3/23/22 – Dr. Jeffrey Gruen –The New Yale Program for Learning Disabilities Research

Transcript

• 00:00Spring.
• 00:05We have a few announcements,
• 00:06upcoming grand rounds next week,
• 00:09March 30th is one of our.
• 00:11A special lecturers named lecture
• 00:14and part of our Centennial series,
• 00:17the C DAF Cook Lectureship.
• 00:19Those of you who don't remember
• 00:21that Cook was a former chair of
• 00:24the Department of Pediatrics.
• 00:27And Kinari Webb,
• 00:28who's in family medicine and
• 00:29founder of health and harmony,
• 00:31will be speaking on healing
• 00:33the planet by recognizing the
• 00:36fundamental sickness of colonialism.
• 00:38Uh.
• 00:40Then on April 6th we're going
• 00:42to be having care rounds,
• 00:43which are conversations and
• 00:46reflections experiences in the
• 00:48Children's Hospital and look forward
• 00:51to that interactive grand rounds.
• 00:57Another announcement coming up on
• 00:59this Monday or monthly pediatric
• 01:02educational learning community
• 01:03series will be led by Galloping
• 01:06Me Soma and Gunjan Tiagra,
• 01:09both from the section of emergency
• 01:11medicine on introduction to
• 01:12qualitative research methods,
• 01:14exploring factors that influence
• 01:16the choice of academic pediatricians
• 01:18by underrepresented minorities.
• 01:25And also Joe reminder.
• 01:27Another one of our major
• 01:29events for a Centennial.
• 01:30Is the Richard Ehrenkrantz Neonatology
• 01:33Symposium and this year's topic
• 01:35is ethical issues in neonatology?
• 01:37This will be taking place virtually Tuesday,
• 01:40April 5th from 1:00 to 5:30.
• 01:44There will be a incredible
• 01:47lineup of speakers and talking
• 01:50about these important topics in
• 01:52ethics related to neonatology,
• 01:54so please join us.
• 01:59There are no conflicts and no contact,
• 02:02no disclosures that need to be made.
• 02:06This is accredited for see me
• 02:09by the Yale School of Medicine.
• 02:11There's the number.
• 02:12The text to the CME office
• 02:15and will also put this in the
• 02:18zoom chat at various intervals
• 02:20throughout the grand rounds.
• 02:25And with that I'm going to
• 02:28turn it over to Mark Mercurio,
• 02:30to introduce today's speaker.
• 02:38Thank you Cliff.
• 02:39It's an honor to introduce my
• 02:41friend and colleague Jeff Grouin.
• 02:42Today I'm gonna just share my
• 02:44screen for a moment if I could.
• 02:49Let's go with this and share and
• 02:52are you looking at my slides now?
• 02:54So this this of course is doctor Jeff Broin
• 02:57who is known to you all as a professor
• 02:59of Pediatrics and genetics here at Yale.
• 03:01He's certainly one of the pillars of of
• 03:05Yale and neonatology, Yale Pediatrics,
• 03:08and Yale Science, but of course he
• 03:10didn't start out as such a big cheese.
• 03:13He was got his BS and MD at Tulane,
• 03:16came to Yale where he did his residency
• 03:18and fellowship and Jeff and I traveled
• 03:20this journey together ever since.
• 03:22And so it's been my absolute pleasure
• 03:24to watch him rise through the ranks.
• 03:26So let's see if we can get this slide
• 03:29to advance and apparently we can't.
• 03:31Let's try that.
• 03:32So here we go back a little bit
• 03:34in time and we see this here.
• 03:35I don't know if you can see my cursor.
• 03:36We see the second from the left.
• 03:37Standing up is a young Jeff grew in with his
• 03:40dog with his wife Susan here and Michelle.
• 03:42I see everybody.
• 03:43We had a lot of babies were
• 03:44born in Pediatrics that year.
• 03:45This, I think would be the spring
• 03:47of 85 in my backyard in Hamden.
• 03:50This is a young Luciano Pavarotti
• 03:51you see over here at the time.
• 03:53And this is and and again, Michelle.
• 03:56Jeff's daughter was not in this picture,
• 03:58but I've had the the pleasure
• 04:00of watching Doctor Gruen.
• 04:02Just rise through the ranks over the
• 04:04years and grow gradually to be the the
• 04:07fellow that you all know and love today.
• 04:10He became a professor of medicine.
• 04:12Excuse me of Pediatrics.
• 04:13In Unix in 2010 he's also an
• 04:16honorary professor at Shenzhen
• 04:18Tong University in China.
• 04:20He's internationally recognized as a
• 04:22scholar and investigator with collaborators
• 04:24around the collaborators around the world.
• 04:27He's very, very well published.
• 04:29He's been very well funded for
• 04:30a number of years, many,
• 04:31many years, and at Yale,
• 04:33he's really a valued mentor and advisor
• 04:36to medical students to graduate students,
• 04:38to, to our trainees, to our junior.
• 04:40Faculty and, and frankly,
• 04:42to at least one very grateful Chief for
• 04:45whom he's been a valued advisor for many,
• 04:48many years.
• 04:48So it's been my pleasure to watch Jeff
• 04:51really become such an incredibly,
• 04:53highly respected scholar and
• 04:55investigator that he is.
• 04:56You know,
• 04:57he studies genetic variants that
• 04:58underlie common learning disabilities,
• 05:00and you're going to hear a bit
• 05:01about that today.
• 05:02And as such,
• 05:03the talk should really be of interest
• 05:04to anybody who's interested in
• 05:06genetics or studies genetics or
• 05:07who wants to learn more about it,
• 05:09or anybody who's who works with
• 05:11kids with learning disabilities or
• 05:13wants to learn more about that.
• 05:14But there's the lecture will also
• 05:16be of interest to anybody who wants
• 05:18to be a better teacher,
• 05:19because as most of you know,
• 05:21and many of you know,
• 05:22and you're all about to find out,
• 05:24our friend Jeff can teach.
• 05:26He can take difficult subjects
• 05:27and make them accessible to
• 05:29to the point where even a bioethicist can
• 05:32understand he's an extremely gifted teacher,
• 05:34and he's also, by the way,
• 05:35a very gifted neonatologist.
• 05:37He is the triple threat that
• 05:39people talk about on academics,
• 05:41and it's really been my
• 05:42pleasure and honor to.
• 05:43Have this journey with Jeff for
• 05:45the last many years.
• 05:46As you can see from that picture,
• 05:47you know I think Cliff is still celebrating.
• 05:49We're all still celebrating 100 years
• 05:51of Yale Pediatrics and so and so they
• 05:54wanted a couple of guys today who
• 05:56actually were here 100 years ago at
• 05:58Yale Pediatrics and so here we are.
• 06:01It's an absolute pleasure
• 06:02to introduce my friend,
• 06:04Jeff Gruen.
• 06:14You know if you ever want an emotional
• 06:18experience, be introduced by somebody
• 06:20who's been really your friend,
• 06:22not just a colleague for 35 years, it's.
• 06:26You can really get choked up about
• 06:27this stuff. Thank you for doing that.
• 06:29Right before I have to give a talk,
• 06:30I really appreciate that Mark. Thank you.
• 06:34Glad to help, Jeff, thank you.
• 06:38So I'm going to talk a little
• 06:40bit about our new program for
• 06:43learning disabilities research.
• 06:44I'm going to basically answer the
• 06:47five basic questions, why, what,
• 06:49how, where and who very simply.
• 06:52Why is early identification of
• 06:54learning disabilities important?
• 06:56What is the scope of the problem?
• 06:57How will early identification disrupt and
• 07:01change the current educational paradigm?
• 07:03Where can we make a difference
• 07:05and who are we?
• 07:07So let's get started and with all our
• 07:10research we start in the classroom.
• 07:12And that's because worldwide,
• 07:14about 15% of students everywhere
• 07:16struggle with learning disabilities.
• 07:18These include things you've
• 07:20heard of and things you haven't.
