Child Study Center Grand Rounds 01.11.2022

March 21, 2022

The Long Arm of Early Life: Comparative Evidence and Insight from Nonhuman Primates

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00:00Great, so there's still people coming in,
00:04but we might just make a start and so
00:07good afternoon everyone and welcome to
00:09grand rounds at the Child Study Center
00:12and I'd like to start by thanking
00:15Doctor Linda Mays for kicking off
00:17our 2022 lecture series last week.
00:21And you know, one of the themes that
00:22emerged from Linda's presentation
00:23was the importance of community,
00:25so it's so heartening to see you
00:27all on the call today as we continue
00:29with our grand rounds series.
00:31Now just a couple of notices,
00:33and next week we'll hear from Usha
00:35Tummala Narra and from Boston
00:37College after Russia to molinara,
00:39they'll be speaking to us about a
00:42psycho analytical perspective on
00:43the origins of xenophobia and racism
00:45and how such xenophobia and racism
00:47contributes in perpetuates suffering and
00:50trauma within racial minority immigrants.
00:52Here in the United States and now
00:54rounding off our speaker series in
00:56January will be Doctor Jonathan
00:58Omer Hearty from Kings College.
01:00London will be sharing some new data.
01:02From the developing Human Connectome project,
01:04and really emphasizing the importance
01:07of studying individual trajectories of
01:10brain development from the prenatal
01:12period across early life to better
01:14understand braydan behavior associations.
01:17Now today it's my distinct privilege
01:19and pleasure to introduce Doctor
01:22Jenny Tongue from Duke University.
01:24I'd like to especially thank
01:26Jenny for being so flexible.
01:27We really reschedule this to be a virtual
01:30format and with very short notice.
01:33So thank you,
01:34Jennifer,
01:34for being with us today and as you'll hear
01:38from Doctor Tongues presentation today,
01:40the Tongue Group seamlessly integrates
01:42functional genomics with behavioral
01:44ecology to really ask and answer
01:47questions of importance regarding
01:48how the social environment and
01:50social stress shapes individual
01:52differences in a range of phenotypes,
01:54and then how those changes in
01:56behavior can change the function
01:58and the evolution of the genome.
02:00Now,
02:01Doctor Tung's work has been
02:02the impact of doctor Tongue.
02:04Work has been recognized by a number
02:06of different funding institutions,
02:08agencies, and foundations,
02:09including the MacArthur Foundation,
02:11that named Jenny MacArthur Fellow in
02:132019 and which I think was the same
02:15year that you renamed as a fellow in
02:17the Canadian Institute for Advanced
02:19Research Child and Brain Development Program.
02:22Now it's at this stage that I really
02:23wish that I had some canned laugh or
02:25some canned applause to like welcome
02:27you to the Child Study Center.
02:28We're getting some virtual applause
02:30in on zoom,
02:32but really,
02:32it's a pleasure to have you with.
02:34Today and welcome to the CHILD Study Center.
02:40Thank you so much Karen.
02:41Thanks to all of you for for being
02:43willing to carve out time in your
02:44day to do another virtual seminar,
02:46and especially to Karen and Rosemary
02:48for being so flexible and making
02:51this thing work as we go through
02:53the sort of whiplash of wave for
02:56whatever we happen to be on.
02:59OK, can you guys see my screen?
03:01OK, does this look like
03:03it's it's supposed to look?
03:04This is great alright.
03:06As Karen mentioned,
03:07my focal system is largely non
03:10human primates.
03:11I do some work on other social
03:13mammals but by and large not
03:15humans which I suspect is the the
03:17study system of most of you here.
03:19So I'm going to just start my
03:22presentation by introducing you
03:24to a few of our study subjects.
03:27The animals in my title slide are.
03:30Two known females.
03:31This is Rwanda on the bottom
03:33right and her then adolescent
03:35daughter rodeo up on the top.
03:38I'm showing you these particular
03:39individuals because they are the benefits
03:42of substantial amounts of privilege.
03:44At least what counts is privilege
03:46in a wild baboon society,
03:48Rwanda was born to a particularly
03:50high status female and because
03:52in species like these,
03:53females inherit their social status,
03:55their position on the on the social
03:58hierarchy from their mothers, she's.
04:01Tire life.
04:03As either the top ranking female and
04:05her social group or just right below
04:08that that's had some pretty profound
04:10effects on on her life history.
04:13High ranking females in the population
04:16that we study reach maturation
04:19earlier and because of increased
04:21or better access to resources,
04:25they tend to have shorter
04:26inter birth intervals as well.
04:28So Rwanda has been remarkably
04:30successful at producing offspring.
04:32She's had eight.
04:33Live birth so far 2 miscarriages and her
04:36most recent offspring was born in 2020,
04:39so she was a pandemic baby and Rwanda
04:43is still going the the advantages
04:46that accrue to her have been passed
04:49down in an intergenerational
04:50fashion to her daughter Rodeo here,
04:53who benefits from having a large
04:55family including a large number of
04:57sisters who are likely to be her
04:59closest social partners throughout life.
05:01And in fact we know from previous
05:02work in our study.
05:03Population that females who have a
05:05lot of close social partners live
05:07on average years longer than those
05:09who do not see the top quartile
05:12versus the bottom quartile.
05:13Most socially integrated versus
05:15socially isolated baboons.
05:17So the circumstances of early life
05:20surrounding the birth of these
05:22animals shapes their phenotype
05:24in a long lasting fashion,
05:27parallel in some ways to what
05:29has been observed in humans.
05:32This type of the importance of early
05:35life effects I'm talking about here
05:37is something that's been observed
05:39repeatedly in other species,
05:40and in fact,
05:42in much more striking fashions that
05:44I'm even talking about in the baboons.
05:46So here in the top,
05:47I'm showing you spadefoot,
05:50toad tadpoles, water fleas,
05:52and tobacco horn worm larvae,
05:55which actually produced
05:57entirely different morphs,
05:59carnivore versus omnivore, or morphs.
06:02Of the tadpoles, can you see my cursor?
06:05Actually, I can't tell if you can see what.
06:07Yeah, OK. Great, so carnivore and
06:10omnivore or more fear is actually
06:12a carnivore eating an omnivore
06:14morph based purely on what early
06:16life diet looks like in these.
06:17In these in these toads,
06:20this elaborated helmet or long sword
06:24depending on whether eggs of Daphnia
06:27are exposed to predator cues or a
06:29completely different color morph,
06:31just depending on the temperature.
06:33In early development these
06:35are pretty far afield from us,
06:37but there are examples of fairly striking.
06:40Early life effects in other mammals as well.
06:43We know from experimental evidence
06:45that wild red squirrels who are exposed
06:48to cues of high density actually
06:50accelerate the their offspring growth.
06:52We know that voles who are born
06:54in the cold season versus a wet
06:56season develop a thicker codes and
06:58from work in the population that
07:00I'll be telling you about today.
07:02These baboons we know that diet in
07:04the first year of life postnatally
07:07has effects on the overall lifetime
07:09reproductive success of these.
07:10Animals, even years or decades later.
07:14And of course,
07:15in our own species there's been
07:17abundant work linking childhood
07:18adversity in advantage,
07:20including in the adverse childhood
07:22experiences framework to later
07:24life health and mortality rates.
07:27So we know that these things exist.
07:31We know they're common across species,
07:32but there are a number of
07:34lingering questions about why,
07:36how and when these types
07:38of relationships arise,
07:40including whether childhood adversity or
07:42early life adversity leads to differences.
07:45In natural lifespan,
07:46in completely natural primate populations
07:49in the way that has been observed
07:52in humans to get at these questions,
07:54I've been lucky enough to Co direct
07:56the Amboseli Baboon Research Project,
07:59which is a launch toodle field study
08:01of wild primates in southern Kenya.
08:03That's now been running continuously
08:04for over 50 years,
08:06so this is actually the first talk
08:07where I get to say over 50 years
08:09and what we mean by that is that
08:11individually recognized animals
08:12in this population so recognized
08:13on site by trained observers.
