April 29, 2024 • 29 mins
Drs. Zachary Laubach and Wei Perng investigate associations between adverse maternal social experiences and offspring epigenetic aging among 205 mother-offspring pairs of minoritized racial and ethnic groups. "Maternal prenatal social experiences and offspring epigenetic age acceleration from birth to mid-childhood” is published in the February 2024 issue (Vol. 90) of Annals of Epidemiology.
Read the full article here:
https://www.sciencedirect.com/science/article/pii/S1047279723001928
Episode Credits:
- Executive Producer: Sabrina Debas
- Technical Producer: Paula Burrows
- Annals of Epidemiology is published by Elsevier.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Patrick Sullivan (00:12):
Hello, you're listening to EPITalk
Paper, a monthly podcast fromthe Annals of Epidemiology.
I'm Patrick Sullivan,Editor-in-Chief of the journal,
and in this series we take youbehind the scenes of some of the
latest epidemiologic researchfeatured in our journal.
Today we're talking with Drs.
(00:35):
Zach Laubach and Wei Perngabout their article "Maternal,
prenatal Social Experiences andOffspring Epigenetic Age
Acceleration from birth tomid-childhood.
You can find the full articleonline in the February 2024
issue of the journal at www.
annalsofepidemiology.
org.
So I'll briefly introduce ourguests.
(00:57):
Dr.
Zach Laubach is a researchassociate in the Department of
Ecology and Evolutionary Biologyat the University of Colorado,
Boulder.
He's a behavioral ecologist andevolutionary biologist
interested in how and why(proximate and ultimate) early
life environments influence thephenotypes upon which selection
acts.
And Dr.
(01:18):
Wei Perng is an AssociateProfessor of Epidemiology at the
Colorado School of PublicHealth and the Life Courseourse
Epidemiology of Adiposity andDiabetes, or LEAD Center.
She is a nutritional and lifecourse epidemiologist whose
research leverages omics scienceas a tool to study early
origins of excess adiposity andmetabolic risk in youth.
(01:39):
Doctors, fascinating work thatyou do individually, and so I
can't wait to talk about whatyou've done together and thank
you so much for joining us today.
Wei Perng (01:48):
Yeah, we're happy and excited to be here.
Patrick Sullivan (01:51):
Great.
So,Dr.
Perng, can you start out justby giving us some background on
the problem that's described inyour paper?
What is the aging epidemic andwhat is the EAA, and why is this
an important issue to study?
Wei Perng (02:04):
Yes, thank you for this question and I'll just
start by saying that I don'tknow if I'm a big fan of the
term aging epidemic,acknowledging that we use it in
the paper.
But you know, this term remindsme of other terms like
geriatric pregnancy.
That makes me cringe todescribe people who are older
than 35 when they get pregnant.
I just think this term is notideal because it really assigns
(02:27):
the notion of a disease state towhat is actually a normal,
ongoing process of senescence,whether that's biological,
functional and or reproductive.
But regardless of that, theterm is referring to this recent
increase in older populations,and here we're typically
thinking of folks who are 65years or older.
(02:48):
I believe we've observed anincrease in this population over
the last century, which is agood thing, because it's really
resulted from a general increasein overall population size, but
also the improvements in healthof older persons worldwide due
to better sanitation, in healthof older persons worldwide due
to better sanitation, healthcare, reduced infectious disease
(03:09):
burden and better access tonutritious foods, for example.
And the growth of olderpopulations worldwide, I think
is really relevant to the fieldof public health because we seek
not just to prevent disease butalso to optimize health across
the life course.
So primordial prevention and, asmy co-author, who is also on
(03:29):
this call, Dr.
Zach Laubach, will tell you, akey reason why aging coincides
with higher incidence of chronicconditions like cardiovascular
disease, cancer and diabetes isbecause natural selection will
act on reproductive fitness, sooptimizing health through the
reproductive years, and thatleaves very little selective
(03:50):
pressure after this life stage.
So I would say the latter onethird of our lives do tend to be
more fraught with poor ordeclining health and with the
growing number of aging personsworldwide, a better
understanding of the agingprocess, both in terms of
molecular markers and mechanisms, of which epigenetic age
(04:13):
acceleration is one of them, andjust a quick recap, epigenetic
age acceleration is thisdifference between your
biological age, based on DNAmethylation markers, and your
actual calendar or chronologicalage.
So a better understanding ofthese types of markers or
mechanisms and also the upstreamdeterminants of aging, can help
(04:35):
to inform public healthstrategies to promote healthy
aging, so that we can compressmorbidity at the latter stage of
the lifespan.
Patrick Sullivan (04:44):
Thanks for that explanation, and so here
you're trying to understand theassociation of maternal prenatal
social experiences and thissort of better marker or a very
indicative marker of aging?
Just for context, are theresome other kinds of exposures
that have already been proven tobe associated to sort of
accelerate aging in that way?
(05:05):
That would just help us have aframe of reference for like what
kinds of things speed up thisparticular clock.
Wei Perng (05:12):
Right- That is a bit of a challenging
question to answer becausewhether or not epigenetic age
acceleration is happening or not, so if it's higher or lower, we
don't always know what thatmeans depending on the age of
the population.
So most of this evidence hasbeen generated in adults and we
know that your typical unhealthylifestyle like smoking and
(05:35):
nicotine use, unhealthy diet,lack of physical activity, et
cetera, that those areassociated with accelerated
aging and, in turn, highermorbidity and mortality as you
age.
And we also know that thestructural determinants of
health or social determinants ofhealth, including experiences
of racial bias anddiscrimination, can get under
(05:57):
the skin and in adults isassociated with accelerated
aging.
In children, less is knownbecause it is harder to draw
blood from little people.
And on top of that, we don'tquite know yet what epigenetic
age acceleration means beforepuberty and this is something
that I think Zach will talkabout later in one of his
(06:18):
responses because from anevolutionary standpoint, there
are different selectivepressures that act right up
until you hit puberty.
So we as a group of co-authors,when we wrote this paper, tried
hard not to assign a valence,if you will, to the direction of
association that we observed,and it's really something that
we can't do until we can linkepigenetic age acceleration in
(06:42):
young children to a clinicallyrelevant health outcome that can
provide us a better grasp onwhat our findings might mean.
Patrick Sullivan (06:49):
Yeah, it's so interesting because the method
you know probably is relativelyrecent, just given the
acceleration of understanding.
So really that correlation withthe long-term outcomes, there's
just not sort of a historysince this metric has been
measured.
