. So that’s great. I have a lot of things I want to respond to. So interesting that you had more of that artistic background. I do not have any of that at all, but I understand like your upbringing of, you know, choosing that route or kind of focusing on your studies because I love soccer, played soccer growing up. But I was at the point where I was like, okay, could probably go to school
Lauren Schmitz (08:06.013)
Yeah.
Lauren Schmitz (08:09.65)
Thank you.
Hannah Went (08:19.777)
this, but I want to go to a larger school and, you know, probably need to go more on the path of my studies. So I understand you there and just think it’s really interesting about your time you spent in New York and, you know, riding the train and seeing all the diverse kind of groupings because you’re right, you don’t see.
Lauren Schmitz (08:27.05)
there and it’s just really…
Lauren Schmitz (08:32.749)
to know the diverse and the group needs to be right. Mm-hmm. Mm-hmm. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah.
Hannah Went (08:37.597)
those, I don’t know what to say, the, you know, it’s, like you said, it’s usually a segregated area that you’re living in and there’s not much diversity. So it’s really interesting that you’re able to kind of physically see that and study alongside of that. Um, something I wanted to make clear for the listeners, you talked about two different studies, right? There’s the normative aging study in the health and retirement study, two different studies, correct?
Lauren Schmitz (09:00.04)
I’m not familiar with the normative aging study. Or yeah, just the health and retirement study that I have used the most in my research because they have such rich social
Hannah Went (09:01.357)
What was it? Okay, so it’s just the health and retirement study, correct? Okay. Okay.
Lauren Schmitz (09:14.49)
data on individuals and then also such rich biological data, which is quite rare.
Hannah Went (09:16.257)
Okay.
Hannah Went (09:19.477)
Perfect, perfect. I may have heard that wrong and just made that up. Sorry, I wanted to be clear. Health and retirement study, perfect. And then, yeah, funny that you went to Michigan as well. So I’m from north of Dayton, Ohio, actually a really small town. So yeah, have a couple of friends who went to Michigan and whatnot. But loved hearing about that. Thank you for giving our listeners an introduction, Dr. Schmitz. You know, I wanna focus more on the work that you do now. You know, your current work
Lauren Schmitz (09:22.851)
No, don’t worry, don’t worry.
Lauren Schmitz (09:32.05)
Oh, no.
Lauren Schmitz (09:40.05)
Thank you.
Lauren Schmitz (09:43.493)
Yeah, of course.
Hannah Went (09:49.717)
taking this cutting edge genetic and epigenetic measures, like you said, kind of, you know, being married together with data on social environment, population-based longitudinal studies and randomized controlled trials. So I know you primarily use methods for learning causal effects from observational data with the aim of identifying policy targets that support quality of life and extend health span. So what does that mean? You know, what are you focusing on now? Ha ha.
Lauren Schmitz (10:15.875)
Yeah, yeah, no, I know it’s a large umbrella and I think yeah, my training is an economist in economics if you go into the field of microeconomics, which is really using more, you know, person level data rather than the field of macroeconomics where you’re looking at inflation rates and things like that. So if you’re, you know, doing health economics, you’re looking at
Hannah Went (10:31.857)
Thank you. Thank you.
Lauren Schmitz (10:37.99)
in our training on identifying causal effects. So using or exploiting policy changes or other kind of unexpected random events that we ourselves are not manipulating as researchers, but rather we’re kind of using historical events or things like that that happen to see that people were not expecting. And so it’s kind of almost as good as random is what we like to say.
using those events to look at causal effects. And that’s very challenging, and it requires a lot of robustness checks and things to kind of show that, you think you indeed are showing a causal effect. That’s kind of like in the background, a little thing about, my training as an economist that I think makes my approach in this field unique as well as opposed to perhaps people from other fields who are looking at social determinants of health.
Hannah Went (11:31.157)
Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you.
Lauren Schmitz (11:37.79)
Increasingly, my current and future work is taking a life course perspective on aging, which means that I’m particularly interested in how early life events from gestation through adolescence and into midlife impact late life disparities and in health and mortality. And this is really challenging to study because we don’t usually have good longitudinal data on individuals that follow them from birth until old age.
So typically we have to use data on older individuals and then exploit these historical shocks or policy changes that happened when they were younger to look at how that affected them later in life. And so for example, a current study that I’m doing is I’m looking at how exposure to cigarette tax policies, which vary at the state level, how those exposures in adolescence impacted
became a lifetime smoker and continued to smoke after age 50. And whether these policies were particularly helpful for individuals who were born with a higher genetic risk for smoking behavior. So some people have genetics that help them metabolize nicotine faster, so they’re more likely to want another cigarette sooner, and then they become more addicted. There’s also genetic pathways that expose us more to addiction. And so there I’m looking at, if people were growing up
Hannah Went (12:40.365)
Ah.
Lauren Schmitz (13:08.07)
where they had higher cigarette taxes, you know, were they less likely as a result to become addicted to smoking? Because typically people become addicted to cigarettes in adolescence, they don’t usually pick up smoking in their fifties. So I’m observing them in their fifties in the health and retirement study, but I’m using the information that we have on where they grew up and marrying that with historical tax rates to see, you know, did these people, you know, they were exposed to these tax rates, did that impact whether or not
Hannah Went (13:19.457)
Mm-hmm.
