- [Worker] All set?
- All set. - The straighter you go.
- [Crowd Member] But I had to ask if we were going straight.
- [Announcer] I'd like to introduce, I know you all
know her, Mary Cushman.
So Mary's the university's distinguished professor
of medicine and pathology and laboratory medicine
here at LCOM.
She is vice chair for emerging researchers,
the Department of Medicine, and is also director
of the Thrombosis and Hemostasis Program
in the Vermont division.
And of course, as you all know,
she's co-director of VCCBH with Mark Nelson.
Mary completed her MD residency and fellowship here at UVM
and her Master of Science and Epidemiology at Harvard,
and she's been continuously funded now for over 28 years.
Mary's work focuses on positive factors for heart disease,
stroke, cognitive impairment, venous thrombosis,
and others using molecular epidemiology approaches.
She's very prolific.
She's authored over 750 original research articles
and she has an h-index 160.
Mary has won many, many awards,
including the American Heart Association
2018 Population Research Prize
recognizing research achievement, the AHA 2020 award
Meritorious Achievement for impact in promoting careers
of early professionals and women in science and medicine.
She is one of only three Vermont physicians
selected as a member of the Association
of American Physicians and today she'll be talking
about her work in stroke and cognitive impairment
in an ongoing national biracial cohort
funded by NIH that's a REGARDS study, which is Reasons
for Geographic and Racial Differences in Stroke.
Mary? - Thank you.
So I just put up some objectives for the talk.
We'll start with discussing risk factors for stroke
and cognitive impairment and the commonalities in those
and then discuss the role of biomarkers
in determining risk and studying pathogenesis
of cognitive impairment and stroke, and then
utilize this framework to discuss research
on biomarkers of brain health and how this can help
improve brain health in the population.
So I'll be discussing racial differences in health,
comparing Black Americans to white Americans,
and reference to race is in the context
of understanding social determinants of health.
We all know race is not a biological construct.
There are cases where we might consider genetic markers
that are more common in people of African ancestry,
and which in turn are more common
in Black than white people in the United States,
but race is a different thing than ancestry.
Just making sure we're on the same page.
So some basic facts to get everybody also on the same page.
- [Crowd Member] Hey, I was curious,
is that NIH definitions or does that come from...
Where does that, the epidemiology, this-
- Where does what come from?
- [Crowd Member] Oh, the last slide.
Is that- - It's just the fact.
It's just the fact.
- Yeah. - It's our current
understanding of what race in America, you know...
Race is a social construct, not a biological one.
- [Crowd Member] So is that common across
all publications, across journals?
- [Crowd Member] It is among everybody I know, yes.
- Okay. - And it was
at my journal that I edited.
- I don't publish in this area so I don't use that
when I describe basic science with you, so I'm just-
- If you wanna talk about-
- You know, when you do both-
- -the genetic architecture or whatever,
you can talk about ancestry, which is more complicated
in a way because ancestry is,
most people have multiple (chuckles) ancestries.
So yeah.
- [Crowd Member] Okay.
- Okay, so stroke is the fifth leading cause of death
and the leading cause of disability.
Well, I was corrected recently that it's among
the leading causes of disability
and every 40 seconds someone has a stroke.
So it's a disease that I have to say
working in stroke now for more than 20 years, kinda hard
to get stroke research published in mainstream,
like general medical journals.
They're just not as interested in it for some reason
compared to like birth and cancer.
But it's an important morbid condition,
leads to cognitive problems and dementia as well itself.
And dementia is also rising rapidly, mostly due
to the aging of the population, not an actual rise.
And 10% of people over age 70 are affected
and it's the seventh leading cause of death in the U.S.
And we have common risk factors for these two conditions
and they're shown here, the major ones.
So hypertension, diabetes, heart disease,
smoking, atrial fibrillation.
A little weaker relationship with cognitive impairment
than stroke, but these are the critical things,
and if none of these would exist,
we would have much lower rates of these diseases.
We have persistent strong differences,
large differences by race in stroke death
in the United States.
So stroke death is twice as common in Black
than white Americans, and you can see on the graph
from 2000 to 2020, the non-Hispanic Black group
is at the top in blue, and the overall line
is the Black line, and then white people
pretty much overlap with the overall line.
And then the other race and ethnic groups
in the U.S. have lower death rates than white individuals.
So this is a disparity.
You look at the line, that has not changed,
and it's actually starting to worsen.
So why would it be worsening?
Why aren't Black individuals benefiting
from this decline over 20 years
that's largely due to blood pressure control,
risk factor control?
Why is this happening?
I'll get to that at the end of the talk.
We don't really know.
Dementia is also 40% more common
in Black than white individuals.
So back around 2000 I get a call from my friend,
well, soon to become my friend, George Howard.
We were acquainted.
We met at a meeting and I was like a middle author
of like 15 people on a paper that he wrote.
And he said, "Hey, Mary, do you think
if we could get into the homes of 30,000 people
all around the country, could you get blood
or do anything with it?"
George is a biostatistician who functions
like also an epidemiologist.
And I said, "Yeah, why not?"
So we proceeded to write a grant
to try to study these racial differences
and also geographic differences in stroke
using a national sample, because George
was really intensively interested
in geographic differences in stroke,
which you can't study if you have just a few clinic sites
enrolling patients or participants.
You have to blanket the country.
So we got a great score at that time.
A 10 percentile was pretty sure, you know,
for funding, not like now.
But we got a great score and the study was born.
And now we have multi PIs, who are shown here.
And the funding actually started in 2002.
Our funding comes from NINDS and NIA.
And we have George Howard, Suzanne Judd,
who is a biostatistician nutritional epidemiologist,
Jennifer Manley who's one of the leading people
in the country on cognitive epidemiology, and myself.
We also have now added to the group Virginia Howard,
who happens to be Georgia's spouse.
She was here last spring presenting the Nancy Jenny lecture.
And Ginny is actually gonna receive
the AHA Population Research Prize on Monday
at the AHA meeting, so we're very proud of her.
So REGARDS is a cohort study.
What is a cohort study?
It's a study where you enroll lots of people,
you collect as much information as you can
about those people using validated
instruments and techniques.
You then follow the people for clinical outcomes.
So our outcomes were stroke and cognitive function.
The reason we did cognitive function actually
is not in the grant.
It was because NINDS said
you have to add cognitive testing.
We're not gonna give you any extra money,
but we have to do that too.
And that was very wise on their part.
And we're not cognitive researchers
so we found a few people to help us develop instruments
we could administer by telephone.
And so the dual kinda outcomes of REGARDS
were born right at the beginning.
Other diseases have been collected,
disease outcomes, through what we call ancillary studies.
Somebody wants to study heart failure or heart disease
or venous thrombosis or whatever it is,
they write their own grant and we use our infrastructure
to get those outcomes for them, which they have to pay for
with their grant money.
And so ancillary studies are a key part of REGARDS.
It allows us to do so much more
than what was originally envisioned.
