Yale Psychiatry Grand Rounds: May 28, 2021

Transcript

• 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.