- [Tom] Welcome, everyone, to Wednesday Nite @ the Lab .
I'm Tom Zinnen. I work here at the UW Madison
Biotechnology Center.
I also work for UW Cooperative Extension.
And on behalf of those folks and our other
co-organizers, Wisconsin Public Television,
Wisconsin Alumni Association
and the UW-Madison Science Alliance,
thanks again for coming to Wednesday Nite @ the Lab .
We do this every Wednesday night, 50 times a year.
Tonight it's my pleasure to introduce to you
Brian Parks.
He's a new professor
in the Department of Nutritional Sciences.
He was born in Fredericksburg, Virginia,
and went to high school there,
and got his undergraduate degree at the
University of Virginia's College at Wise.
And then he went to the University of
Alabama at Birmingham for his PhD,
and did a post-doc at UCLA.
He moved here back in August.
This is his first summer...
oh, excuse me, this is his first winter
of ice fishing.
(audience laughing)
Yeah.
He lives out in cross plains.
He's talking to us about,
he's giving us hope tonight.
Hope.
Hope because he's talking about beyond fast
foods, DNA is also responsible for
expanding waistlines.
I'm very interested in this so I can blame
my parents.
(audience laughing)
Please join me in welcoming Brian Parks
to Wednesday night at the lab.
(audience clapping)
- Thanks everyone for coming out on this
very cold night.
It was my first really cold weather
this week.
I never realized the purpose of a scarf.
(audience laughing)
Until I moved to Wisconsin, but now I'm
very friendly with my scarf.
(audience laughing)
So today I'm going to talk about a topic
that is extremely complex, and often very
socially...people have their opinions, right?
So I'm just going to ask that everyone kind
of keep their minds open a little bit.
Everybody probably has their ideas about
what causes obesity, and what the reasons are
for obesity across the nation and the world, but
I'm just going to present to you the scientific
evidence and then we can talk about it.
So the title of my talk is beyond fast food, DNA
also responsible for expanding waistlines,
and I can't really take credit for this title
because I published some work, when I was
at UCLA, and a news reporter actually came
up with this title.
So I thought they do a much better job of
titling things than I do.
So before we get into kind of some
background on obesity, and the epidemic that's
taken across the nation and the world,
we need to introduce at least one
key measure of obesity.
How do we measure it?
The main top issue is this body mass index,
or BMI, that most people are probably
familiar with.
The basic idea behind BMI is if you take a
person that's the same height and then you
sort of take a ratio of their height and weight,
as their BMI increases, you can classify
their obesity levels.
So normal weight is considered 18 to 24,
and then overweight 25 to 29,
and obesity is above 30.
And then it can break down into more classes.
Now, as you might expect, there are some
caveats to this.
For example, if you're Arnold Schwarzenegger,
when he was involved in Mr. Universe, he
obviously would have an extremely high BMI,
so there are some issues.
But most of us are not professional athletes
or bodybuilders, so for the general public,
BMI works fairly well.
Okay, so now we kind of know what BMI is,
and obesity.
It's really a huge global health problem.
Obesity can lead to a number of
significant problems, including most notably,
it can lead to diabetes and insulin resistance,
it can predispose you to cardiovascular
diseases, such as atherosclerosis.
People that are obese tend to have higher
rates of cancer, as well, and also,
metabolic syndrome.
So you might be asking well what is
metabolic syndrome?
It's worth taking at least one slide to mention.
Metabolic syndrome, or what's sometimes
referred to as syndrome X, is this kind of
myriad of traits,
including central obesity, so kind of that apple
shape, high blood pressure, high triglycerides,
low HDL, and insulin resistance.
And when you're obese, when you become
more and more obese, you're very likely to
have these traits all going together.
And of course one of the most significant
problems with being obese and having a high
BMI is that you can have, it can predispose you
to die, or a high mortality rates.
And this was a study that was done in one
million people, published in the New England
journal of medicine in 1999.
And what you can take away from this is mainly
looking at the solid dark black line.
These are nonsmokers with no history
of disease, and you can see, as you go from
left to right you're increasing your BMI,
and you see the curve drastically goes up.
So in these people, that are nonsmokers with
no history of any disease, the higher their
BMI, the more likely they are to die.