- [Crowd Member] Yeah.
Since 2002 it's been going on in such a high-impact study
for so many years, like the Framingham study.
How do you keep the 30,000 participants?
Do they dwindle with time or do you continually enroll?
Or how do you maintain a cohort of that size?
- I'll talk about the methods in a minute
so you'll get a sense.
That's a good question.
You know, you have to have people that have value
in their participation.
But I'll tell you just the nuts and bolts of how it works.
So in epidemiology, we work in big teams usually.
Think of us like herds of people
collaborating together as one.
We have a steering committee for the study.
This is over in Colchester Research Facility
with a steering committee meeting that we had here,
and the people sitting along the window
are a bunch of our trainees, 'cause they tend
to not sit at the table.
But REGARDS actually has a really small team
compared to other studies like MESA,
or ERIC, or even Framingham.
And so this is us in the early years.
I won't like point myself out,
but quite a different look back then.
And this is down at UAB on a nice sunny day.
University of Alabama Birmingham
is where the coordinating center is, where George is.
So the way we did the recruitment really broke the mold
of how you can do epidemiology research,
'cause remember I said we couldn't have clinics
'cause we wanted to study geography,
and if you have a clinic, geography and city
are totally confounded.
You can't like separate them.
You might have like, you're interested in poor health
in the south, then you can't have just
two cities in the south and three cities
outside the south.
Doesn't work.
So we recruited by telemarketing methods.
We sent people our mailing and followed up
with a phone call, and if they agreed,
then we did a baseline interview.
This was done as a computer-assisted interview
where just like telemarketing, the interviewer
is reading a script and punching in answers.
Some things were recorded.
Some of the cognitive testing was recorded.
That was followed a few weeks later by an in-home visit.
So the key thing to get REGARDS to happen
was that we've learned from David Goff who's now
the chief of heart section of NHLBI.
At the time he was at Wake Forest
and is a cardiovascular epidemiologist.
David realized he needed some more life insurance,
so he applied for some life insurance and they called him up
and they said, "We're gonna send a nurse to your house
and do a physical." (laughs)
And at the time George was at Wake Forest
and David went in and said, "George,
I know how you can do your study!"
He said, "You're gonna hire this company.
They came to my house, they drew my blood,
they did an EKG, they measured my height and weight,
blah blah blah," right?
So we hired EMSI, Examination Management Services Inc.
It was their first real research study.
They have 8,000 employees.
They trained 'em all in human-subject research
to work with us.
It was really a nice partnership.
So they went into the home and did the visit
to our specifications.
- [Crowd Member] Did you get baseline cognitive assessments?
- We started shortly after baseline, yeah,
'cause we were adding it as we were starting.
Yeah. - So you could follow,
but you got cognitive function early in.
- Yes. - Because it's not...
Okay. - Yes, yes.
It was part of the baseline visit,
or near to the baseline visit.
It was all done by phone.
- [Crowd Member] Yeah, it is a tough thing is the outcome.
We've done that for TBI it's hard to do cognitive function
as the outcome- - Oh we know to-
- [Crowd Member] -if you haven't done it as baseline.
You have to know who's gonna get a stroke
or get injured, know the-
- Yeah.
- [Crowd Member] It's not just the outcome
you get with the delta. - Precisely.
Yep. - Gotcha.
- So we are the central lab, so I'll tell you
a little bit about that.
And then the follow up, this gets
to your point about retention.
Every six months the participants are called
to find out how they're doing, to do certain things
like cognitive testing, to implement ancillary studies
that might wanna know about certain diseases
or things that are going on with them.
We've done things like sending them devices
like accelerometers so we can get
physical activity measures.
There's been all kinds of things.
There's I think 170 ancillary studies in the funding.
Those are people providing their own money to do it.
And during those follow-up visits, if a person indicates
they were hospitalized, we try to determine
if they had a stroke or if they think it was a stroke.
The medical records are obtained from all around
the country, every hospital that you can imagine.
And those are validated by committee
to determine if stroke occurred.
So here's the team for the central lab.
It was quite a process to get this started.
We had never done anything quite like this.
We usually work with clinical sites that are sending us
the samples like once a month in batches and stuff like that
from all the people they've seen at their clinical site,
but here we were gonna get one box for each participant
delivered to us overnight after the in-home visit.
So the first person I hired was this guy, Andrew Betsy,
who worked at a chocolate factory as a systems engineer.
And he helped us figure out how we would like
deal with this, how we would set up like an assembly line
and get all the data into data sets
by just scanning the tubes and so forth.
So here's how it works.
You have your in-home visit, the blood draw,
which is relevant to what we're interested in.
DHL was the shipper that we used.
EMSI was their biggest client and EMSI was able
to get us a discount on the shipping,
which saved us some money on our grant, (laughs)
and the samples would come overnight.
And if you haven't been there,
that's Colchester Research Facility.
If anybody ever wants to come out, happy to show you around.
It's quite a nice facility for us
and we have a lot of space over there.
We'd get as many as 100 boxes a day,
Tuesday through Friday only, 'cause we couldn't
deal with weekend.
But this is what they look like when they come in.
And we've limited that now.
We have another study that's doing this
and we've done REGARDS, another home visit after baseline.
We pretty much keep it to no more than 40 in a day,
'cause this takes a long time to handle.
This is what the kit looks like when we were to open it.
There's paperwork, there's a consent form.
There's some paperwork that of data
that was collected during the visit.
We take those out, we remove the samples,
we re-centrifuge everything at high speed
in refrigerated centrifuge because the processing
at the site into serum and plasma
is done in kinda just tabletop centrifuges
that the examiners have often in their homes
or the trunk of their car or whatever.
And then they go into our freezers,
and this is what our freezer towers look like,
and in each box there's a grid.
And every aliquot that we have stored is barcoded
and we know exactly where it is in which tower,
which row of the tower, which freezer, et cetera
so we can retrieve what we need when we need it.
So the baseline visit filled up 24 of these test reserves,
750 liters of serum, plasma, and urine,
whole blood, and half a million aliquots.
We aliquot everything into small sizes
so that we can minimize freestyle effects
on the material.
And that's our warehouse, which is in Burlington
and currently has upwards of 200 freezers in it.
Crazy.
And this is where the cohort lived at the end.
So 30,239 participants.
We targeted age range 45 to 100.
We over-sampled the southeast because we're interested
in stroke disparities in the southeast
where stroke rates are higher and death rates
from stroke are higher than other parts of the country.
There's other pockets of risk,
but the southeast is a hotbed for stroke.
- [Crowd Member] Can I just quickly ask,
does that coincide with the dementia as well?
- Yes!
We've discovered that, with cognitive impairment.
And you can see there are like seven people in Vermont.
Red is white, blue is African American,
and of course the Vermont participants are all white.
Maria?
- [Maria] Do they specifically ask about Hispanic?
So is this like white non-Hispanic?
- It's not Hispanic.
- [Maria] So it was specifically put in here.
- Yes. Yes.
It's a good question.
