New Research Pinpoints Midlife Brain Decline & How to Slow It

Lily: 
I think the message of this potential insulin resistance in the brain is that just like insulin resistance in the rest of the body. It may be entirely preventable through diet.

Bret: 
Welcome to the Metabolic Mind Podcast. I’m your host, Dr. Bret Scher. Metabolic Mind is a nonprofit initiative of Baszucki Group where we’re providing information about the intersection of metabolic health and mental health and metabolic therapies such as nutritional ketosis as therapies for mental illness.

Thank you for joining us. Although our podcast is for informational purposes only and we aren’t giving medical advice, we hope you will learn from our content and it will help facilitate discussions with your healthcare providers to see if you could benefit from exploring the connection between metabolic and mental health, dementia, alzheimer’s disease, cognitive decline. 

These are words that strike fear into many people who would do anything to try and prevent that outcome as they age. But now, new research by Dr. Lily Mujica Parodi and her research team suggests that there’s a critical age window where we can do something about it and that something might surround and involve metabolic health and ketones. So I’m joined by Dr. Kirk Nylen and Dr. Lily Mujica Parodi to discuss this fascinating research and what it might mean for preventing or possibly even in the future treating dementia.

All right, Dr. Mujica Parodi, thank you so much for joining me on Metabolic Mind. 

Lily: 
Thanks so much for inviting me. it’s such a pleasure to be here. 

Bret: 
And I’m also really pleased to have Dr. Kirk Nylen, our Managing Director of Neuroscience at Baszucki Group, joining as well because this is going to require another level.

This is such an interesting study that I had to bring in the heavy hitter scientist with Kirk here to help me get through this. So thanks for joining us as well, Kirk. 

Kirk: 
Thanks for having me, Bret. Good to be here. 

Bret: 
Yeah, so this, we’re able to do a lot of things that we can talk about here, but one of the things to certainly focus on is this paper, which I guess if I was going to try to summarize it or what I’ve seen written is the non-linear brain imaging, which shows a critical window for metabolic intervention.

It talks about brain networks and the role of ketones and stabilizing networks. But such a sort of like a hit home practical implication that there’s maybe like this age window where we really need to focus on brain health to prevent cognitive decline. But before we get into all that, because I’m sure there’s going to be just a lot we can discuss, tell us about you. Bring us up to date on who you are, what you’re working on so we are on the same page here. 

Lily: 
So my name’s, Lillian Mujica Parodi. I go by Lily. I’m in the Department of Biomedical Engineering at Stony Brook University. I’m a Baszucki Endowed Chair of Metabolic Neuroscience.

And just a little bit about the approach that we take. I’ve always been fascinated by control circuits and that way that we conceive of very basic, fundamental questions about what is health? What is disease? What does it look like to have a transition between states of health and states of disease and, vice versa?

And so I think that approach very much has informed how we went about thinking about this study and interpreting the results. 

Bret: 
Yeah, I really like that approach. So Kirk, I brought you on for the science mind. Why don’t you kick us off and start asking some questions about this study so we can dig into it?

Kirk: 
Sure, happy to. Maybe firstly, you mentioned control circuits, can you just tell us what you mean by that? Is this the idea that the brain has a lot of things going on, and if there aren’t proper controls in place that you can get runaway activity or what do you mean by control circuits?

Lily: 
It’s actually a really much more fundamental concept. So, control theory and control circuits are really well understood within fields like electrical engineering, robotics. Anytime you have a system where you want to maintain control of that system in the face of chaotic input. If you have a self-driving vehicle, for example autopilot, as you start to veer in one direction, if the road is in the opposite direction, you have to correct for it.

And if you start to veer off in the other direction, it’ll correct for it in the opposite direction. So the fact is that when you design a system, you’re often embedding control circuits in order to maintain a particular trajectory. But physiologically, evolution has accomplished the same thing.

And the way physiology is set up is that it’s designed to maintain homeostasis within the face of chaotic inputs. And so what I mean by that is that all of the typical measures within physiology that we typically think of as being associated with health, whether it’s our nitrogen levels or oxygen levels or glucose levels, anything that you can think of really needs to be maintained within some optimal range where if it’s too low, it’s a problem. If it’s too high, it’s a problem. And so there are all these mechanisms within physiology that acted as a kind of a autopilot in maintaining the body within a set trajectory.

