Metabolic Health

Tom Bunn: Good morning everybody, and welcome to I Select’s deep Dive webinar series. My name is Tom Bun. I’m an associate on the Isec Buns Ventures team, and I’m excited to welcome you all to our discussion today for those new to these webinars. I select is an early stage venture capital firm in St. Louis, focused on early stage companies in food, agriculture, and health.

I select invest at the forefront of innovation, seeing emerging problems, solutions and technologies at their infancy. We use these deep dive presentations not only as a way for us to better engage with and understand new science and technology, but also to engage with the experts and entrepreneurs who are driving change in innovation in their respective fields.

One theme that we have been researching is metabolic health for increasingly the absence of metabolic health. Metabolic Health comprises so much of what we focus on at isec. It touches healthful and sustainable food systems, chronic disease management, longitudinal data, cutting edge biomarkers, and a massive opportunity to do well and do good.

For these reasons and others, which we’ll cover in today’s webinar. Metabolic Health is of increasing interest to I select a few process comments. We are not soliciting investment or giving investment advice in any way whatsoever. This presentation is general industry research based on publicly available information.

We’ve invited you to this because you are technologists, thought leaders, entrepreneurs, industry experts, early adopter customers or sophisticated investors that are part of the isec Network. We value your thoughts, questions, comments, and insights into this topic and greatly appreciate it if you actively engage during the presentation.

We will have q and A open throughout the, Presentation and then we’ll have hopefully some time towards the end to get to any questions that remain. So thank you in advance for your attendance and active participation. Finally, this presentation is being recorded and will be available for replay.

So with that, I’m pleased to bring you this week’s deep dive on Metabolic Health Ke

So quick table of contents. We’ll do some quick speaker introductions. We have a great a great crew of doctors here today to, tell us about their work and their research and their companies. I will introduce you, introduce them here in just a second. Then we’ll get into some background.

I will briefly give some overview on metabolic health trends and how I select is thinking about it and thinking about the opportunity. And then we’ll get right into the expert discussion. Finally, as I mentioned, we will have some time for conversation and q and a.

So again, a big thank you to our guests. We have a great, crew today. We’ll start with Sarah Godfried. Sarah is the director of the Precision Medicine Program at the Marcus Institute of Integrative Health. At Jefferson Health. She’s a clinical assistant professor in the Department of Integrative Medicine and Nutritional Science at Sydney Kimmel Medical College at Thomas Jefferson University.

Dr. Godfried has developed novel clinical programs that are highly personalized with a focus on scientific wellness and grounded in deep phenotyping of the gene environment interface. She explores innovative ways of optimizing performance, energy, metabolism, hormones, muscle mass, bone density, sexual function, gut brain issues, and healthy aging.

She’s a New York Times bestselling author of three books, the Hormone Cure, the Hormone Reset Diet, and Younger, and she just came out with a new book called Woman Food and Hormones. She’s, an expert in functional medicine and is one of the nation’s top physicians for evidence-based bioidentical hormone therapy for women and men.

Thanks for joining us, Sarah. Secondly, we have Dr. Casey Means. Casey Means is a Stanford trained physician, chief medical officer, and co-founder of Metabolic Health Company Levels and associate editor of the International Journal Disease Reversal and Prevention. Permission is to maximize human potential and reverse the epidemic of preventable chronic disease by empowering individuals with tech-enabled tools that can inform smart, personalized, and sustainable dietary and lifestyle choices.

Dr. Me’s perspective has been recently featured in the New York Times Men’s Health, Forbes Business Insider, TechCrunch Entrepreneur Magazine, the Hill Metabolism Endocrine. Today and more, she has held research positions at the N I H Stanford School of Medicine and N Y U. Thanks for joining us, Casey. And finally, Dr.

Mark cela. Dr. Mark cela is a retired Air Force Reserve, Lieutenant colonel and practices family medicine in Ranson and Martinsburg, West Virginia. He’s a professor at West Virginia University School of Medicine and conducts continuing medical education courses on health, fitness, and running through Health Fit you and develops the US Air Force Efficient Running Program.

Mark has been an advocate for nutritional science and helped develop the Med Chefs program for West Virginia University School of Medicine and has published several papers. On low carbohydrate diet for diabetes and metabolic syndrome. He has also been named a distinguished mountaineer by the governor of West Virginia, a Blue Ridge Outdoors, pioneer Air Force Athlete of the Year, Colorado Academy of Family Physicians Teacher of the Year, and is inducted in the Marine Corps Marathon Hall of Fame and has received the President’s Award from the American Academy of Pediatric Sports Medicine.

So thank you all to our guests today and excited to get into the conversation. So a little bit of background here just on what metabolic health is. So we’ve all heard the word metabolism probably since we were just kids. And you might think you have a fast or slow metabolism in that it’s static.

But turns out that’s not really the case. So metabolism was all the chemical and cellular reactions. Produce and store energy from food in the human body. And it turns out when things aren’t ideal, we get what’s called metabolic syndrome. And as you can see here, metabolic syndrome is diagnosed when someone has three or more of the following ailments.

So that’s high blood glucose, which we’ll talk about in greater detail today from all three of our, great guests. That’s blood, sugar levels low levels of HDL or the good cholesterol in the blood, high levels of trig, triglycerides in the blood, large waste circumference. I believe it’s above 40 inches per men and above 36 for women and high blood pressure.

