Why Low Cholesterol & ApoB Levels Are Critical for Longevity | Dr. Peter Attia & Dr. Andrew Huberman

Summary

In this insightful dialogue, Peter Attia and Andrew Huberman discuss the causal relationship between smoking and lung cancer, emphasizing the importance of causality in medicine. They extend this concept to the link between ApoB (a protein in the blood) and atherosclerosis, questioning current medical practices that wait for a high risk threshold before intervention. Attia advocates for proactive treatment to modify modifiable risks, regardless of current risk levels, to prevent diseases like heart attacks and strokes.

Takeaways

• 🚭 Smoking is causally related to lung cancer, as agreed by both Peter Attia and Andrew Huberman.
• 🔍 The discussion emphasizes the importance of establishing causality in medical research and practice.
• 🛑 Peter Attia suggests that the current approach to smoking cessation is flawed, proposing a model based on risk assessment.
• 📉 Attia argues against waiting until a certain risk threshold is reached before recommending smoking cessation.
• 🚫 The analogy is made that endorsing smoking until a risk threshold is as absurd as the hypothetical scenario presented.
• 🧬 Mendelian randomizations, which use genetic variants, provide strong evidence for the causal relationship between ApoB and atherosclerosis.
• 📊 Current medical practice involves calculating a 10-year risk of MACE (major adverse cardiac events) to assess the need for treatment.
• 🤔 Attia criticizes the practice of only treating LDL or ApoB when the 10-year MACE risk is above a certain percentage.
• 💯 He advocates for modifying modifiable risks regardless of the duration of the risk tail, suggesting earlier and less aggressive treatment.
• 🩺 Attia discusses the use of CT angiograms to assess the condition of coronary arteries and determine treatment goals for ApoB levels.
• ⚠️ A high ApoB level, even without symptoms, is considered a significant red flag and an indication for potential treatment.

Q & A

What is the consensus between Peter Attia and Andrew Huberman on the causal relationship between smoking and lung cancer?

Both Peter Attia and Andrew Huberman agree that smoking is causally related to lung cancer, not just associated with it.

What does Peter Attia consider an obsession of his in the context of medicine?

Peter Attia considers causality an obsession of his in the context of medicine, as he spends most of his day thinking about it.

What is the difficulty Peter Attia points out in studying medicine with respect to human beings?

Peter Attia points out that the difficulty in studying medicine with respect to human beings is inferring causality for most things that are done.

What is the logical equivalency according to Peter Attia if smoking is causally related to lung cancer?

The logical equivalency according to Peter Attia is that smoking cessation reduces the probability of lung cancer.

What is the new philosophy around smoking cessation that Peter Attia proposes in the script?

Peter Attia proposes a philosophy where people are allowed to smoke but are assessed for lung cancer risk using a model that predicts when their 10-year risk exceeds a certain threshold, at which point they are advised to stop smoking.

What does Peter Attia consider 'idiotic' in the context of smoking and lung cancer?

Peter Attia considers it 'idiotic' to endorse smoking until a person crosses a certain threshold of risk for lung cancer, rather than advising against smoking from the start.

What is Mendelian randomization and how does it relate to the causal relationship between ApoB and atherosclerosis?

Mendelian randomization is a method that uses genetic variants as a natural experiment to determine causality. It relates to ApoB and atherosclerosis by showing a gradation of LDL or ApoB concentration from very low to very high, indicating a causal relationship.

What does Peter Attia argue is the current backwards approach in medicine regarding LDL or ApoB treatment?

Peter Attia argues that the current approach in medicine is backwards because it only considers treating LDL or ApoB when the 10-year risk of a major adverse cardiac event is above a certain threshold, rather than modifying it regardless of the risk level if it is causal and modifiable.

What is MACE and why is it significant in the context of the script?

MACE stands for Major Adverse Cardiac Event, which includes heart attack, stroke, or death resulting from these conditions. It is significant in the script as it is the metric used to assess the 10-year risk for patients, which influences the decision on LDL or ApoB treatment.

What does Peter Attia suggest regarding the treatment of ApoB levels in patients with different risk factors?

Peter Attia suggests treating ApoB levels to the 5th percentile (about 60 mg/dL) if there are no signs of disease, but to the 1st percentile (30-40 mg/dL) if there are risk factors present such as calcification, soft plaque, family history, or other significant risk factors.