So that's where, and you can see the people
are pretty much where people live.
But we have rural.
We cover two thirds of the counties in the U.S.
We have thousands of rural people,
so there's a lot of opportunity
to study rural health as well.
So all kinds of baseline data that we have.
I'm not gonna go through all of this.
We actually, the genomics data, I'm really excited
'cause we never were able to get our study section
to help us do any genetics research,
'cause a big barrier to genetics research
is the cost of DNA extraction.
It's about $35 a sample.
Anything times 30,000 is a lot of money.
And at the beginning on our first renewal,
we wanted to get DNA extraction covered (laughs)
and the study section said, "That's not science.
No way, take it out."
And so when we resubmitted we had to take it out,
but ultimately we were able to get
DNA available on everyone thanks to a recent collaboration
with a NIA intramural group.
They're completing GWAS on everyone
that we already have it on, which is really great.
Really a multimillion dollar effort
because they like us and it's a service
to the research community and to America.
So the follow up, as I said, every six months.
The cognitive battery, it was developed
right after we started, so there was a phase-in of it,
but basically you have close-to-baseline measures
and then every two years there's a battery
consisting of four tests, and here's all the outcomes.
Somewhat updated numbers, but you can see
how many of everything that we've had,
and these are outcomes among people
who did not have that disease at baseline.
So you see 2,000 strokes, 600 end-stage kidney disease,
over 1,000 cognitive impairment, dementia death.
Lots of diabetes and hypertension developing in new people.
- [Crowd Member] So those numbers drop in hypertension,
is that is similar to the other overall finding?
- Pretty much. You mean to the country?
- [Crowd Member] Yeah, so that this is the number
in regard positive parts and only
the hypertension percentage, they feel a little
lower than that. - Remember they're 45
and older at baseline.
- But that's- - So about 60%
of the Black people have hypertension at baseline.
- [Crowd Member] Oh, okay.
- Right, they already have it.
So you're catching new ones
in largely the middle-aged people.
- Thank you. - Yeah, it's a good question.
The characteristics of the cohort are pretty similar
to Black and white Americans in general though.
We were really proud of that, 'cause that's always an issue.
Like is it generalizable?
Do they represent real people, right?
They're people who, honestly, they answered the phone,
they let us come into their house,
they let us take their shirt off to do an EKG (laughs)
and give us their blood.
I mean, would you even talk to a person
who called you asking you to do that?
Like think about it.
They're really amazing individuals who really did-
- [Crowd Member] Were there like incentives for them?
- At the baseline visit, I think we gave them like $25,
and so the UAB got good at processing these checks.
And occasionally there was a participant
who mailed it back (laughs) and it was just like,
that created a huge crisis at UAB,
'cause managing the budget and putting the money back
or whatever was kind of a pain.
But yeah, and I think at the second visit we gave 'em $100.
Inflation.
The second visit was 10 years after the baseline,
and I'll talk about that a little bit more.
So what have we learned?
Fundamental information about the stroke disparity.
We didn't know when we started if the disparity
in stroke death in the United States by race
was due to higher incidences of stroke
or higher mortality after stroke, right?
Basic stuff that we didn't know.
And who does it affect?
And it turned out it's affecting young people.
So you can see here at age 45 to 55,
the excess risk of stroke in Black
compared to white is three times greater,
and over age it gets weaker such that the oldest group,
75 plus, had no excess risk of stroke.
And so this is really bad.
This just shows the same thing on a graph.
So the blue line is the relative risk
and you can see the three at the youngest age
going down to no increased risk.
There's one.
The no increased risk at the older age.
The dotted lines are the confidence intervals
for those estimates.
And I told you that stroke is a leading cause of disability.
So this is terrible, right?
So this is robbing these people in the prime of their life
of their ability to function in the world, right?
So it's really terrible.
There's been estimates of the excess cost,
like a cost analysis, something like 10 or $20 billion
a year in lost productivity and economic impact.
When you add stroke risk factors to this
to try to figure out are the risk factors explaining this?
Does the higher prevalence of hypertension or diabetes
in Black people explain this relationship?
What you see is some reduction in that risk.
So about half of the risk is explained
by including risk factors in the analysis.
If you then on top of that add income
and education as proxies for socioeconomic status,
you see really not much difference as the risk factors.
So basically about half of that racial excess
is due to those risk factors that I showed you
at the beginning.
What other things could there be?
So physical activity, stress, racism,
medication adherence, access to care.
There's all kinds of things that could be involved.
Nutrition and pretty much all of this stuff
has been addressed over the years in different manuscripts
from the study.
Blood pressure is a really key factor.
So this shows the association of systolic blood pressure,
whether you have hypertension or not,
and the risk of stroke.
And so you see here everyone, the relative risk of stroke
is about 15% higher for every 10 millimeters mercury
greater for blood pressure, okay?
In white people the relationship's
a little weaker, 8% greater.
In Black people it's 24% greater.
So the relation of blood pressure with stroke risk
in Black individuals is three times greater
than a white individual.
It's a more potent risk factor
for the same incremental blood pressure.
When you add in all the other risk factors
to see if you can explain that away,
doesn't change anything, right?
So this is really revealing, and you know,
so we determined that high blood pressure
is more common in a Black individual.
It's actually more difficult to treat
and it's a more potent risk factor.
Blood pressure was also related to cognitive decline
and the association was greater
in Black than white individuals.
And we know from clinical trials
that intensive blood pressure control,
systolic blood pressure down to 120 as the target
is associated with reductions in risk of stroke
and cognitive impairment, although I think
that's not published yet, but it was presented
last year at AHA.
- [Worker] Have you made a distinction
between male and female?
- Yeah, we often look for sex differences as well,
and whole nother topic and talk.
I'm not gonna get into that much,
but I don't think these differences differ by sex.
Yeah.
It's hard when you cut it into four groups,
race and sex, between Black men and Black women
and white men and white women, but we try to do that
as much as we can 'cause it's important.
Research that occurred this summer by Nels Olson
and Liz Henelbury looked at whether this difference
in the blood pressure relation with cognitive impairment
is the same as it is for stroke,
and she really didn't find much difference.
There was a little difference,
but it wasn't statistically significant.
So perhaps the same pattern, but not clear enough
in the data that we have so far.
- [Crowd Member] So sorry, Mary.
So the last slide, you're saying that that difference
in the pressure is not-
- That this racial difference-
- [Crowd Member] Okay, okay.
- It doesn't look like that.
It looks more like that. (laughs)
- [Crowd Member] Oh, okay. OKay, okay, okay.
- Yeah, and the confidence intervals are wide
and it wasn't as robust.
- Okay. - Yeah.
So she's working on that paper.
I'm not involved with that paper,
but that's what I saw at lab meeting.
So we did a second visit 10 years after baseline.
That grant renewal, part of the purpose was to study
why there are racial differences in development
of risk factors to begin with.
Why do Black people have higher hypertension
and diabetes in particular?
And so we got funded every, you know,
five years just like everybody else.
