The Peter Attia Drive - #286 ‒ Journal club with Andrew Huberman： the impact of light exposure on mental health and an immunotherapy breakthrough for cancer treatment

00:00:00.000 Hey, everyone. Welcome to the Drive podcast. I'm your host, Peter Atiyah. This podcast,

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00:00:53.200 of the subscription. If you want to learn more about the benefits of our premium membership,

00:00:58.020 head over to peteratiyahmd.com forward slash subscribe. Welcome to another special episode

00:01:06.660 of The Drive. This episode is actually a dual episode with my good friend, Andrew Huberman,

00:01:12.240 where we are going to be releasing our conversation on both the Huberman Lab podcast and The Drive.

00:01:17.780 In this special episode, Andrew and I team up again for another round of Journal Club,

00:01:23.980 and you may recall this is the second time we've done it, having done it back in September of 2023.

00:01:29.680 We enjoy this so much that I suspect we're going to continue to do this, potentially at the cadence

00:01:34.500 of about once a quarter, but of course, we'll see. In today's Journal Club, we start by looking at a

00:01:40.100 paper that Andrew highlighted, which looks at how light exposure and dark exposure can affect mental

00:01:45.800 health. After that, I present a paper, which is kind of a landmark study on a class of drugs that

00:01:52.080 I believe are some of the most relevant classes of drugs in cancer therapy over the past 20 years,

00:01:58.040 the so-called checkpoint inhibitors. The hope here is not only that this conversation gives you

00:02:03.340 insights in the specific papers that we're discussing, both of which I think are highly fascinating,

00:02:09.600 but equally importantly, that you can learn something about how to read scientific papers,

00:02:14.080 what to look for, and what the papers say, and what's being reported, and how that doesn't

00:02:19.120 necessarily match with what the news is telling you. That's a really common issue, as many of you know,

00:02:24.080 and I certainly rail against this, where I'll comment on a paper that the media has picked up on

00:02:29.920 and completely misrepresented. And again, there's really only one antidote to this, and the antidote

00:02:35.000 is learning how to read the papers yourself. And unfortunately, there really is no better way to do

00:02:40.860 that than practice. And so what we really hope is that people will sit with us and maybe take a look

00:02:47.100 at the papers before they watch the podcast or listen to the podcast, and try to get a sense of

00:02:52.240 what they notice about these papers, what questions arise for them, and see if we touch on similar

00:02:56.920 topics. As a brief reminder to anyone who's been up in the Himalayas hunting Yeti for the past six years

00:03:02.500 and doesn't know who Andrew is, he is an associate professor of neurobiology and ophthalmology at the

00:03:07.000 Stanford University School of Medicine and the host of the very popular Huberman Lab podcast. He's also

00:03:11.880 a former podcast guest on episodes 249 and 270. So without further delay, please enjoy my conversation

00:03:20.020 with Andrew Huberman. Andrew, great to have you here for journal club number two. I'm already confident

00:03:31.540 this is going to become a regular for us. I'm excited. I really enjoy this because I get to pick

00:03:37.200 papers I'm really excited about. I get to hear papers that you're excited about, and we get to

00:03:43.420 sharpen our skills at reading and sharing data, and people listening can do that as well.

00:03:49.920 So last time I went first, so I think I'm going to put you on the hot seat first and have you go first,

00:03:54.840 and I'll follow you. Okay. Well, I'm really excited about this paper for a number of reasons. First of all,

00:04:00.860 it, at least by my read, is a very powerful paper in the sense that it examined light exposure

00:04:08.400 behavior as well as dark exposure behavior. And that's going to be an important point in more

00:04:13.500 than 85,000 people as part of this cohort in the UK. I'll just mention a couple of things to give

00:04:20.160 people background, and I'll keep this relatively brief. First of all, there's a longstanding interest

00:04:25.880 in the relationship between light and mental health and physical health. And we can throw up

00:04:30.660 some very well-agreed-upon bullet points. First of all, there is such a thing as seasonal affective

00:04:37.560 disorder. It doesn't just impact people living at really northern locations, but basically there's

00:04:43.400 a correlation between day length and mood and mental health, such that for many people, not all,

00:04:51.200 but for many people, when days are longer in the spring and summer, they feel better.

00:04:55.820 They report fewer depressive symptoms. And conversely, when days are shorter,

00:05:01.900 significantly more people report feeling lower mood and affect. There's a longstanding treatment

00:05:07.860 for seasonal affective disorder, which is to give people exposure to very bright light,

00:05:13.620 especially in the morning. The way that that's normally accomplished is with these sad lamps,

00:05:19.280 seasonal affective disorder lamps. And those lamps are basically bright, meaning more than 10,000

00:05:24.880 luxe lights that they place on their kitchen counter or at their table in the morning or in their

00:05:31.200 office. So they're getting a lot of bright light. That has proven to be fairly effective for the

00:05:37.140 treatment of seasonal affective disorder. What's less understood is how light exposure in the middle

00:05:42.260 of the night can negatively impact mood and health. And so where we are headed with this is that there

00:05:49.420 seems to be based on the conclusions of this new study, a powerful and independent role of both

00:05:57.300 daytime light exposure and nighttime dark exposure for mental health. Now, a couple of other key

00:06:03.740 points, the biological mechanisms for all this are really well established. There's a set of cells in

00:06:09.680 the neural retina, which aligns the back of your eye. They're sometimes called intrinsically

00:06:13.800 photosensitive. Retinal ganglion cells are sometimes called melanopsin retinal ganglion cells. We'll talk

00:06:19.860 about those in a bit of detail in a moment. It's well known that those cells are the ones that respond

00:06:25.720 to two different types of light input, not one, but two different types of light input and send

00:06:31.640 information to the hypothalamus where your master circadian clock resides. And then your master

00:06:36.180 circadian clock sends out secretory signals. So peptides, hormones, but also neural signals to the brain

00:06:42.920 and body and say, Hey, now it's daytime. Now it's nighttime, be awake, be asleep. But it goes way

00:06:48.940 beyond that. These melanopsin intrinsically photosensitive retinal ganglion cells, we know

00:06:53.640 also project to areas of the brain like the habenula, which can trigger negative affect, negative mood.

00:06:59.940 They can trigger the release of dopamine or the suppression of dopamine, the release of serotonin,

00:07:05.180 the suppression of serotonin. And so they're not just cells for setting your circadian clock.

00:07:10.240 They also have a direct line, literally one synapse away into the structures of the brain that we

00:07:16.260 know powerfully control mood. So the mechanistic basis for all this is there. So there's just a

00:07:21.240 couple of other key points to understand for people to really be able to digest the data in

00:07:26.020 this paper fully. There are basically two types of stimuli that these cells respond to. One is very

00:07:33.540 bright light, as we just talked about. That's why getting a lot of daytime sunlight is correlated with

00:07:39.300 elevated mood. That's why looking at a 10,000 lux artificial lamp can offset seasonal affective

00:07:44.620 disorder. By the way, just a couple of questions on that. How many lux does the sun provide on a

00:07:50.180 sunny day at noon? Okay, great question. So if you're out in the sun with no cloud cover or minimal

00:07:57.360 cloud cover in the middle of the day at noon, chances are it's over a hundred thousand lux.

00:08:03.700 On a really bright day could be 300,000 lux. Most indoor environments, even though they might seem

00:08:12.720 very bright, department store with the bright lights, believe it or not, that's probably only

00:08:18.320 closer to 6,000 lux maximum and probably more like 4,000 lux. Most brightly lit indoor environments

00:08:26.440 are not that bright when it comes down to total photon energy. Now, here's the interesting thing.

00:08:32.400 On a cloudy day, when you're outside, it can be as bright as an average of 100,000 lux, but it won't

00:08:42.040 seem that bright because you don't quote unquote see the sun. But it's also because when there's cloud

00:08:47.900 cover, a lot of those long wavelengths of light, such as orange and red light aren't coming through.

00:08:53.340 However, and this is so important, the circadian clock, the suprachiasmatic nucleus,

00:08:58.180 it sums photons. It's a photon summing system. So basically if you're outside in 8,000 lux,

00:09:08.400 very overcast UK winter day, and you're walking around hopefully without sunglasses, because

00:09:15.000 sunglasses are going to filter a lot of those photons out, your circadian clock is summing the

00:09:20.420 photons. So it's an integration mechanism. It's not triggered in a moment. And actually the experiments

00:09:26.620 of recording from these cells first done by David Burson at Brown were historic in the field of

00:09:31.520 visual neuroscience. When shown bright light on these intrinsically photosensitive cells, you could

00:09:36.140 crank up the intensity of the light and the neurons would ramp up their membrane potential and then

00:09:42.260 start spiking, firing action potentials or long trains of action potentials that have been shown to

00:09:47.700 go on for hours. And so that's the signal that's propagating into the whole brain and body.

00:09:52.900 So the important thing to understand is this is not a quick switch. That's why I suggest on

00:09:58.040 non-cloudy days, we'll call them, that people get 10 minutes or so of sunlight in their eyes in the

00:10:04.380 early part of the day, another 10 minimum in the later part of the day, as much sunlight in their

00:10:09.760 eyes as they safely can throughout the day. But since you're a physician and you had a guest on

00:10:13.880 talking about this recently, when the sun is low in the sky, low solar angle sunlight, that's really the

00:10:18.340 key time for reasons we'll talk about in a moment. And when the sun is low in the sky, you run very,

00:10:24.020 very little risk of inducing cataract by looking in the general direction of the sun. You should

00:10:27.780 still blink as needed to protect the eyes. It's when the sun is overhead, there's all those photons

00:10:32.760 coming in quickly in a short period of time. You do have to be concerned about cataract and

00:10:37.980 macular degeneration if you're getting too much daytime sunlight. So the idea is sunglasses in the

00:10:43.300 middle of the day are fine, but you really should avoid using them in the early and later part of the day,

00:10:47.140 unless you're driving into the sun for safety reasons. Another question, Andrew, if a person

00:10:52.300 is indoors, but they have large windows, they're getting tons of sunlight into their space. They

00:10:59.280 don't even need ambient indoor light. How much of the photons are making it through the glass

00:11:03.740 and how does that compare to this effect? In general, unless the light is coming directly

00:11:10.540 through the window, most of the relevant wavelengths are filtered out. In other words, if you can't see the

00:11:16.280 sun through the window, even if sufficient light is being provided, that's insufficient to trigger

00:11:21.640 this phenomenon? That's right. However, if you have windows on your roof, which some people do,

00:11:27.640 skylights, that makes the situation much, much better. In fact, the neurons in the eye that signal

00:11:34.360 to the circadian clock and these mood centers in the brain reside mainly in the bottom two-thirds of the

00:11:39.640 neural retina and are responsible for looking up. Basically, they're gathering light from above.

00:11:45.620 These cells are also very low resolution. Think of them as big pixels. They're not interested in

00:11:51.160 patterns and edges and movement. They're interested in how much ambient light there happens to be.

00:11:55.620 Now, keep in mind that this mechanism is perhaps the most well-conserved mechanism in cellular organisms.

00:12:01.880 And I'll use that as a way to frame up the four types of light that one needs to see every 24 hours

00:12:08.480 for optimal health. And when I say optimal health, I really mean mental health and physical health,

00:12:13.200 but we're going to talk about mental health mainly today in this paper. There's an absolutely beautiful

00:12:18.180 evolutionary story whereby single-cell organisms all the way to humans, dogs, rabbits, and everything in

00:12:25.620 between have at least two cone options, one that responds to short wavelength light, aka blue light,

00:12:32.500 and another one that responds to longer wavelength light, orange and red. So your dogs have this,

00:12:38.140 we have this, and it's a comparison mechanism in these cells of the eye, these neurons of the eye.

00:12:44.100 They compare contrast between blues and orange, or sometimes blues and reds and pinks, which are also

00:12:49.360 all long wavelength light. There are two times of day when the sky is enriched with blues, oranges,

00:12:57.080 pinks, and reds, and that's low solar angle sunlight at sunrise and in the evening. These cells are

00:13:05.600 uniquely available to trigger the existence of those wavelengths of light early in the day and in the

00:13:12.840 evening, not in the middle of the day. So these cells have these two cone photopigments and they say,

00:13:17.100 how much blue light is there? How much red light is there or orange light? And the subtraction

00:13:21.780 between those two triggers the signal for them to fire the signal off to the circadian clock of the

00:13:27.420 brain. And that's why I say, look at low solar angle sunlight early in the day. What that does

00:13:32.140 is it, what we call it is phase advances the clock. This can get a little technical and we don't want

00:13:36.600 to get too technical here, but think about pushing your kid on a swing. The period of that swing,

00:13:41.020 the duration of that swing is a little bit longer than 12 hours. So when you stand closer to the

00:13:49.520 kid, so your kid swings back and you give it a push, you're shortening the period. You're not

00:13:54.400 allowing the swing to come all the way up. That's what happens when you look at morning sunlight,

00:13:58.700 you're advancing your circadian clock. Translate to English or non-nerd speak. You're making it such

00:14:04.500 that you will want to go to bed a little bit earlier and wake up a little bit earlier the next

00:14:09.360 day. In the evening, when you view low solar angle sunlight, the afternoon setting sun or evening

00:14:16.040 setting sun, you do the exact opposite. You're phase delaying the clock. It's the equivalent of

00:14:21.340 your kid being at the very top of the arc. And so it's gone, you know, maybe let's say 12 and a

00:14:25.900 half hours is the duration of that swing. And you run up and you push them from behind and give them a

00:14:31.240 little more push. That's the equivalent of making yourself stay up a little later and wake up a

00:14:35.660 little later. These two signals average so that your clock stays stable. You don't drift, meaning

00:14:41.500 you're not waking up earlier every single day or going to sleep later every single day. This is why

00:14:46.620 it's important to view low solar angle sunlight in the morning and again in the evening as often as

00:14:52.920 possible. And it's done by that readout of those two photopigments. Now, midday sun, it's bright

00:15:00.140 light, but you see it as white light, contains all of those wavelengths at equal intensity.

00:15:05.120 So the middle of the day is the so-called circadian dead zone. In the middle of the day,

00:15:10.040 bright light triggers the activation of the other opsin, the melanopsin, which increases mood,

00:15:16.260 increases feelings of well-being, has some other consequences, but you can't shift your circadian

00:15:20.040 clock by viewing the sun in the middle of the day because it's in the circadian dead zone. It's the

00:15:24.260 equivalent of pushing your kid on the swing when they're at the bottom of the arc. You can get a

00:15:29.120 little bit more, but not much. And in biological terms, you get nothing. So this is why looking

00:15:35.120 at sunlight in the middle of the day is great, but it's not going to help anchor your sleep-wake cycle.

00:15:39.620 And if you think about it, this is incredible, right? Every organism from single cells to us

00:15:45.380 has this mechanism to know when the sun is rising and when the sun is setting. And it's a color

00:15:49.580 comparison mechanism, which tells us that actually color vision evolved first, not for pattern vision,

00:15:56.380 not for seeing beautiful sunsets and recognizing that's beautiful or paintings or things of that

00:16:00.960 sort, but rather for setting the circadian clock. Now, what if you only do one of these, Andrew? So

00:16:06.140 what if you've got constant exposure to low morning light, but your job prevents you from doing the

00:16:13.500 same in the evening or vice versa? Better to get the morning light because if you have to pick between

00:16:19.440 low solar angle light early or later in the day. And keep in mind, if you miss a day, no big deal.

00:16:24.120 It's a slow integrative mechanism averaging across the previous two or three days. But if you miss a

00:16:29.800 day, you'll want to get twice as much light in your eyes that next morning. The reason it's better

00:16:35.240 to do in the morning as opposed to the evening, although best would be to do both, is that most

00:16:40.540 people are getting some artificial light exposure in the evening anyway. And here's the diabolical thing.

00:16:46.020 Your retina is very insensitive to light early in the day. You need a lot of photons to trigger this

00:16:51.540 mechanism early in the day. As the day goes on, retinal sensitivity increases and it takes very

00:16:56.120 little light to shift your circadian clock late in the day. Keep in mind also that if you do see

00:17:01.480 afternoon and evening sunlight, there's a beautiful study published in Science Reports two years ago

00:17:07.360 showing that that can partially offset the negative effects of artificial light exposure at night.

00:17:12.660 I think of this as your Netflix inoculation. The amount of melatonin suppression from nighttime light

00:17:17.920 exposure is halved by viewing evening setting sun. Now, keep in mind, you don't need to see the sun

00:17:24.060 cross the horizon. It can just be when it's low solar angle. So you're looking for those yellow,

00:17:28.300 blue or blue, pink, blue, red contrasts. And on cloudy days, believe it or not, they're still there.

00:17:34.220 Just you don't perceive as much of it coming through. So that's three things that we should all strive to do.

00:17:40.120 View low solar angle sunlight early in the day. View solar angle sunlight later in the day and get as much

00:17:45.140 bright light in our eyes as we safely can, ideally from sunlight throughout the day.

00:17:49.880 And if you can't do that, perhaps invest in one of these satellites so that they can be a bit

00:17:54.580 expensive. There are a couple of companies that are starting to design sunrise simulators and evening

00:17:59.500 simulators that are actually good, that actually work. But right now, my read is that aside from one

00:18:05.460 company out there, which by the way, I have no relationship to, it's called the Tuolite, T-U-O.

00:18:10.140 And that light bulb was developed by the biologists of the University of Washington who

00:18:15.500 basically discovered these color opponent mechanisms. Those lights are not particularly

00:18:21.060 expensive, but they do seem to work. In fact, the study that is emerging, again, unpublished data

00:18:26.340 seems to indicate that if you look at it for more than five or six minutes, it can induce a mild euphoria.

00:18:31.880 That's how powerful this contrast is. And what they did there in that light, I'll just tell you the

00:18:35.920 mechanism, is they figured out that when most people look at low solar angle sunlight in the

00:18:39.880 morning, they're getting 19 reversals of blue-orange per second. So when you look at this

00:18:45.080 light, it looks like a barely flashing white light, but it's reversals of orange and blue,

00:18:50.620 orange and red and blue, and it's happening very fast.

00:18:53.720 What does the person looking at it perceive?

00:18:55.820 Well, I've used one of these. It just looks like a flickering light. And of course, there's always the

00:19:00.740 potential of a placebo effect.

00:19:02.040 Well, that's what I was going to say. Is there a way to control for that by having something that

00:19:06.320 looks the same to the user, but of course, is not producing the same photo effect?

00:19:12.420 Yeah, well, they've done that with the 10,000 luxe sad lamps, which most people use to try and

00:19:18.240 induce sunrise simulation in their home. But keep in mind that sunrise gives you this comparison

00:19:24.040 of short and long wavelength light. Just a bright 10,000 luxe light triggers one of the options,

00:19:30.280 but it won't set your circadian clock. So most of the sad lamps that are out there

00:19:34.660 are activating only one of the mechanisms in these cells that's relevant and not the one that's most

00:19:41.060 relevant. So I'm excited about what 2.0 is doing. I think that, and again, I have no relation to them,

00:19:46.020 except that I know the biologists who did the work that provide the mechanistic logic for that

00:19:50.140 engineering. I still think we're in the really early days of this stuff. What should be done

00:19:56.280 is to have this stuff built into your laptop. It should be built into your phone, and hopefully

00:20:00.800 it will be. Now, I mentioned this color contrast thing in sunrise and sunset. I mentioned the bright

00:20:06.820 light throughout the day, but there's a fourth light stimulus that turns out to be really important,

00:20:11.440 and this will provide the segue into the paper. It turns out that dark exposure at night,

00:20:16.800 independent of light exposure during the day, is important for mental health outcomes.

00:20:21.280 Most people think dark exposure. How do I think about that?

00:20:23.580 Absence of light exposure? It's the absence of light, but what this paper really drives home

00:20:29.360 is that people who make it a point to get dark exposure at night, aka the absence of light at

00:20:34.900 night, actually benefit even if they're not getting enough sunlight during the day. And this is especially

00:20:39.340 true for people with certain mental health issues. So I don't think we can overstate the value of

00:20:45.260 accurately timed light exposure to the eyes in the context of mental health. I think there's so much

00:20:51.880 data by now. I will say, however, that some people seem more resilient to these light effects than

00:20:58.220 others, meaning some people also don't suffer from jet lag too much. Some people can stay up late,

00:21:03.760 get a lot of bright light exposure in the middle of the night, and during the day,

00:21:06.620 they've got their sunglasses on all day, and they're in a great mood all the time.