Lauren Schmitz (13:37.91)
lifetime smokers and were there differences there by genetics? So that’s one example of how and there you know it’s we’re you know because we’re utilizing these differences across states in terms of tax rates which are decided by state governments rather than individuals you know we say that we can somewhat extrapolate a more causal effect than if we were just looking at self-reported smoking behavior or something like that. So there I’m really exploiting this
Hannah Went (13:42.378)
Yeah.
Hannah Went (14:01.424)
Mm-hmm.
Hannah Went (14:06.077)
Yeah, that’s a great example. Yeah, I love that. So it’s almost like you’re kind of like working backwards almost by looking at what’s happening now and kind of saying, you know, this may be the reason because of, you know, these changes. So, and it’s really interesting. And like you said, with your background of, you know, looking into the economy and kind of what’s happened on a historical level. So do you do much then with, I guess, trying to suggest different policy changes based on your data? Would that ever be?
Lauren Schmitz (14:08.315)
Yeah, yeah, so…
Lauren Schmitz (14:12.572)
Yeah, yeah.
Lauren Schmitz (14:25.591)
Yeah.
Hannah Went (14:36.219)
part of your work.
Lauren Schmitz (14:37.75)
I mean, I think so usually where my work has what I would say more policy implications rather than direct evaluation of policies, but I will say that in this study, for example, we see that higher cigarette tax rates were effective at discouraging smoking, and especially amongst people with high genetic risk. And so there, I guess it’s reassuring to see that that cigarette tax rates did have that effect.
Hannah Went (14:44.777)
Okay.
Hannah Went (15:04.398)
Mm-hmm.
Lauren Schmitz (15:08.11)
And, you know, so there, I think there’s a suggestion that these types of taxation policies could help deter, you know, health behaviors that might, you know, in the long run really cause people to age faster and die sooner.
Hannah Went (15:23.577)
Yeah, yeah, I like the policy implications. I think that’s a great way to explain it. So yeah, why is it important to look at these early life exposures to adverse events? What else can we learn from them? Is there anything else you wanna add there? I think that’s a great question. I think that’s a great question. I think that’s a great question. I think that’s a great question. I think that’s a great question. I think that’s a great question. I think that’s a great question. I think that’s a great question.
Lauren Schmitz (15:31.95)
Thank you.
Lauren Schmitz (15:37.45)
Yeah, definitely. And so, and I think this will feed more into, you know, what we’ll discuss when we get to my epigenetics work. And, and that is that, you know, especially when we talk about the epigenome, it plays such a critical role in our very, very early life. So during, you know, embryogenesis, during the time when we’re developing in the womb, because this is really where, you know, our, our proliferation of cellular diversity, you know, our transcriptional networks,
Hannah Went (15:43.367)
Mm-hmm.
Lauren Schmitz (16:07.43)
being calibrated while we’re growing by epigenetic processes that are basically regulating, you know, whether a cell becomes a nerve cell or a muscle cell. And this is all happening at a very rapid pace when we’re developing, especially in the womb. And then also after we’re born, you know, we continue to develop at a high rate, you know, in early childhood. But especially in the womb, the developmental plasticity, the malleability of our epigenetics
and is responsive to what’s happening to mom in the outside world. So because of this, what happens to us in utero and in those early years of life could really exert lasting effects on gene expression, how we develop, how our organs develop, things like that. And when we refer to it as far as this developmental process that’s happening in the womb with epigenetics,
Hannah Went (16:42.44)
Mm-hmm.
Lauren Schmitz (17:07.35)
programming. And I really like that programming metaphor that, you know, our cells are being programmed to help us be successful in the world, you know, and so if we’re born or in utero during a famine, our cells might, you know, try to compensate for the fact that we’re not getting the nutrition that we need. And this could then affect us later in life when maybe, you know, we finally are in an environment where, you know, nutrition is not an issue. You know, we might, our cells then, you know,
Hannah Went (17:16.222)
Mm-hmm
Lauren Schmitz (17:37.45)
know to change their behavior in that way. And so perhaps we then experience more metabolic disorders or we gain weight faster, things like that, because our cells have been trained from the time we were developing to hold on to those calories. So that’s just, that’s an example that’s been studied a lot in the literature. But within the literature, this is known as fetal programming. And I think that’s super interesting because it’s saying something about how maternal malnutrition
Hannah Went (17:45.677)
Mm-hmm.
Hannah Went (18:00.457)
Thank you. Thank you.
Lauren Schmitz (18:07.35)
inflammation and other sources of prenatal stress could really contribute to fetal growth restriction, preterm birth, and kind of damage to organs that is going to impact our health and how we age. So yeah, as I’ve gotten more and more into aging, I used to think of aging as something that happened to us when we were older, but I think in part because of what we’re learning from epigenetics,
Hannah Went (18:16.46)
Mm-hmm. Mm-hmm.
Hannah Went (18:25.059)
Yeah, yeah.
Hannah Went (18:29.757)
Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you.
Hannah Went (18:34.323)
Right?
Lauren Schmitz (18:37.43)
that, no, these disparities in aging actually start when we’re developing in the womb.