So, obviously obesity and becoming severely
obese is becoming a huge problem and it's
really placing a huge, tremendous burden on
our healthcare systems, not only in the United
States, but also across the world.
This isn't just a US problem.
This is a problem in Europe.
This is even a problem in developing countries.
So, if you want to see the graphs for it,
it is a serious problem, obesity and diabetes.
Here are obesity rates for BMI above 30.
You can see here, 1994, no dark red colors,
and then as we go 2000, 2007, you can see
obesity rates are really escalating, where we
have a lot of the country above 26 percent
for obesity.
And then, diabetes kind of closely follows this,
and that's because when you become obese,
you put more strain on your pancreas, your
insulin levels increase, you need more insulin
to work better, so this is why diabetes is
closely following that.
Okay, so I like to look at things visually, so
I thought I'd do one example.
What if we just take a hundred random, US adults?
35 percent of these people would be obese.
And 10 percent would have diabetes.
So that's a lot of people.
So we're talking about a huge population
across the world.
Okay.
So now that we've kind of gone through some
basics of just obesity, obviously, it can lead to
many serious consequences including
cancers, diabetes, heart disease, and mortality,
and of course it's a global problem.
So what is the cause?
So this is often where people have their thoughts.
Could it be psychological?
Maybe obese people lack willpower.
Maybe they just should stop eating.
I think some people maybe, I often
think that skinny people like to think this.
What about the environment?
We live in a modern world, we work in
desks, we don't move around as much as
we used to, so maybe our environment's
changed significantly.
What about biology?
Genetics.
Maybe that's what's predisposing us
to being obese.
Or maybe it's a combination of them all?
And that's probably really the true answer.
So I'll try to present some data,
or looking at the environment and biology.
I'm not going to talk about the psychological
or socioeconomic's associated with obesity,
because I'm not a psychologist,
so I can't really speak to that answer.
But I can talk about biology and genetics.
So what about our environment?
Our environment is certainly changed, right.
Wherever we go, we're surrounded by places
that serve really high calorie food, energy dense,
rich in sugar, rich in fat.
I mean, it's everywhere, right?
You can drive down the street.
All these places, the majority of their menu
would be packed with calories.
And then you couple that with a snack food
industry, and when you think about it,
this is a billion dollar industry that's designed
to make you eat when you don't need to eat.
That's a powerful force.
Constant advertisements.
Really, do I need to have some Reeses
in the afternoon?
Probably not.
Do I?
Sometimes.
(audience laughing)
The other thing I find really staggering,
and this is really where there are a lot of
research coming out now, is the amount of
sugar and refined carbohydrates that we're
consuming in today's society is really astounding.
So this is an interesting look at
sugar consumption.
This is actually done in England.
From 1700 to 2000.
You didn't consume much sugar in 1700,
probably because there wasn't much around.
It came from the Caribbean, and it was
pretty hard to get.
And then gradually, over time, we're just
really increasing our amounts of sugar
through the current century, and then up to
now we're just drastically increasing it.
And currently, it's anywhere estimated,
anywhere from 150 to 175 pounds are the
current estimates of sugar per year.
So if you just do a back of the envelope
calculation, if we say on average somebody
might eat 150 pounds of sugar, that's 20,000
sugar packets from the coffee place!
That's astounding, right.
20,000 packs of sugar you're eating a year.
When you think about it like that, it's just crazy!
Of course, it's not all,
we don't eat sugar by the packet, it's often
in our foods.
McDonald's puts it in the buns,
it's everywhere.
It's just amazing that sugar and refined
carbohydrates are just everywhere.
So clearly our environment's changed.
But what about genetics?
I put my favorite genetics slide ever here.
So clearly genetics has a powerful role
in traits, such as height.
Likely, if your parents are tall, you're likely
going to be tall.
And this is similar to obesity.
If you have obese parents, it's likely
that you will be obese too.
The heritability of obesity is anywhere
estimated up to 80 to 90 percent.
That's right up there similar to height,
anywhere from 80 to 90 percent.
So clearly genetics is a strong force.
Just like you can have the horizontal
stripe and the vertical stripe parent,
and the checkered stripes.
