Yale Psychiatry Grand Rounds: Lustman Awards 2024

Transcript

• 00:00Thanks, Kelly for that
• 00:02very nice introduction.
• 00:07Well, thank you everybody for being here.
• 00:08I'm excited to talk to you
• 00:10about my research today.
• 00:11I'm going to talk to you a bit about the
• 00:15histone deacetylase 6 and it's work in PTSD.
• 00:19We have some exciting translational
• 00:21evidence of suppression in PTSD
• 00:24for this enzyme we term HDAC 6.
• 00:28So you know PTSDI think most of us in
• 00:31psychiatry are familiar with this disorder,
• 00:33but it is anxiety,
• 00:35it's under the anxiety disorder
• 00:38diagnosis within our DSM 5.
• 00:40The treatments that we have currently
• 00:42that are FDA approved and most commonly
• 00:45used are primarily symptomatic treatments.
• 00:48And you know, with the leading treatment
• 00:50as starting treatment as our SSRIs,
• 00:52our selective serotonin reuptake inhibitors.
• 00:55But we know that we only have a 50 to
• 00:5860% response rate and and that's sort of
• 01:00on the best end with these treatments.
• 01:03And, you know,
• 01:04we have a variety of other symptomatic
• 01:05treatments we can go to as second,
• 01:07third, fourth lines to treat
• 01:09different parts of the disease,
• 01:11the nightmares, the insomnia, flashbacks.
• 01:14But we have a hard time really
• 01:17targeting the entire illness.
• 01:19Part of that is because this
• 01:21illness is so pleotropic and,
• 01:22and presents in so many different ways and,
• 01:25and at different times.
• 01:26It can present within, you know,
• 01:28six months after a trauma,
• 01:30it anytime after one month after the trauma,
• 01:32it is considered PTSD and,
• 01:35and no longer the acute stress diagnosis.
• 01:37But it can also, you know,
• 01:38we've seen Vietnam Veterans who
• 01:40present with symptoms of PTSD
• 01:4230-40 years after their trauma.
• 01:45And so how is that, how is that happening?
• 01:48And how,
• 01:48how is this all one disorder that
• 01:50we are trying to treat in one way?
• 01:52And, and what does that really mean?
• 01:54And,
• 01:55and how can we better understand this
• 01:57disorder and the pathophysiology of it
• 02:00such that we can target our treatments?
• 02:03And so I think, you know,
• 02:04the field as a whole is really starting
• 02:06to follow in the footsteps of,
• 02:07of the oncology research and of cancer.
• 02:09And we're,
• 02:10I think a little bit behind them
• 02:12in this precision medicine pursuit
• 02:13and this pursuit to,
• 02:15to find targeted treatments
• 02:17for individuals and,
• 02:18and where we can really help with that.
• 02:21I think maybe I'm biased,
• 02:23but I feel that H Dax and epigenetics,
• 02:25which I'll get into a bit more
• 02:27and utilizing neuroimaging,
• 02:28non invasive imaging modalities to be
• 02:31able to better understand the brain,
• 02:33allow us to,
• 02:35to really better understand these
• 02:37disorders on an individual basis.
• 02:39And so I think, you know,
• 02:41that allows us to hopefully down
• 02:42the road be able to stratify,
• 02:44stratify medications based on
• 02:47an individual's pathophysiology
• 02:48rather than trying to treat this,
• 02:51especially this pleiotropic
• 02:52disease as one and one only.
• 02:56So epigenetics and histone deacetylases,
• 02:58they're a class of 18 enzymes and they're,
• 03:01they're canonically known as
• 03:02epigenetic enzymes because of their
• 03:05role deacetylating or removing
• 03:06acetylomorides from the lysine
• 03:08tails on the histone core proteins.
• 03:11And so these tails are very lysine rich.
• 03:13They can be added an acetylm Y,
• 03:15they can be added or removed and that
• 03:17alters how closely the DNA is held
• 03:19and whether or not an open reading
• 03:21frame can be formed and therefore
• 03:24genomic transcription can occur.
• 03:25So the the H docs as they're known,
• 03:28it is 18 enzymes.
• 03:30However, within the H doc classes,
• 03:32there are four classes and they
• 03:34all function very differently.
• 03:36So I think H docs one through
• 03:38three are sort of very much this,
• 03:41this epigenetic role, but one that
• 03:42we are going to talk about today.
• 03:44H doc 6 is part of class 2B and it
• 03:48actually is more more predominant in
• 03:51the cytoplasm than in the nucleus.
• 03:52So it does shuttle between the cytoplasm and
• 03:55the nucleus of the cell and of the neuron,
• 03:57but in the brain,
• 03:58but it is actually more functional
• 04:00in the cytoplasm.
• 04:01So it's not quite an epigenetic enzyme in the
• 04:04in the way that we think about epigenetics.
• 04:07But it was originally found to be a
• 04:11microtubule deacetylase in its role
• 04:13of deacidylating the alpha tubulin at
• 04:15lysine 40 and in that it stabilized
• 04:18and destabilized alpha tubulin and
• 04:20part of the microtubule structure.