Hannah Went (18:42.917)
Yeah, yeah. It’s pretty crazy to think about that and like the epigenetic inheritance and transgenerational inheritance. And yeah, I mean, they start even really before, you know, you conceive, right? All the choices that we’re making if we decide to have kids one day. And that honestly scares the hell out of me. You know, I’m not a mother. I have friends who are mothers. You know, I think I may want to have children one day, but I don’t think there is a,
Lauren Schmitz (18:46.375)
Yeah.
Lauren Schmitz (19:00.27)
I know, I know.
Hannah Went (19:12.857)
there’s, I know there’s definitively not like a suite of algorithms or epigenetic test, we can have the mother take that says, Hey, this is what, you know, your epigenetic says, maybe take these precautions to help with preterm birth or, you know, X, Y, Z, whatever it may be. So I think that’s a part of the field that will really boom and we’ll, we’ll start to learn more and more about. Mm hmm. Yeah.
Lauren Schmitz (19:32.43)
Yeah, yeah, and I think it’s something we still know so little about in humans. Um, and, um, and that’s, yeah, I think I know that as the more I study this, um, you know, I’m a 38, I haven’t had children, but the more I think about having children and knowing that I need to do that soon, but also knowing the risks that could happen because I’m an older mother and how that might, you know, would be an older mother and how that might affect development and things like that. Um, and also my partner who’s older. Um, yeah. It starts to kind of freak you out.
Hannah Went (19:35.977)
Mm-hmm.
Hannah Went (19:51.757)
Mm-hmm.
Hannah Went (20:00.157)
Thank you. Bye.
Lauren Schmitz (20:02.51)
you a little bit in your head about it because you just start to realize how incredibly sensitive this period is.
Hannah Went (20:07.917)
Yeah. Yeah. Um, there’s some hope there though too, right? Like you’re in control of the, the epigenetics too. So like making those decisions and kind of, um, yeah, taking, taking that power back, I think that can be, be very hopeful. So it’s, it’s all very interesting. We can talk about, you know, all the fertility epigenetics and everything and go down a rabbit hole.
Lauren Schmitz (20:22.731)
Yeah, I like, yeah.
Lauren Schmitz (20:28.474)
Yeah, right? No, no, but you’re right. You’re right. It should also empower us to make good decisions that way.
Hannah Went (20:34.798)
Yeah, yeah. So work is super interesting. I mean, you’re all these papers you have. I mean, you just have a huge list as I was going through trying to create this agenda for our talk today. So with these early life exposures to adverse events, how are you able to look at that through the lens of epigenetics? I know you hinted that, you know, a little bit, but can you, can you maybe elaborate more there?
Lauren Schmitz (20:58.41)
Yeah, so right now I would say in general with my work I’m using epigenetics in that I’m using epigenetic clocks. So I am using these kind of epigenome-wide measures of biological aging, kind of these biomarkers of aging that as your listeners know have just been a huge kind of boon to the field of gerontology and to other people who are studying these issues
Hannah Went (21:06.957)
Mm-hmm.
Lauren Schmitz (21:28.25)
because they seem to be such accurate predictors of faster biological aging or slower biological aging beyond our chronological age. So currently my work has been using these epigenome-wide indicators when I’m linking how does an early life event affect you, your aging later in life. And what’s so great about that is you could use other phenotypes to study aging. You could look at measure frailty indices.
you know, metabolic syndrome or things like that, that you’re just taking from self-reported data, that individuals report. But that often has a lot of measurement error. And so you need a lot bigger samples to actually really get at what you’re trying to measure, which is faster biological aging. So what I’ve been so impressed with, with the use of these clocks is just that you can, you can see how, you know, an early life event, you know, impacted and persisted and
and presumably affected how fast someone is aging biologically in a much smaller population of individuals. So yeah, so far I’m mostly using the biological clocks and then I’m starting to work more on getting at the CPG level. So yeah, so far I’m mostly using the biological clocks, and then I’m starting to work more on getting at the CPG level. So yeah, so far I’m mostly using the biological clocks, and then I’m starting to work more on getting at the CPG level. So yeah, so far I’m mostly using the biological clocks, and then I’m starting to work more on getting at the CPG level. So yeah, so far I’m mostly using the biological clocks,
Hannah Went (22:35.764)
Yeah.
Hannah Went (22:44.637)
Yeah, but it’ll be interesting to find what you, you know, look at at the CPG level and then what we know about those genes and more kind of of those mechanisms of actions and what may be causing it. So again, just keep digging and digging and digging. So I’ll keep my eyes out there. One paper that, you know, caught my eye in general, I’m, you know, hopefully some of our listeners have heard about this too is you have this paper titled in utero exposure to the Great Depression is reflected in late life.
Lauren Schmitz (22:51.014)
Mm-hmm
Yep.
Yeah, exactly. Yeah.
Hannah Went (23:13.737)
signatures. So you talked a little bit about the in utero epigenetics and can you walk us through that study though, you know, what you found, the population you studied there?
Lauren Schmitz (23:23.19)
Yeah, absolutely. So here we use the health and retirement study. And we looked at 832 individuals who were born in the 1930s, or were in utero and then were born during the 1930s across 48 different US states to compare their markers of epigenetic aging decades later when they were in their 70s and 80s. So these people were in the womb in the 1930s. And then in 2016,
Hannah Went (23:26.457)
Thank you. Bye.
