Huberman Lab - Journal Club with Dr. Peter Attia | Effects of Light & Dark on Mental Health & Treatments for Cancer
Episode Date: January 22, 2024In this journal club episode, my guest is Dr. Peter Attia, M.D., a Stanford and Johns Hopkins-trained physician focusing on healthspan and lifespan and the host of The Drive podcast. We each present a... peer-reviewed scientific paper chosen because it contains novel, interesting, and actionable data. First, we discuss a paper on how bright light exposure at sunrise and throughout the day and dark exposure at night independently improve mental health and can offset some of the major symptoms of mental health disorders such as depression and anxiety. Then, we discuss an article that explores a novel class of immunotherapy treatments to combat cancer. We also discuss some of the new data on low-calorie sweeteners and if they are safe. This episode should be of interest to listeners curious about maximizing their vitality and longevity and to anyone seeking science-supported ways to improve mental health and lifespan. For show notes, including referenced articles and additional resources, please visit hubermanlab.com. Thank you to our sponsors AG1: https://drinkag1.com/huberman Eight Sleep: https://www.eightsleep.com/huberman BetterHelp: https://betterhelp.com/huberman Joovv: https://joovv.com/huberman LMNT: https://drinklmnt.com/huberman Momentous: https://livemomentous.com/huberman Timestamps (00:00:00) Dr. Peter Attia, Journal Club (00:02:40) Sponsors: Eight Sleep, BetterHelp & Joovv (00:07:14) Light, Dark & Mental Health; Retina (00:11:16) Outdoor vs. Indoor Light, Cataracts, Sunglasses (00:16:17) Tools: Sunrise & Sunsets, Circadian Rhythm; Midday Light (00:24:55) Tools: Night & Light Exposure; Waking Before Sunrise (00:31:05) Article #1, Light/Dark Exposure & Mental Health (00:36:50) Sponsor: AG1 (00:38:18) Odds Ratio, Hazard Ratio (00:45:43) Night vs. Daylight Exposure, Mental Health Disorders (00:51:35) Major Depression & Light Exposure; Error Bars & Significance (00:59:15) Sponsor: LMNT (01:00:39) Prescriptions; Environmental & Artificial Light; Red Lights (01:08:14) Nighttime Light Exposure; Sleep Trackers & Belief Effects (01:13:54) Light Directionality, Phone, Night (01:17:21) Light Wavelengths & Sensors; Sunglasses (01:20:58) Hawthorne Effect, Reverse Causality, Genetics (01:26:26) Artificial Sweeteners, Appetite (01:31:16) Natural Light Cycles, Circadian Rhythm & Mental Health (01:39:53) Article #2, Immune System & Cancer (01:43:18) T-Cell Activation; Viruses (01:50:41) Autoimmunity; Cancer & Immune System Evasion (02:00:09) Checkpoint Inhibitors, CTLA-4 (02:06:45) Anti-CTLA-4 Study Drug (Ipilimumab), Melanoma (02:12:07) Patient Population, Randomization, GP100 (02:18:09) Response Rate (02:22:52) Overall Survival & Response (02:28:38) Median Survival vs. Overall Survival, Drug Development (02:35:45) Gender & Dose (02:40:32) Adverse Events; Autoimmunity (02:46:42) Pancreatic Cancer; Aging & Immune System Health (02:53:57) Melanoma; Lynch Syndrome, Keytruda (02:58:43) Immunotherapy & Cancer Treatment; Melanoma Risk (03:06:26) Zero-Cost Support, Spotify & Apple Reviews, YouTube Feedback, Sponsors, Momentous, Social Media, Neural Network Newsletter Disclaimer
Transcript
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Welcome to the Huberman Lab Podcast, where we discuss science and science-based tools
for everyday life.
I'm Andrew Huberman, and I'm a professor of neurobiology and ophthalmology at Stanford
School of Medicine.
Today marks the second episode in our Journal Club series with myself and Dr. Peter Atia.
Dr. Peter Atia, as many of you know, is a medical doctor who is a world expert in all things health span and Dr. Peter Atia. Dr. Peter Atia, as many of you know, is a medical doctor
who is a world expert in all things health span
and lifespan.
He is the author of the bestselling book Outlive,
as well as the host of his own terrific podcast, The Drive.
For today's episode, Peter and I
each select a different paper to share with you.
We selected these papers because we feel they are both
extremely interesting and extremely actionable.
First, I present a paper that is about how light exposure during the morning and daytime
as well as dark exposure at night each have independent and positive effects on mental
health as well as the ability to reduce the symptoms of many different mental health disorders.
Now, I've talked before on this podcast and elsewhere about the key importance of seeing morning
sunlight as well as trying to be in dim light at night.
However, the data presented in the paper today really expands on that by identifying the
key importance of not just morning sunlight, but getting bright light in one's eyes as
much as is safely possible throughout the entire day and a separate additive effect
of being in as much darkness at night as possible.
I describe the data in a lot of detail,
although you do not need a background in biology
in order to understand that discussion.
And there's a key takeaway,
which is that if you can't get enough light in your eyes
during the daytime, you would be well advised
to get as much darkness exposure
at night.
In other words, light and dark have independent
and additive effects on mental health.
And during today's discussion, you'll learn exactly
how to apply light exposure and dark exposure
in order to get those benefits.
Then Peter presents a paper
about novel treatments for cancer.
I must say it's an extremely important conversation that everybody, regardless of whether or not you may have had cancer
or know somebody who's had cancer, ought to listen to. He highlights the current technology
of cancer treatments as well as the future technology of cancer treatments and the key
role that the immune system and the autoimmune system play in treatments for cancer.
I assure you that by the end of today's Journal Club episode, you will have learned a ton
of new information about light and dark and mental health, as well as cancer and the immune
system and treatments for curing cancer.
Before we begin, I'd like to emphasize that this podcast is separate from my teaching
and research roles at Stanford.
It is, however, part of my desire and effort to bring zero cost to consumer information
about science and science-related tools to the general public.
In keeping with that theme, I'd like to thank the sponsors of today's podcast.
Our first sponsor is AteSleep.
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I've spoken many times before in this podcast
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Today's episode is also brought to us by BetterHelp.
BetterHelp offers professional therapy
with a licensed therapist carried out online.
I've been going to therapy for well over 30 years.
Initially, I didn't have a choice.
It was a condition of being allowed to stay in school,
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The reason I know therapy is so valuable is that if you can find a therapist with whom
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Insights that can allow you to better not just your emotional life and your relationship life,
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Today's episode is also brought to us by Juv.
Juv makes medical grade red light therapy devices.
Now, if there's one thing I've consistently emphasized
on this podcast, it's the incredible role
that light can have on our biology.
And of course, I'm always telling people
that they should get sunlight in their eyes
as soon as possible after waking on as many days
of their life as possible for sake of setting
circadian rhythm, daytime mood focus, and alertness,
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Now, in addition to sunlight,
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And now for my discussion with Dr. Peter Atia.
Andrew, great to have you here for Journal Club number two.
I'm already confident this is gonna become a regular for us.
I'm excited.
I really enjoy this because I get to pick papers
I'm really excited about.
I get to hear papers that you're excited about
and we get to sharpen our skills at reading
and sharing data and people listening can do that as well.
So last time I went first,
so I think I'm gonna put you on the hot seat first
and have you go first and I'll follow you.
Okay. Well, I'm really excited about this paper
for a number of reasons.
First of all, at least by my read
is a very powerful paper in the sense that
it examined light exposure behavior
as well as dark exposure behavior.
And that's gonna be an important point
in more than 85,000
people as part of this cohort in the UK. I'll just mention a couple of things to give people
background and I'll keep this relatively brief. First of all, there's a long standing interest
in the relationship between light and mental health and physical health. And we can throw
up some very well agreed upon bullet points-upon-bullet points.
First of all, there is such a thing
as seasonal effective disorder.
It doesn't just impact people
living at really northern locations,
but basically there's a correlation between
day length and mood and mental health.
Such that for many people, not all,
but for many people,
when days are longer in the spring and summer,
they feel better.
They report fewer depressive symptoms.
And conversely, when days are shorter,
significantly more people report feeling lower mood
and affect, okay?
So there's a longstanding treatment
for seasonal affective disorder,
which is to give people exposure to very bright light,
especially in the morning. The way that that's normally accomplished is with these sad lamps,
seasonal effective disorder lamps, and those lamps are basically bright, meaning more than
10,000 lux lights that they place on their kitchen counter or at their table in the morning or in their office.
So they're getting a lot of bright light. That has proven to be fairly effective for the treatment of seasonal affective disorder. What's less understood is how light exposure in the middle
of the night can negatively impact mood and health. And so where we are headed with this is that there seems to be, based on the conclusions of this new study,
a powerful and independent role of both daytime light exposure
and nighttime dark exposure for mental health.
Now a couple of other key points,
the biological mechanisms for all this are really well established.
There's a set of cells in the neural retina,
which aligns the back of your eye. There's sometimes called intrinsically photosensitive.
Retinal ganglion cells are sometimes called melanopsin retinal ganglion cells. We'll talk
about those in a bit of detail in a moment. It's well known that those cells are the ones
that respond to two different types of light input, not one, but two different types of
light input and
send information to the hypothalamus where your master circadian clock resides. And then
your master circadian clock sends out secretory signals. So peptides, hormones, but also neural
signals to the brain and body and say, Hey, now it's daytime. Now it's nighttime. Be awake,
be asleep. But it goes way beyond that. These melanopsin,
insurance, the photosensitive retinal ganglion cells,
we know also project areas of the brain
like the habanula,
which can trigger negative affect, negative mood.
They can trigger the release of dopamine
or the suppression of dopamine,
the release of serotonin,
the suppression of serotonin.
And so they're not just cells
for setting your circadian clock.
They also have a
direct line, literally one synapse away into the structures of the brain that we know powerfully
control mood. So the mechanistic basis for all this is there. So there's just a couple of other
key points to understand for people to really be able to digest the data in this paper fully.
There are basically two types of stimuli
that these cells respond to.
One is very bright light as we just talked about.
That's why getting a lot of daytime sunlight
is correlated with elevated mood.
That's why looking at a 10,000 lux artificial lamp
can offset seasonal effective disorder.
By the way, just a couple questions on that.
How many lux does the sun provide on a sunny day at noon?
Okay, great question. So if you're out in the sun with no cloud cover or minimal cloud cover in the middle of the day at noon,
chances are it's over 100,000 lux. On a really bright day, could be 300,000 lux.
Okay, most indoor environments,
even though they might seem very bright,
I like to think of your kind of like a department store
with the bright lights, believe it or not,
that's probably only closer to 6,000 lux maximum
and probably more like 4,000 lux.
Most brightly lit indoor environments are not that bright
when it comes down to total photon energy.
Now, here's the interesting thing.
On a cloudy day, when you're outside,
it can be as bright as an average of 100,000 lux,
but it won't seem that bright because you don't quote unquote see the sun.
But it's also because when there's cloud cover,
a lot of those long wavelength of light,
such as orange and red light aren't coming through.
However, and this is so important,
the circadian clock, the super charismatic nucleus,
it sums photons.
It's a photon summing system.
So basically, if you're outside in 8000 lux, very overcast UK winter day,
and you're walking around hopefully without sunglasses, because sunglasses
are going to filter a lot of those photons out.
Your circadian clock is summing the photons.
So it's an integration mechanism.
It's not triggered in a moment.
And actually that the experiments of recording from these cells, first done
by David Berson at Brown were, you know, historic in the field of visual
neuroscience when you shown bright light on these intrinsically photosensitive
cells, you could crank up the intensity of the light and the neurons would ramp up their membrane
potential and then start spiking firing action potentials or long trains of action potentials
that have been shown to go on for hours.
And so that's the signal that's propagating into the whole brain and body.
Okay, so the important thing to understand is this is not a quick switch. That's why I suggest on non-cloudy days, we'll call them,
that people get 10 minutes or so of sunlight in their eyes
in the early part of the day,
another 10 minimum in the later part of the day,
as much sunlight in their eyes
as they safely can throughout the day.
But since you're a physician, I should just,
and you had a guest on talking about this recently,
when the sun is low in the sky, low solar angle sunlight,
that's really the key time for reasons we'll talk about in a moment.
And when the sun is low in the sky,
you run very, very little risk of inducing cataract
by looking in the general direction of the sun.
You should still blink as needed to protect the eyes.
It's when the sun is overhead,
and there's all those photons coming in quickly
in a short period of time
that you do have to be concerned about cataract and macular degeneration if you're getting
too much daytime sunlight.
So the idea is sunglasses in the middle of the day are fine, but you really should avoid
using them in the early and later part of the day unless you're driving into the sun
and you need, you know, for safety reasons.
Well, another question Andrew, if a is indoors, but they have large windows.
So they're getting tons of sunlight into their space.
They don't even need ambient indoor light.
How much of the photons are making it through the glass?
And how does that compare to this effect?
Yeah, in general, unless the light is coming directly through the window,
most of the relevant wavelengths are filtered out.
In other words, if you can't see the sun through the window, even if sufficient light is being
provided, that's insufficient to trigger this phenomenon.
That's right.
However, if you have windows on your roof, which some people do, skylights, that makes
the situation much, much better.
In fact, the neurons that in the eye that signal to the circadian clock and
these mood centers in the brain reside mainly in the bottom two thirds of the
neural retina and are responsible for looking up.
Basically they're gathering light from above.
These cells are also very low resolution.
So think of them as big pixels.
