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Child Study Center Grand Rounds 02.09.2020

March 22, 2021
  • 00:00Here and and then Karen take it from there.
  • 00:05So may I call Doctor Tara Thompson Felix.
  • 00:09Take it away.
  • 00:10Doctor Thompson feelings, yeah,
  • 00:12so good afternoon everyone.
  • 00:13My name is Tara Thompson.
  • 00:15Felix I'm one of the first year child
  • 00:18Psychiatry Fellows so I actually met
  • 00:20Doctor O'Donnell a few months ago
  • 00:22on virtually in one of our breakout
  • 00:24sessions and grand rounds and just
  • 00:27heard a lot about his research who
  • 00:29really got me excited because I've
  • 00:31done some research and in utero,
  • 00:33and epigenetics and I really wanted
  • 00:35the opportunity to kind of explore
  • 00:37that more so Doctor O'Donnell
  • 00:39has been awesome and discussing.
  • 00:41Potential projects with me.
  • 00:43Since then an I am very excited
  • 00:46to announce that I will be a
  • 00:48PhD student in his lab.
  • 00:50Starting in July,
  • 00:52so I'm very excited to pass it
  • 00:55along to Doctor Karen O'Donnell.
  • 00:58Thank you.
  • 01:00But
  • 01:00congratulations again, Tara Anne.
  • 01:02I'm very happy that you got into
  • 01:05the program and delighted that
  • 01:06you'll be working in the lab,
  • 01:08and I'll be looking forward to when you
  • 01:11were doing Grand Ryans showing some.
  • 01:13Hopefully you're very interesting data,
  • 01:15fetal exosomes and how they are shaped
  • 01:17by exposure to prenatal adversity
  • 01:19and how they can inform on child in
  • 01:22your development and Doctor Martin.
  • 01:24Thank you very much for that
  • 01:26kind introduction for not giving
  • 01:28the game away about where I am.
  • 01:30Chrome I thought I would start by giving
  • 01:33you a little bit of a background on
  • 01:36how and where I've come from an end to
  • 01:38end up here at the Child study Center
  • 01:41and as Doctor Martin mentioned, an.
  • 01:42If this is an experiment between
  • 01:44the Department of Citrix and
  • 01:46the Child Study Center,
  • 01:47I'm more than happy to be a subject in
  • 01:50this study because it's such a pleasure
  • 01:52to be acting as a bridge between these
  • 01:55two Fantastic Department's an so as
  • 01:57Doctor Martin at knows I actually,
  • 01:59I'm from the West coast of Ireland.
  • 02:01A very small village,
  • 02:02around 200 people an on the
  • 02:05western coast of Ireland,
  • 02:06very close to a small town called Belona.
  • 02:09It's right on the Atlantic coast.
  • 02:11The red line that you're seeing on
  • 02:14this map is what's called the Wild
  • 02:16Atlantic way that has a roadway that
  • 02:19hugs the Atlantic coast of Ireland.
  • 02:21And for those of you who are
  • 02:24avid cyclists like Doctor Martin,
  • 02:26it's 1500 miles and that you
  • 02:28can cycle around our lender,
  • 02:30driver and arnensee some fantastic sites.
  • 02:32Such as the Stone Age settlement
  • 02:34that's around 20 minutes from my home,
  • 02:37Amore Dan Patrick head.
  • 02:38I can tell you it took a long
  • 02:41time to take this photograph.
  • 02:42This isn't representative of the
  • 02:44weather that we have in Ireland,
  • 02:46Ann,
  • 02:47but there are some beautiful scenes
  • 02:49to be had in the West Coast of
  • 02:51Ireland and up until very recently
  • 02:53that would have been the most
  • 02:55famous thing about where I'm from.
  • 02:58This wonderful coastline and
  • 02:59this Stone Age settlement.
  • 03:00And but then Joe Biden got elected.
  • 03:03And his ancestral home is around 20 minutes
  • 03:06from my home in a small town called Belle.
  • 03:10And all you can see is distant relatives
  • 03:13celebrating when the election was announced,
  • 03:15and mural that remains in
  • 03:17our small town and were,
  • 03:19among other works.
  • 03:21So where everyone was very excited by this,
  • 03:24this is actually the 2nd president
  • 03:26that belona can lay claim
  • 03:28to because Mary Robinson,
  • 03:30the first woman President of Ireland,
  • 03:32also hails.
  • 03:33From Belona,
  • 03:34so a little fun fact,
  • 03:36but as Doctor Martin mentioned,
  • 03:38I my trading didn't occur in
  • 03:40Ireland and I had to travel a
  • 03:42little bit further East for that,
  • 03:44and that was to London where I
  • 03:47completed my undergrad Masters and
  • 03:48eventually my PhD where I worked
  • 03:50with Vivek Glover and who's an
  • 03:53expert and perinatal cycle biology
  • 03:54and also with Tom O'Connor.
  • 03:56Andthat PhD was actually a little
  • 03:59bit of an experiment at the time as well.
  • 04:01It was in an NIH funded.
  • 04:04PhD occurring in London using the Avon
  • 04:06Longitudinal Study of Parents and Children,
  • 04:09which is along the Tunal perspective
  • 04:11cohort of around 15,000 pregnancies
  • 04:13where these children have been
  • 04:15followed up continuously there,
  • 04:16now approaching their 30s themselves,
  • 04:18having children of their own,
  • 04:20and I'll talk to you a little
  • 04:23bit about that cohort today.
  • 04:25Now following my PhD,
  • 04:26I moved back out West but much
  • 04:29further West than where I'm from.
  • 04:31An ended up at McGill
  • 04:33University where I completed it.
  • 04:35Post doctoral fellowship with Michael Meaney,
  • 04:38who many of you will know and
  • 04:40it's really been a pioneer in
  • 04:43the field of social epigenetics.
  • 04:45So how the environment can shape
  • 04:47variation in the epigenome?
  • 04:49When I talk about the epigenome,
  • 04:51I'm talking about chemical marks
  • 04:53or modifications that sit on or
  • 04:56close to the genome that can change
  • 04:58the way the genome functions and
  • 05:01throughout all of my training.
  • 05:03Really, what's been at the heart of my.
  • 05:06Fascination,
  • 05:06really with science is the idea that
  • 05:09the early environment can shape health
  • 05:11and disease across the lifespan.
  • 05:14Ann and this notion or this idea has
  • 05:17been described as the developmental
  • 05:19origins of health and disease and which
  • 05:22has led to a whole field of research.
  • 05:25A SoC adore had society that was
  • 05:27really an largely based on findings
  • 05:30from the work of David Barker.
  • 05:32In fact,
  • 05:33it used to be referred to as the Barker.
  • 05:37Hypothesis that and the fetal
  • 05:39origins of disease,
  • 05:40that the the origins of many
  • 05:43types of disease could be traced
  • 05:45back to the neutral environment
  • 05:48and these observations initially
  • 05:50stemmed from David's work,
  • 05:52where he notice to parallel between
  • 05:55high rates of infant mortality
  • 05:57and subsequent rates of death
  • 05:59from coronary heart disease,
  • 06:01and these were largely in deprived
  • 06:04areas in the United Kingdom.
  • 06:07And what you're looking at here is
  • 06:09the relationship of risk from death
  • 06:11for death from coronary heart disease
  • 06:13as a function of birth weight.
  • 06:15I want David Barker noticed,
  • 06:17was that lower birth weight was
  • 06:19associated with an elevated or an
  • 06:21increased risk from death from coronary
  • 06:24heart disease before the age of 65,
  • 06:26and you can see a greater decline in
  • 06:28risk as we move to larger birth weights.