Lauren Schmitz (23:53.25)
epigenetics. And so, you know, this was again the first time we were actually able to utilize this geographic variation to try to see, you know, is there a causal effect of this in utero exposure on aging? And the reason we could use these statewide differences is as it turns out that the depression was more severe in some states rather than others. So, you know, the Great Depression, it was the most severe recession in the history of the United States.
you know, on average across all states, the unemployment rates, you know, were as high as 25%. But in some states, they were actually higher. In some states, they were lower. So we were able to kind of utilize the fact that these people were in utero in some states where they were, you know, perhaps being exposed to much worse conditions than others who were in states where maybe things were a little better. And we were able to use those differences across states to see
on to differences in how they were aging biologically decades later. And so we did find that those who were born in states that were hardest hit by the recession, so places where unemployment and wage reductions were highest actually seem to show or have cells that are showing accelerated signs of aging. And so what this would suggest is that exposure to changing economic conditions,
Hannah Went (24:59.537)
Mm-hmm.
Hannah Went (25:16.765)
Mm-hmm.
Lauren Schmitz (25:24.17)
in the 1930s, these really drastic economic conditions that were occurring in the 1930s actually had lasting impacts on people who were born during this time. And so that we saw that they had, they were aging faster according to their epigenetic clock, but also then in subsequent HRS waves, excuse me. So after 2016, we could then also observe these people in 2018. So they had their blood drawn
Hannah Went (25:51.483)
Mm-hmm.
Lauren Schmitz (25:53.17)
then the HRS went back and re-interviewed them in 2018. And we saw that those who had higher epigenetic aging in 2016 were more likely to die in 2018 or had higher rates of illness and morbidity. So I think the other really interesting thing about this study is we were able to isolate when in childhood these impacts of the recession
Hannah Went (26:09.637)
And wow.
Lauren Schmitz (26:23.67)
were the worst in terms of how they impacted late life aging. And we really saw that the depression had its biggest impact on late life epigenetic aging if people were exposed to it during the in utero period. Or that exposure, I should say, they were all exposed in utero. And then we had exposure measures up to age 16 in our models. But for everybody, it looked like the only period that was significant in terms of its impact on later aging was the in utero period.
Hannah Went (26:37.098)
Mm-hmm.
Hannah Went (26:44.777)
Mm-hmm
Lauren Schmitz (26:55.252)
And so this was a really significant finding because there’s very few studies. You know, I can count them on one hand that actually show causal connections between early life insults and epigenetic programming in humans.
Hannah Went (27:10.077)
Yeah. And if I remember correctly from your paper, you have a really nice graph showing like the in utero, right? The difference of the effect. So I can, I can include that paper and you all can check that out. And it’s, it’s laid out beautifully. So yeah, super interesting. I mean, again, that scares me about everything that’s going on in today’s world more than anything with the, you know, Silicon Valley bank crashing and whatnot. But yes, super interesting that we’re, we’re able to go back and look at that data just because we have that health and
Lauren Schmitz (27:12.55)
Thank you. Thank you.
Lauren Schmitz (27:16.132)
Yeah.
Lauren Schmitz (27:23.991)
Thank you.
Lauren Schmitz (27:27.65)
I’m so proud of you.
Hannah Went (27:39.957)
retirement study now. So I think, and again, the biological aging clocks, the epigenetic methylation clocks, they’re interesting, but what makes them even more interesting is if you’re able to relate it to the mortality and that morbidity. So when you did the follow-up, you said, from 2016, I think to 2018, that the people who had that faster aging were more likely to have a chronic disease or actually pass away as a result of that increased aging. So again, we’re getting real life data, and this can be so,
Lauren Schmitz (27:49.55)
Thank you.
Lauren Schmitz (27:54.69)
Yeah.
Lauren Schmitz (28:02.57)
I’m not sure if they passed away. That’s what I was saying. So again, we’re getting real life data.
Hannah Went (28:09.957)
super applicable and we can learn from what these aging clocks have to tell about us. So I just, I think that’s a great study and one that you explained in a really nice way.
Lauren Schmitz (28:19.98)
Thank you, thank you. Yeah, thanks for highlighting it.
Hannah Went (28:22.897)
Yeah, definitely. Um, you know, I’m going to move on to another one. We can always come back, but you, you mentioned, um, actually, no, this is still part of the same paper. Um, yeah, you, you mentioned as a result and you’re finding from that paper that early life investments may actually help postpone these age related morbidity and immortality and extend healthy lifespan. So this can be, you know, hopefully fixed or, you know, mitigated. So what type of early life investments are you talking about here?
Lauren Schmitz (28:50.33)
Yeah, so I think from this study, for me as someone who studies inequality, an economist in general, we all know that there’s going to be a certain degree of inequality. There’s perfect equality is very hard to achieve in a capitalist society. But when it gets sticky to the point of it persisting in generations and things like that, I think that’s troubling
Hannah Went (29:03.341)
Mm-hmm.
Hannah Went (29:07.257)
Thank you.