And so what happens in a state of what we call disease is that those mechanisms start to degrade, which means that we get off trajectory. And one of the interesting features about disease states is that getting off trajectory, getting out of balance actually puts additional stress on the system.

And because it puts additional stress on the system, it often pushes it even further out of whack. So you have a system that gets out of balance, and the fact that it’s out of balance actually makes it more out of balance. And that’s how we get into disease states that then become intractable. 

But by the same token, if you can catch that dysregulation, or that getting out of balance off your trajectory very early on, it’s actually much easier to correct. And taking that perspective, I’ve been very interested in looking at pre-disease states, what’s known as prodromal disease states. What happens to the body before we become diagnosed with being ill, and can we actually correct those states before they become symptomatic? 

Now in the case of the brain, it’s just one of, it’s just one case of what is generally true within physiology. And because I’ve always thought of the brain as just one more physiological system that is part of physiology, but also interacting with physiology, the rest of physiology in various ways, it felt very natural to think about how different physiological states, like hypometabolism or hypermetabolism, could actually interact with brain function. 

Kirk: 
That’s really great context, I think, for the study that we’re going to talk about today. Can you start off just by walking us through what you were, what the reason for doing this study was and, how you carried it out?

Lily: 
We know that the hallmark of frank dementia. So by the time you walk into a neurologist’s office and you say, I’m starting to have memory loss issues, i’m having to have some impairment on functioning. At that point, the gold standard is to do a scan known as FDG-PET (positron emission tomography).

And what that scan does is it looks at glucose uptake within the brain because the hallmark feature of dementia is actually glucose hypometabolism. And so one of the things that I was very intrigued by is that if you look at individuals who have mild cognitive impairment, as opposed to just frank dementia, you see that same hypometabolism but just less. And that made me wonder whether, in fact, hypometabolism wasn’t something that you just woke up with someday but actually was a long degenerative process that started far before you actually started seeing those signs and symptoms that got you into neurologist’s office? At that point, I started thinking about how do we probe the system, and how do we also potentially think about its mechanisms and then how do we potentially compensate for it?

And there are many potential pathways that could lead to hypometabolism. It wasn’t even obvious, and this is one of the dominant themes within this paper, it wasn’t even obvious that hypometabolism was the driving cause. It could have been that hypometabolism was the effect of something else. One of the difficulties in testing people who are already aged is that so many different problems have occurred by that stage.

That when you look at the brain. They have vascular issues. There’s often changes in the immune function with inflammation. There is that hypometabolism, and so figuring out the cause and the effect becomes very hard. So for that reason, we started with a particular hypothesis which had to do with the question of whether insulin resistance of neurons could be actually the driving mechanism.

And if that was the case, that suggested a particular way that we might be able to reverse the effects because the insulin resistance, true to its name, is actually insulin dependent. And so it’s dependent on a particular way of getting glucose into the cell, into neurons, which, is GLUT4 transporter–dependent. So it’s a transporter that’s very specific to insulin in the brain.

There are also transporters that are not insulin dependent in the brain. But if it was insulin dependent, then we knew that there was actually a backdoor for refeeding those neurons, which was ketones. Because neurons, like other cells, are actually capable of utilizing two fuel sources.

They can utilize glucose; they can utilize ketones from fatty acids. And so if in fact those neurons were insulin resistant, then the ketones should reverse the effects. And if there were a different mechanism, then ketones might not have any impact at all. So we felt that it was not just something that was useful in terms of figuring out whether there might be some clinical role to play therapeutically with ketosis, but we also felt that if it worked, it was actually going to give us some really critical piece of information about the potential pathways by which this hypometabolism was occurring. 

Bret: 
Yeah, that’s a really great explanation of the hypothesis that you were testing and what you’re looking at.

So how do you measure an insulin resistant neuron? 

Lily: 
That’s a great question because unlike glucose or ketones, which are relatively straightforward to measure in the brain using techniques like magnetic resonance spectroscopy, insulin really can’t be measured directly. So we have to be clever about inferring the behavior of insulin, as opposed to other potential sources of glucose uptake. And the way we did this in this paper is we looked at gene expression because, so GLUT4 is the mechanism for insulin regulating uptake of glucose in the brain, but there are other glucose transporters as well, GLUT1 and GLUT3.

