Nick Norwitz

Overweight, class one obesity, no increase. Class two obesity, LDL actually went down. And if you look at the individual participant level data, there was an inverse association across the BMI spectrum, where the leaner you were, the higher your LDL went. So this is encoded in the human randomized controlled trial literature. And I'll give a big hat tip to my friend Adrian Sotomoto, who is the...

uh guns behind that one the first author and then david ludwig we worked with on that paper what happens when people who are obese yeah and diabetic become thin and fit healthy and have more mass that's the fascinating thing so do they flip over to the other side i've seen this happen i've seen i'll give you one instance was a patient with a starting bmi of 43.2 that's big that's very big and actually you had low lvl baseline like in the 80s

uh guns behind that one the first author and then david ludwig we worked with on that paper what happens when people who are obese yeah and diabetic become thin and fit healthy and have more mass that's the fascinating thing so do they flip over to the other side i've seen this happen i've seen i'll give you one instance was a patient with a starting bmi of 43.2 that's big that's very big and actually you had low lvl baseline like in the 80s

uh guns behind that one the first author and then david ludwig we worked with on that paper what happens when people who are obese yeah and diabetic become thin and fit healthy and have more mass that's the fascinating thing so do they flip over to the other side i've seen this happen i've seen i'll give you one instance was a patient with a starting bmi of 43.2 that's big that's very big and actually you had low lvl baseline like in the 80s

Despite that, you know, I mean, they had high triglycerides, low HDL, and probably a pattern B LDL phenotype, but they had lowish LDL at 80. They started losing weight. They went on a ketogenic diet. They were losing lots of weight. BMI went to 30, 27. And right around BMI 26, 25, their LDL took a hairpin turn, where it was more or less stable, sub 100, and then shot up to 250.

Despite that, you know, I mean, they had high triglycerides, low HDL, and probably a pattern B LDL phenotype, but they had lowish LDL at 80. They started losing weight. They went on a ketogenic diet. They were losing lots of weight. BMI went to 30, 27. And right around BMI 26, 25, their LDL took a hairpin turn, where it was more or less stable, sub 100, and then shot up to 250.

Despite that, you know, I mean, they had high triglycerides, low HDL, and probably a pattern B LDL phenotype, but they had lowish LDL at 80. They started losing weight. They went on a ketogenic diet. They were losing lots of weight. BMI went to 30, 27. And right around BMI 26, 25, their LDL took a hairpin turn, where it was more or less stable, sub 100, and then shot up to 250.

just shot up as they got, they didn't really change their diet at all. They just got into this lean area and their LDL went through the roof.

just shot up as they got, they didn't really change their diet at all. They just got into this lean area and their LDL went through the roof.

just shot up as they got, they didn't really change their diet at all. They just got into this lean area and their LDL went through the roof.

So as a practical takeaway to people and things I'd highlight for the healthcare practitioners listening is like, if you have a patient with insulin resistance, type two diabetes, obesity, and you're interested in trying a ketogenic diet for them, they're very unlikely, to see the LDL change that might scare you. They're unlikely to have that response.

So as a practical takeaway to people and things I'd highlight for the healthcare practitioners listening is like, if you have a patient with insulin resistance, type two diabetes, obesity, and you're interested in trying a ketogenic diet for them, they're very unlikely, to see the LDL change that might scare you. They're unlikely to have that response.

So as a practical takeaway to people and things I'd highlight for the healthcare practitioners listening is like, if you have a patient with insulin resistance, type two diabetes, obesity, and you're interested in trying a ketogenic diet for them, they're very unlikely, to see the LDL change that might scare you. They're unlikely to have that response.

There might be a transient bump that's small that comes back down. We do see that in the literature. But as for this like jump to 400, you're unlikely to see it. So I think a few things that really need to be reconciled that are points of confusion around this are terms like, you know, LDL is causal and necessary for cardiovascular disease. in this idea of context dependency.

There might be a transient bump that's small that comes back down. We do see that in the literature. But as for this like jump to 400, you're unlikely to see it. So I think a few things that really need to be reconciled that are points of confusion around this are terms like, you know, LDL is causal and necessary for cardiovascular disease. in this idea of context dependency.

There might be a transient bump that's small that comes back down. We do see that in the literature. But as for this like jump to 400, you're unlikely to see it. So I think a few things that really need to be reconciled that are points of confusion around this are terms like, you know, LDL is causal and necessary for cardiovascular disease. in this idea of context dependency.

So what I'm not saying is that LDL or Applebee don't matter. I'm also not saying they're not part of the causal cascade. They are. But just because something is part of a causal cascade and necessary doesn't mean you need to treat it. Because context matters so much. Explain what you mean by context. in the context of the rest of their metabolic health?

So what I'm not saying is that LDL or Applebee don't matter. I'm also not saying they're not part of the causal cascade. They are. But just because something is part of a causal cascade and necessary doesn't mean you need to treat it. Because context matters so much. Explain what you mean by context. in the context of the rest of their metabolic health?

So what I'm not saying is that LDL or Applebee don't matter. I'm also not saying they're not part of the causal cascade. They are. But just because something is part of a causal cascade and necessary doesn't mean you need to treat it. Because context matters so much. Explain what you mean by context. in the context of the rest of their metabolic health?

Their metabolic health is one element of context. The context around like, what is actually driving up the biomarker? Because biomarkers can change for different reasons. And you can start to gain insight into why a biomarker might be where it is when you start to know the whole patient story. Yeah.