Uh, they're not interested in patterns and
edges and movement. They're interested in how much ambient light there happens to be. Now,
keep in mind that this mechanism is perhaps the most well-conserved mechanism in cellular organisms.
And I'll use that as a way to frame up the four types of light that one needs to see every 24
hours for optimal health. And when I say optimal health,
I really mean mental health and physical health,
but we're gonna talk about mental health
mainly today in this paper.
There's an absolutely beautiful evolutionary story
whereby single cell organisms, all the way to humans,
dogs, rabbits and everything in between
have at least two cone options. one that responds to short wavelength light, aka
blue light, and another one that responds to longer wavelength
light, orange and red. So your dogs have this, we have this, and
it's a comparison mechanism in these cells of the eye, these
neurons of the eye, they compare contrast between blues and
orange or sometimes blues and reds and pinks which are also all long wavelength light.
There are two times a day when the sky is enriched with blues, oranges, pinks, and
reds and that's low solar angle sunlight at sunrise and in the evening. These cells are uniquely available to trigger
the existence of those wavelengths of light
early in the day and in the evening,
not in the middle of the day.
So these cells have these two cone photopigments
and they say, how much blue light is there?
How much red light is there? Or orange light?
And the subtraction between those two triggers the signal
for them to fire the signal off
to the circuiting clock of the brain.
And that's why I say look at low solar angle sunlight early in the day.
What that does is it, what we call it is phase advances the clock.
This can get a little technical and we don't want to get too technical here, but think
about pushing your kid on a swing.
The period of that swing, the duration of that swing is a little bit longer than 12 hours.
Okay.
So when you stand closer to the kid, so your kid swings back and you give it a push, you're
shortening the period, right?
You're not allowing the swing to come all the way up.
That's what happens when you look at morning sunlight.
You're advancing your circadian clock.
Translate to English or non-nerd speak, you're making it such that you will want to go to bed a
little bit earlier and wake up a little bit earlier the next day.
In the evening, when you view low solar angle sunlight, so in the afternoon setting sun or
evening setting sun, you do the exact opposite, you're phase delaying the clock.
It's the equivalent of your kid being
at the very top of the arc.
And so it's gone, you know, maybe 12 and a half hour,
let's say 12 and a half hours is the duration of that swing.
And you run up and you push them from behind
and give them a little more push.
That's the equivalent of making yourself stay up
a little later and wake up a little later.
These two signals average so that your clock stays stable,
you don't drift, meaning you're not waking up earlier
every single day or going to sleep later every single day.
This is why it's important to view
low-cell angle sunlight in the morning
and again in the evening, as often as possible.
And it's done by that readout of those two photo pigments. Now, midday sun, which contains its bright light,
but you see it as white light,
contains all of those wavelengths that equal intensity.
So the middle of the day is the so-called circadian dead zone.
In the middle of the day,
bright light triggers the activation of the other ops
and the melanopsin, which increases mood,
increases feelings of well-being,
has some other consequences,
but you can't shift your circadian clock
by viewing the sun in the middle of the day
because it's in the circadian dead zone.
It's the equivalent of pushing your kid on the swing
when they're at the bottom of the arc.
You can get a little bit more, but not much.
And in biological terms, you get nothing.
So this is why looking at sunlight in the middle of the day is great, but it much. And in biological terms, you get nothing. So this is why looking at
sunlight in the middle of the day is great, but it's not going to help anchor your sleep
wake cycle. And if you think about this is incredible, right? Every organism from single
cells to us has this mechanism to know when the sun is rising and when the sun is setting.
And it's a color comparison mechanism, which tells us that actually color vision evolved first, not
for pattern vision, not for seeing beautiful sunsets and recognizing that's
beautiful or paintings or things of that sort, but rather for setting the
circadian clock. Now what if you only do one of these, Andrew, so what if you've
got constant exposure to low morning light, but your job prevents you from
doing the same in the evening or vice versa.
Yeah, a great question. Better to get the morning light because if you have to pick between low solar angle light earlier later in the day,
and keep in mind if you miss a day, no big deal. It's a slow integrative mechanism averaging across the previous two or three days.
But if you miss a day, you'll want to get twice as much light in your eyes that next morning. The reason it's better to do in the morning as opposed to the evening, although both would be to do,
best would be to do both, excuse me, is that most people are getting some artificial light exposure
in the evening anyway. And here's the diabolical thing. Your retina is very insensitive to light
early in the day. You need a lot of photons to trigger this mechanism
early in the day.
As the day goes on, retinal sensitivity increases
and it takes very little light to shift your circadian clock
late in the day.
Keep in mind also that if you do see afternoon
and evening sunlight, there's a beautiful study
published in Science Reports, yes, Science Reports,
two years ago showing that that can partially offset the negative effects
of artificial light exposure at night.
I think of this as your Netflix inoculation.
And the amount of melatonin suppression
from nighttime light exposure is halved
by viewing evening setting sun.
Now, keep in mind, you don't need to see the sun
cross the horizon, it can just be
when it's low solar angle.
So you're looking for those yellow, blue,
or blue, pink, blue, red contrast.
And on cloudy days, believe it or not,
they're still there, just you don't perceive
as much of it coming through.
So that's three things that we should all strive to do.
View low solar angle sunlight early in the day,
view solar angle sunlight later in the day,
and get as much bright light in our eyes
as we safely can, ideally from sunlight throughout the day view solar angle sunlight later in the day and get as much bright light in our eyes as we safely can ideally from sunlight throughout the day. And if you can't do that, perhaps invest
in one of these sad lights so that they can be a bit expensive. There are a couple of companies
that are starting to design sunrise simulators and evening simulators that are actually good,
that actually work. But right now my read is that aside from one company out there,
which by the way, I have no relationship to it's called the two O light T U O.
And that light bulb was developed by the biologists of the university of Washington
who basically discovered these color opponent mechanisms.
Um, those lights are not particularly expensive, but they're, um but they do seem to work.
In fact, the study that is emerging, again, unpublished data, seems to indicate that if
you look at it for more than five or six minutes, it can induce a mild euphoria.
That's how powerful this contrast is.
What they did there in that light, I'll just tell you the mechanism, is they figured out
that when most people look at low solar angle sunlight in the morning, they're getting 19 reversals of blue orange
per second.
So when you look at this light, it looks like a barely flashing white light, but it's reversals
of orange and blue orange and, you know, red and blue and it's happening.
And so what is the what is the person looking at it perceive?
Well, I've used one of these.
It just looks like a flickering light.
And of course there's always the potential
of a placebo effect.
Well, that's what I was gonna say.
Is there a way to control for that
by having something that looks the same to the user,
but of course is not producing the same photo effect?
Yeah, well, they've done that with the 10,000 lux sad lamps
and which most people use to try and induce sunrise simulation
in their home. But keep in mind that sunrise gives you this comparison of short and long
wavelength light. Just a bright 10,000 lux light triggers one of the options that,
but it won't set your circadian clock. So most of the sad lamps that are out there are activating
only one of the mechanisms in these cells that's relevant and not the one that's most
relevant. So I'm excited about what 2O is doing. I think that, and again, I have no relation
to them except I know the biologists who did the work that provide the mechanistic logic
for that engineering. I still think we're in the like, the really like early days of this stuff.
What should be done is to have this stuff
built into your laptop, right?
It should be built into your phone
and hopefully it will be.
Now, I mentioned this color contrast thing
in sunrise and sunset.
I mentioned the bright light throughout the day,
but there's a fourth light stimulus
that turns out to be really important.
And this will provide the segue into the paper.
Turns out that dark exposure at night,
independent of light exposure during the day
is important for mental health outcomes.
Now, most people think dark exposure,
how do I think about that?
Well, it is dark yet.
Absence of light exposure.
It's the absence of light,
but what this paper really drives home
is that people who make it a point to get dark exposure at night,
aka the absence of light at night, actually benefit even if they're not getting enough sunlight during the day.
And this is especially true for people with certain mental health issues.
So I don't think we can overstate the value of accurately timed light exposure to the eyes
in the context of mental health.
I think there's so much data by now.
I will say, however, that some people seem more resilient
to these light effects than others.
Meaning some people also don't suffer from jet lag too much.
Some people can stay up late,
get a lot of bright light exposure in the middle of the night
and during the day, they've got their sunglasses on all day, and they're in a great mood all the
time. Other people are more susceptible to these sorts of things, and we don't know whether or not
polymorphisms underlie that. I personally am very sensitive to sunlight in the sense that if I don't
get enough sunlight, I don't feel well after a couple of days, but I'm less sensitive to light exposure at night, for instance. But I think
it is perhaps, this is a big statement, but is perhaps the most fundamental environmental stimulus
for levels of arousal and alertness, which correlate with all sorts of, you know,
neuromodulator and hormone outputs. And so none of this should come as any surprise.
I will mention one last
thing. There was a study published gosh over 10 years ago now from Chuck Zeissers lab at Harvard
Medical School is a phenomenal lab exploring circadian human health behavior. He's just considered a
no pun, a luminary in the field. But there wasn't a study that was in error where they had published
in Science Magazine
that light shown behind the knee could shift circadian rhythms.
And that paper was retracted.
And a lot of people don't know that it was retracted.
Light exposure to the eyes is what's relevant here.
And as far as we know, the color of one's eyes, the darkness or lightness of one's eyes,
bears no relevance on their sensitivity to these types of mechanisms and on and on.
So, so one question, one comment.
The question again is going back
to the morning, evening, light.
And I spend a lot of time looking at those types of skies,
for example, just because of the nature of my hobbies.
Right, because I'm always doing archery in the morning
and rucking in the afternoon.
So it's not uncommon that I'm seeing both of those.
How relevant is it that the sun be above the horizon?
So for example, it begins to get light about in 30 minutes before sunrise. And then, you know,
right, it's so sun rises at 730. First light is seven. And then, you know, sort of 715 to 730 is
actually quite bright. I mean, you can see anything and everything and the same is true at sunset.
So does that 30 minutes pre,
or when sun is beneath the horizon,
constitute part of that 10 minutes?
It does.
I mean, in an ideal circumstance,
you'd get outside and see the sunrise every day
and you'd see the sunset every day, even on cloudy days.
Some people like myself wake up before the sun comes up.
In which, and I get this question all the time.
Well, in the absence of powers to make the sun rise faster,
which I'm not aware anyone has, certainly not me.
I think the best thing to do is simply to turn on
as many bright lights as you can indoors
to trigger that melanopsin mechanism.
If you wanna be awake,
if you wanna stay asleep or sleepy, then keep them dim
and then get outside once the sun is starting to come out. Some people wake up after the sun has risen, right? In which case,
get what you can. And some people wake up 10am or noon, in which case you can still get the bright light
exposure, but you won't shift your circadian clock. Now, in the evening, especially in the winter
months, it's important to look west and try and get some sunlight in your eyes in the evening, especially in the winter months, it's important to look west and try
and get some sunlight in your eyes in the evening.
If you've ever gone into the clinic, for instance, at two o'clock in the afternoon, after lunch,
and then in the winter, and then come out and it's dark when you're walking into your
car, it's a kind of eerie feeling.
That sort of eerie feeling may correlate with the fact that you missed a signal.
Your brain is trying to orient your brain and body in time.
And that's what all of this is, right?
It's trying to orient in time.
And again, some people are more susceptible to that than others.
Some people might like that feeling of, oh, I went in when it was bright and I come out when it's dark.
But the vast majority of people feel better when they're getting this morning and evening sunlight exposure.
And this is especially important in kids.
All right, this is one of the things that, you know, this paper points out and there
are good data that people are spending approximately 90% of their time indoors nowadays, daytime
time indoors.
And those indoor environments are simply not bright enough.
You think, oh, there's all these bright lights.
And some people are putting blue blockers on in the middle of the day,
which is the worst thing you could possibly do.
If you're gonna wear blue blockers,
and I don't think they're necessary,
but if you're going to wear them,
you'd wanna wear them at night.
And in the evening, you don't need to wear blue blockers,
you just simply should dim the lights
and ideally have lights that are set
a little bit lower in your environment,
which the Scandinavians have been doing for a long time.
So, you know, kill the overhead lights
and don't obsess about bright light exposure
in the middle of the night.
In fact, for a long time, I and some other people
were saying, oh, you know, even just a brief flash
of light in the middle of the night
can quash your melatonin.
That's true.
But the other time in which you're
in this quote unquote circadian dead zone
is in the middle of the night. You can't circadian dead zone is in the middle of the
night. You can't shift your circadian clock in the middle of the night. But you know,
all of this gets down to inter weaving rhythms of light sensitivity, temperature, hormone
output cortisol. I mean, there's a whole landscape of circadian biology. This paper, which was
published in a new journal I'm really excited about called Nature Mental Health.
This journal was just launched recently, is entitled
Day and Night Light Exposure Are Associated with Psychiatric Disorders
and Objective Light Study in More Than 85,000 People.
Now I have to say that I think the title of this paper is terrible.
Sorry folks at Nature Mental Health, because if one just read the title, it sounds like day and night light exposure associated with psychiatric
disorders. If this were a newspaper headline, you'd be like, oh my goodness, what are you supposed
to do? But that's not the conclusion. The conclusion is that getting a lot of sunlight exposure during
the day and getting a lot of dark exposure at night
is immensely beneficial for psychiatric health
and in a number of ways.
Now, I'm not one to bring up another paper unannounced,
but I will say that this paper built off a previous study
entitled, Time Spent in Outdoor Light is associated
with mood, sleep, and circadian rhythm related outcomes.