  • 06:31These are birth weights
  • 06:32expressed in pounds and answers,
  • 06:34and then maybe a slight uptick.
  • 06:37In at disease risk,
  • 06:39and as I mentioned,
  • 06:41this is really led to really an
  • 06:43expansive literature on how the neutral
  • 06:46environment can shape vulnerability
  • 06:49for cardiovascular disease,
  • 06:50and really a whole host of
  • 06:54metabolic phenotypes.
  • 06:55But of course,
  • 06:56the question is if the cardiovascular
  • 06:58system is so sensitive to the unusual
  • 07:01environment into adversity in usual,
  • 07:03what about the brain?
  • 07:05And as we heard from Kartek last
  • 07:08week and from Amanda study as well,
  • 07:11we know that the prenatal
  • 07:13environment can also shape variation
  • 07:15in brain related phenotypes.
  • 07:17So, for example,
  • 07:18at the Dutch hunger,
  • 07:20winter and the Holocaust have all
  • 07:22been associated with increased
  • 07:24risk for adverse.
  • 07:25Mental health outcomes in the
  • 07:27offspring and in the next generation,
  • 07:30and these have largely been
  • 07:32from retrospective studies where
  • 07:33this evidence first emerged.
  • 07:35And of course from our own work
  • 07:37with the Avon Longitudinal
  • 07:39Study of Parents and Children.
  • 07:41What we found is that maternal
  • 07:43prenatal anxiety and also
  • 07:44maternal prenatal depression,
  • 07:46associate's with an increased
  • 07:48risk for adverse mental health
  • 07:50outcomes in the child and what
  • 07:52you're looking at here is the
  • 07:54predicted population prevalence.
  • 07:56Of a probable mental disorder at
  • 07:59children from age 4 all the way
  • 08:01up to age 13 an and what we can
  • 08:05see is that those children born
  • 08:07to women that experience high
  • 08:09levels of anxiety in the prenatal
  • 08:12period have approximately double
  • 08:13the risk of ending up in the group
  • 08:16that is likely to suffer from
  • 08:19a probable mental disorder,
  • 08:20and we see this elevated risk across
  • 08:23childhood and into early adolescence,
  • 08:25and indeed.
  • 08:26As studies follow up,
  • 08:28studies have been completed
  • 08:29now into the early 20s,
  • 08:31and Sean a similar pattern of
  • 08:34Association between high rates of
  • 08:36prenatal anxiety and depression
  • 08:37and increase risk for adverse
  • 08:39mental health outcomes.
  • 08:41And I just want to point out that
  • 08:43these effects are independent
  • 08:45of socioeconomic status.
  • 08:47So you may think that this may be
  • 08:49confounded by maternal education
  • 08:51or maternal age,
  • 08:53or indeed taxol crowding or
  • 08:55obstetric outcomes.
  • 08:56Birth weight,
  • 08:57gestational age.
  • 08:57Because of the large sample
  • 09:00size of this court,
  • 09:01we can statistically control for
  • 09:03the effects of those exposures,
  • 09:06and we still see this independent
  • 09:09Association with maternal prenatal anxiety.
  • 09:11So for any of you that have
  • 09:14heard me speak before,
  • 09:16I always talk about 414 and 44 being
  • 09:18one in four women that are likely to
  • 09:22experience or struggle with their
  • 09:24mental health in and around pregnancy.
  • 09:27So I say one in four other estimates
  • 09:30they went in five, one in six,
  • 09:33and really what I think we're seeing
  • 09:35from these epidemiological analysis,
  • 09:38particularly the more recent
  • 09:39epidemiological analysis,
  • 09:40is increased rates.
  • 09:41Of perinatal mental health problems.
  • 09:44So,
  • 09:44for example,
  • 09:45Louise Howard Publishing in 2018 and
  • 09:47one in four women struggling with their
  • 09:50mental health in and around pregnancy.
  • 09:53Rebecca Pearson,
  • 09:53using the Avon Longitudinal Study
  • 09:56of Parents and children using the
  • 09:58second generation from that cohort.
  • 10:00Showed a generational increase in
  • 10:03rates of perinatal mental health
  • 10:06problems with again one in four
  • 10:09women experiencing perinatal
  • 10:11mental health problems.
  • 10:13So this is a common problem and
  • 10:16what is challenging with this
  • 10:18problem is that we're still not
  • 10:20screening women effectively,
  • 10:22and when we do screen women and
  • 10:24they're still not receiving
  • 10:26adequate treatment,
  • 10:27so we know that around 25% of
  • 10:30women who do experience perinatal
  • 10:32mental health problems receive
  • 10:34treatment and less than 5% of
  • 10:36those women achieve remission
  • 10:38or experience receive adequate
  • 10:40treatment to reduce their symptoms
  • 10:42down below clinical levels.
  • 10:43So this is a common problem that we are
  • 10:46not addressing sufficiently at the moment.
  • 10:49It is also a costly problem,
  • 10:51so we know that the per
  • 10:53year costs of untreated
  • 10:55perinatal mental health problems is
  • 10:57around 14 billion US dollars per year,
  • 11:00with around 40% of those costs attributed
  • 11:03to the adverse effects on the child.
  • 11:05So that's in the United States.
  • 11:07What about the in the UK where the
  • 11:10first cost estimate was produced?
  • 11:12Well, we see that around.
  • 11:14An 8 billion pounds is the cost
  • 11:17associated with untreated paradata mental
  • 11:19health problems in the United Kingdom,
  • 11:22but in contrast to the United States,
  • 11:25we see that 72% almost 3/4 of those
  • 11:27costs are attributed to the adverse
  • 11:30effects of untreated perinatal mental
  • 11:32health problems on child outcomes,
  • 11:35and you may ask,
  • 11:36rightfully So what is the difference
  • 11:38between these two cost estimates?
  • 11:41Why is it 40% in the United States and 72%?
  • 11:45In the United Kingdom or one
  • 11:47of the explanations for that is
  • 11:49because in the United States,
  • 11:51costs were only calculated on
  • 11:53child outcomes from zero to five,
  • 11:56whereas in the United Kingdom costs
  • 11:58were calculated from zero to 18.
  • 12:00So I think you can appreciate that if
  • 12:03we extend the follow up period in the
  • 12:06United States that 40% an proportion
  • 12:08of costs is likely to increase in
  • 12:11addition to the total costs that have
  • 12:14been reported from that cost analysis.
  • 12:16In the United States.
  • 12:19And of course,
  • 12:20you may ask about what is the impact
  • 12:22of the post Natal environment.
  • 12:24And of course,
  • 12:24we know that there is an effect
  • 12:26of the post Natal environment,
  • 12:28and in our studies from the Avon
  • 12:30Longitudinal Study of Parents and Children,
  • 12:32we see that perhaps,
  • 12:34as you would expect,
  • 12:35children that are exposed to high
  • 12:37levels of anxiety in the pre and post
  • 12:39Natal period are the children who do
  • 12:41worse than children who are exposed
  • 12:43to anxiety at one but not both.
  • 12:45Time points end up somewhere in the middle.
  • 12:48Now hasten to add, this is not a treatment.
  • 12:51And study this is not an intervention.
  • 12:54This is simply an epidemiological analysis,
  • 12:56but I think it provides proof of
  • 12:59principle that if we could pull down
  • 13:01or reduce maternal symptoms of anxiety,
  • 13:04ideally at both time points,
  • 13:06we could improve child outcome.
  • 13:10So again, just thinking about what are the
  • 13:13consequences for untreated perinatal mental
  • 13:15health problems on the next generation?
