Yale Psychiatry Grand Rounds: May 28, 2021

May 28, 2021

Information

2021 Seymour L. Lustman, MD, PhD, Resident Research Awards

Co-First Place Awards

Emily Olfson, MD, PhD: "Whole-Exome Sequencing in Childhood Anxiety Disorders Identifies Rare De Novo Damaging Coding Variants"

Zachary Harvanek, MD, PhD: "Psychological and Biological Resilience Modulates the Effects of Stress on Epigenetic Aging"

Honorable Mention

Albert Higgins-Chen, MD, PhD: "A Computational Solution for Bolstering Reliability of Epigenetic Clocks: Implications for Clinical Trials and Longitudinal Tracking"
Peter Na, MD, MPH: "Prevalence, Risk and Protective Factors Associated With Suicidal Ideation During the COVID-19 Pandemic in U.S. Military Veterans With Pre-Existing Psychiatric Conditions"
Ryan O'Dell, MD, PhD: "Association of Aβ Deposition and Regional Synaptic Density in Early Alzheimer's Disease: A PET Imaging Study with [11C]UCB-J"

ID6653

To CiteDCA Citation Guide

00:00We have a lot to go through today and
00:02some exciting science to hear from some
00:05wonderful trainees in our department.
00:07I want to welcome you to grand rounds
00:10into the 2021 Seymour Lustman Memorial
00:14Awards in psychiatric research.
00:17This I have to say is one of my favorite
00:20days in the life of our department
00:22and in our grand rounds series.
00:24As we acknowledge the work of trainees
00:26in our department and the research
00:28that they've done, and we also
00:30celebrate the legacy of our department,
00:32the Lastman Awards has been his allotment.
00:35Orders been given since 1973,
00:37and if you look over the list
00:39of past winners.
00:40Who are in an engraved plaque outside
00:42the the auditorium where unfortunately
00:44not able to meet in person today.
00:46It's really an extraordinary list and we have
00:49some new people to add to that plaque today.
00:52I want to thank the
00:54Lustman family Susan Katz,
00:57Jeffrey Lastman,
00:57Seymour Lessmann's children and the
00:59less than Family Foundation who have
01:02generously provided support for
01:03this award for decades now and have
01:06therefore contributed to an enabled.
01:08The history that I referred to.
01:13So see more lost men. Make me you you.
01:17You might not feel,
01:18especially if this is the first
01:19time you've come to the last
01:20minute award ceremony.
01:21You may not know the history of
01:23Seymour last minum less been served
01:25in the army in World War Two,
01:27he obtained his PhD in psychology at
01:29the University of Chicago and then
01:31his MD at the University of Illinois.
01:34Before coming to Yale for his
01:36psychiatry residency in 1955.
01:38During his PhD studies,
01:40before coming to Yale,
01:41he became very interested in the
01:43question of nature versus nurture.
01:45In the words of the day,
01:47we might call it environment versus genetics.
01:51And he he continued with that interest
01:54throughout his clinical and research career.
01:57After completing his psychiatry
01:58residency in his child Fellowship,
02:00he joined the faculty in 1962 and a
02:03grand total of two years later was
02:06promoted to the rank of full professor,
02:08which is a rather impressive
02:10trajectory that speaks, I think,
02:12to how evidenced his his,
02:13his excellence in his contributions
02:15to the department were.
02:17He was a dedicated teacher,
02:19gifted clinician and a very
02:21careful and creative scientist.
02:23One thing he did.
02:25That that story I've heard told many times
02:28this was after the polio was on the wane,
02:31and there were all of these iron lungs.
02:33These big breathing machines that were used,
02:35but it had been used to keep people alive
02:37when they had severe cases of polio,
02:39and they weren't needed anymore,
02:41and lessman repurpose them into
02:43basically laboratories to study to study
02:46children in a controlled environment,
02:48and shows both creativity and
02:50dedication to to advancing the
02:53understanding of children.
02:55And child development.
02:56And that became the touchstone of his career.
02:59He was particularly well known for
03:01working together with other luminaries
03:03of our department of end of our field.
03:05Also let Anna Freud and JoJo Goldstein,
03:08and they wrote a text called Beyond
03:10the best interests of the child,
03:11which is really a landmark in
03:14in the development of child
03:16psychiatry in the last century.
03:19Seymour, less than tragically,
03:20died at the age of I believe,
03:2251 in 1971 in a boating accident,
03:25and our department was robbed of
03:27one of its one of its luminaries.
03:30And shortly thereafter, in 1973,
03:33his family began their support of
03:35this award to honor his legacy and
03:38to honor the causes of science in
03:41the service of great clinical care
03:44that we continue to celebrate.
03:48So, remembering and celebrating
03:50that history of our department
03:51is one reason that I think this
03:52is a particularly special day.
03:54A second reason
03:55is that it's a chance to
03:56honor and celebrate our commitment
03:58to our trainings. I think that, uh.
04:00A particular characteristic of
04:02the department and one that I
04:03think through many of us here,
04:05is that our dedication to supporting
04:07the young people in our field.
04:08The people who are going to bring new,
04:10exciting ideas and move us forward.
04:12And that's what we do today.
04:15And of course,
04:15we also celebrate great science,
04:17and you're going to hear some
04:20wonderful science across a wide range
04:22of clinical translational areas.
04:24In the five presentations today.
04:26And the final thing that we honor in
04:28this in this grand rounds is mentorship.
04:31The you know, bringing new,
04:33bringing new scientists into the field,
04:36training new clinicians,
04:37and advancing the careers of
04:38those who are going to lead us
04:40forward in the coming decades,
04:42only happens with the dedication of
04:44mentors who are willing to give of
04:46their time their energy and their
04:48caring to the to the young people
04:51who are entering our field and
04:52and so each of our honorees today
04:55will be introduced very briefly.
04:57Because of our schedule,
04:58but very importantly by mentor
05:00who they've selected and who's
05:01been important to them and guiding
05:04their work and and in addition to
05:06honoring the award is we want to,
05:07we want to honor their mentors.
05:09Thank you.
05:09Thank you to those mentors for
05:10being with us today.
05:13The last man selection committee,
05:15who I really want to thank,
05:17consists of my Co chair,
05:18young Sunchoke, Kristen Brennan,
05:20Marina Picciotto, Khushoo,
05:22Mark Potenze, Tom Fernandez,
05:24Jerry Santa Cora with the support in
05:26the background from John Crystal.
05:28So I want to thank them for the
05:29time that went into this selection.
05:31We had an unusually difficult job this year.
05:34We had really a an unusually
05:36large group of really excellent
05:38presentations and we're able to
05:40honor five of them today too with
05:43first price first place awards.
05:45And three with one runner up
05:46awards and we'll hear brief
05:47presentations from each of them.
05:50But the last thing I want to say
05:51in introducing here is you
05:52know a bit of a poignant note.
05:54It's bittersweet to me to introduce this
05:58award today and to manage these ceremonies,
06:02because that's previously been done
06:04by one of my mentors, Bob Malison,
06:06who shepherded this process for the
06:09last 20 years and was taken from us.
06:13Like Seymour last man far
06:15too soon last summer.
06:17And so I I regret that Bob is not
06:20with us today and I honor his
06:22memory in this in this presentation.
06:27So with that introduction, let's
06:30move on. We have 5 great talks to
06:33here today and 1st is by ARCO.
06:35First place winner Zach Harvin.
06:37And I'm going to invite his mentor Riggi
06:40to Sinha to give a brief introduction.
06:42Oh, I'm sorry.
06:43Just one brigitta sorry.
06:44One logistical thing which is about
06:47question since we do have five talks,
06:50we're going to go through today.
06:51It's going to be a little tight
06:52so we're going to limit it to one
06:54or two questions after the longer
06:55Co first place talks and we're not
06:57going to be able to have questions
06:58after the shorter runner up talks.
07:00If we stayed remarkably on
07:02time and have time at the end,
07:04then we can perhaps have a little
07:05time for questions and discussion
07:07for any of the presenters at
07:08the end if time permits.
07:09So with that,
07:10Regina, please.
07:12Thank you Chris. It's my real pleasure.
07:16An honor to introduce Doctor Zachary.
07:18Have our neck and congratulations Zach.
07:22Let me give you a little quick background.
07:24Zach grew up in Boulder, Co and attended Duke
07:28University for undergraduate work, where
07:30he studied biomedical engineering
07:32and biology and then became
07:34interested in the biology of aging.
07:36He went on to the University of
07:39Michigan for his MD and pH D.
07:41His dissertation was focused
07:43on neurobiological mechanisms
07:45through which social stressors
07:47influenced aging and fruit flies.
07:50That was really fruitful.
07:51It led to four top notch
07:54publications in science,
07:56nature, ecology and so on.
07:58And then after returning to medical school,
08:00he developed an interest in
08:03psychiatry and the mechanisms through
08:05which stress and mental illness
08:07influence physical health and aging.
08:09He came to Yale and we were thrilled
08:12to have him and has worked with
08:15myself at the Yale Stress Center
08:16as well as with Doctor Kasshu.
08:19Really in, I guess,
08:21very apropos for this award.
08:23An in the legacy of Seymour Lessman,
08:25a sort of bringing nature
08:27and nurture together,
08:28looking at epigenetic mechanisms
08:31by which stress may influence
08:33the process of aging.