And these are not homogeneously distributed throughout the brain. So there are only specific parts of your brain that are utilizing insulin and others that are not. And that gives us actually a really important clue. Because if we look at which parts of the brain are aging fastest versus lowest, if we coregister geographically the areas of the brain that are aging fastest then compare those to the parts of the brain that use one glucose transporter versus another glucose transporter, it starts to give us some clues as to what the mechanism is underlying that hypermetabolism. And one of the very important results we found is that GLUT4 dependent regions, but not GLUT1 and not GLUT3 dependent regions were the ones that were aging fastest.

That then isolates the mechanism most probably to insulin mediated effects and specifically insulin resistance. This is also really important because one of the genes that confers the greatest risk for Alzheimer’s disease and dementia is APOE4, right?

And APOE was another gene expression. that was very strongly associated with brain aging, but APOE does many different things. And so the question is what role is it playing here? It turns out that one of its very important roles is that it’s associated with insulin signaling. And so we think that actually these genes are playing complementary roles that are specific to insulin as a mechanism.

Kirk: 
Lily, one of the really interesting things, I think one of the reasons this paper is getting so much attention, is it highlights that there’s these kind of two these, this biostable brain where you have a certain level of stability leading up into your late forties. And then things begin to destabilize to some extent, peaking, I think, in the sixties or so. And then reaches a new level of stability, which I, the way I interpreted the paper anyway is that it’s a lower level of functioning stability or not as optimal the state.

Can you just talk a little bit about how you discover those two brain states and the interventions that you examined in seeing whether or not you could actually either reverse or improve, going from the one level of brain stability in an earlier age, the lower level of brain stability in older age? 

Lily: 
So we can think of it as an inverted u.

So many different phenomenon in biology and physiology follow that inverted u. Again, because too much of something is a problem; too little of something is a problem. But there are many cases where you could be at the same point but for very different reasons. And we think that’s what’s happening here.

So in the 20 to 40 age range, it could be that there’s already the beginning of this process that’s starting. It’s at a very low level. It’s this kind of encroaching hypometabolism due to insulin resistance. But the brain is still able to compensate and so it’s able to maintain homeostasis and that gets manifested, we think, through the stability of brain networks where stability we’ve shown from other more mechanistic experiments looking at neurons and neuron signaling.

It seems to be the ability of different brain regions to maintain their signaling over longer periods of time, which is metabolically expensive and maybe something that starts to fall apart as the brain has more metabolic stress or greater metabolic demand.

And so what we find is that once we start that 40 to 60 age range, that process of destabilization is starting in the mid forties more or less, and the destabilization, the way I interpret it, is that it’s the brain trying to maintain homeostasis, but gradually unsuccessfully.

And the reason why I interpret it that way is that this is a trajectory that, again, is very common within other physiological systems. So if you get outside the brain and you look at insulin resistant within other cells, that insulin resistance again, is not something that starts all at once.

It’s a gradual process where a genetic predisposition or high glycemic index diet puts a lot of stress on the system. It tries to maintain homeostasis as long as it can, and then it gradually starts creeping into a state of dysregulation. And we think that gradual state of dysregulation is what is starting really in the early forties, and then accelerating, up until about 60, and then eventually plateaus at a state of instability.

And so it’s not that it’s a bistable state at 60 where you go from stability to stability, it’s actually destabilizing and it reaches its plateau in terms of that destabilization. So instead of it getting worse and worse and worse and worse, you hit a plateau where it’s as bad as it’s going to get and then it stays there.

But what eventually happens at the end of that, at that trajectory, which is not something that we showed in this particular paper, but we’ve seen in other large scale trajectories, is that eventually it comes plummeting down. And that stability is not due to the stabilization of signaling, it’s actually due to cell death.

So what’s happening is this state of neuronal atrophy, which occurs when the neurons have been starved of fuel long enough that they cease to be able to function. And so what we’re getting to is a point where we really want to make sure that the neurons don’t get to the point where they atrophy and die.

At which point, game over. It’s really not possible to do anything at that point. But even before then, you can get to a point of metabolic stress where what we think is happening is that initial metabolic stress is triggering a cascade of other effects. And that cascade is turning that dysregulation into more than just a sum of its parts.

So it’s causing stress on the system in the way that I started off describing, that then further disregulates the system by affecting other systems as well, like the vascular system, the immune system. And then that cascade gets worse and worse to the point where the therapeutics that we’re working in middle age are no longer effective.

And so what we think is happening is that there is actually this critical window where you can still knock the system back onto its original trajectory. And so that is, I think, the hopeful message from the paper. 