00:21:09.760 Other people are more susceptible to these sorts of things, and we don't know whether or not

00:21:13.140 polymorphisms underlie that. I personally am very sensitive to sunlight in the sense that if I don't get

00:21:19.880 enough sunlight, I don't feel well after a couple of days, but I'm less sensitive to light exposure

00:21:25.340 at night, for instance. But I think it is perhaps, this is a big statement, but it is perhaps the most

00:21:32.080 fundamental environmental stimulus for levels of arousal and alertness, which correlate with all

00:21:38.820 sorts of neuromodulator and hormone outputs. None of this should come as any surprise. I will mention one

00:21:44.840 last thing. There was a study published, gosh, over 10 years ago now from Chuck Zeiser's lab at

00:21:49.040 Harvard Medical School. It's a phenomenal lab exploring circadian human health behavior. He's

00:21:55.720 just considered, no pun, a luminary in the field. But there was a study that was in error where they

00:22:02.600 had published in Science Magazine that light shone behind the knee could shift circadian rhythms,

00:22:07.780 and that paper was retracted. And a lot of people don't know that it was retracted. Light exposure to

00:22:12.360 the eyes is what's relevant here. And as far as we know, the color of one's eyes, darkness or

00:22:17.140 lightness of one's eyes bears no relevance on their sensitivity to these types of mechanisms.

00:22:22.480 So one question, one comment. The question again is going back to the morning, evening,

00:22:26.180 light. And I spend a lot of time looking at those types of skies, for example, just because of the

00:22:31.800 nature of my hobbies, because I'm always doing archery in the morning and rucking in the afternoon.

00:22:35.660 So it's not uncommon that I'm seeing both of those. How relevant is it that the sun be above

00:22:41.540 the horizon? So for example, it begins to get light about in 30 minutes before sunrise. So if sun rises

00:22:49.540 at 730, first light is seven, and then 715 to 730 is actually quite bright. I mean, you can see

00:22:57.280 anything and everything. And the same is true at sunset. So does that 30 minutes when sun is beneath

00:23:03.000 the horizon constitute part of that 10 minutes? It does. In an ideal circumstance, you'd get

00:23:08.480 outside and see the sunrise every day, and you'd see the sunset every day, even on cloudy days.

00:23:13.800 Some people like myself wake up before the sun comes up. And I get this question all the time.

00:23:18.460 Well, in the absence of powers to make the sunrise faster, which I'm not aware anyone has,

00:23:22.880 certainly not me. I think the best thing to do is simply to turn on as many bright lights as you

00:23:27.040 can indoors to trigger that melanopsin mechanism. If you want to be awake, if you want to stay asleep,

00:23:32.920 or sleepy, then keep them dim, and then get outside once the sun is starting to come out.

00:23:37.840 Some people wake up after the sun has risen, in which case get what you can. And some people wake

00:23:43.720 up 10 a.m. or noon, in which case you can still get the bright light exposure, but you won't shift

00:23:48.800 your circadian clock. Now, in the evening, especially in the winter months, it's important to look west

00:23:55.520 and try and get some sunlight in your eyes in the evening. If you've ever gone into the clinic,

00:24:00.060 for instance, at two o'clock in the afternoon, after lunch, and then in the winter, and then come

00:24:05.760 out and it's dark when you're walking to your car, it's an eerie feeling. That sort of eerie feeling

00:24:11.880 may correlate with the fact that you missed a signal. Your brain is trying to orient your brain

00:24:16.220 and body in time. And that's what all of this is. It's trying to orient in time. And again,

00:24:20.800 some people are more susceptible to that than others. Some people might like that feeling of,

00:24:24.580 oh, I went in when it was bright and I come out when it's dark. But the vast majority of people

00:24:29.580 feel better when they're getting this morning and evening sunlight exposure. And this is especially

00:24:34.460 important in kids. This is one of the things that this paper points out and there are good data that

00:24:39.080 people are spending approximately 90% of their time indoors nowadays, daytime time indoors. And those

00:24:47.140 indoor environments are simply not bright enough. You think, oh, there's all these bright lights. And

00:24:51.380 some people are putting blue blockers on in the middle of the day, which is the worst thing you

00:24:55.680 could possibly do. If you're going to wear blue blockers, and I don't think they're necessary,

00:24:59.100 but if you're going to wear them, you'd want to wear them at night. And in the evening,

00:25:02.560 you don't need to wear blue blockers. You just simply should dim the lights and ideally have

00:25:07.180 lights that are set a little bit lower in your environment, which the Scandinavians have been doing 1.00

00:25:11.860 for a long time. So kill the overhead lights and don't obsess about bright light exposure in the

00:25:18.200 middle of the night. In fact, for a long time, I and some other people were saying, oh, you know,

00:25:22.340 even just a brief flash of light in the middle of the night can quash your melatonin. That's true.

00:25:27.180 But the other time in which you're in this quote unquote circadian dead zone is in the middle of

00:25:32.560 the night. You can't shift your circadian clock in the middle of the night. But all of this gets down

00:25:37.320 to interweaving rhythms of light sensitivity, temperature, hormone output, cortisol. I mean,

00:25:45.100 there's a whole landscape of circadian biology. This paper, which was published in a new journal,

00:25:50.460 I'm really excited about called nature mental health. This journal was just launched recently

00:25:54.900 is entitled day and night light exposure are associated with psychiatric disorders and

00:25:59.840 objective light study in more than 85,000 people. Now I have to say that I think the title of this

00:26:05.800 paper is terrible. Sorry, folks at nature mental health, because if one just read the title,

00:26:10.680 it sounds like day and night light exposure are associated with psychiatric disorders,

00:26:15.260 right? If this were a newspaper headline, you'd be like, oh my goodness, well, what are you supposed

00:26:18.360 to do, right? But that's not the conclusion. The conclusion is that getting a lot of sunlight

00:26:24.920 exposure during the day and getting a lot of dark exposure at night is immensely beneficial for

00:26:31.240 psychiatric health in a number of ways. Now, I'm not one to bring up another paper unannounced,

00:26:36.440 but I will say that this paper built off a previous study entitled time spent in outdoor light is

00:26:42.180 associated with mood, sleep, and circadian rhythm related outcomes. And that was a cross-sectional

00:26:47.500 longitudinal study in 400,000 biobank participants. So this UK biobank is an incredibly valuable resource.

00:26:55.300 And there are now multiple studies establishing that one's pattern of light exposure is extremely

00:27:00.600 important. Now, the previous study in 400,000 participants basically nailed home the idea that

00:27:06.860 the more time you spend outdoors, the better is your mood, the better is your sleep, the better is

00:27:13.720 the rhythmicity of your sleep-wake cycles, and on and on. Something that I think, even though people

00:27:18.980 say we've known that for thousands of years, needed scientific substantiation. This new study

00:27:24.780 essentially looked at the relative contributions of daytime light exposure and nighttime dark

00:27:31.520 exposure. And they did that on a background looking in particular people who had major depressive

00:27:36.340 disorder, generalized anxiety, PTSD, bipolar disorder. Here's the basic takeaway. I'll quote them

00:27:43.000 here. I'll tell you my interpretation. Here I'm quoting, avoiding night at light and seeking light during

00:27:48.160 the day. I love that word seeking. Maybe a simple and effective non-pharmacologic means for broadly

00:27:54.720 improving mental health. So that's a pretty bold statement. And I love that they say seeking

00:27:59.100 because it implies that people aren't reflexively getting the light exposure that they need, that

00:28:03.720 this needs to be a practice, much like zone two cardio or resistance training. So what did they

00:28:08.360 do in this study? So basically they gathered up a hundred thousand people or so. It eventually

00:28:14.540 was pared down to about 86,000 participants because some just didn't qualify or didn't report

00:28:21.160 their data back. They equipped them with accelerometers on their wrists and those wrist devices also could

00:28:28.420 measure ambient light. Now that's not a perfect tool because what you'd love to do is measure

00:28:32.580 ambient light at the level of the eyes. By the way, will somebody design an eyeglass frame that

00:28:37.980 changes color when you've gotten sufficient light from sunlight during the day? And then at night

00:28:42.960 is a different color. And then if you're getting too much light exposure, we'll go to a different

00:28:46.760 color frame. This has to be possible so that you don't have to wonder if you got enough light during

00:28:51.240 the day. And of course, if it's at the level of the eyes, then you know, that's what's landing at

00:28:55.680 the eyes. So I was going to ask you about that. Do these wrist based devices potentially get covered

00:29:01.040 by clothing and some turned over, you have your sleeves down. I have my sleeves. Yeah. They had it

00:29:05.420 on the outside of the sleeve, but they asked that people just keep it on their dominant hand.

00:29:09.000 It's not perfect, but in some ways it's kind of nice that it's not perfect. We could turn that

00:29:13.600 disadvantage into advantage by thinking when the person is out and about, they're not often looking

00:29:18.600 right at the sun. If you're talking to a colleague under an overhang, for instance. So it's not

00:29:24.520 perfect. It's directionally right. Okay. And then they had two hypotheses, two primary hypotheses. One

00:29:30.460 that greater light exposure in the day is associated with lower risk for psychiatric disorders. And two

00:29:34.560 second hypotheses, greater light exposure at night is associated with higher risk for psychiatric

00:29:39.700 disorders and poor mood. This is oh so relevant for the way we live now. People on screens and

00:29:44.860 tablets in the middle of the night. Then they collected information about how much light exposure

00:29:49.040 people were getting as well as their sleep and their activity and so on. I should mention this was

00:29:54.100 done in males and females. It was a slightly older cohort than one is used to seeing people in their

00:29:59.060 fifties and sixties. They had psychiatric diagnosis information and then they divided people into

00:30:05.020 essentially two groups, but they had a lower. So a Q1 and a Q2, a lower quartile. That meant people

00:30:10.880 that were getting less daytime light as opposed to the third and fourth quartile, more daytime light.

00:30:17.000 They also had a nighttime light exposure evaluation and they had people with the low Q1 and Q2. So

00:30:24.300 these people are getting less nighttime light versus Q3, Q4, more nighttime light. Nicely,

00:30:30.900 they also looked at sleep duration and they looked at photo period, meaning how long the days were for

00:30:37.700 those individuals, how active they were, like 10 hours a day, 14 hours a day, because the more active

00:30:42.420 you are, the more opportunity for light exposure you have during the day or night, for instance. Okay.

00:30:49.060 So they had, I would say, fairly complete data sets then, and I'm just going to hit the top contour of

00:30:55.560 what they did. And sorry, sleep duration, sleep efficiency, et cetera, was determined off the accelerometer.

00:31:00.900 That's right, as well as self-report. Not ideal, right? You'd love for people to be wearing a whoop band

00:31:05.760 or a ring or something of that sort, but this was initiated some time ago. So they either didn't have

00:31:11.780 access to that technology or for whatever reason, didn't select it. Then what they did is they have

00:31:18.260 information on who has major depressive disorder, who has PTSD, generalized anxiety, bipolar, psychosis,

00:31:24.680 et cetera. And then they ran three models. You can tell me what you think about the power of these

00:31:29.960 models, but you know, as somebody who thinks about the mechanistic aspect of all of this a lot, but not

00:31:35.580 somebody who's ever run this type of study, I'd be really curious. Model one examined the unadjusted

00:31:41.600 association between day and nighttime light exposure and psychiatric outcomes. So just basically asking,

00:31:47.700 is there a relationship between how much light you get during the day and how much light you get at

00:31:51.960 night and how bad your depression is or anxiety is, et cetera. Looking at just a standard ratio of

00:31:59.480 the probability that you have a certain symptom or set of symptoms versus you don't given a certain

00:32:06.460 amount of light exposure. Model two adjusted for the age of the person, their sex and ethnicity

00:32:13.000 and photo period. So they looked at how long the days were in that given person's region of the

00:32:18.660 world. These people were all in the UK or were they around? They were all in the UK as far as I

00:32:22.980 know. And then model three adjusted for employment. So employed versus unemployed, which if you think

00:32:28.540 about it is pretty important, like you say, well, an unemployed person has a lot more time to control

00:32:32.180 these variables, but an employed person who's doing shift work does not. They incorporated

00:32:37.560 information about employed versus unemployed physical activity, which turns out to be very

00:32:43.520 important. And then things like shift work, et cetera. We can say very safely the outcomes with

00:32:49.980 each of these models, the results were very similar. So we don't want to discard the differences

00:32:56.620 between those models entirely. But in my read is in every figure of the paper, it doesn't seem like

00:33:02.060 model one, two, or three differ from one another in terms of total outcome.

00:33:06.100 That's an unusual aspect of this paper. So these adjustments are very standard. This is a classic

00:33:12.360 tool that's used in most epidemiology because you don't have randomization. So once randomization is

00:33:18.380 out the window, so for example, the paper I'm going to present is based on an RCT, there will be no

00:33:22.960 models. It's just here are the data. Yeah. Here they're asking people, what do you do? Report back

00:33:27.840 to us. We're going to measure your light exposure, but no one was assigned to any groups or swap,

00:33:32.040 whatever quote unquote controls are there. They were really not there. It's just comparisons

00:33:35.900 between groups. So what is interesting to me is that it's exactly as you said, and we'll make all

00:33:41.940 these figures available in addition to the papers, but it's very unusual that there's no difference

00:33:46.880 between the unadjusted and the adjusted models. And as you say, there's probably two places out of

00:33:55.120 30 when you look at all the different quartile comparisons where you might creep from statistically

00:34:02.480 significant just out of it or just into it. But yeah, you could simplify this figure two completely

00:34:08.720 by just showing one of the models and you would be getting 95% of the information. I think in one way

00:34:14.960 that suggests that there's less dependency on those variables. Of course, it still doesn't address

00:34:23.840 probably the greatest question I have here, which I'm sure we'll get to at some point as you continue.

00:34:28.960 I'm very curious what that question is. I'll suppress my curiosity for the moment.

00:34:33.820 So if we look at figure two of this paper, and I realize a lot of people are listening and they're

00:34:37.200 not able to look at this, although we have posted the figures on the YouTube version of this,

00:34:41.880 just want to make clear what's going on just for those that are listening. Essentially what they're

00:34:46.880 looking at is what they call the odds ratio, which is the probability of something happening in one

00:34:53.020 group divided by the probability of something happening in another group. I guess by way of example,

00:34:57.220 would be if you were going to look at the odds ratio of the probability of somebody getting lung

00:35:01.520 cancer if they smoke versus probability of somebody getting lung cancer if they don't smoke.

00:35:06.060 So odds ratios and hazard ratios are often confused. They're very similar and odds ratios generally refer

00:35:12.800 to a lifetime exposure, whereas a hazard ratio is defined over a specific period of time. But the math

00:35:19.260 is still effectively the same. And using the example you gave, if you took the odds ratio of death,

00:35:26.580 so let's talk all-cause mortality for a smoker versus a non-smoker, and the answer were 1.78.

00:35:31.600 I'm making that up, but that's directionally correct. 1.78 as an odds ratio means there's a

00:35:37.160 78% chance greater of the outcome of interest, in this case, death by any cause in the affected

00:35:44.580 group, which would be the smokers. So odds ratio of two is 100%, and odds ratio of three is 200%. So

00:35:51.380 the math is take the number, subtract one, and that's the percent.

00:35:55.100 Thank you for that.

00:35:56.280 Right. So figure two of this paper is one of the key take-homes. Essentially look at the odds ratio

00:36:02.260 of people who are in the, let's just look at the nighttime light exposure.

00:36:08.060 And just remind me, Andrew, and everybody else watching, every one of these is showing second,

00:36:13.020 third, fourth as your x-axis, meaning they're all being compared to the first quartile.

00:36:18.240 That's right.

00:36:18.660 And the first quartile is lowest light exposure or highest light exposure.

00:36:23.900 That's right. Lowest.

00:36:24.340 Well-

00:36:24.620 With the differentiate between day and night.

00:36:26.040 That's right. That's right.

00:36:27.160 Restate it.

00:36:28.040 Sure. So if we look at what is your risk of a psychiatric challenge, broadly speaking,

00:36:34.920 well, panel A is major depressive disorder. If you are in the second quartile, third quartile,

00:36:41.040 or fourth quartile of nighttime light exposure. So second being the least amount of nighttime light

00:36:46.740 exposure, third being more nighttime light exposure, and fourth, the most nighttime light exposure

00:36:52.780 relative to the first quartile. 1.00

00:36:55.000 This is just a stupid thing. Like if I were doing this figure, if you were doing this in a lecture, 0.99

00:37:00.260 you know what you would do to make it so easy? You would draw arrows on it that say increasing

00:37:04.500 light exposure at night, decreasing light exposure in the day. It's the same information. It just

00:37:09.800 makes it easier for the reader to understand. Maybe the teaching point I think is for people

00:37:14.060 when they review articles, like don't be afraid to do that and just-

00:37:18.100 Oh, I've got scribble all over this.

00:37:19.600 Yeah, exactly. So it's like, I draw the arrow. That's increasing light,

00:37:22.580 that's decreasing light. And that's how I can pay attention to what's actually happening.

00:37:25.660 Right. And I'm actually in touch with the editorial staff at Nature Mental Health,

00:37:29.380 although they don't know that I'm covering this paper until after this comes out. You know,

00:37:32.400 I think one thing that scientific journals really, really need to do is start making the

00:37:37.260 readability of the articles better for non-experts. I mean, chances are, if you can't understand a

00:37:43.800 graph, and this is true for everybody, chances are there's a problem with the way it's presented.

00:37:49.780 Put it on them, but then of course, try and parse it because rarely, if ever, is it all spelled out

00:37:55.140 clearly. But anyway, that's what we're trying to do here. So yeah, the way I would have done is say

00:37:58.660 second quartile is low amounts of nighttime light exposure and define what that is. Third quartile

00:38:03.960 is more light exposure and then fourth maximum amount of light exposure at night. And basically

00:38:08.180 what you see is that the probability of having worse major depressive symptoms linearly increases

00:38:16.480 as you go from the second to third to fourth quartile. So more nighttime light exposure, worse

00:38:22.340 for you. And there's a dose response, if you will, of the effect. Now we can march through or describe

00:38:31.060 figure two pretty quickly by saying the same thing is true. Now we're just talking about nighttime light

00:38:37.080 exposure for generalized anxiety disorder. So that's panel C. Bipolar disorder, although the difference

00:38:43.380 between the second and third quartile and bipolar disorder isn't as dramatic. Once you get up to

00:38:47.280 the fourth quartile, bipolar symptoms get much worse when people are getting nighttime light

00:38:53.260 exposure. I really want to emphasize that point because they go on in the discussion of this paper

00:38:58.540 to reemphasize that point several times. In fact, they say that while light exposure during the day,

00:39:04.760 of course, we will go into the data, is beneficial for mental health. For people with bipolar disorder,

00:39:10.780 it seems that light exposure at night is especially problematic, independent of how much sunlight

00:39:16.460 they're getting during the day. The person with bipolar disorder who's struggling with either a manic

00:39:20.760 or a depressive episode, who's making a point to get sunlight during the day, who's also getting

00:39:25.520 light exposure at night, is making their symptoms worse. And keep in mind, they couldn't completely

00:39:30.180 control this, but this is largely independent of things like sleep duration. So that doesn't necessarily

00:39:36.940 mean that the person's sleeping less, although in a manic episode, presumably they are. It's independent

00:39:41.680 of exercise. It's independent of a bunch of other things because any logical person will hear this

00:39:46.580 and say, okay, well, they gain more light at night because they're doing a bunch of other things,

00:39:49.440 but it's largely independent of those other things. Likewise, the symptomology of PTSD gets far worse

00:39:55.660 with increasing light exposure at night. Self-harm really takes a leap from being fairly,

00:40:02.340 I don't want to say minimal, at the second and third quartile. So low and let's say medium,

00:40:07.100 I'm taking some liberties here, but low and medium amounts of artificial light exposure at night

00:40:10.940 than for people who get quite a lot of nighttime light exposure. Self-harm goes up, probability of

00:40:17.280 psychotic episodes goes up or psychotic symptoms. Now, what's nice about the data is that the exact

00:40:22.980 inverse is basically true for daytime light exposure. Although not across the board, we can

00:40:28.280 generally say that for major depressive disorder, generalized anxiety, bipolar symptoms, there it's a

00:40:34.260 little more scattered, PTSD and self-harm, the more daytime light exposure, ideally from sunlight,

00:40:40.720 because that's actually what's being measured in most cases. We can talk about how we know that

00:40:45.020 is going to approximately linearly drop the probability or the severity of these symptoms.