08:34He's also collaborating with the sickle
08:36cell program to examine psychological
08:39resilience influences on pain,
08:41an overall health.
08:42It's been a real pleasure
08:44for Doctor Kosu and myself to work closely
08:47with Zach. He's been wonderful.
08:49His optimism and positive
08:50energy and an just burst of new
08:53ideas has been very refreshing,
08:55and so I'm thrilled to.
09:00Congratulate him and would invite
09:02you to join me in in wishing him and
09:06in hearing what he has to say. Zach
09:11thank you for that overly
09:13kind introduction for beta.
09:18So, uh, today I'll be talking to
09:20you about how psychological and
09:21biological resilience modulate the
09:23effects of stress on epigenetic aging.
09:26Next slide. 1st, I have no relevant
09:30disclosures or conflicts of interest,
09:32but now, as Regina mentioned before,
09:34coming to GAIL, I studied the mechanisms
09:37through which social stressors
09:39regulate aging and intra Sofala,
09:41and I'm not going to bore you
09:42with talk about fruit flies.
09:43But fundamentally what we found was
09:45that perception of the opposite sex,
09:48basically a social stress led to changes
09:51in neuropeptide ergic signaling,
09:53downstream Physiology,
09:54and ultimately accelerated aging and death.
09:57However, these negative outcomes could be
09:59minimized by specific protective factors.
10:01In this case it was successful
10:03made next slide.
10:08After finishing my PhD in
10:09returning to medical school,
10:10I learned what psychiatry and I suspect
10:12most people here have known for a long
10:15time that patients with serious mental
10:17illness die earlier than those without.
10:19The plot on the left is from a study
10:21out of Denmark demonstrating that
10:22for pretty much all causes of death
10:24and mortality rates significantly
10:26higher in patients with mood disorders
10:28compared to healthy controls,
10:30and they've gone to demonstrate similar
10:32findings for other psychiatric disorders.
10:34Now, notably,
10:34this isn't just true for things we
10:36might expect to be psychiatric related.
10:38Also infections, cardiovascular disease,
10:40other similar costs.
10:42And this is a pattern similar
10:43to what we see as people age.
10:45You are risk for many different diseases
10:47increases as we get older and on the
10:49right is a data from a meta analysis
10:51showing that across a wide range of
10:53different categories of mental disorders,
10:56patients tend to have shorter TILA
10:58mirrors than healthy controls and
10:59shorten telem ears are thought to be
11:01related to accelerated rates of aging.
11:03Next slide.
11:06Now one uncertain thing about our
11:08mental health diagnostics is that
11:10the difference between pathologic and
11:12non pathologic isn't always clear.
11:14Other researches has shown that
11:16certain stressors,
11:16even in the absence of a diagnosed
11:19mental illness,
11:19can cause similar patterns
11:21of accelerated aging.
11:22A range of studies have examined
11:24physical health outcomes and
11:25stealing your length associated with
11:27stressors like early life adversity,
11:29associate economic status, discrimination,
11:31or even medical internship.
11:33The plot here is from the intern
11:35Health study,
11:35which is actually being run by a yell
11:37cyka lump doctor Sen and shows the
11:39more hours per week into his work.
11:41The more their tillers,
11:42short and over the course of that year.
11:44Now this idea brought me back to my PhD work.
11:47If a stress like this can
11:49cause accelerated aging,
11:50we should be able to identify the
11:51physiologic pathways to which is.
11:53Happening and hopefully we can identify
11:55ways to protect against next slide.
11:58And while psychiatric diagnosis
12:00can be unclear,
12:01the term stress can times be equally vague.
12:03So I want to provide a
12:05definition that can be helped.
12:06We can define stress as a process,
12:08and it's the process of identifying,
12:10interpreting, responding to,
12:11and adapting to potential
12:13threats or challenges.
12:15Now first it involves individuals
12:17identifying these stressors,
12:18and second,
12:19it involves their interpretation of
12:21the stressor which could include both
12:23societal and individual factors.
12:24And this interpretation could lead to
12:27either amplifying or suppressing the stress.
12:29Depending on these factors,
12:31next,
12:31there's an acute response and
12:32it can be behavioral but also
12:34physiological heart rate might elevate.
12:36Specific circuits might fire
12:38changes might occur in cortisol
12:39or metabolic pathways,
12:41and ultimately these short term
12:43responses can lead to long term effects.
12:47Next slide.
12:49Now,
12:49using this definition of stress,
12:51we can return to this overall hypothesis
12:53that stress accelerates aging via
12:56physiologic changes moderated by
12:57protective factors in a systematic way.
13:00First,
13:00we can ask whether cumulative
13:02lifetime stress leads to
13:03accelerated aging as a long term consequence
13:05in an otherwise healthy Community population.
13:08Even in the absence of diagnosis,
13:09mental illness. If so, we can ask whether
13:13stress related Physiology like changes
13:15in the HPA axis and insulin signaling
13:18are also related to accelerated aging.
13:21And finally, we can ask if an individual
13:24psychological resilience can serve as a
13:27protective factor in these relationships.
13:28Next slide. Now to measure aging,
13:31a lot of the previous studies I've
13:33mentioned utilized stealing their life,
13:35particularly in young populations.
13:37We we don't have more obvious indications
13:40of aging like frailty or death,
13:43but telomere length is really only weakly
13:45correlated to aging related outcomes.
13:47Might care about like morbidity
13:49and mortality.
13:50Luckily, recent advances in epigenetics have
13:52led to the development of epigenetic clocks,
13:55and these are based on
13:57DNA methylation patterns,
13:58and these clocks have really been a leap
14:00forward in terms of predictions of frailty,
14:02morbidity and mortality when
14:04compared to tumor based studies.
14:06Here we're going to utilize
14:08one of these epigenetic clocks,
14:09rimage, to address our hypothesis,
14:11but I think we might actually hear more
14:13about how we can continue to improve our
14:15measures of aging from Albert Higgins,
14:17Chanina.
14:17Later presentation,
14:18next slide.
14:22Our study population was a group of 444
14:25individuals between the ages of 18 and 50,
14:27taking no prescription medications with
14:29no chronic health issues and with no DSM.
14:32Four diagnosis of their
14:34indicati use disorder.
14:35So healthy in this group,
14:37we obtained survey measurements of
14:39stress and psychological resilience,
14:41as well as physiological epigeic measure.
14:44Next slide. Now in this population
14:47we see a positive correlation between
14:49cumulative stress levels as measured by
14:52interview and grammage acceleration.
14:53I want to take a moment to discuss
14:55these measures because we're going
14:56to be using them throughout the talk.
14:58The cumulative adversity index
14:59or CE AI is on the X axis,
15:02and it's an interview based measure of
15:04cumulative stress taking into account
15:06of a multitude of different types of
15:08stressors across the lifespan and
15:09higher lifetime stress leads to higher.
15:11See AI score.
15:12You can see that see AI is positively
15:14correlated with brimmage acceleration,
15:17which fundamentally represents the
15:19difference between individuals.
15:21Epigenetic age and chronological age
15:23with a positive number indicating
15:25that they are biologically older than
15:27their chronological age would suggest.
15:29Next slide.
15:31The one potential explanation for these
15:33findings is that stress might result
15:35in substance use, behavior changes,
15:36or be due to different demographic factors.
15:39But even when we take into account
15:42a smoking BMI, alcohol use, race,
15:45sex, marital status, income,
15:47education,
15:48when we do that via multivariate
15:51linear regression,
15:52there's still a significant independent
15:54effective stress on grammage acceleration.
15:57Now, except where I mentioned otherwise,
15:58all the rest of our analysis will
16:00account for all of these covariates,
16:02and notably,
16:03these covers are related to to aging,
16:06as demonstrated by the large change in
16:09the R-squared you get from the simple
16:11going from the simple relationship
16:13on the plot to the full models R ^2.
16:15Next slide.
16:17So going back to our hypothesis,
16:19cumulative stress,
16:19even in the absence of mental illness,
16:22is associated with accelerated aging.
16:24Even were accounting for all of
16:26those covariates.
16:27So next we decided to look at measures
16:29of stress related Physiology,
16:30including both metabolic and hormonal
16:33factors,
16:33and see if they are also related
16:36to accelerated biological aging.
16:37Next slide.
16:39So we first assess the relationship
16:41between grim age acceleration in
16:43HP I8HP axis via the cortisol.
16:45The ACTH ratio,
16:46which is a measure of adrenal sensitivity.
16:49Now in this plot you can see a
16:51significant negative correlation
16:52between adrenal sensitivity on the X
16:54axis and grim age acceleration on the Y axis,
16:57But this relationship becomes nonsignificant
16:59when we account for covariates.
17:01This does seem to be appeared to be.
17:02This appears to be driven in part by a
17:05differential responses in men and women's.
17:07When we remove sex is a covariant that.
17:09Their relationship is once again significant.
17:12Next slide.
17:14We next examined insulin resistance,
17:16which is another physiologic process,
17:18are related to stress and to do
17:20this we use the measurement Houma,
17:22which is calculated based on
17:24individuals glucose, insulin.
17:25Now in this plot you can see that Houma,
17:28which increases as an individual's
17:30insulin resistance increases,
17:32is positively correlated
17:33with cream age acceleration.
17:35Now, unlike the cortisol ACTH ratio,
17:37this relationship remains significant
17:39after accounting for ARCO very next slide.