And again, it turns out that’s, this is actually fairly rare to, to have absence of of these ailments. And a very important and seminal study. A couple years ago, the, at the university of North Carolina, it found that only 12% of American adults, or about one in eight Americans are metabolically healthy by the metrics that I just discussed on the left.

Blood glucose, htl, triglycerides, waste, and high blood pressure. Again very, rare. And what this means the way I select is looking at it is really as a source of problems downstream of metabolic health. So if I select we’re invested in companies related to diabetes obesity cancer and tangentially cardiovascular disease.

And really the way we’re thinking about it is that metabolic syndrome is, upstream of these Of these diseases, which are incredibly taxing on the financial system and incredibly common. So while obviously there’s been a lot of money spent on trying to address the symptoms and manifestations of the disease of these diseases we at select are increasingly interested in kind of the, fountain the, well of of, upstream causes that are causing these diseases.

And increasingly that’s pointing us in the direction of, metabolic health and how we can really prevent and, delay onset of all these incredibly taxing diseases on the US healthcare system. So that’s where we’re coming from. And we have again, a great group of entrepreneurs, physicians, and researchers to help us understand this a little better today.

So Dr. Sarah Godfried is with us. Sarah, thank you for joining.

Sara Gottfried: My pleasure, Tom. So happy to be with you, with Joan and with the I Select team and all of our viewers and listeners.

Tom Bunn: Yeah, it’s great to be with you. So can, we start by talking just a little bit about why should the average person care about, metabolic health?

I know I, I mentioned some of the downstream causes, but how do you frame the problem and, why should people really pay attention to it?

Sara Gottfried: The way I frame the problem is with an analogy. So I was just watching a show called the Hundred Foot Wave with my husband last night, and I think that this is a really apt analogy because metabolic health has become such a serious problem in this country and really worldwide.

And the fact is most people don’t know about it. So you mentioned already that about 88% of Americans are metabolically unhealthy. They have at least one of those criteria that you mentioned of metabolic syndrome, but those five criteria I would say are somewhat outdated. We can look much deeper at metabolic health, and we can actually predict the transition from health to pre-use much earlier.

So the way that I talk about it with my patients is that metabolic health is really more important than your bank account. It’s more important than your retirement account. In fact, you should think about it as your retirement account. Don’t wait until you’re 65 to start caring about metabolism, care about it when you can really do something about it, which is as early in the process as possible.

And when it comes to some chronic diseases, whether that’s hypertension, coronary heart disease, Alzheimer’s disease, these changes are happening under the hood way earlier than you might expect as soon as in your twenties, thirties, forties, and fifties, certainly by midlife. So that’s how I frame it for my patients.

And I don’t just take care of women as the director of precision health. I take care of both men and women. I even take care of professional athletes, and it’s amazing to me that. N b a players that are playing games during the season right now, they’ve got typically two to three games per week.

They’re doing so much training, and yet I can tell you somewhere around 20% of N B A players, at least that I’ve taken care of, which is the N of 20 have pre-diabetes. So it’s really important to care about this, to understand what’s going on with your own metabolic health. And I would even challenge our listeners to, to know what your fasting glucose is like Elise, start there.

Don’t outsource it to someone else, to a healthcare professional. Know what those numbers are.

Tom Bunn: Awesome. I love the analogy of, the bank account. You wouldn’t check your bank account once a year. So why, check your, lipid panel and your metabolic panel once a year? Because it’s frankly as important.

So can you talk a little bit about about some of the, research you’re using to diagnose and, recognize patients at, an earlier and earlier stage and where you think that’s going?

Sara Gottfried: Yeah, so I’m gonna, I’m gonna nerd out with you guys for a moment because I’m trained as bioengineer.

And what we know when it comes to network medicine is that health is a state of homeostasis. When you have a perturbation to that state of balance a steady state when you have a perturbation that puts you into a pre-disease state, in this case with metabolic health, that would be pre-diabetes, that then can progress to a disease state.

And a new state of homeostasis. Now this is, this homeostasis. It’s not the kind of homeostasis that we want. So as you think about those three points, health to pre-disease, to disease, what we know is that along that continuum, the sooner that you intervene, the better. So in my research, what we look at is the earliest biomarkers of the transition from health to pre-diabetes.

So we look at a lot of different buckets. I do multi omic phenotyping, so we look at genotype. There’s dozens and dozens hundreds of genes that are involved in the glucose and insulin signal. We look at the microbiome, we look at many other oms including the metabolome, the transcriptome oms that maybe we don’t have as much time to get into today.

But what we’re trying to understand is how does a dense data set. Help us to identify people who are at risk and how does that compare to the gold standard? Because the gold standard is that we do a single snapshot. While that needle is in your vein, maybe you go see your primary care doctor once a year and you’ve got the, blood draw, the vena puncture.

We draw something like a fasting glucose. We look at your hemoglobin a1c. Hopefully you get at least a lipid panel maybe even an advanced lipid panel. We look at some of these measures that you’ve mentioned already, like H D L D L, so forth triglycerides. But that is such a limited picture of what’s going on.

The hemoglobin A1C is a, an average of what’s been going on for the past three months, and it’s not an even average. It’s it’s, more the more recent six weeks is more highly represented. So in our work, With identifying patients at an earlier stage, we’re finding some of these biomarkers that are incredibly important.