00:40:52.860 And we could just explain again that the odds ratios now seem to be going down. So an odds ratio

00:40:57.540 of 0.7 now refers to a 30% reduction in the variable of interest here.

00:41:03.680 Exactly. Now the psychosis panel F, which focuses on psychosis, I think is also worth mentioning

00:41:09.180 in a bit more detail. There's a fairly dramatic reduction in psychotic symptoms as one gets more

00:41:14.960 daytime light exposure, independent of nighttime light exposure. There's a well-known phenomenon called

00:41:21.140 ICU psychosis, which is that people come into the hospital for a broken leg or a car accident,

00:41:27.280 maybe they were getting surgery from Peter back when for something totally independent.

00:41:31.820 They're housed in the hospital. And as anyone who's ever been in a hospital as a patient or visitor

00:41:35.960 knows, the lighting environment, the hospital is absolutely dreadful for health. Just dreadful.

00:41:41.420 People often complain about the food in the cafeteria as being unhealthy. That's often not always true,

00:41:47.020 not always true, but the lighting environments in hospitals is absolutely counter to health.

00:41:52.280 Especially in the intensive care unit. I think the intensive care unit at Hopkins, the main one

00:41:57.280 main SICU didn't have windows. People who go into the hospital with a brain injury or

00:42:02.780 with a stroke or something, I get contacted all the time, even though I'm not a clinician. What should

00:42:06.680 I do for my kid, my parent? I always say, get them near a window and start to the best of your

00:42:11.320 abilities, controlling their sleep-wake cycle. Now, oftentimes there's nurses coming in and taking 0.97

00:42:15.940 blood tests and measuring pulses in the middle of the night. That's disruptive. There's bright light,

00:42:20.140 not just blue light. That's disruptive. It's noisy. That's disruptive. ICU psychosis is when

00:42:25.440 non-psychotic individuals start having psychotic episodes in the hospital because of nighttime light

00:42:31.240 exposure and in some cases, lack of daytime sunlight. We can say that with some degree of confidence

00:42:37.560 because when those people go home, even though sometimes their symptoms for what brought them

00:42:41.700 to the hospital in the first place get worse, their psychosis goes away and it's independent of

00:42:47.320 medication. So let's just be really direct. There is a possibility that we are all socially jet-lagged,

00:42:56.040 that we are all disrupting these mood regulation systems by not getting enough daytime light and by

00:43:02.180 getting too much nighttime light. If we want to look at just some of the bullet points of the takeaways,

00:43:06.960 and then Peter, thank you. You highlighted a few of these. Can we just go back to this figure too

00:43:11.220 for a second? Oh yeah, sure. There's a handful of things that really jump out. I had a feeling Peter was

00:43:14.200 going to want to dig in the data more. Let's do it. Let's do it. And again, I normally wouldn't make

00:43:18.020 so much hay out of this except for the fact that they're so tight. There are a few that really stand

00:43:23.300 out. And again, I love this figure. I would have labeled it a little differently to make it

00:43:27.320 completely user-friendly, but nevertheless, the increasing light at night and the impact on

00:43:34.220 depression, let me be really technical in what I say, and the relationship or correlation to

00:43:39.120 depression is very strong. The relationship to light and self-harm in the upper quartile,

00:43:46.640 so when you take those 25% of people with the most nighttime light, that relationship to self-harm

00:43:52.900 is interesting and completely uncoupled from the other 75%. That's interesting. 0.85

00:43:57.720 By uncoupled, you mean that at the lower levels of light exposure at night, you're not seeing an

00:44:01.680 increase in self-harm. Not whatsoever.

00:44:03.500 And then once you get to that fourth quartile-

00:44:05.720 It's a big step.

00:44:06.380 It's like a 30% greater risk of self-harm.

00:44:09.580 That's right. Yeah. So it's totally flat. The first, second, third quartile,

00:44:12.920 no different. And then fourth, big jump. And then the inverse relationship. As light increases during

00:44:18.500 the daytime, you see this reduction in self-harm. Interesting. The PTSD relationship based on

00:44:24.980 nighttime light and the psychosis relationship based on daytime light. Those are the ones that really

00:44:31.180 jumped out to me. I think anxiety, relatively less impressive here. And bipolar disorder didn't seem

00:44:39.060 as strong as well. So I think those are the big ones that jumped out to me.

00:44:43.960 Yeah, I agree. There's a bit more scatter on generalized anxiety and the degree of significant

00:44:48.000 change is not as robust. In other words, getting a lot of daytime light, ideally from sunlight,

00:44:53.420 is not necessarily going to reduce your levels of anxiety. Getting a lot of nighttime light exposure

00:44:58.860 is not increasing nighttime anxiety that much. Although 20% is not nothing for nighttime light

00:45:05.760 exposure. But yeah, the psychosis, major depression, and self-harm, they leap out.

00:45:11.780 Maybe we can just drill a little bit deeper on major depression. And basically when you go from

00:45:15.280 the second to third quartile of nighttime light exposure, so more nighttime light exposure,

00:45:19.060 you basically go from no significant increase to almost a 20% increase. And then as you get

00:45:25.320 up to the fourth quartile, so the most nighttime light exposure at about 25% increase in major

00:45:33.260 depressive symptoms. And that's no joke. I think that we don't have the data right here,

00:45:38.000 but if we were to look at standard SSRI treatment for major depression, people debate this pretty

00:45:43.140 actively, but light is a very potent stimulus. And the timing of light is critical because the inverse

00:45:49.140 is also true. As you get to the fourth quartile of daytime light exposure,

00:45:52.120 you get about a 20% reduction in major depressive disorder.

00:45:56.860 Yep. What I like about a study like this is that it puts the error bars so easy to see on the data.

00:46:03.720 And why is that interesting? Well, there's a belief that bigger is always better in sample size.

00:46:10.340 And we often talk about that through the lens of power analysis. So how many subjects do we need

00:46:16.020 to reach a conclusion that is powered to this level? That's true. But what I don't think gets

00:46:22.300 discussed as often is the opposite of that, which is what if you overpower a study? In other words,

00:46:28.500 what if the power analysis says to have a level of power at 90%, you need a thousand subjects and you

00:46:35.060 say, great, we're going to do 10,000 subjects. Well, you're clearly powered for it, but you might be

00:46:40.160 overpowered and people might say, well, why would that be a bad thing? It could be a bad thing

00:46:44.240 because it means you are very likely to reach statistical significance in things that might

00:46:49.720 not be actually significant. And so one thing about this study that is just a quick and dirty way to

00:46:56.400 tell that it's probably not overpowered is that you have varying lengths of error bars. And what that

00:47:04.120 tells me is that, and again, this is not like a formal statistical analysis. It's just kind of like a

00:47:10.520 back of the envelope statistical analysis. If you look, for example, at self-harm in the top quartile,

00:47:15.620 you actually have pretty big error bars. In fact, all the self-harm have sort of slightly bigger error

00:47:19.700 bars. And yet when you look at, for example, the depression, even though the error bars aren't all

00:47:23.920 the same size, they're tighter. In fact, when you look at the relationship between depression and

00:47:27.700 daytime light, the error bars are really, really small. So that just gives me confidence that there

00:47:33.380 is variability in this, which paradoxically you kind of want to see, because it tells me that

00:47:38.140 this wasn't just done. There was, I think you said 8,000 subjects were in this.

00:47:43.020 86,000.

00:47:43.740 86,000. Sorry. Yeah. You realize that it wasn't that, oh, this should have been done with a 10th

00:47:48.500 of that or a half of that. And we're picking up signal that is statistically relevant, but

00:47:53.060 clinically irrelevant.

00:47:54.560 Thanks for that point. I didn't pay attention to that. I mean, I paid attention to the error

00:47:59.460 bars, but I didn't know that. So thank you. I'm learning too. I suppose for people that are

00:48:04.260 listening, we can just give them a sense of what the error bar ranges are. For self-harm,

00:48:08.700 you know, they're running as much as 20% either side of the mean, the average. And for major

00:48:14.080 depression, it looks like it's more like, if that, maybe more like five. Yeah. I see what

00:48:18.680 you're saying. So when you get a very large sample size, you're going to have some outliers

00:48:24.520 in there and you can mask those outliers just by having so many data points.

00:48:29.900 Because these error bars directly tell you whether or not you're statistically significant.

00:48:34.120 So what's really nice about this type of graph, and you see these in, there's going to be a graph

00:48:39.620 in my paper where you see the same analysis. They're always drawing the 95% confidence interval

00:48:45.180 on the data point. And if the 95% confidence interval does not touch the line of unity, which

00:48:52.960 in this case is the Hod's ratio of 1.0 or the x-axis, then you know it's statistically significant

00:48:58.120 to the confidence interval they've defined, which is almost assuredly 95%. Sometimes they'll make it

00:49:02.880 tighter at 99. And so that's why you can just look right at these and go, oh, look, in depression,

00:49:08.140 the second quartile didn't reach statistical significance because the error bars are touching

00:49:12.640 the line, just as the case for the second and third quartile for self-harm. But when you look at

00:49:18.860 the fourth quartile, you can see that the lower tip of the error bars isn't anywhere near unity.

00:49:23.900 And so we know without having to look up the p-value that it's smaller than either 0.05

00:49:29.520 or 0.1, however they've defined it. And it's really amazing when you see these overpowered

00:49:34.480 studies, which are easier to do epidemiologically, where the p-value ends up being microscopic.

00:49:40.360 They can drive their p-values down to anything low because sample size can be infinite, but

00:49:44.880 you can see that it's just, the error bar is just skimming above the unity line, but it's so,

00:49:51.360 so, so tight. Interesting. One thing that I hope people are taking away from this study is that

00:49:57.920 imagine you're somebody who has a very sensitive circadian mood system. Well, that would mean you

00:50:06.240 need less daytime light exposure to feel good or less bad, but it also means that you might need

00:50:14.080 very little light at night in order to negatively impact your mood systems. And in fact, they make

00:50:22.260 this argument in the discussion as an interesting point. Again, what I like about the study is that

00:50:27.520 they've separated day and nighttime light exposure. It turns out that many of the drugs that are used

00:50:33.100 to treat bipolar disorder are effective, perhaps in part because they reduce the sensitivity of the

00:50:39.520 light sensing circadian apparati. Now that's interesting, right? If you think about this, okay, so these

00:50:45.840 are drugs that can ameliorate some of the symptoms of bipolar, perhaps in part by reducing the extent to

00:50:51.460 which nighttime light exposure can exacerbate bipolar symptoms. Conversely, there's evidence that people

00:50:57.600 who take certain antidepressants may suppress the ability for daytime light to positively impact the mood

00:51:05.100 systems of the brain. Now, of course, we don't want people halting their medication on the basis of that

00:51:09.900 statement alone, please don't talk to your psychiatrist. But if we know one thing for sure, it's that if you want

00:51:16.180 a significant outcome and a paper, as a scientist, give a drug, any drug, and look at the amount of rapid eye

00:51:25.940 movement, sleep, or the circadian cycle, pretty much any drug alters a circadian rhythm, for better or worse. If we start

00:51:33.060 to think about which medications might adjust our overall sensitivity to light, sometimes this could

00:51:37.760 be a good thing. You think less sensitivity to light. Well, for people who have bipolar disorder, the amount

00:51:42.580 of daytime light exposure isn't that important for their overall mood regulation, but the amount of

00:51:47.280 nighttime light exposure really is. In other words, darkness for eight hours every night should be

00:51:52.200 viewed, in my opinion, as a treatment for bipolar disorder, not the only treatment. But it's also clear

00:51:58.080 that we should all be avoiding really bright, extensive, really bright nighttime light exposure. I mean, if

00:52:04.080 anything, my takeaway from this study is that darkness at night is the fourth key light stimulus. A couple of

00:52:10.620 things, very bright moonlight, very bright candlelight is probably only like, gosh, three to 50 lux. When you go

00:52:20.780 outside on a brightly lit full moon night, I encourage people to download this free app. I have no relationship to it

00:52:26.960 called light meter. It gives you a pretty good read of what the lux are in that environment. By the way,

00:52:31.760 a lot of people don't realize this. They think you just tap the button and then it tells you how many

00:52:35.180 lux. You hold it down. It's kind of fun. You can scan around the room and see how many lux are on

00:52:39.520 average coming from that location or outside. Go out on a really bright, moonlit night.

00:52:44.520 We should have a full moon tonight.

00:52:46.060 Yeah. Let's do it. You're not going to get above 100 lux.

00:52:48.800 That's incredible.

00:52:49.680 You're sitting at a candlelight dinner with your spouse or with friends, and it's clearly bright enough to

00:52:54.420 see them. Put that lux meter right up, not too close to the flame, 50 to 200 lux. Maybe 400 lux.

00:53:03.280 I had an interesting experience a couple of months ago on an elk hunt where it was a full moon,

00:53:08.200 which actually makes the hunting not so great. But it was the first time I've ever noticed my shadow

00:53:15.240 in relation to the moon. That's how bright it seemed the light was.

00:53:19.540 This is Halloween appropriate. We're recording this close to Halloween.

00:53:22.340 Super interesting to think it could be that dim.

00:53:25.580 Campfire, firelight. You think, okay, gathering around a campfire, then okay,

00:53:29.840 everyone's circadian rhythm must have been disrupted for ages before the development of

00:53:33.540 electricity. No. Those campfires are extremely bright, but they're not that bright compared

00:53:39.020 to a very densely overcast day.

00:53:41.820 And what is your phone if you don't use any sort of light mitigating tech on it?

00:53:46.980 Well, distance matters.

00:53:48.880 At the distance we're holding it?

00:53:50.080 Yeah. So with all the wavelengths cranked up, there is a nice feature intrinsic to the phone

00:53:55.620 where you can eliminate the blues at night or this kind of thing. But if you crank it up to maximum

00:53:59.340 light intensity, probably something like 500 to 1000 lux. Now, keep in mind though, it's additive.

00:54:05.640 So it's over time. So lux is a measure of, I think it relates back to candelas is the amount of light

00:54:13.220 shown. And I think it's like the one meter away and there's a squaring and a falling off of distance.

00:54:18.080 We can look it up. These are old school measurements converted to lux. But keep in mind that if you're

00:54:22.540 looking at your phone or tablet at 800 lux or 500 lux in the evening, you do that for two hours,

00:54:28.240 where you're summing quite a lot of photons. Now it is true. I do want to be fair to the biology

00:54:33.680 and it'd be dishonest to say anything different. We've hammered on people about not shifting their

00:54:39.000 circadian rhythm with light at night, but we know that the middle of the day and the middle of the

00:54:42.740 night are circadian dead zones. You can't shift your circadian rhythm that well in the middle of

00:54:47.600 the day, in the middle of the night, but you can provide a wake-up signal for your body and brain.

00:54:52.280 It's really that sunrise and sunset that are critical. That's why I said there are four

00:54:56.000 things. See sunrise or sun rising. You don't need to see across the horizon. Sunset, bright light

00:55:01.620 during the day, minimize light exposure at night. You don't need pitch black. In fact, pitch black

00:55:07.620 probably just increases the frequency of injury. You know, I get up in the middle of the night to use

00:55:11.020 the bathroom probably once. I think it's normal. I go back to sleep. If it were pitch black, I'd probably

00:55:16.540 injure myself. So just dim it down. Some people use red lights.

00:55:19.940 Our mutual friend. Yeah. Rick Rubin is, uh, can we tell a funny story about Rick?

00:55:24.120 Yeah, of course. Of course. You know this story, but just in case Rick's listening,

00:55:27.620 he'll appreciate this. Rick was here staying last summer. He's up in our guest house and he came

00:55:33.400 down after the first night and he was like unacceptable. You know what I'm talking about?

00:55:37.620 Unacceptable accommodations. What did he do? He removed all the lighting that existed in that

00:55:43.180 room and replaced it with red light bulbs, which I later used when I stayed here and then later stole

00:55:48.480 when I laughed. The teenage me, I took them. I took them. That's why Derek, when he stayed here,

00:55:55.020 Elaine or anyone else when he stayed here, Conti or anyone else didn't have those. I took them. I

00:55:59.300 love them. So funny. Jill is like, you know, Rick changed every light in the guest house to red.

00:56:05.840 No, I didn't know that, but I'm not surprised. Yeah. Well, in his place, he has mostly either no

00:56:11.740 lighting or red lighting. So during the day, it just goes by ambient light and then red light in the

00:56:16.240 evening or candlelight. And it's great. And you know, people hear red lights and they think they

00:56:20.860 have to buy these expensive red light units. That's not what we're talking about. You can

00:56:24.740 literally buy red party lights or just a red bulb. Some people say, well, can I just use a red film

00:56:29.940 or can I put a t-shirt over the lamp? I worry about people putting t-shirts over lamps because

00:56:33.520 of the fire hazard. But I'll be honest, I dim the lights in my home at night. When I travel,

00:56:38.680 sometimes I will bring one of the stolen from Rick Rubin red lights.

00:56:42.300 Rick Rubin stash. Here's something where I've sort of softened my tune. So I used to be kind

00:56:46.660 of a hard liner, no blue light in the evening guy. Everything was red light at night. As far as my

00:56:53.280 phone using flux on the computer, you know, whatever it was, I suspect that that matters somewhat,

00:56:59.700 but I think what matters more is the stimulation that may come from those things. And what I've

00:57:06.260 come to realize, at least in me, which means it probably is true in others as well. And at least

00:57:11.880 some others is that what I'm doing on my phone matters more than how bright my phone is. In other

00:57:20.220 words, if I've got the best blue light filter in the world on my phone, but I'm doom scrolling social

00:57:25.800 media and getting lit up on email, that's way worse for me than if I've got my phone on maximum light

00:57:34.440 and I'm watching YouTube videos of F1 cars and driving around having fun. It's a totally different

00:57:42.420 experience. So the context matters. And I think for that reason, I would want people to be mindful

00:57:48.000 of the whole picture going to bed under a period of intense duress brought on by something that's an

00:57:55.520 equally dangerous component to all of this. That's distinct from what we're talking about,

00:57:59.540 but I want people to be able to think of this in the context of everything.

00:58:02.840 It's a really important point. One thing I'll say is that if you're going to stay up

00:58:07.940 past your normal bedtime, if you're going to get a lot of light in your eyes,

00:58:11.560 I would hope that it would be for fun reasons and for reasons you enjoy. You should definitely

00:58:15.480 spend some nights out. You should definitely do some all-nighters studying if it's going to help

00:58:19.400 you get the grade that's permanent, right? I'd certainly have done all-nighters studying and grant

00:58:23.520 writing for years. There are going to be the inevitable all-nighters due to trip to the hospital or

00:58:29.420 you heard something on the news that really amped you up or you just simply can't sleep. That stuff

00:58:33.880 is going to happen. So I think the goal should be to minimize light exposure at night. And I think

00:58:38.480 what you just said is especially true because we don't know, for instance, people talk about the

00:58:43.720 negative impact of social media. Is it the fact that people are looking at this little box for so

00:58:48.140 many hours per day? Is it all the things they're not doing? Is it what they're looking at per se?

00:58:53.540 All of those things interact and are really important. We know based on studies from the Stanford Sleep Lab

00:58:58.800 that if you wake up in the middle of the night, looking at what time it is, can be very disruptive

00:59:04.220 to your ability to fall back asleep and to your sense the next day. It's a placebo effect, but it's

00:59:09.860 a powerful one of how tired you are the next day. They've done this where they wake people up in the

00:59:15.000 middle of the night and then they say it's 4 a.m. versus 2 a.m. versus 6 a.m. and people's perceived

00:59:20.860 levels of energy during the day in some ways correlate with how much sleep they think they got.

00:59:26.520 Likewise, and this is one of the concerns, potential concerns with sleep trackers.

00:59:31.400 Ali Crumman talked about this when she came on our podcast. If people see a poor sleep score,

00:59:36.360 they often feel worse than if they see a good sleep score. Now, of course, physiology matters. You

00:59:41.500 can't lie to yourself and say you got a great night's sleep simply by virtue of a sleep score. But

00:59:45.880 I worry more about the false, if it's a false negative, we don't want to put valence on this.

00:59:50.820 Seeing a bad sleep score and then deciding that you're going to have a terrible day.

