James McPartland, PhD: Data Blitz, McPartland Lab

December 01, 2020

Information

Professor in the Child Study Center; Director, Yale Developmental Disabilities Clinic; Director of Undergraduate Studies, Yale Child Study Center; Co-Director of Team Science, Yale Center for Clinical Investigation (YCCI); Associate Director, Developmental Electrophysiology Lab

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00:02OK, my name is Dana Mcpartland.
00:04Thanks for the opportunity to
00:06participate in this data blitz.
00:08I am a clinical psychologist by
00:10training the research that I do
00:12is social neuroscience research.
00:14I'll tell you about today.
00:16I direct the autism clinic
00:18at the Child Study Center.
00:19I run a lab and then I also direct
00:21a consortium around the country
00:24called the Autism Biomarkers
00:25Consortium for clinical trials,
00:27and I'll tell you about all
00:30of those things today.
00:31Put really simply,
00:32my the work in our lab is
00:35designed to address this problem
00:37that when we are in the lab we
00:40can do use these amazing tools.
00:42We do a lot of work with EG.
00:45We do a lot of work with eye tracking.
00:48We do some work with PET and MRI and
00:50functional near infrared spectroscopy.
00:52Lots of interesting powerful
00:54ways to understand autism,
00:55which is primarily what we study.
00:58But when I'm in the clinic,
01:00I have one to my my clinical lens and
01:03that's really the same tool that's
01:05been used in the history of autism.
01:07I think that if we had more objective,
01:10sensitive tools like biomarkers,
01:11we would be in a better place
01:14to help people with autism.
01:15And that's really the problem
01:17that we try to solve in the lab.
01:19There are many different purposes for
01:21biomarkers cohorts that we work with.
01:23Are, you know, school age and up,
01:26so the kinds of biomarkers
01:27that I'm interested in.
01:29Really are related to stratification.
01:31The idea that you can take a very
01:33heterogeneous group of people
01:35and find markers either in genes,
01:37brain function,
01:38patterns of visual attention to
01:40subgroup in ways that are meaningful
01:42for figuring out who's going to
01:44respond to treatment for prognosis.
01:46For for purposes like that.
01:49This is a a biomarker that we've
01:52been extremely involved with.
01:53This is a brain electrophysiological
01:55biomarker.
01:55It's an event related potential,
01:57which just means signal processing
01:59applied to the electroencephalogram.
02:01Produces a marker that tells us something
02:03specific about a cognitive process.
02:05In this case,
02:07the cognitive process is face
02:09perception which is really interesting
02:11to us in autism because faces are
02:13a key source of social information
02:15and a pretty reliably affected.
02:19Area function in people with autism.
02:22This negative peak around 170
02:24milliseconds is called the N 170
02:28and this represents the brain
02:30recognizing a face as such,
02:33so the first face specific stage
02:36of face processing.
02:38Work that we did now some time
02:40ago showed us that in people
02:43with autism is very early.
02:45Marker is significantly delayed that
02:47people with autism show inefficiency at
02:49this very early stage of face perception,
02:51since doing this study,
02:52we've done a number of different
02:54studies to really understand
02:56whether this could be a potentially
02:58useful biomarker in autism.
03:00The kinds of things that
03:01we've tried to understand,
03:03you know?
03:04Coming from that first study that showed
03:06us that it's sensitive diagnostic status.
03:09The intergroup mean differences between
03:12people that some people without
03:14we've seen that it N 170 responses
03:16correlated with autism severity
03:18in other kinds of autism symptoms
03:20like difficulty recognizing faces.
03:22It's functionally specific that
03:24these relationships we see with
03:26social function are not generic
03:28relationships with all aspects of visual
03:30function or cognitive performance.
03:32So really, it's not just telling us
03:35something that a brain is performing
03:37differently is telling something specific.
03:40About this social circuitry of the brain.
03:43We've seen that it's applicable
03:45across development.
03:46We see these differences in the
03:48end 170 in very young children,
03:50autism through adults,
03:51we see that it's robust to
03:53variation behavior manipulating,
03:54where a person,
03:55how a person with ASD looks at faces,
03:58which is an important control
04:00because people with autism tend to
04:02look at faces in different ways,
04:04doesn't make worse or fix this delay.