And I would say leading the pack of biomarkers is a continuous glucose monitor. So we’re now doing a systematic review and meta-analysis looking at continuous glucose monitoring as a crucial indicator of a change in metabolic health. And some of the data that’s been published, including the study that’s shown here indicates that when you have more comprehensive data, such as we get with continuous glucose monitoring, it picks up about 15% more pre-diabetics than the standard biomarkers like fastened glucose and hemoglobin a1c.

Even to our glucose tolerance test, it also picks up 2% more type two diabetics. So looking at these earlier biomarkers I think is crucial.

Tom Bunn: Fantastic. And I’ve heard you talk a lot about n of one experimentation. I, imagine that n of one experimentation is really focusing on some of these biomarkers, but can you, can we back up and can you explain what n of one experimentation is, why you think it’s so crucial and how you are using it with, your patients?

Sara Gottfried: So N of one experimentation is probably the most important tool in our toolbox for those of us that practice precision medicine. And the idea is pretty simple. It’s just that instead of doing medicine for the average, which is what I was taught to do at Harvard Medical School, so medicine for the average is where you have randomized trials of, say, interventions for patients with pre-diabetes.

In those randomized trials, you get an answer for a population, it becomes medicine for the average. Now, that’s also what I would call in precision medicine. I say that with so much love and respect for my colleagues who practice mainstream medicine, but what I found was that. It fails many of my patients.

So within precision medicine, what we do is we’ve got a patient with depression diagnosed with say moderate depression. We treat them with a drug like Celexa and we know that it’s gonna take treating about 10 patients for one to benefit. Now, that is in precision medicine with NF one experimentation.

Each patient serves as their own control. You’ve got a period of. Control data that you collect, such as with a continuous glucose monitor, and then you have an intervention and you see what happens to the dataset. Typically, that intervention lasts for about six weeks, so that is n of one experiment.

And what’s illustrated here in this slide, you can see that the lower limits of the dotted line are about 70. The upper limits of the dotted line are about sorry, 80 milligrams per deciliter of glucose. The upper limit is 140 milligrams per deciliter, and in this end of one experiment shown in the red, A patient has a very spiky glucose level, so we’re measuring glucose continuously in the interstitial space.

Typically in the arm, depending on which device you’re using, or sometimes the abdominal wall, and you can see the spiciness. What we know with glucose, what we know with metabolic health is that spiciness is not good. You don’t wanna have severe spiciness, which is also known as a severe gluco type. So this patient had quite a bit of spiciness going up to 200 milligrams per deciliter in response to their food, their standard food kind of food in the wild after an intervention.

You can see the continuous glucose data superimposed in blue, and you can see that the spiciness is dramatically reduced. So using the language of Michael Snyder’s lab at Stanford in the red, you can see a severe gluco type in the blue, you can see a mild gluco type. So that’s how we use n f one experimentation.

I use it with all of my patients. We also have research funding, a restricted gift from levels that is allowing us to do not just the systematic review and meta-analysis of early biomarkers of pre-diabetes, but it’s also allowing us to do an exploratory study of deep phenotyping of 12 subjects where we’re looking at data such as C G M data before and after intervention.

Tom Bunn: Cool. Thank you. And related to that I think what I’m gathering from, this is that one of the reasons why NF one experimentation is so useful is because everybody is different. And they have different ways of their, genes are expressing, have different genes for, to begin with.

And I think one of the things here that I know you’re, looking into is, the different ways, the different phenotypes of patients with type two diabetes and what some of the downstream effects and, maladies are based on those different phenotypes. How are you using this, data in your practice and, what do you think the, long term implications are?

Sara Gottfried: This’s just another Standard concept of precision medicine that we don’t take all patients with pre-diabetes and treat them the same. We don’t take all patients with type two diabetes and treat them the same. Instead, what we look for based on this multi omic phenotyping that we perform is different sub phenotypes.

So if you take the phenotype, the gene environment interaction that leads to type two diabetes, we know that there’s probably somewhere around three to six sub phenotypes of type two diabetes. So what you’re looking at on the right is a topographical analysis from the lab of Joel Dudley at Mount Sinai, and he performed an assessment.

Using dense data from the electronic health rec record, put together with genotype data to map out three sub phenotypes of type two diabetes. And on the left you can see these three different phenotypes. He looked at a total of 11,210 hospital outpatients. He found that 2,500 of them were diagnosed with type two diabetes, so he had a pretty robust data set and he found that subtype one.

Was a cluster of particular conditions, including diabetic nephropathy, diabetic retinopathy. The second subtype shown at the bottom of the illustration was cancer, malignancy, mostly lung and bronchus, as well as cardiovascular disease. That’s my particular interest. And then subtype three is cardiovascular diseases together with neurological diseases such as Alzheimer’s disease, as well as allergies.

So all of them have immune components. More of a neurological component in type three. But I think an important note to make here is that when you look at sub phenotypes, they’ve been done for a lot of conditions, such as in this case, type two diabetes, but not so much for the pre-use state. And that’s what I’m particularly interested in because of that homeostasis issue.

So we can intervene, we’ve got a better chance of reversal the earlier in the process that we make an intervention. We also know that when it comes to sub phenotypes that I. Instead of doing medicine for the average, we think that we can customize treatment based on these sub phenotypes. So the concept with precision medicine is that we’ve probably got somewhere around three to six sub phenotypes of pre-diabetes.