• 07:22Most common is dyslexia,
• 07:24also known as reading disability,
• 07:26specific language impairment,
• 07:27which is delayed onset of speech,
• 07:30verbal trait disorder,
• 07:31which is impairment of articulation,
• 07:34dyscalculia,
• 07:34a math disability and attention disorder,
• 07:38is better known to most folks.
• 07:39Is ADHD and ADD dot.
• 07:42But what I'm talking about
• 07:43today and every and all the kids
• 07:45that I'll be talking studies,
• 07:46I'll be talking about today are students
• 07:49in regular classes at regular schools.
• 07:52And with normal or above normal intelligence.
• 07:56For most children, a durable
• 07:58intervention can make a huge difference,
• 08:01and I'm going to show you that
• 08:02data in a in a few minutes,
• 08:04but in the meantime there are three
• 08:06critical things to know about reading.
• 08:09The first is that dyslexia or
• 08:11reading disability is really common,
• 08:14so if I take the 2000 fourth
• 08:16graders here in New Haven,
• 08:18and I take them,
• 08:19I give them any standardized
• 08:20reading performance assessment.
• 08:22Let's say comprehension or single
• 08:24word reading, and we.
• 08:26We graph them the number of
• 08:28readers at each point,
• 08:29low scoring versus high scoring.
• 08:31Not surprisingly,
• 08:32you'll get a normal distribution
• 08:33if you have enough students with
• 08:35a mean and what we call reading
• 08:38disability is basically a cut off.
• 08:39It's a cut off at the tail end.
• 08:41It's a lower end,
• 08:42so most places do around the 10th percentile.
• 08:45Some places do 15, some do 12 percentile.
• 08:48But in the United States we're talking
• 08:50about 5 to 10 million US schoolchildren.
• 08:53Again, these are in regular kids.
• 08:54These are regular kids in regular schools.
• 08:58The second thing to know is
• 09:00that it's genetic, and so again,
• 09:01if we take our distribution of children,
• 09:04let's say again 4th graders and we do
• 09:06say comprehension and we chart them.
• 09:08So we have a normal distribution.
• 09:10Not only will it have a mean,
• 09:11but it'll be a variance around
• 09:13the mean as well.
• 09:14And if we ask the factors,
• 09:15ask which factors can account for that
• 09:18variance and in fact non genetic factors.
• 09:21To the surprise of most people actually
• 09:23account for a very small percent,
• 09:25probably in the 20 to 30% range.
• 09:27Ras cumulative genetic factors
• 09:29account for the vast majority of
• 09:32reading performance or the variance
• 09:34around the mean for all of us,
• 09:36and that's why it's really important
• 09:37to pick our parents carefully,
• 09:39because this is what really is
• 09:41important for our performance
• 09:42in reading.
• 09:45So what we say is that genetic factors
• 09:47account for up to 80% of reading performance,
• 09:50and we call this concept heritability.
• 09:52And since genetic factors are mostly
• 09:55responsible for dyslexia and our
• 09:57performance and meeting our past
• 10:00was to discover reading genes.
• 10:02And so to identify these kids at
• 10:04risk when intervention works best,
• 10:06we developed a genetic screening panel.
• 10:09We collect saliva from saliva.
• 10:11We extract genomic DNA and we've
• 10:13done these studies in two forms.
• 10:15Our first one was about 10 years ago.
• 10:17Was the grad study of the genes
• 10:19reading and dyslexia study.
• 10:20The first study of its kind of a
• 10:22strictly African American Hispanic
• 10:24American kids in the United States
• 10:26using genetics and then more recently
• 10:28the longitudinal program called
• 10:30the New Haven Lectionum project.
• 10:32And these have been informative for kids
• 10:35that are European American background,
• 10:37Hispanic American background
• 10:39and African American background.
• 10:41And we published these in in
• 10:43in in peer review journals.
• 10:45Some pretty high quality peer review
• 10:47journals and that in a very nice very
• 10:50nicely that many of them are reproduced
• 10:52sometimes in other populations,
• 10:54even in other languages.
• 10:57So the third thing to know
• 11:00about reading is that.
• 11:02Is that dyslexia can be effectively treated,
• 11:04and so let me share with you data
• 11:07from my colleague Maureen Lovett
• 11:09at the University of Toronto and
• 11:12State Kit and Maureen study.
• 11:15Does randomized control trials and
• 11:17kids who struggle with reading and she
• 11:19does a very intense intervention that
• 11:21lasts for about a year and what she's
• 11:24done is she's retested them two years
• 11:26after completion of the intervention.
• 11:28So these are outcomes 2 years after
• 11:30completion of an intervention for
• 11:32children that were picked up in grade.
• 11:34One children in grade two children
• 11:36in grade 3/4, etc.
• 11:38All the way out to grade 12 and what
• 11:41you can see here pretty obviously is
• 11:43that these are the kids that perform
• 11:45the best that are most responsive.
• 11:47So about 75% of these kids will
• 11:50respond to intervention and will be
• 11:52reading at grade level two years
• 11:54after completion of the intervention.
• 11:57Whereas in contrast,
• 11:57if you look at kids that are
• 11:59picked up in high school,
• 12:00which is about 50% or so of kids in
• 12:02the United States are picked up.
• 12:04Was reading disability in high school
• 12:07or later only about 1/4 of those
• 12:09kids will actually be respond will
• 12:11be reading it ever brought up to
• 12:13grade level or be reading at grade
• 12:16level even two years afterwards,
• 12:17so early identification is
• 12:19obviously really important.
• 12:20That's the key.
• 12:22The key to effective intervention
• 12:24is early identification,
• 12:26but the window of opportunity is narrow.
• 12:29So let me show you why.
• 12:31Here's our current approach in
• 12:32our educational system today,
• 12:34and that's in private schools,
• 12:35public schools everywhere we
• 12:36call it the wait to fail model.
• 12:38You'll be very familiar with this,
• 12:40and so this would be typical development of,
• 12:42say, comprehension.
• 12:43But again, it could be single word reading,
• 12:45could be spelling of kids of
• 12:47typical children,
• 12:48the United States and around the world.
• 12:50Frankly, in a pre K all the way up through
• 12:52grade five you can see it's nearly linear.
• 12:54The increase in the performance
• 12:56from year to year.
• 12:58But there are children who begin to
• 13:01fall off once they are come face to
• 13:03face with a challenging curriculum,
• 13:05so this will usually happen
• 13:06at the end of grade one,
• 13:07definitely in grade 2 where
• 13:09they really begin to fall off.
• 13:11In the current model,
• 13:12what we do is we wait until
• 13:14they're really performing poorly,
• 13:16and then we do a standard intervention.
• 13:18And even if the intervention
• 13:20is intense and even if they're
• 13:21young enough to respond to it,
• 13:23they never really catch up,
• 13:25and so this gap is never really bridged.
• 13:28What we're proposing is a different model.
• 13:30What we'd like to do is identify the
• 13:33kids here early and then track them,
• 13:35and then when they even fall off,
• 13:37or even even just mildly,
• 13:40then we can initiate an early intervention,
• 13:43and which they would catch up,
• 13:45or at least attain very nearly
• 13:46Gray level reading.
• 13:47And that is then sustainable.
• 13:49But the key here is the early identification.
• 13:54So in in order to do that, that's where.
• 13:57The the identification of genes,
• 13:59genetic variants and creation of a
• 14:02genetic screening panel is so important.
• 14:04So how do we do this?
• 14:05How do we do this magic of this
• 14:08early identification?
• 14:08And so as an example for a minute,
• 14:10let me just talk to you about
• 14:12some of the work we've been doing
• 14:14over the last seven years on
• 14:15the New Haven Leccinum project.
• 14:20You know, hey, the goal in New Haven
• 14:22election project has been to explore
• 14:24the extent to which genetic variants
• 14:26correspond with response to intervention
• 14:28through whole genome sequence analysis,
• 14:30serial behavioral testing and
• 14:32serial functional MRI studies.
• 14:35It's a longitudinal study of
• 14:37normally developing children.
• 14:38Grades we would enroll children
• 14:40in grades one and follow them
• 14:42all the way through grades five.