08:15Have been watched on a near
08:17daily basis for those 50 years.
08:19Of course,
08:20that that constitutes multiple
08:21generations of baboons.
08:22We collect data on their social
08:25interactions on their reproductive history.
08:28On life span and we also complement
08:30those data with information on
08:32their endocrine profiles on their
08:35genetic relatedness to one another
08:37on their microbiome and on their
08:40gene regulation more recently.
08:42Like I said,
08:42this has been a 50 year plus project,
08:45so I've had the the ability to work
08:48on this really singular resource
08:51through the foresight of Jean Altman,
08:53who founded the project in 1971
08:55with her husband, Stuart Altman.
08:57Susan Alberts,
08:58who's also at Duke and Beth Archie
09:00at the University of Notre Dame.
09:02And together we Co. Direct this project.
09:05A large number of our employees
09:07on the project our Kenyan and are
09:09based in Kenya at the field site
09:12or in Nairobi and so all of the
09:14data that I'll be talking to
09:17you about today were collected.
09:19In partnership with them and they are
09:22a really extraordinary professional
09:24and talented group of people.
09:26So I want to acknowledge them and here too.
09:29OK, so I told you we've been
09:31watching these animals for 50
09:33some years in the background.
09:34Here is the pedigree for those animals.
09:37Both maternal lines and yellow
09:38and paternal lines in blue.
09:40We're now up to just over 2100
09:43known individuals in the population,
09:46and the ones who we followed the
09:48longest are from families that we
09:50have up to 9 generations of data for.
09:52So using this information which
09:54goes across the full life course
09:56and intergenerationally.
09:57We are interested in understanding
09:59the consequences of early life
10:01experience and early life adversity
10:03for natural mortality in this
10:05sort of prospectively intensively
10:07monitored setting that is free
10:09from the types of potentially
10:11confounding or potentially mediating.
10:13Depending on your question,
10:15factors that influence early
10:17life effects in humans.
10:18We're interested, of course,
10:20as as as scientists trained from an
10:23evolutionary biology, tradition,
10:24and understanding why these
10:26effects exist in the first place.
10:29Is there a reason for animals to
10:31adjust their phenotypes in a way that,
10:33for example,
10:34predicts how they'll deal with later life,
10:37environmental adversity,
10:38and as many of you may be?
10:42We are interested in how these types
10:44of early life effects may arise.
10:46What links and experience that may
10:49occur decades prior to the phenotypes
10:52that we observe with the internal
10:55physiological states that those organisms?
10:58So there is quite a bit of
11:00literature in our population as
11:02well as in nonhuman primates.
11:04Generally, including from your colleague,
11:06Amanda Detmer,
11:07who I think I saw here.
11:09Hi Amanda,
11:09on different sources of early life
11:12experience and downstream effects
11:13in the juvenile or adult period,
11:16for example, in Amboseli alone,
11:18we know that early life social status
11:20has long term predictive relationships
11:22with the timing of maturation with
11:25glucocorticoid Physiology and
11:26with the ability of animals too.
11:28Resist drought later in life.
11:30We know that mothers are exceptionally
11:32important for baboons because like humans,
11:35baboon babies experience long
11:37periods of nutritional and social
11:40dependency and and and individuals
11:42who lose their mothers early in
11:44life are very unlikely to survive
11:47themselves to adulthood.
11:48Similarly,
11:48animals who have relatively socially
11:51isolated mothers are less likely to
11:54make it to their own reproductive maturation.
11:57Resource competition influences
11:58many of these outcomes as well,
12:00including maturation timing and
12:02certain patterns of gene regulation
12:04and early life drought.
12:05This is a highly variable environment,
12:07has strong effects on female fertility
12:10and later life resilience to drought.
12:13So all of these papers pursued
12:15individual sources of early life
12:18experience and in connection
12:20with individual outcome variables
12:23we became very inspired.
12:24Actually by work done in humans in the
12:27Asus framework to ask what happens
12:29if you look at them in conjunction.
12:32In fact,
12:32if you do something as simple as counting
12:35up the number of sources of advantage
12:38or adversity that baboon baboons
12:40can experience early in life,
12:42so we considered. Six of them,
12:44in a baboon parallel of an ACE score,
12:47early life social status.
12:49So the the dominance rank the
12:51position on a linear social hierarchy
12:53of the mother of a baby baboon.
12:56Whether or not that baby reached
13:00reproductive maturation.
13:00So men are key for females.
13:02Testicular enlargement for
13:04males without losing its mother.
13:08How isolated or integrated that
13:10mother was based on the results I
13:13showed you earlier that that type of
13:15pattern predicts juvenile survival,
13:18whether maternal resources were
13:19diverted by a competing younger sibling.
13:22So inter birth intervals in
13:25our population get very short,
13:26the lowest quartile is about a year
13:28and a half in her birth interval.
13:30So we asked whether individuals were
13:32faced with a little brother or sister
13:35within that very short period of time.
13:38We asked about resource competition.
13:41This experience density so
13:42the size of social groups.
13:44Who of animals?
13:45Who are a given focal animals
13:47immediate competitor?
13:48And we asked about exposure to environmental
13:51adversity in the form of drought.
13:53This is a very dry environment as
13:54I'll show you a little bit later,
13:56but some years are much wetter than others,
14:01so our interest here was not
14:03what happened immediately.
14:04It's perhaps unsurprising if an
14:06animal loses its mother when it's
14:08so nutritionally dependent that
14:10it doesn't do very well,
14:12but rather in what happens
14:13over a longer stretch of time,
14:15separated from early life.
14:16So here we're specifically asking me about.
14:19Events that happen early in life
14:21exposures that occur early in
14:23life and their predictive value
14:25for survival in adulthood.
14:27So starting around age 4 for these animals.
14:31Unlike what is typical in aces and humans,
14:35these six sources of adversity
14:37are actually not very closely
14:39correlated with each other.
14:40In other words,
14:41it's not the case that if an animal
14:43is born to a low status mother,
14:45she is more likely to be born
14:47to a socially socially isolated
14:49mother or experience higher degrees
14:51of resource competition.
14:53So we're able to parse those different
14:55types of experiences separately from another.
14:57A little bit more cleanly than is
14:59typical in human studies, and.
15:01In the same vein,
15:02early life environment is not very
15:05correlated with environment that
15:07experience that animals experience
15:09in adulthood.
15:10So here's the breakdown about 1/5
15:12to 1/4 of this is actually females
15:14in this case of females in our
15:17study population are what we think
15:19of as our silver spoon babies who
15:22experience no particular sources
15:24of major adversity early in life.
15:26Another third of them experienced
15:28one of these six,
15:29and then the more unfortunate ones are.
15:31Faced with two or even three or more
15:34sources of major early adversity.
15:37So I'll cut right to the chase again here.
15:39The ages on the X axis represent
15:42adulthood in baboons,
15:43and here I'm showing you survival
15:45curves stratified by that baboon.
15:47Aces score from zero to three or more.
15:51This is the kind of result where we
15:54actually did not expect something so clean,
15:57and when I show it to you,
15:58it's you know you almost don't
16:00need statistics to see it,
16:01but I'll tell you that what we're showing
16:04you is a difference in median survival.
16:07Highly significant difference in
16:09median survival depending on the
16:11number of adverse experiences,
16:13a baby baboon faced that leads to
16:16a difference in lifespan between
16:17about 18 or 19 years.
16:19Assuming that an animal gets to
16:22reproductive maturation to about 9
16:24years for those animals who experience
16:26three or more sources of adversity,
16:28it's sometimes useful to put these in,
16:30you know, coarsely translated terms,
16:33so this is a decade in real time.
16:36The lifespan.
16:37And the sort of life history of pace
16:40of life of baboons is about 2 1/2
16:43to three times faster than humans.
16:46So what I'm showing you here is a decade.
16:48If we put that in human terms,
16:49we're talking about differences of
16:5120 to 30 years in a population where
16:54everyone has equivalent access to healthcare.