And that was a cross-sectional longitudinal study in 400,000 biobank participants. So this UK biobank is an incredibly valuable resource.
And there are now multiple studies establishing that one's pattern of light exposure is extremely
important. Now, the previous study in 400,000 participants basically nailed home the idea that the more time you spend outdoors,
the better is your mood, the better is your sleep, the better is the rhythmicity of your
sleep wake cycles and on and on. Something that I think even though people will say,
we've known that for thousands of years, needed scientific substantiation. This new study
essentially looked at the relative contributions of daytime light exposure and nighttime dark exposure.
And they did that on a background of looking in particular people who had major depressive disorder, generalized anxiety, PTSD, bipolar disorder.
Here's the basic takeaway.
And I'll quote them here.
And then I'll tell you my interpretation.
Here I'm quoting, avoiding night at light
and seeking light during the day.
I love that word seeking.
Maybe a simple and effective non-pharmacologic means
for broadly improving mental health.
So that's a pretty bold statement, right?
And I love that they say seeking
because it implies that people aren't reflexively
getting the light exposure that they need, this it needs to be a practice much like zone two cardio or resistance training.
Okay, so what did they do in this study? So basically they gathered up 100,000 people or so it eventually was pared down to about 86,000 participants because some just didn't qualify or didn't report their data back.
86,000 participants because some just didn't qualify or didn't report their data back.
They equipped them with accelerometers on their wrist and those wrist devices also could measure ambient light. Now that's not a perfect tool because what you'd love to do is measure ambient
light at the level of the eyes. By the way, will somebody design an eyeglass frame that changes
color when you've gotten sufficient light from sunlight during the day and then and then at night is a different color. And then if you're getting
too much light exposure, we'll go to a different color frame. This has to be possible so that
you don't have to wonder if you got enough light during the day. And of course, if it's
at the level of the eyes, then you know, that's what's landing at the eyes.
Yeah. And it's let I mean, that's what I was going to ask you about that. Do these wrist
based devices potentially get covered by clothing and some like, you have
your sleeves down, I have my sleeves up.
Yeah, they had it on the outside of the sleeve, but they asked that people just keep it on
their dominant hand.
It's not perfect.
But in some ways it's kind of nice that it's not perfect.
We could turn that disadvantage into advantage by thinking, you know, when the person is
out and about, they're not often looking right at the sun.
You know, if you're talking to a colleague
under an overhang, for instance.
So it's not perfect.
It's directionally.
It's directionally right.
Okay, and then they had two hypotheses,
two primary hypotheses.
One, that greater light exposure on the day
is associated with lower risk for psychiatric disorders.
And two, second hypotheses, greater light exposure at night is associated with higher risk for psychiatric disorders and two second hypotheses, greater light exposure at night
is associated with higher risk for psychiatric disorders
in poorer mood.
This is oh so relevant for the way we live now,
people on screens and tablets in the middle of the night.
Okay, then they collected information
about how much light exposure people were getting,
as well as their sleep and their activity and so on.
I should mention this was done in males and females.
It was a slightly older cohort than one is used to seeing people in their 50 activity and so on. I should mention this was done in males and females. It was a slightly older cohort.
Then one is used to seeing people in their 50s and 60s.
They had psychiatric diagnosis information.
And then they divided people into,
essentially two groups, but they had a lower,
so a Q1 and a Q2, a lower quartile.
That meant people that were getting less daytime light,
as opposed to the third and fourth quartile,
more daytime light.
They also had a nighttime light exposure evaluation
and they had people were in the low Q1 and Q2,
so these people are getting less nighttime light
versus Q3, Q4, more nighttime light.
Nicely, they also looked at sleep duration
and they looked at photo period,
meaning how long the days were for those individuals,
how active they were.
Look, 10 hours a day, 14 hours a day,
because the more active you are,
the more opportunity for light exposure you have during the day
or night, for instance.
Okay, so they had, I would say, fairly complete data sets.
Then, and I'm just going to kind of hit the top contour of what they did in each.
And sorry, sleep duration, sleep efficiency, etc.
Was determined off the accelerometer.
That's right, as well as self-report.
Yeah.
Not ideal, right?
You'd love for people to be wearing a woot bander or a ring or something of that sort.
But this was initiated some time ago, so they either didn't have access to that technology
or for whatever reason didn't select it.
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Then what they did is they got,
they have information on who has major depressive disorder,
who has PTSD, generalized anxiety,
bipolar, psychosis, et cetera.
And then they ran three models.
And you can tell me what you think about the power
of these models, but you know, somebody who thinks
about the mechanistic aspect of all of this a lot,
but not somebody who's ever run this type of study,
I'd be really curious.
Model one, examined the unadjusted association
between day and nighttime light exposure
and psychiatric outcomes.
So just basically asking,
is there a relationship between how much light you get it
during the day and how much light you get at night
and how bad your depression is or anxiety is, et cetera.
Looking at just a standard ratio of the probability
that you have a certain symptom or set of symptoms
versus you don't given a certain amount of light exposure.
Model two, adjusted for the age of the person,
their sex and ethnicity and photo period.
So they looked at how long the days were
in that given person's region of the world.
And then model three also-
Were these people were all in the UK
or were they around the world?
They were all in the UK, as far as I know.
And then model three adjusted for employment.
So employed versus unemployed,
which if you think about it as pretty important,
like you say, well, an unemployed person
has a lot more time to control these variables,
but an employed person who's doing shift work does not, right?
And they incorporated information
about employed versus unemployed physical activity,
which turns out to be very important,
and then things like shift work, et cetera.
And so what we can say very safely is that
the outcomes with each of these models, the results were very similar.
So we don't want to discard the differences
between those models entirely, but in my read is
in every figure of the paper, it doesn't seem like model one,
two or three differ from one another
in terms of total outcome.
Yeah, that's an unusual aspect of this paper.
So these
adjustments are very standard, right? So that's this is a
classic tool that's used in most epidemiology, because you
don't have randomization. So once randomization is out the
window, you know, you like so for example, the paper I'm going
to present is based on an RCT, there will be no models. It's
just here the data, right?
Yeah, here they're asking people what what do you do? Report back to us. We're going to measure
your light exposure, but no one was assigned any groups or swap. Whatever quote unquote controls
are there. They're really not there. It's just comparisons between groups.
So what is interesting to me is that it's exactly as you said and we'll make all these figures available in
addition to the papers. But I mean, it's very unusual that there's no difference between
the unadjusted and the adjusted models. And as you say, there's probably two places out
of 30 when you look at all the different quartile comparisons where you might creep from,
you know, statistically significant just out of it or just into it. But yeah, you could simplify
this figure to completely by just showing one of the models and you would be, you know, getting 95%
of the information, which is, you know, I mean, I think in one way that suggests
information, which is, you know, I mean, I think in one way that suggests that there's less dependency on those variables. Of course, it still doesn't address probably the greatest
question I have here, which I'm sure we'll get to at some point as you continue.
Yeah. So I'm very curious what that question is, but I'll suppress my curiosity for the moment.
So if we look at figure two of this paper, and I realize a lot of people are listening and they're not able to look at this,
although we have posted the figures on the YouTube versions of this, just want to make clear what's going on just for those that are listening.
Essentially what they're looking at is what they call the odds ratio, which is the probability of
something happening in one group versus divided by the probability of something happening in
another group. I guess by way of example, if you were going to look at the odds ratio of
the probability of somebody getting lung cancer if they smoke versus probability somebody getting
lung cancer if they don't smoke. So odds ratios and hazard ratios are often confused.
They're very similar and odds ratios generally refer
to a lifetime exposure, whereas a hazard ratio
is defined over a specific period of time.
But the math is still effectively the same.
And using the example you gave,
if you took the odds ratio of death,
so let's talk all cause mortality
for a smoker versus a non-smoker,
and the answer were 1.78, I'm making that up,
but that's directionally correct.
1.78 as an odds ratio means there's a 78% chance
greater of the outcome of interest, in this case death
by any cause in the affected group,
which would be the smokers.
So odds ratio of two is 100%, and odds ratio of three is 200%.
So the math is take the number, subtract one, and that's the percent.
You know, figure two of this paper is one of the key take-homes.
They essentially look at the odds ratio of people who are in the, let's say that, let's
just look at the nighttime light exposure.
And just remind me, Andrew, because everybody else watching, that every one of these is
showing second, third, fourth as your x-axis.
Right.
Meaning they're all being compared to the first quartile.
That's right.
And the first quartile is lowest light exposure or highest light exposure.
Lowest.
Okay. Well, we have to, nighttime. With a different shape between day and night. That's right Lowest, well we have to,
Night time.
It's a different day and night.
That's right.
Okay, so we restate it.
Sure, so if we look at,
what is your risk of a psychiatric challenge,
broadly speaking, well,
panel A is major depressive disorder.
If you are in the second quartile,
third quartile or fourth quartile
of nighttime light exposure. So second being fourth quartile of nighttime light exposure.
So second being the least amount of nighttime light exposure,
third being more nighttime light exposure,
and fourth, the most nighttime light exposure
relative to the first quartile.
This is just a stupid thing.
Like if I were doing this figure,
if you were doing this in a lecture,
you know what you would do to make it so easy?
You would draw arrows on it that say increasing light exposure at night,
decreasing light exposure in the day. It's the same information. It just makes it easier for the reader to understand.
Absolutely.
But then maybe the teaching point I think is for people when they review articles, like don't be afraid to do that and just kind of like,
wait, what is this?
Yeah, exactly. So it's like, I draw the arrow.
That's increasing light, that's decreasing light,
and that's how I can pay attention
to what's actually happening.
Right, and I'm actually in touch with the editorial staff
at Nature Mental Health, although they don't know
that I'm covering this paper until after this comes out.
You know, I think one thing that scientific journals
really, really need to do is start making the readability
of the articles better for non-experts.
I mean, chances are, if you can't understand a graph,
and this is true for everybody,
chances are there's a problem with the way it's presented.
Put it on them, but then of course try and parse it
because rarely, if ever, is it all spelled out clearly.
But anyway, that's what we're trying to do here.
So yeah, the way I would have done it is say,
second quartiles, low amounts of nighttime light exposure
and define what that is.
You know, third quartile is more light exposure
and then fourth maximum amount of light exposure at night.
And basically what you see is that the probability
of having worse major depressive symptoms
linearly increases as you go from the second to third
to fourth quartile.
So more nighttime light exposure, worse for you.
And there's a dose response, if you will, of the effect.
Now, we can march through or describe figure two
pretty quickly by saying the same thing is true.
And now we're just talking about nighttime light exposure
for generalized anxiety disorder.
So that's panel C.
Bipolar disorder, although the difference
between the second and third quartile
and bipolar disorder isn't as dramatic.
Once you get up to the fourth quartile,
bipolar symptoms get much worse
when people are getting nighttime light exposure.
I really want to emphasize that point because they go on in the discussion of this paper
to reemphasize that point several times. In fact, they say that while light exposure during the day,
of course, we will go into the data is beneficial for mental health. For people with bipolar disorder,
it seems that light exposure at night
is especially problematic,
independent of how much sunlight
they're getting during the day.
So you're bipolar, the person with bipolar disorder
who's struggling with either a manic or depressive episode
who's making a point to get sunlight during the day,
who's also getting light exposure at night,
is making their symptoms worse.
And keep in mind, they couldn't completely control this,
but this is largely independent of things like sleep duration.
So that doesn't necessarily mean that the person sleeping
less, although in a man a man a episode, presumably they are,
it's independent of exercise.
It's independent of a bunch of other things
because any logical person will hear this and say,
okay, well they're getting more light at night
because they're doing a bunch of other things,
but it's largely independent of those other things.
Likewise, the symptomology of PTSD gets far worse
with increasing light exposure at night.
Self-harm really takes a leap from being fairly,
I don't wanna say minimal, at the second and third quartile.
So low and let's say medium, I'm using some, I've taken some liberties here, but
low and medium amounts of artificial light exposure at night.
Then for people who get quite a lot of nighttime light exposure, self-harm goes
up and probability of psychotic episodes goes up or psychotic symptoms.
Now, what's nice is that the, what's nice about the data is
that the exact inverse is basically true for daytime light exposure, although not across the board,
we can generally say that for major depressive disorder, generalized anxiety, bipolar symptoms,
there it's a little more scattered, PTSD and selfarm, the more daytime light exposure, ideally from sunlight, because
that's actually what's being measured in most cases, we could talk about how we know that,
is going to approximately linearly drop the probability or the severity of these symptoms.
And we could just explain again that the odds ratios now seem to be going down. So an odds ratio of 0.7 now refers to a 30% reduction in the variable of interest here.
Exactly. Now the psychosis, a panel laugh which focuses on psychosis I think is also worth mentioning
in a bit more detail. There's a fairly dramatic reduction in psychotic symptoms
as one gets more daytime light exposure,
independent of nighttime light exposure.
There's a well-known phenomenon called ICU psychosis,
which is that people come into the hospital
for a broken leg or a car accident.
Maybe they were getting surgery from Peter back when
for something totally independent.
They're housed in the hospital
and as anyone who's ever been in a hospital
as a patient or visitor knows,
the lighting environment in the hospital
is absolutely dreadful for health.
Just dreadful.
I mean, people often complain about the food
in the cafeteria as being unhealthy.
That's often not always true.
Not always true.
But the lighting environments in hospitals
is absolutely counter to health.