• 04:22And so that allows for both
• 04:24the growth cone formation,
• 04:25so cell,
• 04:27cell growth as well as cell some
• 04:30of cell movement through filopod
• 04:32formation and then also replication.
• 04:35As we know,
• 04:37mitophase and anaphase rely
• 04:39predominantly on the microtubules
• 04:42and then it also has a role in
• 04:45autophagosome degradation and and
• 04:47it was found then through some
• 04:49studies about 10 years ago to be
• 04:51abundantly expressed within the
• 04:52serotonergic neurons of the brain and
• 04:54so within the dorsal Raphae nucleus.
• 04:56They found this,
• 04:58this highly studied,
• 05:00highly cited study found that H
• 05:03.6 was very highly expressed in
• 05:05the dorsal Raphae nucleus and
• 05:06within the serotonergic neurons.
• 05:08And moreover,
• 05:09they found that if they knocked
• 05:11it out both constitutively with
• 05:13a a Cree driven deletion of H .6
• 05:15in mice as well as if they did a
• 05:18pharmacologic inhibition with H .6
• 05:20selective inhibitors that they could
• 05:22promote different and a less anxiety
• 05:25prone phenotype of these mice.
• 05:27So this led to this understanding
• 05:29that you know there may be something
• 05:32going on here with H .6 in emotional
• 05:34regulation and an anxiety regulation
• 05:37and they began to better understand
• 05:40that H .6 was needed for the role
• 05:43of the glucocorticoid receptor.
• 05:45And through that and through a
• 05:48few other studies that were done
• 05:50over the next couple of years,
• 05:51this role for HDAC 6IN deacidylating and
• 05:55therefore stabilizing or destabilizing
• 05:57the HSP 90 glucocorticoid receptor and
• 06:01FKBP 5 two complex was better understood.
• 06:04And So what actually under happens
• 06:07is the HDAC 6 removes this acetyl
• 06:10moiety from HSP 90,
• 06:11which is our heat shock protein that
• 06:13is a a commonly known chaperone protein
• 06:15for the glucocorticoid receptor.
• 06:17And that allows it to complex with
• 06:20the glucocorticoid receptor when
• 06:22a glucocorticoid such as cortisol
• 06:23binds and with FKBB 5.
• 06:25And that allows this translocation of
• 06:27the glucocorticoid receptor from the
• 06:29cytoplasm into the nucleus and then
• 06:32therefore the glucocorticoid response
• 06:33elements to be transcribed on the genome.
• 06:36And so the thought was and,
• 06:38and based on their deletion studies,
• 06:40they, the sort of the predominant
• 06:43understanding was that an increase in
• 06:45H Doc 6 therefore would lead to this
• 06:47increase in stress susceptibility
• 06:49because we felt that an increase
• 06:51in H Doc six would allow more of
• 06:54these GR ES to be expressed.
• 06:57And so to better understand that in in the
• 07:01in vivo in humans as well as in animals,
• 07:04there is this novel tracer that
• 07:06has been developed out of MGH and
• 07:08the Martinez imaging Center there.
• 07:11And they developed this tracer
• 07:13called Beveristat,
• 07:14which is a fluorine 18 labeled PET
• 07:17suitable radio lag and targeting HDAC 6.
• 07:20And so this tracer has had had gone
• 07:22into humans first in Belgium and
• 07:24then we redid quite a bit of the test
• 07:27retest studies here at Yale as well.
• 07:30And we decided to put this into to
• 07:32PTSD both in humans as well as in
• 07:34a rodent model to better understand
• 07:36how HDAC 6 and if we could is,
• 07:38is acting both in humans in PTSD.
• 07:42And so our original hypothesis was
• 07:44that the stress susceptibility or PTSD
• 07:47symptoms would be correlated with
• 07:48an increase in HDAC 6 based on these
• 07:51findings from these 2012 and 2015 papers.
• 07:54And we believed that,
• 07:56you know,
• 07:57this translational imaging would
• 07:58allow for this visualization
• 08:00and quantification of H .6.
• 08:01And so the rodent model that we chose to
• 08:03use was a single prolonged stress model.
• 08:06I used predominantly all male
• 08:08Sprite Dolly rats at this point.
• 08:10That's a,
• 08:10we do need to go into females of rats.
• 08:13I, I am not, that's not lost on me,
• 08:16but for the,
• 08:16for the proof of principle of this study,
• 08:19we did all males and we use the
• 08:21single prolonged stress model
• 08:22for a couple of reasons.
• 08:23One is that it's well validated in in rats,
• 08:27which we cannot use mice as well with
• 08:30PET imaging due to the size of the brain.
• 08:33The other is that I felt that it
• 08:36really capitulated a nice model
• 08:37of the pro anxiety and the hyper
• 08:40arousal symptoms of PTSD.
• 08:42And it also recapitulated this single
• 08:44stress event rather than some of the
• 08:48more prolonged stress paradigms that
• 08:51I think sometimes lead to more of a
• 08:54depressive phenotype rather than a
• 08:56a stress or anxiety and PTSD like phenotype.
• 08:59So this procedure involves restraining
• 09:01an animal for 120 minutes,
• 09:04putting them in a tank by themselves
• 09:06to swim for 20 minutes,
• 09:07letting them rest for 15 minutes.