We have to get our grant renewed.
And we tried to get it done sooner,
but it took a couple tries, so it ended up
being 10 years after baseline, and it was just
the same thing we did before, and there were 16,000 people
who participated in the phone interview.
Not all of them did the home visit part.
This gets to the point of, you know,
they might have been losing interest or what have you.
We called them every six months.
For the most part they like us,
and we had higher retention than we thought we would.
a 97.5% per-year retention rate, which was a problem,
because the call center budget
could not cover (laughs) all the calls we needed to do.
So it's a good problem to have,
but we had to divert money from other parts of the grant
to make sure we can do those phone calls.
So basically we observed that Black individuals
had twice the risk of developing hypertension
during follow-up as white individuals,
and there's been a wide range of projects
looking at reasons for this.
And this paper was a labor of love, I have to say.
So George led this paper on determinants
of the excess risk of hypertension
in Black compared to white.
Just like we did for stroke, what are the factors
that could explain this?
And this went into JAMA after three or four revisions.
An 80-page response document.
I told George, "Why are you torturing yourself
like this?" (laughs)
And he said, "I wanna get it in JAMA."
And he did succeed, but it was really painful.
And the differences in the explanatory factors
for developing hypertension did differ by sex.
And so for men it was lower socioeconomic status,
poor diet, high dietary sodium,
and increased levels of inflammation,
and for women there were added impacts
of body size measures, obesity measures.
So some differences by sex there.
For diabetes, same sort of thing.
So back in the data I just showed you earlier
about the factors that explain stroke disparity,
diabetes explained about 20 to 40% depending
of the racial difference in stroke.
And we observed that Black individuals
had a twofold higher risk of diabetes,
just like hypertension, developing over
those 10 years of follow up.
And the main mediators which didn't differ by sex
were adiposity measures, that poor diet
and lower socioeconomic status.
Brittany Palermo wrote this nice paper
about interleukin six levels in the risk of diabetes
and showed that the relationship was very large
but similar in Black and white people.
Brittany is a medical student here
and just received the Research Week Award
for best medical student paper.
I was very proud of her.
And Brittany's going into the match for anesthesia,
so she'll be graduating in the spring.
So basically in terms of stroke,
these traditional risk factors explain
about half the disparity.
Blood pressure, we call it the triple curse
because it's more common, it's more difficult to control,
it's more potent as a risk factor.
This suggests that treatment goals
for blood pressure maybe needs to be different
for Black individuals, but boy wouldn't it be nice
if we could prevent high blood pressure
in Black individuals starting in the first place.
That's primordial prevention, preventing the risk factors.
That would be the holy grail really.
And a better understanding of the origins
of the race difference and risk factors might allow
the best way to reduce stroke risk
rather than try to treat the risk factor.
And I showed you just a little bit of that
and there's a lot of work going on in that area.
So this is kind of the glass half full argument,
which was actually in the title of the paper that showed
the risk factors that explain stroke disparities.
I debated George about that.
I wasn't, like kinda stupid to put that
in the title (laughs) of the paper.
He's like, "No, I won't have it."
But basically you have this unexplained risk
that justifies us getting more grants
and more funding to study, but it's really important.
So the question is whether lab markers
could help explain this, and those lab markers
could work in a couple of different ways.
They could be mediators like the analyses I've shown you.
They're in the pathway, they're involved.
At least the biology they represent is involved.
Or they're moderators, which means
they're race-specific risk factors
meaning there's differences in the relationship by race.
Might be stronger in one group than another.
Have lots of people working on this here over the years.
Lot of med students, postdocs, some fellows,
faculty members, and that's really great
to keep adding to that picture.
So it takes a lot of memory.
You have to snip it, make it smaller
as you get to having more people working with you. (laughs)
All those photographs are a lot.
So we embarked on something called a case cohort study
to study laboratory markers.
And when you have 30,000 people in the study,
you don't need to measure lab markers on everyone.
You measure them in these subsets,
and this design will approximate
what the results would be if you measured it
at everyone if you do it right.
So a case cohort study is when you have followed the people
for some number of years and then you go back
and identify cases, in this case
stroke and cognitive impairment,
and then we take a random sample from the cohort,
and in this case it was 1,100,
and we had those numbers of stroke
and cognitive impairment cases during follow up,
and pull the samples out of the freezer just on those people
and measure a whole variety of things.
And some of the measures we'll go through.
There's a lot more, but just to give you examples,
you can have genetic-related markers,
have circulating proteins.
There's a guy at MGH who's doing metabolomics
who's written some really nice papers.
I don't have time to go into his work.
He did that in an ancillary study,
and he's linking diet to metabolomic markers
and trying to make causal pathway sorts of analyses
and found some really interesting findings.
So sickle trait was a high-priority thing for us.
As time was going on, we have learned over the years
that sickle cell disease and sickle cell trait
are prothrombotic conditions.
Sickle cell trait, the carrier ship of sickle cell disease,
hemoglobin AS is present in 8% of African Americans.
And it's been reported by us and others
in different studies that sickle cell disease
and sickle cell trait are risk factors
for venous thrombosis.
And the idea is probably that you have, venous thrombosis
starts on the backside of these valves,
the venous valves in the legs, and when
these valves are hypoxic actually, the PO2 I think it's 50
in those valves.
And so we think that even heterozygous carriers
of sickle trait, that the red cells could sickle
in that hypoxic environment.
And interestingly, sickle cell trait is also related
to the risk of developing kidney disease
where there are also in the nephron areas of hypoxia
like around an O2 750.
So a really interesting concept which led us
to think about, well, maybe it would relate to stroke
and cognitive impairment as well
because of hypercoagulability.
And so this is a paper that merged data
from multiple studies, including REGARDS,
led by Hyacinth Hyacinth, who was here last year
giving this presentation, and we showed no association
of sickle cell trait with stroke risk.
So here's your head ratio of one
and the risk estimates for each study,
and nothing is significantly different
than a one, which means there's no increased risk.
So that was cool.
Here Christina Cahill who was an medical student here
did that analysis for cognitive impairment in REGARDS
and she looked at it different ways,
both as becoming impaired when you were normal
and there's a definition for that
that I'm not gonna go into, but also looking
at the trajectories of test scores over time
in people with and without sickle trait
and saw no association with cognitive impairment.
Lipoprotein(a) is another genetic related factor.
So Lp(a) is an atherogenic lipoprotein
and it promotes pro-inflammatory milieu
in atherosclerotic plaques, and it also
enhances abnormal clotting.
It's mostly genetically determined.
Pretty much you only have to measure it once
in a person's life and you know what their value is
and it really doesn't change.
One in four people have high levels,
more common in Black than white people to be high.
What we observed is this really interesting
difference by race.
So with stroke risk, this is Pankaj Arora
who's a cardiologist down at UAB,
and the relationship of higher Lp(a) with stroke
was present only in Black individuals.
So they had a twofold greater risk for high Lp(a)
after accounting for other risk factors
while for white people there was no difference.