Each of them should undergo a different type of N of one experimentation. So that’s where we’re heading with precision medicine as we look at metabolic health, especially with pre-diabetes. I’ll say one last thing regarding pre-diabetes. A lot of folks think I don’t have to worry about this until I get a diagnosis of type two diabetes.

The truth is, pre-diabetes is not just some intermediate risk state. It is associated with its own. Sequela. So it is associated with a greater risk of kidney dysfunction probably along this pre subtype. One, it is associated with more cardiovascular disease, coronary heart disease associated more with probably pre subtype two and three as well as retinopathy and damage elsewhere in the body.

And that is especially true in women. So you mentioned earlier that with metabolic syndrome, Part of the criteria is in men with a waist circumference of 40 or greater. In women, it’s actually 35 inches or greater, not 36. I just wanted to correct that, Tom. Thank you. And with women, we know that the average waist size of women is 37.5 inches.

So I would challenge you not just to know what your fasting glucose number is, but know what your waist circumference is so that you are starting to collect your own data set about your metabolic health.

Tom Bunn: Awesome. Dr. Godfrey, it sounds like you are really at the cutting edge and from, the phenotyping point of view, really the tip of the iceberg and excited to see where this research goes and, how you put it into practice.

So thanks for sharing with us. Hopefully we’ll have some time for some more questions at the end. Sure. But moving on to Dr. Casey means Casey is the co-founder and chief medical Officer of Levels. She was gracious enough to let me try. So I have a Levels CGM on right now and have been loving it and obsessed with the data and had a very active and very low carb weekend to try to game it.

But Casey, can you tell us a little bit about levels and,

Casey Means: why you started it? Absolutely. Hi Tom. Thank you so much for having me here. So, grateful to be here with such wonderful panelists and, audience. Levels is the first consumer biosensor program. It empowers individuals to understand how food and lifestyle decisions are affecting their health in real time.

Levels members use continuous glucose biosensors to learn the immediate impact of specific choices. And in doing so, this is creating the first closed loop feedback system on food, and thereby unlocking the power for us to each make better health decisions that keep our glucose more stable, which as we just heard from Dr.

Gottfried, is foundational for metabolic health and longevity over the long term. It also gives people a much more nuanced view into the current status and the trajectory of their metabolic health long before issues might show up on a standard lab test. Simply put, we’re talking about technology that facilitates behavior change and personalized choices and also highlights the trajectory of health and signals of pre-use.

And I think I. One way to think about it is that the average person eats three pounds of food per day. We eat about a metric ton of food each year, and this metric ton of molecular information directly determines our out, our health outcomes, our gene expression, what our cells are made out of.

And yet we have virtually no idea what that food is doing to our body, what the impact is. It’s all based on food marketing. What we’ve heard is good for us, but we don’t actually know the immediate impact. Additionally, different people respond totally differently to the same foods based on different factors like their microbiome or their baseline metabolic health or how much sleep they’ve had, or how much exercise they’ve done the day before and other factors.

So knowing personal response is really critically critical for us to make the best decisions for ourselves. And historically, this may not have been such a, such an issue for people because we were eating primarily real and Whole foods throughout most of human history. But now in the face of a Western culture, which is by and large based on ultra processed foods and novel food chemicals that we’re eating that hijack our metabolic processes and our fundamental cellular physiology lack of understanding about we’re eating is actually killing us.

So, levels is really here to our mission is to reverse the metabolic disease epidemic by empowering people with personal information so that can make better choices for their long-term health. Awesome.

Tom Bunn: Love it. Can you tell us a little bit about the, data you’ve seen to date and, what you think it means at this point and where it’s

Casey Means: going?

Absolutely. Yeah. So we’ve had about 15,000 people go through our beta program. We’ve acquired about 50 million glucose data points. We’ve had about 200 million total health data points cuz we also track sleep and activity data. And people, our beta members have logged about 1.5 million food logs that are paired with that glucose data.

So this is a absolutely massive data set of the impact of food choices on glucose levels in a non-diabetic population. Of, which we’ve really never had access to this, type of data before in the healthcare consumer space. So what you can see here on this slide is, just a, snapshot of a few sort of logs that people would log and then what people’s average glucose rise is, what the average peak of that decision is and then what their average zone score is.

So that’s the, a proprietary levels metric that kind of gives people a score about the glucose impact. Of a particular meal. And so what this type of data set can do for us is show us really for the first time what on a population level, an individual food product is doing to people’s body.

I think in a few years we’re gonna see, think it’s very outdated to choose foods or eat a diet that you haven’t really vetted through the lens of bio wearable data. Which is essentially choosing foods in the dark again, based on just food marketing and what we’re told is good. And I think what we’re seeing from this type of set is that we’re gonna create con new consumer pressures on the food industry and healthcare industry to, to really improve the health impact of the products they’re offering.

And also usher in an era of radical transparency in what. What food companies have to tell us about, their products. It’s no longer gonna be about convincing consumers of anything because we have our own tools to evaluate the outcomes and, the impact. That’s something I’m really excited to see is how these types of large datasets in large populations impact what the food industry is, offering and how they have to share information.

Additionally, this large dataset can feed back into individual insights for the individual. I think on the next slide we have some information about like breakfast choices. So this is looking at across 15,000 people. What breakfast choices have great glucose scores and what breakfast choices have really poor glucose scores.

And what you can see here is that some of our sort of standard American breakfasts like pancakes, cheerios, bagel, and cream cheese, french toast, these have very large glucose spikes in the 37 to 40 range for the post-meal glucose spike. Getting people up to about one 30 milligram per deciliter in their glucose.