• 09:09And then they are exposed to diethyl
• 09:11ether until they lose consciousness.
• 09:13At which point they are single housed
• 09:15and untouched with free access to
• 09:17food and water on a traditional 12
• 09:19hour light dark cycle for seven days.
• 09:21And it has been shown repeatedly in
• 09:23the literature that at this point,
• 09:25after seven days, they will demonstrate
• 09:28APTSD like phenotype or a hyper arousal,
• 09:30high anxiety like phenotype.
• 09:34So the first experiment that
• 09:36we did was really, you know,
• 09:37the, the typical experiment,
• 09:38I think where, you know,
• 09:40we took two groups of animals.
• 09:41We had one group that was stressed.
• 09:43We had one group that was controlled.
• 09:44They were handled both similarly
• 09:46leading up to the stress day.
• 09:48After the stress day, the,
• 09:49the control animals were handled,
• 09:51but no but continue to remain double housed,
• 09:54but we're not single housed after that.
• 09:56And the stressed animals were
• 09:58stressed and then single housed
• 10:00and not handled after that point.
• 10:02They then both underwent open field
• 10:04behavioral testing and H .6 pet on
• 10:06the same day and the following day
• 10:07they were sacrificed and their brains
• 10:09were removed for post mortem analysis.
• 10:13And you know,
• 10:15pretty much as we expected based
• 10:16on the literature,
• 10:17we did see changes consistent with
• 10:20anxiety phenotype and consistent with
• 10:22what was shown in the literature
• 10:24to be this PTSD like model in
• 10:27our behavioral testing.
• 10:29And then interestingly,
• 10:31when we did the H stack 6
• 10:33imaging with Beveristat,
• 10:34we found a decrease in the stressed
• 10:37animals in these key regions of
• 10:38the brain that we identified.
• 10:41So and we didn't see, you know,
• 10:43there was a slight decrease in
• 10:44the cerebellum in the whole brain,
• 10:46but not statistically significant,
• 10:47unlike the other key regions that
• 10:50are affected more under stress
• 10:52such as the amygdala,
• 10:53hippocampus,
• 10:54limbic cortex and the brain stem,
• 10:56notably where the dorsal Raphae
• 10:58nucleus and serotonergic neurons
• 10:59are predominantly located.
• 11:00And this was really surprising to us
• 11:02given our original hypothesis was
• 11:04that there would be an increase.
• 11:06And so because of this and because
• 11:08of the quantification with PET
• 11:10in an animal without an arterial
• 11:12input function to rely on,
• 11:13it's a bit more difficult.
• 11:16We decided to do it within subject analysis.
• 11:18And so I took rats and we
• 11:21I imaged them at baseline,
• 11:22we stressed them and then imaged them
• 11:24again to see what this would look like.
• 11:26And we actually found similarly
• 11:28the same thing. So we found both.
• 11:30We found a decrease in the striatum
• 11:33and amygdala, hippocampus,
• 11:34as well as a non significant decrease
• 11:37but trending in brain stem and limbic cortex.
• 11:39And when we stratified all of these
• 11:41rats by low anxiety and high anxiety,
• 11:43we found that there was a difference.
• 11:44There was a slightly more of a
• 11:47decrease in the high anxiety group
• 11:49as compared to the low anxiety
• 11:50in most of the regions,
• 11:52although it was not always
• 11:53statistically significant.
• 11:57So this led to this next question,
• 11:59which was, you know,
• 12:00are we catching these animals?
• 12:02Are we catching this too late?
• 12:04You know, maybe this is a,
• 12:05this is a compensatory decrease after
• 12:07an increase and maybe the the knockouts
• 12:10that were done before stress in these
• 12:13preclinical studies were knocking out
• 12:15H stack 6 before it increased and
• 12:17therefore they were seeing this response.
• 12:20And now we're seeing sort of the fallout,
• 12:21which is the a larger swing in the
• 12:24opposite direction because we really
• 12:25were trying to understand, you know,
• 12:28why are we seeing this decrease?
• 12:30So the next study was to do
• 12:32an acute stress study.
• 12:34And so we took the animals,
• 12:35we split them into two groups,
• 12:36again, did the same paradigm,
• 12:38stress versus control,
• 12:39but instead only waited 48 hours before
• 12:42doing behavioral testing and imaging.
• 12:44And as predicted based on the literature,
• 12:47at 48 hours,
• 12:48they do not show a significant
• 12:49difference in the anxiety phenotype.
• 12:51So they really don't look that much
• 12:53different than the controls in the way that
• 12:55they're interacting with their environment.
• 12:56However,
• 12:57they do show significant differences
• 12:59or very close to significant,
• 13:01I should say.
• 13:02They're they're not quite there,
• 13:03but in the acute stress time period.
• 13:07So as you can see,
• 13:09they show almost equivalent brain changes
• 13:11of H .6 to the PTSD animals at 48 hours.
• 13:15So this was really striking to
• 13:17us because it demonstrated to us
• 13:19that before the behavior changes,
• 13:21we are seeing these brain changes
• 13:23in H .6 that are preceding the
• 13:26actual behavior of PTSD like model.