• 14:44We recruited these children from
• 14:4632 New Haven public schools.
• 14:47These are the regular schools,
• 14:49not the schools that have children with
• 14:52intellectually impaired children in them.
• 14:53We recruited about 500 and
• 14:55following about 500 children,
• 14:57these included a parent questionnaire
• 14:59based on for past medical history in depth
• 15:03questions about socioeconomic status,
• 15:04learning disability histories,
• 15:06primary language and spoken in the home, etc.
• 15:09And then for each child we did 30X
• 15:13whole genome sequencing through saliva.
• 15:18We also did standard psychometric
• 15:20batteries that assess reading
• 15:22language executive function.
• 15:24Beginning in grade one roughly every
• 15:26six months, all the way through Grade
• 15:285 and the people who did the executive.
• 15:30These assessments were folks from our group
• 15:32and people who are trained to do this,
• 15:34so we didn't rely on school testing.
• 15:36It was our own group who
• 15:38actually did the testing,
• 15:39and we used standard batteries.
• 15:41So just for giving an example for those
• 15:43of you who are familiar with the field,
• 15:45these are standard neuro
• 15:47psychometric testing batteries.
• 15:48These are not batteries that we
• 15:49made up or tests that we made up.
• 15:51These were chosen by skilled
• 15:53neuropsychologists to be part of
• 15:56the educational assessment tool.
• 15:58They include the tower two or the test,
• 16:00averting reading efficiency subtests
• 16:02from the Woodcock Johnson and subtests
• 16:05from the Grey Oil reading test,
• 16:06and so we actually combined
• 16:08for the first study.
• 16:09I'm going to show you to this today is.
• 16:14It's what we call a composite of five
• 16:16subtests from these standardized testing,
• 16:19the first one is a sight word
• 16:21efficiency from the tower,
• 16:22where we ask children in a timed manner
• 16:25to read real words like cat, dog, etc.
• 16:29And then we score them for accuracy.
• 16:31They do it for about 45 seconds,
• 16:33so the next one is a
• 16:35phonemic decoding efficiency.
• 16:36It's called and so and so that
• 16:38memory doesn't play into this.
• 16:39We actually give them non words.
• 16:41Words like zoup.
• 16:42Again, it's timed and we score for accuracy.
• 16:46The letter word ID subtest Woodcock
• 16:48Johnson also looks at real words.
• 16:51It's not timed,
• 16:52but it's progressively more difficult,
• 16:54and here we score for accuracy.
• 16:56The number of words they accurately
• 16:58get and then the word attack,
• 16:59which is again back to non words again to
• 17:01to really look at their ability to decode.
• 17:04Also non timed and finally to
• 17:06look at reading fluency you have
• 17:08them read age appropriate passage.
• 17:10It's time we score for accuracy
• 17:13but also comprehension.
• 17:14So we combine these five subtests.
• 17:16Into a composite phenotype.
• 17:19And it's quantitative, that is.
• 17:21We could score it when we score
• 17:24it by a number,
• 17:25so we have high performers
• 17:27and low performers.
• 17:28And then the the trick here is
• 17:31to relate it to the genetics and
• 17:33we can do that using within the
• 17:36same children single nucleotide
• 17:38polymorphisms and just to re familiarize
• 17:41yourselves with what exactly a
• 17:43single nucleotide polymorphism is.
• 17:45I put up this little diagram that is
• 17:49diagramming a specific single nucleotide.
• 17:52Polymorphism has this horrific name called
• 17:58Rs 6935076. It's specifically
• 18:00located on chromosome 8 and its
• 18:03position is 24 million, 644,000,
• 18:07zero and 94 nucleotides from the top
• 18:12of the short arm of chromosome 8.
• 18:15And here you can see the sequence
• 18:17is very specific and because
• 18:18all of us carry 2 chromosomes,
• 18:20there are two representations of this area
• 18:22and of this specific position and person.
• 18:25One here is inherited from his mother
• 18:27ASI and from his father he's inherited.
• 18:30Also, I see and so we would say
• 18:32that for this snip at this point,
• 18:34which is which has a location
• 18:37specifically assigned to it,
• 18:39this person is homozygous for
• 18:41the C allele or CC.
• 18:43This person I a different person actually
• 18:47carries AT inherited from the mother
• 18:49and AT inherited from the father.
• 18:51So therefore this person would be homozygous
• 18:54for the teal or TT at this specific snip,
• 18:57and then finally we have the heterozygous
• 19:00individual who inherited AC from one parent.
• 19:02And a T from the other parent.
• 19:03So this person would be called the CT or
• 19:06the genotype would be a CT designating
• 19:09that that this person has one of each.
• 19:12So that's what a snip is.
• 19:13It's just a single nucleotide difference
• 19:16at a very specific location for everybody.
• 19:19So Rs.
• 19:226935076 that specific location can
• 19:24be identified in all of us as well
• 19:27as our 500 children enrolled in
• 19:29New Haven election on project.
• 19:31So it does take a look at these
• 19:33three at these three genotypes.
• 19:36The CC,
• 19:37the see T and the TT and what we
• 19:39can do for any individual child
• 19:41since we now can determine the
• 19:43CCC T or TT status of that child
• 19:46is then related to performance on
• 19:49the decoding composite phenotype.
• 19:51And So what you can see here is
• 19:53that the CC in in in a single
• 19:56individual might my correspond with
• 19:58low performance and asked sort of
• 20:00in the middle performance and AT&A.
• 20:03Why, in other words,
• 20:04it would appear here is that the
• 20:07C allele is detrimental and that
• 20:09the more see you have,
• 20:11the lower your performances
• 20:13in this decoding composite.
• 20:17So there's a relationship here.
• 20:18It's actually a linear relationship.
• 20:21More see the worse you do Morty,
• 20:24the better you do,
• 20:25and so if you do this over a lot of
• 20:28individuals then you can actually
• 20:30get a coefficient of correlation.
• 20:32The R-squared over those individuals
• 20:34and you could assign that value
• 20:37AP value a confidence value.
• 20:40And then you can graph that
• 20:42value for that individual snip.
• 20:44So here for this particular snip
• 20:486935076 located where I said 24
• 20:51million etc on chromosome 8 with a
• 20:54particular R-squared in 500 children,
• 20:56you can graph that on a P value
• 20:59on his P value.
• 21:00The confidence interval
• 21:01for that relationship.
• 21:02In fact,
• 21:03you can do this for a lot of snips
• 21:06on chromosome 8. Not just one.
• 21:10In fact.
• 21:11Every one of these dots represents
• 21:13a different snip genotyped in
• 21:15all 500 of our children.
• 21:17In fact,
• 21:18there are many snips on chromosome 8.
• 21:20There's well over 10,000, and so after.
• 21:23If you want to present them graphically
• 21:25again relative to their P value
• 21:27for their R-squared, you literally
• 21:29saturate or paint that chromosome.
• 21:32So represented here is every snip that we
• 21:35tested against the composite phenotype for
• 21:38decoding within our cohort of 500 children.
• 21:42And in fact we did this for every chromosome,
• 21:45so I just depicted chromosome 8.
• 21:47But this is chromosome 9,
• 21:49chromosome 1011, etc.
• 21:50All the way out to 22 and you'll
• 21:53notice that one is the widest because
• 21:56chromosome one is the longest,
• 21:58so it has the most number of snips
• 22:01and chromosome 22 is the shortest.
• 22:03So has the least number of Snips.
• 22:06This is real data.
• 22:07This is the real result we call this
• 22:09for obvious reasons in Manhattan plot.
• 22:12Right, and here's a peek at
• 22:13the Manhattan plot.
• 22:14In fact, for the decoding composite,
• 22:17we got a peak right here on chromosome 19
• 22:20by a number of snips in a very small area.
• 22:24And because of the magic of
• 22:25the Human Genome Project,
• 22:26we now can tell since we know precisely what
• 22:29the nucleotide number in chromosome it is,
• 22:32we can identify the gene
• 22:34that this corresponds to,
• 22:35and it corresponds to a gene that was
• 22:37not previously implicated in reading,
• 22:39but which we found to be very strongly
• 22:41have a very strong effect size called Gary.