How does Peter Attia view the situation of a person with ApoB levels in the low 130s?

Peter Attia views ApoB levels in the low 130s as a huge red flag, indicating a high risk that requires attention, even though causality does not guarantee the disease in every individual.

Outlines

00:00

🚭 Smoking and Causality in Medicine

In this paragraph, Peter Attia and Andrew Huberman engage in a discussion about the causal relationship between smoking and lung cancer. They agree that smoking is not just associated with lung cancer but is a direct cause. Attia emphasizes the importance of understanding causality in medicine, as it is crucial for making informed decisions about health interventions. He introduces a hypothetical scenario where smoking cessation is recommended only when the 10-year risk of lung cancer reaches a certain threshold, which he later deems illogical. Attia then draws a parallel to the established causality between ApoB and atherosclerosis, suggesting that preventative measures should be taken from the start rather than waiting for risk to escalate.

05:00

🧬 Causality of LDL and Medical Treatment Approaches

The second paragraph delves into the medical community's approach to treating LDL and ApoB levels in relation to atherosclerosis risk. Attia criticizes the current practice of using 10-year risk calculators to determine when to intervene with treatments, arguing that it is as unreasonable as endorsing smoking until a high-risk threshold is reached. He advocates for a more proactive approach, modifying modifiable risks regardless of their current level, especially if they are causally related to disease. Attia discusses the use of CT angiograms to assess coronary artery health and suggests treatment goals based on the presence of disease indicators, family history, and other risk factors. The conversation also touches on the limitations of individual risk predictions and the importance of making judgments based on population data and causal inferences.

Keywords

💡Causality

Causality refers to the relationship between an event (the cause) and a second event (the effect), where the latter is a result of the former. In the video, causality is a central theme, with the discussion focusing on the causal relationship between smoking and lung cancer, and by extension, the relationship between ApoB and atherosclerosis. The script emphasizes the importance of understanding causality in medicine to make informed decisions about prevention and treatment.

💡Lung Cancer

Lung cancer is a malignant lung tumor characterized by uncontrolled cell growth in lung tissue. The video script discusses the consensus that smoking is causally related to lung cancer, highlighting the need for smoking cessation to reduce the risk of developing the disease. Lung cancer serves as a prime example in the conversation about the importance of addressing causal factors in medicine.

💡Smoking Cessation

Smoking cessation refers to the act of discontinuing tobacco smoking. In the script, the concept is explored as a preventative measure against lung cancer, given the established causal link between smoking and the disease. The discussion suggests that cessation should be encouraged universally rather than waiting for an individual's risk to reach a certain threshold.

💡Atherosclerosis

Atherosclerosis is a form of arteriosclerosis involving the deposit of lipids and other substances in the inner lining of an artery, leading to restricted blood flow. The video discusses the causal relationship between ApoB and atherosclerosis, indicating that understanding this causality is crucial for developing appropriate treatment strategies.

💡ApoB

ApoB, or apolipoprotein B, is a protein that plays a key role in the transport of lipids in the blood. The script highlights ApoB as a causal factor in atherosclerosis, emphasizing the importance of managing ApoB levels to mitigate the risk of cardiovascular diseases.

💡Mendelian Randomization

Mendelian randomization is an epidemiological method that uses genetic variants as instruments to investigate causality. In the video, this method is mentioned as a way to establish the causal link between ApoB levels and atherosclerosis, by observing the health outcomes of individuals with naturally varying levels of ApoB due to genetic mutations.

💡Major Adverse Cardiac Event (MACE)

MACE refers to a collective term for major heart-related events, including heart attacks, strokes, or death resulting from cardiac causes. The script discusses the use of 10-year risk calculations for MACE to determine treatment strategies, critiquing the approach for not addressing causal factors like ApoB levels proactively.

💡Risk Calculation

Risk calculation in the context of the video refers to the predictive models used in medicine to estimate an individual's probability of experiencing a certain event, such as a MACE, within a specified time frame. The script questions the current practice of using risk calculations to determine treatment, arguing for a more causality-focused approach.

💡CT Angiogram

A CT angiogram is a medical imaging technique that uses X-rays and computer processing to visualize the arteries and veins. In the script, it is mentioned as a diagnostic tool to assess the presence of calcification or plaque in coronary arteries, which can indicate the need for more aggressive treatment of ApoB levels.