17:43So thus far we've identified at least
17:45one potential physiologic mechanism
17:47through which stress might influence aging
17:49through changes in insulin resistance,
17:51as well as a potentially more complex
17:53story with adrenal sensitivity in sex.
17:55It's also worth noting that while
17:57accounting for both of these,
17:58we continue to see an independent
18:01effect of stress on aging as well.
18:04Now, as I mentioned earlier,
18:05we don't just want to find
18:07ways how we're aging faster,
18:08but ways to protect against it,
18:10and one potential counter distress
18:12would be psychological resilience.
18:14So we next asked whether characteristics
18:16such as emotion regulation and self control
18:18might alter the relationship between stress,
18:20Physiology, and aging.
18:23Next slide.
18:25Well when we assess self control we
18:27see that it moderates the relationship
18:29between stress and insulin resistance.
18:31In this plot you can see three lines
18:33representing the relationship between
18:35stress on the X axis in Houma on the
18:37Y axis for individuals with good,
18:39fair or poor self control.
18:41You'll notice that the individual
18:43good self control.
18:44There's little effect of stress
18:46on insulin resistance,
18:47but in those with poor self control,
18:49there's a large effect,
18:50and this moderating effective
18:52self control is significant.
18:54Even we were accounting for covariance.
18:56Now one cover it. I do want to.
18:59A1 covariate.
19:00I'd like to point out there is BMI.
19:04Hey,
19:04well BMI is related to both
19:06stress and insulin resistance.
19:08I want to emphasize that this
19:09relationship between stress,
19:10self control and insulin resistance
19:12is still significant after accounting
19:14for BMI and that self control is
19:17actually specifically moderating
19:18the relationship between stress and
19:20insulin resistance, not stress and BMI.
19:24Next slide.
19:25So now we've identified at least
19:27one psychological resilience factor,
19:29self control that can influence stress
19:32related Physiology and thus aging.
19:34But it was striking to us that there
19:36still remains a significant independent
19:38effects of stress on grammage,
19:39so we access with their other
19:41psychological resilience factors.
19:42Might moderate this seemingly
19:44independent effective stress on H.
19:46Excite
19:49so next we asked whether emotion regulation
19:51might be important for this relationship.
19:54When we examine the effects of emotion
19:56regulation on the relationship between
19:58stress and grammage acceleration,
19:59we see a strong moderating effect.
20:02As you can see in the plot.
20:04People with better emotion regulation
20:06as represented by the blue line leads
20:09have blunted relationship between
20:10stress and grammage acceleration,
20:12whereas poor emotion regulation is
20:14represented by the red line amplifies
20:17that relationship. Next slide.
20:20So going back to our model,
20:22we can think of stress is directly
20:24impacting age acceleration in a fashion
20:26that's moderated by emotion regulation.
20:28And after adding emotion regulation,
20:30stress does continue to impact aging
20:32through elevated insulin resistance,
20:33which again is influenced by self control.
20:36Next slide.
20:38So to bring these results together,
20:40we wanted to compare the
20:43contributions of stress,
20:44emotion regulation and insulin
20:46resistance to aging in the context
20:49of other more familiar variables.
20:51To do this,
20:52we used estimated marginal
20:53means in the linear model,
20:54incorporating all of our covariates are
20:57stress related Physiology factors and
20:59our psychological resilience factors.
21:01And when we do this,
21:02we see that stress continues to have a
21:05significant relationship to grammage.
21:06That's moderated by emotion regulation.
21:08And it's worth noting that when we assess
21:11our model at poor emotion regulation.
21:13And there's a highly significant
21:15effect of stress on crymych.
21:17In these individuals, stress alone,
21:19independent of our covariates,
21:21has a strong impact on Grim Age's BMI.
21:25However,
21:26when we assess our models in those
21:27with good emotional regulation,
21:29this relationship becomes
21:31entirely nonsignificant.
21:32Insulin resistance,
21:33which, as we've shown,
21:35is related to stress via self control,
21:36predicts a further increase in
21:39inflammation cellarage next slide.
21:43So in summary, today I've shown you that
21:45cumulative stress predicts biological
21:47aging is measured by cream age,
21:49and this is not accounted for by
21:52demographic or behavioral covariates.
21:54We see that these interactions are at part
21:56mediated through insulin resistance and that
21:58adrenal sensitivity may also play a role.
22:01Remarkably, these interactions are highly
22:03dependent on psychological resilience.
22:05Factors with strong self control
22:07blunting the relationship between
22:08stress and insulin resistance and
22:11strong emotion regulation dampening the
22:13direct effects of stress on scrimmage.
22:15Next slide. So looking forward,
22:18I would like to use the theoretical
22:20model we built the highlight potential,
22:22future directions,
22:23and possible interventions that
22:24could decrease age,
22:25acceleration in highly stressed populations.
22:28Looking at our biological factors,
22:30an obvious place to intervene is
22:33on insulin resistance.
22:34Metformin is actually being investigated
22:36as an anti-aging broke now is part of
22:39the team trial in future work could
22:40determine if it's effective specifically
22:43in highly stressed populations.
22:44Further studies might also clarify
22:46both the rollup adrenal sensitivity,
22:48but also potentially new neural for
22:50modal or cellular pathways that
22:52mediate this seemingly independent
22:54relationship between stress and aging,
22:56as well as the mechanisms through
22:58which emotion regulation is
23:00moderating this relationship.
23:01There's also the potential for
23:03psychotherapeutic interventions that
23:05prove psychological resilience to
23:06decrease the effects of stress on aging.
23:08For example,
23:09there's evidence that mindfulness based
23:11interventions may improve emotion right now.
23:14And finally we can work for social changes
23:17to decrease environmental stressors.
23:19Societal changes that address poverty,
23:21racism,
23:22and other sources of trauma could
23:24ultimately lead to decreases in
23:26lifetime stress and improvements
23:27in overall health and aging.
23:29And ultimately,
23:30this work could be extended beyond the
23:32healthy population to other groups,
23:34such as those with serious mental
23:36illness in whom stress and adversity are
23:39obviously a significant risk factor,
23:41and that might allow us to address that
23:43mortality gap I mentioned earlier.
23:45Next slide.
23:48So finally I just like to thank
23:49the last Min family and the Lessman
23:51Foundation and the selection Committee
23:53for giving me the opportunity to talk
23:54to you about my work today. My mentors,
23:57including Ira Cheetos and Hypo Shoe,
23:59as well as neofolk woman who helped
24:01tremendously with stats and Albert
24:03Higgins Chen who provided a lot of fruit.
24:05Early guidance on using aperture that clocks.
24:08But also like to thank the yell at
24:10RTP and residency and our funding,
24:11I'm happy to take any questions.
24:18Create. Thank you Zack,
24:20and I applaud both the quality of
24:22your science and the quality
24:23of your time control.
24:24That was 14 minutes 57 seconds,
24:26which is about as spot on
24:28as I've ever seen.
24:30We do have time for a question or two
24:33before moving on to our next presentation.
24:37But how am I going to see if
24:38people are asking questions?
24:39Please raise your hand, use the zoom.
24:44Button to raise your hand. If you
24:45have any questions for Zach. Debbie
24:49I I just want to say
24:51that was extremely clear.
24:53An in the world of epigenetics.
24:55I'm practically layperson Anzac.
24:57You made this absolutely understandable
24:59an as a proponent of psychotherapy,
25:01I'd love to see how that fit in,
25:03and I found that this is the kind
25:05of research that our department
25:06is very proud to sponsor.
25:08So well done and well presented.
25:09Thank you.
25:12Thank you and I am I.
25:15I'm looking forward to looking into
25:17these sort of psychotherapeutic
25:18interventions as to how.
25:21We can use psychotherapeutic
25:23interventions too.
25:24Improve both physical health,
25:25as in addition to mental health.
25:36OK. Seeing no further questions right now,
25:39so we'll go on to our next
25:41presentation and perhaps have a
25:42little time for discussion at the end.
25:44So our second Co first place winner of
25:47the last minute work is Emily Olson,
25:50and to invite her I'm sorry to introduce her.
25:53I'm going to remember Tom Fernandez.
25:57Good morning everyone. I'm so
25:58happy for all the the Lessmann
26:00award winners this
26:01year. So my Congrats to
26:02you all. I'm in especially
26:04happy to introduce Doctor Emily often.
26:09There's a little bit of background.
26:10Emily earned her MD and PhD in Human
26:14and statistical genetics in 2016
26:17from Washington University
26:18in Saint Louis. We're
26:20very fortunate that that Emily
26:23matched into our Solnit integrated
26:24training program at that time,
26:26and since then I have to say she
26:29is proven on every level to be
26:32really a model clinician scientist.
26:34She's been incredibly productive
26:36with research during residency.
26:39She's leading several
26:40gene discovery projects,
26:41including the one you'll hear about today,
26:44but also others,
26:45but I hope you'll hear about in the future,
26:47and those include projects discovering
26:50new risk, genes for hair pulling,
26:52and skin picking disorders.
26:54And ADHD. And just in summary,
26:57you know Emily continues to amaze me with
27:00their ongoing research accomplishments.
27:02Despite her busy clinical schedule.
27:04And I should also mention
27:05a busy family schedule.