In contrast, frittata magic spoon cereal, chia seed pudding a Fab four smoothie, which is a smoothie. The type of smoothie that’s been popularized by nutritionist Kelly Lavec that has a lot of fat and protein and fiber. These have virtually no glucose response. They’re in the seven to nine milligram per deciliter range.

People are only getting up to a glucose of. 90 to a hundred. So what you can start to see in these large population data of glucose responses is that there are clearly types of foods for breakfast that are not going to probably serve your goals, whatever that is in terms of metabolic health, whether it’s weight loss, longevity, and then there are some that are by and large gonna have a minimal glucose response and keep your glucose more stable.

So that type of data can then feed back towards the individual to help them make better choices based on what’s happening with other people. And. More broadly talking about what Sarah was mentioning about gluco types and different, phenotypes of people within this larger population. As our ability to understand this data grows, we’re gonna start to understand different types of subsets of people within the dataset that kind of match other people’s experiences.

And so the predictive element of that feedback is gonna be really interesting where you can say you, respond to foods a lot like this other set of people, so these are the foods that tend to work well for, you. So, that’s the type of insights an example of some of the insights we’ve seen so far.

Great. Go

Tom Bunn: ahead. So ju just a quick question. If you’re not pre-diabetic or you don’t have diabetes, why is having, that spike after a bowl of Cheerios, which you know they say is good for you on the package, why is that so bad? If you maintain.

Fasting glucose levels and insulin levels that are within normal, or even within optimal?

Casey Means: Yeah. So the, impact of a glucose spike has many, different downstream effects. So the there’s, several that are worth knowing about. So high glucose in the bloodstream, acute hyperglycemia and this sort of up and down trend like we saw in Sarah’s graph, the red part where people were up and down That’s called high glycemic variability. And we know that high glycemic variability is. Predictive of downstream metabolic problems like diabetes, obesity, heart disease. In fact, high-glycemic variability is an independent predictor aside from fastening glucose of downstream metabolic problems. So we want to keep glycemic variability to a minimum every time we spike our glucose.

Even if our body is totally capable of bringing that back down with insulin and bringing that spike down, what we’re doing is we’re increasing the amount of insulin that our body is being exposed to. You have a spike and then your body re releases insulin to help take that glucose out of the bloodstream into the cells.

Over time, the cells seeing so much insulin being secreted because of these glucose spikes. Even if you’re otherwise healthy, the body can form an insulin block. It’s called insulin resistance, where it’s seeing so much insulin that it actually puts a block on it to say that there’s too much glucose coming in the cells.

We need to put a sort of a, pause on this. And so over time these spikes over and over again, even if you’re bringing them down because you’re young and healthy and otherwise doing fine over time, it can lead you down this trajectory of insulin resistance, which ultimately what is, what leads to metabolic disease.

And We really want to keep those spikes to a minimum, to keep our cells really sharp and primed to responding to insulin and not having this dulled insulin block effect. The other thing is, that spikes on their own, especially high spikes, can cause acute inflammation, high spikes in the blood can cause a process called glycation, which is where sugar actually sticks to proteins and other molecules in the body and causes dysfunction.

And it can also cause oxidative stress, which is where you’ve overloaded the body with glucose. And that creates stress in the mitochondria of our cells, which actually blocks our metabolic functioning. So insulin resistance, inflammation, glycation, oxidative stress, these are big words, but all of it really focuses on keeping spikes down, keeps us metabolically in the place we, wanna be.

No one should fear a single spike, like your body knows how to deal with it. It’s these trends over time that we wanna avoid and learning to eat, which you can really do rapidly with tools like continuous glucose monitor, learning to eat to keep our glycemic variability down and our glucose spikes down really reduces the burden of increased glycemic variability over time.

Awesome.

Tom Bunn: Thanks for that. And one of the things I’ve been loving is, not just seeing how food affects it, but also how exercise or, a walk will. And obviously you guys are focused on that intensely. So what, have you learned so far about lifestyle things other than, what you put in your

Casey Means: mouth?

Yeah, your glucose levels are not just a readout of what you put in your mouth, but also of the holistic set of lifestyle factors that you’re engaged in, such as sleep, stress management, exercise really those have a, massive impact on, what our glucose levels are. So we’ve, done several experiments looking at some of the, these lifestyle factors in our levels.

Population one was what we called the Levels Coke Experiment, where we shipped our members. They opted in if they wanted to join a 12 ounce can of Coke and we had them drink a can of Coke. One morning see what their glucose response is, which here you can see it’s the red dots on the graph on the left.

And then the next day they drank a 12 ounce can of Coke and then took a walk, just a gentle walk for about a half an hour after the Coke. And what we saw was that in the group that did not take the walk, just drank the coke alone, their average glucose spike was in the a hundred and sixties milligrams per deciliter.

And after just taking a, gentle 30 minute walk after drinking the Coke, there was an about a 35% reduction in the glucose peak. And the area under the curve the average spike was in the one 30 s with taking a walk. This, has large implications. If you compound this type of information over time having a 30% reduction in your glycemic variability after meal is, a big deal.

Something as simple as taking a walk, there’s a lot of evidence to suggest that it really has a positive impact on reducing glycemic variability. We also done some experiments actually with the whoop team where we had people use whoop and glucose monitors. And what we saw in that is that sleep is the impact of sleep on our, glucose.

