Why Low Cholesterol & ApoB Levels Are Critical for Longevity | Dr. Peter Attia & Dr. Andrew Huberman
00:00:00.000 | Would you agree that smoking is causally related to lung cancer?
00:00:07.520 | Yes.
00:00:08.520 | So just to be clear, Andrew, you do not think that it's just an association that smokers
00:00:13.800 | get more lung cancer?
00:00:15.120 | No, I do not.
00:00:16.840 | You, in other words, you believe that smoking causes lung cancer then?
00:00:22.040 | Yes.
00:00:23.040 | Okay.
00:00:24.040 | I mean, there are a number of mechanistic steps in between.
00:00:26.200 | I mean, if somebody was really wanting to drill into the logic, they could say, okay,
00:00:31.460 | it's not actually the smoking, it's a, you know, some disruption of the endothelial cell
00:00:36.600 | lining that, you know...
00:00:37.600 | But smoking triggers that, that triggers that.
00:00:40.240 | I assume so.
00:00:41.240 | And I agree with you, by the way.
00:00:42.240 | I think the data are very clear.
00:00:43.240 | I'm very relieved to hear that.
00:00:44.240 | Yeah, yeah.
00:00:45.240 | But I'm going someplace very important here, because if there's one topic that doesn't
00:00:50.840 | get enough attention in medicine, it's causality.
00:00:55.420 | And causality is an obsession of mine.
00:00:58.960 | Like most of the day on some level, I sit around thinking about causality.
00:01:05.760 | And I think the hardest part about studying medicine with respect to human beings is how
00:01:12.720 | difficult it is to infer causality for most things that we do.
00:01:18.660 | So if you believe that smoking is causally related to lung cancer, then smoking cessation
00:01:30.060 | reduces the probability of lung cancer.
00:01:33.620 | That is a logical equivalency.
00:01:36.480 | There can be no debate about that.
00:01:39.900 | What if I said to you, Andrew, this is going to be our new philosophy around smoking cessation.
00:01:45.500 | I'm going to anoint you the czar of smoking cessation.
00:01:50.460 | So if people pick up smoking, no problem.
00:01:53.580 | We're going to let them smoke.
00:01:56.300 | But we're going to assess their risk for lung cancer using a model that predicts when their
00:02:03.460 | 10-year risk of lung cancer gets above a certain level, we're going to recommend that they
00:02:08.080 | stop smoking.
00:02:09.620 | So we're going to look at their age, their sex, their family history, some biomarkers
00:02:13.980 | that might help us.
00:02:14.980 | We're going to even do scans of their lungs.
00:02:17.880 | And once we think they cross a threshold where their risk of lung cancer is high enough,
00:02:23.060 | let's just say it's 25%, boom.
00:02:26.020 | You make them stop.
00:02:27.020 | You tell them it's time to stop.
00:02:28.780 | Is that a logical approach to treating smoking and lung cancer?
00:02:33.500 | Or would it be better to say, given that we know cigarettes are causally related to this,
00:02:40.300 | how about you never start smoking, and the minute you do, we pull the cigarette out of
00:02:44.260 | your mouth and explain to you that you're doing something that is causally related?
00:02:49.060 | Of course, it would be the latter, not the former.
00:02:51.020 | It would be idiotic to suggest that we endorse smoking until you cross a certain threshold.
00:02:57.660 | Well, this now becomes the germane question.
00:03:01.900 | There is no ambiguity that ApoB is causally related to atherosclerosis.
00:03:09.020 | You know, how can I tell you that?
00:03:10.780 | I can tell you that looking at all of the clinical trial literature, all of the epidemiologic
00:03:16.580 | literature, and perhaps even most importantly, the Mendelian randomizations.
00:03:21.340 | All of these things tell us...
00:03:23.940 | Because by the way...
00:03:24.940 | Mendelian randomizations meaning genetic mutants, humans out there that make very little ApoB
00:03:29.340 | or excessive ApoB.
00:03:30.340 | And very much, exactly.
00:03:31.340 | So we have the whole gradient.
00:03:32.340 | So you can say if you make very little, you aren't going to die as quickly in your life
00:03:37.140 | as if you make too much.
00:03:38.420 | That's right.
00:03:39.420 | So the Mendelian randomization is such an elegant tool where you basically let genes
00:03:43.340 | do the randomization.
00:03:45.340 | And as you said, there is a gradation of LDL concentration or ApoB concentration that occurs
00:03:51.300 | from insanely low to insanely high.
00:03:54.780 | And this is a wildly polygenic, polymorphic set of conditions.
00:03:59.220 | And we can look at the outcomes of those people based on the random sorting of those genes
00:04:04.900 | and there's no ambiguity.