(audience laughing)
So, very powerful force.
So I wanted to go through one
really, really famous case study.
So if we look on the boy on the left,
clearly obese.
Is it maybe genetics, or willpower?
If you ask me, well this boy maybe just
eats too much food, I would tell you yes,
this boy eats a lot of food.
Huge amounts of food.
More than most people in this room.
And that's because this boy has a deletion
or mutation and a specific protein that makes
it so he can not shut off his amount of
food that he eats.
He doesn't know when he's full.
He eats all the time.
But then, this is actually the same boy,
on the right.
This is supplemented back with this
powerful protein, and you can see over,
this is over about two years, I believe,
supplementing back with this protein.
You can see he's lost quite a bit of weight.
He's gotten taller because it's been a few years.
But clearly, he is lacking willpower.
He constantly eats.
But there is a very powerful genetic cause
for this, because he lacks the specific protein.
And this protein is called leptin.
And leptin is secreted by our fat tissue, and it
circulates to the brain to inhibit food intake.
So the boy simply lacked the ability to produce
this protein, and he was not able to shut off
the ability to stop eating.
So, while he might lack willpower,
clearly there's a genetic underlying cause,
and that's simply all my point,
is that there is a genetic reason for this.
And I'm not going to go into the biology
of leptin.
It's a huge body of literature.
But this is extremely powerful hormone
that regulates a lot of obesity.
So the big question that I really have in my
research, and one of the questions that
I've really tackled in the past six or seven
years, is that of how do genes and our
environment interact to contribute to
obesity and diabetes?
Clearly, we know that our environment
has changed.
We eat lots of sugar.
We eat lots of refined carbohydrates.
We're surrounded by it.
Our genes probably haven't changed a whole lot,
but there are clearly genetic reasons to why
some people are obese.
But then the question I wanted to understand
was how do these environmental factors
interact with genetics?
Per se.
We all know somebody that can eat McDonald's
Big Macs every day and never gain an
ounce of fat, whereas if I look at one,
I'm going to gain probably five pounds.
So what causes that?
Why are some people able to do that, and
some people aren't?
So that's really kind of the basis of my research.
There was a very famous study done in the 90s
by Claude Bouchard in Quebec, Canada,
where he kind of tried to look at this question
of environment and genetics, and he did
it using twins, specifically monozygotic twins.
So these are people that would share the
same DNA, so since they have the same DNA,
you would expect that those twins to respond
the same potentially to diet.
What they did in this study was they overfed
these twins by 10,000 kilocalories a day
for a couple weeks.
And then they measured their responses
to this overfeeding.
And what you can see is each dot represents
two twins, so twin one and twin two.
So what you see is, say, one pair of twins
gained about this much fat, and then another
pair gained about this much.
And there was a little mix between.
But what you see is there was kind of a continuum.
Each twin appeared to gain about similar.
So this was really some of the first evidence
that said indeed, genetics is responsible for
these environmental interactions, per se,
that both twins appeared to respond
similarly to the diet.
So I wanted to extend this a little bit
farther and ask a more detailed question,
and really understand.
Are these genes and environmental
interactions really strong?
What are the genes that are contributing
to these traits?
And how are they predisposing to
obesity and diabetes?
So the big question is: how do we study this?
Well what we can do is we can take advantage
of genetics.
So, every person in this room has their own
unique genetics, or genetic makeup.
We can really harness this information.
We have powerful technologies now where
we can sequence your DNA, we can identify
the differences between different people,
and we can harness that power to really
understand what's causing these differences.
So if we look at a simple example,
so we have our DNA, right, As, Ts, Gs, Cs,
just strings of code.
So these are about 20 different pieces of DNA.
Doesn't really look like much, does it?
But what if you were to look at it a
little bit closer?
You might see there's variations in this DNA.
For example, some of these people might have
a G, and some people might have a C,
and so on so forth.
So this is what we call a single nucleotide
polymorphism, or SNIP.
So different people, just like different people
in this room, some people might have a G here,
at this position, and some people might
have a C.
So this is kind of like a flag.
It tells us that there's differences in the DNA.
And over here at this position, we see the
same thing.
Some people have an A, some people have
a C, and so on.