27:07Emily and her husband have welcomed
27:082 new additions to their family
27:11during her training and what a way to
27:14welcome me back from maternity leave.
27:16With this award today.
27:19I am certain that Emily, as a researcher,
27:22will continue to advance the field of
27:24psychiatric genetics for years to come,
27:26and I really look forward to
27:27continuing to work with her as a
27:29clinical and research colleague.
27:31So thank you Emily. The floor is yours.
27:36Thank you Tom for that very
27:38kind introduction slide.
27:43So I don't have any disclosures today, fine.
27:47So before I get started, I just wanted
27:50to thank the Seymour Lessman award,
27:52and although I never had the chance to meet
27:54Doctor Glassman from reading about him,
27:57I feel that his legacy has really
27:59influenced my training here at Yale.
28:01And I thought I would just
28:03highlight this quote written by the
28:05namesake of the residency program.
28:07I'm in Doctor Schoolnet,
28:08and so he writes in a scholarly
28:11and courageous way.
28:12Dr Lessman repeatedly wrote about the
28:15importance of basic research and spoke out.
28:17For conditions that would promote
28:19opportunities for young investigators to
28:21develop their interests and capacities,
28:24and I'm so grateful to doctor
28:26Lessman doctor Solnit,
28:28my mentors and the many others
28:30who paved the way for me to be
28:32able to work on the research.
28:34Then going to present with
28:34you to you today slide.
28:38So today in the next I
28:40guess 14 minutes or so,
28:42I'm going to talk to you a little bit
28:44about our genomics work of childhood,
28:46anxiety disorders,
28:49and this makes up the most common class
28:51of childhood psychiatric conditions.
28:53And for a long time we've known that
28:55genetic factors are important than
28:57we know this from family studies,
28:58and we know this from twin studies.
29:00And he studies show us that there
29:02is a genetic overlap between
29:04different anxiety disorders and
29:06that the contribution of genetic
29:08factors to anxiety may change
29:09over the course of development.
29:11And specifically,
29:12there's some evidence there's a.
29:15There's a larger genetic contribution to
29:18anxiety that develops in early childhood,
29:21and so this highlights the discovery
29:24potential of genomic investigations that
29:26focus on childhood anxiety disorders slide.
29:31And so we know that genetic
29:33factors are important,
29:34but something that's been harder
29:36for scientists until recently
29:38is finding specific risk genes.
29:40And when we think about
29:42identifying druggable targets,
29:43this process of finding risk
29:45streams is really important.
29:46And it's only been in the
29:48last five years or so.
29:50With Genome wide association studies
29:52that a few common variants have been
29:54associated with anxiety disorders and
29:57actually the largest of these studies
29:59was led by Daniel Levy Angelica learner.
30:01Here at Yale.
30:03But in addition to common variance,
30:05it's also likely that rare variants
30:08influence the risk of anxiety disorders,
30:11and to study these we need
30:15DNA sequencing studies slide.
30:18And one approach that's been
30:19especially fruitful in the field of
30:22child psychiatry is DNA sequencing.
30:24Studies of parent child trios,
30:26where the child is impacted by the disorder.
30:29So since all of us inherit half of our DNA,
30:32in theory from our parents,
30:34this process can allow us to identify
30:37rare variants associated with
30:39the condition that are inherited,
30:41but also new or DENOVO mutations
30:44that are specific only found
30:47in the child and not found.
30:48In the parents.
30:49And all of us have about 50 to 100
30:53knew or de Novo mutations.
30:55And when these occur within genes,
30:58they can actually impact the resulting
31:01protein function. Anhava impact
31:03on brain function as well slide.
31:07And so this approach of sequencing parent,
31:10child trios an looking for these de Novo
31:12variants in order to find risk genes was
31:15initially pioneered in the field of autism.
31:18In the first study,
31:19only had about 200 trios and they were able
31:23to find a high confidence Christine SCN,
31:252A, which is now continues to be one of
31:28the most well studied risk genes for autism.
31:31But since that time,
31:33now they've sequenced thousands of
31:35it treos an I'm highlighting here.
31:37A recent paper where they've now found over
31:39100 high confidence risk genes for autism.
31:42Slide.
31:44And this is important because these risk
31:47genes are already impacting clinical care.
31:50So for families just knowing why
31:53their child has autism is important,
31:56understanding the likelihood of other
31:58family members being impacted and some
32:01of these risk genes are associated
32:03with other medical comorbidities
32:05that impact clinical care as well,
32:07and so this approach was pioneered in autism,
32:11but more recently it's been shown.
32:14To have discovery potential and several
32:18other psychiatric conditions slide.
32:20And so here I'm just highlighting
32:22two papers led by my mentor Tom,
32:24that use this approach to find risk genes,
32:26interet disorder and OC D sign.
32:30And so our goal really was trying
32:32to use this approach to see if we
32:35could similarly find risk genes
32:37in childhood anxiety disorders.
32:39So we collaborated with the program for
32:41Anxiety disorders at the Child Study Center,
32:44and I want to give a big thank
32:45you to Wendy Silverman.
32:47Annelie Liebowitz,
32:49who let our recruitment and clinical
32:51assessments and gave me the opportunity
32:53to work on this project.
32:56So we recruited children who were presenting
32:58with a primary concern of anxiety.
33:01In both of their parents,
33:02we collected saliva for DNA analysis
33:05and all families completed the aidas.
33:08The anxiety disorder interview schedule
33:11that assesses for anxiety disorders
33:14and commonly Co occurring conditions.
33:17We then conducted high coverage
33:20whole exome sequencing of at 76
33:23parent child trios with anxiety,
33:25and we compared this to 225 controls
33:29and we did a variety of quality
33:31control checks on our sequencing data.
33:33And we ended up comparing 65 trios to
33:38222 previously sequence control trios.
33:41Next slide.
33:44So here are the characteristics of the
33:4768 children with anxiety disorders that
33:49we ended up including in our Dinovo
33:52analysis and what I'm highlighting here
33:54in the red box is that many of these
33:57children met criteria for several.
34:00Anxiety disorders and this is really
34:03typical of clinical samples and anxiety.
34:05So the most common disorders were
34:08generalized anxiety disorder,
34:09social phobia,
34:11separation,
34:12anxiety disorder and specific phobia slide.
34:16And in our genomic analysis,
34:18we focused on rare de Novo variants
34:21that were thought to influence
34:23the coding region of genes,
34:25and our hypothesis was based on
34:27studies of other neuro psychiatric
34:29conditions and that we thought we
34:31would find an enrichment of these
34:34Sonoma de Novo damaging mutations
34:36in cases versus controls slide.
34:43And So what we found here
34:45what I'm showing here in red.
34:48Are the anxiety cases an in blue?
34:50Are the controls and I'm showing you
34:52that there is an enrichment of these
34:55damaging de Novo mutations and so
34:57this shows for the first time that
34:59this approach of focusing on de Novo
35:02variants in anxiety has the potential
35:04to identify risk genes and these
35:07damaging variants that are enriched
35:09in cases compared to the controls are
35:12thought to alter protein functions.
35:14So specifically here we're
35:16focusing on damaging variance.
35:18That are likely Jinja struct?
35:20If so, these may introduce a stop
35:23codon early in the gene cause a
35:25frameshift insertion or deletion
35:28or alter a critical splice site.
35:31We also included missense variants
35:33that may change in amino acid that is
35:37predicted to be damaging of the protein.
35:40Uhm?
35:41So.
35:41I guess I just want to highlight
35:43that this was very exciting,
35:46that even for this common class of
35:48conditions for anxiety disorders,
35:50we still see this enrichment
35:52of de Novo variance slide.
35:57And what we can do is we can look at
36:00the list of genes that have damaging
36:02mutations in these anxiety cases and
36:05see if they overlap with risk genes
36:07for other nuro psychiatric conditions.
36:10And I'm highlighting here the
36:11two dream jeans that did so.
36:13The first gene CAC N A1A in codes of
36:16voltage gated calcium channel and
36:18this has been identified as a risk
36:21gene for developmental disorders
36:23in denovo sequencing studies as
36:25well as epileptic encephalopathies.
36:28The second gene is a regulatory
36:32subunit of protein phosphatase 2A,
36:35and this has been associated with
36:38developmental disorders as well
36:40as intellectual disability slide.
36:45But here in our cohort we're finding
36:48damaging mutations in these genes
36:50and individuals who have anxiety.
36:52They don't have any known history of
36:55neurologic or neurodevelopmental conditions,
36:57and so this really gets at this
36:59idea of Pleo tropi wear jeans with
37:01damaging variants may lead to different
37:03clinical manifestations in different
37:05individuals and this is something
37:07that we're continuing to explore.
37:11Slide.
37:12So we can also use this list of
37:15genes with damaging mutations to
37:17conduct exploratory pathway analysis
37:19by looking at whether these genes
37:22cluster in certain pathways more
37:24than might be expected by chance.
37:26And here I'm showing all of the gene
37:29ontology based sets that have a Q
37:32value less than .05 and the darker
37:34red indicates more significance and
37:36the bigger circle indicates that
37:38more genes are contributing and you
37:40can see here that the top pathway,
37:43which is the darkest red in terms
37:45of significance is glutamatergic
37:46synapse and so this is kind of
37:49consistent with the potential role
37:51of glutamate neurotransmission in
37:53the development of anxiety.
37:57Uhm?