• 22:45One in our cohort of 500 children.
• 22:48What do I mean by that?
• 22:49Let's go back into our cohort of 500
• 22:52kids and let's look at four different
• 22:54assessments of reading or reading subtests.
• 22:57The word, letter ID, word attack.
• 22:59Which word letter ID is timed,
• 23:02word comprehension, and reading fluency?
• 23:04That's the.
• 23:05That's the paragraph passage.
• 23:07And let's look at kids who have the
• 23:09Gary run risk allele here in orange,
• 23:11and you can see is that they enter
• 23:14first grade behind the kids in the
• 23:17same cohort at the same schools.
• 23:19At the same age in the same grade,
• 23:22at at, at, at, at,
• 23:24at a significant disadvantage.
• 23:25And if we follow these same kids
• 23:27because it's a longitudinal study,
• 23:29you can see they never catch up.
• 23:32Let me show you what that looks like.
• 23:34This is a comprehension,
• 23:36right,
• 23:36a fundamental and important things
• 23:38skill in reading.
• 23:39If we look at kids in grade at the
• 23:42start of grade one at the end of Grade
• 23:441 starter grade two end of grade 2 all
• 23:47the way up to the start of grade five,
• 23:49you can see is that children in oak.
• 23:51Our cohort here at the risk
• 23:53allele for Gary One,
• 23:54started off at a disadvantage
• 23:55to kids who do not carry any
• 23:57risk alleles for Gary one,
• 23:59and it's never really.
• 24:00They never really filled a gap.
• 24:02Even at the start of the Great Five,
• 24:04so it's sustained.
• 24:05It's a sustain effect over this age group.
• 24:12We can look further into Gary one we didn't
• 24:14know this so we looked in the text portal,
• 24:16which gives you expression data in different
• 24:19parts of the body and specifically
• 24:21in different parts of the brain.
• 24:23And to our surprise, Gary went well.
• 24:25It's not surprising that Gary
• 24:26wins expressed in the brain,
• 24:28but its strongest expression is
• 24:30in the cerebellum, the cerebellum
• 24:32hemisphere and total cerebellum.
• 24:35That was a surprise.
• 24:36But not really that much because what
• 24:38we know is that the cerebellum is
• 24:41intimately linked to the cerebral cortex,
• 24:43the cortical area where there are
• 24:47specific and specified specialized
• 24:49reading areas by a circuit or a
• 24:52cerebellar cerebral cortex loop.
• 24:55This is well known and in fact
• 24:57its support of a theory that was
• 25:00put forward in the 1990s called a
• 25:03cerebellar theory of reading disability.
• 25:05Nicholson Faucet observed that reading
• 25:07disability was also associated with
• 25:10deficits in cerebellar related functions.
• 25:12Distonia time estimation skill
• 25:15optimization and balance,
• 25:18and so they posited that the cortical
• 25:21cerebellar circuit shown here has
• 25:23an important role in reading.
• 25:24There has now been a whole lot
• 25:26more published.
• 25:27On the cerebellar theory of reading.
• 25:29And sometimes some people are in
• 25:31favor and some people are not,
• 25:32but we go where the science is taking us.
• 25:35And since Gary one is implicated,
• 25:36certainly by association studies,
• 25:39we pursue that.
• 25:41And so I don't really have the time
• 25:42to go through all the data and
• 25:44all the projects that we're going,
• 25:46so let me sort of summarize
• 25:49those briefly here.
• 25:50So our New Haven,
• 25:51Lexington project,
• 25:52which began to implicate the cerebellum,
• 25:54actually spurred a number of
• 25:57interesting projects Haley Dasilva
• 25:58in our lab has actually worked
• 26:01on a a program for processing and
• 26:04preprocessing imaging data that
• 26:06she calls Neuro Stack specifically
• 26:08made for a WS to Amazon Web server.
• 26:11And that's really important because
• 26:12a lot of the imaging data,
• 26:14for example from ABCD, is stored,
• 26:17allocated,
• 26:17processed and worked on in an
• 26:20Amazon Web Services up on the web.
• 26:22So in this is all cloud based work
• 26:24and Haley actually created this
• 26:27new tool that is now generally
• 26:29available as it's free and it's
• 26:32incredibly useful for neuroscientists.
• 26:33You know who don't want to get into
• 26:36the specifics of preprocessing and
• 26:38processing data. Tremendous work.
• 26:41We also calcium xerac in our lab who's
• 26:44been working with Young Frieder is unusual.
• 26:46Haley also,
• 26:47as well as Emily Curtain,
• 26:48has been working in ABCD.
• 26:50ABCD is a longitudinal study of
• 26:54typically developing 10,000 US
• 26:56children from across like 32 sites
• 26:58in the United States and they're
• 27:01getting cereal imaging studies
• 27:02as well as genotyping.
• 27:04Genotyping,
• 27:05one serial imaging studies and and
• 27:07as and some cognitive assessments
• 27:10to the NH Toolbox.
• 27:11That data is publicly available and
• 27:13so with kelson's been doing is he's
• 27:16been doing genetic correlation studies
• 27:18between the Leccinum project and ABCD,
• 27:20and in a way that he's been
• 27:22using these to create sort of to
• 27:24leverage our small data set with
• 27:27a larger data set. This is a theme
• 27:29that that goes on and on with us.
• 27:33Seeing Wang has been working by doing
• 27:36our due osis one I just showed you as
• 27:40well as T Ross is Tiwa Sizarr transcript
• 27:43transcript own wide association studies
• 27:45and So what she does is she goes back
• 27:49into GTX that expression data data
• 27:51data set in the brain either in the
• 27:53celebra ballimore the whole brain
• 27:55and she uses that information to
• 27:57wait the snips for the for the guasa.
• 28:00Therefore it's called that
• 28:02waser transcriptome.
• 28:03Wide Association study and she's and and
• 28:06we've been working with helping as well.
• 28:09Helping Zang Kate Connors from the
• 28:11group with young Frieders has been
• 28:13doing looking at our math data
• 28:15because I think initially,
• 28:17when I explained how the
• 28:19election project works,
• 28:20we do executive function which
• 28:22includes attention as well as math,
• 28:24math subjects as well.
• 28:26So Kate's been been really focusing
• 28:28on math and we'll be hearing some more
• 28:30data from that in the next couple of years.
• 28:33And then finally Steven Penny Agra.
• 28:35His spirit had had a collaboration
• 28:37with Indian Park over the stem Cell
• 28:40center and developing neurons human
• 28:42neurons from human embryonic stem
• 28:44cells and so the idea here being
• 28:46is that one of the things that's
• 28:47really held back.
• 28:48Translational Neuroscience is access
• 28:50to brain human brain material,
• 28:53and so unlike cancer,
• 28:54when you can get lots of material,
• 28:57in fact it's would be difficult.
• 29:00I would say it's impossible to get.
• 29:02Human brain material from from normal brains.
• 29:05And so in order to.
• 29:07If you want to study human neurons
• 29:09that what you do is you get human
• 29:12embryonic stem cells and then
• 29:14you begin to develop you.
• 29:18You can induce them to develop
• 29:20into human neurons along the way,
• 29:22and what Steven has done is
• 29:24he's knocked down using CRISPR.
• 29:26The expression of a prominent reading
• 29:31or dyslexia gene called KA 319 and
• 29:33what he's shown is that this puts
• 29:36the cells in a quiessence state,
• 29:38so these are neuronal progenitors
• 29:40arrested in a quiescent state.
• 29:42So to analyze that data which you know
• 29:45we've been doing a lot of sequencing there,
• 29:47is you.
• 29:48You are a few,
• 29:49I'm just doing a marvelous job
• 29:51again from Helping's group and one
• 29:52of our undergraduate students.
• 29:54Is he Lopez?
• 29:54So these are things that are
• 29:56currently ongoing.
• 29:57Major projects in the lab.