• 13:28And we also did Western blocks which
• 13:31demonstrated that at two days post
• 13:33stress in the prefrontal cortex we
• 13:35were seeing a significant decrease
• 13:37in the glucocorticoid receptor.
• 13:39This was total cell,
• 13:41total tissue glucocorticoid
• 13:43receptor concentration,
• 13:44which I think is a little bit hard
• 13:45to to understand exactly what that
• 13:47means when we're talking about a
• 13:48translocation from the cytoplasm to
• 13:50the nucleus rather than up or down.
• 13:52But I think it was, you know,
• 13:53is it interesting finding to go along
• 13:55with this decrease in HDAC 6 as well.
• 14:00So to change over to humans,
• 14:03this is what we found in the animals.
• 14:04And now we were interested to see does the,
• 14:07do these findings hold in humans
• 14:09with PTSD as they did in rats?
• 14:11Because again,
• 14:12we don't know what the translation
• 14:14is necessarily from rat rats to humans.
• 14:16We know that the rodent models of
• 14:19PTSD are good, but not always great.
• 14:21And we know that the pathophysiology of
• 14:24PTSD in particular as a psycho pathology
• 14:26and as a psychiatric illness is,
• 14:28is not one that is well recapitulated in
• 14:31animal models consistently because of its
• 14:34difficulty to really get to the the human.
• 14:37I think the human nature of the
• 14:39flashbacks and the memories are
• 14:40very difficult to know that we're,
• 14:41we're actually putting that into an animal.
• 14:45And so moving into human work,
• 14:47we, we took a sub,
• 14:50took three groups of humans,
• 14:51healthy controls, trauma,
• 14:53exposed controls and PTSD.
• 14:55They were relatively well matched.
• 14:58There were some slight age differences,
• 14:59but otherwise relatively well matched
• 15:01groups with the exception notably of course,
• 15:04of their scores.
• 15:05So we looked at key PTSD scores that we use
• 15:10particularly in research such as the CAPS 5,
• 15:12the PCL 5 and then we did a number
• 15:14of others and addressed the HAM
• 15:16DMA to better understand their
• 15:18anxiety and depressive phenotype.
• 15:21And when we looked at this,
• 15:25we,
• 15:25So we imaged all of these individuals
• 15:27and found that we did see significant
• 15:30decreases in the PTSD individuals as
• 15:33compared to the healthy controls.
• 15:35But we also saw decrease in
• 15:38the trauma controls,
• 15:39most notably in the dorsal Raphae nucleus.
• 15:41And we have the dorsal Raphae
• 15:43nucleus we know is sort of a,
• 15:45it's a long,
• 15:47a long nuclei across the brain stem.
• 15:49And so this encompasses both the midbrain
• 15:53sort of locus and the ponds locus.
• 15:55And so we for the purposes of
• 15:56quantification of the imaging,
• 15:57we have them separated.
• 15:59But it was notable to us both
• 16:01that there was a decrease which
• 16:03was consistent with the animals,
• 16:05but also that that this was lower
• 16:08in the trauma controls and not just
• 16:12in the PTSD and that there was no
• 16:14difference between the trauma control
• 16:16and the PTSD significant or statistically.
• 16:18Sorry.
• 16:20So going back to our original hypothesis,
• 16:23why are we seeing,
• 16:24you know, this?
• 16:25We originally hypothesize we
• 16:26would see higher HDAC 6.
• 16:28We're now seeing lower HDAC 6.
• 16:31And what what does that mean?
• 16:32And so,
• 16:33you know,
• 16:34we had originally hypothesized
• 16:35that that that increased HDAC 6
• 16:38would relate to increased stress
• 16:40susceptibility and more translocation.
• 16:42But we also have this prior evidence from
• 16:45another excellent resident and physician,
• 16:48scientist Doctor Shivani Bhatt,
• 16:50and with her mentorship under
• 16:53Doctor Cosgrove that looked
• 16:55at some cortisol imaging.
• 16:57And so this was looking at an enzyme
• 16:59that produces cortisol in the brain
• 17:01and they found that this was increased
• 17:03in the brain in PTSD individuals
• 17:05as compared to trauma controls.
• 17:07So you know,
• 17:09there's a,
• 17:10I'm wondering now we're
• 17:11wondering if there's a
• 17:12chance that this is a compensatory
• 17:14response if there is increased cortisol
• 17:17centrally and that therefore the HDAC 6 is,
• 17:20is sort of trying to down regulate that
• 17:23response and decreasing the glucocorticoid
• 17:26receptor translocation into the nucleus.
• 17:29And so, you know, is that is that,
• 17:31is that a possibility?
• 17:33I think we, we don't know yet,
• 17:35but that's, that's sort of one
• 17:38response to this hypothesis.
• 17:40And, and you know,
• 17:41the difference between the trauma
• 17:43control and the PTSDI think one,
• 17:45one note that we're also interested in is,
• 17:48is could this lower H .6 be a
• 17:51trauma marker that's indicating
• 17:53this predisposition for PTSD?
• 17:55You know, we don't we,
• 17:56we know that many people who undergo
• 17:59multiple traumas are more likely after
• 18:01their first traumas or after childhood
• 18:03trauma to acquire PTSD later in life,
• 18:06either from that trauma or
• 18:07from subsequent traumas.