Kirk: 
Yeah. What some people might look at this study and think, of course we get older and things become less efficient and they start to break down.

We see that with our muscles. We see that with different parts of our body. But you were able to show that, in fact, you could mitigate, or at least attenuate, this instability through the use of both the ketogenic diet and exogenous ketones. Can you speak a little bit about the interventions that you used and the findings that you’re able to detect and relate that back maybe to this idea of maybe this isn’t just normal aging and the way things should go, but there’s actually something we can do?

Lily: 
Normal aging is very environment dependent. So within an evolutionary context, our physiology evolved within an environment that would’ve been, had a far less high glycemic load than the one that we currently have. We would’ve also been moving much more, which would’ve also compensated for glycemic load when it did occur.

And so we’re in a situation which again, is very common to many different areas of physiology where when you push the system past its normal bounds in the beginning, it can compensate. But when you do it over and over again as a chronic kind of stressor, eventually the system starts to break down.

That’s true for every sort of physiological system. We think it’s definitely true for metabolism, in general, but also specifically in the context of the brain. So if you think about it, there are many examples where what we think is a brain disease is really a physiological disease. The way I think about dementia is type 2 diabetes in the brain.

Vascular dementia is heart disease in the brain. In both of those cases, what you’re seeing in it is an interaction between personal genetics. There are some people who can tolerate more of that stress than others. There’s some people who just have more vulnerability to it than others. But on top of it, it’s a two part process because on top of that vulnerability, you also need to stress the system.

And so the first part of, I think, the message of this potential insulin resistance in the brain is that just like insulin resistance in the rest of the body, it may be entirely preventable through diet. By reducing the glycemic load in such a way that you’re not stressing your metabolism for such a long period of time, and therefore retarding that degradation that will occur over time.

And then on top of it, what we’re seeing is that even once that process has started, we’re able to reverse it by correcting course and providing an alternative fuel. So I see those as being inextricably linked. Prevent the process from starting at the beginning and once you diagnose this process as early as possible, correct course and compensate for the problem that already exists so that it doesn’t become worse.

Bret: 
So what are some of the results that you’ve been able to see by providing ketones to the brain? 

Lily: 
We initially started, not by providing ketones directly, but actually by changing diet. So when we first started doing this research, we started actually putting people on ketogenic diet and comparing it to a high glycemic index diet, which was actually their normal diets, and then comparing that to a fasted state. And that was actually the context in which we first noticed this feature of network instability. So you have to consider that all of these large scale data sets were taken with individuals who were following their own regular diets. So that was what we wanted to consider as the baseline, and then asked whether a ketosis could actually show an effect.

And actually we were very surprised that we were able to stabilize networks even in young people, even in that 20 to 40 age range, after just one week of putting people on a ketogenic diet. So that was very encouraging, but at the same time, it was from a scientific standpoint, a little hard to interpret.

And the reason why is that when you put someone on a diet, you’re changing many different factors. And so I think this has really been a bugaboo of the nutritional research within human clinical settings is that when you put a someone on a diet, you’re often changing the macronutrient profile.

The ratios you’re changing often the caloric value, the satiety, all sorts of different variables. And so we wanted specifically to be able to control for those factors and really isolate the effects to the fuel source. And so in order to do that, we used ketone ester, ketone monoester.

And that by doing that, we were able to control specifically for weight dosing. We used 395 milligrams per kilogram, and then for the ketones, and then we’re able to calorically match the ketone ester to the glucose. We then replicated this study that originally had been done by putting people on a ketogenic diet with the glucose and ketone bolus.

Having them normalize their results for their, for fasting so they fasted a baseline and then on one day they received glucose, and the other day they received ketones again completely controlled for in terms of their weight, dosing and caloric value. And what we found is that we were able to replicate the effects that we saw in diet using just glucose and ketones.

That was really critical because it showed that the effects were really specific to ketones. And when I say specific to ketones, that also means not just reducing the glycemic load because one of the things that happens when you put someone on a ketogenic diet is by definition you’re also reducing the amount of glucose that they’re taking in.

But because we were using these kind of artificial ways of inducing a glycemic load and and ketosis, we were also able to do other sorts of experiments that would not be possible with diet. For example, we gave people glucose and ketones and said, okay, if we give you both, which one does the brain prefer?

Under what circumstances does the brain still then stabilize? And it turns out that if you give people both glucose and ketones at the same time, it still stabilizes. So that shows that it’s really specifically the ketones that are having the beneficial effect. 