So these are two different flags on the DNA
that tell us there's variation between
these individuals.
So then, what if I were to tell you that
some of these people have a disease?
And some people don't.
The bottom half.
Say these people are predisposed to obesity
and these people aren't.
Well the first thing you'd probably notice is
that, "Hey, all these people with obesity seem
to have these 'A's."
Maybe there's something going on there.
Maybe there's some genetic variant near here,
or maybe this is coding for something that's
predisposing these individuals to obesity.
And that really forms the basis of kind of what
I'm going to talk about today, is this analysis,
in its simplest form.
So if we look at it at a genome wide level,
and this is what we call genome-wide
association study, or GWAS.
So this is what's really revolutionized
genetics in the past decade, is our ability
to look at these DNA differences on a
genome wide scale.
And when we do that, we can use
computers and do analysis,
to look at, and see if there are any
associations with the trait.
So say we're interested in obesity, and we
can plot this out.
So this is across the genome, looking at
all the chromosomes, and we can plot out the
P value, or the level of significance,
and what you'll see is that there's peaks
and valleys, and peaks and valleys,
and peaks and valleys, and this is actually
called a Manhattan plot, because it's
supposed to look like the skyline of Manhattan.
You hope it does, at least.
Sometimes it doesn't and then you're disappointed.
But really, all you're looking at is,
say you see a peak right here.
All that means is just like that example
I showed you, that one of these variants
has a lower level than the other.
So there's a difference here, and that's significant.
So say these people are more predisposed to
obesity than these people, that's all we're doing.
We're just doing it on a genome wide scale,
doing millions and millions of calculations.
And then, if you look at an area that's not
significant, you see that there's no difference.
So, this is how we can kind of analyze this data
on a genome wide level.
And this can kind of tell us, potentially, what's
contributing to obesity, diabetes, and also,
what I'm really interested in, is these gene
environment interactions.
Okay.
So this has actually been done for BMI,
and it's been done in huge, huge numbers
of people.
For example, this paper
looked at 250,000 people
and measured their DNA variations,
and looked at what was associated with BMI
in these people.
And what they found is astounding
number of these peaks.
You can see them all over the place.
So clearly, there are genetic factors that
are controlling BMI, and there are labs
across the world trying to understand
what some of these regions of DNA are doing,
specifically, probably many of you noticed
this huge tall one right here.
I think scientists have worked on this
for decades, trying to figure out,
and only in the past year have they
finally figured out that this variant here,
this big tall one, what it does is it
changes your ability for energy expenditure.
And I'm not going to talk about that, but I'll
just say that some people have a variant
here, associated, where they actually have
higher levels of energy expenditures
than others.
But, humans aren't the best research subjects.
We all have a different environment, we all
sleep differently, we have very different
diets, certainly living in Wisconsin versus
California, my diet has changed significantly.
I think my beer consumption has gone up.
My brat consumption has gone up.
(audience laughing)
And my cheese consumption has
definitely gone up.
I had never had a cheese curd until
moving to Wisconsin.
(audience laughing)
Certainly levels of exercise are very variable
between people, and just lifestyles in general
are extremely different.
So this genome wide analysis, even though
we can use this powerful technology to
do that, it's kind of a little bit plagued, right,
because everybody's so different.
And clearly these lifestyle factors have such
a huge effect on obesity and diabetes
and these diseases.
So my work works with mice.
So mice are a lot like humans, except
they live in cages.
And also in the wild.
But we can harness the power.
We have lots of different types of mice.
And like humans, different types of mice
can have different types of genetic backgrounds.
And they're really nice, because
they can only eat what I give them to eat,
so I can adjust their diet.
I can control a lot of factors that are very
variable between humans.
So in that sense, they're a very powerful model.
So my basic question was really to understand
how does this constant consumption of these
high fat, high sugar, refined carbohydrates
diet, how is that interacting with the DNA,
and potentially, what are the genes
responsible, and also, what's also predisposing
us to develop diabetes in addition?
Because some obese, many obese people
don't become diabetic.
So my research really involves
really more than a hundred unique mice strains.
They actually don't come in all these colors.
(audience laughing)
Most of them are black or white, gray, tan,
those kind of colors.