• 18:08And so, you know,
• 18:10is this evidence that this may be one of the
• 18:14changes that is predisposing them to PTSD?
• 18:16Certainly not all individuals.
• 18:17Some individuals,
• 18:18it is their first trauma and
• 18:20only trauma that triggers PTSD,
• 18:22of course.
• 18:23But what you know what,
• 18:25what's happening here?
• 18:25Why are we seeing this change both in
• 18:28the animals at this acute period and in
• 18:30the humans and these trauma controls,
• 18:32as well as in the PTSD individuals?
• 18:34And so I think that's part of an
• 18:37ongoing question that we need more,
• 18:40more studies to better answer.
• 18:41But this was an exciting
• 18:43first step to to understand
• 18:48in summary, you know,
• 18:49we contrary to the hypothesis,
• 18:51we now see lower levels of
• 18:54HDAC 6 both in trauma and in,
• 18:57in following trauma in
• 18:58both humans and in animals.
• 19:00These do we do consider these
• 19:02pretty robust findings given the
• 19:04reproducibility across multiple cohorts
• 19:06of animals within subject and across
• 19:09groups as well as within humans.
• 19:11And then, you know,
• 19:12this would imply that there's a
• 19:14decreased glucocorticoid receptor
• 19:16translocation into the nucleus and,
• 19:19and we have these hypothesis about
• 19:21possibly a compensatory mechanism
• 19:22due to increased central cortisol,
• 19:25but I think more studies are needed
• 19:27to better understand that full system.
• 19:31And with that, I'd like to thank
• 19:32you all for listening. And I'll,
• 19:34I think we have time for questions.
• 19:37So I can take any questions.
• 19:38And of course,
• 19:39thank both Doctor Cosgrove and Dr.
• 19:41Matt Dugante, who's sitting here as well,
• 19:43who's also been a,
• 19:44a foundational mentor to me and has really
• 19:47supervised all of the animal work and,
• 19:50and blended quite a bit of
• 19:51resources from his lab.
• 19:52So we thank him as well.
• 19:54Thank you.
• 19:58Thank you, Tom for that
• 20:00really nice introduction.
• 20:02So I'm I'm excited to be able
• 20:05to talk to all of you about my
• 20:07research trying to understand the
• 20:10role of rare genetic variants
• 20:12in the development of OCD.
• 20:19So I'll start just by describing
• 20:21some of what we already know
• 20:24about the genetic basis of OCD.
• 20:26So firstly, we know that it's
• 20:28moderately to highly heritable.
• 20:31So this means that the proportion
• 20:33of the variants in the trait,
• 20:35basically whether or not someone has OCD,
• 20:38is determined in part by genetic factors,
• 20:41and that heritability is higher for the
• 20:44childhood early onset form of the disorder.
• 20:47We also know that OCD is polygenic,
• 20:51so there's a contribution from
• 20:54estimated hundreds of genes,
• 20:57all that can contribute to OCD etiology,
• 21:00but we don't know what
• 21:02most of those genes are.
• 21:04And that's ultimately what our
• 21:06goal is from this research,
• 21:08is to identify more of those
• 21:10genes that could tell us about
• 21:13the underlying biology and could
• 21:15be potential novel drug targets.
• 21:18The
• 21:18other thing we know is that
• 21:20there's a contribution
• 21:21from many different types
• 21:23of genetic variations.
• 21:25So there's contribution from common
• 21:28variants that are relatively
• 21:30common in the human population.
• 21:32This is what we study with
• 21:35genome wide association studies.
• 21:36There's a contribution from rare
• 21:39inherited variants that are passed
• 21:42along through families and there's
• 21:45a contribution from Genovo variants,
• 21:47which our lab is particularly interested in.
• 21:52So Genovo genetic variants are not
• 21:56passed down from parent to child.
• 21:58They are spontaneous DNA mutations that
• 22:02arise from an error in DNA replication.
• 22:06And we all have a few of these,
• 22:08but they're relatively rare.
• 22:10And because they're so rare,
• 22:13they can be used to statistically implicate
• 22:16genes in the development of a disorder.
• 22:20And our lab was actually able to
• 22:23do this previously by looking at
• 22:26small de Novo variants in OCD.
• 22:30So by small,
• 22:31I mean point mutations and and small
• 22:34insertions or deletions of DNA sequence.
• 22:37And we found an increase in the rate
• 22:40of these small de Novo variants that
• 22:43were likely to damage the protein
• 22:46product of a gene in children
• 22:49with OCD compared to controls,
• 22:51which suggests that this type
• 22:53of variation was playing some
• 22:55role in development of OCD.
• 22:57And we were able to use these de Novo
• 23:00variants to implicate 2 risk genes that
• 23:04are thought to be associated with OCD.
• 23:10So we were interested in using a similar
• 23:13methodology and applying it to other
• 23:17types of de Novo genetic variants
• 23:20and other types of rare variation.
• 23:22So one thing we were interested in
• 23:24looking at was copy number variants.
• 23:26So these are large deletions or
• 23:30duplications of chunks of DNA sequence,
• 23:34so much larger changes than
• 23:36what we were looking at before.