So thanks for that answer.
Dr.
Laubach, I'm going to move toyou now and just see if you
could tell us a little bit moreabout the purpose of this
(07:11):
particular study and theresearch question that you were
seeking to answer.
Zach Laubach (07:15):
Yeah, sure.
So this was an exploratorystudy involving data from about
200 mother-offspring pairs,where we asked a relatively
simple question, which was dosocial experiences of the mom
affect the development of herkids?
And, more specifically, welooked at whether or not
maternal experiences of racialbias or discrimination, social
support or these indicators ofsocioeconomic disadvantage
(07:38):
during these prenatal periods,whether they correspond with
epigenetic age acceleration orthis EAA marker, which is, as Dr
.
Perng mentioned, a biomarker ofaging, and then we were asking
if these differences in EAA wereevident in the mom's kids
across early and mid-childhood.
Patrick Sullivan (07:56):
So thanks for describing the question Dr.
Perng.
I wonder if you could walk usthrough what specific methods
you used to answer this questionand why that methodology this
question and why thatmethodology?
Wei Perng (08:07):
Sure.
So we didn't choose all of themethods per se, because we were
capitalizing on extant data.
This was secondary dataanalysis of the Project Viva
cohort, which is an ongoingpre-birth cohort of what was
originally over 2,000mother-offspring pairs who were
recruited during early pregnancy, at a median of nine
(08:30):
gestational weeks, I believe,and then followed up across 18
years.
Now, granted, this study didn'ttake advantage of all 18 years,
but I think a major strength ofthis study is having this
prospectively collected cohortdata to work with, because it
enhances our ability to maketemporal and therefore causal
(08:52):
inference although we know thatis a tall ask right using
observational data.
In terms of the actual analyticdesign, which is where we did
have more of a choice, we usedinformation collected from the
women at the early pregnancyvisit at around nine gestational
weeks, asking about theirsources of social support, their
(09:15):
experiences of racial bias anddiscrimination and various
indicators of both structural aswell as individual level
socioeconomic status.
So these exposures arehappening during pregnancy or
across the woman's life courseprior to getting pregnant, and
then what we have is repeatedbiosamples collected from the
(09:35):
offspring at birth using cordblood, and then in early
childhood as well asmid-childhood, so those
represent ages three to sixyears and then ages six to 10
years.
And I think that having theserepeated longitudinal bio
samples for the epigenetic ageacceleration assays is quite
unique.
(09:55):
You know I mentioned earlierhow challenging it is to obtain
blood from children, but to havethese repeated measurements
allowed us to look at patternsof change over time, look at
stability in the associationsover time, of change over time,
look at stability in theassociations over time.
And you know, we know, thathaving more measurements
provides more information aboutan outcome.
And you know, in terms of otheraspects of the analysis, we
(10:19):
started off drawing directedacyclic graphs and we use prior
knowledge as well as theprinciple of parsimony to
determine which set of variablesto account for in our
multivariable models, with theprimary goal of really
accounting for confounding andsome precision covariance.
So for this study it wasmaternal prenatal smoking, which
(10:41):
is known to affect epigeneticmarkers in offspring, the
offspring's biological sex andthen, as a precision covariate,
cell type composition, becausethat can affect epigenetic age
measures.
Patrick Sullivan (10:55):
Great, and so, when you take all those factors
into account, what were some ofthe main takeaways from your
analysis?
How did you answer the questionthat you asked at the outset?
Zach Laubach (11:06):
So our main finding was that maternal
experiences of racial bias anddiscrimination were associated
with slower epigenetic aging inthese children prior to puberty,
and these findings suggest thatsocial stresses contribute to
this intergenerational embedding, if you will, of health
disparities, possibly by slowingthis tempo of development early
in life.
And the idea here is thatchanging this tempo of
(11:30):
development may be a precursorto future pathologies that may
develop in these children.
Patrick Sullivan (11:35):
Interesting.
So is the thought that theseexposures that may occur during
gestation right, because you'remeasuring the exposures during
the time of gestation but theeffects of them play out then
over the time period that you'reactually doing the analysis as
researchers who are collectingthese specimens collected them
over time.
(11:55):
That's a pretty profoundmechanism.
I would just say, is it?
Obviously you hypothesized it,but was it surprising based on
how you went into this?
that these biological markers would show
these associations fromexposures that happened, you
know, so many years before.
Wei Perng (12:14):
I mean what I'll quickly say and put in a plug
for that is that Zach and Ipublished a prior paper using
the same cohort and it was adifferent type of analysis.
It was an epigenome-wideassociation analysis and with
these types of studies what weknow is that sometimes effects
are more detectable as childrenget older.
But it can also be the otherway around, in that the
(12:36):
epigenome becomes noisier whenthey get older, so it gets
cluttered and it's really hardto tell the toss up.
But if you're asking, we weresurprised by the findings.
I was, but Zach wasn't, and hecan probably talk a little bit
about why he wasn't.
Patrick Sullivan (12:50):
That's awesome .
So, Zach, I have anothercomment about that.
But, Zach, so you weren'tsurprised.
Why were you less surprised,would you say?
Zach Laubach (12:57):
Well, so yeah, this idea that I guess I was,
let me think about this.
So the idea that theseadversities were associated with
slower epigenetic aging wassomewhat surprising, I guess
because of the fact that most ofthe literature is looking at
these adversities and then thesevarious environmental exposures
(13:20):
that are associated with fasterbiological aging.
And I think in an adultpopulation that makes pretty
good sense.
We expect that if you're agingfaster at the latter part of
life, then you're likely goingto not live as long, and so that
makes sense there.
The part that I guess that atleast it can be that we think
might be happening or where youknow you can make some
(13:40):
justification for the resultsthat we found is that these
deviations from an average mayin and of themselves be
indicative of something that isdysregulated or where the system
is not functioning properly.
For these children, if they arenot aging as fast as maybe they
should be, that could beindicative of underlying
(14:02):
conditions, because at theseearly points in development
there's coordination and rapidchange of many biological
systems.
So this may, in and of itself,this lower epigenetic aging may
be a marker of some underlyingcondition that is preventing the
natural developmental pace.
Patrick Sullivan (14:19):
Yeah, and I think so often we have our
preconceptions about what theresults are.
We can just call it analternate and null hypothesis.
But the real progress ofscience here is that when our
questions sort of raise morehypotheses and lead to further
exploration.
Why do you think there is somuch conflicting findings
(14:40):
regarding EAA in the literature.