Especially in the intensive care unit.
Yeah, right.
I think the intensive care unit at Hopkins,
the main one, the main SICU didn't have windows.
People who go into the hospital with a brain injury
or with a stroke or something,
I get contacted all the time,
even though I'm not a clinician,
what should I do for my kid, my parent?
I always say, get them near a window
and start to the best of your abilities
controlling their sleep wake cycle.
Now, oftentimes there's nurses coming in
and taking blood tests
and measuring pulses in the middle of the night.
That's disruptive.
There's bright light, not just blue light.
That's disruptive.
It's noisy.
That's disruptive.
ICU psychosis is when non-psychotic individuals start having psychotic episodes in the hospital
because of nighttime light exposure
and in some cases lack of daytime sunlight.
We can say that with some degree of confidence
because when those people go home,
even though sometimes their symptoms
for what brought them to the hospital
in the first place get worse,
their psychosis goes away.
Now, and it's independent of medication.
So let's just be really direct.
There is a possibility that we are all socially jet lagged,
that we are all disrupting these mood regulation symptoms,
the systems, excuse me,
by not getting enough daytime light
and by getting too much nighttime light.
If we wanna look at just some of the bullet points
of the takeaways, and Peter, thank you,
you highlighted a few of these, but.
Can we just go back to this figure two for a second?
Oh yeah, sure.
There's a handful of things that really jump out.
I had a feeling Peter was gonna wanna dig in the day.
Yeah, yeah, let's do it, let's do it.
And again, I normally wouldn't make so much hay out of this
except for the fact that they're so tight. But there are
a few that really stand out. And again, I love this figure. I would have labeled it
a little differently to make it completely user friendly. But nevertheless, the increasing
light at night and the impact on depression. Pen light. Let me be really technical in what I say.
And the relationship or correlation to depression
is very strong.
The relationship to light and self-harm
in the upper quartile,
so when you take those 25% of people
with the most nighttime light,
that relationship to self-harm is interesting
and completely uncoupled from
the other 75%. That's interesting.
By uncoupled, you mean that at the lower levels of light exposure at night, you're not seeing
an increase in self-harm.
Not whatsoever.
And then once you get to that fourth quartile.
It's a big step.
It's like a 30% greater risk of self-harm.
That's right. Yeah, so it's totally flat. The first, second, third quartile, no different,
and then fourth big jump.
And then the inverse relationship, right? As light increases during the daytime,
you see this reduction in self-harm, interesting.
The PTSD relationship based on nighttime light
and the psychosis relationship based on daytime light.
Those are the ones that really jumped out to me.
I think anxiety relatively less impressive
here and bipolar disorder didn't seem as strong as well. So I think those are the big ones that
I agree that jumped out to me. Yeah, I agree. There's a bit more scatter on generalized anxiety and
the degree of significant change is not as robust.
In other words, getting a lot of daytime light,
ideally from sunlight,
is not necessarily going to reduce your levels of anxiety.
Getting a lot of nighttime light exposure
is not increasing nighttime anxiety that much,
although 20% is not nothing for nighttime light exposure.
But yeah, the psychosis major depression
and self-harm are really, you know, they leap out.
Actually, maybe we can just drill a little bit deeper
on major depression.
And basically when you go from the second to third quartile
of nighttime light exposure,
so more of nighttime light exposure,
you basically go from no significant increase
to almost a 20% increase. And then as you get
up to the fourth quartile, so the most nighttime light exposure, at about 25%
increase in major depressive symptoms. That's no joke. And I think that we,
you know, we were to, I mean, we don't have the data right here, but if we were to look at like
standard SSRI treatment for major depression, you know, um, people debate
this pretty actively, but, um, light is, is a very potent stimulus.
And the timing of light is critical because on the, the inverse is also true
as you get to the fourth quartile of daytime light exposure, you get about a
20% reduction
in major depressive disorder.
What I like about a study like this
is that it puts the error bars so easy to see on the data.
And why is that interesting?
Well,
there's,
there's a belief that bigger is always better
in sample size.
And we often talk about that
through the lens of power analysis, right?
So how many subjects do we need
to reach a conclusion that is powered to this level?
And that's true, but what I don't think gets discussed
as often is the opposite of that,
which is what if you overpower a study?
In other words, what if the power analysis says to be
to have a level of power at 90% you need a thousand subjects and you say great, we're gonna do 10,000 subjects?
Well, you're clearly powered for it, but you might be overpowered and people might say well
Why would that be a bad thing? It could be a bad thing because it means you are very likely to reach statistical significance
in things that might not be actually significant. And so one thing about this study that is just a
quick back, like kind of a quick and dirty way to tell that it's probably not overpowered is
probably not overpowered is that you have varying lengths of error bars.
And what that tells me is that, and again, this is not like a formal statistical analysis. It's just kind of like a back of the envelope,
statistical analysis. If you look, for example, at self harm in the top quartile,
you actually have pretty big error bars. In fact,
all the self harm have sort of slightly bigger error bars.
And yet when you look at, for example, the depression, even though the air bars aren't all the same size, they're tighter. In fact,
when you look at the relationship between depression and daytime light, the air bars are
really, really small. So that just gives me confidence that there is variability in this,
which paradoxically you kind of want to see, because it tells me that this wasn't just done,
you know, there's, I think you said 8,000 subjects
were in this and I realized-
More than 86,000.
86,000, sorry.
Yeah, you realize that it wasn't that,
oh, this should have been done with a tenth of that
or a half of that.
And we're picking up signal that is statistically relevant
but clinically irrelevant.
Yeah, thanks for that point that I didn't pay attention to that.
I mean, I paid attention to the error bars, but I didn't know that.
So thank you, I'm learning too.
And I suppose for people that are listening, we can just give them a sense of what the error bar ranges are.
For self-harm, they're running as much as 20% either side of the mean, the average.
And for major depression, it looks like it's more like,
let's say, eight to 10%. If that maybe five. Right. So yeah, I see what you're saying. So when you
get a very large sample size, you're going to have some outliers in there. And you can mask those
outliers just by having so many data points, right?
Yeah, because these error bars directly tell you whether or not you're statistically significant.
So what's really nice about this type of graph and you see these in there's gonna be a graph in my
paper where you see the same analysis. They're always drawing the 95% confidence interval on
the on the data point. And if the 95% confidence interval
does not touch the line of unity,
which in this case is the Hodds ratio of 1.0 or the x-axis,
then you know it's statistically significant
to the confidence interval they've defined,
which is almost assuredly 95%.
Sometimes they'll make it tighter at 99.
And so that's why you can just look right at these and go,
oh, look, in depression, the second quartile
didn't reach statistical significance
because the error bars are touching the line,
just as the case for the second and third quartile
for self-harm.
But when you look at the fourth quartile,
you can see that the lower tip of the error bars
isn't anywhere near unity.
And so we know without having to look up the p-value
that it's smaller than either 0.05 or 0.1
however they've defined it.
And it's really amazing when you see these
overpowered studies, which are easier to do
epidemiologically where the P value ends up
being microscopic, they can drive their P values
down to anything low because sample size can be infinite.
But you can see that it's just like the error bar
is just skimming above the unity line,
but it's so, so, so tight.
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And that correct ratio of electrolytes is extremely important
because every cell in your body,
but especially your nerve cells, your neurons,
relies on electrolytes in order to function properly.
So when you're well hydrated
and you have the appropriate amount of electrolytes
in your system, your mental functioning
and your physical functioning is improved. I drink one amount of electrolytes in your system, your mental functioning and your physical functioning
is improved.
I drink one packet of element dissolved in about 16
to 32 ounces of water when I wake up in the morning,
as well as while I exercise.
And if I've sweat a lot during that exercise,
I often will drink a third element packet dissolved
in about 32 ounces of water after I exercise.
Element comes in a variety of different flavors,
all of which I find really tasty.
I like the citrus, I like the watermelon,
I like the raspberry, frankly I can't pick just one.
It also comes in chocolate and chocolate mint,
which I find taste best if they are put into water,
dissolved, and then heated up.
I tend to do that in the winter months
because of course you don't just need hydration
on hot days and in the summer and spring months,
but also in the winter when the temperatures are cold and the environment tends to be dry. If you'd like to try Element,
you can go to drinkelement spelled elementi.com slash huberman to try a free sample pack. Again,
that's drinkelement.com slash huberman. One thing that I hope people are taking away from this study is that imagine you're somebody who has a very sensitive
circadian mood system. Well, that would mean you need less daytime light exposure to feel good
or less bad, but it also means that you might need very little light at night in order to
negatively impact your mood systems.
And in fact, they make this argument in the discussion
as an interesting point that I think is worth mentioning
because here, again, what I like about the study
is that they've separated day and nighttime light exposure.
Turns out that many of the drugs that are used
to treat bipolar disorder reduce the sense are are effective
Perhaps in part because they reduce the sensitivity of the light sensing circadian
apparatus
Now that's interesting right if you think about this. Okay, so these are drugs that can ameliorate some of the symptoms of bipolar
Perhaps in part by reducing the extent to which nighttime light exposure
can relieve bipolar symptoms, excuse me, can exacerbate bipolar symptoms.
Conversely, there's evidence that people who take certain antidepressants may suppress
the ability for daytime light to positively impact the mood systems of the brain.
Now of course, we don't want people halting their medication
on the basis of that statement alone, please don't,
you know, talk to your psychiatrist.
But if we know one thing for sure,
it's that if you want a significant outcome
and a paper as a scientist,
give a drug, any drug, and look at the amount
of rapid eye movement sleep or the circadian
cycle, pretty much any drug alters a circadian rhythm for better or worse. But if we start
to think about which medications might adjust our overall sensitivity to light, sometimes
this could be a good thing. You think less sensitivity to light. Well, for people who
have bipolar disorder, the amount of daytime light exposure isn't that important for their overall mood regulation,
but the amount of nighttime light exposure really is.
In other words, darkness for eight hours every night
should be viewed, in my opinion,
as a treatment for bipolar disorder,
not the only treatment,
but it's also clear that we should all be avoiding
really bright, extensive,
really bright nighttime light exposure.
I mean, if anything, you know, my takeaway from this study is that darkness at night
is the fourth key light stimulus. Now, a couple of things, very bright moonlight, very bright
candlelight is probably only like, gosh, three to 50 lux.
What?
When you go outside on a brightly lit full moon night, I encourage people to download
this free app.
I have no relationship to it called Light Meter.
It gives you a pretty good read of what the lux are in that environment.
By the way, a lot of people don't realize this.
They think you just tap the button and then it tells you how many lux.
You hold it down.
It's kind of fun.
You can scan around the room and see how many luxe are on average
coming from that location or outside.
Go out on a really bright moonlit night.
I mean, we should have a full moon tonight.
Yeah, let's do it.
Yeah, you're not going to get above 100 luxe.
That's incredible.
You're sitting at a candlelight dinner with your spouse or with friends.
And it's clearly bright enough to see them put that lux meter right up not too close to the flame.
50 to 200 locks. I had an interesting experience a couple of months ago on an elk hunt where it was
a full moon which actually makes the hunting not so great but it was the first time I've ever
noticed my shadow in relation to the moon. That's how bright it seemed the light was.
This is Halloween appropriate.
Since we're coming up, we're recording this
close to Halloween.
So, it's remarkable.
It's super interesting to think it could be that dim.
Campfire, you know, in firelight,
you think, okay, gathering around a campfire,
then okay, you know, everyone's circadian rhythm
must have been disrupted for ages
before the development of electricity.
No, no, those campfires are extremely bright, but they're not that bright compared to a
very densely overcast day. And what is your phone if you don't use any sort of light mitigating
tech on it? Well, distance matters. But at the distance we're holding it. Yeah. With, so with all the, the wavelengths cranked up.
So no, uh, there is a nice feature intrinsic to the phone where you can
eliminate the blues at night or, you know, this kind of thing.
But if you crank it up to maximum light intensity, probably something like,
you know, 500 to 1000 lux.
Now, keep in mind though, it's additive, right?
So it's over time.
So lux is a measure of, I think it relates back to
Candela's is the amount of light shown.
And I think it's like the one meter away and there's a
squaring and a falling off of distance.
We can look it up.
Um, these are old measurement, old school measurements
converted to Lux.
But keep in mind that if you're looking at your phone or
tablet at 800 Lux or 500 Lux in the evening, you do that for two hours, where you're summing quite a lot of photons. Now it is true. And I do want to be fair to the biology. And it'd be dishonest to say anything different. You know, we've hammered on people about not shifting their circadian rhythm with light at night. But we know that the middle of the day and the middle of the night are circadian dead zones. You can't shift your circadian
rhythm that well in the middle of the day and the middle of the night, but you can provide
a wake up signal for your body and brain. It's really that sunrise and sunset that are
critical. That's why I said there are four things. See sunrise or sun rising. You don't
need to see it cross the horizon. Sunset, bright light during the day,
minimize light exposure at night.
And you don't need pitch black.
In fact, pitch black probably just increases
the frequency of injury.
You know, I get up in the middle of the night
to use the bathroom probably once.
I think it's normal.
I go back to sleep.
You know, if it were pitch black,
I'd probably injure myself.
So just dim it down.
Some people use red lights.
You know, our friend Rick Rubin.
Our mutual friend. Yeah, Rick Rubin is like. Can we tell a funny story about Rick? Yeah, of course it down. Some people use red lights, you know, our friend Rick Rubin. Our mutual friend.
Yeah, Rick Rubin is like.