37:58And so this further highlights the
38:02significant discovery potential of
38:05using this approach to understand the
38:09pathways involved in anxiety slide.
38:12So at the beginning of this talk,
38:14I discussed how this approach of
38:16sequencing parent child trios had
38:17led to the discovery of risk genes,
38:19first in autism,
38:21and now many other psychiatric conditions.
38:24Sign.
38:26And today I'm showed you new
38:29evidence that this approach also
38:31has significant discovery potential
38:33in childhood anxiety conditions.
38:36And as Tom mentioned,
38:38we also have promising data looking at ADHD,
38:43trichotillomania and excoriation
38:44disorder as well,
38:45and it's likely that many other
38:48psychiatric conditions could
38:49benefit from this approach for
38:51finding risk genes side.
38:54So in terms of next steps,
38:56given our promising data,
38:58we're continuing to recruit and
39:00sequence parent child trios to
39:02find high confidence risk genes.
39:05As I mentioned previously,
39:06usually studies have needed about a
39:09few 100 trios to find these first high
39:13competence risk genes due to rare variants.
39:15And then I also want to highlight that
39:20you know my talk today focused really
39:22on the process of finding risk genes,
39:24and I think it's important to highlight
39:26that that's really just a first step.
39:28It's an important first step,
39:29but once we find these risk genes
39:32understanding the pathways that are involved,
39:34the mechanisms for which they
39:36contribute to anxiety and other
39:38psychiatric conditions is
39:39really a critical next step.
39:41In turn, when we think of
39:44developing better treatments.
39:45Sign. So with that,
39:48I first want to thank all of the family
39:50members who participated in the study.
39:53It wouldn't have been possible without them.
39:55I want to thank my mentor,
39:58Tom Fernandez, who's been
40:00incredibly supportive and generous,
40:02and I've just learned so much
40:04working in his lab and I'm looking
40:06forward to continuing to work on
40:08this and other projects slide.
40:10I also want to take Wendy Silverman Eli
40:13Lebowitz for giving me the opportunity
40:15to work on this project and for leading
40:18our recruitment and clinical assessments.
40:20I also want to thank Michael Block.
40:23He wasn't directly involved in this
40:25project but has mentored me on several
40:28projects during my time in residency slide.
40:30And I want to thank everyone who's part
40:33of all their groups have contributed
40:35to this Ain other projects that
40:37neurogenetics group here at Yale
40:39the Psychiatry residency program,
40:41the NRT PHE,
40:42and especially this moment program.
40:44The work I presented today was funded by
40:47the Yale Child Study Center and the NIH.
40:50I also want to give a big thank you
40:53for to the Seaman Lessman award in
40:56the selection committee as well.
40:58Fine.
40:58And I want to thank this is my
41:01village so all my family and friends.
41:04These are my Co residents both
41:06in the adult program.
41:07The sole net program, my parents,
41:09my sister, my husband and I
41:12couldn't not mention my two kiddos.
41:15So next slide.
41:16So with that,
41:18I'm happy to take any questions.
41:22I guess I'm only allowed a few questions.
41:24Yeah couple
41:25questions though. Again,
41:26you were right on time and I appreciate that.
41:28So yeah, we have time for a couple
41:30questions for Emily on that wonderful
41:32talk in the data she showed us
41:34I did miss a couple questions
41:35in the chat after Zacks talks.
41:36I'll keep an eye on that,
41:38so please raise your hand
41:39or put something in the chat
41:40if you have any questions.
41:41Family at this time.
41:50Emily, I have a question if I may.
41:53So in this study with the 70 ish
41:55trios you found a bunch of hits,
41:58but you didn't find any duplicates, right?
42:01And then you compared to the existing,
42:03you know the data that's already out there,
42:05and I know that in the original
42:06studies that are looking at this
42:08kind of exome sequence that hits
42:09were continued considered real when
42:11you have duplicates because that
42:13increases your statistical confidence.
42:14But I think it's really interesting
42:16what you did now that we're getting
42:18more hits in more disorders.
42:19That kind of you know,
42:20overlap with existing with findings from
42:22other disorders is a really interesting
42:25alternative way to find valid hits,
42:27and I wonder if you can speak
42:28a little to that.
42:28Do you consider these proven hits or
42:30do you consider these provisional
42:32until replicated an you know they
42:34are the things that we should we
42:36should run within functional studies?
42:37Or is this still?
42:38A little work to do before we
42:40get to that point,
42:41I'd
42:42say they're still provisional. I.
42:43I mean, you made a great point,
42:45so I tried to allude to this a little bit,
42:48but in autism the first study they
42:50did 200 trios and they found one
42:52risk gene in that first study, right?
42:54They got 1 double hit.
42:56So I think you're right, it's like
43:00lightning striking twice in the same place.
43:02So then you know something
43:03weird is going on right, right?
43:04So that's really the statistical
43:05power of this approach, right?
43:07Is because these de Novo
43:08variants are so rare.
43:10If you see them in unrelated individuals,
43:12it's likely that that's very
43:14unlikely to just be due to chance.
43:17And so you're right,
43:18that's kind of what we were harnessing here.
43:21I think there's a lot of evidence
43:23across different areas of psychiatry
43:25that instead of thinking of risk,
43:27genes for individual disorders,
43:28we may be thinking more
43:30about brain genes in general.
43:32But I think still,
43:33they're going to be jeans that are
43:35more common in one disorder versus
43:36more common in another disorder.
43:38And I think sorting that out is
43:41important in terms of understanding.
43:42Kind of the circuits involved.
43:46So this that was the approach,
43:48as he said that we took here because
43:49we thought it could give more insight.
43:51I I wouldn't run with these yet.
43:53I I think getting these double
43:55hits will be helpful.
43:56I think the thing here that
43:58was encouraging is you know,
43:59even though we had this hypothesis,
44:01anxiety is different than
44:02these other conditions,
44:03so we weren't even sure we would see this
44:06damn increase in damaging mutations.
44:08But I think this is reassuring
44:09that using this approach in larger
44:11cohorts may lead us to those double
44:13hits that you're alluding to.
44:16So that's the whole great stay tuned.
44:20Well, we have a question in
44:22the chat from Zarins in below.
44:24It says great talk Emily.
44:25Any evidence that the same
44:27gene like a phosphatase,
44:29for example with different mutations,
44:31might lead to different disorders.
44:33It's kind of the converse of
44:34the point you were just. Making
44:36yeah so that I think as we.
44:40That's something that's really interesting.
44:42I didn't spend just because of the numbers,
44:44and I only I didn't have a double hit.
44:46I didn't spend time looking at exactly
44:48where like the point mutation is,
44:49but there are definitely examples in other
44:52areas of genetics where a mutation in one
44:55area predisposes you to one condition in
44:57a mutation in a different area than the
44:59gene predisposes you to another mutation.
45:04Actually, that SCN 2A mutation that
45:06gene that I mentioned earlier?
45:08That's an example of that where?
45:10You get epilepsy if the mutations
45:14gain of function and you get autism.
45:17If it's kind of a loss of function.
45:19So so there definitely is something
45:21in that I didn't quite do that here.
45:24'cause I think it's a little premature,
45:26but definitely something worth
45:28thinking about.
45:29As more and more genes pop up.
45:33Great, thank you.
45:35Alright, another great talk
45:37and we'll move on to our three
45:40runners up for this year's award,
45:42beginning with Albert Higgins Chen.
45:45Albert Albert's primary mentor,
45:47Morgan Levine,
45:48was unable to be with us today,
45:49but she's written up an introduction,
45:51which I will give.
45:53So Morgan says I would like to
45:55introduce Doctor Albert Higgins Chen
45:57and congratulate him on being selected
45:59for honorable mention for the 2021 Last
46:01minute award for psychiatric research.
46:03Albert was the recipient of the 2020
46:05Lustman Award and is being honored again.
46:07The only goes to show how remarkable he is.
46:10Albert is the embodiment of what it
46:12means to be a physician scientist.
46:13He is a brilliant independent researcher
46:16with deep scientific knowledge,
46:17intellectual curiosity,
46:18creativity and compassion.
46:20Albert has perfectly melded his research
46:23training in genetics and aging biology.
46:25With his work as a psychiatry resident,
46:27as the field continues to delve
46:29into the molecular mechanisms
46:30underlying psychiatric disorders,
46:32progress will depend on people like Albert,
46:34who have interdisciplinary,
46:36clinical,
46:36molecular and computational
46:38expertise to unravel the complex
46:41signals of multifactorial traits.
46:43Today he will discuss his recent paper,
46:45aimed at dramatically bolstering
46:46the reliability of epigenetic
46:48biomarkers of aging.
46:50While our lab was not the first to show
46:52that these measures can be extremely noisy,
46:54Albert's paper is the first
46:55to offer a solution.
46:57In doing so,
46:57the work he presents today will
46:59have far reaching implications
47:00for longitudinal an intervention,
47:02studies of aging and disease.
47:04So with that Albert take it away.
47:07OK,
47:08thank you Chris and thank
47:10you Morgan by proxy.
47:12Exline for disclosure is the
47:16methodology presented in this
47:17talk is the subject of a pending
47:19patent application and related
47:21technologies have been licensed
47:23to Alicia Mhealth next slide.