• 23:38And these have been identified
• 23:41in patients with OCD,
• 23:43They've been studied before,
• 23:46but there's not yet a good evidence
• 23:50base showing their association
• 23:52with the development of OCD.
• 23:56So we opted to use our previous data set,
• 24:02whole exome sequencing data in
• 24:06trios with children who had OCD.
• 24:09So these were families where the
• 24:12parents were unaffected and the
• 24:15children have OCD and comparing
• 24:17this to unaffected control families
• 24:20with children who don't have OCD.
• 24:22So we performed quality control
• 24:26and used this data set to identify
• 24:31in silico copy number variants,
• 24:34classify them and do a comparison
• 24:36of the mutation rates.
• 24:41So we did quality control with PCA and
• 24:45made sure the cohorts were ethnically
• 24:47matched and these are the demographics of
• 24:50the samples that passed quality control.
• 24:57And what we found was that rare
• 25:01deletions were increased occurring
• 25:04at both an increased rates and a
• 25:08greater proportion of children with
• 25:11OCD compared to children without.
• 25:14And this effect was particularly
• 25:16marked for de Novo deletions.
• 25:23And looking at some of the more
• 25:26specific features of the de Novo CN BS
• 25:29that we identified in our OCD sample,
• 25:32a few things jump out.
• 25:33The 1st is that a lot of these individuals
• 25:37have Co occurring psychiatric disorder,
• 25:41most notably Tourette's, which we know
• 25:43goes along with OCD quite commonly.
• 25:45So we did a secondary analysis
• 25:48removing the individuals with the
• 25:50Tourette's diagnosis and found
• 25:52that the finding still holds.
• 25:54The other thing to note is that
• 25:57a lot most of the mutations,
• 26:00the copy number variants that we
• 26:04identified in individuals with OCD
• 26:06are predicted to be pathogenic
• 26:09or likely pathogenic,
• 26:10meaning they're disrupting
• 26:12or affecting gene products.
• 26:15And this is in comparison to the
• 26:18control samples where all the
• 26:20CN VS that we identified were
• 26:23not predicted to be pathogenic.
• 26:25So that further suggests that
• 26:27there may be some role for CN VS
• 26:30that are predicted to be damaging
• 26:32in the development of OCD.
• 26:38So what we can say from this finding
• 26:42is that de Novo rare, rare deletions,
• 26:46but primarily de Novo deletions
• 26:48are more common in children
• 26:51with OCD compared to controls.
• 26:53Most of the de Novo CN BS that
• 26:56we identified in our sample are
• 26:58predicted to be pathogenic.
• 27:00And this suggests that de Novo CN
• 27:03BS might play a role in the etiology
• 27:07of OCD and we could use this to
• 27:10help implicate new OCD risk genes.
• 27:13This is a really robust approach
• 27:16that at this point has identified
• 27:19100 some risk genes and autism,
• 27:22and we're hoping that it'll lead
• 27:24to the identification of more risk
• 27:27genes in OCD that could be potential
• 27:29drug targets someday and help us
• 27:31understand the biology of the disorder.
• 27:36So I'd like to end by thanking everyone
• 27:39who was involved in this research and
• 27:43in my clinical and research training,
• 27:46many of whom are are here in the audience.
• 27:48So thank you for your support and
• 27:51for funding sources for the award
• 27:54committee and my wonderful colleagues.
• 28:02Hello, my name is Jay.
• 28:03I'm a PG I3 resident.
• 28:05I'm sorry that I could
• 28:06not be there in person.
• 28:08I'm on my honeymoon now.
• 28:09So so I'll try to be available for
• 28:12questions after this presentation,
• 28:14but I'm sorry that I cannot be
• 28:16be there with you in person.
• 28:18So my presentations on mental health
• 28:21stigma by gender uncondition in
• 28:24rural Uganda and I'm excited to
• 28:26share with you our findings today.
• 28:29So a little bit of background.
• 28:31So mental illness are the leading
• 28:34cause of disability globally and 80%
• 28:36of those with mental illness reside
• 28:38in no and middle income countries
• 28:40as defined by the World Bank.
• 28:43But most of like the resources
• 28:44and most of the research done,
• 28:46mental illness is done in high income
• 28:49countries and a major factor in mental
• 28:52illnesses are mental illness stigma.
• 28:54So it's very prevalent globally and it,
• 28:58you know,
• 28:58it has many downstream effects
• 29:00such as levels of funding
• 29:01available for mental health care,
• 29:03treatment seeking behaviors and
• 29:06treatment outcomes as well.
• 29:10So in terms of characterizing mental
• 29:12illness stigma, as we all know,
• 29:14mental illnesses can be very,
• 29:16it can have very varying presentations.
• 29:19It can be schizophrenia,
• 29:20it can be anxiety,
• 29:21it can be alcohol use disorder.
• 29:23There's many different
• 29:25types of mental illnesses.
• 29:27So there have been studies in high income
• 29:30countries characterizing, you know,
• 29:32how people receive these different diverse,
• 29:35you know, mental illnesses.
• 29:37But there have not been so many studies
• 29:40in low and middle income countries
• 29:43characterizing the differences in how
• 29:45people perceive these different conditions.