00:04:06.380 | LDL is causally related, LDL cholesterol or ApoB, causally related to atherosclerosis.
00:04:14.340 | Well, if that's true, and I haven't seen a credible argument that it's not...
00:04:21.220 | There are people who argue that it's not, by the way, but they just don't have credibility
00:04:23.940 | in their arguments.
00:04:25.260 | Then you have to say that what we're doing in medicine today is very backwards.
00:04:30.740 | Because what we're doing in medicine today is the following.
00:04:33.980 | We're saying, I'm coming at this in a long way, but your question is so important that
00:04:38.660 | I want to answer it this way.
00:04:40.140 | We're answering your question today as follows.
00:04:42.460 | We're saying, "Andrew, let's do a 10-year risk calculation of your risk of MACE."
00:04:50.260 | MACE stands for Major Adverse Cardiac Event.
00:04:53.220 | It is the metric we use in medicine.
00:04:56.180 | So a Major Adverse Cardiac Event is a heart attack, stroke, or death basically resulting
00:05:01.740 | from these things.
00:05:04.020 | And we have calculators that are pretty good at predicting your 10-year event risk.
00:05:10.340 | They'll look at your cholesterol levels, your blood pressure, they'll ask if you smoke,
00:05:14.980 | they'll ask some family history questions, and they'll spit out a number.
00:05:19.180 | Now we should do yours after the fact.
00:05:23.380 | And I don't know, if we did it for a person who's as, you know, you're in your mid-40s,
00:05:28.740 | like it would probably spit out less than 5% risk for a Major Adverse Cardiac Event
00:05:34.980 | in the next 10 years.
00:05:35.980 | In fact, the models don't even work if age is below 40.
00:05:41.800 | So the first time I went to do one of these tests when I was in my mid-30s, I couldn't
00:05:46.980 | do it.
00:05:49.140 | The algorithm breaks.
00:05:50.140 | That's sort of like, you know, just doesn't work.
00:05:51.860 | So the implication there is if your MACE risk is less than 5%, the thinking is you do not
00:06:01.660 | need to treat LDL or ApoB.
00:06:05.180 | I argue that that makes absolutely no sense.
00:06:07.800 | It's just as idiotic as the analogy I used around smoking.
00:06:12.020 | If a risk is causal and it is modifiable, it should be modified regardless of the risk
00:06:18.420 | tail in duration.
00:06:21.340 | So then the question becomes, to what level?
00:06:24.180 | And again, the earlier you start, the less aggressive you need to be, the less damage
00:06:29.020 | that's there already.
00:06:30.340 | So for example, we do CT angiograms on our patients.
00:06:33.580 | If the CT angiogram shows no evidence of calcification, no evidence of soft plaque, that means grossly
00:06:40.100 | their coronary arteries are still normal.
00:06:42.100 | Histologically, they're probably not because nobody probably makes it to our age with histologically
00:06:47.340 | perfect coronary arteries.
00:06:50.060 | You know, we might be satisfied with a person's ApoB being at the fifth percentile of the
00:06:55.180 | population, which would be about 60 milligrams per deciliter.
00:06:59.660 | But if we have any other factors, meaning we're starting later in life, you know, or
00:07:05.380 | a person already has gross evidence of disease, calcification, soft plaque, family history
00:07:12.100 | is significant, any other risk factors are present, I mean, we'll treat ApoB to 30 to
00:07:18.740 | 40 milligrams per deciliter, which is, you know, probably the first percentile.
00:07:22.460 | And if somebody's sitting up in the, say, low 130s, where does that, what kind of flag
00:07:28.420 | does that raise for you?
00:07:29.420 | And I realize it's highly contextual, age, et cetera.
00:07:31.740 | No, no.
00:07:32.740 | It's a huge red flag.
00:07:34.140 | Again, just because something is causal doesn't mean you're guaranteed to get it.
00:07:38.700 | There are smokers who don't get lung cancer.
00:07:40.500 | So, you know, there's going to be somebody listening to this who says, "My grandmother
00:07:44.820 | is 95 years old, she's, her cholesterol is sky high and she's alive and well."
00:07:50.420 | And I will say, "Absolutely.
00:07:51.740 | There are a lot of people walking around that way."
00:07:53.760 | Just as there are a lot of smokers walking around who don't get lung cancer.
00:07:59.900 | You can't, you can't impute these things on an individual basis.
00:08:04.700 | You basically have to ask the question, "How do I make the best judgment about an individual
00:08:11.380 | from heterogeneous population data and based on what are causal and non-causal inferences
00:08:18.420 | around risk?"
00:08:19.180 | [Music]