Kirk: 
That’s really interesting. So you had two groups and you controlled for, I guess, the caloric input, whether it was glucose or beta hydroxybutyrate.

Lily: 
Actually one group. 

Kirk: It was one group that got either or they got both? 

Lily: 
It was a within subject study, which is absolutely critical. So people are very different from one another, genetically in terms of their baseline diets and so forth. And so it was very important that the same people were being tested under both conditions. 

Kirk: 
Right?

So, in one of the instances, they got glucose. In the other instance, they got beta hydroxybutyrate. Those were controlled for dose. And you saw that the brain networks stabilized in the, when the ketones were present versus when it was just glucose. Is that right? 

Lily: 
Actually, destabilized in response to glucose.

Stabilized in response to ketones. 

Kirk: 
I’m just curious to get your thoughts on this. Endogenous ketones, in other words, ketones or bodies make as a result of being on a ketogenic diet or a low carb diet versus exogenous ketones, you’re taking these as supplements. Did you see any difference between those two groups or between those two interventions?

Lily: 
The effects were stronger with the diet than with the exogenous ketones. And I believe one likely reason for that is that when you’re in endogenous ketosis, you know you’re in that state all the time, right? And so those were people who have been in ketosis for a week. And so they may have had a stronger effect simply because it was a more systemic effect than giving someone the ketones just at one moment and then testing them 30 minutes later. Although we know they remained in ketosis for several hours and we also were able to measure their blood glucose and ketone levels, and we know that they were comparable to those in the diet. We still saw better effects with the diet. 

Bret: 
Yeah, and that’s a super interesting point because with the diet, you can say you’re improving metabolic health systemically and providing ketones for the brain, whereas if you’re just giving ketones or ketones and glucose, you’re not really impacting the metabolic health systemically as much but still providing that fuel for the brain.

So interesting that you see benefits in both, but maybe a little bit better benefits when you have the systemic metabolic health improvements, or I should say with the ketogenic diet as well. Yeah, I think that’s a really interesting point. 

Lily: 
I think one of the most important factors long term in terms of seeing those benefits would be during sleep.

So we know that sleep has a really critical role to play in terms of protecting the brain from aging in terms of clearance of metabolic byproducts like these beta-amyloid plaque and tau proteins that are associated with states of dementia. All of that is happening during sleep. And it’s really important actually that your glycemic load not be high during sleep so that process can occur.

It actually occurs through something known as insulin degrading enzymes. And insulin degrading enzymes actually can’t do their job in clearing the brain if insulin levels are heightened. And so In terms of giving the exogenous ketones, again, that wasn’t the motivation. The motivation was to isolate the variable in as precise a way as possible so we could understand exactly what the mechanism was.

But in terms of therapeutics, you would really want to be in that state a lot of the time, not just every now and then, and specifically you’d want to be in that state during sleep. 

Kirk: 
This is maybe a premature question, but I’m curious nonetheless.

So, obviously, we’re in the early stages of understanding this phenomenon, and I think this paper has really raised a lot of attention that this may not just be natural aging. Maybe, it’s not normal for 60-year-old brains to destabilize like they are and that there might be something we can do about it.

What do you see as next steps to, I guess first of all, what do you see as the end goal here in the real world? How does the science play out? And why might it be useful? And then what are the steps that you envision between where we are now and getting there? 

Lily: 
So we started with a general measure like brain, looking at brain networks and stability because it was agnostic to any particular circuit, any particular network. It was a good way of thinking, how does the brain overall react to this state of metabolism? But ultimately when we think about what dementia means, we often think of dementia in the context of memory loss, disorders of cognition.

And so one of the very important next steps for us is to take these results and extend them specifically towards understanding how it affects the brain circuits that are specific to learning and memory. And so one of the directions that our lab has really invested in heavily is developing, tools for multi-scale computational modeling that take us all the way from our results that we’ve seen at the single neuron and neuron signaling levels, the scales that are associated with how the neurons are actually communicating with one another.

All the way up to the fMRI scale and EEG scales where we’ve seen this network destabilization. And that’s all the way to cognition and being able to link this mechanistically so we can ask, all right, if we’re seeing this change at the very bottom scale, how is this affecting the regulation of these circuits that are actually associated with cognition?