So really it's just different types of mice
that we can use that have a different genetic
background that vary between each other,
similar to the human stuff that I just showed you.
And this panel of mice that we call is called the
hybrid mouse diversity panel, and this was
developed in the lab where I did my post-doc.
And, like I said, it's just a hundred fully
genotyped, genetically unique and bred mice.
We have about 500,000 different variations.
Huge diversity and clinically relevant parameters.
No matter what trait you're looking at, they're
very different between them, whether it be
obesity, diabetes, maybe heart disease,
and the great thing about these mice is we
can do the same thing as they do in humans,
we can do GWAS, we can do genome wide
analysis and we can do this across lots of
different scales of biology.
We can look at proteins, lipids,
since they're mice, we can take out specific
tissues and look at those directly very easily.
And the great thing is we can really understand
biology as it works under kind of natural
genetic variation.
We're not looking at specific knockouts
or anything like that.
We're kind of just tweaking biology with different
polymorphisms, just like all of us vary
differently by our DNA.
Okay.
So on to the project.
So the project that I did and designed was what I
kind of called the obesity and metabolics
syndrome project.
And here's the study design.
So essentially all these mice, these hundred some
mice, we aged them for about eight weeks.
When they were about eight weeks old, we
switched them from their kind of normal diet
that they eat in the vivarium, to a high fat,
high sugar diet.
And then, every two weeks after we intervened
with this diet, we looked at their body fat
percentage, so we actually took them and
measured the amount of body fat they had.
And then after the study was done for about
four weeks, I did a food consumption study
just to see how much the food they were eating,
and then at the end of the study,
we terminated and collected all their tissues.
So I wanted to choose a diet that was really
relevant to human obesity.
A lot of times in research we use
very artificial systems,
where, per se, the diet might contain 60
percent from fat.
That's not probably really relevant to many
humans diets, 60 percent from fat.
So what we ended up doing was
choosing a diet that was 32 percent from
fat, here, so the diet we chose was right here.
Here's the standard mouse diet that they
normally eat, so protein doesn't change,
carbohydrates fairly similar, obviously fat
is significantly increased, and the amount of
sugar is drastically increased.
And the source of fat is butter fat
and corn oil.
And if you look at it, I didn't actually know this
at the time, but it doesn't,
it isn't that far off from a big mac and a Coke.
Pretty similar.
Obviously the source of fats would be
very different, but just for fun, it's not
too different.
So we do think it's probably relevant.
Especially with that high amount of sugar.
So what does it look like when you feed
a hundred different types of mice?
And actually, this data is 1500 different
types of mice, or different, unique mice.
So just huge variation in response to this diet.
So this is normalizing each mouse to baseline,
where we intervened with this diet,
and then taking every two weeks, we measured
that body fat percentage, so we're able to
calculate the percent body fat gain.
So what you can see is, it's just amazing, right?
Some of these mice, they're just gaining
almost, not exponentially, but just continually,
linearally gaining upwards, 400 percent of
their body fat in just eight weeks, and then some
of the mice don't gain any, they just kind of
eat the diet and don't seem to gain any
fat at all.
And then there's kind of a mixture of population
in between.
So clearly, just huge variation in their ability
to put on fat.
And the other kind of thing that you might notice
from this figure is that
most of the mice seem to about, after two
to four weeks, they kind of reach this plateau,
and then they kind of steady off.
And this is kind of another interesting concept
in obesity, where you reach this set point,
and you don't seem to really get any more fat,
and this is kind of unique, where there might
be forces that strongly resist continued
body fat gain.
And I like to leave this figure up, just for a minute,
because it took me two years to generate, so...
(audience laughing)
If everybody could just look at it for just a minute.
(audience laughing)
Okay, so what about that food intake, right?
So a lot of people always ask me well, Brian,
the mice that are gaining the most weight, are
they just eating more than everybody else?
And so we did this food intake study,
so these are all the dots from all the mice,
and this is looking at food intake, grams per day,
compared to body weight, and what you can see
is that there is indeed a correlation, or
relationship between food intake and body weight,
and also if you look at it a little bit nicer, since
we have all this body composition data, we can
look at lean mass, or muscle mass, and you can
see there's an even stronger relationship.