• 29:59I don't have time to talk about a
• 30:01whole lot today, but I just wanted
• 30:03to know that they're going on.
• 30:05OK,
• 30:05so the question is or what the
• 30:08question I posed before I left this
• 30:10slide was how do we do this magic?
• 30:13How do we identify these children
• 30:14early and when I said was we do this
• 30:17molecular genetic studies and I showed
• 30:19you a nice example focusing on dyslexia.
• 30:24But do we really disrupt by doing this?
• 30:27Do we really disrupt the current
• 30:29current educational program?
• 30:30Like how to disrupt the
• 30:32current educational paradigm?
• 30:33Is that really the question or is the
• 30:36question is how do we really disrupt
• 30:39the current educational paradigm?
• 30:40And I think that's really,
• 30:41really an important question for us,
• 30:43because doing our studies
• 30:45and publishing them,
• 30:46even publishing them in peer
• 30:48reviewed journals has been great.
• 30:50It's been great. You know,
• 30:51we've been able to get support for that,
• 30:53both private foundation.
• 30:54Age foundation and do
• 30:55these really cool studies,
• 30:57but are we really moving
• 30:59them into the classroom?
• 31:00And I would say I have to
• 31:02admit in fact that we were not.
• 31:03So if we really want to do this,
• 31:05where can we make these changes
• 31:07so we can translate our findings?
• 31:09Our ability to identify kids at
• 31:11high risk for learning disabilities
• 31:13at a young age when it's really
• 31:15important saying kindergarten?
• 31:16How do we get that adopted in
• 31:19public schools across America?
• 31:20Even in New Haven,
• 31:22across the state of Connecticut or America?
• 31:25So to do that,
• 31:27we really need policy level change.
• 31:30In the last five years,
• 31:31dyslexia and learning disability
• 31:33policies at the state and federal
• 31:36levels have improved significantly,
• 31:38most notably in the areas of
• 31:41teacher training and universal
• 31:42dyslexia screening in grades,
• 31:44kindergarten through third grade.
• 31:4841 states today have universal
• 31:50evidence based screening for dyslexia,
• 31:53including Connecticut and Massachusetts.
• 31:56And the feds have clarified that you
• 31:58can now use this term Once Upon you couldn't.
• 32:00You could use this term when,
• 32:03when,
• 32:04when teachers create the iep's,
• 32:06the individual educational
• 32:07programs that are so important in
• 32:10mandated for each child that has
• 32:12a disability learning disability,
• 32:1432 states across the country provide a
• 32:17list of approved evidence based screeners.
• 32:20None of them are genetic.
• 32:23So our goal is to pass legislation
• 32:26that includes reliable and validated
• 32:28genetic screening for risk of, say,
• 32:31dyslexia or any learning disability.
• 32:34And get it,
• 32:35get it on the improved list
• 32:37of evidence based screeners.
• 32:40This would allow parents to screen
• 32:42their child as early as even birth,
• 32:45but definitely pre K for risk of
• 32:46any of the learning disabilities,
• 32:48including dyslexia.
• 32:49It would require school districts
• 32:51to take those results into account
• 32:54when when they create the iips,
• 32:56the individual educational
• 32:57program plans and the 504 plans.
• 33:02And this would enable children
• 33:04finally to receive an evidence based
• 33:06reading instruction or intervention
• 33:08method at the very earliest
• 33:10stages of reading acquisition,
• 33:12when they are most important
• 33:14and are most likely to work.
• 33:17So I've last 20 minutes or so.
• 33:20I presented a hodgepodge really
• 33:22of information from a number
• 33:24of seemingly discordant fields.
• 33:26I presented some epidemiological data
• 33:29showing what is the frequency of of.
• 33:31Well, I presented reading disability,
• 33:33but in fact of learning disabilities and
• 33:35it's somewhere in the 10 to 20% range,
• 33:37I presented an intervention
• 33:39program from my colleague or or
• 33:41the results of an intervention
• 33:43intense intervention program for
• 33:45my colleague Maureen.
• 33:46Love it at the University of Toronto
• 33:48and showed how important it is.
• 33:50For early intervention and for
• 33:52it to work and to be and for
• 33:55its effects to be sustained.
• 33:57I presented some genetic genetic studies,
• 33:59both molecular genetic studies
• 34:00and statistical genetic studies
• 34:02to show the importance of
• 34:03genetics and why genetics should,
• 34:05could and should be used for early
• 34:07screening to identify kids at high
• 34:09risk for attention disorders,
• 34:11reading disabilities,
• 34:12language disorders, etc.
• 34:15And I presented an education paradigm
• 34:17that doesn't work the wait to fail role
• 34:20model and an alternative to that model.
• 34:22And finally I I presented some
• 34:25policy stuff and so the fact is
• 34:28is that it's a bit of a mess,
• 34:30so to find a form that accommodates
• 34:33the entire mess that I've just
• 34:35presented and to unite these from my
• 34:38friend Samuel Becker from 1961 and
• 34:40to unite these seemingly unrelated
• 34:43initiatives under a single umbrella
• 34:46this year.
• 34:48With a lot of help from Gene Shapiro,
• 34:50Cliff Boag and the Dean,
• 34:53we created the Yale Program for
• 34:57Learning Disabilities Research.
• 34:59Our program is multidisciplinary.
• 35:01It covers the fields of neuropsychology,
• 35:04Biostatistics,
• 35:05education, neuroimaging,
• 35:06and genetic and the people
• 35:09who come into this group.
• 35:12They know their field well,
• 35:14but neuro psychologists who come in
• 35:15don't know a whole lot about genetics.
• 35:18Geneticists that come in don't
• 35:19know a whole lot about education,
• 35:22often not a whole lot about neuroimaging,
• 35:24so it's some very important and
• 35:26we really stress that we begin to
• 35:28learn each other's vocabulary that
• 35:29we really interact personally.
• 35:31Although this year it's been
• 35:33difficult to interact personally and
• 35:35so we can inform each other studies
• 35:37and help and work collaboratively
• 35:38collaboratively within the lab.
• 35:40And I think we've been pretty successful.
• 35:42I think that's like,
• 35:43for example,
• 35:44the study I presented from the
• 35:45Haven election on project.
• 35:46You can see that's a combined effort from
• 35:50neuropsychologist geneticist Biostatistics.
• 35:52I didn't show you the neuroimaging data,
• 35:53but it's remarkable how well that works and
• 35:56now we're moving into education with a PhD,
• 35:58PhD,
• 35:59postdoc in education recently joined the lab.
• 36:01So these are great initiatives
• 36:03and show how we're really blurring
• 36:05all the lines amongst all these
• 36:07different disciplines.
• 36:08But we're also trying to go cross
• 36:10campus and reach out and bridge
• 36:12the gap to other schools to other
• 36:14students and the other professional
• 36:16schools in the university.
• 36:18So I'm especially proud to say that
• 36:20we've been working with the folks at
• 36:22the Yale Educational Studies program,
• 36:24and we'll be offering a A1
• 36:27semester long course,
• 36:28mostly for undergraduates
• 36:29beginning this fall.
• 36:31This is the first course that they've been.
• 36:33Offering on learning disabilities and
• 36:35it's a full I think it's 17 lectures
• 36:37over the course of the semester,
• 36:39so this is developed by the
• 36:41folks in our in our group most.
• 36:44There's no Lee,
• 36:46Kim Tsujimoto and John Boston,
• 36:49and so they're prepared to present this.
• 36:51It is currently under review, but it's it's.
• 36:53It looks like it's going to start
• 36:55in the fall. We work really strongly
• 36:57with the folks in the computational
• 36:59biology and bio for Mattix program,
• 37:01but they have members from those
• 37:03programs in our lab and plus we
• 37:05present to them on a regular basis.
• 37:07This is a really extraordinary new
• 37:09program here at the School of Management.
• 37:12It's called the broad center or
• 37:14the Broad Center for Educational
• 37:16Leadership and Public Education.
• 37:18It's a brand new initiative.
• 37:19I think there are about a dozen broad
• 37:21Centers for this across the country.