• 29:48So in high income countries,
• 29:49the research shows that those whose
• 29:52symptoms align with gender based
• 29:54stereotypes are more susceptible
• 29:56to experiencing stigma.
• 29:58But, you know,
• 29:59those studies,
• 29:59to our knowledge,
• 30:01differentiate mental illness stigma by
• 30:03gender or condition in low income countries,
• 30:06to our knowledge.
• 30:06And that's, and by gender,
• 30:09you know, it means you know,
• 30:10the gender of like the person that's
• 30:13experiencing mental illness and the
• 30:14gender of the person that's that's
• 30:16evaluating or that's endorsing
• 30:18stigmatizing attitudes towards
• 30:19that person with mental illness.
• 30:21So,
• 30:22so both from both perspectives in
• 30:25understanding how people perceive
• 30:28these different mental illnesses
• 30:30are very helpful because then
• 30:33anti stigma interventions can
• 30:35be designed accordingly to that.
• 30:38So now I'm going to talk about
• 30:40methods and you know,
• 30:41I'm going to break this down step by step.
• 30:44So first, you know,
• 30:45we design some vignettes that describes
• 30:47a person with a mental illness.
• 30:49Then we randomly use random
• 30:51sampling methods to select the
• 30:52vignette to read a participant.
• 30:54And then we administered a survey with
• 30:58two with two with two parameters,
• 31:02one's measuring proximal personal stigma
• 31:04and another one measuring personal
• 31:08stigma about the person in the vignette.
• 31:12So for the vignette development,
• 31:15for developing these vignettes,
• 31:17we developed 4 vignettes illustrating
• 31:19alcohol use disorder, anxiety disorder,
• 31:22depression, and schizophrenia.
• 31:24And we created both a male and
• 31:26a female version of those,
• 31:28so you know,
• 31:31111 So each condition had two vignettes,
• 31:331 depicting depicting a man with
• 31:35a vignette and another depicting
• 31:36a woman with a vignette.
• 31:38In the vignettes,
• 31:39depression and schizophrenia were
• 31:41adapted from a study in Western
• 31:43Uganda and vignettes and alcohol use
• 31:46disorder and anxiety were developed
• 31:48utilizing the SM5 criteria and and
• 31:50having an intercultural team as I
• 31:53was involved as well as Ugandan
• 31:56collaborators as well to make sure
• 31:59that it is adaptable and under and
• 32:02understandable to the local context.
• 32:05So this is where we did the study.
• 32:07You can see Puyenda district is
• 32:09highlighted in purple on the map.
• 32:11This is by Lake Choga.
• 32:12It's a very rural district.
• 32:14It's got about four,
• 32:15a little bit over 400,000 people.
• 32:17It's also a very underserved area
• 32:20of Uganda which is a low income
• 32:23country and majority of population
• 32:25are subsistence farmers.
• 32:26There's 45% illiteracy rate above
• 32:2918 years old.
• 32:33So the study procedure,
• 32:34so we selected 20 villages and three
• 32:37sub counties in Vienna district.
• 32:40Each sub county has about 50,000 people.
• 32:42So we have a list of all the
• 32:44villages in these three sub
• 32:46counties and we utilize a number,
• 32:48a random number generator to to pick
• 32:50which villages we're going to do.
• 32:52So each village is numbered
• 32:54and we picked them randomly.
• 32:55And then once we arrived at the village,
• 32:58the community health workers have a
• 33:00registry of all households in the village.
• 33:03And so we again use the random number
• 33:06generator to select households.
• 33:08And once we selected a household,
• 33:10we again use a random number
• 33:12generator to select an adult,
• 33:14defined as 18 years or above
• 33:17in each household to interview.
• 33:19And then once we arrived at the household,
• 33:22we randomly selected the vignette.
• 33:24So there are 8 possible choices
• 33:27also with a random number generator
• 33:30for each participant.
• 33:32And this is a tool that we use
• 33:34to measure the level of stigma
• 33:36is adapted from a doctor Bob
• 33:39Rosenhach studies SO2 batteries.
• 33:41We're measuring a stigma and one
• 33:43is personal acceptance Scale,
• 33:45which measures proximal interpersonal stigma.
• 33:48So what I mean by proximal personal
• 33:51interpersonal stigma is, you know,
• 33:53what would that person do?
• 33:55So would that person be willing
• 33:57to have somebody with mental
• 33:59illness as a neighbor or not?
• 34:01And then we have another scale,
• 34:03which should be named a
• 34:04broad acceptance scale,
• 34:05which measures distal interpersonal stigma.
• 34:08So that's more questions like
• 34:09what should a society do about
• 34:11this person with mental illness?
• 34:16And so going into results.
• 34:18So these are some descriptive statistics.
• 34:20And you can see that we we got a pretty even
• 34:23distribution across all four conditions.
• 34:26And, and you know,
• 34:28we have more females and males, but you know,
• 34:32it's pretty evenly distributed otherwise.
• 34:34And this is the results of the
• 34:37personal Acceptance scale by condition,
• 34:40gender of the vignette and
• 34:41sex of the participant.
• 34:43So higher numbers means greater
• 34:45acceptance or less stigma.
• 34:46So this measure is personal acceptance scale.