00:59:53.740 You know, I think a bad sleep score is an indication that you might need to dial some

00:59:57.380 things in a bit better. Getting a great sleep score is an indication that you might be doing

01:00:01.700 a number of things right and start looking at these things as averages. Would you agree?

01:00:05.920 Yeah, completely. I don't think it's that different from CGM. I think that CGM is an amazing tool to

01:00:11.240 provide insight and you pretty much know the insights after a relatively short period of time.

01:00:15.800 30 days, maybe at the outside 90 for a person with a very complicated life and you know all you need

01:00:22.860 to know about how the inputs affect the output. Thereafter, if you choose to use it, it's a

01:00:28.500 behavioral tool. In other words, you're using this to build in a Hawthorne effect. I think the same is

01:00:33.420 largely true with sleep trackers. Most people have this profound sense of learning when they first

01:00:39.820 encounter one of these things. And it's again, you've heard it all a hundred times. Oh my God,

01:00:43.180 I can't believe what alcohol does to my sleep. Or caloric trackers. Exactly. Like I think

01:00:47.980 Lane Norton's app Carbon, I have no financial relationship to it. I use it. It's taught me,

01:00:54.440 wow, like I consume a lot of calories in the form of certain things at certain times of day. And

01:00:58.680 there's just a lot of good learning in that. But it's the act of tracking that helps you manage

01:01:03.120 it. And similarly, I think it's the act of knowing you're going to be looking at that score that

01:01:08.440 gamifies it, that kind of helps people do the right things. Oh, you know what? I'm not going to

01:01:12.300 have that drink tonight, or I'm not going to eat that snack before bed because I've now been

01:01:16.280 conditioned to see how that impacts score. That said, I think that recovery scores and things like

01:01:22.280 that are just notoriously poor at predicting performance. And I think there's a reason that

01:01:29.000 serious athletes would never use things like that. They would tend to rely on the more tried and true

01:01:34.120 methods of predicting behavior, such as heart rate, maybe heart rate variability, but morning resting

01:01:39.520 heart rate, probably more predictive than anything else. And then in workout things such as heart

01:01:44.400 rate, heart rate recovery, lactate threshold, things like that. So yeah, I agree. I think we have to,

01:01:49.460 and I say this as a guy who's generally perceived to be the most pro device guy in the world, people

01:01:54.880 would be surprised how sparingly I use things like that. I mean, I do some tracking, not as much as you.

01:02:02.220 I love things that seem to work the first time and every time in terms of our natural biology,

01:02:09.300 based on a couple of criteria, there's an established mechanism. It's been explored in

01:02:14.300 the context of pathology, like mental health disorders, as well as pro health in healthy

01:02:19.040 individuals, that it make really good sense at the level of kind of wellness. And let's just say

01:02:25.500 ancient health. You know, when you're talking about getting a lot of sunlight during the day,

01:02:29.200 a lot of people will say, well, of course, get outside and play, not getting too much light at

01:02:33.600 night. Of course, this is just good old quote unquote, good old fashioned advice. People spend

01:02:38.260 90% of their time indoors. Now their daytime environments are too dim. Their nighttime

01:02:43.800 environments are too bright. And this misleading aspect of artificial light that when you see a

01:02:51.080 bright bulb, you think I'm getting a lot of photons is part of the problem. And the fact that when

01:02:57.080 you're out on a overcast day and it, you know, you think there's sun quote unquote, isn't out,

01:03:01.720 well, it's hidden by cloud cover, but just think about how well you can navigate that environment

01:03:07.440 without a flashlight versus at night where you would require a flashlight. We evolved under this

01:03:14.180 traumatic difference in day, night availability of photons, independent of whether or not you can

01:03:21.100 see the sun. And it's just very clear that all the mechanisms in our brain and body that regulate mood

01:03:27.420 are just powerfully regulated by this stuff. So I've made it a point to really reduce the amount

01:03:32.280 of nighttime light that I'm getting, but I am less concerned about flipping on the light switch to use

01:03:37.420 the bathroom as I used to be. I used to think, oh, I'm like quashing all my melatonin. This is

01:03:41.680 terrible. I know I can't shift my circadian clock. Then I know that that light, yes, while it's bright,

01:03:46.880 if it's brief, I'm not going to worry about it too much. Would it be better to have a dim light on

01:03:51.800 as opposed to a bright light? Sure. But I'm not going to stress it in a hotel bathroom or something.

01:03:55.320 I'm not going to walk around, you know, shielding my eyes. People will sometimes ask me, by the way,

01:03:59.240 is it different to look at the phone directly versus if you tilt the phone away? Well, it absolutely

01:04:04.620 is. I mean, think about a flashlight shown on the ground in front of you, very few photons getting

01:04:09.440 in your eyes versus shown directly into your eyes. Think about ambient light from the sun going

01:04:14.140 everywhere versus looking in the general direction of the sun. So east in the morning,

01:04:18.240 west in the afternoon, of course, the directionality of the light matters. So I'm not saying it,

01:04:23.580 you know, that you need to like peek at your phone as if you're looking over the edge of a bowl or

01:04:28.720 something into it. But my friend, Samer Hattaru is head of the chronobiology unit at the National

01:04:33.840 Institutes of Mental Health. We used to room together at meetings. We stopped because he's a terrible

01:04:37.860 snorer. There were a few times when I considered suffocating him in the middle of the night,

01:04:41.500 since he was already suffocating himself. Now we just, we don't stay in the same rooms anymore.

01:04:46.340 We're no longer postdocs, but I caught him looking at his phone in the middle of the night

01:04:51.040 and he would tilt it away. Like he's holding a platter for those that are just listening and

01:04:55.280 kind of like looking over at the screen there. I'm like, what are you doing? This is ridiculous.

01:04:58.760 He said, I'm trying not to get so much light in my eyes. That's a little extreme, but I think it 0.98

01:05:02.080 illustrates the point, which is how much direct light exposure you get at night matters. How much

01:05:06.660 direct sunlight exposure you get, especially early morning, late afternoon,

01:05:10.940 and throughout the day, it really matters. Now remind me, Andrew, what is the wavelength

01:05:15.000 of sunlight? Great. So sunlight is going to include all visible, visible, which runs from how many

01:05:20.740 to what? Well, let's answer two questions there. This wrist sensor detected 470 nanometer to 650

01:05:27.780 nanometer light. So that's going to be blue and ultraviolet. Ultraviolet's kind of blue to orange.

01:05:34.340 Yeah. Blue to orange. That's what this was measuring. So red light is going to be more like 680.

01:05:39.180 Far red is getting out to 7720 and up. Upwards of that blue light is going to fall somewhere in the

01:05:45.560 low fours. Ultraviolet is getting down into the high threes and lower. And so these spectra of

01:05:52.080 light. So during the day, you know, midday light, you're getting what looks like white light. You'll

01:05:55.520 see, oh, the sky is blue and the sun is bright white light. It's not even yellow to your eye. And of

01:06:01.100 course, don't stare at it, especially in the middle of the day, you're getting all visible spectra. So

01:06:05.340 you're getting everything from UV all the way out to red light. It's just coming in at equal

01:06:09.500 intensities. So is that a potential limitation of this study in that it didn't have a sensor that

01:06:14.580 could pick up the full spectrum of light? Potentially. We don't think of humans as UV

01:06:20.500 capable. Like we can't perceive UV light. A ground squirrel, for instance, has UV sensors in its eyes.

01:06:27.060 Turns out, you know why they use this? It's crazy. You know, when the ground squirrels sit up

01:06:30.480 on their haunches, they're actually signaling one another. They rub urine on their belly and

01:06:34.860 it reflects UV. The New York Times, for some reason, has been running a series of articles

01:06:39.640 about naturally occurring fluorescence at night and all sorts of scorpions and monotremes like

01:06:46.020 the platypus. No one really knows the reason for these odd wavelength of light emissions for all

01:06:51.120 these animals. But, you know, we view things in the blue, violet, and up to red. And we're not pit

01:06:57.900 vipers. We can't see far red. But we can see lower than 470 nanometers. And we can see higher

01:07:03.840 than 650. Is there a technology reason why they had such a narrow band in these sensors? Is it not

01:07:09.860 possible that they could have used a wrist sensor that was wider? This study was initiated in 2013.

01:07:15.280 The tech was probably far worse than it is now. Again, I would love for somebody to design an eyeglass

01:07:21.380 where it's measuring how many photons you're getting across the day. I'm not a big fan of having

01:07:27.600 everything be amplified. So I would love it if the frame would just shift color across the morning.

01:07:32.440 Like you go outside on a cloudy day, you know, you wear these glasses. And by the way, it's fine to

01:07:36.560 wear eyeglasses or contacts for sunlight viewing for setting your circadian rhythm. People always

01:07:40.940 say, well, why is that okay when a window is not? Well, corrective lenses are actually focusing the

01:07:45.300 light onto your retina. The windows and windshields are scattering the light and filtering.

01:07:49.900 And how much are sunglasses filtering this out?

01:07:52.320 Too much. We can safely say way too much, probably causing a tenfold decrement in the total luxe count

01:08:00.240 that's landing on your retina. But of course, sunglasses are important driving into sun. And some

01:08:04.920 people have very sensitive eyes. I can't sit at a cafe with a bright, brightly reflective table in the

01:08:10.760 afternoon. I just squint like crazy. I can't do it. My dad, who's darker eyed and, you know, he's

01:08:15.340 South American descent. He can just sit there just fine. My mom, who's got light eyes like me and,

01:08:20.240 you know, we're like, oh, it's really tough. You just have a terrible time. People differ in their

01:08:25.160 light sensitivity. So there's one other macro question I have here, and it's not answerable

01:08:31.440 because without randomization, we can't know it. But it's the question of how much reverse causality

01:08:39.200 can exist in these observations. So again, these observations demonstrate very tight correlations,

01:08:46.300 very strong associations, especially in the five areas that we highlighted. But it's possible that

01:08:53.120 part of what we're seeing is reverse causality brought on by both the treatments, which you've

01:08:59.040 already kind of alluded to, and also the condition itself. Do you want to explain reverse causality

01:09:03.880 for people? And maybe could you mention for those that missed the Hawthorne effect?

01:09:08.040 The Hawthorne effect is an effect that is named after an observation of what took place in a factory

01:09:13.880 where they were actually studying worker productivity with light of all things. What it

01:09:18.520 refers to is the idea that people will change their behavior when they are observed. So if I said,

01:09:25.020 well, I really want to know what a day in the life is like for Andrew Huberman, I'm going to follow him

01:09:30.040 around for a day. It's very unlikely that his behavior that day will be exactly as it was if I wasn't

01:09:36.440 there. Which is why you probably will never see a day in the life of Andrew Huberman.

01:09:40.300 Although it's pretty scripted unless I'm traveling. It's morning sunlight, hydration,

01:09:45.180 and some cardio or weight training, and then a lot of time reading papers. It'd be the most boring

01:09:49.500 video in the world because it'd be mostly me reading and underlining things.

01:09:53.080 But it's why gamifying things can be beneficial, right? It's why a CGM can be beneficial because

01:10:00.820 it's sort of like somebody's watching you and you're going to modify what you eat in response to it,

01:10:05.280 or why tracking can really be an effective way to reduce input because there's a sense of being

01:10:11.700 monitored by doing that, especially if someone literally monitors it. In other words, you can

01:10:15.420 set up an accountability partner where your health coach or someone is actually seeing the data. So

01:10:20.460 that's what it is. Now, as far as reverse causality, when you look at variables, so let's just pick a

01:10:27.940 common one that's unrelated to this. So there's an association that more diet soda consumption is

01:10:34.660 associated with greater obesity. It's a bit paradoxical. Is that true? It is. Yeah, it's been

01:10:40.980 demonstrated in many series. The greater the consumption of diet soda, the greater the prevalence

01:10:46.840 of obesity. And that has been postulated by some to suggest that non-nutritive sweeteners,

01:10:53.780 such as aspartame or sucralose or things like that, are actually part of what's causing obesity.

01:10:59.800 And while there are probably some arguments you could make around the impact that those things

01:11:03.480 might have on the gut microbiome, and maybe there's some way and that's happening, it's also equally

01:11:08.020 likely, if not probably more likely, that there's reverse causality there. That a person who is obese

01:11:13.460 is therefore contemplating how much they're eating or thinking, hey, what's an easy way that I can

01:11:19.560 reduce calories? How about instead of drinking a Coke, I drink a diet Coke?

01:11:23.780 And so there, the causality which you would impute to mean the drink is causing the obesity,

01:11:30.720 it might be no, the obesity is causing the choice of drink. So here the question is,

01:11:36.000 how much of the effect we're seeing is a result of the condition that's being studied? How much of the

01:11:43.560 disruption in both day and night light exposure is the result of the depression? It's dysregulating

01:11:50.900 the sleep. Maybe they're sleeping more during the day and more awake at night because of depression.

01:11:56.060 Again, you can't know this. This is where epidemiology never allows us to determine this.

01:12:02.340 And sadly, these questions can only be answered through either direct randomization or Mendelian

01:12:07.900 randomization, which by the way, I was going to also ask you, do you know if anyone has examined this

01:12:12.660 from a Mendelian standpoint? That would be very interesting. I don't know enough about the

01:12:17.560 biology to know what SNPs would be studyable, but that would be interesting.

01:12:22.740 Yeah. What Peter is saying is, you know, if you knew something about the genomes of these people,

01:12:28.320 you would be in a great position to perhaps even link up like sensitivity genes with genes for

01:12:34.920 pathways involved in major depression, bipolar. Getting to this issue of reverse causality,

01:12:39.720 I mean, I think it's very straightforward to imagine that the person who's experiencing a

01:12:43.900 manic episode is going to be up for two weeks at a time, sadly, and getting a lot of nighttime light

01:12:50.780 exposure. Now, nighttime dark exposure as a treatment for bipolar is something that people

01:12:55.640 are starting to talk about. So making sure that those people are awake, that they're at least blue

01:12:59.860 blocking at night, reducing their online activities, but people with severe manic episodes have a hard

01:13:04.960 time regulating their own behavior, of course.

01:13:07.420 And it's not one or the other. Like, I don't want the question to come across to the listener

01:13:11.600 that it has to be one or the other. It's only A can cause B or B can cause A. No, it's actually a lot

01:13:18.700 of times these things feed off each other. Going back to the soda example, I actually think there's a

01:13:23.240 bit of both. I actually think there's a real clear body habitus dictates beverage choice, but I also am

01:13:30.320 starting to think that in susceptible individuals, non-nutritive sweeteners will alter the gut biome,

01:13:36.840 and that alters metabolism.

01:13:39.320 What about just hunger? I remember Lane telling me, I've seen at least one of the studies that

01:13:45.280 water is probably better for us than diet soda, but that for some people, diet soda is a great

01:13:51.800 tool for reducing caloric intake. I also know some individuals, not me, who drink diet soda. I drink

01:13:59.160 diet soda from time to time, mainly stevia sweetened sodas. But what I'm referring to here are people

01:14:04.060 besides myself who drink diet soda and it seems to stimulate their appetite. There's something

01:14:09.140 about the perception of sweet as driving hunger, whereas not eating or drinking anything with any

01:14:16.280 sweetness doesn't seem to. This is one of the things I wonder if it impacts why some people like

01:14:21.240 intermittent fasting, because for some people, I wonder if the perception of sweetness, even just the

01:14:27.700 smell of food we know can stimulate appetite. So you can imagine the perception of sweetness in the

01:14:31.700 mouth, even if there's no calories there. I don't think it necessarily makes people hypoglycemic,

01:14:36.460 but perhaps it makes them think about like sweet means food. For instance, for years,

01:14:41.560 I love the combination of a diet Coke and a slice of pizza whenever I was in New York,

01:14:46.540 ideally two slices of pizza. Now, every time I have a diet Coke, which isn't that often,

01:14:51.060 but I like diet Coke, especially with a little bit of lemon in it. I just think about a slice of cheese

01:14:56.080 or mushroom or pepperoni pizza. It's like, I want it. I crave it more. So there's a

01:15:00.080 paired association there that I think is real. And we know based on Dana Small's lab at Yale,

01:15:05.340 that there's this paired association between the sweetness from sucralose and that there's an

01:15:10.620 insulin response. They actually had to cease the study in kids because they were becoming

01:15:14.760 pre-diabetic, which unfortunately meant the study was never published. Have you talked to Dana on this

01:15:19.500 podcast? I really want to get her onto my podcast.

01:15:21.580 No, we wrote a premium newsletter on this several months ago. It's got to be like,

01:15:28.060 I don't know, 10 to 20,000 words on all things related to sugar substitutes.

01:15:33.400 Okay. I'll read that.

01:15:34.100 So yeah, folks who are interested in this topic, I would refer them to the premium newsletter on

01:15:38.340 sugar substitutes. I think it was our September edition. The short of it is the data are a little

01:15:43.700 bit noisy, but there is indeed some sweeteners in some studies do result in that phenomenon you

01:15:48.960 described, the cephalic insulin response. And I came away from the research that went into that,

01:15:54.320 which was Herculean effort on the part of the team, a little bit more confused than when I went

01:16:00.920 in, but being even more cautious around artificial sweeteners than I was going in. And not for the

01:16:08.120 reasons, I didn't find any evidence that these things are cancer causing. So that's the headline

01:16:12.920 stuff people worry about.

01:16:13.900 You have to ingest like 10 grams of it or something crazy like that.

01:16:17.320 I came away more confident that from a long-term safety perspective in terms of cancer and

01:16:23.200 catastrophic outcomes like that, that wasn't the issue. But I came away much more cautious

01:16:27.200 around these things can really be mucking around with both your brain chemistry and your gut

01:16:32.640 chemistry, which can pertain to your metabolism. And therefore my takeaway was buyer beware,

01:16:39.880 use limited amounts only.

01:16:41.800 The one, by the way, that still emerged to me as a reasonable one, it's the only one that I use,

01:16:46.820 and I've talked about a lot is xylitol, xylitol for chewing. So for gum and allulose as an

01:16:53.240 additive safer. You're saying, yes, those are basically the only two I will consume.

01:16:59.020 I'll drink a diet Coke every now and again, if I'm on a plane or something, this law that got

01:17:03.320 passed a few years ago, you couldn't bring liquids of your own into the airport and on the plane.

01:17:07.380 What a great scheme to get people to buy overpriced fluids in the airport. I mean,

01:17:13.940 there are more important issues in the world, but this one really gets me. But I drink things

01:17:18.420 with a little bit of stevia in it, the occasional diet Coke. I generally avoid sucralose. I don't

01:17:24.000 like the way it tastes. Monk fruit's too sweet, but maybe we'll do a podcast on that in the future.

01:17:28.420 Okay. So I think we can wrap this paper.

01:17:30.560 But tell me what you think about that point. You know more about this stuff than I do. But

01:17:34.800 if you had to just lay on your judgment, if it were a hundred to zero, you would say the light is

01:17:42.000 100% causal in the effects we're seeing. If it were zero to a hundred, you'd say, nope,

01:17:49.220 the behavior is 100% causal of the exposure to light. Again, you can't know it, but what does your

01:17:55.640 intuition tell you?

01:17:56.460 Okay. There's my intuition. And then there's my recognition of my own bias because I started

01:18:02.000 working on these circadian pathways originating in the eye back in 98 as a graduate student at

01:18:08.580 Berkeley. The cells, these melanopsin intrinsically sensitive retinal ganglia cells were discovered

01:18:12.880 in the early 2000s by a guy named Iggy Provencio, Dave Burson, Sam Rattar, Sachin Pant, and others.