  • 13:18Well, I showed you the effects on child
  • 13:21outcomes from 4 to 13 years of age,
  • 13:24but this is another study
  • 13:26from the same cohort.
  • 13:28the Avon Longitudinal Study of Parents
  • 13:30and Children where they looked at the
  • 13:33rates of prenatal depression in women
  • 13:36that were born to ALS back moms who
  • 13:39either didn't or did experience.
  • 13:40Prenatal depression,
  • 13:41and so when we look at the daughters of women
  • 13:46who didn't experience prenatal depression,
  • 13:48we see that around 16% of those
  • 13:51women who want to experience prenatal
  • 13:53depression in their own pregnancies.
  • 13:56So what about the daughters from women
  • 13:58who did experience prenatal depression?
  • 14:01Or 54% of those women went on to experience
  • 14:04prenatal depression in their own pregnancies.
  • 14:08So I think you can begin to appreciate.
  • 14:11Add there can be marked intergenerational
  • 14:14effects of exposure to prenatal
  • 14:16depression and this makes it critically
  • 14:18important that we try to support
  • 14:21pregnant women and their mental
  • 14:23health both for the pregnant woman's,
  • 14:25all mental and physical health,
  • 14:27but also to potentially mitigate the
  • 14:30effects of this intergenerational
  • 14:33transmission of risk.
  • 14:34But there are some unanswered questions
  • 14:37and many of you will be looking at and
  • 14:40some of the slides that I presented
  • 14:42in some of the data that I presented
  • 14:45and thinking about the advances
  • 14:47that we've made in characterizing
  • 14:48genetic variation and thinking,
  • 14:50well,
  • 14:50isn't this just all confounded
  • 14:52by underlying genetic propensity
  • 14:54for psychiatric disorders and and
  • 14:55there have been many studies that
  • 14:58have attempted to address this,
  • 14:59perhaps indirectly,
  • 15:00and perhaps the most well established or
  • 15:02well known paper to address this question.
  • 15:05Was at this study by Hanigan and
  • 15:08colleagues based in the mobile
  • 15:10quarter large Norwegian study of
  • 15:13around 30,000 pregnant women,
  • 15:15Ann and they used a children of children
  • 15:19and sibling children of Twins design.
  • 15:22Basically it's a twin study that
  • 15:25looks at the offspring and their
  • 15:28conclusion was that a genetic
  • 15:30factor that explained relatedness
  • 15:33between Twins and siblings was.
  • 15:36The explanation for the effects of
  • 15:38prenatal depression on child outcome.
  • 15:40So they concluded that the entire
  • 15:43fetal origins hypothesis was
  • 15:45confounded by genetic variation using
  • 15:47an indirect assessment of genetic
  • 15:50variation using a twin design.
  • 15:52So we wanted to revisit this question
  • 15:55to really ask and provide a more
  • 15:58direct test of this hypothesis
  • 16:00as to whether or not there was
  • 16:03confounding by underlying genetic
  • 16:05propensity or genetic vulnerability.
  • 16:07For adverse mental health outcomes
  • 16:10now many of you will have heard from
  • 16:13our recent ground round sessions.
  • 16:16The use of polygenic risk scores
  • 16:18to capture common variation that is
  • 16:21associated with psychiatric disorders
  • 16:23and the use of these genetic tools
  • 16:26has really an been greatly facilitated
  • 16:29by these incredibly large genome
  • 16:31wide Association studies largely
  • 16:33conducted by the Psychiatric Genomics
  • 16:35Consortium where we have.
  • 16:3710s or hundreds of thousands of
  • 16:40individuals with a psychiatric disorder
  • 16:42and where we look at the snips,
  • 16:44the genetic variants that are associated
  • 16:47with the psychiatric disorder
  • 16:49and that provides us with an
  • 16:51effect size for that snip and
  • 16:53risk of psychiatric disorder.
  • 16:55Now what we can do is take those
  • 16:58effect sizes and we can count
  • 17:00up and using our own data using
  • 17:03genetic data from our own court,
  • 17:05we can count up the number of.
  • 17:08Risk snips that an individual carries,
  • 17:11and we can wait.
  • 17:12Each one of those snips by the
  • 17:15effect size that has been derived
  • 17:18from these very large scale genome
  • 17:21wide Association studies and what
  • 17:23you get is a simple summary score
  • 17:26that reflects an individual's
  • 17:28genetic vulnerability for adverse
  • 17:30mental health outcomes,
  • 17:31whether it be ADHD, schizophrenia,
  • 17:33or depression.
  • 17:34So the general principle is that once
  • 17:37we calculate this summary score.
  • 17:40And this polygenic risk,
  • 17:41or you will generally see that
  • 17:44cases or individuals that have
  • 17:46high risk for psychiatric disorder,
  • 17:48generally have a higher score
  • 17:51than non cases or controls.
  • 17:54So we use this methodology and
  • 17:56we can talk about the limitations
  • 17:58of this methodology and in the
  • 18:01question period and but we use
  • 18:03this methodology as what we think
  • 18:05of as the best approach at the
  • 18:08moment to capture genetic risk
  • 18:10for psychiatric disorders.
  • 18:11We calculated these polygenic risk
  • 18:13scores in the Outback children
  • 18:15around just over 5000 children.
  • 18:17We calculated them for ADHD,
  • 18:19schizophrenia and depression and then
  • 18:21we used child mental health symptoms,
  • 18:23derives from the strength.
  • 18:25Difficulties questionnaire from age
  • 18:284 to 16 years of age and then we use
  • 18:32long to tude ainle model modeling.
  • 18:35Generalized estimating equations to
  • 18:36ask whether or not the prediction
  • 18:39from maternal prenatal depression
  • 18:42or maternal prenatal anxiety was
  • 18:44confounded by child genetic risk for ADHD,
  • 18:47schizophrenia, or depression.
  • 18:49And.
  • 18:49And the take home message from these
  • 18:53analysis was that even when we
  • 18:55adjusted for child genetic risk for ADHD,
  • 18:58schizophrenia,
  • 18:59or depression,
  • 19:00we still saw a significant
  • 19:02independent effect of maternal
  • 19:03prenatal depression on child outcome.
  • 19:05And this is just a representative
  • 19:08figure using the ADHD polygenic
  • 19:10risk score and what you can see is
  • 19:13that children with a high burden of
  • 19:16genetic risk for ADHD and exposed to
  • 19:18high levels of maternal prenatal depression.
  • 19:21Show increased symptoms relative to
  • 19:23children with low genetic risk for
  • 19:26ADHD and low and exposure to low
  • 19:28levels of maternal prenatal depression,
  • 19:30depression and we see this for
  • 19:33the external Ising subscale.
  • 19:34We see this for the total symptom
  • 19:37scores and we see this at four years
  • 19:41of age but also at 16 1/2 years of age.
  • 19:45Now,
  • 19:46one of the interesting observations
  • 19:48from this study was that there
  • 19:51was no interaction with time.
  • 19:53We found a stable prediction from
  • 19:56maternal prenatal depression overtime.
  • 19:58Conversely, for both the schizophr.
  • 20:00Any other polygenic risk score
  • 20:02and for the depression polygenic
  • 20:05risk or we found a significant
  • 20:07interaction with time where the
  • 20:09polygenic risk score for schizophrenia
  • 20:12or depression strengthened as these
  • 20:14children approached adolescence,
  • 20:15so perhaps in the question period
  • 20:18we can discuss how developmentally
  • 20:20dynamic symptoms or phenotypes may
  • 20:22require developmentally informed
  • 20:24genome wide Association studies,
  • 20:26but going back to the question
  • 20:28at hand as to whether or not.