47:27So a patient comes
47:28to your office 65 year old veteran,
47:31recently placed in assisted Living
47:33Quick chart review shows that he
47:36has schizophrenia, PTSD, HIV, A50,
47:38plus pack year, smoking history,
47:40and multiple comorbidities,
47:41and the first thing you notice about
47:43him when he walks into your office is
47:45that he looks like he is 85 years old.
47:48So all of these conditions along
47:49with the social diversity and
47:51discrimination that goes along with it,
47:53accelerates the biological aging process.
47:56Now this patient has a far higher risk
47:58of cardiovascular disease, dementia,
47:59and numerous other conditions.
48:02So turns out that we can actually quantify
48:04this accelerated aging with the blood test.
48:06As Zach is mentioned.
48:08Next slide.
48:11So this is the difference between
48:14chronological age and biological age.
48:16So chronological age is simply time
48:19since birth, it's not modifiable
48:20and we can't do anything about it.
48:22But importantly,
48:23it has positive connotations and
48:25it is something to celebrate.
48:27Biological age, however,
48:28quantify is how much ones biology
48:31actually changes with time,
48:32and this is something that is modifiable,
48:34and it predicts morbidity and mortality.
48:38Importantly, these are separable
48:40and people can differ dramatically
48:42in the rate of biological aging,
48:45and we can measure this using aging
48:47biomarkers, and if you can measure it,
48:49you can manage it next line.
48:52So some of the best current biomarkers
48:55of aging are ethnic locks as Zach heads
48:58discussing it in his excellent talk.
49:00These use the insight of that
49:02millions of DNA metalation sites
49:03change with age and we can use
49:05machine learning techniques to select
49:06a few hundred that predict age or
49:08mortality risk with high accuracy.
49:11Now I previously found that these
49:13clocks are the predicted mortality.
49:15Find that people with schizophrenia
49:16are older,
49:17consistent with him dying 15
49:19years earlier than everyone else.
49:21So there is a ton of interest.
49:22Then eventually using these biomarkers in
49:25clinical practice or in clinical trial,
49:27however,
49:27I found that there is a major problem
49:31with these epigenetic clocks.
49:34Next slide.
49:36So I looked at these aging
49:38clocks an ask very simply.
49:40If you measure the same
49:41sample multiple times,
49:43do you get the same answer?
49:45No, so I looked at 36 blood samples,
49:48each measured twice and I calculated
49:50the epigenetic clocks and plotted
49:52in the biological ages of the two
49:54replicates against each other.
49:55Here on the left,
49:56and the correlation is not nearly as
49:58strong as one with like on the right.
50:00Then I plotted the difference between
50:03the two repeated measurements and some
50:05samples differed by as much as nine years.
50:08So in plain English,
50:09what that means is that if I could
50:11measure your age one day and it says
50:13you're 50 and next day says you're 59.
50:15Oh, so these are not
50:19particularly reliable next line.
50:21So I tried many methods of improving
50:24the reliability of these clocks
50:26and eventually I found a simple
50:28solution using principle component
50:30analysis which I won't describe
50:31in detail but just know that it
50:34is a method that can separate
50:35signal from noise and instead
50:37of using directly the metalation
50:39sites to predict biological age,
50:41I transformed the DNA methylation
50:44using principle component Alesis
50:46and then used the new variables to
50:49predict biological age next line.
50:53And this new clocks are way more reliable.
50:55Here we can look again at 36 samples each,
50:57measure twice and blue is our new clocks.
51:01And now the replicates.
51:02Now agree far more closely and most agree
51:05within one year and we applied this
51:07method to six commonly used clocks and
51:10they all greatly improved next slide.
51:14And so does this mean the clocks
51:16more clinically relevant?
51:17Yes, so I showed that these have
51:20much stronger relationships with
51:21mortality and many other factors,
51:22and because they are now less noisy
51:25and furthermore we can actually
51:27use these clocks to track someones
51:29aging process overtime.
51:30So I looked at 300 people followed for
51:3320 years and we see that the original
51:36clocks actually fluctuate wildly over time.
51:38Turns out that this is mostly just noise,
51:40so and our new clocks actually show
51:43a nice steady aging trend there
51:46on the bottom right next slide.
51:49And could we even use this to
51:51discover new treatments that might
51:53be able to help our patient?
51:55Yes,
51:55so I simulated a clinical trial that
51:57aims to modify someone's trajectory of aging.
52:00Measuring these epigenetic
52:02clocks longitudinally.
52:03Now the issue of reliability
52:04is critical here,
52:05because noise affects both baseline
52:07and follow up measurements.
52:09It's cures our ability to detect the
52:12effect of an intervention and power
52:14analysis indicate that these new
52:16PC clocks are far more sensitive,
52:18reducing the sample size needed to
52:20detect an effect by up to tenfold.
52:23Now given how challenging clinical trials
52:24are, this could save a lot of money.
52:26And resources next slide.
52:29So what can we actually do for our patient?
52:31Well,
52:31we can measure his biological age and
52:33find that all those years of living,
52:35mental illness and all the discrimination
52:37is a social hardships that put him at a
52:39high risk of morbidity and mortality.
52:41And we can look to the many aging
52:43treatments currently being investigated
52:44and we may eventually be able to treat
52:46this problem at least partially.
52:48Importantly,
52:48this would help prevent all the diseases
52:50of aging or once cardiovascular disease,
52:53cancer, dementia,
52:53etc.
52:54And this will be made possible by
52:57aging biomarkers that are highly.
52:59Reliable so I will wrap up a wrap
53:02up there next slide.
53:03And I like to think that lesson
53:05family that live in lab is she
53:07doctor been all my collaborators
53:09and everybody else in time trade.
53:15Great thank you. Albert was very
53:17clearly presented presentation
53:18of very important work.
53:20We're not going to have time
53:22for questions at this point.
53:23We're going to move on to our our
53:27second honorable mentioning here.
53:29The 2021 Last Minute awards.
53:31Peter Na and I want to invite
53:33Rob Pietrzak to come and
53:35introduce Peter in his work.
53:38Thank you Chris.
53:39Good morning everyone.
53:40Thank you to the Lawson family
53:42and congratulations to all of
53:44the last minute award ease.
53:45Well it's my pleasure this morning
53:47to introduce Doctor Peter Na,
53:48recipient of an honorable mention
53:50for the 2021 lesson in the world.
53:52I first met Peter just five months ago
53:54when he reached out to me to inquire
53:56about potential research opportunities
53:58using data from the National Health
54:00and Resilience and Veterans Study.
54:02This is a nationally representative
54:04prospective cohort study of
54:05veterans that Steve Southwick,
54:07John Crystal,
54:07and I have been conducting
54:08for the past 10 years.
54:10I was immediately impressed by
54:12Peter's academic background,
54:13which includes an undergraduate
54:15degree from Seoul National University
54:17where he graduated Summa Cloudy.
54:19An MD degree also from Seoul
54:21National and MPH from Harvard
54:23internship training at the Male
54:25Clinic Psychiatry Residency at NYU,
54:28and most recently in addiction psychiatry.
54:30Quite so much chip at Yale.
54:31In recognition of his work,
54:33Peter has already received three awards,
54:35including a Samsung Fellowship from Appa,
54:38the NMH Outstanding Resident Award,
54:40Honorable mention.
54:40And the John Runner Award from
54:42the American Academy of Addiction,
54:44Psychiatry.
54:44In addition to his academic accomplishments,
54:48Peter has served as a senior
54:50noncommissioned officer of the
54:52G3 Liaison Office as part of the
54:54Korean augmentation of the US Army,
54:56otherwise known as Catoosa in Camp Red Cloud.
54:59In recognition of his service,
55:00he received 2US Army achievement
55:02medals and a certificate of
55:04Achievement for excellence in service.
55:07Peter came to Yale,
55:08already quite accomplished with three.
55:09First off in manuscripts and eight
55:12first offered meeting abstract since
55:14the start of his fellowship in July 2020.
55:16Peter has accelerated
55:17his productivity further.
55:18First authoring 9 manuscripts
55:20that are currently in press,
55:22except that are under review,
55:23including five in which I've been
55:25fortunate to services primary mentor.
55:27So run on average right now
55:28with paper per month will see if
55:30we can keep up with that.
55:31Peters exemplary productivity speaks
55:33to his deep rooted interest and
55:35commitment to a career as a clinician,
55:37scholar,
55:37and psychiatry as well as to his
55:40dedication to make meaningful
55:41scientific contributions to our field,
55:43particularly in veteran mental
55:45health this July.
55:47Peter will join the VA Connecticut
55:49staff and is currently already
55:50preparing an application for a
55:52be a career development award to
55:53expand his research to consider
55:55the role of genetic factors in
55:57suicide and substance use disorders.
55:59He's already developed a detailed
56:01research and primary mentor ship
56:02plan with Doctor Joel Gelernter and
56:04me that will enable him to develop
56:06new skills and expertise in genetic
56:08psychiatric epidemiology with the
56:10ultimate goal of identifying
56:12modifiable psychosocial,
56:13moderators or polygenic risk for
56:15suicide and substance use disorders.
56:17I must note that throughout my
56:19experience of working with Peter,
56:20I've been impressed by his scientific
56:21writing and critical thinking skills,
56:23as well as his remarkable ability
56:26to translate very complex
56:27epidemiological findings into
56:29actionable clinical implications.