And we saw the same pattern
for the risk of cognitive impairment.
So cognitive impairment, this definition
is kind of like a mild cognitive impairment
or worse phenotype.
It's not dementia, if you will, based on the test scores
and how your scores relate to other people
and what scores signify an impaired state.
So here we saw the same thing, weaker relationships.
Often the relationships of the stroke risk factors
with cognition using this outcome in REGARDS
are weaker than they are for stroke.
But the same sort of pattern seen for cognitive impairment.
- [Crowd Member] Mary, can I ask a question?
So you're studying these risk factors by themselves.
You're not cross correlating a whole bunch of risk factors?
- What we're doing in these analyses,
we're adjusting for the traditional factors,
- Right. - The ones I was describing
in the first part of the talk.
- But not all- - We're not throwing
all the biomarkers together.
- [Crowd Member] Is that all the time?
- You could do it.
I mean we're trying to pick apart biology,
so I'm not really as interested in...
You know, like Lp(a) levels for example
don't really relate much to sickle trait.
They're not gonna be different, right?
- So that analysis- - So there's not really
a point to putting them up against each other
to study the biology.
If you wanted to know like which ones could be used
in the clinic, you could throw 'em all in
to pick the best ones, but to study biology,
potentially if you wanted to adjust for other biomarkers,
you would adjust for ones that you think
are part of that pathway.
- [Crowd Member] But with multi-correlation,
maybe 100 biomarkers-
- Becomes problematic.
- Right. - Yeah.
- [Crowd Member] So you don't know the interaction with-
- You can test for that.
We're gonna be doing some of that later.
I'll introduce that at the end. Yeah.
So Lp(a), there are drugs in development
for lowering Lp(a) and they are being tested in people
with established cardiovascular disease.
We're waiting for the trials to end.
Should be maybe in the next year.
And you can make a hypothesis that these drugs,
at least from the point of view of stroke and cognition,
might have greater effects in Black than white people
or be more useful in Black than white people.
So I wanna talk about inflammatory cytokines
and I want to point out this work was done by Nancy Jenny.
I'm not sure anyone here knew her.
So Nancy was a faculty member in our group in Colchester,
and Maria knew her, and Nancy really was a wonderful person,
and Nancy died suddenly in an accident
about five years ago?
Six years ago.
And Nancy's office was next to mine.
We roomed together when we traveled, we worked together.
She was an amazing, giving, and caring scientist.
Very collaborative.
And I wanna take a moment just to mention her,
because this was a tragic thing for our group
to lose a person like that.
There one day, gone the next.
No warning, no indication anything was wrong.
It was an accident.
So just appreciate the people around you.
This really taught me to just take a little extra effort
to appreciate the people that are around you,
because they might not stay.
So anyway, after she passed away,
this paper she had been finishing up at the time,
we were able to get it published,
which we were very proud of.
And then the journal "Neurology" made this infographic
for us, which is nice, 'cause you can chop up pieces of it
and put it in a talk like this.
So she looked at interleukin 6,
IL-8, and IL-10 as the cytokines we had chosen to measure
in that case cohort study of stroke
and cognitive impairment risk.
And higher IL-6 was the only one that was related
to stroke, and it was a substantial relationship.
So levels in the top quarter of the distribution
compared to the bottom doubled stroke risk.
So the inflammatory basis of stroke, very important.
And it was independent of adding
all the typical stroke risk factors.
- [Crowd Member] I had a quick question.
Are all these results you're describing,
are these coming from what you say were ancillary studies?
- No, this was the main study.
That case cohort study was an aim in one of our...
But ancillary studies that built on the framework
of that case cohort study to add things,
like the guy that did the metabolomics.
He said, well, I'm gonna use those same people,
'cause you've showed us that it works,
and do metabolomics layered on top of this.
So if we wanted to look at pathways for metabolomic markers,
we could kind of play around with the data
using the other biomarkers we've...
We've measured a whole variety of things on these people.
So yeah, but good question.
So what we discovered in this paper,
what Nancy discovered, is that the IL-6 mediation
of the race disparity in stroke was actually
through the other risk factors.
I'm not gonna show you all the statistics
around that, but just trust me.
And the way we concluded that part of the paper
is that the stroke risk factors are pro-inflammatory
which leads to stroke in a way that's more relevant
for Black individuals than white individuals, okay?
So the question would be from that
is maybe you could manipulate inflammation
to prevent stroke.
Now, we already do that.
Statins lower inflammation, for example.
Physical activity lowers inflammation.
So a lot of things that are healthy lifestyle things
and primary prevention treatments lower inflammation.
And if you could figure out pathways
that might be targetable in different ways
than the things you already do, maybe lower inflammation
would reduce racial disparity.
Daniela Zambrano in vascular neurology
is working on a paper now looking at these cytokines
and the risk of cognitive impairment.
Turns out IL-6 is probably the most important one
for that too.
So here's just some other biomarkers.
I'm not gonna spend much time on it
'cause I wanna get through the rest,
but just some sampling of some of the things we've measured.
And what you can see in general, and this holds
for other ones that we've done, is the relationships
are often concordant for stroke and cognitive impairment.
It reflects the underlying common pathophysiology, right?
And the relationships with cognitive impairment
often are a little weaker than they are for stroke,
except for blood group, which is interesting. (laughs)
You know, blood group AB or non-O blood groups
are related to hypercoagulability
and impaired endothelial function.
And so blood group AB is an interesting proxy
for really interesting biologies
that relate to cardiovascular diseases,
and so that was similar for stroke and cognitive impairment.
When my postdoc published this paper (laughs)
on cognitive impairment, it was like a media firestorm.
It was all over the world.
It was on all the media outlets, you know,
saying that your blood group tells you about your cognition.
It was a very like sexy topic.
We had emails from people, I had emails from this lady
in England who said, "Oh, I finally understand
why my brain is the way it is!" (laughs)
And she's like, "Thank you for doing this research."
It was so funny.
But it never seemed to stop.
It lasted for like three years.
Every once in a while a health writer would contact us
asking to talk about that paper.
It was so weird.
So this part I wanna talk about the importance
of seeing who's around you in your travels
and interacting with people and why networking
is so important, especially for those of you
who are just starting.
So the International Society on Thrombosis and Hemostasis,
one of my groups, has an early career lounge
at their annual meeting, which I think
most groups have these days.
And I was in the early career lounge as the journal editor
for the "Society" journal wanting to just talk to people,
meet people, answer their questions
about publishing and what have you,
and this guy, Robbie Campbell, comes up to me
and he says, "Oh, can we talk about this project?"
And I'm like okay.
So Robbie had a postdoc, Frederik Denorme,
working on this project in the lab
looking at a Power Four variant,
which is a platelet protein
that is a variant
more common in Black individuals,
in people of African ancestry, I should say.
So they were studying a mouse that had this mutation
that is more common in people of African ancestry
and they were showing that these mice
compared to wild type had bigger strokes
in the stroke model.