What we found is that the whoop recovery score, which incorporates sleep quality different sleep stages, resting heart rate and heart rate variability correlates with the levels metabolic score. The essentially the better the recovery score you have, meaning sleep and and, heart rate variability the better the glucose results are.

So this is real world evidence suggesting that what we know from the research literature Applies to a non-diabetic population. That’s, essentially trying to figure out which lifestyle decisions are gonna have the highest impact for their long-term health. And I think we’re, sometimes overwhelmed with all the different things we can do in wellness and in lifestyle.

And to have the objective data and these integrated data streams like sleep markers of stress, like heart rate variability and glucose to create these higher level insights for you about what is really working for you, what are the highest yield interventions for you, and then when you see those results, motivates you to keep them going.

I think really is, a big step up in the wellness industry. Awesome.

Tom Bunn: Thanks for sharing Exciting times for, you in levels and excited to see where it goes. Thank you. So next we have Dr. Mark cela. Mark you’re a family physician, family medicine physician in, West Virginia.

Tell us a little bit about how it is practicing family health and focusing on diabetes and, one of the most obese states in the country and, what you think we can really do to, make a dent there and, other, and everywhere else.

Mark Cucuzzell: Oh, thank you Tom. And certainly great to follow Casey and Sarah.

And my message parallels theirs in a little different population I work right now I’m standing in a, rural health hospital. It’s called a Critical Access Hospital, 24 Bed Hospital. These hospitals are throughout the country and mostly underserved rural areas, and most of my patients don’t have a lot of medical sophistication, access to technology.

But the, message is actually very easy to communicate. And even giving them simple tools as much as a simple glucometer to start with, as well as the CGMs helps them really learn their disease and take ownership of, their disease. So we see people from, I’m a family doc, so we have a, pilot study that we just submitted for I R b for obesity in children, because that’s the full catastrophe right now is childhood obesity because these children will become obese and metabolically sick adults, they’re already metabolically sick children.

So, we, I wish we focused on that, not necessarily their bmi. But if we can capture them at the childhood level work with the schools, work with the government really in policy affecting what kids get at, their school lunches, maybe we can make some impact together. But seeing the data is profound.

You can’t unsee what you see when you look at data on biomarkers such as glucose or ketones if you’re doing a low carbohydrate diet and trying to follow your results there.

Tom Bunn: Cool. You mentioned that study on pediatric diabetes, and I know you’ve connected with Jim Howard, who is the c e O of I select portfolio Company Readout Health, doing keto monitoring.

Curious to get your, take on, the Promise of Keto monitoring in conjunction with prep, perhaps other biomarkers to address this issue and how you think that will roll out in this in this pediatric diabetes study. You’re, undertaking.

Mark Cucuzzell: Just a, quick correction. It’s a pediatric obesity study, but probably these children are all pre-diabetic, meaning they all have fatty liver.

And if we actually could measure their insulin real time, that would probably be the holy grail because then we could see which kids are hyperinsulinemic in the first grade which precedes the diabetes because kids will start pumping out more and more insulin to fill their liver with fat.

And develop all the other even they start to develop cardiovascular complications even before leaving high school. But so the, question stands, what can we give patients and their families that are simple tools that might help them adhere and learn a little better and maybe tweak the way they’re eating?

So children usually don’t like to be stuck unless they are type one. Maybe they’re been used to that because they started really young and, to them it’s routine, but so children really don’t want to get stuck. So a breath keone meter, maybe it, it will have a marker of which chil like we, we see which kids respond and which don’t.

In our can, we use technology to identify. A group that might need more counseling, really, it’s going to more support where are they getting their carbohydrates if we’re seeing there’s a trend in the kids that are blowing a little higher keone level versus the ones that aren’t is there a difference in the group?

With, weight loss and really waste waste loss is what we really want. Same as a glucose monitor the, and children. The diabetes is like the last domino to fall. They’re, gonna have multiple other metabolic comorbidities before they’re diabetic so, they’ll pump out a lot of insulin before their sugars rise.

But like Casey’s graphs are showing, are we gonna see and Sarah mentioned the spiky pattern. Are we gonna start to see a lot of spiky pattern? And as well as these hypoglycemia episodes? Reactive hypoglycemia is really driving kids are hungry and if they’re hungry, they’re gonna eat.

Why are they so hungry all the time? Unless we can answer that question. We can’t put kids on diets. We and, our whole premise with low carbohydrate in children and it’s in the Obesity Medicine Association algorithm as the most effective way to treat pediatric obesity. But I think there’s a bias.

It’s hard so I, I don’t think we should be offering this cuz it’s hard I, live in not only the most obese state, but we probably have the highest tobacco prevalence in the country too. Would we ever tell a patient or just assume? I, don’t think they can quit. It’s hard and we’re seeing patients with end stage emphysema a lot of those patients are very susceptible to covid now we have a whole floor full of covid patients right below me right now.

So of course we’re gonna give them opportunity and support to, to make the, right choice so this is the optimum choice is to do this and we’re gonna support you.

Tom Bunn: Awesome. Thank you very much. And I know you’re working on or you perhaps just finished a, another clinical trial looking at in this case diabetics, sorry for the confusion earlier.

Yeah. This was recently diagnosed diabetics would love to hear about the about the, this trial. Yeah. This

Mark Cucuzzell: little trial we did was a pilot, basically it’s a small study of Casey’s big database. A very low low support intervention. We just gave patients who are new diabetes patients.