  • 20:32Effects of the prenatal environment are
  • 20:34confounded by child genetic variation.
  • 20:36At least from this study,
  • 20:39we can see that our best efforts to
  • 20:41assess genetic risk for psychiatric
  • 20:43disorders doesn't seem to confound
  • 20:46the Association between maternal,
  • 20:48prenatal depression or maternal
  • 20:50prenatal anxiety and child outcome,
  • 20:52and we do see an independent significant
  • 20:55prediction from child genetic risk
  • 20:58factors with the child ADHD PRS
  • 21:00being the strongest predictor.
  • 21:03Now for many years we spend a lot of
  • 21:05time talking about the importance
  • 21:07of maternal mental health,
  • 21:09but of course maternal mental health
  • 21:11can be associated with many other
  • 21:13phenotypes that are also at risk
  • 21:15factors for adverse mental health
  • 21:17outcomes and one of the other
  • 21:19exposures that we were particularly
  • 21:21interested in assessing and perhaps
  • 21:23especially relevant in the context
  • 21:24of an ongoing global pandemic,
  • 21:26was the role of maternal infection,
  • 21:28and again with the idea of trying
  • 21:31to understand whether or not there
  • 21:33could be synergy between.
  • 21:34Maternal prenatal anxiety or depression
  • 21:37and maternal infection to produce
  • 21:40an works outcomes for the child and
  • 21:44what you're looking at here in this
  • 21:47slide is symptoms from the social
  • 21:49communication disorder checklist,
  • 21:51which can be thought of as essentially
  • 21:54symptoms related to autism like features,
  • 21:57and we cut,
  • 21:59characterized or assessed maternal
  • 22:01infection in pregnancy,
  • 22:02and we particularly focused on.
  • 22:05Infections that may give rise to systemic,
  • 22:08an inflammation and infection an
  • 22:10and what we found was that the
  • 22:12number of maternal infections was
  • 22:14associated with increased symptoms.
  • 22:16Scores for the social communication
  • 22:19disorder checklist and the question
  • 22:21was whether or not maternal
  • 22:23anxiety would have an independent
  • 22:24effect and multiplicative effect,
  • 22:26and what we found was indeed
  • 22:29an additive effect.
  • 22:30An independent additive effect
  • 22:32of maternal prenatal anxiety,
  • 22:33and infection on child symptoms.
  • 22:36We saw this first social
  • 22:37communication disorder checklist,
  • 22:39but also for symptoms of 80 HD.
  • 22:42So,
  • 22:42just to summarize this first part of my talk.
  • 22:45I think that what we've documented
  • 22:47using the OS backward is that there
  • 22:49can be a persisting influence of the
  • 22:51prenatal environment on child outcome,
  • 22:53and we don't think that this is completely
  • 22:56confounded by child genetic risk factors.
  • 22:58Could it be amplified by
  • 23:01genetic variation in the child?
  • 23:03That's an open question and we have
  • 23:06published papers previously showing
  • 23:08evidence of gene environment interactions
  • 23:11and the prediction of child outcome.
  • 23:14Really highlights is that there are
  • 23:17multiple opportunities to intervene to
  • 23:19try and improve maternal mental health,
  • 23:21ideally as early as possible in
  • 23:23pregnancy and certainly early
  • 23:25in the post Natal period.
  • 23:27Of course,
  • 23:28I think our data also speak to the
  • 23:30importance of considering maternal
  • 23:32physical health as another point of
  • 23:35intervention to ensure that we can
  • 23:38bolster both maternal well being but
  • 23:40also potentially improve child outcome.
  • 23:43Now one of the characteristics
  • 23:45of this research area,
  • 23:47the developmental origins
  • 23:48of health and disease,
  • 23:49is that there can be marked
  • 23:51variation or marked individual
  • 23:53differences in the effects of the
  • 23:55prenatal environment on child
  • 23:57outcome, and the question is,
  • 23:59how can we better identify children
  • 24:01that are at risk and to try and get at
  • 24:04this question or address this question?
  • 24:07And I moved to Montreal to
  • 24:09study social epigenetics with
  • 24:11Michael Meaney and that's really.
  • 24:13Features heavily in my current
  • 24:15research program because epigenetics,
  • 24:17really, while it's heavily involved
  • 24:19in cellular differentiation,
  • 24:20there was a paradigm shift in
  • 24:22the early 2000s where we began to
  • 24:25appreciate that the environment could
  • 24:27also shape epigenetic modifications.
  • 24:29But before we get into that,
  • 24:32I think it's helpful to start with a
  • 24:35definition of epigenetics and I like
  • 24:37add this definition that comes from
  • 24:40the road map project and which is really.
  • 24:43Markable initiative that sought to
  • 24:45act as a parallel to the Human Genome
  • 24:49Project and to characterize different
  • 24:52epigenetic modifications across the
  • 24:54genome and across different cells
  • 24:56and tissues and integrate those
  • 24:58data to provide a richer perspective
  • 25:00and a deeper understanding of the
  • 25:03epigenome across cells and tissues.
  • 25:05Now,
  • 25:06what many of you on the call
  • 25:09will probably be aware of is the
  • 25:12very controversial area of.
  • 25:14Transgenerational epigenetic inheritance,
  • 25:15which posits that epigenetics
  • 25:17states can be transmitted across
  • 25:19multiple generations with Fidelity,
  • 25:21and the evidence for that in
  • 25:23humans is lacking an.
  • 25:25As I mentioned,
  • 25:27it is a very controversial subject,
  • 25:29and there is an excellent review by
  • 25:32Edith Heard for any of you that are
  • 25:35interested in getting a having a
  • 25:38deeper dive into this controversy,
  • 25:41but also the evidence we can see.
  • 25:44Evidence for transgenerational
  • 25:45epigenetic inheritance in C.
  • 25:47Elegans.
  • 25:47In certain plants,
  • 25:48an Indra Sofala fruit flies and but
  • 25:51again trying to establish that evidence
  • 25:54in humans is particularly challenging.
  • 25:57It doesn't rule out the possibility an,
  • 26:00but there is no clear evidence for
  • 26:03that in humans at the current time.
  • 26:06But when I think about epigenetics
  • 26:09and really the definition that
  • 26:11I use in my work is different.
  • 26:14The genetic states or epigenetic
  • 26:16modifications that can alter the
  • 26:18transcriptional potential of a cell,
  • 26:20or indeed a system and what I mean by
  • 26:23that is directly related to gene expression,
  • 26:27so epigenetic modifications have the
  • 26:29potential to alter gene expression,
  • 26:31and that's one of the reasons that
  • 26:34people are so interested in the
  • 26:36epigenome trying to understand how
  • 26:39these epigenetic modifications can
  • 26:40alter the function of the genome.
  • 26:43And as.
  • 26:44Doctor Martin very kindly pointed
  • 26:46out we've written a review on
  • 26:49the evidence for and against the
  • 26:52epigenome underlying the biological
  • 26:54embedding of experience and what
  • 26:56we conclude from this review is
  • 26:59that there is quite a lot of a good
  • 27:02correlational evidence suggesting
  • 27:04that the epigenome may underlie the
  • 27:07biological embedding of experience,
  • 27:10but trying to establish causality
  • 27:12does require model or.
  • 27:14Organisms and I think,
  • 27:16will be greatly facilitated by the
  • 27:18advent of EPI genome editing technology,
  • 27:21where we can actually directly
  • 27:23manipulate in a site specific
  • 27:24manner and different epigenetic
  • 27:26States and establish functional
  • 27:28associations with gene expression
  • 27:30and different brain based phenotypes.