Can we tell a funny story about Rick?
Yeah, of course, of course.
You know this story, but just in case Rick's listening,
he'll appreciate this.
You know, when Rick was here staying last summer,
he's up in our guest house
and he came down after the first night
and he was like unacceptable.
You know what I'm talking about, right?
Yeah, unacceptable accommodations.
What did he do?
He removed all the lighting that existed in that room
and replaced it with red light bulbs,
which I later used when I stayed here
and then later stole when I left. Ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, ha, Elaine or anyone else who stayed here, Conti or anyone else didn't have those.
I took them, I love them.
So funny, Jill is like, you know,
Rick changed every light in the guest house to red.
I'm like, yeah, no, I didn't know that,
but I'm not surprised.
Yeah, well in his place, he has mostly
either no lighting or red lighting.
So during the day, it just goes by ambient light
and then red light in the evening or candlelight. And it's great. And you know, people hear red lights
and they think they have to buy these expensive red light units. But that's not what we're
talking about that you can literally buy red party lights or just a red bulb. Some people
say, well, can I just use a red film or can I put a t shirt over the lamp? I worry about
people putting t shirts over the lamp because of the fire hazard. But I'll be honest, I dim the lights in my home at night.
When I travel, sometimes I will bring one of the stolen from Rick Rubin red lights.
The Rick Rubin stash.
Here's something where I've sort of softened my tune.
So I used to be kind of a hardliner, no blue light in the evening guy.
You know, had the, you know, everything was red light at night as far as my
phone using flux on the computer, you know, whatever it was. I suspect that that matters somewhat,
but I think what matters more is the stimulation that may come from those things. And what I've
come to realize, at least in me, which means it probably is true in others as well,
and at least some others,
is that what I'm doing on my phone matters more
than how bright my phone is.
In other words, if I've got the best blue light filter
in the world on my phone,
but I'm doom scrolling social media
and getting lit up on email. That's way worse for me than if I've got my phone
on maximum light and I'm like watching YouTube videos
of F1 cars and driving around having fun.
Like it's a totally different experience.
So the context matters and I think for that reason,
I would want people to be mindful of the whole picture.
Going to bed under a period of intense duress
brought on by something,
that's an equally dangerous component to all of this
that's distinct from what we're talking about.
But I want people to be able to think of this
in the context of everything.
Yeah, it's a really important point.
You know, one thing I'll say is that if you're going to stay up
past your normal bedtime, if you're gonna get a lot of light in your eyes,
I would hope that it would be for fun reasons and for reasons you enjoy. You should definitely spend some nights out.
You should definitely do some all-nighters studying if you really, you know, if you, if it's gonna help you get the grade
that's permanent, right? I'd certainly have done all-nighters studying and grant writing for years.
You know, there are going to be the inevitable all-nighters due to, God forbid, a trip to the
hospital or you heard something on the news that really amped you up or you just simply can't sleep.
That stuff is gonna happen. So I think the goal should be to minimize light exposure at night.
And I think what you just said is especially true
because we don't know, for instance, people talk
about the negative impact of social media.
Is it the fact that people are looking at this little box
for so many hours per day?
Is it all the things they're not doing?
Is it what they're looking at per se?
All of those things interact and are really important.
We know based on studies from the Stanford sleep lab
that if you wake up in the middle of the night,
looking at what time it is,
can be very disruptive to your ability to fall back asleep
and to your sense the next day.
It's a placebo effect, but it's a powerful one
of how tired you are the next day.
They've done this where they wake people up
in the middle of the night and then they say,
it's 4 a.m. versus 4am versus 2am versus 6am and
people's perceived levels of energy during the day in some ways correlate with what they think,
how much sleep they think they got. Likewise, and this is one of the concerns, potential concerns
with sleep trackers. Yeah. Allie Crumlin talked about this when she came on our podcast, you know,
if people see a poor sleep score, they often feel worse than if they see a good sleep score.
Now, of course, physiology matters.
You can't lie to yourself and say, you know,
got a great night's sleep simply by virtue of a sleep score.
But I worry more about the false,
well, if it's a false negative that we don't want
to put valence on this, seeing a bad sleep score
and then deciding that you're going to have a terrible day.
You know, I think a bad sleep score is an indication that you might need to dial
some things in a bit better.
Getting a great sleep score is an indication that you might be doing a
number of things right and start looking at these things as averages.
Wouldn't you, would you agree?
Yeah, completely.
I don't think it's that different from CGM, right?
Like I think that CGM is an amazing tool to provide insight and you pretty much
know the insights after a relatively short period of time. 30 days maybe at the outside 90 for a person with a
very complicated life and you know all you need to know about how the inputs
affect the output. Thereafter if you choose to use it it's a behavioral tool.
In other words you're using this to build in a Hawthorne effect. I think the same
is largely true with sleep trackers.
Most people have this profound sense of learning when they first encounter one of these things.
And it's again, you've heard it all 100 times, oh my God, I can't believe what alcohol does to my sleep.
Right, or caloric trackers.
Exactly.
Like I think a Lane Norton's app, Carbon, I have no financial relationship to it.
I use it or and it's taught me, wow, like I consume a lot of calories in the form of certain things at certain times of day.
And there's just a lot of good learning in that.
But it's the act of tracking that helps you manage it.
And similarly, I think it's the act of knowing you're going to be looking at that score that gamifies it, that kind of helps people do the right things.
You know what? I'm not going to have that drink tonight or I'm not going to eat that snack
before bed because I've now been conditioned to see how that impacts score.
That said, I think that, um, you know, recovery scores and things like that are
just notoriously poor at predicting performance.
And I think there's a reason that serious athletes would never use things like that.
Um, they would tend to rely on the more tried and true methods of predicting
behaviors such as heart rate, maybe heart rate variability, but morning resting heart rate,
probably more predictive than anything else.
And then, you know, in workout things such as heart rate, heart rate recovery,
lactate threshold, things like that.
So yeah, I agree.
I think we have to, and I say this as a guy who's generally perceived to be the most pro-device guy in the world.
People would be surprised how sparingly I use things like that.
I mean, I do some tracking, not as much as you.
I love things that seem to work the first time and every time in terms of our natural biology based on a couple
of criteria. There's an established mechanism. It's been explored in the context of pathology
like mental health disorders as well as pro health in healthy individuals that it make really good
sense at the level of kind of wellness and let's just say ancient health.
You know, when you're talking about getting a lot
of sunlight during the day,
like a lot of people will say,
well, of course, get outside and play,
not getting too much light at night.
Of course, this is just good old,
quote unquote, good old fashioned advice.
People spend 90% of their time indoors now.
Their daytime environments are too dim.
Their nighttime environments are too bright.
And this kind of misleading aspect of artificial light that when you see a bright bulb, you
think I'm getting a lot of photons is part of the problem.
And the fact that when you're out on an overcast day and it, you know, you think there's sun,
quote unquote, isn't out, well, it's hidden by cloud cover. But just think about how well you can navigate that environment without a flashlight versus
at night where you would require a flashlight. We evolved under this traumatic difference
in day night availability of photons, independent of whether or not you can quote see the sun.
And it's just very clear that
are the all the mechanisms in our brain and body that regulate mood are just powerfully
regulated by this stuff. So I've made it a point to really reduce the amount of nighttime
light that I'm getting, but I'm less concerned about flipping on the light switch to use
the bathroom as I used to be. I used to think, oh, I'm like quashing all my melatonin. This
is terrible. I know I can't shift my circadian clock then. I know that that light, yes, while it's bright,
if it's brief, I'm not going to worry about it too much. Would it be better to have a, you know,
dim light on as opposed to a bright light? Sure. But I'm not going to stress it in a hotel bathroom
or something. I'm not going to walk around shielding my eyes. So people will sometimes ask me, by the
way, is it different to look at the phone directly versus if you tilt the phone away? Well, it absolutely is. I mean, think about
a flashlight shown on the ground in front of you, very few photons getting in your eyes
versus shown directly into your eyes. Think about ambient light from the sun going everywhere
versus looking in the general direction of the sun. So east in the morning, west in the
afternoon, of course, the directionality of the light matters.
So I'm not saying that you need to like peek at your phone as if you're looking over the
edge of a bowl or something into it.
But my friend, Samar Hattaru, is head of the Chronobiology Unit at the National Institute
of Mental Health.
We used to room together at meetings.
We stopped because he's a terrible snorer.
So I just could, there were a few times when I considered suffocating him in the middle of the night, since he was
already suffocating himself. Now we just, we don't stay in the same rooms anymore. We're no longer
postdocs, but I caught him looking at his phone in the middle of the night and he would tilt it
like away, like he's holding a platter for those that are just listening and kind of like looking
over at the screen there and like, what are you doing? This is ridiculous.
He said, I'm trying not to get so much light in my eyes.
That's a little extreme, but I think it illustrates the point,
which is how much direct light exposure you get at night matters.
How much direct sunlight exposure you get,
especially early and late, early morning,
late afternoon and throughout the day, it really matters.
Now remind me, Andrew, what is the wavelength of sunlight?
Great. So sunlight is going to include all visible, visible.
Which runs from how many nanometers?
Yeah. So, well, let's, let's, we can answer two questions there.
This wrist sensor detected 470 degrees, 70 nanometer to 650 nanometer light.
So that's going to be blue and ultraviolet.
Ultraviolet's kind of like blue to orange.
Yeah. Blue, blue to orange. Yeah,
blue, blue to orange. That's what this was measuring. So red light is going to be more
like 680 far red is getting out to 7, 720 and up upwards of that blue light is going
to fall somewhere in the low fours ultraviolet is getting down into the high threes and lower.
And so these these spectra of light. So during the day, you know, midday light,
you're getting what looks like white light.
You'll see, oh, the sky is blue
and the sun is bright white light.
It's not even yellow to your eye.
And of course, don't stare at it,
especially in the middle of the day.
You're getting all visible spectra.
So you're getting everything from UV
all the way out to red light.
It's just coming in at equal intensities.
So is that a potential limitation of this study in that it didn't have a sensor that
could pick up the full spectrum of light?
Potentially especially since they're, you know, we don't think of humans as UV capable,
like we can't perceive UV light, like a ground squirrel for instance can has UV sensors in
its eyes. Turns out you know why they use this, it's crazy. They actually, for instance, can has UV sensors in its eyes. Turns out, you know why they use this?
It's crazy.
They actually, you know, when the ground squirrels sit up
on their haunches, they're actually signaling one another,
they rub urine on their belly and it reflects UV.
The New York Times for some reason has been running
a series of papers or articles,
rather about naturally occurring fluorescence at night
and all sorts of scorpions and monotremes like the platypus.
No one really knows the reason for these odd,
odd wavelength of light emissions for all these animals.
But we view things in the blue, violet, and up to red,
and we're not pit vipers, we can't see far red.
But we can see lower than 470 nanometers and we can see
higher than 650.
Is there a technology reason why they had such a narrow band in these sensors?
Is it not possible that they could have used a wrist sensor that was wider?
This study was initiated in 2013.
The tech was probably far worse than it is now.
Again, I would love for somebody to design an eyeglass
where it's measuring how many photons you're getting
across the day.
I'm not a big fan of having everything be apified.
So I would love it if the frame would just shift color
across the morning, like you go outside on a cloudy day,
you know, you wear these glasses and,
and by the way, it's fine to wear eyeglasses or contacts
for sunlight viewing, for setting your circadian rhythm.
People always say, well, why is that okay?
And a window's not.
Well, corrective lenses are actually focusing the light onto your retina.
The windows and windshields are scattering the light and filtering.
And how much are sunglasses filtering this out?
Way too much.
We can safely say way too much, probably causing a 10-fold decrement in the total luxe count that's landing
on your retina.
But of course, you know, sunglasses are important driving into sun and some people have very
sensitive eyes.
I can't sit at a cafe with a brightly reflective table in the afternoon.
I just squint like crazy.
I can't do it.
My dad who's darker eyed and he's South American descent,
he can just sit there just fine.
My mom who's got light eyes like me,
we're like, it's really tough.
You just have a terrible time.
People differ in their light sensitivity.
So there's one other macro question I have here
and it's not answerable because without randomization we can't know it.
But it's the question of how much reverse causality can exist in these observations. So again these
observations demonstrate very tight correlations, very strong associations, especially in the five areas that we highlighted. But it's possible that
part of what we're seeing is reverse causality brought on by both the treatments, which you've
already kind of alluded to, and also the condition itself.
Do you want to explain reverse causality for people? And maybe could you mention, for those
that missed the Hawthorne effect? Just yeah,
yeah, the Hawthorne effect is, is an effect that is named after an, you know, an
observation of what took place in a factory where they were actually studying
worker productivity with light of all things. But what it refers to is the idea
that people will change their behavior when they are observed.
So if if I said, well, I really want to know what a day in the life is like for Andrew Huberman, I'm going to follow him around for a day.
It's very unlikely that his behavior that day will be exactly as it was if I wasn't there.
And so the reason why you probably will never see a day in the life of Andrew Huberman.
Although it's pretty it's pretty scripted unless I'm traveling.
It's a, it's a, you know, it's morning sunlight, hydration and, you know,
some cardio or weight training. And then a lot of time reading papers.
It'd be the most boring video in the world because it's mostly me reading and
underlining things.
But it's why gamifying things can be beneficial, right?
It's why a CGM can be beneficial
because it's sort of like somebody's watching you
and you're gonna modify what you eat in response to it
or why tracking can really be an effective way
to reduce input because there's a sense
of being monitored by doing that,
especially if someone literally monitors it.