Zach Laubach (14:43):
Yeah, I'll just follow up.
It's sort of related to what Ijust said.
I think a lot of the work thathas been done has focused and
for good reason on theseepigenetic marks in adults, and
so there's now more work comingout looking at EAA and
determinants of this in younger.
(15:04):
Just the timing of when theseepigenetic markers are measured
could be some reasons why thereare some conflicting results.
Secondarily, these markers aredeveloped in different
populations and because of thatthese algorithms that use these
DNA methylation data they vary,so there are many different
(15:24):
kinds of epigenetic locks andthey are developed in different
populations or validated indifferent populations, and so
these two factors also couldcontribute to a lack of
generalizability, just becauseof how the algorithms are
developed or the validationpopulation in which the
algorithm is developed.
Patrick Sullivan (15:43):
Yeah, thank you, and I think it really just
reminds us that, even in areally specialized field like
this, that the questions aboutyou know how we measure and our
confidence in the measurement isone of the issues we have to
consider, and another one youknow that I always sort of
lurking for me is bias.
And so for either one of youhere you have, the biological
(16:04):
outcomes are, you know, are veryempiric, but the data on the
maternal social experiences areself-reported.
So how do you sort of weigh thepotential biases, I guess, in
the self-report aspect of theexposures?
Wei Perng (16:18):
That is a great question and it is one I think
about all the time in thecontext of nutritional
epidemiology, where we know thatthere's differential recall
bias, often with respect to thehealth outcome of interest, when
you are assessing someone'sdietary intake using a food
frequency questionnaire or arecall right, and then we have
the gold standard of havingpeople weigh their foods and
(16:41):
keep a diet record and et cetera.
In this case, what we'reinterested in is the perceived
experience of bias anddiscrimination, and there is no
gold standard.
If there is, that is theperson's self-report, and so I'm
not too worried about bias inthis particular setting,
especially because it's anobservational cohort study right
(17:04):
now.
It's not as though, you know,we found this and then went back
and asked the women.
You know what did you perceive?
So I don't think it's an issueand I think when we think about
these types of structural socialexperiences, it is the lived
experience that really is thegold standard.
Patrick Sullivan (17:20):
Great, thank you.
So I'm going to pivot a littlebit.
And the sort of other thing wealways try and get at is
understanding how scientistswork, work together, how you
come to ask the questions thatyou did, and here the two of you
worked on this together and I'mso grateful to have both of you
here to talk little bit aboutthis.
So I wonder if you can justtalk about- in the analysis that
was done, what roles you played.
I mean, you have really interesting and
(17:46):
complementary, I think, kinds oftraining.
So what roles did you play inthe research process and how do
you think those differentperspectives let you ask this
particular question?
What it would have been likemissing one of those expertise?
Wei Perng (18:08):
Well, I'm a co-investigator of the Project
Viva cohort and so Zach is ofteninterested in asking questions
that parallel his research inspotted hyenas in Kenya.
He has a cohort of spottedhyenas there.
So when I see opportunities andones that I'm also interested
in, I'll often relay it to him.
And I would say our roles haveshifted over time, because
(18:32):
initially I was primarily themethodologist and he was more
the question asker, and we tryand figure out how we can
operationalize the questionsthat he was asking in a
quantitative fashion.
Now, you know, over the yearsZach has taken epidemiology
courses.
At one point in time wanted toget an EPI certificate but
decided it was more important tojust finish his dissertation,
(18:54):
and so he's actually mastered alot of the EPI concepts.
Like he lives and breathes DAGs.
People from his lab go to himto ask about, you know, what's
the best analytic approach forthis, and so for this project I
would say it was really split50-50.
You know, aging is somethingthat we both become interested
in.
It's kind of at the other endof the spectrum of what I study,
(19:17):
which is early origins anddevelopmental origins of health
and disease, but it's very mucha part of life course research
and we both believe that thissocial aspect of you know our
experiences is increasinglyrecognized as one of the
strongest drivers of health anddisease.
So we were both interested inthe topic.
We came up with the analyticapproach together and then Zach
(19:40):
implemented the analysis thistime so, and we we split the
paper writing.
So you know, the methods cameeasily to me because I know the
cohort so well, but he reallydrafted the intro and the
discussion and we workedtogether on it and sent it to
co-authors.
Patrick Sullivan (19:57):
Thanks.
Dr.
Laubach, any other thoughtsabout, like how you work
together on this?
Zach Laubach (20:01):
Yeah, so, as Dr.
Perng mentioned, we've beenworking on science related
questions for a while.
We met in grad school and, yeah,we met teaching a physiology
lab as grad students and we'reactually- I guess it's worth
mentioning that we're partnersas well and I think it's sort of
interesting and not so uncommon.
There's a number of scientistswho, I know, at least, that have
(20:22):
formed these collaborations.
It lends to lots of sciencediscussions over dinner and that
may sound like a fairly drydinner conversation, but I
actually find it really reallyuseful.
As Wei mentioned, I'm justgoing to say Wei, the epi
methods have always been veryinteresting to me because they
apply ways or they're a methodthat can be used to test these
(20:44):
causal hypotheses withobservational data, which is the
problem that many ecology andevolutionary biologists also
face.
So these dialogues that we'vehad have allowed us to think
about ways in which there can beuseful crosstalk between these
disciplines that are otherwise,I think, fairly siloed or have
been, that are otherwise, Ithink, fairly siloed or have
(21:05):
been, but I think there's anincreasing interest in combining
the expertise and the theoryacross these two different
fields.
Patrick Sullivan (21:11):
Yeah, the most interesting science happens at
the margins, you know the littleintersections of fields, I
think.
So these are really interestingones and sometime although we
don't have time on the podcasttoday, but sometime I want to
hear about the hyenas.
I mean, probably everybodywants to hear about the hyenas.
Wei Perng (21:29):
It's true, Zach gets to show pictures of the
Serengeti and safaris on his jobtalks and I have nothing like
that to show.
I just have tables of numbers.
Patrick Sullivan (21:39):
Well, it takes all these pieces, and I do
think that the combination ofthese methods and your mutual
interest in epidemiology is areally interesting aspect of the
paper that you brought forward.
So I'll just ask either of youkeeping, in mind that I think
we're really interested in thescience, but also in how science
happens and how these fieldscome together, whether you have
(21:59):
any last thoughts that you'dlike to share with the listeners
?
If they read it before, this maygive context.