And they were working out the physiology of that in the lab.
And he said, "Can we look at that variant in REGARDS?"
And I said, "Sure, we have GWAS on all Black individuals,
so we can look at the association of this variant
with stroke risk in Black individuals."
And so with this variant,
anti-platelet drugs seem less effective
in the animal model.
That's kind of interesting.
And what we found is that the variant
was more common in African ancestry,
or by proxy Black individuals in REGARDS.
62% of them had the variant compared to 21%
of the white participants.
And in the mice, Frederik had observed,
as I said, that they have worse strokes.
They had greater net formation.
Part of the possible pathway for that.
And we showed an increased risk of stroke
with that variant, 1.264 increase.
Modest relationship for a gene variant
that's a pretty good, pretty solid number.
Most gene variants are, you know, mild risk factors.
So 25% increased risk if you have this variant,
which is much more common in Black individuals,
so hey, there's another one, right?
Maybe it is partly explaining this pattern we see
in the population.
And then Robbie is like, "Well, the mice get worse strokes.
Can we look at the size of the stroke
or the severity of the stroke?"
And I'm like, we've never done that before.
This is why it's so good to collaborate with people
who think differently than you.
And it turned out that there was this project
that had extracted from the charts
of several hundred of the stroke cases we had
stroke severity measures.
There are validated measures that physicians use,
kind of required for them to calculate
in the records in every stroke patient.
And indeed, we showed that if they had this mutation,
they had higher odds, a higher risk
of more unfavorable stroke outcome.
So 70% higher risk of unfavorable.
So maybe they were having also bigger strokes
if they have this.
So that was cool!
And I would say any of you in the room,
you know, working in vascular function,
and Osama, we've tried to (laughs) do
some translational work around a PAO1
and we had a lot of challenges with it
that someday we'll maybe overcome,
but this kind of work is not hard to do,
especially if you have an identified mutation
that you're studying that is prevalent enough
in the population that we can study it.
What about clinical applications?
This is really not related to race differences,
but Sam Short, who graduated from medical school
here the year before last, he also won the Best Paper Award
last year after he left when he was an intern
down at Chapel Hill.
He looked at, we had some money in our carry forward,
like a lot of money during the pandemic,
and we decided we're gonna measure a whole bunch
of biomarkers in everybody in REGARDS
to baseline atrial fibrillation, because atrial fibrillation
is an important risk factor for stroke.
And we use anticoagulant therapy
to prevent stroke in people with AFib,
and so we thought, well, can we make that risk prediction
for who should get anticoagulation better
by using biomarkers?
There's risk scores that physicians use
in primary care to decide who should get anticoagulation
or who needs it and who doesn't,
because these scores predict stroke risk.
And so Sam is a great analyst and he's a wonderful creator
of imagery, (laughs) and so this was a figure
he created looking at these biomarkers
that cut across different domains.
Clotting activity, cardiac function,
kidney function, vascular dysfunction, et cetera.
Liver dysfunction.
And you can see several of these biomarkers
from here over had greater risk of stroke in AFib.
And these are all in people who were not taking
an anticoagulant at baseline, so they're the kind of people
who would be risk assessed, for example,
for whether they should take an anticoagulant.
And accounting for all the risk factors for stroke,
you see these relationships, and like we saw
in the general population, the largest association
was for NT-proBNP, measure of atriopathy,
left atrial dysfunction, which makes sense
for its relationship with AFib with stroke risk,
'cause it's the atrium that's sick in AFib
and creating clots that embolize to the brain.
GDF-15 was another one which is turning out
to be a really robust marker.
We haven't worked with it much before,
but it's a marker of kinda inflammation fibrosis probably,
but it predicts a lot of vascular outcomes.
There's Lp(a) you see and cystatin C,
which is kidney function, and IL-6.
So you can see the theme maybe emerging
from some of the other findings for stroke overall.
What Sam did was essentially developed a new model
for risk prediction.
So CHADSVASc is the name of the score that we use
and he made a CHADSVASc biomarkers model
and showed that it was superior to the CHADSVASc model.
So you can add improved risk classification of people
by adding actually just a couple of biomarkers.
NT-proBNP and GF-15 is all you need to add
and you get a better risk prediction.
So perhaps that is something that could potentially lead
to practice change and how stroke risk
is assessed in AFib if it catches on.
You never know if these things are gonna catch on.
So essentially we showed some biomarkers
underlie the effects of risk factors on stroke.
I didn't show in CRP, but interluekin 6
and C-reactive protein are other inflammatory marker.
Some appear to be race-specific risk factors for stroke
or cognitive impairment.
Gluconic acid is the one that the metabolomics work
came up with in that regard.
Some did not relate, which is, you know,
what you're gonna find.
Not all your hypotheses are correct.
And so the hypercoagulability of sickle trait
is not enough to raise stroke risk.
And then some could suggest possible new treatments
to improve brain health, and the example with the AFib
that I showed you and others that I mentioned.
So I'm giving a talk to this group.
So how can I talk not about
cerebral small vessel disease, right?
So Hyacinth and I and Nels Olson just submitted
an R1, an ancillary study through REGARDS
to try to untangle the pathways
of cerebral small vessel disease with stroke
and cognitive impairment in REGARDS.
So Hyacinth has a grant now. This is so cool.
And he didn't talk about this in his talk when he came here.
He's collecting MRIs from all of our participants
from the hospitals where they were treated for stroke
or evaluated for TIA and he's rereading those MRIs
for cerebral small vessel disease phenotype.
It's so cool.
He's got about 1,200 and some in hand
and he's expecting to have 1,500.
And there's a lot of interesting things about this.
The MRIs it turns out from the smaller hospitals
tend to be better quality, (laughs) which I found
like so weird.
But anyway, he's characterizing that
so we can start really getting at the epidemiology
of small vessel disease.
It's not like we have MRIs on everybody at baseline,
but it's better than nothing.
We can't afford to do MRIs on everybody in REGARDS,
and it would be a logistical nightmare,
'cause we have no clinics.
But at any rate, what we're gonna do in the proposed work,
which we just submitted, is to look at the proteomics
of cerebral small vessel disease using the latest,
newest Olink platform which measures over 5,000 protein.
This will be done down at the Broad
and we'll relate those proteins
to cerebral small vessel disease phenotypes,
all different kinds, and then to ADRD and also stroke.
But basically post-stroke cognitive impairment,
because even after people have the stroke,
we're still following them.
And use the imaging and proteomic data to try to understand
or prove our understanding of the racial disparity,
which gets to your point that you asked
about would you throw all these things
in the same model or whatever.
And we can use machine learning
and all kinds of different approaches
once we have this data to try to understand
like pathways and stuff with 5,000 protein.
So here's some of the images from actual participants.
So this is one participant. This is another.
They're not really easy to see,
but at the top you see the yellow
is white matter hyperintensities,
and this participant didn't have any.
We have here
three examples of three types of cerebral
small vessel disease that are being characterized.