In other words, you can set up an accountability partner
where your health coach or someone is actually seeing the data. So that's what it is. Now, as far as reverse causality, when you look at variables, so let's just pick a common one that's unrelated to this. So there's an association that more diet soda consumption is associated with greater obesity. It's a bit paradoxical,
right? Is that true? It is. Yeah, it's been demonstrated in many series that the greater
the consumption of diet soda, the greater the prevalence of obesity. And that has been postulated
by some to suggest that non-nutritive sweeteners such as Aspartame or
sucralose or things like that are actually part of what's causing obesity. And while there are
probably some arguments you could make around the impact that those things might have on the gut
microbiome and maybe there's some way and that's happening, it's also equally likely, if not probably
more likely, that there's reverse causality there. That a person who is obese is therefore contemplating
how much they're eating or thinking,
hey, what's an easy way that I can reduce calories?
How about instead of drinking a Coke, I drink a diet Coke?
And so there, the causality which you would impute
to mean the drink is causing the obesity,
it might be no, the obesity is causing the choice of drink. So here the question is, how much of the effect we're seeing is a result
of the condition that's being studied, right? How much of the disruption in both day and
night, light exposure is the result of the depression. It's dysregulating the sleep.
Maybe they're sleeping more during the day
and more awake at night because of depression.
Again, these are, you can't know this.
This is where epidemiology never allows us
to determine this.
And sadly, these questions can only be answered
through either direct randomization
or Mendelian randomization,
which by the way, I was going to also ask you,
do you know if anyone has examined this
from a Mendelian standpoint?
That would be very interesting
because I have to believe, well, it would be interesting.
I don't know enough about the biology
to know what SNPs would be studyable,
but that would be interesting.
What Peter is saying is, you know,
if you knew something about the genomes of these people,
you would be in a great position to perhaps even link up
light susceptibility genes or like sensitivity genes
with genes for pathways involved in major depression,
bipolar.
I mean, getting to this issue of reverse causality,
I mean, I think it's very straightforward to imagine that the person who's experiencing a manic episode is going to be up for two
weeks at a time, sadly, and getting a lot of nighttime light exposure.
You know, now, dark nighttime dark exposure as a treatment for bipolar is something that
people are starting to talk about.
So making sure that even those people are awake, that they're at least blue blocking at night,
reducing their online activities,
but people with severe manic episodes
have a hard time regulating their own behavior, of course.
And it's not one or the other.
Like I don't want the question to come across
to the listener 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 of times
these things feed off each other. Going back to the soda example. No, it's actually a lot of times these things feed off
each other. Going back to the soda example, I actually think there's a bit of both, right? I
actually think there's a real clear body habit as dictates beverage choice, but I also am starting
to think that insusceptible individuals, non-nutritive sweeteners will alter the gut biome and that alters metabolism.
What about just hunger?
I remember Lane telling me, and I've seen at least one of the studies that, you know,
water is probably better for us than diet soda, but that for some people diet soda is a great
tool for reducing caloric intake.
I also know some individuals, not me, who drink diet soda.
I drink diet soda from time to time, mainly stevia sweetened sodas, but what I'm referring
to here are people besides myself who drink diet soda and it seems to stimulate their
appetite.
There's something about the perception of sweet as driving hunger, whereas not eating or drinking anything with calorie,
with any sweetness doesn't seem to. This is one of the things I wonder if it impacts why
some people like intermittent fasting, because for some people, you know, just even the perception,
I wonder if the perception of sweetness or even just the smell of food, we know, can stimulate
appetite. So you can mention that the perception of sweetness in the mouth the smell of food we know can stimulate appetite. So you can
mention the perception of sweetness in the mouth, even if there's no calories there.
I don't think it necessarily makes people hypoglycemic, but perhaps it makes them think about,
like, sweet means food. For instance, for years, I love the combination of a diet Coke and a slice
of pizza whenever I was in New York, ideally two slices of pizza. So now every time I have a Diet Coke,
which isn't that often, but I like Diet Coke,
especially with a little bit of lemon in it.
I just think about a slice of cheese
or mushroom or pepperoni pizza.
It's like I want it, I crave it more.
So there's a paired association there that I think is real.
And we know based on Dana Small's lab at Yale
that there's this paired association
between the sweetness from sucralose
and that there's an insulin response.
They actually had to cease the study in kids
because they were becoming prediabetic,
which unfortunately meant the study was never published.
Have you talked to Dana on this podcast?
No, we wrote a premium newsletter on this several months ago.
It's gotta be like, I don't know, 10 to 20,000 words
on all things related to sugar substitutes.
Okay, I'll read that.
I need to read that.
Folks who are interested in this topic, I would refer them to the premium newsletter
on sugar substitutes.
I think it was our September edition.
The short of it is the data are a little bit noisy, but there is indeed some sweeteners in some studies
do result in that phenomenon you described,
the cephalic insulin response.
And I came away from the research that went into that,
which was a Herculean effort on the part of the team,
a little bit more confused
than when I went in, but being even more cautious
around artificial sweeteners than I was going in.
And not for the reasons that I don't necessarily,
I didn't find any evidence
that these things are cancer causing, right?
So that's the headline stuff people worry about.
Oh, I protein causes.
You have to ingest like 10 grams.
Yeah, yeah, yeah, yeah.
Like crazy.
I came away more confident that from a long-term safety perspective, in terms of cancer and
catastrophic outcomes like that, that wasn't the issue. But I came away much more cautious
around these things can really be mucking around with both your brain chemistry and your gut chemistry, which can pertain to your metabolism.
And therefore my takeaway was buyer beware use limited amounts only.
The one by the way, that still emerged to me as a reasonable one,
it's the only one that I use. And I've talked about it a lot is Xylitol.
Xylitol is the, pardon me, I shouldn't say it, Xylitol for chewing, so for gum,
and allulose as an additive.
So those were the-
Safer, you're saying?
Yes, those are basically the only two I will consume.
Yeah, I'll drink a diet coke every now and again
if I'm on a plane or something.
Yeah, yeah.
You know, this law that got passed a few years ago
that you couldn't bring liquids of your own
into the airport and onto the plane.
Like what a great-
A few years ago.
What a great scheme.
What a great scheme to get people to buy overpriced fluids
in the airport.
Like, I mean, there are more important issues in the world,
but like this one really gets me.
But yeah, I use a little bit,
I drink things with a little bit of Stevia
and the occasional diet coke.
And I generally avoid sucralose.
I don't like the way it tastes.
Monk fruit is too sweet, but yeah, we get, we maybe we'll do a podcast on that in the future.
OK, so I think we can wrap this paper because I really.
Well, but tell me what you think about that point, Andrew, like how, I mean, you know,
you know more about this stuff than I do.
But if you had to just lay on your judgment,
right? So so if it were if it were 100 to zero, you would say
the light is 100% causal in the effects we're seeing. If it were
zero to 100, you'd say, nope, the behavior is 100% causal of the exposure to light. Where
do you, again, you can't know it. What does your intuition tell you?
Okay, there's my intuition and then there's my recognition of my own bias. Because I started
working on these circadian pathways originating in the eye back in 98 as a graduate student
at Berkeley,
the cells, these melmopsin intrinsically sensitive
retinal ganglion cells were discovered in the early 2000s
by a guy named Iggy Provencio, Dave Burson, Sam Ratar,
Sachin Panta and others.
And it was like one of the most important discoveries
in all of biology, clearly.
So I've been very excited about these systems,
but if I set that aside, so bias disclosure made,
I think 65 to 75% of the effects
are likely due to light directly.
Now it's impossible to tease those apart, as you mentioned,
but to play devil's advocate against myself,
you know, you could imagine that the depressed
individual is laying around indoors with the curtains drawn. They didn't sleep well the
night before, which gives you a photosensitivity that isn't pleasant like it sucks to have bright
light in your eyes first thing in the morning, especially if you didn't sleep well. And then
they're, you know, making their coffee in a dimly lit, what they think is brightly lit environment,
and then they're, you'll look at their phone and the state of the world
sucks and their state of their internal landscape is rough. And they're, maybe they're dealing with a
pain or, or, you know, injury or something, and their likelihood of getting outside is low. And
when they do get outside, they're going to shuffle and not, you know, so I could see how
the behaviors could really limit the amount of light exposure and then evening
rolls around, they've been tired all day and a common symptom of depression.
You fall asleep and then two or three in the morning, they're wide awake.
What are you going to do it two or three when you're wide awake, sit in the dark?
No, you're going to get online, you're going to listen to things you might have.
I'm not recommending this, but an alcoholic drink in order to try and falsely.
I mean, this is the pattern.
And so, you know, shaking up that pattern is really what, what so much of my
public health work these days is about and trying to get people onto a more
natural daylight night, night dark rhythm.
Uh, but yeah, it's impossible to tease apart.
We do know this and this is really serious. We
know that in almost every instance, almost every psychopathology report of suicide,
in the weeks, but especially in the days preceding suicide, that person circadian rhythms looked
almost inverted from their normal patterns. And that's true of non bipolar individuals as well.
You know, circadian disruption and disruption in psychiatric
health are inextricable.
Conversely, positive mood and affect and circadian behavior
seem very correlated.
I mean, I think it's clear that if you want to become an early riser, get light in your eyes and get activity in your body early in the day, you built the you entrained to those rhythms so that you start to anticipate that morning workout, you start to anticipate the morning or just sunlight that's illuminating your environment. As you said, you don't even have to see the sun itself, that there's a 50, 50% increase in the amplitude of
the morning cortisol spike, which is a good thing. Right. That's when you want it. Because it's
inversely, the amplitude of the morning cortisol spike is inversely related to the amplitude of
the evening cortisol spike and high evening cortisol is associated with middle of the night waking
bike and high evening cortisol is associated with middle of the night waking and on and on. So, you know, I'm very bullish on these mechanisms. I also love that they're so deeply woven into our
evolutionary history, you know, that we share with single cell organisms. It's so wild. But of course,
there's going to be a bidirectionality there and it's impossible to see where one thing starts and the other one stops.
I mean, here's my take, Andrew.
First of all, I actually, with far less authority than you, agree with your assessment and might
even be a little bit more bullish, might even put it at 80-20.
And here I'll give you my explanations, which stem more from my fastidious battles
with epidemiology in general, right?
Like, because so much of the world that I live in
still has to rely on epidemiologic data.
And so how do you make sense of it?
And the truth of it is most of it is really pretty bad.
But I tend to find myself looking
at the Austin Bradford Hill criteria all the time.
And for folks who don't know,
he was a statistician who basically proposed a set of criteria. Believe there are eight of them,
and I can't believe I don't know every one of them off by heart. I certainly used to.
But the more of these criteria that are met within your correlations, the more likelihood
are met within your correlations, the more likelihood you will find causality. So when I think of your data here, the data in this paper, I'll tell you what makes these
correlations seem to have causality within them in the direction that's being proposed.
Look at the dose effect.
So dose effect matters, and this is done in quartiles. And that's a very elegant
thing. If they just did it as on off, it would be harder.
High, low.
That's right. But the fact that they did it in quartiles allows you to see that every
example in figure two, I don't believe there is an exception to this.
No, and I think also in the, in the other, there's only one exception to what I'm about
to say. Sorry, two out of like God knows how many, they're all monotonically increasing and decreasing. In other words, the dose effect is always
present. Another thing is biologic plausibility. You've spoken at length
about that today. So in other words, sometimes you have to look at epidemiology
and ask, is there a biologic explanation? And here there is. You've added another
one which is evolutionary conservation to the biologic plausibility. Then you can talk about animal models or experiments in
humans over short durations that generally support these findings. And so those are just
a couple of the Bradford Hill criteria that that lead to, you know, my belief that, yeah,
there's reverse causality here, but it's not the full explanation
and that more of the explanation is probably the direction that's being proposed.
And if that's true, because then at the end of the day, like what's the purpose of the
discussion?
The purpose of the discussion is if you are under the influence of any of these psychiatric
conditions, in addition to the treatments you're doing now,
what else can you do?
And to me, the takeaway is follow these light behaviors.
I mean, it's a relatively low lift
when you consider some of the other things.
Like I'm over here asking people to do zone two
for three hours a week and VO2 max workouts
and all this other stuff.
And like, I think all those things matter
for mental health as much as physical health. But this strikes me as on the spectrum of
low asks. If it shows, if it's only even 30% causality, 70% reverse causality, like I'll
take those, I would still in state that.
Yeah. And it's, you know, it's taking your coffee on the balcony. It's, and people will often say, well, how do you do this with kids? The kids should be doing it too. Right? You
know, it means popping your sunglasses off. It means getting out for just a few minutes. And
the fact that it's additive that these, you know, these photon, uh, mechanism, photon counting
mechanisms they sum is great. And look, this paper also says, and I should have stated this earlier,
if you missed your daytime light ration,
get your nighttime dark ration.
They are independent and additive.
So that's, I mean, that's a really something,
but of course, ideally you get both,
but I appreciate your take on it.
And, you know, and thanks for your expertise
in parsing epidemiology.
I look at fewer studies of that sort,
but I learned from you.
And that's one of the reasons I love doing
these journal clubs is I learn.
So along those lines, tell us about the paper you selected.
I'm really eager to learn more.
Well, I wanted to pick a paper that was kind of interesting
as a paper.
And this paper, I think, is interesting in that it is kind of the landmark study of a class of drugs.