So that makes sense, right?
If you have more muscle mass, you're going
to eat more than most people.
And the mice that have more lean mass
are eating more.
But what was kind of surprising to us was that
when you look at body fat percentage, there
wasn't really a strong relationship,
and if you look at the amount of body fat
percentage growth, the amount that they
gained, during the start and when we took
the food intake study, there doesn't appear
to be a relationship at all.
So at least for these mice, food intake itself
did not account for the levels of obesity
that we observed.
Okay.
Now,
the big question was, so did this big project,
analyzed all these mice, we have so
much variation.
Some mice don't gain any fat at all, and then
we have some mice that just don't seem
to ever want to stop.
Are there any genetic controllers?
Is there anything genetically inherent that's
predisposing these mice to obesity?
Maybe some mice have susceptible genes,
maybe some mice have protective genes.
So that was really one of the big questions.
And back to our GWAS analysis that we can
do in the mice, so the short answer is yes,
I spent two years in the mouse room and I got
the right answer.
I got peaks and valleys and peaks and valleys.
So these peaks are regions of the DNA that are
associated with body fat gain when they're
consuming this high calorie diet.
So this was really exciting.
This was some of the first evidence that
we've ever generated that shows that our
DNA is responsible for how our bodies respond.
Scientifically, we can show that.
Not just anecdotally saying you can eat Big
Macs and I can't.
And it was really even more exciting to us
because this is obviously a study in mice,
there's caveats with mice, they're not humans
is the problem.
So, but what was exciting about this is if
you look at some of these regions of DNA,
say chromosome three right here,
which I'm labeling Amy1,
this is actually right an amylase gene.
So amylase genes are really responsible
for breaking down starch.
So it's not too hard to envision how
variations in starch breakdown might
contribute to obesity.
Also, if you look over here on chromosome 18,
there's a gene called NPC1.
This is Niemann-Pick C1.
And these two genes are the most exciting,
and a little bit disappointing, too,
in a sense, because they've already been studied.
But they've been identified in human studies.
So here in a study published in 2009 in
Nature Genetics, they identified a variant
near NPC1 that predisposed humans to obesity.
So that was exciting.
We found the same variant,
or right near there.
And then also, in 2014, recently,
they found that variations in amylase genes
can predispose humans to obesity.
So we saw this human connection with our data,
which was really exciting, because that makes
me be able to stand up here and say, well every
other locus probably has, or every other piece
of DNA that I found, probably contains a gene
that's relevant to human obesity.
So it was exciting.
There's kind of this conservation of potential
pathways, or biological pathways, operating
to contribute to these diseases.
But what about some of the other regions of DNA
that were not able to see a human connection?
So clearly, here's looking at one,
so here's the picture of all the different DNA
variants that we found, or regions of the genome.
So here's kind of looking at it a little bit closer,
so you can see the SNIPS, the p-values are very
low, or the levels of significance is very low, it
kind of goes up really high, stays up high,
and goes down, and comes over.
So there's about eight different genes
in this region.
One of them that came out in our analysis
early on was this gene called CBR1.
And this gene is called carbonyl reductase 1.
So you might be wondering, what is carbonyl
reductase 1?
NADPH dependent reductase with broad
substrate specificity.
So really, it just catalyzes a bunch of
different reduction reactions for carbonyl
containing compounds.
And the main point is not really to
understand the biology of this carbonyl
reductase 1, but for us to say that
this gene has never before been studied
in obesity and metabolism.
So it's a completely brand new gene that
we can relate to this trait, or obesity.
And as many of you probably know, or if
you don't know, in the mouse we have the
unique ability we can knock out specific
genes, we can make what we call knockout mouse.
So, luckily, many years ago, somebody had made
a carbonyl reductase 1 knockout mouse,
so this would be a mouse that does not
produce this gene, and we can test that in
our model.
So what we did is we obtained these mice,
and lo and behold, when you put these
knockout mice on this high fat, high sugar diet,
you can see they gain about half as much fat.
So that kind of was really exciting.
We were able to identify a region of DNA,
we were able to pinpoint a gene, and then
validate it and say well, it looks like we might
have a new gene that's affecting obesity.