  • 27:32Now the modification that
  • 27:34I'm going to spend most of
  • 27:36my time talking about today
  • 27:38is that of DNA methylation,
  • 27:41which is the addition of a
  • 27:43methyl group are represented.
  • 27:45Here in red to a cytisine,
  • 27:47that's a C in the genetic code,
  • 27:50Anne Anne, but I also want to point
  • 27:52out from this figure from this
  • 27:54review that this is one of many
  • 27:57different epigenetic modifications.
  • 27:59In fact, some people call them
  • 28:01epigenetic systems that work in
  • 28:03conjunction with one another,
  • 28:05and as we make progress in our
  • 28:07understanding of the epigenome,
  • 28:09and indeed, social epigenomics,
  • 28:11we're beginning to realize the
  • 28:13importance of integrating different
  • 28:14layers and levels of information.
  • 28:16About the epigynum.
  • 28:18To fully understand its impact
  • 28:21on genome function.
  • 28:22So let's think about this
  • 28:24in more simple terms.
  • 28:26I think it can be very helpful to think
  • 28:29about the epigenome in terms of metaphor.
  • 28:32And so some great metaphors exist to
  • 28:34try and add describe the epigenome.
  • 28:37I particularly like the idea of
  • 28:39the epigenome as a conductor,
  • 28:41so as sheet music and as a conductor.
  • 28:44So we think about genes being the
  • 28:46individual and instruments or musicians.
  • 28:48And really,
  • 28:49if we want to create a Symphony to create.
  • 28:53A phenotype that makes sense.
  • 28:55It's important that all of these
  • 28:57different units and work together
  • 28:59in a coordinated manner,
  • 29:00and one of the ways that they
  • 29:03do so is by following the signs
  • 29:06of the signals of the conductor.
  • 29:08One of the other metaphors that I
  • 29:11love to use to describe how the
  • 29:13epigenome influences the function
  • 29:15of the genome is that of grammar,
  • 29:18and so you can have all of the
  • 29:21correct letters and text.
  • 29:23In a book, but if you don't have punctuation,
  • 29:27if you don't have grammar,
  • 29:29then you lose all meaning and we all
  • 29:32know that grammar can be critically
  • 29:35important for our understanding of text,
  • 29:38and similarly with the epigenome.
  • 29:40Epigenetic modifications are critically
  • 29:42important for placing emphasis on
  • 29:44certain genes or silencing other genes,
  • 29:47so really playing a functional role.
  • 29:50Now,
  • 29:50historically we've thought
  • 29:51about DNA methylation as being
  • 29:53a repressive modification.
  • 29:55People have likened it to a light switch,
  • 29:58so turning a gene on turning.
  • 30:00Aging off and the evidence really
  • 30:03to support DNA methylation
  • 30:04as a repressive modification.
  • 30:06Cones from X inactivation where DNA
  • 30:09methylation plays a role in silencing
  • 30:11one of the X chromosomes an in females,
  • 30:15but also from an imprinting where
  • 30:18there can be silencing of 1 copy
  • 30:21of a gene for ad that occurs
  • 30:23in a parent of origin fashion.
  • 30:26But we've begun to realize that we
  • 30:28as we add more deeply characterized
  • 30:31DNA methylation.
  • 30:32Is that it's Association with gene
  • 30:34expression can be more nuanced.
  • 30:36In some cases it can act like a dimmer
  • 30:40switch, turning gene expression up,
  • 30:41or Dan.
  • 30:42Indeed in other situations,
  • 30:44demethylation is not associated
  • 30:45with gene expression,
  • 30:46and in other cases still we can find
  • 30:49the DNA methylation at certain sites
  • 30:51within a gene can actually alter
  • 30:54the product or the splice variant
  • 30:56that's produced from a given gene.
  • 30:58I think the take home message is that
  • 31:01the context is critically important.
  • 31:03Another cool curring epigenetic modifications
  • 31:05can also have an impact on whether
  • 31:08or not DNA methylation is negatively
  • 31:10associated with gene expression or
  • 31:12positively associated with gene expression,
  • 31:15or indeed not associated
  • 31:17with gene expression at all.
  • 31:20Now, one thing to consider when we look
  • 31:22at DNA methylation across the genome is
  • 31:25that DNA methylation is a binary event,
  • 31:28it's either on or it's off.
  • 31:30But throughout my talk you'll hear me talking
  • 31:33perhaps about percentage DNA methylation,
  • 31:3590% DNA methylation, 60% DNA methylation,
  • 31:38or 10% DNA methylation, and that is
  • 31:40because when we look at DNA methylation,
  • 31:43particularly in clinical studies,
  • 31:44we're looking at an average across
  • 31:47multiple cells, and so when we look within.
  • 31:50Multiple cells we can see that there may
  • 31:53be methylation at a given site in one cell,
  • 31:56but not in another,
  • 31:58and so when we report back DNA methylation,
  • 32:01an results were talking about
  • 32:03it as percentage metalation.
  • 32:05Essentially,
  • 32:05the number of metalation marks within
  • 32:07the cells of your tissue of interest.
  • 32:10And that brings me to one of the issues
  • 32:13with epigenetics in clinical studies,
  • 32:16and that is the rule of
  • 32:18cellular heterogeneity.
  • 32:19So one of the principle
  • 32:21rules of the epigenome.
  • 32:22Is to ensure that there is cellular
  • 32:25differentiation and the maintenance
  • 32:27of those cellular phenotypes,
  • 32:29and in fact where you have disorders
  • 32:32related to DNA methylation.
  • 32:34Another epigenetic modifications.
  • 32:36You can require pluripotency increase
  • 32:38the stemness of these cells,
  • 32:40giving rise to disorders and
  • 32:43diseases such as cancer.
  • 32:45But one of the other interesting
  • 32:48features of the epigenome and one of
  • 32:51the functions that is emerging for the
  • 32:53epigenome is the idea of genomic priming.
  • 32:56So this is the idea that there can
  • 32:59be an exposure that gives rise to a
  • 33:02change in an epigenetic state such
  • 33:05as DNA methylation, and that am,
  • 33:08instills,
  • 33:08or instantiates the capacity to then
  • 33:11have an even greater response to an
  • 33:13exposure subject to subsequent exposures.
  • 33:16That an individual or sell may
  • 33:18experience as subsequently,
  • 33:20and this is really nicely articulated
  • 33:22in this paper from my colleague
  • 33:24Nadine Provincal,
  • 33:25working with Elizabeth ****** where
  • 33:27they treated hippocampal stem
  • 33:29cells with dexamethasone,
  • 33:30which is a synthetic glucocorticoid.
  • 33:32And you can think of it like
  • 33:35a synthetic cortisol,
  • 33:37an that produced widespread changes
  • 33:39in DNA methylation and what was
  • 33:41interesting about this particular study
  • 33:43was that the changes in DNA methylation.
  • 33:46Didn't always correlate with the gene
  • 33:49expression response to dexamethasone,
  • 33:51but the DNA methylation changes that
  • 33:53did occur did predict the magnitude
  • 33:56of response to subsequent exposures
  • 33:58to dexamethasone,
  • 33:59supporting this notion of genomic priming,
  • 34:02and you may be asking,
  • 34:04well, how could that occur?
  • 34:07What would be the molecular mechanism?
  • 34:09Well,
  • 34:10one of the reasons that we're interested
  • 34:13in steroid hormones such as cortisol,
  • 34:16progesterone, estradiol,
  • 34:17testosterone.