56:31I'd also like to highlight that
56:33Peters research and veteran
56:35mental health and suicide is inspired by
56:37his own military experience and losses
56:39that he personally endured on that note,
56:41as we head into Memorial Day weekend,
56:43I'd like to share a quote from the author,
56:45Richelle Goodrich, who said on Memorial Day.
56:48Take time to remember those who have fallen,
56:51but on every day after,
56:52do more put the freedoms that they
56:55died for to greater and nobler uses.
56:58Today Peter will present results of a
57:00recent study on factors associated with
57:02suicidal thinking during the pandemic and
57:04US veterans with pre-existing conditions.
57:07To speak to Peter's amazing efficiency,
57:09he wrote this paper in one week.
57:11Peter, please. Thank
57:14you Doctor Pietrzak for your
57:16kind introduction. Today.
57:17I'll be presenting our research on factors
57:20associated with suicidal ideations during
57:22the COVID-19 pandemic and veterans with
57:25pre-existing psychiatric conditions.
57:26I do not have any disclosures to report.
57:29This paper was published in the Journal of
57:32Psychiatric Research earlier this year.
57:34Next slide.
57:36As we're all aware mental health
57:38burden during the pandemic is on
57:39the rise with reports of increased
57:41prevalence of depression,
57:42anxiety and alcohol consumption
57:44of the general public.
57:45There were also concerns about
57:47possible increase in suicidal
57:49behavior based on the fact that during
57:51previous pandemics and outbreaks,
57:53suicide rate increased historically.
57:55For example,
57:56during the SARS outbreak in Hong Kong,
57:58the most significant increase were
58:00found among older adults, next light.
58:04Possible vulnerable groups
58:05during the pandemic.
58:06Identify where older adults,
58:09possibly due to more physical comorbidities.
58:12Also, who experienced greater
58:14social isolation and loneliness.
58:15Also,
58:16individuals with mental disorders retreat
58:18who may be uniquely vulnerable to increase
58:21psychological distress during the pandemic.
58:23Also,
58:24military veterans were well known.
58:25High risk group for suicide as well
58:27as COVID-19 survivors who showed
58:29higher prevalence of depression,
58:31anxiety and PTSD compared to non survivors.
58:35Next slide so to meet this
58:37urgent public health concern,
58:39we analyze the 2019 to 20 National
58:42Health and resilience in various study
58:44and HRV S among the total 4000 samples.
58:47We analyze subsample of 6061 veterans
58:50who screen positive for pre pandemic
58:53major psychiatric disorders such as MD,
58:56JD, PTSD, and or SUT.
58:59Baseline survey or wave one survey as well.
59:02Call Pre Pandemic survey was completed
59:04prior to the first known identified
59:07COVID-19 case in the US and then the
59:10follow up survey wave two or refer to
59:12a pre pandemic survey was conducted
59:14nine months into the pandemic.
59:17Next line.
59:19Suicidal ideations was measured,
59:21but the two items adapted from page tonight
59:24at 9:00 and purpose in life was assessed
59:27using the purpose in life test short form.
59:29Here's a sample item here and also
59:32be gathered kovin related variables
59:34including COVID-19 infection status that
59:37was reported by Self Report next line.
59:42We ran multivariable logistic regression
59:44analysis as well as interaction analysis
59:47of COVID-19 infection by age and also
59:50by protective psychosocial factors
59:52based on prior literature next line.
59:56The results mean age was 55.2
59:59predominantly male and white,
01:00:0140% were combat veterans and apparel.
01:00:05Pandemic assessment.
01:00:06Almost 20% screen positive for suicidal
01:00:10ideations and among them 58.9% reported
01:00:13both pre and Peri pandemic aside,
01:00:16an 8.9% developed essay during
01:00:19the pandemic next slide.
01:00:22This is the multivariable
01:00:23regression model we found.
01:00:25So as you can see,
01:00:26higher household income and also
01:00:29greater scores and purpose in
01:00:31life scale were associated with.
01:00:34Lower risk of suicidal ideations
01:00:36during the pandemic,
01:00:37whereas Eyecatch greater psychiatric
01:00:39symptoms severity as well as previous
01:00:42suicidal behaviors and cover 19 infection
01:00:45were associated with greater risk of SI.
01:00:48Next slide.
01:00:51Interaction analysis showed that among
01:00:53those who are infected with COVID-19,
01:00:56those age 45 or older were
01:00:58more likely to endorse as I,
01:01:00as you can see during in the 45 to 59
01:01:02year old bracket, it's close to 60%.
01:01:05One possible mechanism to this
01:01:07finding is that older adults tend
01:01:10to have more severe illness courses,
01:01:13or also when they're infected they
01:01:15may suffer more anticipo Tori anxiety
01:01:17because of the possible higher mortality.
01:01:20Next line.
01:01:23Another interaction analysis found that
01:01:24among those were infected with covin 19,
01:01:27those in the lowest quartile of
01:01:29purpose in life score almost 80%,
01:01:32indoors suicidal ideations,
01:01:33and during the pandemic next line.
01:01:37Policy clinical implications of our
01:01:39findings that veterans age 45 or
01:01:42older with COVID-19 infection and
01:01:44also has pre existing psychiatric
01:01:46disorders may require more close
01:01:49monitoring as an policy measures to
01:01:52mitigate financial stress interventions
01:01:53to enhance purpose in life.
01:01:55Size chess acceptance,
01:01:56commitment therapy logotherapy as well
01:01:58as chaplain care which is known to
01:02:01enhance religiosity or in spirituality
01:02:03which is closely associated with
01:02:05purpose in life may help mitigate suicide.
01:02:07Risk behavior risk in veterans
01:02:10during the pandemic.
01:02:11Nick lied.
01:02:13Future directions it's Doctor Pietrzak
01:02:15measured with Doctor Pietrzak angoul counter.
01:02:17I'll be applying for the VA,
01:02:18CDA this fall with plans with proposal to
01:02:22identify modifiable psychosocial factors.
01:02:25Then we interact with.
01:02:27G was derived polygenic risk
01:02:30scores of suicidality as Westworld
01:02:33ssed and as a starter.
01:02:35We just submitted a paper to the
01:02:37journal looking at a seven year.
01:02:40Prospective cord of an HRV S looking
01:02:43at PRS by psychosocial factors.
01:02:46Next line.
01:02:48These are the findings we
01:02:50found and as you can see,
01:02:51those with higher suicidality
01:02:54collision at risk for suicidality.
01:02:57And also endorsed lower dispositional
01:03:00optimism and lower social support were
01:03:04more likely to endorse Chronicus I
01:03:06or develop new onset SI respectively
01:03:09during the seven year study period.
01:03:13I'll put this papers under review next line.
01:03:17We would like to thank the veterans
01:03:19participating in our study,
01:03:20especially with Memorial Day coming
01:03:22around and also our collaborators as
01:03:25well as the crew addictions that country
01:03:27fellowship crew, including doctors,
01:03:29meaning that raucous thank you everyone.
01:03:35Wonderful thank you one week, really.
01:03:40Wow, wait. We have time crunch.
01:03:45Important to get this out so we're
01:03:48very timely. Alright,
01:03:49so we'll move on to our last speaker
01:03:52in our last honorable mention,
01:03:54and this is Ryan O'dell.
01:03:56He'll be introduced by his mentor,
01:03:58Chris Van ****.
01:04:01Great thank you Chris and I want to
01:04:04congratulate all of the awards and I'm
01:04:07especially honored to introduce Ryan O'dell,
01:04:09whom we felt very fortunate to have as
01:04:14a member of our research team with the
01:04:17Alzheimer's Research Unit and Alzheimer's
01:04:19Research Center for the past three years.
01:04:23Starting with this case,
01:04:25rotation and then continuing throughout this
01:04:27Presidency through the N R&R TP program Ryan.
01:04:32As you will see,
01:04:33has focused his research in Nuro pet imaging,
01:04:36in which he is Co mentored by Adam Mecca,
01:04:41an in which he's proven to be a very,
01:04:44very quick study of complex neuroimaging
01:04:48methodology's in statistics,
01:04:50and I think his research abilities will speak
01:04:52for themselves through the paper that Hill.
01:04:54Be presenting to you.
01:04:57But Ryan, I wanted to really emphasize
01:05:00as a person of extraordinary ability,
01:05:03curiosity, and dedication,
01:05:06but also compassion as a clinician.
01:05:11And also you know rare generosity as he
01:05:15regularly shares his his knowledge and
01:05:18experience with our students with our.
01:05:23Staff and with collaborators.
01:05:24And I think he certainly has
01:05:27a brilliant future.
01:05:28As
01:05:28a physician, scientist and
01:05:31teacher, but maybe at least as
01:05:33importantly as a new father.
01:05:35So multiple. Congratulations
01:05:37to Ryan and also to Milda.
01:05:41So take it away, Ryan. Thank
01:05:44you Chris for that very kind introduction.
01:05:47And before I begin I also want to
01:05:49thank the Lussman family as well as
01:05:51the award selection committee for
01:05:53this opportunity to present my work.
01:05:55My recent work using a novel pet imaging
01:05:57tracer to characterize the relationship
01:05:59between amyloid accumulation and synaptic
01:06:02health in early Alzheimer's disease.
01:06:04Next slide, I have no personal disclosures,
01:06:08so next slide.
01:06:09And so just to dive right in.