How does it affect cognition? Why does it affect some cognitive functions earlier than others? And then how does this actually scale therapeutically in terms of being able to prevent the eventual onset of those cognitive signs and symptoms? Although this study was done presymptomatically for very deliberate reasons.

The second direction is we’d want to make sure that, in fact, what we think is potentially a preventative measure actually does work preventatively. And so that leads you to do longitudinal studies where you change people’s behavior during this critical window and you ask whether longer term does this actually prevent the onset of these cognitive symptoms later on in life.

And then the third area that I think really deserves attention is getting back to the question of how metabolism and metabolic disorders are treated within the pharmaceutical world. Typically, these are tested only by really considering the impact on blood glucose levels and really not testing their impact on the brain.

And we know that not all standard therapeutics that are designed for regulating blood glucose actually even fully pass the blood brain barrier. And so as we start to think about treating metabolism holistically and asking, can we also prevent these downstream effects in the brain? We also have to optimize our therapeutics to consider those questions even at the drug development stage.

Bret: 
Yeah, that’s, I think that last point is so important that what are we measuring as the surrogate for the effect that we’re wanting to have? And blood sugar tends to not be the best and I harp all the time. 

Lily: 
It all comes down to what does success look like at the drug discovery phase? And maybe success needs to also consider brain function.

Bret: 
Yeah, and that’s what’s so interesting also about a ketogenic intervention, ketogenic diets. When you develop a drug, it’s often developed with one target, one effect. Now they’re usually not that clean, but that’s usually how it’s studied. What is this one effect? Whereas a systemic change in diet and metabolic health improvements and ketones for the brain, it’s a multifaceted intervention that doesn’t have that sort of razor’s edge one effect.

Which on the one hand is really exciting, but the other hand can be really confusing, especially for researchers and especially for people with a drug developed mindset. So I think the way you’re approaching it is really important to say what does success look like? 

Lily: 
I think, yeah, I think it’s very exciting.

If you think about the naturalistic experiment that’s been performed with GLP-1 agonists where a very large percentage of the population has hopped on these drugs as a way to accelerate, or catalyzed, weight loss. One of the unintended side effects, very beneficial side effects, is that we’ve seen, for example, that it seems to be curbing people’s addiction.

And, you know that’s a wonderful side effect, and it may actually turn out to be much more powerful even than the weight loss effects that were originally deemed. Again, what does success look like In this case? It could be that success turns out to be even more powerful than what was initially hoped for.

But it also goes back to remind us that the idea that the brain and the body are somehow not connected to one another is the, it’s just not true, right? Physiology encompasses lots of brain, body, interactions, feedback in both directions. And so when we think about the health of one, we necessarily need to think about the health of the other.

Kirk: 
Lily, for people that read your paper and went on Amazon to order exogenous ketones that very same day to stave off the brain destabilizing, what would you like, can you speak to the state of the science where you think we’re at and, what you think is actionable here? If anything, what would your advice to those people be?

Lily: 
I think, I think that the way, I think about it for myself and for my loved ones is that the actionable advice, and I say this as someone who has seen my brain in the scanner and how it responds to both glucose and ketones, I think the most actionable piece of advice is to reduce glycemic load as early as possible and reducing glycemic load doesn’t need to mean following a particular diet.

I am not a diet evangelist with stock in any particular diet, but I do think that at this point the evidence is pretty clear that a high glycemic index diet is good for no one. And I also think that the other half of stabilizing your blood, and therefore brain glucose, comes down to exercise because, you know that in the same way that you can reduce your glycemic load by consuming less, simple carbs, you also can stabilize your glucose by just getting out and running around a bit more. And so I think that these natural lifestyle factors, even though they’re not particularly original, I feel doctors have been saying something like this for a long time.

I think that what this study shows for me is that the time to start taking these lifestyle factors very seriously is not when there’s a problem, but actually far before in preventing these effects. I don’t really, I’m not endorsing exogenous ketones as a quick fix. I view exogenous ketones as potentially a way to jumpstart ketosis or a lower glycemic state in people who already have started developing insulin resistance.

And the reason for that is that when you’re in a state of insulin resistance, your insulin levels are very high. And therefore it’s going to be very difficult to get into ketosis on your own simply because insulin actually inhibits glucagon, and glucagon is necessary for jumpstarting ketosis.

So for those individuals, for some of them it may be beneficial to jumpstart that process by trying exogenous ketones. I don’t see it as a long-term path towards sustainable regulation of your glycemic levels. I think it’s so much easier to make lifestyle changes that are more systemic and also much cheaper and easier to maintain.