01:18:18.900 And it was like one of the most important discoveries in all of biology, clearly. So I've been very

01:18:24.060 excited about these systems, but if I set that aside, so bias disclosure made, I think 65 to 75%

01:18:32.560 of the effects are likely due to light directly. Now it's impossible to tease those apart, as you

01:18:39.180 mentioned, but to play devil's advocate against myself, you could imagine that the depressed

01:18:44.240 individual is laying around indoors with the curtains drawn. They didn't sleep well the night

01:18:49.360 before, which gives you a photosensitivity that isn't pleasant. Like it sucks to have bright light 0.64

01:18:53.800 in your eyes first thing in the morning, especially if you didn't sleep well. And then they're, you

01:18:58.780 know, making their coffee in a dimly lit, what they think is brightly lit environment. And then they're

01:19:03.160 looking at their phone and the state of the world sucks and their state of their internal landscape 0.78

01:19:08.080 is rough. And maybe they're dealing with a pain or injury or something. And their likelihood of 0.54

01:19:14.880 getting outside is low. And when they do get outside, they're going to shuffle and up. So I

01:19:19.500 could see how the behaviors could really limit the amount of light exposure. And then evening rolls

01:19:23.840 around. They've been tired all day and a common symptom of depression, you fall asleep. And then

01:19:28.000 two or three in the morning, they're wide awake. What are you going to do at two or three when you're

01:19:31.600 wide awake, sit in the dark? No, you're going to get online. You're going to listen to things you

01:19:36.880 might have. I'm not recommending this, but an alcoholic drink in order to try and fall asleep. I mean,

01:19:41.500 this is the pattern. Shaking up that pattern is really what so much of my public health work

01:19:47.440 these days is about and trying to get people onto a more natural daylight, night, dark rhythm. But

01:19:52.800 yeah, it's impossible to tease apart. We do know this, and this is really serious. We know that in

01:19:58.240 almost every instance, almost every psychopathology report of suicide in the weeks, but especially in

01:20:05.500 the days preceding suicide, that person's circadian rhythms looked almost inverted from their normal

01:20:12.420 patterns. And that's true of non-bipolar individuals as well. Circadian disruption and

01:20:19.600 disruption in psychiatric health are inextricable. Conversely, positive mood and affect and circadian

01:20:26.540 behavior seem very correlated. I mean, I think it's clear that if you want to become an early riser,

01:20:32.800 get light in your eyes and get activity in your body early in the day, you entrain to those rhythms

01:20:38.340 so that you start to anticipate that morning workout. You start to anticipate the morning

01:20:41.780 sunlight. Just one more scientific point. We know that when you view bright sunlight in the morning

01:20:47.200 or just sunlight that's illuminating your environment, as you said, you don't even have

01:20:50.120 to see the sun itself, that there's a 50, 5, 0% increase in the amplitude of the morning cortisol

01:20:56.840 spike, which is a good thing because the amplitude of the morning cortisol spike is inversely

01:21:02.200 related to the amplitude of the evening cortisol spike and high evening cortisol is associated with

01:21:06.680 middle of the night waking and on and on. So, you know, I'm very bullish on these mechanisms.

01:21:13.080 I also love that they're so deeply woven into our evolutionary history, you know, that we share with

01:21:18.000 single cell organisms. It's so wild. But of course, there's going to be a bidirectionality there and

01:21:23.920 it's impossible to see where one thing starts and the other one stops.

01:21:27.060 Here's my take, Andrew. First of all, I actually, with far less authority than you,

01:21:32.760 agree with your assessment and might even be a little bit more bullish, might even put it at 80-20.

01:21:38.180 And here I'll give you my explanations, which stem more from my fastidious battles with

01:21:45.420 epidemiology in general. Because so much of the world that I live in still has to rely on

01:21:50.940 epidemiologic data. And so how do you make sense of it? The truth of it is most of it is really

01:21:56.420 pretty bad. I tend to find myself looking at the Austin Bradford Hill criteria all the time.

01:22:02.960 And for folks who don't know, he was a statistician who basically proposed a set of criteria.

01:22:09.020 I believe there are eight of them. And I can't believe I don't know every one of them off by

01:22:12.200 heart. I certainly used to. But the more of these criteria that are met within your correlations,

01:22:18.520 the more likelihood that you will find causality. So when I think of your data here,

01:22:23.860 the data in this paper, I'll tell you what makes these correlations seem to have causality

01:22:30.480 within them in the direction that's being proposed. Look at the dose effect. So dose effect

01:22:36.420 matters. And this is done in quartiles. And that's a very elegant thing. If they just did it as

01:22:41.260 on off, it would be harder.

01:22:43.240 High low.

01:22:43.820 That's right. But the fact that they did it in quartiles allows you to see that every example

01:22:47.860 in figure two, I don't believe there is an exception to this. There's only one exception

01:22:52.040 to what I'm about to say. Sorry, two out of like God knows how many. They're all monotonically

01:22:57.240 increasing and decreasing. In other words, the dose effect is always present. Another thing is

01:23:02.920 biologic plausibility. You've spoken at length about that today. So in other words, sometimes you have

01:23:08.740 to look at epidemiology and ask, is there a biologic explanation? And here there is. You've added

01:23:13.540 another one, which is evolutionary conservation to the biologic plausibility. Then you can talk

01:23:18.260 about animal models or experiments in humans over short durations that generally support these

01:23:24.340 findings. And so those are just a couple of the Bradford Hill criteria that lead to my belief

01:23:31.280 that, yeah, there's reverse causality here, but it's not the full explanation and that more

01:23:37.120 of the explanation is probably the direction that's being proposed. At the end of the day, like

01:23:41.380 what's the purpose of the discussion? The purpose of the discussion is if you are under the influence

01:23:46.840 of any of these psychiatric conditions, in addition to the treatments you're doing now, what else can

01:23:52.660 you do? And to me, the takeaway is follow these light behaviors. That's a relatively low lift. When you

01:23:59.440 consider some of the things, like I'm over here asking people to do zone two for three hours a week

01:24:03.920 and VO2 max workouts and all this other stuff. And I think all those things matter for mental health

01:24:09.160 as much as physical health, but this strikes me as on the spectrum of low asks, if it's only even 30%

01:24:18.320 causality, 70% reverse causality, like I'll take those. I would still instate that.

01:24:23.700 Yeah. And it's taking your coffee on the balcony. It's people will often say, well, how do you do this

01:24:28.220 with kids? The kids should be doing it too. You know, it means popping your sunglasses off. It means getting

01:24:33.760 out for just a few minutes. And the fact that it's additive, that these photon counting mechanisms, they sum.

01:24:39.640 This paper also says, and I should have stated this earlier, if you missed your daytime light

01:24:43.720 ration, get your nighttime dark ration. They are independent and additive. I mean, that's a really

01:24:50.340 something, but of course, ideally you get both, but I appreciate your take on it. Thanks for your expertise in

01:24:56.180 parsing epidemiology. I look at fewer studies of that sort, but I learned from you. And that's one

01:25:01.660 of the reasons I love doing these journal clubs is I learn. So along those lines, tell us about the

01:25:07.160 paper you selected. I'm really eager to learn more. Well, I wanted to pick a paper that was

01:25:14.100 interesting as a paper. This paper I think is interesting in that it is the landmark study of a

01:25:21.260 class of drugs. But in the same way that you kind of picked a paper that I think has a much broader

01:25:26.740 overarching importance, the reason I picked this paper, which is from the New England Journal of

01:25:32.600 Medicine, it's about 13 years old, is because it is kind of the landmark study in a class of drugs that

01:25:39.920 I believe are the most relevant class of drugs we've seen so far in cancer therapy. And even though the

01:25:47.980 net effect of these drugs has only served to reduce mortality by maybe 8 to 10 percent, which is not a

01:25:56.560 huge amount, it's the manner in which they've done it that gives me great hope for the future, even if

01:26:03.240 it's through other means. So I'll take a step back before we go into the paper for, again, just the

01:26:08.100 context and background. So the human immune system is kind of a remarkable thing. It's hard when you're

01:26:15.920 trying to imagine what's the most amazing part of the human system. And maybe it's my bias as well,

01:26:21.200 because just as you spent your time in the light system and the photosensing system, I spent my time

01:26:25.900 in the immunology world. But it is remarkable to me how our immune systems evolved. And they have this

01:26:32.620 really brutal task, which is how can they be tuned to detect any foreign pathogen that is harmful

01:26:44.560 without knowing a priori what that could be? So in other words, how can you tune a system to be so

01:26:52.320 aggressive that it can eradicate any virus or bacteria billions of years into the future without

01:26:58.620 knowing what it's going to be? But at the same time, it has to be so forgiving of the self that it

01:27:05.740 doesn't turn around and attack the self. It's remarkable. And of course, we can always think of

01:27:10.960 the exceptions. There are things called autoimmune conditions. So clearly the system fails and the

01:27:15.900 immune system turns around and attacks the self. If you see a person with vitiligo, I have a little

01:27:20.800 bit of vitiligo on my back, a couple of spots. Clearly the immune system is attacking something

01:27:26.580 there and destroying some of the pigment. I didn't realize vitiligo was autoimmune.

01:27:30.900 Yeah. There are lots of more serious autoimmune conditions. Of course, you know, somebody that has

01:27:34.980 lupus or immune system can be attacking the kidney. The immune system can be attacking any

01:27:38.900 autoimmune conditions can be deadly, but fortunately they are very rare. And for the most part, this

01:27:44.340 immune system works remarkably well. So how does it work and why is it that cancer seems to evade it

01:27:53.680 virtually all of the time? This is the question. Let's first of all, talk about how it works.

01:27:59.240 And then when I tell you how it works, you'll say, that sounds amazing. Clearly it should be able to

01:28:05.040 destroy cancer. I'm going to simplify it by only talking about one system, which is how T cells

01:28:11.420 recognize and get activated, how T cells recognize antigens. So we have something called an antigen.

01:28:18.900 So an antigen is an antibody generating peptide. So it's a protein, almost always a protein. They can

01:28:26.700 be carbohydrates, but they're almost always proteins and they're very, very small peptides. Like we're

01:28:31.060 talking as little as nine amino acids, maybe up to 20 amino acids. So teeny tiny little peptides,

01:28:38.120 but it's amazing that in such a short peptide, the body can recognize if that's Andrew or not Andrew.

01:28:46.540 We talk about proteins in kilodaltons. We're talking about proteins in terms of thousands of amino acids

01:28:52.980 that make up every protein in your body. And yet if it samples a protein and sees that, Hey, this little

01:28:59.380 nine, 10, 15 peptide amino acid is not part of you. I know it's bad. And therefore I'm going to generate

01:29:08.040 an immune response to it. So we have what are called antigen presenting cells. You have cells that go

01:29:15.120 around sampling peptides and they will on these things called MHC class receptors, bring the peptide

01:29:24.000 up to the surface and serve it up to the T cell. There are two types of these. There's MHC class one

01:29:30.200 and MHC class two. This is major histocompatibility complex. That's correct. We refer to them that way

01:29:37.920 because of the context in which they were discovered, which was for organ rejection.

01:29:42.360 So not surprisingly, when you need to put a kidney into another person, if that kidney is deemed foreign,

01:29:49.780 it will not last long. And the early days of organ transplantation were rife with immediate

01:29:54.780 rejections. The immediates are the ABO incompatibilities, but the sort of next layer of

01:30:00.380 incompatibility was MHC incompatibility, which would lead to within weeks, the organ is gone as opposed to

01:30:05.680 within hours. So you have these two classes of MHC. You have class one and class two. Class one is what we

01:30:12.780 call endogenous. So this is basically what happens when a protein or an antigen is coming from inside

01:30:21.440 the cell. So let's consider the flu. So if you get the flu, the influenza virus infects the respiratory

01:30:28.700 epithelium of your larynx. And that virus, as folks listening might remember from our days of talking

01:30:35.940 about COVID, viruses can't replicate on their own. What they do is they hijack the replication

01:30:41.760 machinery of the host, and they use that either to insert their RNA or DNA to replicate. And in the

01:30:48.620 process, proteins are being made. Well, those proteins are the proteins of the virus, not of us.

01:30:53.900 So some of those peptides get launched onto these MHC class one gloves. Basically the glove comes up to

01:31:01.060 the surface and a T cell comes along. And in the case of MHC class one, it's a CD8 T cell. These are

01:31:08.620 what are called the killer T cells, right? And so this cell comes along and with its T cell receptor,

01:31:14.960 the T cell receptor meets the MHC class one receptor with the antigen in it. And if that's a lock,

01:31:22.380 it realizes that's my target. And it begins to replicate and proliferate and target those. And that

01:31:29.460 creates the immune response. And by the way, that's how it works when you vaccinate somebody. You're

01:31:33.580 basically pre-building that thing up. So would this fall under the adaptive immune response or the

01:31:39.120 innate immune response? So this is adaptive. Innate is just these pure antibody response on the B cell

01:31:44.240 side. I won't get into that for the purpose of this discussion. The other example is MHC class two,

01:31:51.040 and that's also part of the adaptive system or the innate system, which is more what we call the

01:31:57.260 exogenous form. So these are peptides that are usually coming from outside the cell.

01:32:01.880 So we're going to focus more on the MHC class one, because this is peptides that come from inside

01:32:07.360 the cell. Okay. So just keep in the back of your mind, if a foreign protein gets presented from inside

01:32:13.360 a cell to outside a cell, the T cells recognize that and they will mount a foreign response. And by the

01:32:18.740 way, that's why we basically can beat any virus. If you consider how many viruses are around us,

01:32:25.000 the fact that we almost never die from a viral infection is a remarkable achievement of how well

01:32:31.340 this immune system works. Constantly combating these viruses. Constantly. And by the way,

01:32:35.880 we don't really have very effective antiviral agents. It's not like antibiotics. Like we have

01:32:40.520 antibiotics up the wazoo. We're way better at fighting viruses than bacteria. I've always wondered

01:32:46.280 about this. To what extent is our ability to ward off viruses on a day-to-day basis as an adult,

01:32:52.280 reliant on us having been exposed to that virus during development. Like as I walk around today,

01:32:58.320 maybe I'll be exposed to a hundred thousand different viruses. Would you say that half of

01:33:03.080 those, I have already got antibodies too, because I was exposed to them at some prior portion of my

01:33:07.220 life? Yeah. Hard room to quantify. And the other ones, I'm just building up antibodies. Like I was on

01:33:11.600 a plane last night, someone was coughing. So I was hiding and I had COVID a little while ago. So I wasn't

01:33:16.200 too worried about that. And I feel great today, but I just assume that on that plane, I'm in a swamp

01:33:23.580 of viruses, no matter what. And that most of them I've already been exposed to since I was a little

01:33:29.740 kid. So I've got all the antibodies and they're just fighting it back, binding up those viruses and

01:33:33.940 destroying them. Yeah. I think it's part that. And I also think it's part of them that our body can

01:33:38.320 destroy without mounting much of an immune response. So therefore your immune system is doing

01:33:42.480 the work yet. It's not mounting a systemic inflammatory response that you're not sensing.

01:33:46.820 So is it also a physical trapping in, you know, in my nasal epithelium?

01:33:50.760 Yeah. You have huge barriers, right? So the skin, the hairs in your nose, all of these things are

01:33:56.420 huge barriers, but assuming that still a bunch of them are getting in, at least the respiratory ones,

01:34:01.460 that's the other thing to keep in mind, right? There were certain viruses that are totally useless

01:34:04.740 floating around the air. The viruses that most people are really afraid of hep C, hep B, HIV. Well,

01:34:10.800 if they're sitting on a table or floating around the air, they're of no threat to you. They have to

01:34:15.100 be transmitted through the barrier. But again, some of these viruses you're going to defeat without

01:34:20.360 an enormous response. And then some of them, why is influenza, quote unquote, such a bad virus?

01:34:26.320 Whereas the common respiratory cold kind of sidelines you for a day. It's the immune response

01:34:31.940 that you're feeling. The bigger the immune response to the virus, the more you're feeling that. You feel

01:34:37.620 your immune system going crazy. The interleukins that are spiking, the third spacing that occurs

01:34:44.080 to get more and more of the immune cells there, the spike of your temperature as your body basically

01:34:48.840 tries to cook the virus. All of that stuff is your body.

01:34:51.840 The fatigue.

01:34:52.760 Yeah. Yeah. You're being drained and all this happening. So one more point I'll mention just

01:34:57.100 to close the loop on the autoimmunity. How is it that we learn not to attack ourselves? That's

01:35:01.980 something called thymic selection that occurs in infancy. So you and I have a no good for

01:35:08.740 nothing tiny little thymus that would be, it's almost impossible to see these things. You know,

01:35:13.120 when we used to operate on people, the thymus is barely visible in an adult, in a healthy adult

01:35:18.480 outside of thymic tumors. And a child, the thymus is quite large. And the purpose of the thymus

01:35:23.160 is to educate T cells and basically show the T cells what self is. And any T cell that doesn't

01:35:31.760 immediately recognize it gets killed. It's a really clever system where we basically teach you

01:35:38.260 to recognize self at a very early age. And if you can't do that, you're weeded out. And then

01:35:44.180 the thymus involutes thereafter because it's sort of served its purpose.

01:35:47.560 Okay. Now let's talk about cancer. So what do we know about cancer? So we know that, again,

01:35:53.700 cancer is a genetic disease in the sense that every cancer has genetic mutations.

01:35:59.660 Most of those mutations are somatic, which means most of those mutations are mutations that occur

01:36:06.660 during the course of our life. They're not germline mutations.

01:36:10.000 The germline being the eggs and sperm, right? So it's all other cells. And I love that you pointed out

01:36:16.360 that cancer can be genetic, but isn't necessarily inherited. People hear genetic and they think

01:36:21.640 inherited. Inherited is always genetic to some extent, but genetic isn't always inherited.

01:36:27.820 Yeah. So there are a handful of cancers that are derived from inherited mutations. So Lynch

01:36:35.140 syndrome is an example of that. Hereditary polyposis is an example of that, where you have a gene

01:36:43.000 that gets passed through the germline and that gene codes for a protein, like all genes do. And it's

01:36:49.520 either you have too much of a gene or too little of a gene. So it's either a gene that promotes cancer

01:36:53.920 and you have too much of that, or it's a gene that prevents cancer and you have too little of it or a

01:36:59.160 dysfunctional version of it, right? So BRCA is an example of that. BRCA is hereditary. BRCA codes for a

01:37:05.880 protein. And the women and men, but mostly the women that we think about who have a BRCA mutation,

01:37:11.780 that in some cases almost guarantees breast cancer, it's because of a defective copy. So it's like

01:37:18.600 they don't get the protein that they need to protect them from breast cancer. So what do we know? Well,

01:37:23.500 we know that, and this is probably one of the most remarkable things I've ever learned, and it still

01:37:31.400 blows my mind every time. Well, actually, before I get to that point, I want to make another point.

01:37:35.520 Okay. So cancer, our cells become cancerous, but they're clearly hijacked because they have these

01:37:41.500 mutations. And as a result of these mutations, they make proteins that allow cancers to behave

01:37:47.780 differently. And cancers behave differently from non-cancers in two very critical ways.

01:37:54.260 The first way is that they do not respond to cell cycle signaling. So if you cut your skin,

01:38:00.560 it heals, but how does it know to heal just right and not to keep growing and growing and growing and

01:38:06.840 growing and growing? Well, it knows that because there are cell cycle signals that tell it time

01:38:11.220 to grow, time to stop. Believe it or not, this is an extreme example. If you donated to me half of your

01:38:16.840 liver, which I know you would. Absolutely. I'd give you more than half of my liver. If it meant that we

01:38:22.200 could keep doing these journal clubs, right? Yeah, yeah, yeah. Within months, you would regenerate a full

01:38:28.340 liver. Isn't that amazing? That's so wild. It's like a salamander. You cut off a salamander limb

01:38:32.520 and please don't do that experiment because other people are doing it anyway. And it grows back.

01:38:36.980 And it knows how much to grow back. When the cell is perfectly functioning, it knows how much to grow.

01:38:43.560 Well, cancer loses that ability. That is one of the hallmarks of cancer. It just keeps growing.

01:38:48.700 It doesn't grow faster, by the way. That's a misnomer. People think cancers grow faster than

01:38:52.420 non-cancers. There's no real evidence that that's the case. They just don't stop growing.

01:38:55.920 The second property of cancer is the capacity to leave the site of origin, go someplace else and

01:39:04.520 take up residence. So that's metastasis. That's the metastasis component. So if you think about it

01:39:08.620 for a minute, a cell that never stops replicating and has the capacity to up and leave and move and

01:39:15.480 take up residence is clearly different from the cell itself. So if I have a cell of colonic epithelium,

01:39:21.320 the cell that lines the inside of my colon, clearly got a set of proteins in it. But if all of a sudden

01:39:26.240 that thing can grow, grow, grow, grow, grow, not stop, not stop, not listen to the signal, and then

01:39:32.320 somehow wind its way into the liver and just keep growing and growing and growing, it must have

01:39:36.600 different proteins. So the question then becomes, why does cancer even exist? How has our immune system

01:39:43.880 not figured out a way to just silence this and eradicate it the way it does to virtually every

01:39:50.140 virus you encounter? And to me, this is one of the most interesting questions in all of biology,

01:39:54.900 and it really comes down to how clever cancer is, unfortunately, how evolutionarily clever it is.