• 37:23It was just started this past
• 37:24fall that brings in educational
• 37:26leaders from around the country.
• 37:28These are superintendents and school
• 37:30principals in the largest districts in the
• 37:32United States and they engage in a yearlong,
• 37:34transformative leadership
• 37:35program in public education.
• 37:38And so we're in contact and we're
• 37:39working with these folks as well.
• 37:41And then finally,
• 37:42of course,
• 37:42we're based here in the Department
• 37:44of Pediatrics and Genetics,
• 37:45where which is our home base and
• 37:48where we're going to also be reaching
• 37:51out to residents and hopefully.
• 37:53Increase the exposure they're
• 37:54having to learning disabilities
• 37:56that they're going to encounter
• 37:58when they enter practice as well,
• 38:00'cause it's so common.
• 38:02So this is our Yale program for
• 38:05Learning Disabilities Research.
• 38:06Its comprehensive, it's large,
• 38:08it's ambitious.
• 38:10We just got started this past September.
• 38:12These are the different components
• 38:14I tried to present to you,
• 38:15and with that I'm happy to take
• 38:18questions and also a big shout out
• 38:20to all these wonderful people who
• 38:21make this sort of research possible,
• 38:24as well as our funding groups
• 38:26from private foundations,
• 38:27them and foundations to the
• 38:28NIH as well as to individuals.
• 38:31And of course, thanks to all the children.
• 38:33Families who participated in
• 38:34all these studies.
• 38:36So if there are questions,
• 38:37I'm happy to take them.
• 38:44OK, Jeff, thank you so much.
• 38:46That was amazing.
• 38:47That was fantastic.
• 38:48Now we do have questions.
• 38:49I mean, I invite folks to submit
• 38:52questions via the chat or the Q&A,
• 38:54but we've got some questions already.
• 38:56Doctor Who in one of your
• 38:58earlier slides indicated that
• 39:00heritability for dyslexia is 0.80.
• 39:02How much of that is accounted
• 39:04for it by the SNP and Gary one?
• 39:06Is there a polygenic risk score for dyslexia?
• 39:09If so, how much variance?
• 39:11Does it account for?
• 39:12That's a great question.
• 39:14Thank you for asking so as clearly
• 39:17the you know Paul knows is that
• 39:20there's really two types of.
• 39:23Yeah, of variants that you can account
• 39:25for heritability that you can account for.
• 39:27There's broad sense heritability,
• 39:29and there's narrow sense heritability.
• 39:31When I say 80%, it's it's broad sense
• 39:34heritability that is when you look
• 39:36at twin studies and family studies,
• 39:38and then you see,
• 39:39and then you ask the question,
• 39:40what's the concordance rate between
• 39:42siblings who are affected, say,
• 39:44was reading disability in those that aren't,
• 39:46and you compare them the the classic
• 39:48example would be identical twins
• 39:50which share 100% of their genome.
• 39:53The concordance rate there versus
• 39:55the concordance rates and non
• 39:57identical twins which only share
• 39:58on average about 50% and so if
• 40:00you do those sorts of those are.
• 40:02Those are standard heritability studies
• 40:04in the 1980s and they would say that
• 40:07the genetic component is about 80%.
• 40:10There has been a polygenic risk score.
• 40:14Publication from Robert Plomin's
• 40:17group from the UK.
• 40:19He has the largest collection of twins,
• 40:22I think in probably the largest one is
• 40:24in Australia but he has the largest
• 40:26one that was reading assessments.
• 40:28I think it's 10,000 twins and he
• 40:30was able to account for all snips
• 40:32that he looked at and he looked
• 40:34at a genome wide panel.
• 40:36I think about 700,000 snips.
• 40:38He was able to account for
• 40:40about 8% of the heritability.
• 40:42This is pretty common
• 40:44for polygenic disorders.
• 40:45That is that even if you look at cancer etc
• 40:48etc etc and just look at common variants,
• 40:51which is what's represented and a
• 40:53single nucleotide polymorphism panel,
• 40:55you generally there's a huge gap
• 40:57between broad sense heritability
• 40:58and narrow sense heritability.
• 41:00Now, to answer you Paul direct
• 41:02your question directly, Paul,
• 41:03if you look at any single snip,
• 41:05you're looking only at a fraction
• 41:07of the heritability that is Gary.
• 41:09One explains only a tiny amount,
• 41:12so all that's why.
• 41:13And I didn't get into it on this talk,
• 41:16but in previous.
• 41:17Oxide, I mentioned it is that is
• 41:19that dyslexia language acquisition,
• 41:21language impairment,
• 41:23verbal trait disorder,
• 41:25dyscalculia,
• 41:25or the all these are polygenic disorders.
• 41:28You have to be lucky enough to
• 41:30have the smorgasbord of the right
• 41:32variants all at once for that.
• 41:34For that to happen,
• 41:35it is rarely a single gene disorder,
• 41:38although we have been looking
• 41:40at rare variants,
• 41:41and it does occur from time to time.
• 41:43None of them are in Gary want.
• 41:47Thank you Jeff. A much more general question.
• 41:48How did you become involved in this research?
• 41:52Uh. So. Most people think that you know,
• 41:58Jeff. He's a pediatrician,
• 41:59and so he cares about children
• 42:01and he cares about reading and he
• 42:03got somehow seduced into genetics.
• 42:05But actually it's the opposite.
• 42:08And yes, I'm a pediatrician.
• 42:10Yes, I care about children.
• 42:11Yes, I care about reading,
• 42:12but the way I got in was during
• 42:15fellowship with with you Mark,
• 42:17I actually got first.
• 42:19Initially I was in cell biology and then
• 42:21I got seduced over to molecular genetics
• 42:23just at the time of the beginnings.
• 42:25Of the Human Genome Project,
• 42:27and I thought, you know,
• 42:27this is a pretty cool thing,
• 42:29and so I ended up in a lab that
• 42:31does that was really pioneering
• 42:33many of the methods for the human
• 42:35Genome project and my first.
• 42:37This was insuring Weismans lab here at Yale,
• 42:39and at that time what we were doing is
• 42:42remember there is no human genome project.
• 42:44It was just starting off the ground.
• 42:45Nobody really knew how to
• 42:47clone the human genome,
• 42:48and so one of my early
• 42:49projects was the clone.
• 42:50The short arm of chromosome 6 and then one
• 42:52day Sherm came up to me and said, Jeff,
• 42:55why do you clone the hemochromatosis?
• 42:58And of course, I said sure you know,
• 43:00I'm a pediatrician,
• 43:01I don't really know very
• 43:02much about hemochromatosis.
• 43:04It sounds like a disease of adults and
• 43:07Alcoholics, and he goes no, no, no you.
• 43:08We we've known that it's genetic
• 43:10for a long time,
• 43:11and you've already cloned it.
• 43:13It's one of your one of your 6 or
• 43:157000 tubes you have in your freezer,
• 43:17so just go figure out which one it was,
• 43:19and so that's how it got started.
• 43:21We got scooped by a private
• 43:23company several years later,
• 43:24but I had all these resources
• 43:26for chromosome 6.
• 43:27I looked around and there was this locus.
• 43:29There was this location of a strong
• 43:32genetic effect on the short arm
• 43:34of chromosome 6 for which I was,
• 43:36I think,
• 43:36at that time probably the only
• 43:38person in the universe who actually
• 43:40had complete coverage in new
• 43:42were all the markers were,
• 43:43and that's how I got started.
• 43:45And so the truth is, yes, I'm Peter, Trish.
• 43:48And yes, I practice medicine.
• 43:49Yes, I care about children.
• 43:51I care about reading,
• 43:52but the reason I really jumped into
• 43:54this is 'cause I had a strategic,
• 43:56scientific advantage.
• 43:57And I took advantage of it.
• 44:01Thank you. From Steve uptegrove.
• 44:05He even has, unfortunately a well
• 44:07known history for a high prevalence
• 44:08of childhood lead poisoning while
• 44:10childhood lead exposure is supposed
• 44:12to be documented on all children PE
• 44:14forms upon school entry in Connecticut.