  • 34:17Is because they are there.
  • 34:19Their receptors are nuclear receptors.
  • 34:22So when you have high levels of
  • 34:24glucocorticoids such as cortisol,
  • 34:26they can bind to the glucocorticoid
  • 34:29receptor highlighted here in Gray,
  • 34:31and the binding of that receptor
  • 34:33to the DNA can
  • 34:35result in DNA demethylation or changes
  • 34:38in DNA methylation at the site that
  • 34:41the transcription factor binds.
  • 34:43So here you can see before
  • 34:46exposure to glucocorticoids.
  • 34:47You have higher levels of DNA methylation
  • 34:50at this particular site or glucocorticoid
  • 34:53response element then you have
  • 34:55glucocorticoids binding to its receptor,
  • 34:57resulting in changes in DNA methylation
  • 34:59and then when you have subsequent
  • 35:02exposures to glucocorticoids,
  • 35:03you then have enhanced response
  • 35:05to that exposure.
  • 35:07And I think this is a particularly
  • 35:10interesting hypothesis and model
  • 35:12when we think about the effects
  • 35:14of prenatal adversity or early
  • 35:16adversity and how that may.
  • 35:18Confer or prime the genome for subsequent
  • 35:23exposures or responses to those exposures.
  • 35:27So how do we analyze DNA methylation?
  • 35:30Well,
  • 35:30there are many approaches that we can use.
  • 35:33We can use an epigenome wide
  • 35:35Association study or metalation
  • 35:37wide Association study an if we use
  • 35:40whole genome bisulfite sequencing,
  • 35:42we can assess roughly around 24 million
  • 35:44CPG's more commonly because of cost.
  • 35:47We're using an microarray based technology
  • 35:49where we assess around 850,000 sites.
  • 35:52Now, what you can quickly appreciate
  • 35:54is that you're going to need very.
  • 35:57Large courts to to adjust for
  • 36:00multiple comparisons with so many
  • 36:02sites and so what's promising in
  • 36:04this regard is the PACE consortium,
  • 36:07which is a consortium that's combining
  • 36:10multiple different studies to
  • 36:12perform meta analysis of prenatal
  • 36:14exposures on DNA methylation.
  • 36:16So they have performed a meta analysis
  • 36:19of maternal prenatal smoking and
  • 36:21DNA methylation and cord blood,
  • 36:23and found over 2000 sites that
  • 36:26survived genome wide.
  • 36:27Adjustment and then the figure that
  • 36:30you're looking at here on the right
  • 36:32is showing all of the sites in
  • 36:35blue and red across the different
  • 36:37chromosomes in the human genome
  • 36:39that were associated with infant
  • 36:41birth weight in cord blood and
  • 36:44from around 9000 participants.
  • 36:46Now,
  • 36:46one of the challenges with this approach is,
  • 36:49as I said, you need very large sample sizes,
  • 36:53but you also ideally would
  • 36:55need to have longitudinal data.
  • 36:57So for example in the birth weight
  • 36:59study that I'm talking about here,
  • 37:02they identified around 900 CPG's that
  • 37:04were associated with birth weight
  • 37:06for a subset of those participants.
  • 37:09They then had longitudinal data and
  • 37:11what they found was that of those
  • 37:14900 sites only around 10% of them.
  • 37:17We're still associated with
  • 37:19birth weight at 7 years of age,
  • 37:22and this highlights a complexity with
  • 37:25epigenetic analysis that you don't have
  • 37:28as it's not as strong a confounder
  • 37:30with genome wide Association studies.
  • 37:33This idea that there can be
  • 37:35dynamic change in DNA methylation
  • 37:37requiring longitudinal sampling.
  • 37:40So what approaches can we
  • 37:42take to overcome these issues?
  • 37:44Well,
  • 37:45one approach that has I've used extensively.
  • 37:48Is that of an biomarkers?
  • 37:50Epigenetic biomarkers that distill
  • 37:52down and genome wide data into
  • 37:55a single unit of measurements,
  • 37:57and perhaps the most well
  • 38:00established of these biomarkers,
  • 38:01is that of epigenetic age,
  • 38:04initially developed by Steve Horvath,
  • 38:06an at UCLA Ann,
  • 38:08and the idea with these epigenetic
  • 38:10biomarkers is that we can identify
  • 38:13sites that are predictive
  • 38:15of chronological age,
  • 38:17and we can create.
  • 38:18A measure of epigenetic
  • 38:20age for an individual.
  • 38:22These clocks now exist with
  • 38:24multi tissue predictors,
  • 38:25so you can take any biological
  • 38:27sample from anyone and you can then
  • 38:30measure their epigenetic age and
  • 38:32what we notice in population levels
  • 38:34is that there are some individuals
  • 38:37that you'll hire epigenetic age,
  • 38:39relative chronological age and
  • 38:40others that show lower epigenetic
  • 38:42age relative to their chronological
  • 38:44age and what's interesting is
  • 38:46that those individuals with higher
  • 38:48epigenetic age acceleration.
  • 38:50Show increase risk for age related?
  • 38:55Disorders including cardiovascular disease,
  • 38:58but also all cause mortality.
  • 39:01Now, one of the challenges with
  • 39:03this epigenetic Clock from the
  • 39:05multi tissue epigenetic Clock
  • 39:07is that it was developed using
  • 39:09primarily samples from adults and
  • 39:11they ranged in age from zero to 100,
  • 39:14but it was primarily samples from
  • 39:16adult participants and the error in
  • 39:18the prediction of the epigenetic
  • 39:20Clock is around 3.6 years and
  • 39:22which obviously is a very long
  • 39:25time in the life of a child.
  • 39:27So we set about creating a
  • 39:30novel pediatric specific.
  • 39:31Epigenetic Clock,
  • 39:32which was published last year.
  • 39:34We used approximately 2000 DNA
  • 39:36methylome's and we simply asked what
  • 39:38were the sites that were associated
  • 39:41with chronological age in this cohort.
  • 39:43This is data from longitudinal cohort
  • 39:45where we use the original epigenetic
  • 39:47Clock with longitudinal samples,
  • 39:49and what you can appreciate from this is
  • 39:52that the slopes are all over the place.
  • 39:55An long digital samples that
  • 39:57should be epigenetically older
  • 39:59are appearing epigenetic.
  • 40:01Younger and you can see this again here,
  • 40:03and this simply reflects the error
  • 40:05in the conventional epigenetic Clock.
  • 40:07When we plot these data using the
  • 40:09new pediatric epigenetic Clock,
  • 40:11I think you can appreciate that the
  • 40:13slopes become a lot more positive,
  • 40:15so we brought the error in prediction of
  • 40:18epigenetic age down to around six months,
  • 40:21and many of you may be thinking,
  • 40:23well, you know, that's great.
  • 40:25You can just calculate someones
  • 40:26age based on their date of birth.
  • 40:29What is what value is this?
  • 40:31An and so in this particular study,
  • 40:34what we found was that children
  • 40:36of the autism spectrum disorder
  • 40:38had accelerated epigenetic age,
  • 40:40an Association that we saw with the
  • 40:42pediatric specific epigenetic Clock,
  • 40:44but not with the conventional Horvath Clock.
  • 40:47But of course,
  • 40:48bringing us back to the topic of interest,
  • 40:51the fetal origins of health and disease,
  • 40:54we wanted to ask whether or not
  • 40:56maternal prenatal anxiety would
  • 40:58be associated with epigenetic age,
  • 41:00acceleration,
  • 41:00and to do that we made use of
  • 41:03two longitudinal at courts,
  • 41:05one from the Netherlands.