So here we have deep and periventricular
white matter hyperintensities.
Here we have basal ganglia, enlarged perivascular spaces.
And here we have multiple cerebral microbleeds,
which can be due to cerebral amyloid angiopathy
or hypertensive encephalopathy.
So really important phenotyping.
- [Crowd Member] Is this also based...
Okay, sorry.
- Yeah. (laughs) I gotcha.
So we generated a bunch of preliminary data on the grant,
and this is based on the first 1,000 or so MRIs that he got.
And what you see is that every region of the brain
for this, this is for white matter hyperintensity volume,
the amount of white matter hyperintensities that you have,
you can see there were all these differences.
They're all unfavorable in Black
compared to white individuals.
There were two regions, I took 'em off
'cause the slide was so busy, cerebellum
and one other region where there wasn't a difference.
But all of these areas had differences,
sometimes very large differences
in terms of statistical significance.
And then we said okay, well, we can show associations
of biomarkers with these things.
So this is just in 168 participants
who we had some lab data in and risk factor data in
from that case cohort studies.
Remember, we had 650 strokes.
And so so far with the numbers that we have
the full characterization of small vessel disease,
we had 168 participants with lab data.
And this is shown here, and you can see
some of the biomarkers relate to different types
of cerebral small vessel disease.
So basal ganglia in large cardiovascular spaces.
We got D-dimer.
For some reason factor XI is inversely associated.
It's probably just advanced minding. (chuckles)
But HGF has a growth factor strongly related
to cerebral microbleeds.
- [Crowd Member] So all of these individuals are Black or-
- No.
- [Crowd Member] The 168 still includes both parties?
- Yeah, yeah.
I mean, there's not enough ability to look at it,
but once we have everybody, 1,500 MRIs,
1,500 assays for 5,000 proteins,
then, you know, we'll be able to pick apart more detail.
But look, you know, hypertension, we all know this, right?
Basal ganglia, 25 or greater risk of basal ganglia.
That hypertension is the cause of that. We know that.
So it's really just good proof principle
that we can see these relationships.
So hopefully we get the score.
I like the grant, but just 'cause I like it
doesn't mean the study's actually gonna like it,
as we were talking about earlier.
So you know, I think we've identified some actionable steps
to try to improve the health of Black people in the U.S.
Always we hope that clinical trials
will represent those people appropriately.
We learned in COVID we could do it.
If you're interested in that, we just published
in "NEJM Evidence" our experience in the COVID trials,
'cause over half of our participants
were underrepresented minority.
But we know we can do that.
We have a poor history of that in this country.
I bet you the people doing those Lp(a) trials
have no idea of our data, right?
Or probably aren't even thinking about it.
And then there's so much ongoing research.
You know, Minaz is here.
She's studying the intersectionality
of social factors, race, sex, and class
with risk factors.
We have Nels Olson, just got an R01 to study
the proteomics of cognitive impairment
where he probably is gonna use dementia death
as the outcome, 'cause it's the hardest outcome we have.
It's more strongly related to all the risk factors
than our cognitive impairment type measures.
There's more going on in AFib and the effects
on other aspects of health.
Andres Cordova, who's a cardiology fellow,
is writing about biomarkers that predict MI
in people with AFib, 'cause we know AFib
is a risk factor for MI and we don't understand why.
Vinh Le, our postdoc, is looking at AFib
and the risk of cognitive impairment
and biomarkers that might relate to cognitive impairment
just in people with AFib.
He's making great progress during his one year
that he has with us.
And we submitted our renewal for REGARDS
the second time in 2023.
We got a bad study section and a bad review.
Basically submitted the same grant
to a different study section and we got a perfect score.
Just goes to show where you send it is really important,
where it gets assigned.
Pay attention. (laughs)
I mean, it was in a SEP first time
'cause of conflict actually, 'cause Hyacinth
was on the study section we usually go to.
And so it was in a SEP, and there was not even
a vascular neurologist in the panel.
It was just ridiculous.
So it was torture and it really caused a lot of delays
and really like picking ourselves up by the bootstraps
and tightening up our budgets to cover no-cost extension
and keep our people employed.
But what we're doing here, this is the title.
This is what's going on since the 60s in the United States.
This is the Black/white stroke mortality disparity
getting larger, and since about 2013,
everyone is having an increasing rate
of stroke mortality.
It's rising.
You know, we've had 20 years
of declining in cardiovascular disease.
Now stroke is rising.
Not CHD. We don't know why.
So we want to understand risk factor differences
in birth cohorts over time, so we're gonna enroll
12,000 new people in REGARDS.
Gets to one of Cal's questions.
And they're gonna be middle aged people, Black and white.
We're gonna compare their respective profiles
to the original cohort of the same age
to try to understand what's happening.
We know the risk factors are probably gonna be worse now
with the obesity epidemic affecting these people
when they young adults, and so we'll try to figure that out
and then understand how those differences
in risk factors might explain this rising stroke risk.
We're also gonna do a lot on Alzheimer's disease biomarkers
and circulation stuff to kind of really
get at their epidemiology.
So it's a really exciting time for us,
and we're gonna start in April.
So tons of people to acknowledge.
You can't fit them all on one slide really.
But if you have other questions, I know I'm over time,
but I'm happy to answer other questions you might have.
And I wanna point out, you know, Debora was postdoc,
is now faculty and funded by our center
to do her work on intersectionality of social factors
and how that relates to cardiovascular health
and what the proteomic profiles are a biological embodiment
of those social injustices in the population.
Minaz is her postdoc if you haven't met her yet.
And Debora's up at AHA, so not here today.
Anyway, free to take questions.
- [Crowd Member] I'll slip in a quick question.
So you talked about incentives to these participants.
- Yes.
- [Crowd Member] One of the incentives would be
to give a forward prediction based on their
risk factors and biomarkers, how long they're gonna live or-
- Oh.
Yeah, I mean, at the baseline, they get their results back.
So they get their EKG, their lipid profile,
their glucose, creatinine, hemoglobin, A1C, blood pressure.
They get all that back.
- Right. - So they get our results.
So when the examiner is in the home,
there's a little card they fill out
with their blood pressure and stuff.
And then we send a results letter with the lab data
and the ECG data, and so they can act on that,
if they should choose.
We have to be careful though.
- [Crowd Member] I know it's probably politically incorrect,
but all your risk factors, if you assemble them together,
you would get a forward prediction model
of their likelihood of getting a stroke
in the next 10 years.
That would be useful information.
If they're like, oh, I'm gonna die at 60,
give or take three years, it might change
the way they live their life.
- Yeah, so there are standard risk prediction scores
that are used in practice, like the whole cohort equation,
the ASCD risk score, which is used
for statin prescription.
There's Life's Simple 7 and now Life's Simple 8
which are health assessments that can help people
identify areas they need to change.
We have to be a little careful about doing care
for the people, because they can take that report
to their physician.
Everything on that report is stuff
they should be having anyway pretty much
in the course of their primary care.