If they haven't read it,interesting to understand how it
came about and how you workedon it.
But any closing thoughts aboutthe manuscript or the way that
it came about that you want toshare with our listeners?
Wei Perng (22:18):
I will just keep this brief.
I think Zach has a much betterresponse to this question,
especially about what would youtell your younger self which I
think is a great quI guess Iwould say and Zach reminds me of
this a lot that the bestscience happens when it's
interdisciplinary and there'schallenges at the beginning,
because it's as though you speakdifferent languages, some
(22:41):
terminology that epidemiologistsare really specific about.
It's like nails on thechalkboard when you hear someone
misusing it, and similarlythere's times when I've used the
word evolve in completely thewrong way and Zach will remind
me.
So I think it's been a reallynice synergistic collaboration
and I've learned a lot.
I still struggle to think abouthow to place my research
(23:02):
findings in the context ofevolution, knowing that
everything happens in thecontext of evolution.
So I would like to be able tobetter use an evolutionary
framework in the way that Ithink about my research,
especially because some of myresearch is in precision
medicine, which that reallystarts with the gene by
environment interaction and ourgenetics is due to our ancestry,
(23:24):
and so it is actually quiterelevant to my work.
So I do see futurecollaborations with Zach in that
realm, and that's kind of whatI have to say about that, but
maybe I'll let Zach talk about.
You know something that he'dlike to share with the audience.
Zach Laubach (23:38):
I'll share two quick things if we have time for
that.
Just thinking a little bitabout the question of, you know,
epidemiology is thismethod-based approach, so it's
very applicable and it's alsovery clear, and it extends
naturally to other disciplines.
But one piece of or sort offood for thought that I could
give about how epidemiology orpublic health researchers can
(23:59):
use evolution is more of aconceptual idea and it comes
from this paper that was writtenby Randolph Nessie and Stephen
Stearns, and they're arguing forthe ways in which evolutionary
biology is important for publichealth.
And they're arguing for theways in which evolutionary
biology is important for publichealth, and I'll paraphrase them
as I recall it.
They say that we are humans.
We are vulnerable to diseasesbecause we're not these machines
(24:19):
that are built from a plan, butrather we're just this bundle
of compromises that have beenshaped by natural selection that
maximizes reproduction and nothealth, and that was something
Wei mentioned earlier.
So it can be the case that whatis good for your fitness may
not necessarily improve yourhealth, and I think that is
worth keeping in mind becausewhile these mechanisms that may
(24:41):
affect health are important,they're not acting in isolation
from other important processesontology and phylogeny and
adaptive functions.
And then, moving to thisquestion about what would you
tell your younger self or whatadvice would you give for
professionals that areinterested in these
interdisciplinary collaborations, and much like what you said
(25:02):
about Dr.
Sullivan, about the good signshappening at the margins, I
would agree and say that peopleshould embrace this uncertainty
of what you don't know, becausethere's a lot to be learned
outside of these silos ofexpertise.
And I think here in these spaceswe're sort of uninhibited by
this established dogma or fieldor the expectations of what we
maybe should know or how wethink about a problem.
(25:24):
And I think if we, yeah,embrace those margins, then we
can think openly and injectcreativity.
And along those lines it'sworthwhile to just take time and
observe biology and nature andmaybe quietly.
So, some of the most notable,both public health achievements
like John Snow's removal of thepump handle, or to stop the
(25:44):
cholera outbreak, or CharlesDarwin's description of
evolution by natural selection.
A common thread of all of thesesort of monumental
contributions to the field isthat these came from scientists
who were really astute observersof the natural world.
So combining these twopractices of embracing a bit of
uncertainty and taking time tolisten, I think it'd be pretty
(26:06):
transformative and I guess Iwould agree with what you said.
I think that's really where wefind some innovative and often
impactful science is in thosemargins.
Wei Perng (26:17):
I will just add one more thing to that, because I
can't help it.
But you know, in the context ofthinking about experiences of
racial bias and discrimination,I heard a speaker, Dr Sandro
Galea, who you may know, DrSullivan.
He came and talked at asteering committee meeting that
I was at and he said the textureof the lived experience is much
more informative than any fancymethod, and I think that's a
(26:40):
form of listening and observingand I think we would do
ourselves a great service to,you know, do more of that.
You know we're so boxed intoquantitative analyses but maybe
more qualitative work, andthat's something that I'm
learning as well.
Patrick Sullivan (26:57):
Yeah, thank you for sharing those words from
Dr.
Galea, and I'm actually justgoing to reflect back like what
a rich conversation this hasbeen, and the thing that I'm
going to put on my coffee mug,with all credit given to Dr
Lobach, is, if I got it right, abundle of genetic mistakes
shaped by natural selection/ Did.
Zach Laubach (27:11):
I get that righ hat's the paraphrase and that's
from a physician.
I think they're a physician,andolph Nessie and Steven Stern,
who is a life historyevolutionary biologist, and I do
think, yeah, that life historybiology is really integral into
these questions of developmentalplasticity and aging.
Patrick Sullivan (27:30):
So, thank you, got the attribution right, but
I still want to put it on acoffee mug.
If I make them, I'll make onefor each of you as well.
There you go.
Wei Perng (27:38):
Oh well, thank you for the coffee mug from this
year.
Oh right, those would be nice Ymugs, yes next year wit.
Patrick Sullivan (27:49):
OYes, ynext year with natural selection.
So this has been a greatconversation.
We have done another podcastwith like a pair of researchers,
but I think when you commentthings from different
perspectives, that what reallyI've seen animated, heard in
your voices for our listeners,but seen in our Zoom- because we
also have a Zoom conversationis just how these ideas sort of
ping off each other and scaffoldto answer interesting questions
(28:12):
.
So I want to thank you for yourwork.
I want to thank you for bringingit to Annals for publication
and especially for thegenerosity of your time to
answer these questions today,and although we sort of
brainstorm a little bitbeforehand about what we might
ask.
I'm also infamous for going offthe script, so also thank you
for rolling with the punches.
But I think it's a greatconversation and a pleasure to
(28:33):
have you on the podcast, and welook forward to what your future
research will be.
Wei Perng (28:37):
Likewise.
Thank you for your time and Iknow it's close to dinner time
for you if you're on the EastCoast.
Patrick Sullivan (28:43):
Yeah, I am on the East Coast and dinner is
looming.
So, thank you, thank you bothso much.
Thank you very much.
Thank you.
Thank you both so much.
Thank you very mu I'm your host, patrick Sullivan.