Lauren Schmitz (29:20.25)
people are exposed to before birth and at early ages should affect how long they live. I think we all deserve an equal shot, at least at birth. And so, you know, this is seeming to suggest that perhaps we need to start intervening a little more or providing more support or social programs for pregnant women and families, particularly during tough economic times. And that that could really help improve the health of children, not just in the short run, but also throughout their entire life.
Hannah Went (29:25.699)
Mm-hmm.
Mm-hmm. Mm-hmm.
Hannah Went (29:41.855)
Hmm
Lauren Schmitz (29:50.33)
And then, you know, at older ages when healthcare costs get really expensive. So these kind of investments really early on may be quite efficient and pay off if they reduce medical care costs when they’re highest, when people are older. So I think as our population continues to age and we continue to live longer because of medical advances and so forth, we really need to start thinking about the costs and benefits of social programs.
Hannah Went (30:03.257)
Thank you.
Hannah Went (30:06.757)
Mm-hmm.
Hannah Went (30:18.598)
Mm-hmm.
Lauren Schmitz (30:20.33)
these really sensitive periods of development. We have some of the worst maternal leave and policies in the world. Women are out there, they’re working, they’re doing it all and they deserve to be supported if they need to be.
Hannah Went (30:27.077)
Anyhow, yeah.
Hannah Went (30:33.498)
Mm-hmm.
Hannah Went (30:41.237)
Yeah, increasing those resources. I know, you know, I’m sure everyone can relate, but I’ve had friends who are pregnant who are scared to tell their employers that they’re pregnant. And that’s just not fair. I’m sure that’s adding a ton of stress and in utero, they’re going to have that stress being relayed. So, um, I definitely think we can do better for, for those working conditions. I was just talking to one of my friends the other day, um, who, who has a position who I think her maternity leave is like, it was something crazy, like four or five months. Um, just. She had a really great
Lauren Schmitz (30:47.752)
Yeah!
Lauren Schmitz (31:10.291)
Wow.
Hannah Went (31:11.157)
position and in the US, believe it or not. And yeah, we were kind of just talking about the differences there and, you know, how that’s even possible. So I totally hear you on that and think it’s something we need to do a better job.
Lauren Schmitz (31:14.55)
Wow.
Lauren Schmitz (31:23.67)
Yeah, yeah.
Hannah Went (31:25.837)
Um, all right, now I’m moving to another paper. I skipped ahead last time. So you have, you know, another one you recently published titled, uh, the socio-economic gradient and epigenetic aging clocks evidence from the multi-ethnic study of atherosclerosis sclerosis and the health and retirement study. Um, so, so yeah, tell us about this one. You know, why is it important to conduct research on the connection between epigenetic pathways of the socio-economic gradient?
Lauren Schmitz (31:31.65)
Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you.
Lauren Schmitz (31:45.45)
Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you. Thank you.
Lauren Schmitz (31:50.51)
Yeah, yeah. So here what we were doing is we were using the health and retirement study, which in total they collected over 4,000 epigenetic samples. And then the, to double check this in the, in MESA, which is a study of cardiovascular health at older ages, they had around 1,200 people with epigenetic data. So we wanted to see in two large, you know, population representative studies, what could we see just in terms of associations
Hannah Went (31:58.199)
Mm-hmm.
Lauren Schmitz (32:20.97)
socioeconomic status in childhood and in adulthood, and how that was associated with epigenetic aging. And so, I think as we’ve discussed, epigenetics seem to be this particularly sensitive indicator of environmental exposures. And this includes exposures that are related to social inequality. So this could include everything from the nutrition we receive as children, all the ways you were just mentioning the stress
Hannah Went (32:38.861)
Mm-hmm.
Lauren Schmitz (32:50.49)
have in the workplace, or perhaps other harmful exposures like pollution or other things about our neighborhood that could affect us as adults. So we have this kind of lifetime collection of exposures because of our social status. And that can vary widely across people. And so this is one thing that just interests me so much about DNA methylation.
Hannah Went (32:57.667)
Yeah.
Hannah Went (33:10.865)
Mm-hmm.
Lauren Schmitz (33:20.99)
is that it is on this pathway between our day-to-day exposures and our gene expression. And so it might help us elucidate some of the biological factors that are driving socioeconomic differences in health and mortality. And I think, even though these things have been these gradients and social status, these health gradients have been really well studied for decades. I think there’s something about seeing it at a biological level that really draws people to the point that
Hannah Went (33:26.907)
Mm-hmm
Lauren Schmitz (33:50.45)
people and help some think a little bit more about the consequences to really see how that might be impacting people on a biological level. So here we were just looking at associations. We weren’t claiming anything about causality, but we were interested if we, and this study came out a few years ago before the Great Depression study. So we just kind of wanted to see what clocks are more highly associated with socioeconomic status. Are there some that seem to be capturing these pathways a little bit?
Hannah Went (34:01.057)
Thank you.
Hannah Went (34:12.505)
Mm-hmm.
Lauren Schmitz (34:20.553)
it better.
Hannah Went (34:21.957)
Yeah, yeah. That’s interesting. When I think of socioeconomic gradient, I mostly think of, I don’t know, socioeconomic status, I guess, right? And those differences that we might find in aging, according to if you’re poor, middle income, or rich, just kind of categorizing those. But you mentioned, well, it might be the connection to the environment you’re in, right? Because they’re all going to live in different areas. So it may be due to that instead. And I know there are several papers
Lauren Schmitz (34:30.957)
Yeah.