But in the same way that you kind of picked a paper that I think has a much broader overarching
importance, the reason I picked this paper, which is um from New England Journal of Medicine,
it's about 10 years old, no correction 13 years old, is because it is kind of the landmark study
in a class of drugs that I believe are the most relevant class of drugs we've seen so far in cancer
therapy. And even though the net effect of these drugs has only served to reduce
mortality by maybe 8 to 10 percent, which is not a huge amount. It's the manner in which they've
done it that gives me great hope for the future, even if it's through other means. So I'll take
a step back before we go into the paper for again, just the context and
background. So the human immune system is kind of a remarkable thing. It's hard when you're sort of
trying to imagine what's the most amazing part of the human system. And maybe it's my bias as well,
because just as you spent, you know, your time in the light system and the photo sensing system, and maybe it's my bias as well because just as you spent, you know, your time in the light system and the photosensing system, I spent my time in the immunology world.
But it is remarkable to me how our immune systems evolved.
And they have this really brutal task, which is how can they be tuned to detect any foreign pathogen that is harmful
without knowing a priori what that could be.
While at the same, so in other words,
how can you tune a system to be so aggressive
that it can eradicate any virus or bacteria,
billions of years into the future
without knowing what it's going to be.
But at the same time, it has to be so forgiving
of the self that it doesn't turn around and attack the self.
It's remarkable. And of course we can always think of the exceptions. There are
things called autoimmune conditions.
So clearly the system fails and the immune system turns around and attacks
the self. If you see a person with vitiligo,
I have a little bit of vitiligo on my back,
couple of spots.
Clearly the immune system is attacking something there
and destroying some of the pigment.
I didn't realize vitiligo was autoimmune.
Yeah.
If, you know, there's, there are lots of, you know,
more serious autoimmune conditions.
Of course, you know, somebody that has lupus or, you know,
where the immune system can be attacking the kidney, the immune system can be attacking any, autoimmune conditions, of course, you know, somebody that has lupus or, you know, where the immune system can be attacking the kidney, the immune system can be attacking any autoimmune
conditions can be deadly. But fortunately, they are very rare. And for the most part,
this immune system works remarkably well. So how does it work? And why is it that cancer
seems to evade it virtually all of the time. This is the question.
Now, let's first of all talk about how it works.
And then when I tell you how it works,
you'll say that sounds amazing.
Clearly it should be able to destroy cancer.
I'm gonna simplify it by only talking about one system,
which is how T cells recognize and get activated,
how T cells recognize antigens.
So we have something called an antigen.
So an antigen is an antibody generating peptide.
So it's a protein, almost always a protein,
they can be carbohydrates,
but they're almost always proteins
and they're very, very small peptides.
Like we're talking as little as nine amino acids, maybe up to 20 amino acids.
So teeny, tiny little peptides.
But it's amazing that in such a short peptide, the body can recognize if that's Andrew or
not Andrew.
I mean, when you again think about like, we talk about proteins in kilodaltons, right?
We're talking about proteins in terms of thousands of amino acids that make up
every protein in your body. And yet if it samples a protein and sees that,
Hey, this little nine, 10, 15 peptide amino acid is not part of you.
I know it's bad. And therefore I'm going to generate an immune response to it.
So we have what are called
antigen presenting cells. You have cells that go around sampling peptides and they will on these
things called MHC class receptors bring the peptide up to the surface and serve it up to the T cell.
There are two types of these. There's MHC class one and MHC class two. I only
This is major histocompatibility complex. That's correct.
And we refer to them that way because they did, because of the context
in which they were discovered, which was for organ rejection.
So not surprisingly, when you need to put a kidney
into another person, if that kidney is deemed foreign,
it will not last long.
And the early days of organ transplantation
were rife with immediate rejections.
And by not, I mean, the immediate are the ABO
and compatibilities, but the sort of next layer
of incompatibility was MHC incompatibility,
which would lead to, you know, within within
weeks, the organ is gone, as opposed to within hours. So you
have these two classes of MHC, you have class one and class two
class one is what we call endogenous. So this is basically
what happens when a protein or an antigen is coming from inside the cell.
So let's consider the flu.
So if you get the flu, the influenza virus
infects the respiratory epithelium of your larynx.
And that virus, as folks listening might remember
from our days of talking about COVID,
viruses can't replicate on their own.
What they do is they hijack the replication machinery of the host and they use that either to insert their RNA or DNA
to replicate. And in the process, proteins are being made. Well, those proteins are the proteins
of the virus, not of us. So some of those peptides get launched onto these MHC class one gloves, basically the
glove comes up to the surface and a T cell comes along.
In the case of MHC class one, it's a CD8 T cell.
These are what are called the killer T cells, right?
And so this cell comes along and with its T cell receptor, the T cell receptor meets the MHC class 1 receptor
with the antigen in it. And if that's a lock, it realizes that's my target. And it begins
to replicate and proliferate and target those. And that creates the immune response. And
by the way, that's how it works when you vaccinate somebody, you're basically pre building that
thing up.
So would this fall under the adaptive immune response or the innate immune response?
Though this is adaptive.
Yep.
Inate is just these pure antibody response in the, on the B cell side, I won't
get into that for, for the, for the purpose of this discussion.
The other example is MHC class two, and that's also part of the adaptive system
or the innate system, which is more
what we call the exogenous form.
So these are peptides that are usually coming from outside the cell.
So we're going to focus more on the MHC class, one, because this is peptides that come from
inside the cell.
Okay, so just keep in the back of your mind, if a foreign protein gets presented from inside
a cell to outside a cell, the T cells recognize that and they will mount a foreign response.
And by the way, that's why we basically can beat any virus. Like if you consider how many viruses
are around us, the fact that we almost never die from a viral infection is a remarkable achievement
of how well this immune system works. We're constantly combating these viruses.
Constantly. And by the way, we don't really have very effective antiviral agents.
It's not like antibiotics. Like we have antibiotics up the wazoo.
I mean, we're way better at fighting viruses than bacteria.
Can I just ask one question? I've always wondered about this.
To what extent is our ability to ward off viruses on a dated basis as an adult, reliant on us
having been exposed to that virus during development?
As I walk around today, maybe I'll be exposed to 100,000 different viruses.
Would you say that half of those, I've already got antibodies too because I was exposed to
them at some prior portion of my life?
Yeah, hard to quantify.
And the other ones, I'm just building up antibodies.
Like I was on a plane last night, someone was coughing.
So I was hiding.
And I had COVID a little while ago,
so I wasn't too worried about that.
And I feel great today.
But, you know, I just assume that on that plane,
I'm in a swamp of viruses, no matter what.
And that most of them I've already been exposed to since I was a little kid. So I've got
all the antibodies and they're just fighting it back, binding
up those viruses and, and, and destroying them.
Yeah, I think it's part that. And I also think it's part of
them that our body can destroy without mounting much of an
immune response. So therefore, your immune system is doing the
work and it's yet it's not mounting a systemic inflammatory
response that you're not sensing.
So is it also a physical trapping in you know in my nasal
epithelium? Yeah, so yeah like you have huge barriers right so the skin you
know the hairs in your nose all of these things are huge barriers but assuming
that still a bunch of them are getting in at least the respiratory ones that's
the other thing to keep in mind right there were certain viruses that are
totally useless floating around the air right right? There are certain viruses,
you know, the viruses that most people are really afraid of, you know, Hep C, Hep B,
HIV, well, you know, if they're sitting on a table or floating around the air, they're
of no threat to you. They have to be, you know, sort of transmitted through the barrier.
But again, some of these viruses, you're going to defeat without an enormous response.
And then some of them, you know, why is influenza, quote unquote, such a bad virus, whereas the
common respiratory cold kind of sidelines you for a day.
It's the immune response that you're feeling.
The worse, the bigger the immune response to the virus, the more you're feeling that
you feel your immune system going crazy, right?
You know, the inner leucons that are spiking,
the third spacing that occurs
to get more and more of the immune cells there,
the spike of your temperature
as your body basically tries to cook the virus,
all that stuff is your body doing.
The fatigue.
Yeah, yeah, you're being drained
and all this happening.
So one more point I'll mention,
just to close the loop on the autoimmunity. How is it that we
learn not to attack ourselves? That's something called
thymic selection that occurs in infancy. So you and I have a
no good for nothing tiny little thymus that would be it's
almost impossible to see these things. You know, when we used
to operate on people, you know, the thymus is barely visible in an adult,
in a healthy adult outside of thymic tumors.
But as a child, the thymus is quite large.
And the purpose of the thymus is to educate T cells
and basically show the T cells what self is
and any T cell that doesn't immediately recognize it
gets killed.
So it's a really clever system where we basically teach you
to recognize self at a very early age.
And if you can't do that, you're weeded out.
And then the thymus involutes thereafter
because it's sort of served its purpose.
Okay, now let's talk about cancer.
So what do we know about cancer?
So we know that, again, cancer is a genetic disease
in the sense that every cancer has genetic mutations.
Most of those mutations are somatic,
which means most of those mutations
are mutations that occur during the course of our life.
They're not germline mutations.
The germline being the eggs and sperm, right?
So it's all other cells.
And I love that you pointed out that, you know,
there can be, the cancer can be genetic,
but isn't necessarily inherited, right?
In fact, it's really inherited.
People are genetic and they think inherited, right?
Yes.
But inherited is always genetic to some extent,
but genetic isn't always inherited.
Yeah, so there are a handful of cancers
that are derived from inherited mutations.
So Lynch syndrome is an example of that.
Hereditary polyposis is an example of that,
where you have a gene that gets passed through the germ line
and that gene codes for a protein like all genes do, and it's either you have too much of a gene that gets passed through the germline and that gene codes for a
protein like all genes do and it's either you have too much of a gene or too
little of a gene so it's either a gene that promotes cancer and you have too
much of that or it's a gene that prevents cancer and you have too little of it or
a dysfunctional version of it right so BRCA is an example that BRCA is hereditary
BRCA codes for a protein and and the women and men, but
mostly the women that we think about who have a BRCA mutation, that in some cases almost
guarantees breast cancer, it's because of a defective copy. So it's like they don't
get the protein that they need to protect them from breast cancer.
So what do we know? Well, we know that, and this is probably one
of the most remarkable things I've ever learned, and it still blows my mind every time. Well,
actually, before I get to that point, I want to make, I want to make another point. Okay,
so, so you might think, so cancer, we, we, you know, ourselves become cancerous, but
they're clearly hijacked because they
have these mutations. And as a result of these mutations, they make proteins that allow cancers
to behave differently. And cancers behave differently from non cancers in two very
critical ways. The first way is that they do not respond to cell cycle signaling. So if you cut your skin, it heals. But how does it know to heal
just right and not to keep growing and growing and growing and growing and growing? Well, it knows
that because there are cell cycle signals that tell it time to grow, time to stop. If, believe it
or not, this is an extreme example, if you donated to me half of your liver, which I know you would.
Absolutely.
I'd give you more than half a month.
Well, you don't need to give me half.
If it meant that we could keep doing these general clubs, right?
Within months, you would regenerate a full liver.
Isn't that amazing?
That's so wild.
It's like a salamander.
You cut off a salamander limb and please don't do that experiment because other people are
doing it anyway and it grows back.
Yeah. And it knows how and it grows back. Yeah.
And it knows how much to grow back.
It's so loud.
So, so when the cell is perfectly functioning, it knows how much to grow and it's, well,
cancer loses that ability.
That is one of the hallmarks of cancer.
It just keeps growing.
It doesn't grow faster, by the way.
That's a misnomer.
People think cancers grow faster than non-cancer.
There's no real evidence that that's the case.
They just don't stop growing.
The second property of cancer is the capacity to leave the site of origin, go someplace else and take up residence.
So that's a metastasis component.
So if you think about it for a minute, a cell that never stops replicating and has
the capacity to up and leave and move and
take up residence is clearly different from the cell itself, right?
So if I have a cell of colonic epithelium, the cell that lines the inside of my colon,
it's clearly got a set of proteins in it.
But if all of a sudden that thing can grow, grow, grow, grow, grow, not stop, not stop,
not listen to the signal and then somehow wind its way into the liver and just keep growing and growing and growing. It must have different proteins.
So the question then becomes, why does cancer even exist? How has our immune system not figured out a
way to just silence this and eradicate it the way it does to virtually every virus you encounter?
And to me, this is one of the most interesting questions
in all of biology, and it really comes down
to how clever cancer is, unfortunately,
how evolutionarily clever it is.
It basically does a lot of things
to trick the immune system.
So it has its own secretory factors
that tamp down the immune system.
It grows in an environment because of its nature.
So one of the things that's long understood about cancer
is it's heavily glycolytic.
And when something is heavily glycolytic,
it's going glucose to pyruvate, to lactate, nonstop.
There are lots of reasons for that.
I think there's more than one. The war- What does that afford it? Is that a migratory potential?
No, so it's super interesting. So that's the effect that what I just described is called
the Warburg effect. And when Warburg proposed this, which God was probably in the 1920s,
it was before World War II, he thought the mitochondria of cancer cells were defective.
So he proposed that the cancer cells,
mitochondria don't work,
hence they have to undergo glycolysis,
they can't undergo aerobic metabolism.
We now know that that's not the case.
So we now know that the Warburg effect
or the Warburg effect,
if I'll refer to him correctly by his name,
almost assuredly does not have to do
with defective mitochondria.
Others have proposed several mechanisms.
I think there's probably more than one thing going on.