Thanks for tuning in to thisepisode and see you next time on
EpiTalk, brought to you byAnnals of Epidemiology, the
official journal of the AmericanCollege of Epidemiology.
(29:04):
For a transcript of thispodcast or to read the article
featured on this episode andmore from the journal, you can
visit us online atwwwannalsofepidemiologyorg.
Hello, you're listening to EPITalk
Paper, a monthly podcast fromthe Annals of Epidemiology.
I'm Patrick Sullivan,Editor-in-Chief of the journal,
and in this series we take youbehind the scenes of some of the
latest epidemiologic researchfeatured in our journal.
Today we're talking with Drs.
(00:35):
Zach Laubach and Wei Perngabout their article "Maternal,
prenatal Social Experiences andOffspring Epigenetic Age
Acceleration from birth tomid-childhood.
You can find the full articleonline in the February 2024
issue of the journal at www.
annalsofepidemiology.
org.
So I'll briefly introduce ourguests.
(00:57):
Dr.
Zach Laubach is a researchassociate in the Department of
Ecology and Evolutionary Biologyat the University of Colorado,
Boulder.
He's a behavioral ecologist andevolutionary biologist
interested in how and why(proximate and ultimate) early
life environments influence thephenotypes upon which selection
acts.
And Dr.
(01:18):
Wei Perng is an AssociateProfessor of Epidemiology at the
Colorado School of PublicHealth and the Life Courseourse
Epidemiology of Adiposity andDiabetes, or LEAD Center.
She is a nutritional and lifecourse epidemiologist whose
research leverages omics scienceas a tool to study early
origins of excess adiposity andmetabolic risk in youth.
(01:39):
Doctors, fascinating work thatyou do individually, and so I
can't wait to talk about whatyou've done together and thank
you so much for joining us today.
Wei Perng (01:48):
Yeah, we're happy and excited to be here.
Patrick Sullivan (01:51):
Great.
So,Dr.
Perng, can you start out justby giving us some background on
the problem that's described inyour paper?
What is the aging epidemic andwhat is the EAA, and why is this
an important issue to study?
Wei Perng (02:04):
Yes, thank you for this question and I'll just
start by saying that I don'tknow if I'm a big fan of the
term aging epidemic,acknowledging that we use it in
the paper.
But you know, this term remindsme of other terms like
geriatric pregnancy.
That makes me cringe todescribe people who are older
than 35 when they get pregnant.
I just think this term is notideal because it really assigns
(02:27):
the notion of a disease state towhat is actually a normal,
ongoing process of senescence,whether that's biological,
functional and or reproductive.
But regardless of that, theterm is referring to this recent
increase in older populations,and here we're typically
thinking of folks who are 65years or older.
(02:48):
I believe we've observed anincrease in this population over
the last century, which is agood thing, because it's really
resulted from a general increasein overall population size, but
also the improvements in healthof older persons worldwide due
to better sanitation, in healthof older persons worldwide due
to better sanitation, healthcare, reduced infectious disease
(03:09):
burden and better access tonutritious foods, for example.
And the growth of olderpopulations worldwide, I think
is really relevant to the fieldof public health because we seek
not just to prevent disease butalso to optimize health across
the life course.
So primordial prevention and, asmy co-author, who is also on
(03:29):
this call, Dr.
Zach Laubach, will tell you, akey reason why aging coincides
with higher incidence of chronicconditions like cardiovascular
disease, cancer and diabetes isbecause natural selection will
act on reproductive fitness, sooptimizing health through the
reproductive years, and thatleaves very little selective
(03:50):
pressure after this life stage.
So I would say the latter onethird of our lives do tend to be
more fraught with poor ordeclining health and with the
growing number of aging personsworldwide, a better
understanding of the agingprocess, both in terms of
molecular markers and mechanisms, of which epigenetic age
(04:13):
acceleration is one of them, andjust a quick recap, epigenetic
age acceleration is thisdifference between your
biological age, based on DNAmethylation markers, and your
actual calendar or chronologicalage.
So a better understanding ofthese types of markers or
mechanisms and also the upstreamdeterminants of aging, can help
(04:35):
to inform public healthstrategies to promote healthy
aging, so that we can compressmorbidity at the latter stage of
the lifespan.
Patrick Sullivan (04:44):
Thanks for that explanation, and so here
you're trying to understand theassociation of maternal prenatal
social experiences and thissort of better marker or a very
indicative marker of aging?
Just for context, are theresome other kinds of exposures
that have already been proven tobe associated to sort of
accelerate aging in that way?
(05:05):
That would just help us have aframe of reference for like what
kinds of things speed up thisparticular clock.
Wei Perng (05:12):
Right- That is a bit of a challenging
question to answer becausewhether or not epigenetic age
acceleration is happening or not, so if it's higher or lower, we
don't always know what thatmeans depending on the age of
the population.
So most of this evidence hasbeen generated in adults and we
know that your typical unhealthylifestyle like smoking and
(05:35):
nicotine use, unhealthy diet,lack of physical activity, et
cetera, that those areassociated with accelerated
aging and, in turn, highermorbidity and mortality as you
age.
And we also know that thestructural determinants of
health or social determinants ofhealth, including experiences
of racial bias anddiscrimination, can get under
(05:57):
the skin and in adults isassociated with accelerated
aging.
In children, less is knownbecause it is harder to draw
blood from little people.
And on top of that, we don'tquite know yet what epigenetic
age acceleration means beforepuberty and this is something
that I think Zach will talkabout later in one of his
(06:18):
responses because from anevolutionary standpoint, there
are different selectivepressures that act right up
until you hit puberty.
So we as a group of co-authors,when we wrote this paper, tried
hard not to assign a valence,if you will, to the direction of
association that we observed,and it's really something that
we can't do until we can linkepigenetic age acceleration in
(06:42):
young children to a clinicallyrelevant health outcome that can
provide us a better grasp onwhat our findings might mean.
Patrick Sullivan (06:49):
Yeah, it's so interesting because the method
you know probably is relativelyrecent, just given the
acceleration of understanding.
So really that correlation withthe long-term outcomes, there's
just not sort of a historysince this metric has been
measured.
So thanks for that answer.
Dr.
Laubach, I'm going to move toyou now and just see if you
could tell us a little bit moreabout the purpose of this
(07:11):
particular study and theresearch question that you were
seeking to answer.
Zach Laubach (07:15):
Yeah, sure.