  • 41:06That's primarily Caucasian one
  • 41:08from Singapore,
  • 41:09that's multi ethnic and what we found
  • 41:11was that maternal prenatal anxiety
  • 41:13was associated with accelerated
  • 41:15epigenetic age at six years of age.
  • 41:17In the 10 years of age in the Bible
  • 41:20course and again we replicated
  • 41:23this in the coastal court,
  • 41:25finding that maternal prenatal
  • 41:26anxiety was associated with
  • 41:28accelerated epigenetic age,
  • 41:29an effect that strengthens overtime
  • 41:32is particularly pronounced at 48
  • 41:35months of age. Now, one of the questions
  • 41:37that again I'm very interested in is
  • 41:40is trying to understand whether or not
  • 41:41there are features or aspects of the
  • 41:44Pulcinella environment that may be able
  • 41:46to buffer or moderate the effects of the
  • 41:48prenatal environment on epigenetic states.
  • 41:50Because of course it's very
  • 41:52depressing to to give a talk and say,
  • 41:54well, it's all over at birth,
  • 41:56and of course it's much more optimistic
  • 41:58and positive to say that there are
  • 42:00potential interventions that we can
  • 42:02implement that may buffer or mitigate
  • 42:04the effects of prenatal adversity.
  • 42:06This is a paper from my PhD mentors
  • 42:08showing that an infant attachment style,
  • 42:11so each child's perception of
  • 42:13the predictability an index of
  • 42:16the quality of care in the pools.
  • 42:18Naval environment moderates the
  • 42:20Association between prenatal cortisol
  • 42:21exposure and child cognitive development.
  • 42:23Of course, other examples exist.
  • 42:25This is from the Boukris Early
  • 42:28Intervention Project,
  • 42:28showing that secure an infant attachment
  • 42:31can buffer or moderate the effects of
  • 42:34early adversity on child psychopathology.
  • 42:36So of course,
  • 42:37the question we wanted to ask with
  • 42:39this study was whether or not infant
  • 42:42attachment would buffer or moderate the
  • 42:44effects of maternal prenatal anxiety
  • 42:46on child epigenetic age acceleration.
  • 42:48And this is unpublished data.
  • 42:49But what we find is that yes indeed in
  • 42:52children that have secure attachment
  • 42:53we see a positive but nonsignificant
  • 42:55Association between maternal prenatal
  • 42:57anxiety and child epigenetic age
  • 43:00acceleration,
  • 43:00but the effects of maternal prenatal
  • 43:02anxiety on child epigenetic age
  • 43:04acceleration are particularly
  • 43:05pronounced in children.
  • 43:06With an insecure attachment style.
  • 43:09Again supporting this idea of a potential,
  • 43:12pools Natal moderation of infant attachment.
  • 43:16Now of course there are other M
  • 43:19epigenetic biomarkers that we can
  • 43:21use to try and probe our describe
  • 43:23the effects of the environment
  • 43:25on health related outcomes.
  • 43:27This is one that we're starting
  • 43:29to make use of.
  • 43:31It's a second generation after genetic
  • 43:33Clock and what is different about
  • 43:35this epigenetic biomarker is that it
  • 43:37incorporates information about plasma
  • 43:39proteins that are associated with
  • 43:41cardiovascular disease risk as well
  • 43:43as sites that are associated with.
  • 43:46Aging and we wanted to determine
  • 43:48whether or not there was any Association
  • 43:50between an early adversity and this
  • 43:53epigenetic biomarker making use
  • 43:55of the Nurse Family Partnership,
  • 43:57which many of you will know is
  • 43:59a randomized control trial of
  • 44:01the perinatal intervention that
  • 44:02targets vulnerable low income.
  • 44:04First time moms and it provides
  • 44:06nurse visitations have been shown to
  • 44:09reduce child maltreatment an improve
  • 44:10outcomes for both mothers and children.
  • 44:13We published the first epigenetic
  • 44:15analysis in this cohort.
  • 44:16A collaboration with Jim Lechman and
  • 44:19Elena Grigorenko when she was based
  • 44:21here and we found that there was some
  • 44:24preliminary Association between nurse
  • 44:26Visitation and variation in DNA methylation.
  • 44:29But really the take home message was
  • 44:32that there was a profound effect of
  • 44:35childhood maltreatment on DNA methylation,
  • 44:37but we couldn't distinguish the
  • 44:39effects of maltreatment from,
  • 44:41say, for example,
  • 44:42the effects of associated
  • 44:44confounders like smoking.
  • 44:45So what about?
  • 44:47This measure of epigenetic age,
  • 44:49acceleration in the context of the Nurse,
  • 44:52Family, Partnership,
  • 44:52or what we see is that children with
  • 44:55a documented or substantiated case of
  • 44:58child maltreatment show accelerated
  • 44:59epigenetic aging using this disease.
  • 45:02Relevant epigenetic biomarker.
  • 45:03But what about when we break this
  • 45:06down by an intervention group or
  • 45:08what we find is that in the nurse
  • 45:11visit a group in purple here and
  • 45:14the yellow is the control group.
  • 45:16We find no difference in
  • 45:18epigenetic age acceleration.
  • 45:19As a function in those individuals that
  • 45:22don't have a history of child maltreatment.
  • 45:25But when we look in the group that does
  • 45:27have a history of child maltreatment,
  • 45:30we see significantly increased
  • 45:31an epigenetic age,
  • 45:33acceleration and those individuals that
  • 45:34have a history of child maltreatment
  • 45:37that are in the control group.
  • 45:39But it seems that exposure to
  • 45:41nurse Visitation to that early
  • 45:42intervention seems to be buffering
  • 45:44the effects of child maltreatment.
  • 45:46An epigenetic age acceleration.
  • 45:48Now we can discuss.
  • 45:50Potential explanations for this
  • 45:51one possibility is that perhaps
  • 45:53the severity of abuse was less in
  • 45:56the nurse visited group that there
  • 45:58was greater surveillance of abuse,
  • 46:00and the nurse visited group an.
  • 46:02An alternative hypothesis is that
  • 46:04the early intervention is providing
  • 46:06some buffering capacity,
  • 46:07so even in the face of child maltreatment,
  • 46:10there's less of an impact on
  • 46:12epigenetic age acceleration just
  • 46:14in the last couple of minutes.
  • 46:16I just like to tell you about one of
  • 46:19the biomarker that we're making use of.
  • 46:22Which is a measure that relates
  • 46:24to this paper I highlighted,
  • 46:27previously speaking to this
  • 46:28idea of genomic priming,
  • 46:30and in this paper they created an epigenetic
  • 46:33biomarker of glucocorticoid exposure,
  • 46:35and so this essentially we can create
  • 46:38a an index or a proxy measure for
  • 46:41glucocorticoid exposure based on
  • 46:43DNA methylation, and so we created.
  • 46:46We use this array.
  • 46:47Tested this out in a court
  • 46:50where we had DNA methylation.
  • 46:52Data upper than at one year of age in a
  • 46:55cohort from the University of California,
  • 46:58Irvine,
  • 46:58and we also had structural imaging in
  • 47:01this cohort and what we simply asked
  • 47:03was whether or not the sites that
  • 47:05were associated DNA methylation sites
  • 47:07that were associated with maternal
  • 47:09prenatal depression did they overlap
  • 47:11with the sites that were identified
  • 47:13to be glucocorticoid sensitive sites
  • 47:15in that paper that I showed you.
  • 47:17And indeed,
  • 47:18we found significant enrichment
  • 47:19of glucocorticoid sensitive sites
  • 47:21in the sites that were associated
  • 47:23maternal prenatal depression.