16:57Because there is no health care.
16:59There is no smoking.
17:01There is no alcoholism.
17:03There are no illicit drugs.
17:04There are no motorcycles, etc etc.
17:07And yet there's this very pronounced.
17:09Long lasting effect on adult mortality rates.
17:13OK, perhaps interestingly,
17:14for any of you who use the Asus framework,
17:19which is proposed in some cases to move
17:22through an intermediary of effects on social,
17:25emotional and cognitive development,
17:26what we find is that individuals
17:28are silver spoon.
17:29Babies end up growing up to be socially
17:31more integrated and socially better
17:33connected than are individuals who
17:35experienced a lot of early life adversity,
17:38which is perhaps one of the mediating
17:40factors that may explain this relationship.
17:43Although separate analysis suggest
17:45it certainly can't explain at all.
17:48And for any of you who may be
17:50interested in the evolutionary
17:51ramifications of this result,
17:53what we find is that this shortened
17:56lifespan not only influences a
17:59female's own time on time on earth,
18:02but also the likelihood that
18:04she'll leave many copies of her
18:06own genome in future generations,
18:08and Amboseli females produce another
18:11surviving offspring you know,
18:13not quite like clockwork,
18:14but pretty close to it about every 2.1 years.
18:17So a difference in lifespan of 10 years
18:21is a dramatic difference in terms of an
18:25individual's lifetime reproductive success.
18:28So a former graduate student working
18:31with the project specifically,
18:33and Susan Alberts lab,
18:34was interested in whether this
18:36also had knock on effects.
18:38Intergenerationally given the importance
18:40of moms to their offspring in particular.
18:44So what I've been showing you so far is early
18:46adversity accruing to a particular female,
18:49and the consequences for her own life.
18:51What he wanted to know is whether.
18:54Early adversity experienced by the mother
18:57had cascading effects on her kids survival,
19:00even controlling for that kids own
19:02exposure to the same sources of adversity.
19:05Remarkably remarkably,
19:06we see that it does so here again,
19:09our survival curves, in this case,
19:11survival to reproductive maturation
19:13for the offspring of mothers
19:15who experienced maternal loss.
19:17You know what could have been
19:19decades earlier in life,
19:20or mothers who experienced that competing
19:22younger sibling again in what could
19:25have been decades earlier in life?
19:27So in both cases kids of moms who
19:31experienced early adversity were
19:33more likely to to die before they
19:36hit their own period of independence.
19:38We think we know what's mediating this,
19:41at least at a gross level and
19:44and that is likely an effect on
19:47maternal health or viability.
19:48That is, the moms of those.
19:50Those second generation
19:52offspring to ask this question.
19:54Matthew divided up those
19:56first four years of life.
19:58From birth to earliest maturation,
20:00he asked what the survival probability
20:04was of offspring in the in the
20:07period from age 0 to age 2 as a
20:11function of whether mothers were.
20:14Able to survive or not during the
20:16period in which that offspring would
20:17have been age 2 to 4 sodas later,
20:21maternal mortality predict something
20:24about the survival for offspring
20:26earlier in life and for females
20:28who either experience maternal loss
20:30themselves or competing younger sibling.
20:32That's the case.
20:33So in other words, if you are a baboon,
20:37is the offspring of an individual who
20:39experienced early adversity in its own life,
20:42that individual is likely to
20:43be in poor somatic.
20:44Quality in a way that influences
20:46whether or not that kid is able to
20:49make it to age 2 even if its mother
20:51is there the whole time and I'll just
20:53tell you that this relationship.
20:55This difference between offspring
20:56survival as a function of later
20:59maternal death does not exist for
21:01the offspring of mothers who did not
21:04themselves experience early mortality.
21:06So we think that this is explained
21:09by what's going on with the mother's
21:11condition and doesn't necessarily
21:13require any sort of complex.
21:15For example,
21:16epigenetic explanations that that go
21:18into sort of transgenerational effects.
21:21So in this population we find
21:24that as in humans,
21:26early life is a critical period for
21:28development that affects lifelong survival.
21:30Even in a time period that's quite
21:32separated from the early life exposures.
21:34It appears to be profoundly
21:35affected by social resources.
21:36In particular,
21:37many of the things that pop out to
21:40us as individually predictive sources
21:42of variance have to do with moms,
21:45in particular maternal presence
21:47and maternal attention or maternal
21:50resources spent.
21:51With that particular offspring.
21:53Our data suggests that multiple
21:55hits compound to influence risk,
21:57so the the risk of or of earlier
22:01death with higher aces exceeds the
22:04explanatory power of looking at each
22:06of those individual effects alone,
22:08and this has intergenerational consequences,
22:11meaning that the viability of an
22:14animal that we happen to watch at a
22:16given point in time is affected not
22:18only by its own experience but by
22:20the experiences in previous generations.
22:22So I already told you that.
22:25But this has major consequences
22:27for the the currency of
22:29Darwinian fitness, right lifetime,
22:31reproductive success,
22:32how many offspring females leave behind.
22:35So this raises a natural question
22:37about why these early life effects
22:38have evolved in the 1st place.
22:40If this has such costly
22:43consequences for fitness,
22:44then shouldn't over the course of
22:48evolutionary history we and other
22:50longer lived primates you know,
22:52quit paying attention to
22:54those early life experiences.
22:56This was a question that a
22:57former PhD student of mine,
22:58Amanda Lea,
22:59is now faculty at Vanderbilt
23:01was very interested in,
23:03and she attempted to disentangle 2
23:05of the predominant hypothesis for
23:08why early life effects evolved.
23:10These are often used to explain
23:12early life effects in humans too,
23:14so I think that there is some
23:17some generalizability here.
23:20The 1st is a class of of explanations
23:22I'll refer to as early life programming,
23:25adaptive programming,
23:26or sometimes you'll see.
23:27Adaptive responses which posits
23:29that what's going on is that young
23:34animals are taking cues from their
23:36environment to adjust their phenotype
23:38in a way that better prepares
23:40them for a similar environmental
23:43exposure later in Life OK,
23:45and so if you use these kind of fitness
23:47nor sorry reaction norm representations,
23:50what that means is that individuals
23:52who are born in a poor early
23:54environment actually do better.
23:56If the quality of the environment.
23:57Is also poor in adulthood and vice versa.
24:00Individuals who are born in a
24:03benign environment do better
24:04in an environment that are high
24:07quality in adulthood relative to
24:09that other class of individuals.
24:11A major alternative class of hypothesis
24:13is what is often termed developmental
24:15constraints or a silver spoon effect,
24:18which basically posits that good
24:21benign early environments are
24:23good for you no matter what your
24:26adult environment looks like,
24:27and so the consequences of early
24:30life adversity are because.
24:32Individuals have to physiologically
24:34adapt to their environment,
24:35and they're basically making
24:36the best of a bad job.
24:39A real challenge with distinguishing these
24:41between these two hypothesis is that often,
24:44particularly in human natural experiments,
24:46what we what we have our data from.
24:48Individuals born in poor versus
24:50high quality early environments.
24:52You can think about classical
24:53studies like the Dutch hunger,
24:54winter or the Great Leap
24:57Forward studies in China,
24:58but they're measured in adulthood
25:00in relatively benign environments.
25:02In other words,
25:02we're seeing two of these points,
25:04not four of these points,
25:05and if you only see two of these
25:06points on the right hand side,
25:07you can't actually distinguish.
25:09Between that crossing pattern,
25:11that interaction pattern or a pattern
25:13that would be much more consistent
25:15with developmental constraints.
25:17So we think we can do this in
25:20Amboseli because there is a major
25:22source of environmental variation
25:23that can cause hardship or relative
25:26advantage that is completely
25:28exogenous to the fabulous themselves,
25:30and that's simply defined by
25:31patterns of rainfall in Amboseli,
25:33which can be quite dry in some years less
25:35than rainfall in Phoenix for comparison.