• 44:16This information is not routinely been used
• 44:18to identify those at high risk for the
• 44:21same disabilities you were concerned with.
• 44:23Rather, they come to the light
• 44:25only by the same weight to fail,
• 44:27model the wait to fail model you mentioned.
• 44:29What has been lacking are the
• 44:31resources in schools for particularly
• 44:33districts like New Haven, Kubara,
• 44:35Heavy burden of potentially at risk hits.
• 44:39Steven, that's a great question.
• 44:41First of all, I want to tell and just,
• 44:43you know, reach out to Steve is that
• 44:45when we first started our studies
• 44:47here in New Haven Public Schools,
• 44:49Steven was one of the earliest
• 44:51persons that I reached out to because
• 44:54I think at that time Steve you
• 44:56were either on New Haven School,
• 44:58you were on the school board or you
• 45:00add connections to the school board.
• 45:02And so you were one of the first people
• 45:04and you were wonderful and I greatly
• 45:06appreciate all the help that you
• 45:08offered and all the advice that would.
• 45:09Proved to be very, very useful.
• 45:12Second of all is that I'm not
• 45:15discounting the environmental exposures,
• 45:17they're huge and and they're a big deal,
• 45:19and they are certainly a big deal
• 45:22to different socioeconomic groups.
• 45:23I can't answer your your your excellent
• 45:26question directly because that would
• 45:28that would require is probably you know
• 45:30more lead testing and more documentation,
• 45:33but what I can say is that we've
• 45:35begun as part of the Yale Program
• 45:37for Learning Disabilities Research.
• 45:39We've begun a formal program to look
• 45:42at the electronic medical record we
• 45:44started looking at by just looking
• 45:47at coding for learning disabilities.
• 45:49And we we're doing this project
• 45:52collaboratively with Emily Power,
• 45:53so so I think we're just starting to
• 45:55get the data at interesting enough.
• 45:58Interestingly enough,
• 45:58we're probably looking right now
• 46:00at about 40,000 kids in total,
• 46:03and amongst the 40,000 kids there.
• 46:05We're looking for codes that would at
• 46:07least implicate some learning disability.
• 46:09From there, we'll go on and that is.
• 46:11We'll try and peel the onion and
• 46:13get to be well.
• 46:14What is the real learning
• 46:15disabilities that they have could be?
• 46:16They could? Could they be overcoated?
• 46:18Could be undercoated,
• 46:19but one of the things that we
• 46:21will definitely look look for now
• 46:23that you've mentioned it.
• 46:24And thank you for asking is we'll
• 46:26look at lead levels 'cause we can do
• 46:28that in the electronic medical record
• 46:30and we'll try to see if that is a
• 46:31significant factor in these things.
• 46:34I suspect it is,
• 46:35but I also suspect there correlate
• 46:37strongly with socioeconomic status,
• 46:39which is something I didn't mention
• 46:41in the GWAS that I presented.
• 46:42But in that GWAS it is corrected
• 46:45for socioeconomic status.
• 46:46We always do that as well as sex and age,
• 46:50and so that's an important part.
• 46:51But I'm going to add lead to the list.
• 46:53I think that's a great question.
• 46:57Jeff from Jim Pelligrini Jeff.
• 46:58Truly amazing.
• 46:59You mentioned executive functioning.
• 47:01Any research at the genetic level.
• 47:02Here schizophrenics can have
• 47:04excellent verbal and reading skills,
• 47:06but severely poor executive function.
• 47:11No, I I've been very careful to
• 47:13stay away from the psychosis Jim.
• 47:16That's a that's a well populated
• 47:19field to be politically correct.
• 47:22And so I, you know, sort of stay in my
• 47:25lane and within within with children
• 47:27and typically and specifically.
• 47:29And typically developing children
• 47:31if you're not typically developing.
• 47:34That is, if you have a neuro
• 47:36psychosis or even autism.
• 47:38We've been excluding those
• 47:39children from our studies.
• 47:41Really trying to focus on those
• 47:43pathways and circuits that are
• 47:45specific for either reading
• 47:47language or executive function.
• 47:49Having said that,
• 47:51we have extensive executive function
• 47:53assessments on all 500 of our kids
• 47:56in our longitudinal study as well as
• 47:59the 1300 kids in our initial cross
• 48:01sectional study called the Grad study,
• 48:03and so we've actually performed
• 48:05our first juos and tiwas on that
• 48:07data specifically on attention,
• 48:09and I can tell you that our
• 48:11preliminary results.
• 48:12Look really,
• 48:12really good,
• 48:13so I think yes we will have some
• 48:16jeans and genetic variants that
• 48:18will correspond beautifully and and
• 48:20will identify risk for attention.
• 48:22I can tell you is that that there
• 48:24are a lot of good people in this
• 48:26field and a number of handful
• 48:27of genes for us specifically for
• 48:29attention have been identified,
• 48:31and so I think this is a very
• 48:33cool area of interest.
• 48:35We continue to pursue it
• 48:37and I'll keep you posted I.
• 48:39I think we'll have something solid.
• 48:42I'm hoping the manuscript will
• 48:43go out before June.
• 48:47Thanks Jeff from Julia Rosenberg.
• 48:49Thank you for a great talk.
• 48:51I'd love to learn if English language
• 48:53learners have been included in these
• 48:54studies in New Haven schools and if
• 48:56you have any insight into how some of
• 48:58these findings may factor in for those
• 49:00who are English language learners.
• 49:02Thank you. Hi
• 49:03Julia, so the short answer is yes,
• 49:06you know there are.
• 49:07So if you're going to be in New Haven
• 49:09public schools, you're going to be.
• 49:11You're going to have English
• 49:13language learners. So the.
• 49:15We for our initial study of the grad study,
• 49:19we required that so that
• 49:21was an older age group,
• 49:23so those kids were nine,
• 49:26roughly 9 years old,
• 49:27and we required that they have been at
• 49:30least three years in instruction in the
• 49:32United States to be in our studies.
• 49:34Remember that study?
• 49:35The grad study was the 1st,
• 49:37and remains the only study of
• 49:40underrepresented minorities of
• 49:41genetics and reading disability effort,
• 49:44and so, and we identified variants.
• 49:46Do that and publish variance through
• 49:48that and so that was for the grad
• 49:50studies in the haven next rental project.
• 49:53We didn't have much.
• 49:55Basically they could get by
• 49:57with a cursory understanding.
• 49:59In English we didn't.
• 50:02We didn't offer in the initial
• 50:04study the grad study we offered
• 50:06Spanish language testing.
• 50:08We actually, interestingly enough,
• 50:09we really see a difference between
• 50:12English and testing them in English
• 50:14or Spanish and the New Haven next.
• 50:16Project just about all the kids
• 50:18are pretty proficient in English,
• 50:20but it wasn't an exclusionary criteria.
• 50:24Thanks Jeff. Question from Susan Blvd.
• 50:28Do you know why New York and
• 50:30California were two of the states that
• 50:32were not doing dyslexia screening
• 50:33and any concerns that prenatal
• 50:35screening might be used to terminate.
• 50:37Quote non ideal End Quote babies so
• 50:41I can't tell you about California New York.
• 50:43Sorry but I do know that there that
• 50:46they haven't passed legislation
• 50:47yet for universal screening.
• 50:49I suspect it has a lot to do with
• 50:51money and so you know these are
• 50:53expensive things, but I don't.
• 50:55I don't know the specifics.
• 50:56Regarding prenatal diagnosis,
• 50:57I get this question a lot.
• 50:59People find me, they call me and
• 51:01this is what I tell them and it,
• 51:03you know I I don't work
• 51:06with children with dyslexia,
• 51:08I'm a neonatologist,
• 51:08but I my group does and and and
• 51:11certainly I interact with people
• 51:13from around the world that work with
• 51:16children with reading disability
• 51:18and they tell me two things.
• 51:19Yes, they struggle.
• 51:21And they also tell me that a
• 51:23significant number of them have
• 51:25other really significant talents.