Freestyle Libra CGM gave them a guide on food and gave them like a log. So basically it was let them teach themselves what affected their blood glucose. So we called it glucose excursion model. And it became pretty evident in day one or two, what foods would raise their blood sugar. But the exercise component was interesting too.

Some patients had a very brisk reduction in glucose with exercise, some not so much. So they tuned and learned themselves. And we did this over four months, new diabetes patients. And our goal was to reverse the diabetes without medications. So if you go with just standard treatment for diabetes, no one reverses their diabetes.

They all manage it. But the goal is to make it go away and, that’s not possible with all patients, but I think it should be offered to. Anyone who wishes to give that a go. And the American Diabetes Association, Tom, has actually just acknowledged that diabetes remission is not magical thinking because they made a consensus report defining it because the definition was all over the place.

So what is it? Can you be on metformin? Can you be on a GLP one agonist? But no. The, so the, and this has also followed the UK and Australia. So diabetes remission is A1C less than 6.5, no medication maintaining for three months. So we did a four month trial. These were new diabetes patients, no meds, gave them the Libra.

My patients weren’t even sophisticated enough to figure out how to upload the data onto their computer. So I, would grab their reader and download it from my clinic. They didn’t have daily support from coaches or anything. They just learned on their own. And they saw us back in four months.

And it was I had a group of five. We had five at U V A and five patients at University of Colorado. And they, fit an age range of, most of ’em were in their forties, fifties, sixties mixed African American, Caucasian, mixed female and male. And two thirds of the patients reached diabetes remission which is pretty good, right?

Compared to zero. And the average A1C reduction was two. Without medication held over four months and there was really robust responders and then there were folks that improved, but not dramatically. And I could share a little of my thought on that. If, we have time, just it’s what I see clinically and, the small pilot just validated who are the responders and who struggled a bit and, that’s just the real world.

Sure.

Tom Bunn: Super fascinating. We, touched on the, use of ketones monitoring for this childhood obesity study. And interested, to dive a little bit deeper into how you said some folks are struggling and one of the things you sent me in, the presentation you shared was just how many screenshots of your communication with.

With your patients and, those you work with. And it was super impressive. Obviously these, patients think they’re older than you. I, say it’s a good tech side manner. I’ve never heard

Mark Cucuzzell: that term, but yeah, I don’t have a, technology platform I’m in a small, these are Medicaid patients, a lot of them Medicare I’m just, it’s me and my text, and you have to give people support if they’re gonna reduce medications.

You can’t have help these folks. You gotta, either you help ’em or you don’t. And I commit to people, Tom, if they’re willing to do this, I commit to them a hundred percent. I will help guide them through it. They text me what their sugars are every day if they’re on medications, we’re gonna land the plane slowly reduce their medications, maybe even add a medication from a different category if we can help them achieve stable sugar.

But they do. And these are really quick inter that you can see quick. Three seconds, look at their screen, looks good, stay the course. And when they see that support, they know you care. And, it goes way back to the original medicine textbooks. The, most important thing about caring for patients, it’s caring for patients.

They see you care. And that’s something that’s really not common now in healthcare. That care and empathy we’re commodities in a lot of places. We’re just working for VU components, seeing as many patients as we can, and that’s what burns us out. But this brings me joy.

I have patients this afternoon who are coming off meds, who’ve been sharing their screen, and it’s gonna be wonderful to see ’em really, and even give ’em a hug with our masks because there are people doing things that they thought couldn’t be done. And like you give them hope that they can do it.

That’s fantastic.

Tom Bunn: Dr. Mark, thank you for for sharing your work here.

Mark Cucuzzell: Thanks for the opportunity, but just real quick on the responders and non-responders, you asked about that. So when you talk to people about this it’s, almost like tobacco sens cessation. There’s a group that get it, they’re all in, they do it.

Their life has changed in a week. And then there are people who struggle with processed food processed food addiction. Dr. Robert Lustig has written a ton about this. I think he’s on in the chat. But those people struggle and they need more support because they’ll try and they’ll get off the wagon, try to get back on the wagon, just like people trying to quit smoking.

And, then there’s a group that I’ll see that just aren’t ready yet. They’re going through a life struggle, a stress financial crisis. We’re an opioid capital kid just got released from jail and they’re not ready to start a lifestyle change. So that group in the middle that’s struggling really wants to do it and struggling.

That’s how I think technology can really help, because they need that daily kind of reminder from their arm that’s gonna bark at ’em a little bit. But then there’s that one group that just jumps on board and does it, and they’re free and they’re healed and they don’t need us anymore.

And that’s a wonderful place. They’re, healthy people again. Fantastic.

Tom Bunn: I think one of the questions we had from the audience is related to, that on new technology and nudges. This could go for the whole. Group, but curious to hear your thoughts on most promising biomarkers and biosensors coming down the pike.

If, you guys could have one biomarker that isn’t able to be continuously measured now, what would it be? And, what do you think the, what do you think the most likely one is coming next?

Mark Cucuzzell: I could throw some I mentioned the insulin. I think if we could have a continuous measure of insulin to catch the pre, pre-diabetic might be something. But I think most of us see that with the glucose so the glucose legs a little bit, but we see it.

Casey Means: I would I would definitely second that.