25:38So desert like these are
25:40hydrological years going back into
25:41the 70s, or they can be relatively high,
25:45not as high as New Haven.
25:46In case you're interested
25:47in putting this in context,
25:48New Haven get spelled.
25:491200 millimeters of precipitation a year,
25:52but high enough that we aren't talking
25:54about desert like conditions anymore.
25:56OK, and of course this variation again is
25:59something that the baboon like baboons,
26:01nor we have any kind of control over.
26:04Now in 2009 we had the equivalent
26:06of a weight of a natural experiment
26:08in our own natural population,
26:10which was the worst drought ever recorded
26:12in the history of this ecosystem,
26:14and it was compounded by the fact
26:16that the year before 2008 was
26:18actually also a low rainfall year,
26:19so animals were really suffering
26:21in the basin.
26:22There was large scale die
26:24off of large animals.
26:25We did not see a lot of mortality
26:28consequences in the baboons,
26:30but we did see a huge drop in fertility.
26:32So here on the Y axis.
26:34I'm showing you rates of conception per
26:37adult female by hydrological year and this
26:40is 2009 where it dropped by about 25%.
26:43So the animals are very much
26:45feeling these kinds of effects,
26:47so this gave us the ability to ask in
26:50a poor quality adult environment 2009
26:53versus good quality adult environments.
26:56So the middle 50% of rainfall years
26:59were treating in that sort of way.
27:01In this analysis,
27:02how did individuals who were born in poor?
27:04Early environments during early life
27:07droughts do compared to individuals born
27:09in modern high quality early environments.
27:12In terms of their ability to conceive
27:15offspring and also to resume reproductive.
27:20Cycling after a period of postpartum minaria.
27:24OK,
27:25so that's what we'll focus on.
27:28These fertility related outcomes.
27:29And here's what we get as a result.
27:32What we find is that for females who are
27:34born in relatively benign environments,
27:37there's actually very little
27:39difference in their probability of
27:42conceiving or resuming cycling.
27:44This is conception data.
27:45Here in moderate years versus in the drought.
27:49They're relatively buffered,
27:50although you see a little bit of a decrement.
27:53This is actually a comparison within
27:55individuals for for females who conceived
27:58in both of those types of environments,
28:00so these comparisons are going
28:02to be centered around 0,
28:04whereas for females who were
28:05born during droughts,
28:06they took a much larger hit in
28:09comparison to their own reproductive
28:10performance and mop in moderate years.
28:13In other words,
28:14there is a difference between how well
28:16females who were born and droughts and
28:18females who were born in good years did,
28:20but is in the opposite direction
28:22as predicted by the predictive
28:24adaptive response model.
28:26We actually also see some,
28:27some some preliminary evidence for
28:29social buffering in this situation
28:31for females who were both born in a
28:33drought and lived as reproductive adults
28:35through that very severe 2009 drought,
28:38we find that females were able to maintain
28:42their ability to conceive if they were
28:45born to high status mothers versus
28:47females who were born to low status.
28:49Mothers were less able to buffer
28:52her against these multiple hits.
28:54And so you know, Amanda came to me.
28:56And she found this result.
28:57She said, well, I think all we're
28:59saying is that if you were born in
29:01a terrible year and then you had
29:02the bad luck of living through,
29:04you know one of the worst years on record.
29:05And you know you are.
29:09Experiencing social disadvantage
29:10is the result of being low on a
29:13social hierarchy than that is bad.
29:14And that's true.
29:15I mean, maybe that's not very surprising,
29:17but the fact is it is counter to one
29:20of the dominant predictions in the
29:23literature about why these things happen.
29:26So
29:27you're going on to that.
29:28There's just a little bit of *********
29:29that we're hearing from the audio.
29:30I'm wondering if there's anything with
29:32your microphone or something on your
29:34microphone that we could try moving,
29:36and it's not. It's not too too bad,
29:38it's just a little bit of *********.
29:40OK, I can probably switch my
29:42microphone. This may switch.
29:46This may switch the image
29:47for a SEK, so bear with me.
29:50Sorry to interrupt you. I just
29:51Oh no, no problem. It's better
29:54to to actually be able to hear
29:56we can. We can hear you fine. It's just
29:58a little bit of of of of *********.
30:01OK yeah I'm going to switch
30:02mikes in just a second once.
30:06Just as you did your shadow to Amanda,
30:07I thought that was a knife, nice.
30:10Correct, OK? Are you seeing a
30:12presenter view now or are you seeing
30:16no? We're seeing a blank screen?
30:18Well, just seeing a square of white
30:21square of white, that's not
30:22what I want to show you, OK?
30:26Yeah, the baboon pictures
30:27are far more preferable.
30:30Let me let me try and work on that.
30:32I can probably go. We've got him.
30:33Now we can see your slides, but just OK.
30:38And then let me go back to zoom.
30:41I'm gonna stop share for just a second.
30:43I just fix this problem.
30:45Sorry about that Dani.
30:46No no, no that's OK.
30:47Thank you for telling me.
30:51OK.
30:55OK, I've just switched.
30:57Microphones is that better?
30:59We don't hear any *********
31:00at the moment then.
31:01OK, great and then.
31:06Go back to the screen share, oops.
31:18OK, are you seeing my slides?
31:20We can see your Internet actually.
31:23Yeah now we can see your slides
31:26and it looks like the way it's
31:27supposed to and not not presented.
31:29It looks great.
31:30OK perfect, thanks so much no problem.
31:33So I think the evidence that we have is
31:36against the idea of adaptive programming,
31:38but much more easily explained
31:42by contingently experience,
31:43developmental constraints in other words.
31:45Females who are born in a
31:47disadvantageous environment do
31:48worse even in that same type of dis,
31:50and fit advantageous environment
31:52when they grow up.
31:54We actually don't see those effects
31:56in moderate years and for females
31:59who were born in moderate years.
32:01The effect is is much attenuated relative
32:04to females who were born in in dry years.
32:09Additionally,
32:09there are other sources of relative
32:11advantage in diversity that can
32:12have the same kind of effect,
32:14including being born to a relatively
32:17socially privileged family.
32:20OK, and I'll just note that this is
32:22fairly consistent with the pattern that I
32:24think is emerging from long lived species,
32:27including humans that because
32:29of our very long lives,
32:32setting a strong, making a strong bet,
32:34making a strong prediction from
32:36an experience in in utero,
32:38or in the first years of life,
32:41is probably not wise for animals that live,
32:45you know, decades,
32:46whereas it may be very wise
32:48for a water free or.
32:50Or for a tobacco hornworms?
32:52OK.
32:52So finally I think one of the biggest
32:57puzzles that is of shared interest
32:59to people interested in early life
33:01effects is of course this very
33:02general question of how where we can
33:04be talking about multiple types of
33:06different types of mechanisms from
33:08social and behavioral mechanisms
33:10to biological mechanisms that are
33:12adjusted based on the early life
33:14environment and one of the puzzling
33:15things about relating early life
33:18adversity to phenotypic outcomes
33:19later in life is that they don't
33:22affect you know single types of
33:24outcomes with very clear ideology.
33:26But rather tend to have very general
33:29effects on a lot of different
33:31outcomes that have lots of different
33:34underlying mechanisms.
33:35So I think a common and influential
33:38idea about how this works is through a
33:42general process of biological embedding.
33:44And here I'm using the criteria
33:46defined by herzman,
33:48where the environment somehow you know,
33:51influences what's going on under
33:53the skin is at the physiological
33:55and molecular level to influence
33:58biological and developmental processes,
34:00meaning that systematic differences
34:03in experience like being born.
34:05Two in a low resource environment
34:08and an environment that produces
34:10material deprivation or social
34:11deprivation can lead to systematically
34:14different types of biological
34:16states that remain stable overtime.
34:19And crucially, to actually mediate,
34:22you know this sort of bubble on the left.
34:25At the relationship with bubble on
34:27the left and the bubble on the right,
34:29these differences,
34:30whatever changes at that molecular
34:32and physiological level,
34:33must have the capacity to influence
34:36trait variation over the life course.