Lauren Schmitz (34:46.214)
Yeah.
Hannah Went (34:51.857)
connections where according to your epigenetic methylation data, we can actually tell you where you live down to the zip code based on environmental exposure, which I think is, is pretty crazy too. So it’s, they’re all just all these kind of factors and socioeconomic kind of gradient levels are interconnected and all play a role based on where you live. So yeah, I guess I didn’t, it seems rather obvious, but I guess I didn’t make that connection before and always thought that they were, you know, kind of these single buckets.
Lauren Schmitz (35:02.171)
Yeah.
Lauren Schmitz (35:12.73)
I didn’t it seems rather obvious but I guess I’m gonna be back next time and I always thought that they were
Yeah, no, it is this very, it’s a socioeconomic, it’s a very multifaceted, you know, multi-dimensional, you know, marker or indicator. Yeah, because it does, it includes, you know, how we grew up, you know, what was our parents’ socioeconomic status, right? So there’s these intergenerational things of, you know, if we grew up in a wealthy household versus a low income household and how that might have affected us when we were younger. And then how
Hannah Went (35:24.722)
Yes.
Hannah Went (35:32.557)
Mm-hmm
Hannah Went (35:36.657)
Mm-hmm.
Hannah Went (35:45.377)
Mm-hmm.
Lauren Schmitz (35:49.65)
to our education, our own achievement. And so education is in there too, and then income and wealth, occupation, right? Yeah, and then you’re right, these things are all then connected to our neighborhood environment. And so yeah, it’s really, they’re all consequential and linked together in this way that makes it hard to separate. And so yeah, it’s really, they’re all consequential and linked together in this way
Hannah Went (35:53.378)
Mm-hmm.
Hannah Went (36:00.257)
great.
Hannah Went (36:03.98)
Yeah.
Hannah Went (36:13.417)
Yeah, even the family level and neighborhood level. That’s crazy too. So you could be in one particular socioeconomic grouping, but on a neighborhood level, you could be in a different one which could have different effects. So I just think that’s all really, really fascinating. Yeah, yeah, there you go. Yeah.
Lauren Schmitz (36:16.232)
Yeah.
Lauren Schmitz (36:27.21)
Yeah, it’s an ecosystem. I think it’s an ecosystem. When I think about, I’m very lucky to have a stable job, to be able to live in a good neighborhood. And when I think about my day-to-day ecosystem and how that differs from people who might be in areas or neighborhoods where they don’t have those advantages and what their day-to-day life looks like, it’s very different.
Hannah Went (36:40.057)
Mm-hmm
Hannah Went (36:45.498)
Mm-hmm.
Lauren Schmitz (36:57.17)
ecosystems.
Hannah Went (36:58.637)
Yeah, I’m going to use that and I’m going to quote you. Oh, I’m going to tell people I got it from you. But I like that. I like the ecosystems. And, and, you know, that’s exactly what it is. Um, kind of, yeah, kind of the pathway we’re, you know, choosing to take every, every day of our lives and, um, whether that, you know, is, is good or not for, for aging based on these different factors. So, um, no, that’s, that’s great. Dr. Smith’s and just as a kind of a summary for our listeners, um, because I know I, I kind of went, went off the rail there. What exactly did you find in, in those socioeconomic gradients as, you know, a result of?
of that paper.
Lauren Schmitz (37:29.51)
Yeah, so we did this comprehensive comparative analysis of associations between education, income, wealth, occupation, neighborhood environment. And then we also looked at childhood SES by looking at parental education. And so we looked at associations between all those factors and eight epigenetic clocks and in these two large, well-powered U.S. aging studies as we mentioned. And in both studies,
Hannah Went (37:36.957)
Mm-hmm.
Hannah Went (37:43.157)
Mm-hmm.
Lauren Schmitz (37:59.55)
Mesa and in the health and retirement study, we found robust associations between these socioeconomic measures in adulthood and second or next generation clocks. So in particular, Grimmage and Dunedin Poam, at that time it was Poam before Pace came out. So Grimmage and Dunedin Poam. And then in that was in both studies. And then in the HRS, we also saw some associations
Hannah Went (38:15.057)
Mm-hmm.
Hannah Went (38:28.777)
Thank you. Thank you.
Lauren Schmitz (38:29.45)
But the Grimm age and the Poam clocks stood out as being the best and being able to capture these gradients and socioeconomic status or these gradients between socioeconomic status and epigenetic aging. And we looked at a index that kind of combined all the socioeconomic measures and then we looked at each of them individually. And when we looked at them individually, we found that educational attainment and income, had the most robust associations with these clocks,
Hannah Went (38:42.873)
Yeah.
Lauren Schmitz (38:59.47)
individuals in the most disadvantaged categories. So for those who didn’t have a degree, an education, you know, a degree or a most a high school degree. So either high school degree or less, and or people who are making under $35,000 a year in terms of their household income. We saw the most kind of extreme gradient in these folks. And then we looked at, you know, what happens is this all being
Hannah Went (39:11.42)
Mm-hmm.