  • 47:24And when we created this Google
  • 47:27Corticoid exposure score,
  • 47:28we saw a significant negative Association
  • 47:30between maternal prenatal depression
  • 47:32and this glucocorticoid exposure score.
  • 47:34And interesting Lee,
  • 47:35what we found was that this glucocorticoid
  • 47:38exposure score at birth predicted
  • 47:40lower hippocampal volume birth,
  • 47:41and as you'll appreciate,
  • 47:43the hippocampus is enriched
  • 47:45for glucocorticoid receptors.
  • 47:46So we find that the direction of
  • 47:48this Association is consistent
  • 47:50with a higher maternal prenatal
  • 47:52liberation predicting a lower score.
  • 47:55And a lower score predicting
  • 47:58lower hippocampal volume.
  • 47:59So, just to summarize,
  • 48:01I think that with some of the
  • 48:03studies that I've tried to
  • 48:05highlight perhaps very quickly
  • 48:06today, we can see that variation in
  • 48:09DNA methylation is associated with
  • 48:10variation in the early environment.
  • 48:12I think as we move towards trying to
  • 48:15make these findings clinically relevant,
  • 48:17we need to move towards more integrative
  • 48:19models where we're incorporating
  • 48:20measures of genetic variation,
  • 48:22and we're incorporating an greater
  • 48:24measures of the social environment,
  • 48:26and I think one way that we
  • 48:28can really begin to probe.
  • 48:30Causal associations between the social
  • 48:32environment and epigenetic states
  • 48:34is through the use of interventions,
  • 48:36and this is an area that I'm
  • 48:39particularly keen to do more work in,
  • 48:42and one collaboration that I'm very
  • 48:44excited about is a cluster randomized
  • 48:46control trial of parental intervention
  • 48:48that begins in early pregnancy that
  • 48:51seeks to reduce prenatal anxiety
  • 48:53and depression but also provide an
  • 48:56information about nutrition and sleep,
  • 48:58trying to reduce domestic violence, an.
  • 49:00An increase female empowerment and
  • 49:02we're doing this in rural Vietnam
  • 49:04with my colleague James Fisher,
  • 49:06where one in three women can
  • 49:08experience or struggle with their
  • 49:10mental health and pregnancy.
  • 49:12We're just coordinating to receive
  • 49:14samples from approximately 1200 mothers
  • 49:17and their infants with biological
  • 49:18samples at birth at 12 months and a 24
  • 49:21months MA which have been collected
  • 49:23in parallel with standardized
  • 49:25measures of child newer development.
  • 49:27And really the goal with these
  • 49:29kind of studies and the goal of.
  • 49:32Understanding epigenetic States and
  • 49:34modifications and implementing them
  • 49:36in clinical studies is really to
  • 49:38try and understand how we can make
  • 49:40interventions work from war individuals,
  • 49:42so I'll leave it there with maybe
  • 49:45just one kind of call to action.
  • 49:47I was very pleased to be invited to
  • 49:49take part in the Scientific Council
  • 49:52of Postpartum Support International,
  • 49:54and this is a plug for their
  • 49:56national strategy on how we can
  • 49:59improve perinatal mental health.
  • 50:00And so I think this is a societal problem
  • 50:03that requires a societal response,
  • 50:06and I think we're all responsible
  • 50:07for playing our part and trying
  • 50:10to support perinatal mental health
  • 50:12and recognizing that there are
  • 50:14structural and societal factors
  • 50:15that we can target and to try and
  • 50:18improve perinatal mental health.
  • 50:19And this isn't just all pregnant mothers
  • 50:22and have another thing to worry about an,
  • 50:25so I'll leave it with that and just
  • 50:28thank you all for your attention and take.
  • 50:31Any questions?
  • 50:41Fantastic. Questions please.
  • 50:43Just go for it or put it in the text.
  • 50:51Hi, this is Flora. Do you hear me?
  • 50:54Yes yes Laura hi sorry hi,
  • 50:57how are you really? Nice talk.
  • 50:59I had a question um so so as you
  • 51:02know epigenetics are very much
  • 51:04self type an organ specific so
  • 51:07perhaps you can clarify for us.
  • 51:10I mean of course studies in humans
  • 51:13cannot be done in brain whereas
  • 51:16studies in animals can and I'm
  • 51:18assuming some of those that you.
  • 51:21Elucidated or talked about where
  • 51:23done in mouse or rat brains, right?
  • 51:27So perhaps,
  • 51:28given the course profound difficulties,
  • 51:31you know?
  • 51:32Same brain samples from humans
  • 51:35living individuals.
  • 51:37Is it been any study in animals that has?
  • 51:41Um illuminated this concept to
  • 51:43what extent peripheral samples
  • 51:45like blood can inform us on what's
  • 51:48actually happening in the brain or
  • 51:50the individuals as they grow up,
  • 51:52and an and develop.
  • 51:55Yeah floor this is such
  • 51:57a great great question.
  • 51:58And as as you've shown with your own work,
  • 52:02talking about somatic mutations,
  • 52:03and we know that even genetic variants
  • 52:06may not be shared across different
  • 52:08tissues and so there have been
  • 52:11attempts to address this problem.
  • 52:13And so for example,
  • 52:14there's a tool called Pecan
  • 52:16developed by Michael Horror,
  • 52:18Gustavo Tracking Michael Meaney,
  • 52:19which actually does a paired comparison of
  • 52:22DNA methylation in multiple brain regions,
  • 52:24and unfortunately is just
  • 52:26in peripheral blood.
  • 52:27At the moment and looks at the
  • 52:29correspondence between DNA methylation and
  • 52:31in blood with different brain regions,
  • 52:33and they identify CPG's that show a
  • 52:36higher degree of concordance than others.
  • 52:38I think your point is well taken,
  • 52:41this is the idea that we can take
  • 52:43a peripheral sample like blood and
  • 52:46say that this is going to predict
  • 52:48DNA methylation state in a neuron in
  • 52:51the dentate gyrus of the hippocampus
  • 52:53I think would is a stretch.
  • 52:55I think that it's going to.
  • 52:58Be very challenging to identify and
  • 53:00sites where there is a high degree
  • 53:03of correspondence in specific brain
  • 53:05nuclei between brain and blood.
  • 53:07Where I think we can begin to get
  • 53:09a better understanding of pathways
  • 53:11that are likely to be shared across
  • 53:15brain and periphery is if we focus on
  • 53:18specific regions in the genome where
  • 53:20there may be snips that influence
  • 53:22DNA methylation in the periphery that
  • 53:25also are shared snips that influence DNS.
  • 53:28Relation in central and we can use
  • 53:30the peripheral tissue essentially as
  • 53:32a model Organism to say look this
  • 53:34proof of principle that this exposure
  • 53:36influences DNA methylation or inclusion.
  • 53:38Influences the relationship between the
  • 53:40snip and DNA methylation in the periphery.
  • 53:43And perhaps this could be
  • 53:45occurring in the brain.
  • 53:46But then we would need to
  • 53:48document that experimentally,
  • 53:49either in cell culture in ipsc's.
  • 54:04Any other questions anyone?
  • 54:12Well, it's. It is 2:00 o'clock,
  • 54:14Kieran saved by the Bell.
  • 54:16But thank you so much that was really
  • 54:18a marvelous presentation and we learn
  • 54:20so much and wonderful to have you
  • 54:22here and we look forward to all that
  • 54:24you'll teach us another ideal do.
  • 54:26So thank you here and thank you
  • 54:28very much. Thank you everyone.