34:38For those interested in social epigenetics,
34:43much of this much of the attention to
34:46a potential mechanism has therefore
34:48focused on the epigenome, and for both,
34:50I think reasons of measurement,
34:51and because DNA methylation is a relatively
34:55stable epigenetic mark to the epigenetic
34:59marker of DNA methylation, in particular,
35:01that is the addition or removal of a methyl
35:05group to invertebrates, typically cytisine.
35:08Nucleotides where they're followed
35:09by Queens in the genome.
35:11So there are potentially about 20 million or
35:14so of these CPG sites in in a human genome.
35:18So this is thought to be a plausible
35:20mechanism in part because DNA methylation
35:22is known to be environmentally responsive.
35:25It's part of the gene regulatory machinery,
35:27and our genome must be able to
35:29flexibly respond to its immediate
35:31environment throughout life.
35:33In fact, this is happening even as we speak
35:35as a consequence of what we might have
35:38eaten before circadian rhythms and so on.
35:40Depending on where in the
35:42genome you're talking about.
35:43Again, DNA methylation has relatively
35:46remarkable fidelity across cell division,
35:49and so has the potential to
35:52remain stable overtime even from
35:54early life into into later years.
35:57Evidence that this may in fact be
35:59a plausible pathway comes from
36:01correlative studies that link
36:03early life environmental exposures
36:05with epigenetic change in humans.
36:07But of course,
36:08suffer from the potential confounding
36:10of early environments that affect
36:12adult environments that are actually
36:14immediately responsible for the types
36:16of epigenetic patterns that have been
36:18documented in many population studies so far.
36:22However,
36:22I think of a potentially bigger
36:24problem is that although we know
36:26that DNA methylation can influence
36:28gene regulation and therefore change
36:30the Nixon expression in a way that
36:32it could be phenotypically relevant,
36:35it doesn't always do so.
36:37And we know this from experimental studies,
36:39for example that if used epigenomic
36:42editing technologies to specifically
36:44change DNA methylation at individual sites,
36:47so these are four data from another lab
36:50that focused on changing DNA methylation,
36:53and a very specific manner.
36:55By 4 CPG sites at 1 gene in
36:58the genome and looked at it.
37:00Effects on expression and only
37:02one of these sites is sensitive
37:04to DNA methylation lawyers.
37:05The other changes are effectively silent.
37:08We don't know whether the the cases
37:11where early environment has even been
37:13correlated with DNA methylation later
37:15in life are in that class of silent
37:17changes or in the class of things that
37:20might have physiological consequences,
37:22which are the things that we
37:23have to care about.
37:24If we believe this is mediating.
37:25Early life effects on health and mortality.
37:29So we have the opportunity to
37:30study this in Amboseli as well,
37:32where we can again divorce some of
37:34these early and adult environmental
37:36processes and separate out different
37:38types of early life effects.
37:39We can do this because,
37:41although most of the research we
37:42do on the baboons is non invasive,
37:45occasionally we have reason to
37:47want to take biological samples,
37:48collect morphometric data and so on,
37:50and so we periodically engage in in
37:54brief and estimations darting in order
37:57to collect those sorts of samples.
37:59So this is our very talented field
38:01assistant Kenya Larry Terry here.
38:03You probably can barely see it,
38:04but he's holding about a metre
38:06long metal tube in his right arm
38:08and trying to look as innocuous
38:10as possible around these baboons.
38:12We wait for a period in which nobody
38:14is looking and then very rapidly
38:16deliver an anesthetic containing
38:17dart at our animals in order to
38:19collect these types of samples.
38:21And over time we've been able to
38:22collect hundreds of these samples,
38:24including from individuals where we know
38:26a lot about both their early life and
38:29what's going on with them in adulthood.
38:31We've used a sequencing based method to
38:34generate genome scale DNA methylation
38:37data for several 100 individuals,
38:39including a number of of whom we've
38:41actually had repeated sampling,
38:43overtime and post quality filtering are
38:45able to assess DNA methylation in adulthood.
38:49In this period,
38:51in blue for these baboons,
38:52this is years of life for about
38:55half a million sites in the genome.
38:58We asked how individual sources
39:00of early adversity as well as
39:02cumulative early adversity,
39:03that sort of Aces score.
39:05I talked to you about earlier adding
39:07up these individual exposures in
39:09the first few years of life or at
39:12birth influenced DNA methylation
39:14collected in this blue period.
39:16We also paid attention to whether
39:18animals were born in a relatively high
39:21habitat quality environment versus a
39:23relatively low habitat quality environment.
39:25We had again a sort of natural
39:27experiment in our population.
39:28Where our animals made a fairly
39:30dramatic shift as the quality of
39:32their initial habitat declined to
39:34a much higher quality environment
39:36outside the original area of study.
39:40Finally,
39:40we included a measure of their
39:43adult social circumstance based
39:45on dominance rank or the position
39:47in the hierarchy for both females
39:49and males based on prior evidence
39:51from my student Jordan's work that.
39:56That dominance rank is a major
39:58predictor of differences in gene
40:00expression in our population.
40:01So all of this work was really
40:03led by by Jordan and we're in the
40:05process of putting it together now
40:07again to just skip to the results.
40:09What we find is that early
40:11life effects do persist.
40:13Do leave a signature in
40:15DNA methylation profiles,
40:17but that this is really most
40:19apparent for those individuals
40:20born in that low quality habitat
40:22and not the high quality habitat.
40:25So what I'm showing you here.
40:26On the X axis are the effect sizes
40:30of cumulative early adversity on DNA
40:33methylation levels multi measured
40:35in adulthood for about 470,000.
40:37Sites in the genome.
40:39They're quite close to 0 for animals
40:41born in a resource rich environment,
40:43but they move quite further
40:45away from zero on average.
40:47For those born in low quality
40:49habitats and we can see a
40:52very similar type of quality.
40:54For each of the individual
40:56sources of building per city.
40:59Investigated separately.
41:02So this is what it looks like genome wide.
41:05These are the effect sizes in
41:07the high quality environment.
41:08Individuals born in high quality environment.
41:10These are effect sizes for
41:12for individuals born in low
41:13quality environment for exactly
41:15the same sites in the genome.
41:17And again, you can see that replicated
41:20in individual at individual
41:22sites for individual exposures.
41:23Basically, individuals who
41:25are born during a drought.
41:27You can see a market effect of drought
41:29if they were born in that low quality
41:31habitat that's in that sort of pinkish color.
41:33But a much more attenuated effect for
41:35those born in high quality habitats.
41:37So it looks like we're looking at
41:40compounding effects of resource limitation
41:42that the whole population is exposed
41:45to and individual level exposure to.
41:48Early life adversity.
41:50So to give you a sense of the
41:51relative magnitude of these effects,
41:52these are significantly associated
41:54CP G sites in the genome.
41:56Simply, the number of them of those
41:59that we tested based on each of these
42:01predictor variables and the major effects
42:03other than large scale effects of age,
42:05which are expected based on our
42:07and other people's previous work,
42:09are those habitat quality effects.
42:11The difference between being born
42:13in an environment looks like this,
42:15or exactly the same place in the
42:17ecosystem that's been denuded of the major.
42:20Dietary resources for baboons.
42:22The individual sources of early
42:24adversity that matter are are,
42:26particularly those also associated
42:28with resource deprivation.
42:30Drought,
42:30loss of a mother early in life,
42:32and high levels of resource competition.
42:36If the group is is, is dense.
42:39This by itself doesn't answer the question,
42:41though about whether those types of
42:43epigenetic changes are effectively silenced.
42:45Maybe they're simply passive
42:46biomarkers or early life exposure,
42:48or whether they have any potential to mediate
42:51downstream effects on health and survival.
42:54Part of that question can be
42:56answered at least circumstantially,
42:57by asking where in the genome,
42:59differentially expressed early
43:01adversity associated differentially
43:02methylated sorry sites fall.