Lauren Schmitz (39:29.45)
explained by smoking or health behaviors like smoking, alcohol, consumption, obesity, things that we know also are patterned by socioeconomic status. So we added those to the model and that kind of reduced the associations a little bit, but they still remained. So I think what’s interesting about that is that, again, there’s more here than just health behaviors. It’s more than just that maybe people who have more money can exercise more.
Hannah Went (39:31.84)
Mm-hmm.
Hannah Went (39:46.799)
Mm-hmm.
Mm-hmm.
Hannah Went (39:55.339)
right.
Lauren Schmitz (39:59.55)
eat better. It goes beyond that. There’s something deeper here, which I think might in part be connected to these very early life experiences.
Hannah Went (40:09.097)
Yeah, you’re still getting that signal, regardless of, you know, their, their habits and kind of controlling for those. So, um, an important point to make and, and, you know, for people who are listening, it, you can always see that kind of segregated out in the studies as you read through kind of again, controlling for those different factors. So yeah, super, super interesting. Um, so with the two, two studies we, we’ve kind of reviewed and, and talked about, um, Dr. Schmitz, what about the applications? You know, what, what can we learn from them kind of as a grouping or, or move forward, um, and, and in terms of, you know, those,
Lauren Schmitz (40:14.532)
Yeah, yeah.
Lauren Schmitz (40:24.332)
Yeah, yeah.
Hannah Went (40:39.137)
see implications or again like the, you know, in utero applications, what do you think about that?
Lauren Schmitz (40:47.83)
Yeah, I mean, I think that what makes me hopeful as an economist who studies health inequality is that because we can now link information on people’s cellular worlds with their social worlds, we can really start to see how different life experiences or public policies might actually change people to cellular level and really understand not only the social mechanisms behind early mortality, but also when in the life course people are most sensitive to those
Hannah Went (40:52.542)
Hmm.
Hannah Went (41:08.94)
Mm-hmm.
Lauren Schmitz (41:17.75)
exposures. We only have so much money in an economy at any given time. Where should we put resources? Where do they matter the most? And so in other words, I think we can see what works and what doesn’t when it comes to social policy at a cellular level. And of course, a lot of this is in the future a little bit. I think we need more data. We need to look at things more. But I think down the line, the more we can start to do more
Hannah Went (41:19.32)
Mm-hmm.
Hannah Went (41:27.978)
Mm-hmm.
Hannah Went (41:39.678)
Mm-hmm.
Lauren Schmitz (41:48.87)
where we’re really looking and evaluating direct impacts at the gene level, at the epigenome-wide level, perhaps that might help us develop or design policy interventions that can target health and equality a little more when it matters the most. So, yeah, I think these studies right now just have implications, but as we begin to amass more data, I think we’re going to hopefully start to,
Hannah Went (42:06.878)
Yeah.
Lauren Schmitz (42:17.79)
look more specifically at some of the mechanisms and then how we can perhaps provide resources that might help mitigate some of those potentially, you know, specifically or very harmful pathways or mechanisms.
Hannah Went (42:32.557)
Definitely. I think resource allocation would be huge, right? Like where do we put our time, our effort, our money? Where does that go? And then, you know, being able to learn from the past based on, you know, what’s happened year, decades later, right? And kind of learning from, you know, what, what has happened based on things like the great depression and, and, you know, how we can account for that in later years to come. So, um, yeah. And, and kind of learning a little bit more about, um, those next steps, what’s, what’s next for you? I know you had one.
Lauren Schmitz (42:41.95)
Thank you. Thank you.
Hannah Went (43:02.657)
study, you wanted to talk about that’s, you know, up and coming. And again, these studies are just going to tell us more and more and kind of get closer and closer to, um, yeah, being able to do those, those different, you know, policy changes and whatnot. So, um, yeah, tell us a little bit about that study.
Lauren Schmitz (43:02.89)
study you wanted to talk about that you know up and coming and again these studies are just going to tell us more and more.
Lauren Schmitz (43:18.211)
So yeah, so I’m really excited to be working with Hans Peter Kohler, who is an economist and demographer at the University of Pennsylvania. And he leads the Malawi Longitudinal Study of Families and Health. So this is a long, ongoing longitudinal study of health and aging in Malawi and Africa. And one thing I think that is particularly
important is that we gather diverse data on different populations. To date, all these epigenetic clocks have really been trained in high-income countries and high-income populations. Malawi has a very low economic context. It’s a low-income country. And currently, we don’t have epigenetic data from a low-income country. And so we’ve been working on a…
grant proposal that’s looking like it is perhaps maybe, you know, I don’t wanna jinx anything yet, but it’s fingers crossed it’s looking promising where we would gather epigenetic samples from 3,500 people in the Malawi Longitudinal Studies, Study of Families and Health. So we could first of all look and see, you know, do the clocks that were developed in high income populations, do they also do a good job of predicting aging in these populations?
Hannah Went (44:19.378)
Thank you. Bye.
Fingers crossed.
Hannah Went (44:30.961)
Oh wow.
Hannah Went (44:40.446)
Mm-hmm.
Lauren Schmitz (44:45.67)
the study in particular follows individuals in rule Bilalwe. So these were people who grew up with completely different, talk about ecosystems, completely different ecosystems than what we see. There’s still high rates of HIV in the population, lots of non-communicable diseases, malaria, other things. And they don’t have the same resources that we do. So it’s a very low income context. And part of me,
Hannah Went (44:50.557)
Thank you. Thank you.