04:06In the end, 170,
04:08and we've also seen that this N 170
04:10is responsive to change in clinical
04:12status as children with autism get better.
04:15In treatment we can see this latency
04:18difference in the end when 70 become reduced.
04:20So having done many of these studies
04:23and next goal has been to try to get
04:26the kind of data that we could use
04:29to qualify a biomarker with the FDA.
04:31And this is the work that we've
04:33accomplished in the context of
04:35the Autism Biomarkers Consortium
04:36for clinical trials.
04:38This is a multi site 5 autism
04:40research centers around the
04:41country naturalistic study,
04:42meaning we don't administer intervention we.
04:45We we have now concluded the first
04:47phase in which we worked with a large
04:50group of children 280 with autism and
04:52119 with typical development between
04:54the ages of 611 and with a range
04:56of Iqs from in the intellectually
04:58disabled range to well above average.
05:01We took a battery of well studied,
05:03promising biomarkers from the
05:05modality of e.g and eye tracking
05:07and then study them overtime,
05:08so seeing children over three time
05:10points of baseline to six weeks so we
05:13get a sense of stability in the short
05:16term and we don't anticipate that too
05:18much intervention related change.
05:19Or developmental change should have
05:21happened and then again at 24 weeks
05:23where we might expect more changes
05:25to give us a chance to see how these
05:27biomarkers might track change.
05:29We also drew blood on all these children,
05:31so we have genetic genotypic data
05:33that we have yet to analyze,
05:35but will be able to do in the future.
05:39So in this first phase of the study,
05:41we actually got the kind of data that
05:43we needed in terms of demonstrating
05:46that we replicated the effects
05:47that we anticipated.
05:49We demonstrated stability overtime in
05:50these biomarkers and we demonstrated
05:52relationship with the phenotype.
05:53With that information,
05:54we took two biomarkers to the FDA
05:56biomarker qualification program.
05:58The M170 that I've described to you already.
06:01And the second was an eye tracking marker,
06:03looking at how much time people
06:05with autism spend looking at faces
06:07or people on screen.
06:09The Ocular Motor index of gays
06:11to human faces or
06:12the Omi. We submitted these in the form
06:14of letter of intent to the FDA biomarker
06:17qualification program and they were both
06:19accepted in Maine 2019 and March 2020.
06:22This is a first for autism,
06:24but this is also a first for the field
06:26of psychiatry and that these are the
06:29first biomarkers to be except for any.
06:31Psychiatric condition to be accepted if into
06:34the FDA's biomarker qualification program.
06:36The context of use that we
06:37described was to use these markers
06:40as stratification biomarkers.
06:41The idea that if you see this distribution
06:44here that people with autism their their
06:46histogram values are shown in green.
06:49The typically developing children are shown
06:51in blue and you can see that this is this.
06:55This would not be a good diagnostic
06:57biomarker in that there's much overlap,
06:59but there's a portion of
07:01children with autism.
07:02Crucial values that don't overlap
07:04it off with the typical range,
07:06and the idea is that this group
07:08of children may represent.
07:10A subgroup that may be more similar,
07:13you know, typically or may have more common,
07:17more consistent neuropathology that.
07:19By selecting these children and selectively
07:21admitting them to clinical trials,
07:23clinical trials would have greater power to
07:26determine whether treatments are effective.
07:28We are continuing to work through the
07:31biomarker qualification process with the FDA,
07:33which is extensive.
07:34We're now in the stage of developing
07:36a biomarker qualification plan which
07:39would guide our data collection,
07:41Twords preparing a biomarker qualification
07:43package based on which an FDA FDA
07:46colleagues would make a decision about
07:48whether a biomarker could be qualified.
07:50This is a very exciting time for
07:52us and that being in this cutting
07:54edge space where the FDA is learning
07:57about psychiatric biomarkers.
07:59As we're learning about
08:01psychiatric biomarkers,
08:01it's been a very exciting time to
08:04partner with the FDA in the course
08:06of several grants that permit us
08:09to have ongoing discussions as
08:10to think about how to refine our
08:13biomarkers towards qualification.
08:14We were renewed for second phase in July.
08:17The second phase will consist of
08:19three studies of confirmation.