43:05The genome is a diverse place in
43:07different parts of your DNA sequence
43:10have different roles in gene regulation,
43:12and so a simple question to ask is whether
43:15those differentially methylated sites
43:16tend to fall in regulatory elements
43:19like gene promoters or enhancers.
43:21These elements that tend to loop around
43:23physically interact with the promoters
43:25of genes to modulate gene expression.
43:27Or whether they fall in kind of deserts
43:30of genes or regulatory elements
43:32unannotated regions of the genome and
43:35what we've revealed what we found we think,
43:38is a fairly bimodal pattern,
43:41where if you look at age
43:43differentially expressed sorry,
43:45differentially methylated sites.
43:46For example,
43:47we find that they are enriched in
43:49this pinkish color in Unannotated
43:50region of the unit.
43:51We find a lot of them,
43:52but they don't tend to fall in
43:54places where we believe they're
43:55likely to influence gene regulation.
43:58Habitat quality is fairly neutrally
44:00spread across the genome,
44:01with a little bit of tendency towards
44:03more enrichment in these sort of
44:05functionally important regions of
44:06the genome versus the unannotated,
44:08but it's not very striking,
44:09whereas we if we look at drought
44:12effects or the effects of a social
44:13environment at the time of sampling,
44:15like male rank, we see a pattern
44:17that is opposite to that of age where
44:20those differentially methylated
44:22sites tend to fall non randomly.
44:24In enhancers and gene bodies,
44:26that is, regions of the genome.
44:28That we believe may be important
44:29to the Physiology of the Organism,
44:31and then they tend to be depleted
44:34in those unannotated regions.
44:36Another way to look at this is to use
44:38the chromatin states annotated by the
44:40road map of the Genomics Consortium.
44:43This was done for humans that we can
44:45pull over these annotation to baboons.
44:47They recognize a number of different sites.
44:49You can just think about painting
44:51the genome different colors depending
44:52on what part of that genome,
44:54what that part of the genome
44:55is likely to be doing,
44:56which is defined in turn by
44:58different types of histone marks.
44:59As well as the DNA configuration
45:02DNA methylation.
45:04Where the ones on the top of this
45:06list tend to be linked with active
45:08regulation and the ones on the bottom
45:10of the list tend to be associated
45:13with repression or silencing.
45:15If we look at age,
45:16associated State state sites again,
45:18we see under enrichment or depletion
45:21in those actively regulated regions
45:23of the genome and enrichment in in
45:26repressed or quiescent parts of the genome.
45:29If we look at socio ecologically
45:32associated sites, on the other hand,
45:34here are things like habitat quality,
45:36drought, or male social status.
45:38We see the opposite effect on
45:40this left hand side.
45:41There's enrichment in regions of the
45:43genome that are associated with active
45:45regulation in blood cells as opposed
45:47to depletion in those age associated sites.
45:49We see the same kind of pattern as
45:52age or even more neutral pattern
45:55for just technical batch effects.
45:58Now finally I want to say that.
46:00This is. Still circumstantial.
46:02What we're saying is that there's
46:04an association between a which
46:06is early life exposure and B,
46:08which is DNA methylation and adulthood,
46:10and those associations tend to
46:12fall in particular regions of
46:14the genome that are probably more
46:16interesting than just the background.
46:18They don't provide any direct
46:19causal evidence is which,
46:21which is what you really want to have
46:22if you want to argue for epigenetic
46:25mediation that an epigenetic change
46:26directly influences the phenotype,
46:28or at least gene expression as
46:31approximate molecular phenotype.
46:33So we ended up going after this too.
46:36Inspired by some work done by Alexander
46:38Stark Lab in Vienna on using massively
46:41parallel reporter assays to look at
46:44causal effects of DNA sequence on
46:46the capacity for regulatory activity.
46:49There assay is called star seep
46:51and it basically works by randomly
46:54shearing or amplifying lots and lots
46:56of fragments of the genome and cloning
47:00them into little episomal plasmids like.
47:02This in a structure so that if the
47:05piece you cloned in this little olive
47:07piece actually has the potential to
47:10drive differential gene regulation
47:12when you transfect this little circle
47:14DNA into your cell type of interest,
47:16then it will cause its own its
47:19own sequence to
47:20be transcribed. Basically,
47:22this green sequence loops around,
47:24interacts with the promoter,
47:25and drives its own expression in a
47:28way that we can track using high
47:30throughput sequencing technology.
47:31So regions where you end up with a lot of.
47:33Seeds when you sequence libraries
47:35from this type of assay point
47:38to regions of the genome that
47:40have active regulatory capacity.
47:42So we thought, well, this is really cool.
47:45Can we modify this to look at
47:47changes in DNA methylation and
47:48how those changes in isolation?
47:50Just changing DNA methylation influences
47:53or fails to influence gene expression.
47:56So we ended up tweaking the assay
47:59and and producing a separate plasmid
48:02PM star seek one which you can
48:05actually order yourself from addgene
48:08if you're interested and producing
48:10the same kind of assay idea, but.
48:12But leaving sites targets of DNA
48:15methylation vertebrates only in those
48:17regions that we clone in in olive and
48:19either experimentally methylating them
48:21or leaving them experimentally methylated.
48:24That means we can compare the regulatory
48:26activity of the exact same sequence,
48:28and we can do this for hundreds of thousands
48:29of fragments in the genome at once,
48:31where the only difference between two
48:33fragments of the same location is whether
48:35those sites are methylated or not,
48:37and the results of that assay
48:39for like 1 region of the genome
48:41looks something like this.
48:43This happens to be data from the human
48:46genome in and around the gene NF Kappa BIA,
48:49where if you see higher levels
48:51of RNA produced at that region,
48:54higher levels of expression
48:56relative to the input DNA.
48:58Then that points to regulatory activity,
49:01and in this case that happens
49:03in the methylated condition.
49:04This is an active enhancer,
49:06but not when the exact same
49:07sequence is methylated,
49:08so this was work that was pioneered.
49:10This protocol was led by Amanda Lea,
49:13the same person who took,
49:14but I'm predictive adaptive response stuff,
49:16and we generated data for
49:19bedroom specifically in work led
49:21by my postdoc Dana Lynn.
49:23So basically we cross referenced that
49:24with all the regions in the genome that
49:27we know are differentially methylated.
49:28An association with early life drought,
49:30for example,
49:31or with aging,
49:32and what we find is the following
49:35of about 200,000 windows.
49:36We tested genome wide.
49:38I just want to point out that really only a
49:41minority of them in a particular cell type
49:44have regulatory capacity to begin with,
49:46right?
49:46Most of CP G sites and most of the genome,
49:49whether they're methylated or not,
49:50don't do much of anything,
49:52but if they are drought associated
49:55sites or male ranked associated sites,
49:58they're significantly.
49:58More likely to fall in one of those
50:01active regulatory regions than
50:03expected just by background chance,
50:05where again if we use age,
50:07differentially methylated sites as a control,
50:09you see no such signal of active
50:12participation in regulation.
50:13And so now we were able to start
50:15putting together our results like
50:17this where for a very particular
50:19region of the genome that contains
50:21specific set of CPG sites
50:22we see. Increases.
50:25In RNA relative to DNA,
50:28if that region fragment is not methylated,
50:30so zero methylation means that you
50:32see regulatory activity he there,
50:34whereas if that exact same sequence
50:37is methylated then we see complete
50:40repression of regulatory activity,
50:42so pointing this is a way of
50:44identifying methylation dependent
50:45regulatory activity across the genome.
50:47This particular example gives us
50:49causal evidence in an in vitro
50:51framework that those sites have
50:52the capacity to drive differential
50:54expression and the particular sites
50:56I'm showing you here happen to be.
50:59Forked sites.
50:59That's it.
51:00Just upstream of a gene that's
51:02important to T cell receptor activation.
51:05We can then couple that with the observation.