Bret: 
Yeah. It’s interesting what you said about, it’s not novel advice to exercise more and reduce your glycemic load. We know a lot of people just say, ah, I don’t need to worry about that. I’m not having any problems. I don’t need to worry about that. So you gotta hit them where their concerns or their interests are.

So now we’re talking about the people in their mid forties to approaching mid forties concerned about future cognitive decline, cognitive function. That’s going to be this huge population of people. So now if we get the attention of that person to even say, I don’t have a problem yet, but look at this evidence shows I can do something to prevent problems in the future.

Now all of a sudden, maybe you’re getting some more people’s attention. So even if the advice isn’t the sexy, shiny advice, it’s still reaching the people at the time where they’re most vulnerable or most interested. And, of course, none of this is medical advice. People have to make their own decisions with their own healthcare team.

But I love that message that the research is now identifying the age and the situation where people need to sit up and take notice. I think that’s really important.

Lily: 
I do think also one thing that might be motivating and a good wake up call to identify vulnerability is that now that we can see these effects in the brain.

So we don’t just have to imagine, oh, at some point down the line, something bad could happen because of this, because we saw it in mice. Because we actually can measure it even at the single subject level. It also opens the door to thinking of this as a kind of a general wellness care that occurs in the same way that women might start having a mammogram around this age.

You might, generally go and check your brain stability levels at this age as well. 

Kirk: 
To that point, we started off talking about control systems and used the analogy of a car. A lot of new cars, for example, have a lane departure warning where there’s all sorts of bells that go off if you’re veering out of your lane.

Does our body have any equivalent control system and markers? To your point around population health and check-ins with your position at various points to assess health and wellbeing, any indicators of what we could be looking for should be looking for to get a sense that maybe some of these control systems are not, or that the alarm bells are ringing, we just don’t have a speaker to project them through our bodies? 

Lily: 
I think this gets back to the whole question of biomarkers, right? So what is the value of a biomarker? So the idea is that there are many examples where you have a long-term degenerative process that’s acting as a kind of silent killer, and you won’t actually detect the effects symptomatically until it might be too late.

And so in many other areas of medicine there have been development of biomarkers. So for example, looking at your blood pressure or looking at your lipid density and so forth, in the context of cardiovascular disease, turned what used to be a silent killer into something that you could identify and treat early on.

And I think that neuroimaging, in its ability to identify biomarkers before people are actually able to detect anything like what you’re describing, no. Nobody is detecting at this age these alarm bells that are going off. But if you put someone in a scanner scan, you have the sensitivity and resolution to see effects that are actually more sensitive, have greater detection sensitivity than your own internal alarm bells. And so from that perspective, I see it as a natural progression of medicine. 

Bret: 
Lily, this has been a fascinating discussion and congratulations on the paper and all your work and a lot of research. It presents a lot more questions, but really gives us some great starting points and, a lot to think about and chew on, so to speak, about age related changes.

How to prevent them, and how to set ourselves up for success in the future. But I’m really excited about all the work you’re doing. So if people wanted to learn more about you and your work, where would you direct them to go? 

Lily: 
So I have a website, www.LCneuro.org, which is the lab website.

Although you’ve been talking about my research, of course, it isn’t my research. We have a large lab of people who’ve done all the research together. Botond Antal is the first author of this study that you’re referring to, and I encourage anybody who’s interested to come take a look at our website and see what sorts of research are going on. It’s getting updated all the time.

I’d love to hear from your audience as well in terms of their perspectives on these, questions. 

Bret: 
Great. Great. Kirk, thank you so much for joining and asking all the wonderful questions. And Lily, thank you. It was been a pleasure. 

Lily: 
Oh, it’s been so much fun talking to you. Thank you so much.

Appreciate the invitation. 

Kirk: 
Thank you both. Real pleasure. 

Bret: 
I want to take a brief moment to let our practitioners know about a couple of fantastic free CME courses developed in partnership with Baszucki Group by Dr. Georgia Ede and Dr. Chris Palmer. Both of these free CME sessions provide excellent insight on incorporating metabolic therapies for mental illness into your practice.

They’re approved for a MA category one credits, CNE nursing credit hours. And continuing education credits for psychologists, and they’re completely free of charge on mycme.com. There’s a link in the description. I highly recommend you check them both out. Thanks for listening to the Metabolic Mind Podcast.

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