Of course science is never that easy, and this is
only half the battle.
We don't have any idea of how this gene is
actually contributing to obesity.
As you can see here, this gene is expressed,
the protein is produced in multiple different
tissues, and it's really highly expressed
in the intestine, specifically, the first part of
the intestine, the duodenum.
So maybe this gene is somehow contributing
to effects of intestinal lipid absorption.
It's very speculative at the moment.
But, the main point is to show you that we can
go from a genome wide study to DNA to
new gene to actually identify a gene that's
contributing to obesity.
So that was really exciting.
And we're currently trying to understand more
about how this gene is contributing
to obesity.
Okay.
So what about insulin resistance
and diabetes?
So as I mentioned, in addition to obesity,
diabetes and insulin resistance follow
closely behind.
So we wanted to look at this in this
mouse population.
So as you can see in this graph,
this is looking at HOMA-IR, and this is
basically a ratio of insulin and glucose,
and all you need to know is the higher
HOMA-IR you have, the more likely you
are to have diabetes, and the lower, the more
likely you are to be insulin sensitive.
And you can see a huge spectrum where some
mice have really high levels, and some mice
have low levels.
The other really interesting part about
this data that I'm not going to talk about today,
is that by and large, the females in red, have
significantly lower levels of HOMA-IR, for
almost every strain that we look at.
And this is because females have estrogens,
and estrogens are insulin sensitizing,
so that's good.
Looking at the male data, we wanted to see
if we could find any genetic variants that were
associated with the development of this
diabetic phenotype.
So, what we did was
we did our genome wide analysis again, and
this is actually mapping plasma insulin levels,
so the higher levels of insulin would be
suggestive of diabetic mice, and lower levels
of insulin are sensitive mice,
and what we're able to do is find
one significant region, in chromosome eight,
and we were able to pinpoint this gene
called AGPAT5, and if you want to see another
neat picture of this, this is kind of to demonstrate
as I showed earlier, if you have the one SNIP, you
have high levels of insulin, if you have the other
SNIP, you have low levels.
And what's exciting about this is if you also
carry this SNIP, you have high levels of this
AGPAT5 gene, and low levels on the other one.
So this kind of goes with high levels of AGPAT5,
high levels of insulin, low levels of AGPAT5,
low insulin.
So we made this general hypothesis that
if we inhibit AGPAT5 in mice, maybe we can
improve insulin and diabetes.
So you might be wondering,
what is AGPAT5?
Well I'm not going to get into all the biology,
but I'll just say it's a lipid acyltransferase.
So all that means is that it takes a
lysophospholipid, so this is a lipid with one tail,
and it puts another tail on it.
So it makes a lipid with two tails.
And it can do this to a number of other
lipid species, I'm just demonstrating one here.
So that's the reaction that it does.
So, we teamed up with a pharmaceutical company
and we developed a therapeutic antisense
oligonucleotide that targets this AGPAT5 gene,
and all this is is this is a way to inhibit this
gene and suppress its expression.
And the mice that were treated with this therapy
were able to reduce the levels of AGPAT5
expression in the liver, and also in the
adipose tissue.
So very significantly, 92 percent, and 80 percent.
So we developed a drug to basically target the
gene and inhibit its expression.
And based on our genetic data, we would
hypothesize that if we inhibit this, this would
improve diabetic symptoms.
And that's exactly what we found.
So if we treat mice or rats with the high fat
diet for three months, and then we intervene
with this drug, we can improve what we call
a glucose tolerance test.
So this is when you give an injection of
glucose and you monitor the glucose
disposal across time.
So glucose is disposed primarily in the muscle,
and basically, the take home message is that
when they get our AGPAT5 drug, the mice
dispose of the glucose faster,
and more efficiently in both mice and rats,
than the control.
So the red one is better than the black one.
So we developed a drug to be able to improve
one symptom of diabetes, which is
glucose intolerance.
And then we've been working on this a lot here
in the lab since I've been here, since this is one
of the most exciting projects we have,
and we've also recently shown that,
in addition to improving glucose tolerance,
we can improve the action of insulin.
So one of the problems in diabetes and
insulin resistance is simply that your muscles
and your body cannot respond to insulin,
they become resistant.