Hannah Went (44:54.257)
Mianen
Lauren Schmitz (45:15.25)
You know, my hypothesis, our hypothesis going into that is that we are going to see very different pathways of aging in these populations. You know, this was the population that we’re studying right now. When they were born, the life expectancy in Malawi was 40 years old. And you know, that wasn’t that long ago. I mean, these people are 45 years old. So, you know, why are these people dying sooner? You know, we’re able to study this, you know, in this population that is more resilient
Hannah Went (45:21.899)
Mm-hmm.
Hannah Went (45:33.457)
Wow.
Hannah Went (45:41.257)
Mm-hmm.
Lauren Schmitz (45:45.41)
they survive to age 45 plus and there’s you know there’s older people in the sample as well. So we’ll be able to look at you know do we see similar pathways of aging in these individuals. We can see if the clocks you know replicate in this context and then also develop new clocks you know on this population to see if you know it’s tagging different CPG sites things like that. So you know that’s my hypothesis that we’re going to see different pathways of
Hannah Went (45:57.557)
Mm-hmm.
Hannah Went (46:09.699)
Mm-hmm.
Lauren Schmitz (46:15.39)
lived in very different ecosystems. And so I think this will be a really fascinating opportunity to study accelerated aging in another context and perhaps help us understand more about human diversity in aging.
Hannah Went (46:32.657)
Like you said, nothing, and I mean, I’m not aware of anything else that’s been done like this before, so it’s definitely needed. And it’s almost taking, again, I see kind of two pathways there, number one, using the clocks that are already created to see how they work and maybe validating that they work or validating that they don’t work in that population because it’s never been done before in such an extreme kind of low income area. And then number two, creating new clocks from that that may work in a completely different
Lauren Schmitz (46:48.87)
Yeah, yeah. Yeah.
Hannah Went (47:02.898)
population. So excited for what’s to come there.
Lauren Schmitz (47:05.93)
Yeah, absolutely. And I should mention that there are there are a few studies that have been done. So in Cebu in the Philippines, also, in Kenya and some other areas where they are showing that the clocks do seem to replicate. So, you know, it’s it’s it’s not that they don’t replicate at all. But I think we’re particularly interested to see if if they do in this population, which is, is yeah, even more low income. And then, yeah, if we can also perhaps construct some new clocks that, you know, show us
Hannah Went (47:12.421)
Yep.
Hannah Went (47:20.604)
Mm-hmm.
Hannah Went (47:29.178)
Mm-hmm.
Hannah Went (47:33.857)
Thank you. Bye.
Lauren Schmitz (47:36.011)
provide some additional insights about aging in this population.
Hannah Went (47:39.977)
Yeah, definitely. Well, Dr. Smith, you know, this has been an amazing podcast. So we’re getting to the end here. I’m excited about all your future work to come. You know, you just have a plethora of great studies, you know, infruition that are going to let us know even more about this epigenetic field and shed a lot of light on it. So I do end with one really fun question. It’s just a random question. If you could be any animal in the world, what would you be and why?
Lauren Schmitz (47:44.897)
Yeah
Lauren Schmitz (47:48.291)
Thank you.
Lauren Schmitz (48:07.15)
Oh wow, oh that’s a good one.
Lauren Schmitz (48:13.45)
any animal in the world? Oh gosh, I know, I feel like I’m gonna say an answer and then this will be one of those things where 10, you know, an hour later, I would be like, oh, I should have said dolphin or something, you know, like, you know, I, I know, I know. Let’s, yeah, I mean, I love being human. I think the human experience is awesome. I think, but yeah, it would be so, I think it would be really interesting to be able to fly. I think that would be.
Hannah Went (48:14.121)
Yes.
Hannah Went (48:25.778)
Yeah. I’m gonna regret it.
Hannah Went (48:36.518)
Yeah? Mm-hmm.
Hannah Went (48:43.383)
Yeah?
Lauren Schmitz (48:43.53)
really need to be able to fly or migrate and kind of experience a different way of kind of living in that sense of flying to different areas and things like that. So yeah, maybe a bird.
Hannah Went (48:56.557)
Yeah, definitely. So something that can fly different ecosystems. There you go.
Lauren Schmitz (49:00.791)
Yes, yes, very different ecosystem, yeah. Totally different, non-mammalian experience, yeah.
Hannah Went (49:04.019)
Yeah, no I like that.
Hannah Went (49:08.117)
There you go, well perfect. We’ve come to the end of this amazing podcast interview for people who wanna know a little bit more, reach out, where can they find you?
Lauren Schmitz (49:17.01)
So you can always look on my website to see what’s latest. That’s just laurenlschmitz.com. I also post occasionally on Twitter. And there my handle is at laurenlschmitz.
Hannah Went (49:33.117)
Perfect. And I’ll put that in the show notes for everyone wanting to learn more. You should definitely check it out. Look at, look at all the amazing work she’s done. So, um, thanks everyone for joining us at the everything epigenetics podcast. Remember you have control over your DNA methylation and epigenetics. So tune in next time to learn more. Thanks, Dr. Smiths.
Lauren Schmitz (49:49.591)
Thanks, Hannah.
