- [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)