01:40:02.460 It basically does a lot of things to trick the immune system. So it has its own secretory factors

01:40:10.440 that tamp down the immune system. It grows in an environment because of its nature. So one of

01:40:17.800 the things that's long understood about cancer is it's heavily glycolytic. And when something is

01:40:23.180 heavily glycolytic, it's going glucose to pyruvate to lactate nonstop. There are lots of reasons for

01:40:29.460 that. I think there's more than one. What does that afford it? Is that afforded a migratory

01:40:34.280 potential? No, so it's super interesting. So that's the effect that what I just described is called the

01:40:37.700 Warburg effect. And when Warburg proposed this, which God was probably in the 1920s, it was before

01:40:45.840 World War I, before World War II, he proposed it. He thought the mitochondria of cancer cells were

01:40:51.620 defective. So he proposed that the cancer cells mitochondria don't work. Hence, they have to

01:40:57.520 undergo glycolysis. They can't undergo aerobic metabolism. We now know that that's not the case.

01:41:03.180 So we now know that the Warburg effect or the Warburg effect, if I'll refer to him correctly by

01:41:08.140 his name, almost assuredly does not have to do with defective mitochondria. Others have proposed

01:41:12.900 several mechanisms. I think there's probably more than one thing going on. So a paper that came out

01:41:17.100 in 2009, very influential paper by a guy named Matt Vander Heiden, Craig Thompson, and Lou Cantley

01:41:23.780 proposed that the reason that cancer cells do the Warburg effect is that they're not optimizing for

01:41:30.200 energy. They're optimizing for cellular building blocks. And if you do the mass balance, it completely

01:41:34.500 makes sense. Dividing cells need building blocks more than energy. And glycolysis, while very

01:41:41.640 inefficient for generating ATP, is much more efficient at generating substrate to make more cells.

01:41:46.860 But another proposed mechanism is exactly at this one. Glycolysis lowers the surrounding pH

01:41:52.100 because of lactate. Lactate attracts hydrogen, pH goes down. And guess what that does to the immune

01:41:56.760 system? Detracts the immune system. So it's also a way to hide from the immune system. 0.90

01:42:02.540 Like a pH cloaking, leveraging pH to cloak the signal that the immune system would otherwise see.

01:42:08.340 Yep. And then when you layer on top of that, that it knows how to secrete things like IL-10,

01:42:12.960 TGF-beta, all of these other secretory factors that also inhibit the immune system. Basically,

01:42:19.140 it's figured out a way to kind of hide itself from the immune system.

01:42:21.680 The way you describe it, cancer sounds like a virus.

01:42:25.180 Yes.

01:42:25.520 It sounds a lot like a virus. And that leads me to ask,

01:42:28.220 are there any examples of contagious cancers? I recall seeing some studies about these little

01:42:33.340 critters down in Australia, Tasmanian devils, that they would scratch each other and fight,

01:42:38.840 as Tasmanian devils do. They're actually quite cute. And they would get cancers and tumors growing

01:42:43.520 on their faces. It was like a literal physical interaction that could transmit cancer from one

01:42:48.740 animal to the next. So it's less that there are viruses that cause cancer. So in that sense,

01:42:54.960 you could argue, yes, there are contagious cancers.

01:42:58.020 Well, HPV.

01:42:59.060 Sure. Yeah. HPV, hep B, hep C. But there are even cancers like cutaneous cancers that arise from viruses.

01:43:06.560 But I don't know if that's quite the same as what you're saying.

01:43:09.900 What you're saying is an important point. We don't want to go down the rabbit hole of the HPV,

01:43:13.780 but right, that's increasing susceptibility to cervical cancer. Now there's a vaccine against

01:43:18.740 HPV, right? There wasn't when we were in college, as we all knew, there was no vaccine. But direct

01:43:23.920 transmission of cancers from one organism to the next, more rare.

01:43:28.260 Yes. So now, a moment ago, I said there's this really incredible thing about cancer that blows my

01:43:34.300 mind and about our immune system, which is that at least 80% of solid organ tumors, and we're going

01:43:41.120 to mostly talk about solid organ tumors because that's where the field of oncology has made very

01:43:46.500 little progress. So if you go back 50 years, where has oncology made huge progress? It's made great

01:43:51.940 progress in blood tumors, leukemias, and some kinds of lymphomas. In fact, there's two kinds of

01:43:58.860 lymphomas where the progress has been remarkable. One has been in Hodgkin's lymphoma, and the other

01:44:04.440 has also been in immunotherapy, has been in a type of B-cell lymphoma, where that B-cell demonstrates

01:44:10.240 or presents something called a CD19 receptor. So in B-cell lymphomas with CD19, there's a very unique

01:44:17.240 niche immunotherapy, we won't talk about that today, called CAR-T therapy that has got rid of

01:44:21.820 those guys. And then leukemias have also been pretty good. But in solid organ tumors, there have

01:44:27.880 been only two real breakthroughs in the last 50 years. One has been the therapy for a certain type

01:44:35.140 of testicular cancer, and it's really just a chemotherapy cocktail that has been found to work

01:44:39.480 really well. And the other has been in this really rare kind of gastric cancer called the GI stromal

01:44:44.500 tumor, which happens to result from one mutation in a kinase pathway. And there's one drug that can now

01:44:50.980 target that, and it works. It's kind of amazing. Cures that cancer. Cures that. What I'm talking about

01:44:56.200 are the cancers that kill virtually everybody else. When you sort of line up, what are the big causes of

01:45:02.780 cancer death? Let's start at the top. It's lung. It's then breast and prostate in men and women. 0.60

01:45:09.600 It's colorectal. It's pancreas. Those are the big five. More than 50% of cancer deaths in Americans

01:45:15.160 come from those five. These are what we call the solid epithelial tumors. And you can march down the

01:45:20.160 list, and most cancers that most people are thinking of are those cancers. Well, here's the thing. More than

01:45:24.200 80% of those cancers have antigens that are recognized by the host's immune system. I will state it

01:45:31.440 again because it is so profound. 80% at least of those cancers actually generate an antigen, meaning

01:45:39.820 a little peptide in that cell gets presented to the T cell and it is recognizable. And now the question

01:45:49.200 is, why is that not sufficient to induce remission? And the short answer is there are not enough T cells

01:45:59.060 that are able to act and or they are being sufficiently inhibited from acting, which gets me to the point

01:46:06.120 of this paper. One of the ways in which the body inhibits the immune system, which we should remind

01:46:13.900 ourselves is an important thing, right? Is something called the checkpoint inhibitor. Okay. So go back to

01:46:20.760 that idea that I talked about before. You have an antigen presenting cell. It brings up an MHC receptor

01:46:27.960 with a peptide on it, and there is a T cell that is coming. And I actually brought a diagram, which

01:46:33.760 I'm going to link to this. I don't want to make this too complicated, but I really think that this

01:46:38.480 figure is helpful to understand how these drugs work. So the MHC receptor with the peptide is sitting

01:46:44.300 there and it binds to the T cell receptor on the T cell, but there is another receptor on the T cell,

01:46:51.060 a CTLA-4 receptor. And that binds to a receptor that I won't bother naming now. The names don't

01:46:59.440 matter. But there's another receptor on the antigen presenting cell that binds to that. And that acts

01:47:05.840 as the brakes in the reaction. So CTLA-4, which is on the T cell, binds to another CD receptor on the

01:47:15.800 antigen presenting cell. And it says, tamp down the response. And the reason for that is we want to

01:47:23.480 keep our immune system in check. This basically is a way of asking the immune system. Because remember,

01:47:27.660 when the immune system sees that antigen, it wants to go nuts. It wants to start replicating and

01:47:33.280 killing. This is a CD8 T cell. It is a targeted killer T cell. The checkpoint says, let's double check 0.64

01:47:40.580 that. Let's be sure. Let's tamp down the response. And as a result of that, a thought experiment emerged,

01:47:47.260 which was, what if we block CTLA-4? What if we block the checkpoint? Could we unleash the immune

01:47:55.140 system a little bit more? And I will say this, at the time it was proposed, it seemed a bit far-fetched.

01:48:03.780 Because of the complexity of the immune system, it seemed a little far-fetched that simply blocking

01:48:09.600 the checkpoint would have any effect. It's also worth noting that prior to this, one immunotherapy

01:48:17.360 had found some efficacy, which was trying the exact opposite strategy. Rather than blocking the

01:48:24.220 inhibitor, it was throwing more accelerant at the fire, which was giving something called interleukin-2.

01:48:30.700 So interleukin-2 is, for lack of a better word, candy and fuel for T cells. So the idea was,

01:48:38.340 if we have T cells that innately recognize a cancer antigen, can we just give high doses of interleukin-2

01:48:46.220 and have them undergo proliferation and response? And the answer turned out to be yes, but only in

01:48:53.460 two cancers, melanoma and kidney cancer, and only at very small levels. About 10% of the population

01:48:59.720 would respond to these things. Now, look, that's 10% of people who were going to be dead within six

01:49:04.360 months, because these are devastating cancers. And once they spread, there are no treatments that

01:49:09.800 have any efficacy whatsoever. In fact, I think median survival for metastatic melanoma at the

01:49:14.120 time was probably four months. So this was a very grim death sentence. But the idea now was,

01:49:20.380 what about doing the exact opposite approach? Instead of trying to throw more fire at the T cell,

01:49:26.960 what if we can take its brakes down? Instead of giving more gas, let's give less brakes.

01:49:31.380 And there were some phase one studies that demonstrated efficacy phase two. And the paper

01:49:35.700 I'm going to talk about today is the phase three study that compared the first version of these. So

01:49:42.460 the drug we're going to talk about today is an anti-CTLA-4 drug called ipililumab. There is another

01:49:49.280 drug out there that came along shortly thereafter that is an anti-PD-1 drug. So PD-1 turns out to be

01:49:57.740 another one of these checkpoints on T cells. And the Nobel Prize, by the way, I think it was 2018 or

01:50:05.660 2019 in medicine or physiology, was actually awarded to the two scientists who discovered

01:50:11.960 CTLA-4 and PD-1. So I believe this is the only Nobel Prize in medicine for immunotherapy. It's a very

01:50:18.920 big deal. So this study sought to compare the effect of anti-CTLA-4 to a placebo. And the placebo in this

01:50:30.520 case was not a real placebo. It was a peptide vaccine called GP-100 to ask the question, in patients with

01:50:39.260 metastatic melanoma, what would be the impact on median survival and overall survival? Let's talk a

01:50:48.900 So again, one of the funny things about this, I used to read these papers a lot, Andrew. These

01:50:54.080 used to be my bread and butter papers, reading these like it's my hobby. And I don't read them

01:50:58.700 that much anymore. So it was kind of amazing how long it took me to remind myself of stuff I used

01:51:04.340 to remember. But you do have to kind of go back and read the methods and figure out who were the

01:51:08.900 patients in this? What was the eligibility criteria? Why did they do it this way? And of course,

01:51:14.280 it all kind of came back to me, but it took a minute. So the first thing is these are all patients

01:51:20.160 who had progressed through every standard therapy. So these are patients for whom there were no other

01:51:26.600 options. These patients either had very advanced stage three melanoma, which means it was local

01:51:34.260 regional melanoma, but it couldn't be resected. So an example of that would be a cancer that was

01:51:42.380 completely engulfing. Let's say the primary site was the cheek and it had completely grown into all

01:51:49.540 of the surrounding soft tissue. It hadn't spread anywhere, but it was all the lymph nodes of the

01:51:54.860 neck. And I've seen patients like this and it's just completely disfiguring. And they'd already been

01:51:59.880 through the standard chemotherapy and nothing was working and the thing was growing. And then it was

01:52:04.500 mostly made up of patients with stage four cancer. Now melanoma has a very funny staging system.

01:52:10.100 In cancer, we typically talk about something called the TNM staging system. It is the standard way that

01:52:16.660 cancers are staged. T refers to the tumor size, N refers to the lymph node status, and M refers to

01:52:24.060 the presence or absence of metastases. And for most cancers, it is a very simple system. T is typically

01:52:31.280 a number one, two, sometimes up to three and four. N is typically zero, one, or two, and M is zero or

01:52:37.720 one. Either there's no mets or there are mets. So for example, in colorectal cancer, the T staging

01:52:43.080 determines the depth in the colon wall that it went. N is, did it go to mets? And I think in colon,

01:52:49.900 I'm a little rusty on this. I think colon has N zero, one, or two, depending on how many lymph nodes.

01:52:55.000 And then M zero, did it go to anything beyond that, like to the liver, lung, et cetera, or not?

01:53:00.040 Melanoma is a bit more complicated. It has M zero, meaning no mets, but it also has M one A,

01:53:07.420 M one B, M one C, and M one D. And within each of those, it has a threshold for high and low lactate

01:53:16.420 dehydrogenase or LDH. So it's both a staging based on imaging and biochemical. And the reason for that

01:53:22.900 is LDH level is such a strong prognostic indicator of survival. In addition to M staging,

01:53:28.620 higher LDH levels tend to reflect more acidity, which we talked about why that's problematic,

01:53:34.200 tends to reflect faster growing tumors, higher turnover, higher metabolic activity.

01:53:40.120 M one A, let me see if I can remember this. M one A's are cancers that have metastasized

01:53:47.520 to surrounding soft tissue or soft tissue anywhere in the body. So anywhere else on the skin.

01:53:54.080 And you might think, well, that's kind of crazy. Like how does that happen? And it's really bizarre.

01:53:58.100 You can have a patient who had a melanoma that showed up in one part of their body,

01:54:01.980 and then they have metastases on other parts of their skin. M one B, and I always get B and C

01:54:08.780 confused. I think B is the lung. So M one B is to the lung. M one C is to any internal organs. So

01:54:16.880 liver, et cetera. And M one D is to the CNS. And as those numbers increase, as those letters increase,

01:54:22.620 the prognosis gets lower and lower and lower. So one of the first things I always look at when I look

01:54:26.920 at a paper like this is, tell me about the patient population. What was the breakdown of patients?

01:54:32.860 And in table one, so that's again, in clinical papers like this, table one is always, always,

01:54:38.980 always baseline characteristics. Oh, I should mention one other thing, Andrew. This was done

01:54:44.440 as a three to one to one randomization. So again, in the simplest form, the study would have two groups.

01:54:51.700 We're going to just have a treatment group and a placebo group. But in this arm, you had three

01:54:57.340 groups with one of them being the placebo. The placebo got just GP100, which is just a cancer

01:55:04.180 vaccine. By the way, this is a cancer vaccine that never showed any efficacy. So it was a cancer

01:55:10.420 vaccine that had been tested both with interleukin two directly and as an adjuvant for patients who had

01:55:17.340 melanoma resected who were tumor free and then given the vaccine as adjuvants to see, did that have an

01:55:23.980 effect on outcomes? And it didn't. So it's kind of a known placebo. So you had that group, then you had

01:55:30.080 the anti-CTLA-4 group, and then you had anti-CTLA-4 plus GP100. What's the rationale?

01:55:38.020 For the three to one to one, it's basically, it increases statistical power. This total study

01:55:44.300 was a little under 700 people. They put 400 in the anti-CTLA-4 plus GP100 group, and then a little

01:55:52.940 over 130 in each of the other two groups. So you're always going to be able to make these two

01:55:57.900 comparisons. What you can check by doing this is, is there any effect of GP100 in this setting,

01:56:04.980 which had never been done before. So again, GP100 is a known protein expressed by melanoma.

01:56:12.400 And all of these people were haplotyped to make sure that their immune system would recognize it.

01:56:17.840 And the question was, would giving people anti-CTLA-4, i.e. taking the brakes off their

01:56:23.800 immune system with or without GP100 make a difference? Going through this, you can see it

01:56:28.800 sort of skews about 60% to 40% male to female. They talk about something called the ECOG performance

01:56:34.860 status. That refers to how healthy a patient is coming in. So ECOG zero is no limitations whatsoever,

01:56:41.240 which is kind of amazing when you really consider something. I think this speaks to just how

01:56:45.320 devastating this disease is. These are patients who all have like six months to live, a year max.

01:56:51.760 And yet look at this, 58 to 60% of them have no limitation on their quality of life at this very

01:56:58.240 moment. That's going to change dramatically absent a cure here. And then ECOG one has some limitation.

01:57:04.180 And you can see that ECOG one plus ECOG zero is basically 98% of the population. You can see the

01:57:10.680 staging there. So again, very, very few of these patients are the M zero category. M zeros are people 1.00

01:57:17.660 who have stage three disease that is so aggressive, it can't be resected. That's about 1%. But the majority

01:57:23.520 of these people are the M1As, M1Bs, M1Cs. So these are people with very aggressive cancers.

01:57:30.560 You can also see that about 10 to 15% of these people also have CNS metastases. Again,

01:57:37.580 the poorest prognosis of the poor. And then you can see about 40% of them have the LDH level above

01:57:45.120 cutoff. All of this is to say, we're talking about a group of patients who have a very high likelihood

01:57:52.900 of not surviving more than a year. It would be very unlikely that many of these patients would

01:57:58.940 survive more than a year. So basically more than 70% of these people have visceral metastases.

01:58:04.180 A third have high LDH and more than 10% have brain mets. They've also all progressed through

01:58:10.200 standard therapy. Radiation chemo.

01:58:12.940 Yeah. And the chemo for melanoma can be a toxic chemo that really just doesn't really do anything.

01:58:19.740 So is it commonplace to use a treatment that failed in clinical trials as a placebo in these

01:58:28.500 sorts of studies? Yeah, it's interesting. You're referring obviously to the GP100. I think the

01:58:33.600 thinking was, okay, it hasn't been effective in other treatments, for example, when combined with

01:58:40.860 IL-2 or as an adjuvant, but never before has it been tried with a checkpoint inhibitor, which is

01:58:48.020 the technical term for this type of drug. I think there was also some belief that it would be easier

01:58:55.000 to enroll patients. I don't think they stated this, but that's often the case. It would be easier to

01:58:59.720 enroll patients if they would know that even in the placebo arm, they're still getting an active agent.

01:59:05.520 Got it. And I suppose there's always the possibility that the combination of the

01:59:09.160 failed drug with a new drug would work. So you're increasing the probability for novel discovery.

01:59:14.980 For sure. And again, if you go back to the randomization of three to one to one, it's really

01:59:21.480 only one fifth or 20% of the participants that would get just the GP100. So in other words,

01:59:28.640 you're basically telling people when they come into this study, there's an 80% chance you're going

01:59:34.220 to get anti-CTLA-4. That's a much better set of odds than your typical study where you're going to be

01:59:40.080 50% likely to get the agent of interest. Right. And people who are literally dying of cancer,

01:59:47.060 they don't want to be in the control group. Right. So the primary outcome for this study

01:59:52.280 actually changed in the study. Now they have to get permission to do that. So the original primary

01:59:59.480 endpoint was the best overall response rate. So I have to explain how response rates are measured.

02:00:05.400 This is a bit complicated. Remember, all of these patients by definition have measurable,

02:00:10.580 visible cancer by visible, either on the surface of their body, but more likely on an MRI or CT scan.

02:00:16.500 So all of these patients had to be scanned head to toe within 12 weeks of enrollment.

02:00:21.020 Again, there's another thing I should point out here, which I know you understand,

02:00:23.560 but it's always worth reminding people when a study like this takes place,

02:00:27.340 it usually takes place over many years. And so it's not the case that all 700 of these patients

02:00:33.120 were enrolled on the same day and finished observing them on the same day. No, no, no. This took place

02:00:37.220 for a very long period of time. This took place across tens of centers. I can't remember if this

02:00:43.020 was just globally or across the world. It might've been across the world. And so every center really

02:00:47.640 needs to adhere to a very strict protocol. And you have a central organization that is running this.

02:00:53.800 So you have a drug company. I think this is Bristol Myers Squibb that makes the drug. They provide

02:00:58.000 the drug. And then you have a CRO, a clinical research organization that is basically managing

02:01:04.100 the trial. And the trial is being done at cancer centers all over the world or all over the country.

02:01:10.660 And enrollment, I think, began in 2008 for this. No, no. I think it completed in 2008. It probably

02:01:16.500 started in about 2004, 2005. And therefore, you had to kind of have real clear protocols around this.