💡Percentile

A percentile is a measure that indicates the value below which a given percentage of observations in a group of observations fall. The video discusses treating ApoB levels to certain percentiles of the population distribution as a strategy to reduce the risk of atherosclerosis, with more aggressive targets in the presence of additional risk factors.

💡Plaque

Plaque in the context of the video refers to deposits that can build up in the arterial walls, contributing to atherosclerosis. The script mentions soft plaque as a factor that might warrant more aggressive treatment to lower ApoB levels and reduce the risk of cardiovascular events.

Highlights

Dr. Andrew Huberman confirms the causal relationship between smoking and lung cancer.

Peter Attia and Dr. Huberman discuss the importance of understanding causality in medicine.

Attia emphasizes the difficulty of inferring causality in medical studies involving humans.

The logical equivalency that smoking cessation reduces the probability of lung cancer is established.

Attia introduces a hypothetical smoking cessation philosophy based on risk assessment models.

The conversation highlights the absurdity of endorsing smoking until a certain health risk threshold is reached.

ApoB is identified as causally related to atherosclerosis through various types of evidence, including Mendelian randomizations.

Mendelian randomization is explained as a method using genetic variation to infer causality.

Attia criticizes current medical practices that do not treat LDL or ApoB unless the 10-year MACE risk is above a certain threshold.

The argument is made that modifiable risks should be addressed regardless of their current risk level.

Attia discusses the use of CT angiograms to assess coronary artery health and inform treatment decisions.

Different treatment approaches are considered based on the presence of calcification or soft plaque in the arteries.

The importance of individualized risk assessment in medical decision-making is highlighted.

Attia and Huberman acknowledge the existence of outliers who do not follow typical causal patterns, such as smokers without lung cancer.

The conversation concludes with a focus on making the best judgment for individuals based on population data and causal inferences.

Transcripts

PETER ATTIA: Would you agree that smoking is causally

related to lung cancer?

ANDREW HUBERMAN: Yes.

PETER ATTIA: So just to be clear,

Andrew, you do not think that it's just an association

that smokers get more lung cancer?

ANDREW HUBERMAN: No, I do not.

PETER ATTIA: In other words, you believe that smoking

causes lung cancer then?

ANDREW HUBERMAN: Yes.

I mean, there are a number of mechanistic steps in between.

I mean, if somebody want to get to drill into the logic,

they could say, OK, it's not actually the smoking.

It's some disruption of the endothelial cell lining that--

PETER ATTIA: But smoking triggers that.

It triggers that.

ANDREW HUBERMAN: I assume so.

PETER ATTIA: And I agree with you, by the way.

I think the data are very clear.

ANDREW HUBERMAN: I'm very relieved to hear that.

PETER ATTIA: But I'm going someplace very important here.

Because if there's one topic that

doesn't get enough attention in medicine, it's causality.

And causality is an obsession of mine.

Most of the day, on some level, I

sit around thinking about causality.

And I think the hardest part about studying medicine

with respect to human beings is how difficult it

is to infer causality for most things that we do.

So if you believe that smoking is causally related

to lung cancer, then smoking cessation

reduces the probability of lung cancer.

That is a logical equivalency.

There can be no debate about that.

What if I said to you, Andrew, this

is going to be our new philosophy around smoking

cessation.

I'm going to anoint you the czar of smoking cessation.

So if people pick up smoking, no problem.

We're going to let them smoke.

But we're going to assess their risk for lung cancer using

a model that predicts when their 10-year risk of lung cancer

gets above a certain level, we're going to recommend

that they stop smoking.

So we're going to look at their age, their sex, their family

history, some biomarkers that might help us.

We're going to even do scans of their lungs.

And once we think they cross a threshold where their risk

of lung cancer is high enough-- let's just say it's 25%-- boom.

You make them stop.

You tell them it's time to stop.

Is that a logical approach to treating smoking and lung

cancer?

Or would it be better to say, given

that we know cigarettes are causally related to this, how

about you never start smoking?

And the minute you do, we pull the cigarette out of your mouth

and explain to you that you're doing something

that is causally related.

Of course, it would be the latter, not the former.