So your body produces more insulin to
overcome this resistance.
So it's ideally suited that you find a way to
improve the insulin sensitivity.
So what you can see is looking at two different
types of mice, so these are mice that are getting
either a control drug, or an AGPAT5 drug,
at two different concentrations in blue and red,
a higher dose in red than blue.
And you can see these mice are insulin sensitive,
so they get a bolus of insulin, and this drives
glucose into the muscles and other tissues,
and you can see that glucose goes down, and it
doesn't matter in any of these treatment groups.
But if you look at the other strain of mice here,
you can see that in the black, they get the insulin
dose, glucose drops, and then it comes right
back up.
But in our drug-treated mice, and AGPAT5, you see
that glucose is, after the insulin, glucose gets
disposed and comes back up, so down farther
significantly, almost dose dependently.
So the higher dose a little bit better.
So what we've been able to do is improve
the action of insulin.
So this is very exciting, because diabetes drugs
have pretty much been the same for the past
30 years, so potentially, we might have a new way
to improve diabetes.
So obviously there's a lot still going on with this.
A lot of big questions we don't understand.
So specifically, what is the tissue specificity of
this AGPAT5?
It is expressed in multiple tissues, is it maybe
in the liver, adipose, muscle, or other?
How exactly is AGPAT5 affecting the insulin
pathway, you know, why is it improving
insulin signaling?
We don't know yet.
And then, we have some evidence that AGPAT5
might be influencing the way that mitochondria
operate, so that would be affecting their energy
expenditure, so that would be quite exciting.
And then, you know, all I said was that it's a
acyltransferase, that it made a one tail lipid
into a two tail lipid, but why does that matter?
What are the specific lipids that are making
this phenotype, you know why is it doing that?
We don't know.
So in summary,
I hope I was able to convey that
obesity, it is a complex disease.
Everybody has their opinions.
Clearly genetics plays a role in predisposition
to obesity.
Clearly environment plays a role.
Clearly psychological factors play a role.
Clearly socioeconomic factors play a role.
And it's probably a little bit of everything.
How do we cure obesity?
I heard a talk once from the former surgeon
general, when I was at UCLA, and he was the one
that took on big tobacco and won,
and he's really interested in obesity.
And he came and gave a talk about obesity.
And how do you try to tackle obesity?
And you come away with the talk basically saying
we don't know how.
We don't know how.
Because what do you do, you tax sugar sodas?
I mean, that's not really the answer.
Clearly it's going to be a complex answer, and
interventions and lots of work to do there.
Hopefully what my work will help
maybe identify therapies to help people that
are predisposed to diabetes.
We're never going to find a drug that you're going
to be able to take that's just going to make you
not gain weight if you eat bad food.
Clearly, gene environment interactions do
drive the disease in obesity.
And understanding how these interactions occur,
hopefully my work is starting to shed light
onto some of that, and will identify some of these
biological pathways.
And of course, genetics can be used
to identify new therapeutic targets and
biological pathways.
So I've shown you, highlighted two examples,
CBR1 and AGPAT5, where we've been able to
identify brand new genes that affect a very
complex process, that seem to be
pretty powerful, and we're trying to understand
what biological pathways are they working through.
So hopefully over the next five years,
hopefully, maybe 10 years, we'll be able
to understand how these genes are working.
And maybe, just maybe, in 20 years,
maybe something will make it to a clinical trial.
So there's a lot of people to acknowledge.
Mostly people when I was at UCLA,
my mentor, Jake Lusis,
and I put up a lot of the people in the lab.
I just want to point out
Elizabeth Nam.
She was an undergraduate at UCLA,
and she helped me, I think she came in
every day, and helped me work with these
mice for two years.
And I was really excited when I came here to
find that here at Wisconsin, you have
similar undergraduates that have a really
passion to do research.
We do work with some pharmaceutical companies,
Bristol-Myers Squibb and Isis Pharmaceutical
company, pharmaceuticals.
They were the ones that helped us develop
the Agpat5 drug, and
I'd like to acknowledge my funding from NIH.
That's all I brought today, so hopefully we
have some good questions.
I was told that you guys are very vigorous.
(applause)