We have to be a little careful not to like
change their life too much, right?
'Cause if you do too much of an intervention,
then you're affecting potentially the outcomes
that we're interested in.
This is the observational research.
A great example, when we were starting this study,
the Multi-Ethnic Study of Atherosclerosis, MESA,
started a couple years before REGARDS,
and I was really deeply engaged in the design of MESA.
Russ Tracy was my mentor at the time
and he was on the steering committee.
And MESA was a study of racial differences
across four groups in subclinical atherosclerosis measure
and how they relate to clinical outcomes.
They were all people who never had cardiovascular disease
and they had high-tech imaging for the different types
of subclinical disease.
So coronary calcium was the hot new thing at the time by CT.
If you detect coronary artery calcium,
that's atherosclerosis, right?
And so we wanted to understand the epidemiology of that
and the prevalence of it and the way it relates
to heart disease, stroke, and other outcomes.
So there was a debate during the design phase,
'cause these are NHLBI contracts.
We all apply to be the sites and they pick us
and then we design the study.
So we're following loose parameters of what they want,
but we're designing the study how we see it should be.
And the steering committee had a lot of debate
on the calcium, whether to give people their scores,
should we randomize people to getting their scores,
you know, what we were gonna do with that data.
And I love the idea of randomizing people to getting
the score or not, because at the follow-up visits,
we could then say if they did anything
that improved their health.
There was a study done in military recruits
that did that actually and showed them
the pictures of their calcium and they had no effect, right?
So we debated doing this as an embedded thing
and there was a lot of debate and discussion.
In the end it was decided just give 'em the score
and you know, tell 'em, "See your doctor with this."
Of course at the time, primary care docs,
they didn't know what to do with that information.
Now we know if we have calcium and burden of calcium
is really strongly related to heart-attack risk.
Obviously it's the disease, but at the time
we didn't really know how useful that test would be
as a clinical test.
So you can do things, but you have to be a little cautious
about how much you do.
But you know, getting their results letters,
most people are happy with that.
And our participants, they just love to talk to us.
They send notes.
We occasionally get notes in the boxes. (laughs)
We did a dried blood spot collection during the pandemic
and we sent kits out to people to collect blood,
put it on filter paper, and mail it back to us
so we could do COVID serology.
We did it in 14 of these big studies.
We have 20,000-plus blood spots from people.
And some people would send notes.
"Thank you so much for the research you're doing,
blah, blah, blah," or whatever.
It's so funny.
But these are people who join.
So does that make sense?
- [Crowd Member] I was actually thinking too,
could you cross reference your geographical
risk associations with cost of life insurance
and whether the health insurance companies
are tracking the same risk factors?
- The longevity and stuff?
Yeah, I don't think we've done that.
We've looked at, you know, accessibility to care
and insurance status and things like that.
Of course, our population, half of them are over 65,
so they're on Medicare, have basic insurance at least.
But we ask questions about all kinds of things.
There's a questionnaire called You and Your Doctor
and it's getting at do the people trust
their healthcare teams?
How do they feel about what
their healthcare teams tell them?
What's their relationship like?
There's so many different things.
We wanted to track tobacco taxation with smoking
and health outcomes to see if we could tease out
the impact of tobacco taxation on health as an example,
because in the south, there's like no tobacco taxes.
They're minimal.
But when you are in basically the blue states, you know,
your pack of cigarettes is three, four, five times greater
than it is in the south or on Indian reservations
where they don't have tobacco tax.
So we tried to look at that. It didn't really pan out.
We tried to look at sugary beverage taxes as well,
or sugary beverage intake.
It's hard to do some of these policy questions
in such a small sample, because it is only 30,000 people
scattered all over the place.
But yeah, so it's endless the things you can do.
And we can link to other data.
So there's linkage to Medicare claims data
for the people on Medicare, for example,
and that's used by certain groups to do specific things
because it gives richer outcomes data for certain things.
- [Crowd Member] It's like a mix, you know,
so I reckon that'd influence-
- [Crowd Member] Yeah, no, I figured.
- Oh, so Sully's asking...
- [Crowd Member] It's stuck in my head.
- Can you hear me, Sully? Are you still there?
- [Crowd Member] That changed.
- [Crowd Member] How is that?
- [Sully] Yes, I can hear you, Mary.
- So fatty liver disease, we use something called
the fatty liver index.
It's calculated based on lab tests.
So we don't have imaging deliver.
- [Crowd Member] Okay, yeah.
- So we use the fatty liver index, which is not a bad proxy.
Not great.
There was some resistance in peer review to it,
but that's what we use, yeah.
- [Sully] Cool. Thanks, Mary.
- So we have that in that case folder.
- [Crowd Member] Yeah. Thanks.
- [Crowd Member] Yeah.
- [Crowd Member] How is it going?
- [Crowd Member] That's the question.
- [Crowd Member] It's going well.
- [Crowd Member] We'll see, yeah.
- [Crowd Member] Yeah, it's fine.
- [Crowd Member] Yeah.
- Yeah, Sully, I don't know if you were trying to speak,
but I think what's happening here
was not turned on correctly.
Were you trying to say something?
- [Sully] Oh, I was just saying thank you.
That's good to know, Mary. Thank you.
- Yeah, I can barely hear you.
The sound-
- [Crowd Member] Yeah, yeah, exactly.
- Can we try again?
To see, just so we can test it.
Sully, can you hear?
- [Crowd Member] And so we have to-
- [Sully] Yep, I can hear you good. Is that better?
- The sound wasn't on them.
The mic, you should...
I'm just gonna show Sierra the problem.
This said headphones.
- [Crowd Member] Ugh.
- [Crowd Member] That's crazy.
- So I just changed it to the same.
Turned the sound up.
Not that they can...
I think nobody was trying to speak there.
- [Crowd Member] Right.
I'm just gonna complete that one now. Thank you, though.
- Sully, I'm sorry I didn't go into the chat right away.
- [Sully] Oh, no, it's cool.
But thanks, Mary, thanks for explaining that.
- All right, awesome.
I'm happy to talk to you about it if you wanna look at it.
- [Sully] That'd be great. Yeah, no, for sure.
That'd be great. Thank you.
- Yeah, FLI is kind of cool.
My postdoc tackled that one,
a postdoc that I had in the past.
- [Sully] The fatty liver disease?
- [Mary] Yeah, yeah.
- [Sully] Oh, cool.
- She worked on it.
The papers were a little difficult to publish.
Actually, you know, there's a guy...
Oh, there's a paper.
There's a guy at Columbia who I think did Thrive?
Maybe it was the fifth floor,
and he never finished the paper. (laughs)
But we need an author.
I think it was on stroke.
So if you know someone who might be interested in that,
it's an unfinished project.
- [Sully] Yeah, that's cool.
We should chat for sure.
- Yeah, okay. Awesome.
Take care.
- [Sully] Thanks, Mary.
- Bye. - Yeah, something with-
- [Crowd Member] Exactly.