It would be idiotic to suggest that we

endorse smoking until you cross a certain threshold.

Well, this now becomes the germane question.

There is no ambiguity that ApoB is causally related

to atherosclerosis.

How can I tell you that?

I can tell you that looking at all of the clinical trial

literature, all of the epidemiologic literature

and, perhaps, even most importantly, the Mendelian

randomizations.

All of these things tell us, because by the way--

ANDREW HUBERMAN: Mendelian randomizations

meaning genetic mutants, humans out there

that make very little ApoB or excessive ApoB.

PETER ATTIA: And very much.

Exactly.

So we have a whole grade.

ANDREW HUBERMAN: So you can say if you make very little,

you aren't going to die as quickly in your life

as if you make too much.

PETER ATTIA: That's right.

So Mendelian randomization is such an elegant tool

where you basically let genes do the randomization.

And as you said, there is a gradation

of LDL concentration or ApoB concentration

that occurs from insanely low to insanely high.

And this is a wildly polygenic, polymorphic set of conditions.

And we can look at the outcomes of those people

based on the random sorting of those genes.

And there's no ambiguity.

LDL is causally related--

LDL cholesterol or ApoB, causally

related to atherosclerosis.

Well, if that's true, and I haven't

seen a credible argument that it's not--

there are people who argue that it's not, by the way,

but they just don't have credibility

in their arguments-- then you have

to say that what we're doing in medicine today

is very backwards.

Because what we're doing in medicine today is

the following-- we're saying--

I'm coming at this in a long way,

but your question is so important

that I want to answer it this way.

We're answering your question today

as follows-- we're saying, Andrew,

let's do a 10-year risk calculation

of your risk of MACE.

MACE stands for major adverse cardiac event.

It is the metric we use in medicine.

So a major adverse cardiac event is a heart attack, stroke

or death basically resulting from these things.

And we have calculators that are pretty good at predicting

your 10-year event risk.

They'll look at your cholesterol levels, your blood pressure.

They'll ask if you smoke.

They'll ask some family history questions,

and they'll spit out a number.

Now, we should do yours after the fact.

And I don't know.

If we did it for a person who's-- you're in your mid-40s,

it would probably spit out less than 5% risk for a major

adverse cardiac event in the next 10 years.

In fact, the models don't even work if age is below 40.

So the first time I went to do one of these tests

when I was in my mid-30s, I couldn't do it.

The algorithm breaks.

It just doesn't work.

So the implication there is if your MACE risk is less than 5%,

the thinking is you do not need to treat LDL or ApoB.

I argue that makes absolutely no sense.

It's just as idiotic as the analogy I used around smoking.

If a risk is causal and it is modifiable,

it should be modified regardless of the risk tail in duration.

So then, the question becomes to what level?

And again, the earlier you start, the less aggressive

you need to be, the less damage that's there already.

So for example, we do CT angiograms on our patients.

If the CT angiogram shows no evidence of calcification,

no evidence of soft plaque, that means grossly,

the coronary arteries are still normal.

Histologically, they're probably not,

because nobody probably makes it to our age with histologically

perfect coronary arteries.

We might be satisfied with a person's ApoB

being at the 5th percentile of the population, which

would be about 60 milligrams per deciliter.

But if we have any other factors,

meaning we're starting later in life

or a person already has gross evidence of disease--

calcification, soft plaque-- family history is significant,

any other risk factors are present, I mean,

we'll treat ApoB to 30 to 40 milligrams per deciliter, which

is probably the 1st percentile.

ANDREW HUBERMAN: And if somebody's sitting up

in the, say, low 130s, what kind of flag

does that raise for you?

And I realize it's highly contextual-- age, et cetera.

PETER ATTIA: No, no, it's a huge red flag.

Again, just because something is causal

doesn't mean you're guaranteed to get it.

There are smokers who don't get lung cancer.

So there's going to be somebody listening to this who says,

my grandmother is 95 years old.

Her cholesterol is sky high, and she's alive and well.

And I will say, absolutely.

There are a lot of people walking around that way.

Just as there are a lot of smokers walking around who

don't get lung cancer.

You can't impute these things on an individual basis.

You basically have to ask the question,

how do I make the best judgment about an individual

from heterogeneous population data

and based on what are causal and non-causal inferences

around risk.

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