51:07ULL data from the animals themselves
51:09in vivo in a completely unmanipulated
51:11environment where we see that,
51:13for example,
51:14male social status is also associated
51:17with levels of DNA methylation,
51:20and independently with levels
51:22of gene expression.
51:23So the correlation is consistent
51:25with the causal of the correlation.
51:27Evidence in vivo is consistent
51:30with the causal evidence in vitro.
51:33So to sum up,
51:34we have this hypothesis about
51:36this pathway that connects early
51:39environment to adult phenotypes.
51:41Our data suggests that early
51:42environments also predict DNA
51:44methylation in adulthood.
51:45In this natural environment,
51:46where there's absolutely no
51:48correlation between drought in the
51:49first year of life and rainfall
51:51at the time of measurement,
51:52but that those types of patterns are
51:55compounded by further resource limitation.
51:58In other words,
51:58we're really only seeing this
52:00when the animals are exposed
52:01to fairly severe deprivation.
52:02Material deprivation linked to both
52:06a low quality environment as a whole
52:08and then further knock on effects
52:09of other types of individual adversity.
52:12And that leads to substantial
52:13heterogeneity across different
52:14forms of early life experience.
52:16Where,
52:16grossly speaking,
52:17I would say our data are consistent
52:21with effects of deprivation
52:23related early life experiences
52:25rather than social threat related.
52:29Early life experience like being
52:31born to a low status mother.
52:33Additionally,
52:34our data suggests that DNA
52:36methylation associated with the
52:38social or ecological environment
52:40and including sources of early life
52:43adversity are more likely to be
52:45functionally relevant than background
52:47sites identified in the genome,
52:49including those that we can detect
52:50in the exact same data set in
52:52association with age, for example.
52:54So that's promising, right?
52:56It?
52:56It speaks to the potential for this
52:59mediating pathway to really matter,
53:01but I think that our results also
53:03suggest that care is still warranted.
53:04Warranted we see this enrichment,
53:06but there's lots of individual sites
53:08that are early life associated that,
53:10as far as we can tell from
53:12the data available to us,
53:13don't particularly do anything,
53:15and if they don't particularly do anything,
53:17then they are very unlikely to
53:20rely on a causal pathway between
53:22early life environment and,
53:25for example,
53:26compromised health or earlier
53:27mortality in adulthood.
53:29And I think that the lesson for us
53:31is that those correlations that
53:33we observe in population studies.
53:35So far are really the first step
53:37and the second
53:38step that we should increasingly
53:40think about embedding into studies of
53:43environmental or social epigenetics
53:45in general are causal tests,
53:47especially experimental tests where possible
53:50of whether those differences even matter.
53:53So in some we see effects of early life
53:56environment on later life phenotype that
53:59are in many ways strikingly parallel
54:01to what's been described in humans.
54:04And in fact some of the measurement
54:05constructs that we've been using.
54:06The baboons are directly borrowed
54:08from the literature in humans.
54:10These suggest that early life effects
54:13on later life health are not something
54:16that humans invented and not purely
54:20explained by the types of highly developed.
54:22Urban environments that many
54:24of us live in today.
54:27Rather, they're part of the fabric of
54:31the societies of primates and other long
54:33lived social mammals that have probably
54:36predated our species for millions of years.
54:39However, because these species,
54:40like the baboons live in a relatively
54:43simplified environment compared to humans,
54:45studying them gives an ability
54:47to ask questions about the types
54:49of early environments,
54:50the way they split between
54:52different types of exposure.
54:53And the relationship between early
54:55life and adulthood that are sometimes
54:58difficult to come to grips with in humans.
55:00And so with that I just want to thank the
55:04people who have led a lot of this work.
55:07Susan, Albert Smith,
55:08Archie and Jean Altman,
55:09who are my fellow travelers on all of
55:11the research that has to do with baboons.
55:13Matthew Schippel, Susan,
55:15former student who led the
55:18intergenerational adversity work.
55:19My own lab,
55:20and particularly Amanda Lea,
55:22Jordan Anderson and Dana Lynn,
55:24who were the trainees who produced some of
55:26the work that I talked to you about today.
55:28And if there's time I'd be happy
55:30to take any questions.
55:34Fantastic thank you so much Jenny and
55:36and you do indeed have we do indeed
55:39have some time for questions despite me
55:42interrupting you mid mid presentation.
55:44You know just what. So first of all,
55:47ask anyone that wants to raise
55:48their hand and they can mute
55:50themselves and ask questions.
55:51Or feel free to put your question
55:54into the chat for Jenny.
55:59Hi I have a question. My name
56:00is Tara Vaccarino. Are the trust
56:04a decent? Are wonderful seminar
56:06I can you hear me I wanted yeah I
56:10wanted to ask you to what extent
56:13this you think that this early effect
56:16of the environment are actually
56:17acting on the prenatal stage
56:19rather than early postnatal?
56:20I think in principle there is no
56:23proof that drastic conditions like
56:25what you're studying like drought
56:28for example, or even dominance
56:30amongst these primates
56:32could actually not affect.
56:33Much earlier phases of development,
56:36including the brain,
56:38not just the blood,
56:39which is what you can study postnatally.
56:42So what would
56:44be a potential Ave to study earlier
56:47effect and to what extent do you think
56:50they're possible or even likely? Thank
56:52you. I think they're entirely possible,
56:56and it sort of depends on our
56:58ability to get at that question.
56:59Depends on the source of
57:01early adversity in question,
57:03so for some of the things we're
57:06considering like early life.
57:10Social status, maternal social status
57:12or maternal social integration.
57:14Those don't change a whole lot in our
57:16study system prenatally to postnatally
57:18within a short period of time,
57:21and so we really can't disentangle
57:24whether the crucial point there
57:27is in utero or or post Natal.
57:30We can do a little bit actually with
57:33the drought effects because we have
57:35such seasonality in our population
57:36in year to year variation differs.
57:38So for example, when we were looking
57:40at drought effects on fertility,
57:42we used the first year of life,
57:44but we also did some comparisons
57:46with the prenatal period.
57:48So if you just take birth
57:50minus a year instead,
57:52which would cover conception as
57:54well in these animals and we
57:56get similar kinds of patterns,
57:58but they're weaker, which.
58:00You know,
58:01obviously I think you would
58:02take that with a grain of salt,
58:04but they would suggest to us by
58:05themselves that for that particular
58:07exposure the post Natal period maybe
58:09more important potentially because
58:11mothers are actually buffering
58:13their offspring against against.
58:17The challenges posed by a
58:18drought and they can do so more
58:20effectively when they're neutral.
58:21But here I'm I'm speculating a little bit,
58:23so sometimes we can get it,
58:24and sometimes we can't,
58:25because those correlations can
58:26be quite tight across that
58:28about a year and a half or so.
58:30And I think Karthik had a question.
58:34Great talk is really cool stuff.
58:35My question is kind of similar
58:37to Doctor Vaccarino's,
58:38but one of the interesting things
58:39was just the reduced like fertility,
58:41like or like having less children.
58:43And I mean I could think of
58:44a lot of causes for that.
58:46Like you know their eggs are less
58:47viable or they change their behavior
58:49so they're like having less like
58:51intercourse or the fact that like
58:52just 'cause of their like hierarchy,
58:54they just have less opportunity.
58:56Have you looked at?
58:57Like what is the actual
58:58like granular cause of
58:59this change in like?
59:02Yeah, so in in that severe drought they
59:05just stopped cycling and I think the
59:08the rationale for that is very similar
59:11to reproductive biology in humans,
59:13which is when you know energy
59:16expenditures exceed energy intake.
59:19We stop cycling. I mean you see that,
59:20for example in athletes,
59:22but you also see it in in Syria in
59:26situations of severe caloric deprivation.
59:28Baboons have actually.
59:30In many ways,
59:31very similar reproductive biology,
59:32so I think that's what's happened.
59:34They're not getting pregnant because
59:36they're they're they're not ovulating.
59:38But
59:38that would be like 'cause
59:39there was differences between like the
59:41higher status versus the lower status,
59:43like the higher status it would
59:45affect both of them, right?