So this was an exploratorystudy involving data from about
200 mother-offspring pairs,where we asked a relatively
simple question, which was dosocial experiences of the mom
affect the development of herkids?
And, more specifically, welooked at whether or not
maternal experiences of racialbias or discrimination, social
support or these indicators ofsocioeconomic disadvantage
(07:38):
during these prenatal periods,whether they correspond with
epigenetic age acceleration orthis EAA marker, which is, as Dr
.
Perng mentioned, a biomarker ofaging, and then we were asking
if these differences in EAA wereevident in the mom's kids
across early and mid-childhood.
Patrick Sullivan (07:56):
So thanks for describing the question Dr.
Perng.
I wonder if you could walk usthrough what specific methods
you used to answer this questionand why that methodology this
question and why thatmethodology?
Wei Perng (08:07):
Sure.
So we didn't choose all of themethods per se, because we were
capitalizing on extant data.
This was secondary dataanalysis of the Project Viva
cohort, which is an ongoingpre-birth cohort of what was
originally over 2,000mother-offspring pairs who were
recruited during early pregnancy, at a median of nine
(08:30):
gestational weeks, I believe,and then followed up across 18
years.
Now, granted, this study didn'ttake advantage of all 18 years,
but I think a major strength ofthis study is having this
prospectively collected cohortdata to work with, because it
enhances our ability to maketemporal and therefore causal
(08:52):
inference although we know thatis a tall ask right using
observational data.
In terms of the actual analyticdesign, which is where we did
have more of a choice, we usedinformation collected from the
women at the early pregnancyvisit at around nine gestational
weeks, asking about theirsources of social support, their
(09:15):
experiences of racial bias anddiscrimination and various
indicators of both structural aswell as individual level
socioeconomic status.
So these exposures arehappening during pregnancy or
across the woman's life courseprior to getting pregnant, and
then what we have is repeatedbiosamples collected from the
(09:35):
offspring at birth using cordblood, and then in early
childhood as well asmid-childhood, so those
represent ages three to sixyears and then ages six to 10
years.
And I think that having theserepeated longitudinal bio
samples for the epigenetic ageacceleration assays is quite
unique.
(09:55):
You know I mentioned earlierhow challenging it is to obtain
blood from children, but to havethese repeated measurements
allowed us to look at patternsof change over time, look at
stability in the associationsover time, of change over time,
look at stability in theassociations over time.
And you know, we know, thathaving more measurements
provides more information aboutan outcome.
And you know, in terms of otheraspects of the analysis, we
(10:19):
started off drawing directedacyclic graphs and we use prior
knowledge as well as theprinciple of parsimony to
determine which set of variablesto account for in our
multivariable models, with theprimary goal of really
accounting for confounding andsome precision covariance.
So for this study it wasmaternal prenatal smoking, which
(10:41):
is known to affect epigeneticmarkers in offspring, the
offspring's biological sex andthen, as a precision covariate,
cell type composition, becausethat can affect epigenetic age
measures.
Patrick Sullivan (10:55):
Great, and so, when you take all those factors
into account, what were some ofthe main takeaways from your
analysis?
How did you answer the questionthat you asked at the outset?
Zach Laubach (11:06):
So our main finding was that maternal
experiences of racial bias anddiscrimination were associated
with slower epigenetic aging inthese children prior to puberty,
and these findings suggest thatsocial stresses contribute to
this intergenerational embedding, if you will, of health
disparities, possibly by slowingthis tempo of development early
in life.
And the idea here is thatchanging this tempo of
(11:30):
development may be a precursorto future pathologies that may
develop in these children.
Patrick Sullivan (11:35):
Interesting.
So is the thought that theseexposures that may occur during
gestation right, because you'remeasuring the exposures during
the time of gestation but theeffects of them play out then
over the time period that you'reactually doing the analysis as
researchers who are collectingthese specimens collected them
over time.
(11:55):
That's a pretty profoundmechanism.
I would just say, is it?
Obviously you hypothesized it,but was it surprising based on
how you went into this?
that these biological markers would show
these associations fromexposures that happened, you
know, so many years before.
Wei Perng (12:14):
I mean what I'll quickly say and put in a plug
for that is that Zach and Ipublished a prior paper using
the same cohort and it was adifferent type of analysis.
It was an epigenome-wideassociation analysis and with
these types of studies what weknow is that sometimes effects
are more detectable as childrenget older.
But it can also be the otherway around, in that the
(12:36):
epigenome becomes noisier whenthey get older, so it gets
cluttered and it's really hardto tell the toss up.
But if you're asking, we weresurprised by the findings.
I was, but Zach wasn't, and hecan probably talk a little bit
about why he wasn't.
Patrick Sullivan (12:50):
That's awesome .
So, Zach, I have anothercomment about that.
But, Zach, so you weren'tsurprised.
Why were you less surprised,would you say?
Zach Laubach (12:57):
Well, so yeah, this idea that I guess I was,
let me think about this.
So the idea that theseadversities were associated with
slower epigenetic aging wassomewhat surprising, I guess
because of the fact that most ofthe literature is looking at
these adversities and then thesevarious environmental exposures
(13:20):
that are associated with fasterbiological aging.
And I think in an adultpopulation that makes pretty
good sense.
We expect that if you're agingfaster at the latter part of
life, then you're likely goingto not live as long, and so that
makes sense there.
The part that I guess that atleast it can be that we think
might be happening or where youknow you can make some
(13:40):
justification for the resultsthat we found is that these
deviations from an average mayin and of themselves be
indicative of something that isdysregulated or where the system
is not functioning properly.
For these children, if they arenot aging as fast as maybe they
should be, that could beindicative of underlying
(14:02):
conditions, because at theseearly points in development
there's coordination and rapidchange of many biological
systems.
So this may, in and of itself,this lower epigenetic aging may
be a marker of some underlyingcondition that is preventing the
natural developmental pace.
Patrick Sullivan (14:19):
Yeah, and I think so often we have our
preconceptions about what theresults are.
We can just call it analternate and null hypothesis.
But the real progress ofscience here is that when our
questions sort of raise morehypotheses and lead to further
exploration.
Why do you think there is somuch conflicting findings
(14:40):
regarding EAA in the literature.
Zach Laubach (14:43):
Yeah, I'll just follow up.
It's sort of related to what Ijust said.
I think a lot of the work thathas been done has focused and
for good reason on theseepigenetic marks in adults, and
so there's now more work comingout looking at EAA and
determinants of this in younger.