08:21Study very similar to the first one,
08:23but with a more balanced ratio
08:25of children with autism.
08:27Typically developing children
08:28follow-up study in which will evaluate
08:30the original cohort 2 1/2 to four
08:33years after initial enrollment,
08:34and then a feasibility study in which
08:37will determine whether these biomarkers
08:39can be applied in younger children
08:41three to five year old children.
08:44I want to talk about a few other
08:47studies going on the lab that will
08:49be active in the next few years.
08:52One is really designed to improve
08:54the reach of this line of biomarker
08:57research and really broad biomarker
08:59research using e.g an eye tracking
09:01in general and autism at present
09:03almost all research,
09:04almost all neuroscience research in
09:06autism exclude children who have
09:09any kind of significant intellectual
09:11disability simply because it's
09:12really hard to to collect data.
09:14So what we've tried to do is develop a
09:17basically a behavior modification setup
09:19that's governed by machine learning.
09:21That's automated, and so when we have a
09:24person in the lab where basically monitoring
09:27everything they do where they look,
09:29weather where their head is oriented,
09:32whether their bodies and body is moving
09:34or still, and we basically create
09:36automated thresholds for these levels too,
09:39that we then downward adjust during
09:41periods of natural rust natural rest
09:43so that we can essentially shape.
09:46Person to look at the screen sits
09:48still maintain their orientation
09:50towards the screen as in order to
09:52keep a preferred video playing.
09:54So this is really put simply, these are
09:57the the this is applied behavior Now.
10:00Behavior modification, the kind of things
10:02that are used behaviorally, not ISM.
10:04The idea here is really to automate
10:06it so that we can collect EG data.
10:08An eye tracking data.
10:10And it works.
10:11These are pilot data that this is
10:14an ongoing study that's actually
10:16been slowed because of covid,
10:18but the system works were able
10:21to get children with Iqs,
10:23is lowest 22 to tolerate our procedures
10:26to yield valid eye tracking and EEG data,
10:30and so we're actually we plan actually
10:33to to begin seeing participants
10:35post covid next week.
10:38Another application of this line
10:39of research is to think whether
10:41these biomarkers could provide us
10:43information about potential treatment
10:45targets and so we're interested in
10:47direct brain stimulation really.
10:49Right now,
10:50autism is treated purely
10:51by behavioral treatments.
10:52There are no medications to treat the
10:55core social difficulties in autism.
10:57We understand the brain regions
10:59that underpin these difficulties.
11:00We know that they are the brain region
11:02targeted by behavioral treatments,
11:05and So what we're interested in
11:07doing is targeting them directly
11:08with direct brain stimulation.
11:10Specifically,
11:11we're interested in targeting
11:12this theory of temporal sulcus.
11:13Here you can see me.
11:16Demonstrating what a stimulation
11:18looks like we are.
11:20At this stage,
11:21less interested in whether they
11:23would work therapeutically and
11:25more in terms of proof of concept.
11:27If we target the brain regions that
11:29we believe underpin these biomarkers
11:31that end 170 and attention to faces,
11:34can we see movement in these
11:36constructs in the direction that
11:38we would hypothesize that would be
11:40beneficial to a person with autism
11:42and we do even in typically developing
11:44controls we see that stimulating
11:46the STS decreases in 170 latency,
11:48so there anyone 70 gets faster,
11:50which is what we would want to
11:53see in people with autism.
11:55And we also see that the when we look
11:58at the amount of time a person spends
12:01fixating on the eyes of the face,
12:03we see it being increased in these
12:06typically developing individuals
12:07in response to TMS to the SDS
12:09and less to confuse you,
12:11I TBS just refers to a particular
12:13kind of TMS.
12:14So that's the information that
12:16I want to tell you in my.
12:19Brief datablitz I want to
12:21acknowledge the people who who make
12:24this all happen in the clinic.
12:27In the ABC T.
12:28And in the in the lab,
12:30one of the downsides of this
12:32virtual asynchronous format is
12:33that I don't get to entertain
12:35the excellent questions that I
12:37usually get from this group.
12:38So please, please consider emailing me,
12:40check out our website,
12:41pick Yale and I hope I have the opportunity
12:43to work with you all in the future.
12:46Thanks so much for listening
12:48to the talk today.