59:46'cause they're both starving,
59:47but it seemed like it wasn't as effective.
59:48So what would be like the mechanism
59:50where effects one at the other?
59:52Yeah, so that I can tell you with
59:55less certainty, but one of the reasons
59:57that being a high status female baboon
59:59is probably a nice thing to be.
01:00:01Is a nice thing to be is not only because
01:00:04they suffer reduced much less targeting,
01:00:07social targeting by other animals, right?
01:00:09There's a lot of reinforcement
01:00:11of hierarchies in baboons,
01:00:13so there's a lot of psychosocial stress
01:00:15as well, but because you know it,
01:00:17it it actually increases their
01:00:19access to resources.
01:00:20They have the ability to displace
01:00:23other animals from areas where
01:00:25food might still exist,
01:00:26and so I suspect that in energetic
01:00:28rationale has a big role to play.
01:00:30That's certainly.
01:00:31That's for example,
01:00:32the reason why we think females who
01:00:34are higher status have shorter inter
01:00:36birth intervals than females who
01:00:38are low status in our population.
01:00:40They just come back to reproductive
01:00:42condition faster.
01:00:43It's shorter postpartum area,
01:00:45interesting, cool, thanks sure.
01:00:50I'm very did you have a
01:00:52question there or Preston?
01:00:54Yes, Preston has a question.
01:00:57Question do you want to unmute there?
01:00:59Yep, I'm Preston hi.
01:01:04This was this was fascinating.
01:01:06I I was really intrigued by.
01:01:08I was just wondering with
01:01:10the causes of death.
01:01:12I don't know if if you knew
01:01:13any difference in the causes of
01:01:15death with those who have the
01:01:16social hits versus those who are
01:01:18able to live a long happy life
01:01:19and had that privilege kind of
01:01:21lifestyle you're talking on it.
01:01:22I don't know if there's anything
01:01:23on that. We have limited information on
01:01:27cause of death because we can't do you know,
01:01:30full clinical workups of dead baboons.
01:01:32And honestly we barely recovered
01:01:34their bodies in a state where we
01:01:37would be able to do that, right?
01:01:39'cause so so I'll say the the
01:01:41proximate cause of death for most of
01:01:43our animals is they got eaten by by.
01:01:45Leopard or a lion or something like that?
01:01:48You know we do see pathologies and we record
01:01:50wounds and pathologies over the the lifespan.
01:01:52But they're pretty crude and so the
01:01:55short answer is, we really wish we knew.
01:01:58But everything I showed you today is an
01:02:01all 'cause mortality sort of situation.
01:02:03We could parse some of the individuals
01:02:05who we have better data for,
01:02:06but that just drops our sample size a lot.
01:02:10Thank you I. I imagine that
01:02:12being depressed probably makes
01:02:13you more likely to be eaten,
01:02:15so I I think that's.
01:02:16It make probably makes you slower,
01:02:18probably makes you less liked by
01:02:20your your social peers if you're
01:02:23causing them difficulties too,
01:02:24so I think it makes sense.
01:02:25I just thank you this is this is great.
01:02:28Thanks, I know we've run
01:02:30a little bit over time,
01:02:30but Amanda does have her hand raised,
01:02:32so Amanda,
01:02:32would you like to ask a question?
01:02:34Thank
01:02:35you. Jenny is great talk.
01:02:36I always love hearing a research
01:02:37and as a treat to hear about baboons
01:02:40in a world where consumed
01:02:42by my cats. So but related.
01:02:47I was struck by an image near
01:02:48the end of your talk where a baboon
01:02:50mother and infant appeared to be engaging
01:02:53in some face to face mutual gazing,
01:02:56and this led me to wonder.
01:02:58Are you guys looking at or
01:03:00thinking of looking at?
01:03:02You know mother infant interactions
01:03:03in the middle period and how this
01:03:06might be influencing infant outcomes.
01:03:08Yeah, absolutely.
01:03:09So that was the last part
01:03:12of Matthew Zippel thesis,
01:03:14so he was the the former PhD
01:03:16student who did the work on
01:03:18intergenerational adversity, right?
01:03:19And so where we are there is that we think
01:03:22OK moms who experience early adversity.
01:03:24They grow up and then they have
01:03:28more difficulty keeping their kids
01:03:30alive and that's the phenomenon.
01:03:32But it's not the explanation right?
01:03:34And we think that they're having
01:03:36more difficulty because they
01:03:37themselves are in poor condition.
01:03:39Well,
01:03:39in order for that to translate to the kid,
01:03:41I mean there are a few different
01:03:42ways that could happen,
01:03:43but one is certainly in their
01:03:46interaction and caretaking style,
01:03:48and so he's been aggregating very
01:03:50very granular data on mother infant
01:03:53pairs to try and understand what
01:03:56the differences in sort of very,
01:03:58very granular levels of experience are
01:04:00for the kids of moms who have those.
01:04:03Those adverse early experiences
01:04:05versus those that don't,
01:04:07and they certainly appear to be different.
01:04:09Although not in ways that we completely
01:04:11have our fingers on yet right,
01:04:12they spend more time with adult males.
01:04:14For instance,
01:04:15they spend more time away from Mom.
01:04:19Who is driving that behavior
01:04:21is not entirely clear yet,
01:04:23but hopefully we'll get a little
01:04:26bit more more of an understanding
01:04:28as as that analysis proceeds.
01:04:31I want to see thank you.
01:04:33I know we are, we're time,
01:04:35but I if there are any trainees
01:04:37that are still on the line that
01:04:39would like to ask any questions
01:04:41please do now is your opportunity.
01:04:43Any other questions from the audience?
01:04:48And you know, I just when I,
01:04:50when you're presenting your
01:04:52developmental constraints versus
01:04:53the predictive adaptive response,
01:04:54really resonated with me.
01:04:56Because obviously,
01:04:56with the kind of work I do with exposure
01:04:59to prenatal anxiety or depression,
01:05:00you know the clinical implications
01:05:02of saying the predictive adaptive
01:05:04response is the best fit.
01:05:05Model is actually really appalling,
01:05:07because it suggests that you shouldn't
01:05:09treat anxiety or depression.
01:05:11Pregnancy obviously makes no sense at all,
01:05:13so I can't really subscribe to
01:05:14the predictive adaptive response.
01:05:15And in the context, so.
01:05:17Mental anxiety and depression or
01:05:18perinatal anxiety and depression.
01:05:19So the developmental constraint
01:05:20model really seems to fit a little
01:05:22bit better with the data that I've
01:05:23seen from my my own research as well,
01:05:25you know, Karen, as you probably have,
01:05:27I've seen a couple of papers that
01:05:29actually do go down that path.
01:05:31Yeah, well, we shouldn't try to
01:05:34address this because you know,
01:05:36the phenotype is meant to be matched.
01:05:39And I, I think I think that's problematic
01:05:42from a variety of perspectives.
01:05:45And beyond, whether or not one hypothesis,
01:05:49one class of models is a better
01:05:50explanation versus the other,
01:05:51it also seriously conflates what
01:05:55evolution may have produced with what we
01:05:57might want our societies to look like.
01:06:00And those are not not always
01:06:02the same thing, right?
01:06:04So
01:06:05exactly. Yeah, well, we've got
01:06:07messages coming and saying great talk.
01:06:09I'd just like to reiterate that
01:06:11and thank you once again Jenny,
01:06:12you have an open invitation to New Haven.
01:06:14We will get you here.
01:06:15We will make that pizza comparison
01:06:17happen that we promised.
01:06:19But please join me once again in thanking Dr.
01:06:21Chung for a wonderful presentation.
01:06:23Thanks to all of you. I really
01:06:25appreciate the opportunity to do
01:06:26this and I'm sorry I couldn't be
01:06:27with you in person.
01:06:28Oh my God will make it happen.
01:06:31Wonderful, I think we'll stop
01:06:32the recording that bye bye.
01:06:33Jennie thanks bye.