01:06:12So synaptic loss has been demonstrated
01:06:14both as an early pathological
01:06:16event in Alzheimer's disease,
01:06:18but also a significant major structural
01:06:21correlate with cognitive impairment.
01:06:23An as synaptic loss in Alzheimer's
01:06:25disease has been investigated primarily
01:06:28via postmortem and brain biopsy studies.
01:06:30The ability to measure synaptic density
01:06:32in vivo would not only allow for a
01:06:35more complete understanding of synaptic
01:06:37alterations in early disease stages,
01:06:39but would also be a great utility.
01:06:41For tracking a deep regression and also
01:06:43monitoring the efficacy of potential
01:06:45therapies in clinical trials and so,
01:06:47one suitable target is the synaptic
01:06:49vesicle glycoprotein 2 which is circled
01:06:51in blue in the bottom left of the slide.
01:06:54This is an essential component of synaptic
01:06:56vesicles is located in the presynaptic
01:06:58terminals and one of its isoforms.
01:07:00SV 2A is ubiquitously expressed
01:07:02in almost all of the synapses
01:07:04in the CNS and could be useful.
01:07:06Useful biomarker for synaptic
01:07:07density and so to that end,
01:07:09such a tracer known as you see,
01:07:11BJ's shown in the bottom right.
01:07:13Has been developed for quantitative SV
01:07:152A pet imaging at the Yale Pet Center.
01:07:18Next slide please.
01:07:19So in our previous work with
01:07:21UCB JPEG image Ng,
01:07:22we've demonstrated widespread reductions
01:07:24in synaptic density in Alzheimer's
01:07:26disease in the medial temporal lobe,
01:07:28and also neocortical regions,
01:07:29and on the left this is a slide from
01:07:32a recent publication that displays
01:07:34average coronial images of synaptic
01:07:36density for 19 cognitively normal
01:07:37on the left and 34 Alzheimer's
01:07:40disease participants on the right,
01:07:42and you can see visibly reduced you CBJ
01:07:44binding in the medial temporal lobe,
01:07:46which is the bottom row of corona sections.
01:07:49But you can also see there's a
01:07:51reduction in synaptic density throughout
01:07:52the NEO cortex and subcortex.
01:07:54Which we have quantified below,
01:07:56and although this study did seek out,
01:07:59you know,
01:07:59to fully characterize the extent
01:08:01of synaptic alterations in early AD
01:08:03using SV2 Apetit did leave unclear
01:08:05the relationship of these synaptic
01:08:07alterations with more traditional
01:08:09markers of 80 pathology,
01:08:11specifically amyloid or a beta deposition,
01:08:14and so therefore in the present
01:08:15study we set out to characterize
01:08:17the relationship between a measure
01:08:19of global amyloid deposition and SV
01:08:21two way binding in early Ady across
01:08:22a broad range of cortical regions.
01:08:24Next slide.
01:08:25And so, in the era of amyloid PET imaging,
01:08:28longitudinal studies have generally
01:08:31demonstrated that continued.
01:08:32There's continued amyloid accumulation
01:08:34throughout the prodromal or mild
01:08:36cognitive impairment stages of
01:08:38Alzheimer's disease,
01:08:39with minimal change by the time of
01:08:42conversion to a dementia next slide.
01:08:44And additionally limited postmortem
01:08:46work in these prodromal or mild
01:08:48Adie stages has demonstrated the
01:08:50hippocampus to be the site of the
01:08:53earliest and most profound synaptic loss.
01:08:55Next slide and so therefore,
01:08:57in the prodromal stage of a D when
01:09:00amyloid plaques are still accumulating,
01:09:02we might expect them to be associated
01:09:04with industries of disease severity,
01:09:06which includes synaptic loss,
01:09:08particularly in those brain regions
01:09:10that show marked early synaptic loss,
01:09:12such as the hippocampus. Next slide.
01:09:15Oh yes, there's the primary hypothesis,
01:09:17Yep, so in in this study we have
01:09:22recruited participants between the age
01:09:24of 55 and 85 years old that either had
01:09:27normal cognition or Alzheimer's disease.
01:09:29The cognitively normal participants,
01:09:30Ramel Lloyd negative NAD participants
01:09:33either had mild dementia or
01:09:34mild cognitive impairment,
01:09:36and all were employed positive.
01:09:37We perform pipet for brain amyloid.
01:09:39You see BJ to measure the synaptic density
01:09:42and we did MRI for volumetric segmentation
01:09:45and ROI determination using freesurfer.
01:09:47Parameters and the model parameters that
01:09:49I'm going to be reporting are distribution
01:09:51volume ratios that use a whole cerebellum.
01:09:54Reference region for both tracers.
01:09:55Next slide.
01:09:56So this is some demographic information.
01:09:59The sample consisted of 19 cognitively
01:10:01normal 14 amnestic mild cognitive impairment
01:10:04and 24 mild dementia participants.
01:10:06It was well balanced for age and sex
01:10:08and demonstrated slightly decreased
01:10:10years of education in the dementia
01:10:11group as compared to the CN Group.
01:10:13I have that highlighted in red,
01:10:15but overall we do see expected group
01:10:17differences in measures of disease stage as
01:10:20indicated by the clinical dementia rating.
01:10:22Some boxes score.
01:10:23Global cognition is shown with the MSE,
01:10:26an episodic memory as shown is an average
01:10:28of the logical memory 2IN revolt delay.
01:10:31Onoro psychological tests next slide.
01:10:34So then looking at our primary analysis
01:10:36of the association between global
01:10:38amyloid deposition and hippocampal SV 2A,
01:10:41we see a marginally significant inverse
01:10:44correlation in participants with MCI
01:10:46as shown by the green dots in line,
01:10:48but not in dementia shown in red,
01:10:50and this significant correlation did
01:10:53survive partial volume correction,
01:10:54although I'm not going to be discussing
01:10:57that technique and methodology
01:10:59here next slide.
01:11:00And we can also see this difference in
01:11:02the correlation coefficients between
01:11:03the true groups was significant,
01:11:05as assessed by the Fisher Z transform
01:11:07with a one tailed P value next.
01:11:09And so finally,
01:11:11surrounding our exploratory
01:11:12analysis of the association between
01:11:14global amyloid deposition,
01:11:15an regional S V2 and the remaining
01:11:17medial temporal structures,
01:11:18amygdala, and to rhino,
01:11:20in parahippocampal cortices,
01:11:21as well as cortical composite are wise.
01:11:24We do observe many negative
01:11:25but nonsignificant correlations
01:11:27in both participants,
01:11:28with MCI and mild dementia.
01:11:30We do have other do see a significant
01:11:33inverse correlation between global
01:11:34amyloid and lateral parietal SV
01:11:362A and mild dementia participants,
01:11:38but this significant.
01:11:39Correlation did not survive
01:11:41partial volume correction.
01:11:42Next slide,
01:11:43and so in conclusion we this is the
01:11:45first in vivo study investigating
01:11:48the relationship between amyloid
01:11:50deposition and synaptic alterations
01:11:52in Alzheimer's disease.
01:11:54We feel our findings lend
01:11:55in vivo support to this
01:11:57hypothesis that in the earlier
01:11:58stages of clinical disease,
01:12:00amyloid deposition may still be
01:12:02accumulating across the broad range
01:12:03of cortical regions having yet to
01:12:06reach this hypothesized plateau,
01:12:07and we also feel these results are
01:12:09consistent with prior evidence that
01:12:11amyloid plaques are not well correlated.
01:12:13With the indices of disease severity,
01:12:14at least in the dementia stage,
01:12:16and of course,
01:12:17to better characterize this
01:12:19relationship moving forward,
01:12:20we're recruiting or continuing
01:12:21to recruit a larger cohort of
01:12:24participants with MCI and mild dementia
01:12:26to be followed longitudinally,
01:12:28as well as investigating a separate
01:12:30cohort with preclinical Alzheimer's
01:12:32disease for longitudinal multi tracer
01:12:34PET imaging studies. Next slide.
01:12:38So that's all I have for today.
01:12:39Thank you again for allowing me
01:12:41this opportunity to tell everyone
01:12:42about our ongoing work.
01:12:43I really, really can't give enough
01:12:45thanks to my faculty,
01:12:47mentors, Doctor Vandyken, Dr.
01:12:48Mecca,
01:12:49as well as all of the research
01:12:51faculty and staff that have
01:12:52contributed contributed to this work,
01:12:54many of whom are listed here.
01:12:56And, of course,
01:12:56we can't give enough thanks to
01:12:58the research participants who
01:12:59generously donated their time and
01:13:01efforts to make these studies
01:13:02possible. Thank you.
01:13:10Thank you Ryan for a great talk and I
01:13:12think we've really seen an extraordinary
01:13:15breadth of wonderful science here
01:13:17across many different domains.
01:13:20It just speaks to the the wonderful
01:13:22things that are going on among the
01:13:24trainees in our department and I
01:13:26congratulate all of the winners.
01:13:28Since we've had 11:30,
01:13:28I think we're not going to have time
01:13:30for more questions and discussion now,
01:13:31but I invite you if people have questions
01:13:33for individual winners and presenters,
01:13:35please follow up by email with them.
01:13:38Thank you everyone for being here.
01:13:41Thanks again to the last man family
01:13:43and the last and Family Foundation
01:13:45for supporting this wonderful
01:13:47departmental transition.
01:13:48We'll see you all again next year.