(15:04):
Just the timing of when theseepigenetic markers are measured
could be some reasons why thereare some conflicting results.
Secondarily, these markers aredeveloped in different
populations and because of thatthese algorithms that use these
DNA methylation data they vary,so there are many different
(15:24):
kinds of epigenetic locks andthey are developed in different
populations or validated indifferent populations, and so
these two factors also couldcontribute to a lack of
generalizability, just becauseof how the algorithms are
developed or the validationpopulation in which the
algorithm is developed.
Patrick Sullivan (15:43):
Yeah, thank you, and I think it really just
reminds us that, even in areally specialized field like
this, that the questions aboutyou know how we measure and our
confidence in the measurement isone of the issues we have to
consider, and another one youknow that I always sort of
lurking for me is bias.
And so for either one of youhere you have, the biological
(16:04):
outcomes are, you know, are veryempiric, but the data on the
maternal social experiences areself-reported.
So how do you sort of weigh thepotential biases, I guess, in
the self-report aspect of theexposures?
Wei Perng (16:18):
That is a great question and it is one I think
about all the time in thecontext of nutritional
epidemiology, where we know thatthere's differential recall
bias, often with respect to thehealth outcome of interest, when
you are assessing someone'sdietary intake using a food
frequency questionnaire or arecall right, and then we have
the gold standard of havingpeople weigh their foods and
(16:41):
keep a diet record and et cetera.
In this case, what we'reinterested in is the perceived
experience of bias anddiscrimination, and there is no
gold standard.
If there is, that is theperson's self-report, and so I'm
not too worried about bias inthis particular setting,
especially because it's anobservational cohort study right
(17:04):
now.
It's not as though, you know,we found this and then went back
and asked the women.
You know what did you perceive?
So I don't think it's an issueand I think when we think about
these types of structural socialexperiences, it is the lived
experience that really is thegold standard.
Patrick Sullivan (17:20):
Great, thank you.
So I'm going to pivot a littlebit.
And the sort of other thing wealways try and get at is
understanding how scientistswork, work together, how you
come to ask the questions thatyou did, and here the two of you
worked on this together and I'mso grateful to have both of you
here to talk little bit aboutthis.
So I wonder if you can justtalk about- in the analysis that
was done, what roles you played.
I mean, you have really interesting and
(17:46):
complementary, I think, kinds oftraining.
So what roles did you play inthe research process and how do
you think those differentperspectives let you ask this
particular question?
What it would have been likemissing one of those expertise?
Wei Perng (18:08):
Well, I'm a co-investigator of the Project
Viva cohort and so Zach is ofteninterested in asking questions
that parallel his research inspotted hyenas in Kenya.
He has a cohort of spottedhyenas there.
So when I see opportunities andones that I'm also interested
in, I'll often relay it to him.
And I would say our roles haveshifted over time, because
(18:32):
initially I was primarily themethodologist and he was more
the question asker, and we tryand figure out how we can
operationalize the questionsthat he was asking in a
quantitative fashion.
Now, you know, over the yearsZach has taken epidemiology
courses.
At one point in time wanted toget an EPI certificate but
decided it was more important tojust finish his dissertation,
(18:54):
and so he's actually mastered alot of the EPI concepts.
Like he lives and breathes DAGs.
People from his lab go to himto ask about, you know, what's
the best analytic approach forthis, and so for this project I
would say it was really split50-50.
You know, aging is somethingthat we both become interested
in.
It's kind of at the other endof the spectrum of what I study,
(19:17):
which is early origins anddevelopmental origins of health
and disease, but it's very mucha part of life course research
and we both believe that thissocial aspect of you know our
experiences is increasinglyrecognized as one of the
strongest drivers of health anddisease.
So we were both interested inthe topic.
We came up with the analyticapproach together and then Zach
(19:40):
implemented the analysis thistime so, and we we split the
paper writing.
So you know, the methods cameeasily to me because I know the
cohort so well, but he reallydrafted the intro and the
discussion and we workedtogether on it and sent it to
co-authors.
Patrick Sullivan (19:57):
Thanks.
Dr.
Laubach, any other thoughtsabout, like how you work
together on this?
Zach Laubach (20:01):
Yeah, so, as Dr.
Perng mentioned, we've beenworking on science related
questions for a while.
We met in grad school and, yeah,we met teaching a physiology
lab as grad students and we'reactually- I guess it's worth
mentioning that we're partnersas well and I think it's sort of
interesting and not so uncommon.
There's a number of scientistswho, I know, at least, that have
(20:22):
formed these collaborations.
It lends to lots of sciencediscussions over dinner and that
may sound like a fairly drydinner conversation, but I
actually find it really reallyuseful.
As Wei mentioned, I'm justgoing to say Wei, the epi
methods have always been veryinteresting to me because they
apply ways or they're a methodthat can be used to test these
(20:44):
causal hypotheses withobservational data, which is the
problem that many ecology andevolutionary biologists also
face.
So these dialogues that we'vehad have allowed us to think
about ways in which there can beuseful crosstalk between these
disciplines that are otherwise,I think, fairly siloed or have
been, that are otherwise, Ithink, fairly siloed or have
(21:05):
been, but I think there's anincreasing interest in combining
the expertise and the theoryacross these two different
fields.
Patrick Sullivan (21:11):
Yeah, the most interesting science happens at
the margins, you know the littleintersections of fields, I
think.
So these are really interestingones and sometime although we
don't have time on the podcasttoday, but sometime I want to
hear about the hyenas.
I mean, probably everybodywants to hear about the hyenas.
Wei Perng (21:29):
It's true, Zach gets to show pictures of the
Serengeti and safaris on his jobtalks and I have nothing like
that to show.
I just have tables of numbers.
Patrick Sullivan (21:39):
Well, it takes all these pieces, and I do
think that the combination ofthese methods and your mutual
interest in epidemiology is areally interesting aspect of the
paper that you brought forward.
So I'll just ask either of youkeeping, in mind that I think
we're really interested in thescience, but also in how science
happens and how these fieldscome together, whether you have
(21:59):
any last thoughts that you'dlike to share with the listeners
?
If they read it before, this maygive context.
If they haven't read it,interesting to understand how it
came about and how you workedon it.
But any closing thoughts aboutthe manuscript or the way that
it came about that you want toshare with our listeners?
Wei Perng (22:18):
I will just keep this brief.