I think insulin would be profound for the early pre-disease, as that’s one of the first things that we see rising even before glucose. I think that there’s, definitely a lot of groups working on that. I think it’s going to be challenging. Our current biosensor technology is based on enzymatic technology essentially a chemical reaction between the sensor filament and the glucose.

And with insulin, which is a much larger protein it makes it a bit more technically challenging. However, there’s new technology coming down the pipeline, like aptima based sensing that may be able to accommodate these larger proteins in a real time way. And so I think that’s, an area to watch.

And we’re seeing a lot of really interesting work in lab testing of this type of technology, but not in vivo clinical continuous monitoring. For me personally, I’d also just add on Inflammatory cytokines would be really interesting. Cortisol certainly to understand stress response in real time and actually also uric acid is one that I’m quite interested in.

Uric acid is downstream of fructose metabolism and really highlights how while glucose is an amazing way of getting biofeedback on diet it glucose is not the end all be all in determining what the perfect diet is for you. It’s just the tip of the iceberg. It tells us a lot. But if you just optimize for glucose, you’re not necessarily gonna have a perfect diet cuz of course you could chug canola oil or vodka and still have a fly glucose line.

And so having other nutritional biomarkers that can help disambiguate how a food is affecting your body, whether that’s inflammatory or something like uric acid, which is downstream of fructose we can start to have a more holistic picture and be able to say very concretely, this food. Is great for my body or this food isn’t.

So glucose gets us a huge amount of the way there, but I think other nutritional downstream biomarkers like ketones, uric acid free fatty acids would be great as well. Yeah, I’ll just add on

Sara Gottfried: I agree with what’s been mentioned already and the challenges that we have with some of these larger molecules for continuous measurement.

One of the things I’m excited about is as physicians having better dashboards to be looking at some of these dense data sets and I think levels has taken us pretty far in terms of algorithms and dashboards. In terms of your question, Tom, I’m also very interested in some of the hormones that are part of this signal that changes with glucose.

And as Casey mentioned, we know from pretty robust data sets like the white hall study that. When you look at a change in glucose upstream, there’s this change that happens hormonally sometimes for years before that change in glucose. So that’s certainly true with insulin, it’s true with adiponectin. So these are some of the hormones that I like to look at.

And then some of these confounders such as cortisol and stress I think are very interesting and certainly uric acid, as Casey mentioned.

Tom Bunn: Fantastic. We have just a couple minutes left. If there are any questions, feel free to type ’em in. But curious in the few minutes remaining from each of you, what is the single most important thing somebody can do perhaps today to, take a, small step towards, metabolic fitness and metabolic health?

What’s, the number one thing you’d recommend?

Sara Gottfried: I would say for easy. Sorry, mark. For easy, I would say intermittent fasting. 98% of my patients can do it. Start with an eating window of 14 hours overnight. Less easy is keto a ketogenic diet, a well formulated ketogenic diet, but easy is definitely intermittent fasting.

Sorry, mark.

Mark Cucuzzell: Oh no, Ladies first. Here I actually drew this thing. It’s a little white paper, optimum health and disease. So I think the most important thing you can figure out for yourself is where are you on that scale and self quantify if you’re not in optimal health, that’s why seeing someone like Sarah, if you were a, patient, she would take probably two hours with you and help you figure out what your issues are.

Most people I see have no idea that they’re even pre-diabetic so they, don’t even know what they have, so they can’t even begin to help themselves. Talked to a clinician that actually understands prevention and metabolic health. What’s your scorecard? And not just the five markers, right?

That’s disease, we wanna catch it early. So just figure out where you are and what your levers are to get better in your life. It’s gotta fit within in your life. Most of us are busy and budgets we, have to deal with, the financials of affordable food. Absolutely.

Thank

Tom Bunn: you.

Casey Means: I would echo both of those wholeheartedly. And building off of what Dr. Mark said almost everyone has a cholesterol panel. A lot of us don’t have a fasting insulin test, which ideally all doctors would order, but we all have a cholesterol panel. So even just looking at something like our, just calculating from our last cholesterol test our triglyceride to H D L ratio, which can be a signal Directionally of whether we are insulin resistant and look to see what that is.

Ideally less than one, a ratio would be great. But as you’re creeping up two to one, three to one, four to one, you start recognizing that there may be something happening with insulin resistance. So that’s a really simple way for you yourself today to take a look. There’s actually a blog post that we put together that includes a lot of Dr.

Gottfried’s input called the Ultimate gl the Ultimate Guide to Understanding Your cholesterol test. So that’s on the Levels blog, and it’s just can walk you through exactly how to look at your cholesterol panel and understand your level of metabolic health from it in a more nuanced way than what you might get from your doctor.

So that’s one thing. And then I think for a practical tip, I would just say the biggest thing we can do is eliminate excess refined carbohydrates and, sugars and eat more whole real colorful food.

Tom Bunn: Awesome. Thank you all. Please join me in a big virtual round of applause for Dr.

Godfried means Cella. Thanks so much for, joining us today. Go check them out. They’re, prolific on social media. Go read their books. They’re digital or for purchase. Really cool stuff. And again, thank you all for for, joining us this morning. It’s been great.

And to those in attendance, thank you for for participating. As a reminder, we host these. Deep dives once a month. We alternate between topics in food and health and agriculture. Next month my colleague David Yoakum will be presenting on the future of cheese be it from a animal or otherwise.

So hope to see you soon and hope everyone has a great day and, happy holidays. Thank you all.