• 51:26For example,
• 51:27there's a group that has told
• 51:28me that about 20% this is,
• 51:30and I've I've heard this from multiple
• 51:32neuropsychologists that there's
• 51:33probably somewhere between 10 and 20%
• 51:35of kids with really severe dyslexia.
• 51:37Have this special ability to be able to
• 51:40see things in three dimensional space.
• 51:43It's really a marvel of ability to do,
• 51:46and so if you if you look at all these
• 51:48examples of successes and people
• 51:49who have had pretty severe dyslexia.
• 51:52Done well business and academia
• 51:53etc and they they have been tested
• 51:56and they really do have dyslexia.
• 51:58The question is why would you
• 52:00want to exclude them?
• 52:01Why would you want to
• 52:02do an early termination?
• 52:03So I do my very best to when people
• 52:06call and I think I've been pretty
• 52:09convincing is that this would
• 52:10not be something that he won.
• 52:12I would either test 4 or #2 recommend
• 52:14that it be test four or certainly
• 52:17predicated termination on because
• 52:18it makes no sense whatsoever.
• 52:20These kids are.
• 52:22Are phenomenal,
• 52:23and they turn into phenomenal adults
• 52:25and incredibly happy and productive.
• 52:27They work hard, they struggle.
• 52:29There's no question about it and
• 52:31their parents struggle as well,
• 52:32but they do universally, really well.
• 52:36Well, I think that these kids also may
• 52:39have an even brighter future based on
• 52:40some of the work you've been doing.
• 52:42Jeff, I mean the the ability to
• 52:45identify these kids early and
• 52:46really change a lot of lives.
• 52:49I have a from auto Phoenix.
• 52:51Ask says this is fascinating and so
• 52:53so important that I'm thrilled that
• 52:54you were driving to policy with this
• 52:57for school aged children earlier than
• 52:59reading failure is language delay.
• 53:01Does any of the data point to a way to
• 53:03screen genetically for this in order
• 53:06to intervene even before school age?
• 53:08If we could do newborn screening
• 53:09for language delay,
• 53:10we could start early
• 53:12intervention immediately.
• 53:13So I should pay you out 'cause that was like,
• 53:16that's like the question about language
• 53:18delay or specific language impairment and
• 53:20reading disability comes up all the time.
• 53:22Roughly, if you if you if you if
• 53:26you do a really careful history on
• 53:28children with reading disability,
• 53:30about a third of those kids had had
• 53:34very significant language delay,
• 53:36that is delay in onset of language again
• 53:38just to remind everybody I'm talking
• 53:40about typically developing children.
• 53:42Children with normal IQ's, but if they're
• 53:44struggling and they clearly have,
• 53:46you know, and they're tested,
• 53:47and they really have a reading
• 53:48disability if you do a careful history,
• 53:50you'll find that roughly a third
• 53:52of those kids.
• 53:53Well, it had language impairment,
• 53:54delayed onset and speech.
• 53:5618 months, 22 months,
• 53:5724 months even older than that,
• 53:59there is a significant overlap and when
• 54:01we look at the genetic association of
• 54:04jeans that were primarily identified
• 54:06for reading and then you go around and
• 54:08you and you use those as candidate
• 54:10genes for looking at language,
• 54:11they overlap a great deal.
• 54:13There are some unique genes specifically
• 54:15for language impairment and there
• 54:16are unique genes specifically
• 54:18for reading disability,
• 54:19but the overlap is significant
• 54:20and that can explain why there's
• 54:23the shared heritability.
• 54:24If you go forward and you look
• 54:26at kids who are diagnosed with
• 54:28specific language impairment,
• 54:29again,
• 54:30about 20 to 30% of those kids will
• 54:32get into trouble by the end of first
• 54:34grade beginning of 2nd grade and will
• 54:36have reading disability so those kids
• 54:38have to be very carefully watched as
• 54:40far as newborn screening is concerned.
• 54:43When we ask the question a few years ago,
• 54:46how many tests in a newborn
• 54:47screening were done by DNA?
• 54:49The answer was zero.
• 54:51That's slowly changing,
• 54:53and so DNA screening.
• 54:55Not only is it potentially
• 54:57incredibly sensitive and specific,
• 55:00it's scaleable.
• 55:01That means the cost can be incredibly
• 55:04low and so that's what the hope is,
• 55:07and so we're pursuing various ways
• 55:11to get states to think about this,
• 55:13or at least to fund this at
• 55:15least as a pilot project.
• 55:16But that's exactly right auto.
• 55:18That's what we're trying to do.
• 55:21I think we have time for one more question.
• 55:23Jeff from Joe Abney.
• 55:24Singer exciting work.
• 55:25Have you moved the genetic testing
• 55:27to the point of the test that has
• 55:29a receiver operating curve that
• 55:30provides data on sensitivity,
• 55:32specificity, positive predictive
• 55:33value and negative predictive value.
• 55:36That's well, let me finish the question here.
• 55:39Hold on to that since kids with
• 55:40dyslexia are a heterogeneous group,
• 55:43does your work focus on the most common
• 55:45phenotype of phonological awareness,
• 55:46or do you have data on the
• 55:49orthographic variants?
• 55:51OK, so let me attack the first
• 55:52part of the question. First.
• 55:54Joe, it's a great question.
• 55:55Short answer is no,
• 55:57and and the reason is because
• 55:59in or certainly we could do it
• 56:01retrospectively and when we do
• 56:03we get a reasonable sensitivity
• 56:05and incredibly good specificity.
• 56:06But as far as a receiver operating
• 56:08curve you really want to do that.
• 56:10We could do that, you know,
• 56:13looking backwards,
• 56:13but the real way to do this would
• 56:16be a uh as a looking forward that
• 56:18is your identified or you just.
• 56:21You take a cohort of children,
• 56:22follow them for three to five
• 56:24years and and and do testing,
• 56:25and that's what the next stage is so we
• 56:27can do that receiver operating curve.
• 56:29So we're not there yet,
• 56:30but I think we're getting
• 56:32closer to being there.
• 56:33As far as subtests are concerned,
• 56:35this is the Holy Grail of neuropsychologists.
• 56:37I get asked this question all the time.
• 56:39Can you tell me?
• 56:40Does the reading disability
• 56:41that we're seeing in this child?
• 56:43Is it more to do with orthographic coding?
• 56:45Is more to do with phonological
• 56:47awareness and and and so then the
• 56:49intervention might be a little different
• 56:51and I can tailor to the child.
• 56:52We'd love to do that.
• 56:54The thing to remember is that
• 56:56there is no orthographic coding,
• 56:58and for the the the for the non
• 57:00informed of the group when we're
• 57:02talking about is really spelling
• 57:04there is no spelling gene.
• 57:05There's no grammar gene,
• 57:07there's no decoding gene.
• 57:09Remember genes encode proteins,
• 57:10proteins make up the receptors and
• 57:13the neurotransmitters or the brain.
• 57:15They make up the glea, the neurons, etc.
• 57:17The workhorses of the cell,
• 57:19and so they worked together
• 57:21in combination with different
• 57:22systems in order to enable us.
• 57:24To do these very complex very human
• 57:27things called decoding or reading
• 57:29and spelling and music as well.
• 57:32And so it it's not.
• 57:33It's it probably isn't going
• 57:35to be a single gene,
• 57:36but it may be a panel of genes
• 57:39or a panel a panoply perhaps,
• 57:42or a profile of certain variants
• 57:44that may be more weighted towards,
• 57:46say, decoding versus spelling,
• 57:48but we don't know yet.
• 57:50The studies aren't large enough yet.
• 57:53Well Jeff, you know you.
• 57:54You left plenty of time for
• 57:56Q&A and our time is up,
• 57:58but I apologize to the many people.
• 58:00There's a lot of enthusiasm for
• 58:02this talk and many questions and
• 58:03comments which we didn't get to.
• 58:05So let me just congratulate
• 58:06you on a marvelous talk and I
• 58:09think that takes up our hour
• 58:10and thanks everybody for coming.