I think Zach has a much betterresponse to this question,
especially about what would youtell your younger self which I
think is a great quI guess Iwould say and Zach reminds me of
this a lot that the bestscience happens when it's
interdisciplinary and there'schallenges at the beginning,
because it's as though you speakdifferent languages, some
(22:41):
terminology that epidemiologistsare really specific about.
It's like nails on thechalkboard when you hear someone
misusing it, and similarlythere's times when I've used the
word evolve in completely thewrong way and Zach will remind
me.
So I think it's been a reallynice synergistic collaboration
and I've learned a lot.
I still struggle to think abouthow to place my research
(23:02):
findings in the context ofevolution, knowing that
everything happens in thecontext of evolution.
So I would like to be able tobetter use an evolutionary
framework in the way that Ithink about my research,
especially because some of myresearch is in precision
medicine, which that reallystarts with the gene by
environment interaction and ourgenetics is due to our ancestry,
(23:24):
and so it is actually quiterelevant to my work.
So I do see futurecollaborations with Zach in that
realm, and that's kind of whatI have to say about that, but
maybe I'll let Zach talk about.
You know something that he'dlike to share with the audience.
Zach Laubach (23:38):
I'll share two quick things if we have time for
that.
Just thinking a little bitabout the question of, you know,
epidemiology is thismethod-based approach, so it's
very applicable and it's alsovery clear, and it extends
naturally to other disciplines.
But one piece of or sort offood for thought that I could
give about how epidemiology orpublic health researchers can
(23:59):
use evolution is more of aconceptual idea and it comes
from this paper that was writtenby Randolph Nessie and Stephen
Stearns, and they're arguing forthe ways in which evolutionary
biology is important for publichealth.
And they're arguing for theways in which evolutionary
biology is important for publichealth, and I'll paraphrase them
as I recall it.
They say that we are humans.
We are vulnerable to diseasesbecause we're not these machines
(24:19):
that are built from a plan, butrather we're just this bundle
of compromises that have beenshaped by natural selection that
maximizes reproduction and nothealth, and that was something
Wei mentioned earlier.
So it can be the case that whatis good for your fitness may
not necessarily improve yourhealth, and I think that is
worth keeping in mind becausewhile these mechanisms that may
(24:41):
affect health are important,they're not acting in isolation
from other important processesontology and phylogeny and
adaptive functions.
And then, moving to thisquestion about what would you
tell your younger self or whatadvice would you give for
professionals that areinterested in these
interdisciplinary collaborations, and much like what you said
(25:02):
about Dr.
Sullivan, about the good signshappening at the margins, I
would agree and say that peopleshould embrace this uncertainty
of what you don't know, becausethere's a lot to be learned
outside of these silos ofexpertise.
And I think here in these spaceswe're sort of uninhibited by
this established dogma or fieldor the expectations of what we
maybe should know or how wethink about a problem.
(25:24):
And I think if we, yeah,embrace those margins, then we
can think openly and injectcreativity.
And along those lines it'sworthwhile to just take time and
observe biology and nature andmaybe quietly.
So, some of the most notable,both public health achievements
like John Snow's removal of thepump handle, or to stop the
(25:44):
cholera outbreak, or CharlesDarwin's description of
evolution by natural selection.
A common thread of all of thesesort of monumental
contributions to the field isthat these came from scientists
who were really astute observersof the natural world.
So combining these twopractices of embracing a bit of
uncertainty and taking time tolisten, I think it'd be pretty
(26:06):
transformative and I guess Iwould agree with what you said.
I think that's really where wefind some innovative and often
impactful science is in thosemargins.
Wei Perng (26:17):
I will just add one more thing to that, because I
can't help it.
But you know, in the context ofthinking about experiences of
racial bias and discrimination,I heard a speaker, Dr Sandro
Galea, who you may know, DrSullivan.
He came and talked at asteering committee meeting that
I was at and he said the textureof the lived experience is much
more informative than any fancymethod, and I think that's a
(26:40):
form of listening and observingand I think we would do
ourselves a great service to,you know, do more of that.
You know we're so boxed intoquantitative analyses but maybe
more qualitative work, andthat's something that I'm
learning as well.
Patrick Sullivan (26:57):
Yeah, thank you for sharing those words from
Dr.
Galea, and I'm actually justgoing to reflect back like what
a rich conversation this hasbeen, and the thing that I'm
going to put on my coffee mug,with all credit given to Dr
Lobach, is, if I got it right, abundle of genetic mistakes
shaped by natural selection/ Did.
Zach Laubach (27:11):
I get that righ hat's the paraphrase and that's
from a physician.
I think they're a physician,andolph Nessie and Steven Stern,
who is a life historyevolutionary biologist, and I do
think, yeah, that life historybiology is really integral into
these questions of developmentalplasticity and aging.
Patrick Sullivan (27:30):
So, thank you, got the attribution right, but
I still want to put it on acoffee mug.
If I make them, I'll make onefor each of you as well.
There you go.
Wei Perng (27:38):
Oh well, thank you for the coffee mug from this
year.
Oh right, those would be nice Ymugs, yes next year wit.
Patrick Sullivan (27:49):
OYes, ynext year with natural selection.
So this has been a greatconversation.
We have done another podcastwith like a pair of researchers,
but I think when you commentthings from different
perspectives, that what reallyI've seen animated, heard in
your voices for our listeners,but seen in our Zoom- because we
also have a Zoom conversationis just how these ideas sort of
ping off each other and scaffoldto answer interesting questions
(28:12):
.
So I want to thank you for yourwork.
I want to thank you for bringingit to Annals for publication
and especially for thegenerosity of your time to
answer these questions today,and although we sort of
brainstorm a little bitbeforehand about what we might
ask.
I'm also infamous for going offthe script, so also thank you
for rolling with the punches.
But I think it's a greatconversation and a pleasure to
(28:33):
have you on the podcast, and welook forward to what your future
research will be.
Wei Perng (28:37):
Likewise.
Thank you for your time and Iknow it's close to dinner time
for you if you're on the EastCoast.
Patrick Sullivan (28:43):
Yeah, I am on the East Coast and dinner is
looming.
So, thank you, thank you bothso much.
Thank you very much.
Thank you.
Thank you both so much.
Thank you very mu I'm your host, patrick Sullivan.
Thanks for tuning in to thisepisode and see you next time on
EpiTalk, brought to you byAnnals of Epidemiology, the
official journal of the AmericanCollege of Epidemiology.
(29:04):
For a transcript of thispodcast or to read the article
featured on this episode andmore from the journal, you can
visit us online atwwwannalsofepidemiologyorg.
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