02:01:22.600 So a complete response is the easier of these to understand. A complete response is everything

02:01:28.620 vanishes completely. That's very rare in cancer therapy. So instead, what we look for is a partial

02:01:37.040 response. A partial response, and there are really different ways to define this. There are different

02:01:42.080 criteria, but this is the most common way you define a partial response. A partial response is at

02:01:48.140 least a 50% reduction by diameter. Because remember, in this type of imaging, you're looking

02:01:55.620 at 2D versus 3D. So if you're looking at a lung lesion and it's this big, you know, if it's two

02:02:01.360 centimeters long, it has to go to at least one centimeter in diameter. So it's a 50% reduction at

02:02:06.880 least of every single lesion with no new lesions appearing and no lesions growing. So it's very strict

02:02:14.240 criteria, right? Again, CR means everything vanishes. PR means at least a 50% by diameter,

02:02:22.720 which by the way, is a much bigger reduction in terms of tumor volume when you consider the linear

02:02:27.180 versus the third power relationship of length and volume of every single lesion with nothing new

02:02:33.400 appearing regardless of how small and no lesion growing. So that's a PR. So you basically have

02:02:39.780 no response, progression, we talk about those together, and then partial response and complete

02:02:45.420 response. So initially, the authors of this study, the primary endpoint of this was going to be the

02:02:51.160 best overall response rate. So what was the proportion of patients that hit PR? What was the

02:02:56.460 proportion that hit a CR? That's very common in this type of paper where the outcomes are typically

02:03:02.900 so dire. I don't remember when the study ended, but the amendment was made to change the primary

02:03:09.700 endpoint to overall survival at some point during the study. And by the way, that tends to be the

02:03:15.880 metric everybody cares most about. So the overall survival for metastatic melanoma is zero, with the

02:03:23.560 exception of people who respond to interleukin-2, high-dose interleukin-2, and that will boost the overall

02:03:30.500 survival rate to somewhere between 8% and 10%. Very, very low. These patients, many of whom had

02:03:39.100 already taken and progressed through interleukin-2. Let me refresh my memory on what percentage of those

02:03:48.460 patients. About a quarter of these patients had already taken high-dose interleukin-2, and by

02:03:55.720 definition, the fact that they're in this study means they had already progressed through that. That

02:03:59.880 treatment had failed. Just reiterate the state these patients are in. So now let's look at figure

02:04:07.160 one. So again, I'll describe it because I realize many people are just listening to us. All of this

02:04:12.260 will be available both in the video, and then we'll link to the paper. So figure one is a figure that

02:04:18.480 probably looks really familiar to people who look at any data that deal with survival. It's called a

02:04:23.480 Kaplan-Meier survival curve. So on the x-axis for this curve is time, and time here is shown in

02:04:30.760 months, and on the y-axis is the overall survival. The very top, 100% at the bottom, 0%. And it has

02:04:39.540 three graphs or three curves that are superimposed on one another for each of the three groups. Again, the

02:04:46.480 control group, which is the GP100, the anti-CTLA-4 group by itself, and the anti-CTLA-4 plus GP100.

02:04:55.140 And one of the characteristics of a Kaplan-Meier curve is by definition, they have to be decreasing

02:05:00.520 in a monotonic fashion because it's cumulative overall survival. That just means it can't come

02:05:06.220 down and go back up. Nobody comes back to life. So once a person dies, they are censored from the study,

02:05:12.600 and the curve drops and drops and drops. And you can see that they kind of highlight,

02:05:17.260 and I actually think it makes the graph a little harder to read when they put some of those marks

02:05:21.780 on there. But what really becomes clear when you look at this is that there's a clear distinction

02:05:28.100 between the curve for the placebo group, the GP100 group, and the other two, the two treatment groups.

02:05:37.140 Now, you'll note at the very end that the two treatment groups appear to separate a little bit.

02:05:42.220 I'll talk about that in a second. So when I look at these, Andrew, the first thing I always turn

02:05:47.340 my attention to, I can't resist. I have to look at the right-hand side of the graph because what is

02:05:52.080 that really telling me? The tale of this is showing me the true overall survival. And I want to sort of

02:05:58.560 figure out what is going on. So in the GP100 group, which is the placebo group, it is kind of amazing to

02:06:05.680 think that there is still one person who is alive at 44 months. It's amazing. I mean, it's both sobering

02:06:12.780 and amazing that like one person made it to 44 months. The next thing I ask myself is, well, how long

02:06:18.880 did half of the people make it? That's called median survival. And to do that, you go up to the

02:06:24.760 y-axis and you draw a little line from the 50 over and then you bring that down. That's awfully low. 0.57

02:06:32.680 Yeah. In fact, the table will tell us exactly what that is because I think it's really hard to eyeball

02:06:37.580 that stuff. So let's go to, so there's always a table that will accompany these things. And let's

02:06:44.080 pull up that table. I've got this paper spread out over so many things. That's adverse events.

02:06:49.920 Where's our survival table here? Two subgroup analysis of overall survival.

02:06:56.360 It would probably be helpful if I stapled these things together because it would be easier.

02:06:59.800 Well, this is always a trade-off since this is a journal club episode. I will say that stapling

02:07:04.060 helps, but it also prevents one from separating things out, writing in the margins. I like these

02:07:09.020 little mini clips, no financial relationship to the mini clips either. Just have to state that because

02:07:15.720 if you don't say that, people go, oh, you must have a stake in these mini clips.

02:07:19.120 I like these little mini clips. In fact, I'm such a nerd. I always have one of these

02:07:23.380 Pilot V5 V7s on my pocket or my hip. And then my pockets are always filled with these little mini

02:07:29.700 clips. But then again, I have a friend who's a musician. He's always raining guitar picks.

02:07:33.720 As far as occupational hazards go of being a nerd, these mini clips.

02:07:37.520 I'm a big fan of the mini clip as well. Yeah.

02:07:39.820 I went without it today. All right. So thank you. Yes. Table two. Let's look at table two while

02:07:44.840 looking at the Kaplan-Meier curve because now this allows us to see a couple of things. By the way,

02:07:49.120 remember how I said there's like that one person who is still alive in the treatment group? Well,

02:07:54.840 you can tell that he's not a complete responder. He or she is not a complete responder because

02:08:00.980 under evaluation of therapy in table two, it says best overall response and it says complete

02:08:07.440 responders zero. So there was zero complete responders in the placebo. There were two partial

02:08:13.540 responders. Again, a partial responder is some lesions got smaller, some got bigger. Stable

02:08:20.480 disease. It didn't really change that much. And progressive disease is obviously it went beyond.

02:08:27.980 And when you say partial response, like lesions got smaller, are they literally just

02:08:31.380 tracing the circumference of one of these skin lesions and saying, okay, it got bigger, smaller,

02:08:37.380 like just morphology. Yep. Yep. Gosh, this feels so crude in terms of like, I mean, it makes total

02:08:43.000 sense, but like in terms of modern medicine, oh, like your lesion grew from like three millimeters to

02:08:47.440 six millimeters. And then you're literally like drawing little boundaries around little blotches

02:08:52.100 on the skin. Yeah. You're putting a little measuring tape on them. Now, again, most of these are happening

02:08:56.120 in the radiology suite because most of the disease for these patients is inside the body. Remember more than

02:09:01.740 70% of these patients had visceral metastases. So liver, soft tissue, lung, brain. In fact,

02:09:10.140 if you include lung, liver, brain, and viscera, it's pretty much all the patients. So most of this

02:09:15.640 is looking at a CT scan or an MRI for the brain. Okay. So that's kind of the first thing that comes up.

02:09:20.480 The median response rate should be shown pretty prominently here. So I'm looking through this

02:09:26.880 and where is median response? Maybe it's shown in a different table, not disease control rate time

02:09:37.660 to progression. I remember it's about 10 months, but maybe that's just in the text. Yeah, here it is.

02:09:45.120 I thought this would be in a table, but it's on page 715 of the paper. It just reports it.

02:09:50.620 So, I'm sorry, I misspoke. The 10 months was for the anti-CTLA-4 plus GP100 and 6.4 months

02:10:01.220 for the GP100 alone. That's the control. And then 10.1 for the anti-CTLA-4 alone. And again,

02:10:09.360 I'm just always doing this. I'm kind of going back to the paper to be like, does that make sense?

02:10:12.980 And yeah, you called it, right? You said median survival was about eight. Well, it turns out it's

02:10:17.520 actually like six and change because it has that little ding in it and it's out to a little past

02:10:22.640 10 on the two others. So the net takeaway here is, again, just to put that in English because it's so

02:10:28.220 profound, 50% of the patients in the control group were dead in six months. 50% of the patients in the

02:10:37.820 treatment group, both treatment groups were dead in 10 months. So what that means in cancer speak

02:10:44.160 is these drugs extended median survival by four months. Now, that's an important concept.

02:10:52.640 When we think about how has cancer therapy changed over the past 50 years, median survival for

02:10:59.840 metastatic cancer has increased across the board. So a person today with metastatic colorectal cancer

02:11:06.360 or a woman today with metastatic breast cancer or a person with metastatic lung cancer,

02:11:11.880 these people will live longer with those diseases today. Thanks mostly to treatments. This is not

02:11:19.860 an early detection lead time bias issue. This is treatments are allowing people to live longer.

02:11:26.740 And that's an important part of the story, but it's only half of the story, yet it often gets touted

02:11:32.400 as the story. The other half of the story, and frankly, the story that I think is more important is

02:11:37.280 what is overall survival doing? And if you go back to those cancers, the answer is zero.

02:11:44.700 Overall survival hasn't changed for solid epithelial tumors. It was 0% in 1970, and it's 0% today.

02:11:53.700 Everyone dies. Everyone dies from metastatic solid organ tumors. There's those niche examples I gave you.

02:12:00.340 Testicular cancer is now an exception. GI stromal tumors would be an exception. And I'm not including

02:12:06.140 leukemias and lymphomas where now there are exceptions. Not to try and be overly optimistic,

02:12:12.380 but if I look at the graph in figure one, and I look out at the tail of the graph.

02:12:18.680 That's right.

02:12:19.480 And for those that are just listening, what I see, and I'm far less, far less familiar with this type of

02:12:26.400 work and this analyzing these type of data. But what I see is that people in the placebo group,

02:12:30.680 they're all dead, except that one. They're basically all dead at 44 months.

02:12:35.520 Yep.

02:12:35.880 But when I look at how long it takes for everyone to be dead in the true treatment groups,

02:12:41.500 looks like 53, 54 months or so.

02:12:45.200 And they're not dead. That's the point.

02:12:46.940 They're hanging in there, right? So, because, you know, an extra, somebody who lost both of my

02:12:52.840 scientific advisors, two of the three, the other one to suicide. We've talked about this before,

02:12:58.120 but the other two to different cancers, both had the BRCA2 mutation, by the way,

02:13:03.040 you know, an extra eight to 10 months with your kids or with your spouse, or to quote unquote,

02:13:09.900 get your affairs in order is a big deal. I mean, it's still depressing in the sense that nobody survives

02:13:14.860 long-term, but, you know, an extra 10 months, as long as one is not miserable in that time,

02:13:20.680 completely miserable. I mean, that's an extra 10 months of living.

02:13:24.680 And what's interesting here is the observation period stops and some of these patients are still

02:13:29.240 going. What you're highlighting is kind of the point I want to make, which is overall survival

02:13:34.840 is the most important metric and it's the highest bar, make no mistake about it. And it's certainly

02:13:41.280 not the bar any drug company is ever going to want to talk about for a cancer drug.

02:13:46.960 But why not?

02:13:47.800 None of them work.

02:13:48.440 They only want to talk about cures. They don't want to talk about median survival.

02:13:52.320 They only want to talk about extending median survival. And there are lots of people out

02:13:57.080 there that are on this platform. I don't need to get onto it, but we'll say, look, it's a real

02:14:01.640 racket in oncology today where drugs that are extending median survival by four weeks are being

02:14:08.540 put on the market at a tune of 50 to a hundred thousand dollars per treatment. That's not uncommon

02:14:13.880 in oncology. There was one drug that was approved for pancreatic cancer. I believe it extended

02:14:18.400 median survival by nine days and it costs $40,000.

02:14:22.280 And it's being advertised as significant.

02:14:24.460 That was a statistical significant improvement in median survival. It's really understandable why

02:14:28.700 people are very skeptical of the pharma industry. And I think a much more nuanced view is necessary.

02:14:34.120 Clearly, I don't think pharma is all bad, but I really understand why people lose faith in pharma

02:14:39.000 when these types of products somehow make regulatory approval.

02:14:43.440 Does insurance cover these kinds of drugs?

02:14:46.120 It can. In fact, it often does. It depends on the FDA approval, of course, and the indication,

02:14:50.740 but a lot of times they do. Yeah, there's a societal cost to these things,

02:14:54.880 but there's also a patient cost. So a lot of times insurance doesn't fully cover it and a patient has to

02:15:00.240 bear the cost difference. And on top of that, you alluded to this a second ago, which is what if your

02:15:04.700 quality of life is dramatically compromised as a result of this treatment? And yes, statistically,

02:15:09.760 you're going to live nine days longer or three weeks longer, but at what cost to your health

02:15:15.520 in those final remaining days? And by the way, you're potentially straddling your loved ones with

02:15:21.460 enormous debt in your absence. So it's a super complicated topic.

02:15:25.580 There's a dignity component too. I mean, I've seen this in people dying. At some point,

02:15:30.420 they become such a diminished version of their former selves that they don't want to be seen

02:15:36.400 by people that way. Yep. So what is exciting about this drug, this paper is not the one that

02:15:45.540 shows it. The reason I chose this paper, Andrew, is because it was the first approval. A second drug

02:15:52.380 came along that is an anti-PD-1 drug. That drug is called Keytruda. That drug turned out to be even

02:15:59.040 better, has even a greater response rate, both in terms of median survival and overall survival.

02:16:05.600 But this was the landmark paper. I also have a slight bias here, and I'll disclose in a moment why,

02:16:12.760 but I think it just talks about very interesting biology. Let's talk about a couple of things that

02:16:16.900 stuck out to me in this paper. The first thing that stuck out to me, and the authors didn't comment

02:16:21.360 on it, unless they did and I missed it, is look at figure two. So figure two is the subgroup analyses

02:16:31.700 where you're sort of showing a similar graph to the one you showed earlier. You show the response rate

02:16:38.900 or the change in response between the groups, and then you put the error bars on it. And this is where

02:16:44.940 we talk about how, well, it's a 95% confidence interval, so does it touch the unity line? So

02:16:50.180 these are called tornado plots typically. What you'll notice is that in the top, it's comparing

02:16:56.680 the anti-CTLA-4 with GP-100 versus the GP-100. And in the bottom, you're looking at the anti-CTLA-4

02:17:03.060 versus the GP-100. So at a glance, you can see GP-100 is not doing anything. That's the first takeaway

02:17:09.300 of comparing A to B. What I find most interesting is look at the subgroup analysis of females.

02:17:16.160 Notice that in females, while there's a trend towards risk reduction, and this is risk reduction 0.70

02:17:22.380 for overall mortality. So again, I just want to restate that. The primary outcome of this trial

02:17:27.320 was changed to overall survival, which I think is the better outcome, by the way. And overall,

02:17:32.560 for all patients, when you compare anti-CTLA-4 plus placebo versus placebo, there was a 31% risk

02:17:43.320 reduction in overall mortality. That's the mathematical interpretation of what you're

02:17:49.060 seeing at the tail end of that Kaplan-Meier curve.

02:17:51.780 Living longer.

02:17:52.900 Living longer.

02:17:53.600 And it sounds like a big difference.

02:17:55.180 Sounds like a big difference.

02:17:56.060 Sometimes it is a big difference.

02:17:57.360 It is for those people because you're really looking at basically 0% surviving in the placebo

02:18:04.440 group versus 20% of people are still alive at 56 months in the treatment group. But look,

02:18:13.000 that means 80% have died. But notice that, and sorry, when you just look at the anti-CTLA-4 plus

02:18:19.940 GP-100 in the subgroup B, that hazard ratio is even showing more compression. It's a 36%

02:18:27.120 reduction in risk of death. But notice that the females did not reach significance. So in the

02:18:34.900 first group, they barely do. And you can see that because the confidence interval runs from 0.55 to 0.92.

02:18:42.180 And notice the error bar almost touches the line. And in the second one, it does not reach

02:18:47.220 significance at all. So I actually went and kind of did a little reading on this after. And I said,

02:18:52.600 hey, was this an outlier study? And it turned out it wasn't. And that about half the studies

02:18:58.600 of anti-CTLA-4 did indeed find that the drug was less effective in women than men,

02:19:05.500 which I found interesting. Now, I couldn't find any great explanation for it, but the most

02:19:10.780 plausible explanations fit into two categories. The first are maybe there are differences in the

02:19:16.840 immune response to the drug if you're a man or a woman. The second comes down to dosing. I should

02:19:23.040 have said this at the outset, but of course, these drugs are not like a pill where it's like everybody

02:19:26.820 gets 50 milligrams of this. They're all dosed based on weight. So this study is dosed, I believe,

02:19:33.060 at three milligrams per kilogram. And because most men are heavier than women, men are getting a higher

02:19:39.980 dose than women. And weight and body surface area and immune system, like these things are not all

02:19:47.080 perfectly linear. I kind of wonder if this difference is simply explained by men on average

02:19:54.520 getting a higher dose than women. Last thing I want to talk about here is in table three. So table three, 0.92

02:20:04.760 always an important table to look at in any paper, is what are the adverse outcomes? What are the

02:20:09.640 adverse effects of the drug? I've spent a little bit of time with this and I confess, I definitely

02:20:14.120 don't want cancer to the extent that I can avoid it. But this table made me wonder whether or not I

02:20:19.420 would also want to just avoid cancer treatment given the life extension provided. I mean, these adverse

02:20:25.520 events are pretty uncomfortable. Just to put in perspective, and you always have to kind of be

02:20:31.820 mindful of how many of these adverse events are occurring in people just because their disease is

02:20:36.940 progressing. So the first thing I always want to look at is total adverse events in all three groups.

02:20:43.480 So grade three and grade four are real toxicities. Grade four toxicity is life-threatening toxicity,

02:20:48.900 by the way. Grade three is pretty significant toxicity. Grade one and two, that's not that severe.

02:20:54.020 A little rash, put some corticosteroids on it, it went away kind of thing. Okay, so in the treatment plus

02:20:59.800 GP100 group, 98.4% of people reported some event. So all but 1.6%. In the NTC-TLA-4 group alone,

02:21:10.100 it was 96.7%. So only 3.1% did not. But in the placebo group, it's 97%. So it's important to keep

02:21:17.560 in mind, everybody's having some adverse effect. Okay, well, what if you say, well, let's just limit

02:21:22.040 it to the most severe events? Well, let's just talk about grade four toxicities. There were 6.1%

02:21:29.540 of those in the placebo group, 8.4% in the NTC-TLA-4 group, and 6.8% in the combined group. So not a

02:21:38.140 huge difference in grade four toxicity. Meaning that whatever adverse events are occurring may

02:21:44.800 not be related to the treatment. It may not be related to the treatment. If you think about it,

02:21:49.200 and it's a very awful, sad, morbid thought to imagine, you're looking at the adverse responses

02:21:54.180 of people, more than 80% of whom died during the course of a very, very short study. And so it's

02:22:01.220 very difficult to disentangle what effects or what side effects a person is having just from that

02:22:06.420 process as they are from the actual treatment. But if there is an area where there's a really clear

02:22:12.600 difference, it's down in the autoimmune category. So if you look at any immune-related events,

02:22:19.820 you can see that in the NTC-TLA-4 plus GP100 group, it's about 60% in both of those treatment groups

02:22:28.400 versus 30%. And if you look at the grade three and four toxicities, it's 10% in the NTC-TLA-4,

02:22:37.660 15% in the NTC-TLA-4 alone group, and only 3% in the treatment. So that's a real difference.

02:22:46.860 But it makes sense that people getting this drug plus placebo or just the drug would have autoimmune

02:22:53.060 issues because this is an immunotherapy. It's an immunomodulator. In fact, what is it doing?