• 34:49So so as you can see here,
• 34:52you know, in yellow in the in
• 34:54the bottom is schizophrenia.
• 34:56You know, it's got lower acceptance
• 34:58scores than let's say anxiety overall.
• 35:00And you know,
• 35:01you can also see some gender differences.
• 35:04So, so filled in circles means
• 35:07you know it's a female to female.
• 35:10So you know,
• 35:12both the person being depicted in
• 35:14the vignette is female and the person
• 35:16that is being read to is a female.
• 35:18And hollow circles mean that the
• 35:21person that's being detected is a
• 35:23female or being depicted as female
• 35:25and the person judging is a male.
• 35:27And, you know,
• 35:28likewise for and you can read
• 35:30the legends to to describe the,
• 35:33the the the rest.
• 35:36And this is a broad acceptance
• 35:37scale which had a, you know,
• 35:39somewhat similar story,
• 35:40although with less effect size
• 35:43than personal acceptance scale.
• 35:45So after accounting for multiple testing
• 35:48and model this specification via permutation,
• 35:51have you found significant differences in
• 35:53levels of stigma among the four conditions?
• 35:55For PAS, the P value is .00235
• 35:59and BAS the P value is .04757.
• 36:03So as you can see,
• 36:05the PAS was more had a higher degree
• 36:09of had a lower P value than the BAS.
• 36:12And then we did a pairwise
• 36:14secondary analysis and we found
• 36:16that acceptance differed in among
• 36:18anxiety and schizophrenia according
• 36:19to PAS and BAS significantly.
• 36:24So also we found some differences
• 36:27in acceptances across gender.
• 36:29So,
• 36:30so one thing that we so the PAS
• 36:35the varied across gender combinations
• 36:37for depression with the empirical P
• 36:40value of .017 and we can interpret this
• 36:42result as a reflection of personal
• 36:44acceptance being higher for women with
• 36:47depression than men with depression.
• 36:49If you refer back to our figure and
• 36:51other specific gender effects were
• 36:53not observed for any of the other
• 36:56mental disorders in the PAS or for
• 36:58any of the four disorders on the PAS.
• 37:00So discussion so significant findings.
• 37:03So we found significant differences in
• 37:04the levels of acceptance for depression,
• 37:07anxiety, alcohol use disorder,
• 37:08and schizophrenia after adjusting for
• 37:10the gender of the respondent and gender
• 37:12of the individual depicted in vignette.
• 37:14And schizophrenia was the least
• 37:16accepted in pairwise comparisons.
• 37:18After adjusting for multiple testing
• 37:20found that people with anxiety
• 37:21disorder appear to be more accepted
• 37:24than people with schizophrenia and
• 37:25women with depression were more
• 37:27accepted than men with depression.
• 37:29So compared to existing literature
• 37:31may mean high income countries.
• 37:33You know,
• 37:34our studies backed up the finding that
• 37:37schizophrenia has higher levels of stigma
• 37:39and depression and anxiety predictably.
• 37:41And but contrary to the existing literature
• 37:43that finds the mental illnesses that are
• 37:46more gender typical or more stigmatized,
• 37:48we found the opposite.
• 37:49Like for example,
• 37:50men with depression were were more
• 37:54stigmatized than women with depression.
• 37:57And you know,
• 37:58some other literature suggested
• 38:00substance use disorders are more
• 38:02stigmatized in mental illnesses.
• 38:03So it's also possible that pair wise
• 38:06comparisons between depression and
• 38:08alcohol use disorder and between
• 38:10depression and schizophrenia would
• 38:11have demonstrated significant
• 38:12differences with a larger sample without
• 38:15the Bloemfair or any correction.
• 38:17It did demonstrate significant differences.
• 38:20So strengths of the study were that the
• 38:22measurement of differential levels of
• 38:24stigma based on specific mental illnesses,
• 38:26adjusting for the gender of the
• 38:27respondent and the gender of the
• 38:29individual depicted in the vignette.
• 38:31And this hasn't really been done
• 38:33before in low income country setting.
• 38:35And given the importance of
• 38:37community and family support,
• 38:39especially in low and
• 38:40middle income countries,
• 38:42on outcomes for mental illnesses,
• 38:44the utilization of general population
• 38:48sample is particularly important
• 38:50in some weaknesses of the study.
• 38:51Or that translations can lead
• 38:53to subtle shifts in meaning,
• 38:55possibly affecting the nature
• 38:56of the responses elicited.
• 38:58And you know,
• 38:59it's also vulnerable to
• 39:00social desirability bias,
• 39:01like many surveys are so
• 39:04meaning of the study.
• 39:06Mental illness stigma is a major
• 39:07barrier to treatment and access.
• 39:09But most studies measuring mental
• 39:11illness stigma do not differentiate among
• 39:14different conditions and our study does.
• 39:16And this also in our differential
• 39:18findings also suggest that anti
• 39:20stigma efforts need to be disorder
• 39:23specific and gender specific.
• 39:24And we hope that the static and form
• 39:27the foundation for more targeted anti
• 39:29stigma approaches for mental illness.
• 39:31So there's some references and
• 39:34some acknowledgements below,
• 39:36and I'm happy to take any
• 39:39questions that people have now.