02:22:57.920 It is taking the brakes off the immune system. But then again, the things that they list out,

02:23:03.100 pruritus, is that an irritation of the skin? Yeah. Irritation of the skin. I'm not a physician,

02:23:08.320 but I know that any itis is going to be like an inflammation. And OMA, unfortunately, likely a

02:23:13.440 cancer or cell replication. Look at the gastrointestinal differences. And the vitiligo,

02:23:18.540 so 3.7%, 2.3%, 0.8%. The GI stuff is the most common stuff you're going to see there. Those are the

02:23:26.100 really big ones. And of course, there's diarrhea and there's diarrhea. Oh, yeah.

02:23:29.500 Like there's traveler's diarrhea. There's ate an overly spicy large meal the night before diarrhea.

02:23:34.920 And then there's like, can't really do anything besides make trips back and forth to the bathroom

02:23:39.700 diarrhea. Put it this way. There's colitis here is diarrhea so significant these patients require

02:23:44.080 IV fluids. Now, what you don't see here is how many of these patients actually required

02:23:48.200 corticosteroids to reverse the autoimmunity. So a lot of times what will happen here in these studies

02:23:53.080 or with these drugs is the autoimmunity becomes so significant that you have to stop the drug and give

02:23:59.020 corticosteroids. Do the exact opposite. You now have to shut the immune system down. So you just took

02:24:03.960 the brakes off it with the drug and now you need to shut it down with corticosteroids. When I was in

02:24:09.380 my fellowship, I wrote a paper about autoimmunity correlating with response rate in anti-CTLA-4

02:24:18.840 early on. This was during the phase 2 work. So the NCI was a very early adopter of participating in

02:24:26.600 these trials. And it was observed that, or at least hypothesized, this is what the paper basically

02:24:32.500 wrote about, which was, is there any correlation between autoimmunity and response? And it turned

02:24:38.740 out the answer was yes. There was a very strong correlation. So there was no difference in auto

02:24:44.480 immunity between the doses. So the paper we wrote was two dosing schedules. So it was basically the

02:24:51.400 full dose, the three milligrams per kilogram versus a low dose, one milligram per kilogram. This is a

02:24:55.460 phase two trial. Those are your two arms. There turned out to be no difference in autoimmunity between

02:25:00.320 them, but there was a big difference between the response rate that tied to autoimmunity. In other

02:25:07.840 words, autoimmunity predicted response. Now, I think over time, these investigators, the doctors who

02:25:16.140 administer these treatments are getting better and better at catching these things earlier because

02:25:19.860 these autoimmune conditions can actually be devastating. So on a very personal note, when

02:25:25.360 Keytruda came out, I want to say it was around 2000, 2013, 2014, thereabouts. Again, it was for

02:25:34.400 treatment of metastatic melanoma. I want to come back and explain why melanoma gets all of the attention

02:25:39.400 in immunotherapy conditions. I'll state that. But anyway, a friend of mine got pancreatic cancer

02:25:45.280 and he got the bad type of pancreatic cancer. So this is adenocarcinoma of the pancreas. This is a

02:25:52.300 non-survivable type of cancer. Furthermore, his was unresectable. Can you explain what that is for

02:25:57.180 people? About 20% of people who have pancreatic cancer technically have it in a way where you could

02:26:04.240 still take out the head of the pancreas. Right. The Whipple procedure. The Whipple procedure. 1.00

02:26:08.360 Now, tragically, most of those patients will still recur. My understanding is that pancreatic cancer

02:26:13.920 progresses from anterior to posterior in the pancreas and that the Whipple is a removal of

02:26:19.500 the front end, the anterior. That's the Whipple procedure. So if the cancer has progressed far

02:26:24.960 enough caudal into the posterior pancreas, then there's nothing left to cut out basically. 0.52

02:26:30.960 Can we survive without a pancreas for any amount of time? Oh yeah, absolutely.

02:26:34.200 So why don't they just remove the whole pancreas? Oh, that's my point. It's already 0.99

02:26:37.500 micrometastasized. The surgical procedure is not the challenge anymore. It used to be.

02:26:42.320 So at Johns Hopkins, which is one of the hospitals where this was pioneered,

02:26:45.820 the 30-day mortality for a Whipple procedure was, I don't know, 80%. Whoa. And the reason was

02:26:53.280 to figure out how to suture a pancreas to the bowel. So the pancreas is such an awful organ to operate on

02:27:01.020 because its enzymes are designed to digest anything and everything. So imagine now you have to cut the

02:27:07.880 pancreas in half, take out the head of the pancreas with the duodenum, and then somehow 0.97

02:27:13.180 sew that open half of a raw pancreas to the end of the jejunum and not let it digest itself. 1.00

02:27:20.640 Someone at Hopkins figured this out.

02:27:22.640 No, the first one was actually done by A.O. Whipple. But yes, at Hopkins is where they figured

02:27:29.320 out the way to put drains in, the surgical technique, how to do it in two layers, what type of stitches to

02:27:36.000 use. All of the nuances of this were worked out in a few places, but I would say Hopkins more than

02:27:41.720 any place else. And are there physicians who try this on non-human primates or something,

02:27:47.260 or is this always just done on patients?

02:27:48.980 Well, nowadays, I mean, put it this way, even 25 years ago at a major center like Hopkins,

02:27:55.340 the mortality of that procedure was less than 1%.

02:27:57.940 So there have been some victories.

02:27:59.760 Well, yes, but here's my point. That's no longer the bottleneck.

02:28:02.840 Taking out the pancreas safely, as complicated and challenging as that is, and if you need a

02:28:07.300 Whipple procedure, you only want to have it done by someone who just does that night and day.

02:28:11.580 You don't want weekend warriors doing it. That's not why people are living or dying.

02:28:16.020 They're dying because the cancer just comes back. It was already spread to the liver by the time you

02:28:21.120 did it. You just didn't realize it yet. So whether you took out the whole pancreas or the head of the

02:28:25.680 pancreas or the tail of the pancreas, the location of the tumor is predictive of survival only in the

02:28:32.980 extent that it basically is a window into how soon did symptoms occur. So pancreatic cancers in the tail

02:28:40.600 tend to be more fatal, even though they're way easier surgically to take out because by the time you

02:28:48.280 develop symptoms of a tail pancreas cancer, it's a big cancer.

02:28:53.820 I was going to ask this question later, but I'll just ask it now. Given the link between the immune

02:28:57.580 system and these cancers, is there an idea in mind that people who are, let's say, 40 and older or 50 and

02:29:06.440 older who don't yet, they're not diagnosed with any cancer, would periodically just stimulate their immune

02:29:13.120 system to wipe out whatever early cancers might be cropping up. You know, just take a drug to just

02:29:19.780 ramp up the immune system, even to the point where you start having a little diarrhea, maybe a few skin

02:29:23.880 rashes, and then come off the drug. Just basically to fight back whatever little cell growths are

02:29:30.240 starting to take place in skin or liver for three weeks out of each year. I mean, why not?

02:29:36.540 Yeah, it's an interesting question. I've never thought of it through that lens. I suppose the question is,

02:29:41.060 what can we do to keep our immune systems as healthy as possible as we age?

02:29:45.880 Stay on a normal circadian schedule. There's evidence for that.

02:29:49.220 Sure. No, there's evidence that certainly if it promotes sleep, anything that promotes better

02:29:53.540 rest is going to promote immune health. Because if you ask the macro question, which is like,

02:29:58.840 why does the prevalence of cancer increase so dramatically with age? There are certain diseases

02:30:04.660 where it's really obvious why the prevalence of the disease increases with age.

02:30:08.760 Yeah, like age-related macular degeneration.

02:30:11.220 Sure. Or cardiovascular disease is by far the most obvious because it's an area under the curve

02:30:16.120 exposure problem. The more exposure to lipoproteins and the more the endothelium gets damaged,

02:30:20.900 the more likely you are to accumulate plaque. And again, it totally makes sense why 10-year-olds

02:30:25.660 don't have heart attacks and 80-year-olds do. But when you sort of acknowledge that, well, hey,

02:30:32.180 anybody's accumulating genetic mutations. We're always surrounded and being bombarded by things

02:30:36.900 that are altering the genome of ourselves. Is it simply a stochastic process where the longer you

02:30:42.880 live, the more of these mutations you're going to occur until at some point one of them just

02:30:46.680 wins? I think that's got to be a big part of it. But I think another part of it, clearly I'm not

02:30:51.960 alone in thinking this, is that our immune system is getting weaker and weaker as we age. People become

02:30:56.760 more susceptible to infections as they get older. And I think that that's equally playing a role in

02:31:02.780 our susceptibility to cancer. So yeah, I think the question is how do you modulate immunity as you

02:31:08.460 age? And to me, that's one of the most interesting things about rapamycin potentially is that when

02:31:13.720 taken the right way, it seems to enhance cellular immunity, which again, that's potentially a really

02:31:19.480 big deal. Again, at least in short-term human experiments in response to vaccination, it's

02:31:24.320 enhancing vaccine response. So the question is, would that translate into cancer? Nobody knows.

02:31:29.580 Could that be one of the reasons why animals treated with rapamycin live longer and get less

02:31:35.260 cancer? Don't know. It could also be that it's at a fundamental level that's targeting nutrient

02:31:39.700 sensing. Where I was going with that story was that, and maybe I'll back up for a moment.

02:31:45.420 Why melanoma? So we didn't really know this 30, 40 years ago in the early days of immunotherapy.

02:31:53.400 But what we know now is that most cancers probably have about 40 mutations in them.

02:31:59.580 That's like ballpark. 40, 50 mutations is standard fare for a cancer. But melanoma happens to be one 0.59

02:32:06.840 of the cancers that has many, many more mutations. And the more mutations a cancer has, the more

02:32:13.260 likelihood that it will produce an antigen that's recognized as non-self. And that's why in the early

02:32:19.920 days of immunotherapy, the only things that worked were IL-2 against metastatic melanoma and kidney

02:32:26.020 cancer, because kidney cancer turned out to also be one of those cancers that, for reasons that are

02:32:30.660 not clear, produced hundreds of mutations. And so it's no surprise that the early studies of

02:32:37.660 checkpoint inhibitors were also done in metastatic melanoma, where you basically have more shots on

02:32:43.380 goal. Again, if I'm going to take the brakes off my immune system, I might as well do it in an

02:32:48.240 environment where there are more chances for my T cells to find something to go nuts against.

02:32:54.780 It's 2013, 2014. And this friend of mine who has something called Lynch syndrome, which is a,

02:33:01.920 one of those few hereditary or germline mutations that results in a huge increase in the risk of

02:33:07.980 cancer. He had already had colon cancer at about the age of 40 and had survived that. It was a stage

02:33:13.620 3 cancer, but he had survived it. Well, now five years later had developed pancreatic cancer. And

02:33:20.520 when he went to see the surgeon, they said, there's nothing we can do. It's too advanced. To put that

02:33:26.300 in perspective, that is a death sentence. That's a six month survival. And at around that time, there

02:33:33.060 was a study that had come out in the New England Journal of Medicine that had talked about how patients

02:33:37.300 with Lynch syndrome had lots of mutations. So we talked with his doctors about the possibility of

02:33:44.780 enrolling him in one of the Keytruda trials. There was one going on, I think at Stanford.

02:33:49.860 The thinking being, well, you would want to target a checkpoint inhibitor against somebody who has a

02:33:55.160 lot of mutations. And even though typically we don't see that in pancreatic cancer, his is a unique

02:34:00.020 variant of it because it's based on this. And so sure enough, he was tested for these mismatch repair

02:34:06.040 genes. He had them enrolled in the trial and amazingly had not only a complete regression of

02:34:12.560 his cancer, and he's still alive and cancer-free today, 10 years later, but the treatment worked

02:34:18.660 so well at activating his immune system that his immune system completely destroyed his pancreas.

02:34:24.580 So now he is effectively had a pancreatectomy based on his immune system. So now he actually has

02:34:30.500 type 1 diabetes. He has no pancreas.

02:34:33.720 Jack's insulin to deal with that or implant.

02:34:36.200 No, no. He has to use insulin just like someone with type 1 diabetes.

02:34:38.800 Had to pick being alive with type 1 diabetes.

02:34:41.480 Yeah, of course. No comparison. But it's just an interesting example of how remarkable this

02:34:46.960 treatment was able to work. You could completely unleash the immune system of a person and you eradicate

02:34:54.860 the cancer and the rest of the cells around it. There are many organs we could live without.

02:35:00.520 There are certain organs you can't live without. You can't live without your heart, lungs, liver,

02:35:04.260 kidneys. But many things that kill people arise from organs. The breast, you could live without 1.00

02:35:09.900 all breast tissue. Prostate, you can live without all prostate tissue.

02:35:12.560 I mean, no one would choose to live without these.

02:35:14.560 Right. But I'm saying if you had metastatic cancer and you had a bullet that could selectively

02:35:20.340 target a tissue, you would take it. And right now, the only tissue we can do that against

02:35:25.500 is a CD19 B cell. And that's what those CAR T cells are. So right now, these are not tissue-specific

02:35:31.180 treatments, but they're mutation-specific. The last thing I'll say about this paper that I found

02:35:35.740 interesting, I was looking for it and I was surprised they didn't at all comment on if there

02:35:40.780 was any correlation between autoimmunity and response. So they obviously acknowledge the

02:35:45.320 autoimmunity in table three, but I would have loved to have seen a statistical analysis that

02:35:50.880 said, hey, is there any correlation between response rate and autoimmunity? But they didn't

02:35:56.280 comment to that effect. So we're left wondering what the current state of that is. And I guess

02:36:02.460 in summary, I'll say that the reason I thought this was an interesting paper to present is that

02:36:08.600 I still believe that immunotherapy is probably the most important hope we have for treating cancer.

02:36:17.800 And while I think we're still only scratching the surface of it, collectively, the overall survival

02:36:23.620 increase for patients with metastatic solid organ tumors is about 8% better than it was 50 years ago.

02:36:31.040 And virtually all of that has come from some form of immunotherapy, I think is promising. And I think the

02:36:38.020 holy grail, meaning the next step, if you go back to where we started the discussion,

02:36:43.400 is coming up with ways to engineer T cells to be even better recognizers of antigens.

02:36:53.140 And there's many ways to do that. One is to directly engineer them. Another is to find T cells that have

02:36:59.240 already migrated into tumors. Those are called tumor infiltrating lymphocytes or TIL. And expanding those

02:37:06.360 and engineering them to be better and younger. Is it possible to engineer our own T cells to be more

02:37:12.980 pH variant tolerant? Meaning since this cloaking of the local area by changing the pH, could we pull

02:37:22.120 some T cells? I'm always thinking about the inoculation stuff, like pull some T cells as part

02:37:27.260 of our standard exam when we're 30, you know, and grow some up in an environment that the pH is slightly

02:37:33.240 more acidic than normal, and then reintroduce them to the body. I mean, after all, they are T cells.

02:37:40.080 In other words, give them a little opportunity to evolve the conditions they can thrive in,

02:37:46.440 or even just keep them in the freezer in case we need them.

02:37:49.700 Yes. So the interesting thing is, I don't know that if you just got them to be comfortable in a

02:37:54.420 lower pH, it would be sufficient. Because there are still so many other things that the cancer is

02:38:01.940 doing as far as using other secreting factors. It seems that by far the most potent thing comes down

02:38:09.240 to expanding the number of T cells that recognize the antigen and making sure that you can get that

02:38:17.740 number big enough without aging them too much. So in some senses, it has become a longevity problem

02:38:23.720 with T cells. The way to think about it is, you want an army of soldiers who are wise enough to

02:38:31.600 recognize the bad guys, which comes with age, but young enough to go and kill. And right now, 0.57

02:38:38.900 both extremes seem to be unhelpful. When you go and find tumor infiltrating lymphocytes in a tumor,

02:38:45.280 they're very wise. They've demonstrated that they can do everything. They can outmaneuver the cancer,

02:38:50.280 but they're too old to do anything about it. And when you take them out to try to expand them by

02:38:55.160 three logs, which is typically what you need to do, expand them by a thousand fold,

02:38:59.400 they can't do anything. And what about avoiding melanoma altogether? I mean,

02:39:02.780 obviously avoiding sunburn. Somehow I got couched as anti-sunscreen, and that is absolutely not true.

02:39:09.020 I said some sunscreens contain things that are endocrine disruptors, and we're going to do a whole

02:39:15.000 episode on sunscreen. Maybe we could do some journal clubs on them.

02:39:18.040 I'm actually planning something on that as well. I wanted to do a deep dive on this.

02:39:21.600 And some dermatologists reached out, some very skilled dermatologists reached out and said

02:39:26.120 that indeed some sunscreens are downright dangerous, but of course melanoma is super

02:39:30.480 dangerous. No one disputes physical barriers for sunscreen. Everyone agrees that that is unlikely

02:39:35.560 to have endocrine disruption. So physical barriers are undisputed, but aside from limiting

02:39:41.120 sunlight exposure to the skin, what are some other risks for melanoma?

02:39:45.600 I mean, I think that's the biggest one. I do not believe that smoking poses a risk for

02:39:49.480 melanoma, and if it does, it's going to be very small. There are hereditary cases,

02:39:53.880 so one needs to be pretty mindful when taking a family history. And by the way, there are really

02:39:58.360 weird genetic conditions that link melanoma to other cancers, such as pancreatic cancer,

02:40:04.100 by the way. So whenever I'm taking somebody's family history and I hear about somebody that had

02:40:08.740 melanoma and someone that had pancreatic cancer, there's a couple genetic tests we'll look at

02:40:12.740 to see if that's a person that's particularly sensitive from a genetic predisposition.

02:40:17.800 And by the way, I think with melanoma, although it's not completely agreed upon, I think it's

02:40:23.480 less about sun exposure and more about sunburn. And again, I'm sure there's somebody listening to

02:40:28.800 this who will chime in and apply a more nuanced response to that. But there's a fundamental difference

02:40:33.920 between I'm out in the sun, getting sun, making some vitamin D versus I'm getting scorched and

02:40:40.620 undergoing significant UV damage. There might also be something to be said for the time in

02:40:45.780 one's life. And I've certainly seen things that suggest that early repeated sunburns would be

02:40:50.880 more of a risk. So I think that's not a controversial point in the sense that who wants to be sunburned,

02:40:56.900 right? So it's like whatever one needs to do to be sunburned, whether it's being mindful of what the

02:41:01.800 UV index is, wearing the appropriate cover, wearing the appropriate sunscreen. I also find

02:41:07.080 the whole anti-sunscreen establishment to be a little bit odd.

02:41:11.440 Well, the anti-sunscreen establishment is odd. I'm trying to open the door for a nuanced discussion

02:41:16.320 about the fact that some sunscreens really do contain things like oxybenzenes and things that

02:41:21.360 are real endocrine. And you're spraying them on kids.

02:41:23.880 Yeah, yeah, yeah. But when you just look at the straight, you know, the good old-fashioned

02:41:26.600 mineral sunscreen is perfectly safe. Yeah. As far as we know, dare we cross the seed oil debate into

02:41:33.240 this? Some of the folks who are really anti-seed oil also claim that seed oils increase risk for

02:41:37.880 sunscreen. Peter and I are smiling because we have teed up a debate soon with some anti-seed oil and

02:41:46.640 less anti-seed oil experts. So that's forthcoming. That's going to be a fun one. We'll be doing all of

02:41:52.700 that with our shirts on. I really appreciate you walking us through this paper, Peter. I have never

02:41:58.360 looked at a paper on cancer and certainly not one like this. I learned a lot and it's such an

02:42:04.600 interesting field, obviously because of the importance of getting people with cancer to

02:42:09.240 survive longer and lead better lives, but also because of the interaction with the immune system.

02:42:14.920 So we learned some really important immunology too.

02:42:17.300 And this was great. I feel much more confident now in the belief that the exposure to light early

02:42:24.180 and late in the day can actually have benefits. And as I said, I think that there's some causality

02:42:29.440 here and I think it shouldn't be ignored. Well, this was our second journal club. I look forward

02:42:34.440 to our third. Next time you'll go first. We'll just keep alternating. And we've also switched venues,

02:42:39.460 but we both wore the correct shirt. I hope people are learning and not just learning the information,

02:42:46.060 but learning how to parse and think about papers. And I certainly learned from you,

02:42:49.620 Peter. Thank you so much. Yeah. Thanks, Andrew. This is great.

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The Peter Attia Drive - January 22, 2024

#286 ‒ Journal club with Andrew Huberman： the impact of light exposure on mental health and an immunotherapy breakthrough for cancer treatment

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