So a paper that came out in 2009,
very influential paper by a guy named Matt Vanderheiden
and Craig Thompson and
Lou Cantley proposed that the reason that cancer cells do the Warburg effect is
that they're not optimizing for energy, they're optimizing for cellular
building blocks. And if you do the mass balance it completely makes sense. Like
dividing cells need building blocks more than energy. And glycolysis, while while very inefficient for generating ATP is much more efficient at generating substrate to make more cells.
But another proposed mechanism is exactly at this one.
Glycolysis lowers the surrounding pH because of lactate.
Lactate attracts hydrogen, pH goes down and guess what that does to the immune system?
Detracts the immune system.
So it's also a way to hide from the immune system.
So there's a like a pH cloaking, leveraging pH to cloak the signal that the immune system
would otherwise see.
Yep. And then when you layer on top of that, that it knows how to secrete things like IL-10,
TGF-beta, all of these other secretory factors that also inhibit the immune system, basically,
it's figured out a way to kind of hide itself from the immune system. The way you describe it, cancer sounds like a virus.
Yes.
I mean, it sounds a lot like a virus. And that leads me to ask,
are there any examples of contagious cancers? I recall seeing some studies about these little
critters down in Australia, Tasmanian devils that like they would, they scratch each other
and fight as Tasmanian devils do. They're actually quite cute. And they would get cancers
and tumors growing on their faces. Yes. So, so it, I, and so it was, it was like a, it
was like a literal physical interaction that could transmit cancer from one animal to the
next. So it's less that there are viruses that cause cancer.
So in that sense, you could argue, yes,
there are contagious cancers.
Well, HPV.
Sure, yeah, HPV, Hep B, Hep C.
But there are even cancers like cutaneous cancers
that arise from viruses.
But I don't know if that's quite the same
as what you're saying.
No, no, it's in, they're no, what you're saying is an important point.
I mean, we don't wanna go down the rabbit hole of HPV,
but that's increasing susceptibility to cervical cancer.
Now there's a vaccine against HPV, right?
There wasn't when we were in college, as we all knew.
There was no vaccine.
But the, okay, so, but yeah, direct transmission of cancers
from one organism to the next, more rare. the, okay, so, but yeah, direct transmission of cancers from one, one organism
to the next, more rare.
Yes. Okay. So now, a moment ago, I said there's this really incredible thing about cancer
that blows my mind and about our immune system, which is that at least 80% of solid organ
tumors, and we're going to mostly talk about solid solid organ tumors because that's where the field of oncology
has made very little progress.
So if you go back 50 years,
where has oncology made huge progress?
It's made great progress in blood tumors, leukemias,
and some kinds of lymphomas.
In fact, there's two kinds of lymphomas
where the progress has been remarkable.
One has been in Hodgkin's lymphoma, and the other has also been in immunotherapy,
has been in a type of B cell lymphoma,
where that B cell demonstrates
or presents something called a CD19 receptor.
So in B cell lymphomas with CD19,
immunothera, there's a very unique niche immunotherapy,
we won't talk about that today,
called CAR T therapy that has got rid of those guys.
And then leukemias have also been pretty good, but in solid organ tumors,
there've been only two real breakthroughs in the last 50 years.
One has been the therapy for a certain type of testicular cancer.
And it's really just a chemotherapy cocktail that has been found to work really
well. And the other has been found to work really well.
And the other has been in this really rare kind of gastric cancer called the GI stromal
tumor, which happens to result from one mutation in a kinase pathway.
And there's one drug that can now target that and it works.
It's kind of amazing.
Cures that cancer is that what I'm talking about are the cancers that kill virtually everybody
else. This is what when you sort of line up, what are the cancers that kill virtually everybody else.
This is what when you sort of line up, what are the big causes of cancer death?
Let's start at the top.
It's lung.
It's then breast and prostate in men and women.
It's colorectal.
It's pancreas.
Those are the big five.
They kill more than 50% of Americans.
It cancer-wise, not sorry, let me restate that.
More than 50% of cancer deaths in Americans
come from those five.
These are what we call the solid epithelial tumors.
And you can march down the list,
and most cancers that most people are thinking
of are those cancers.
Well, here's the thing, more than 80% of those cancers
have antigens that are recognized
by the host's immune system.
I will state it again because it is so profound.
80% at least of those cancers
actually generate an antigen,
meaning a little peptide in that cell
gets presented to the T cell and it is recognizable.
And now the question is,
why is that not sufficient to induce remission?
And the short answer is, there are not enough T cells that are able to act and or they are
being sufficiently inhibited from acting, which gets me to the point of this paper.
One of the ways in which the body inhibits the immune system,
which we should remind ourselves is an important thing, right?
Is something called a checkpoint inhibitor.
Okay. So go back to that idea that I talked about before.
You have an antigen presenting cell.
It brings up an MHC receptor with a peptide on it.
And there is a T cell that is coming.
And I actually brought a diagram, which we're gonna,
I'm gonna link to this,
because I don't wanna make this too complicated,
but I really think that this figure is helpful
to understand how these papers, how these drugs work.
So the MHC receptor with the peptide is sitting there
and it binds to the T cell receptor on the T cell, but there is
another receptor on the T cell, a CTLA4 receptor. And that binds to a receptor
that I won't bother naming now because the names don't matter, but there's
another receptor on the antigen presenting cell that binds to that. And that acts as the breaks in the reaction.
So CTLA4, which is on the T cell,
binds to another CD receptor on the antigen presenting cell
and it says tamp down the response.
And the reason for that is
we want to keep our immune system in check.
This basically is a way of asking the immune system,
because remember, when the immune system sees that antigen, it wants to go nuts. It wants to start
replicating and killing. That this is a CD8 T cell. It is a targeted killer T cell. The checkpoint
says, let's double check that. Let's be sure let's tamp down the response. And as a result of that,
double check that. Let's be sure let's tamp down the response. And as a result of that, a thought experiment emerged which was what if we block CTLA4? What if we
block the checkpoint? Could we unleash the immune system a little bit more? And I
will say this, at the time it was proposed, it seemed a bit far-fetched.
Because of the complexity of the immune system, it seemed a little far-fetched that simply blocking
the checkpoint would have any effect. It's also worth noting that prior to this,
one immunotherapy had found some efficacy which was trying the exact opposite strategy.
Rather than blocking the inhibitor,
it was throwing more accelerant at the fire,
which was giving something called interleukin-2.
So interleukin-2 is, for lack of a better word,
candy and fuel for T cells.
So the idea was if we have T cells
that innately recognize a cancer antigen,
can we just give high doses of interleukin-2
and have them undergo proliferation and response?
And the answer turned out to be yes,
but only in two cancers, melanoma and kidney cancer,
and only at very small levels.
About 10% of the population would respond to these things.
Now look, that's 10% of people who were gonna be dead
within six months, because these are devastating cancers,
and once they spread, there are no treatments
that have any efficacy whatsoever.
In fact, I think median survival for metastatic melanoma
at the time was probably four months.
So this was a very grim death sentence.
But the idea now was, what about doing the exact opposite approach? Instead of trying to throw more fire at the T cell,
what if we can take its breaks down? Less gas, pardon me, instead of giving more gas,
let's give less breaks. And there were some phase two, some phase one studies that demonstrated efficacy phase two.
And the paper I'm gonna talk about today
is the phase three study
that compared the first version of these.
So the drug we're gonna talk about today
is an anti-CTLA-4 drug called Ipallilumab.
There is another drug out there that came along shortly
thereafter that is an anti-PD1 drug. So PD1 turns out to be another one of
these checkpoints on T cells. And the Nobel Prize, by the way, I think it was
2018 or 2019 in medicine or physiology was actually awarded to the two scientists who discovered CTLA4 and
PD1. So, you know, this, I believe this is the only Nobel Prize in medicine for
immunotherapy. It's a very big deal.
So this study sought to compare the effect of anti-CTLA4 to a placebo, and the placebo in this case was not a real placebo.
It was a peptide vaccine called GP100 to ask the question, in patients with metastatic melanoma, what would be the impact on median survival and overall survival.
So let's talk a little bit about the paper.
So again, one of the funny things about this is
I used to read these papers a lot, Andrew.
These used to be my bread and butter papers.
So I mean, reading these like I'm, you know, it's a my hobby.
And, and I don't read them that much anymore. So it was kind of amazing how long it took me to remind
myself of stuff I used to remember. But you do have to kind of go back and read the methods and figure
out who were the patients in this? What was the eligibility criteria? Why did they do it this way?
what was the eligibility criteria, why did they do it this way?
And of course it all kind of came back to me,
but it took a minute.
So the first thing is these are all patients
who had progressed through every standard therapy.
So these are patients for whom there were no other options.
These patients either had very advanced stage three melanoma,
which means it was local regional melanoma,
but it couldn't be resected.
So an example of that would be a cancer
that was completely engulfing,
like let's say the primary site was the cheek,
and it had completely grown
into all of the surrounding soft tissue.
It hadn't spread anywhere, but it was, you know, all the lymph nodes of the neck.
Um, and, and I've seen patients like this and it's, you know, it's just completely
disfiguring.
Um, and they'd already been through the standard chemotherapy and nothing was
working and the thing was growing.
And then it was mostly made up of patients with stage four cancer.
Now, melanoma has a very funny staging system.
So in cancer, we typically talk about something called the TNM staging system.
It is the standard way that cancers are staged.
T refers to the tumor size.
N refers to the lymph node status.
And M refers to the presence or absence of metastases.
And for most cancers, it is a very simple system.
It is, you know, T is typically a number one, two, sometimes up to three and four, N is typically zero,
one or two, and M is zero or one. Either there's no Mets or there are Mets. So for example, in
colorectal cancer, the T staging determines the depth in the colon wall that it went.
N is, did it go to METs? And I think in colon,
I'm a little rusty on this. I think colon has N zero one or two,
depending on how many lymph nodes and then M zero,
did it go to anything beyond that? Like to the liver lung, et cetera, or not.
Melanoma is a bit more complicated. It has M zero, meaning no METs,
but it also has M oneA, M1B, M1C and M1D.
And within each of those,
it has a threshold for high and low lactate dehydrogenase or LDH.
So it's both a staging based on imaging and biochemical.
And the reason for that is LDH level is such a strong prognostic
indicator of survival. In addition to M staging, higher LDH levels tend to
reflect more acidity, which we talked about why that's problematic, tends to
reflect faster growing tumors, higher turnover, higher metabolic activity. M1a,
let me see if I can remember this, M1As are cancers that have metastasized
to surrounding soft tissue
or soft tissue anywhere in the body,
so anywhere else on the skin.
And you might think, well, that's kind of crazy,
like how does that happen?
And it's really bizarre.
You can have a patient who had a melanoma
that showed up in one part of their body
and then they have metastases on other parts of their skin.
M1B is, and I always get B and C confused.
I think B is the lung.
So M1B is to the lung,
M1C is to any internal organ, so liver, et cetera,
and M1D is to the CNS.
And as those numbers increase,
as those letters increase, the prognosis gets lower and lower and lower. So one of the CNS. And as those numbers increase, as those letters increase,
the prognosis gets lower and lower and lower.
So one of the first things I always look at
when I look at a paper like this is,
tell me about the patient population.
Like what was the breakdown of patients?
And in table one, so that's again,
in clinical papers like this,
table one is always, always, always baseline characteristics. Um, oh, I should mention one other thing, Andrew,
this was done as a three to one to one randomization.
So again, in the simplest form, a study would have two groups, right?
You would have, um,
we're going to just have a treatment group and a placebo group.
But in this arm,
you had three groups with one of them being the placebo. The placebo got just GP 100, which is just a cancer vaccine.
By the way, this is a cancer vaccine that never showed any efficacy.
So it was a cancer vaccine that had been tested both with interleukin II directly
and as an adjuvant for patients who had metastatic
melanoma, sorry, not metastatic melanoma, who had melanoma resected, who were tumor-free,
and then given the vaccine as adjuvants to see did that have an effect on outcomes and
it didn't. So it's kind of a known placebo. So you had that group, then you had the anti CTA for group, and then you had anti CTA for
plus GP 100, as a rationale for the three to one to one, it's basically it increases statistical
power. Right. So, you know, this total study was a little under 700 people, they put 400 in the anti-CTLA4 plus GP100 group, and then, you know,
little over 130 in each of the other two groups. So you're always going to be able to make these
two comparisons, right? What you can check by doing this is, is there any effective GP100 in
this setting, which had never been done before. So again, GP100 is a known protein expressed by melanoma
and all of these people were haplotyped
to make sure that their immune system would recognize it.
And the question was,
would giving people anti-CTLA4,
i.e. taking the breaks off their immune system
with or without GP100 make a difference?
So kind of going through this, you can see it sort of skews about 60% to 40% male to
female. They talk about something called the ECOG performance status.
That refers to how healthy a patient is coming in.
So ECOG zero is no limitations whatsoever,
which is kind of amazing when you really consider something.
I think this speaks to just how devastating this disease is.
These are patients who all have like six months to live, right? You know, a year max. And yet look at this, 58 to 60% of them have no limitation on their quality
of life at this very moment. That's going to change dramatically, you know, absent a cure
here. And then ECOG-1 has some limitation.
And you can see that ECOG-1 plus ECOG-0
is basically 98% of the population.
You can see the staging there.
So again, very, very few of these patients
are the M0 category.
M0s are people who have stage three disease
that is so aggressive it can't be resected.
That's about 1%, but the majority
of these people are the M1A's, M1B's, M1C's. So these are people with very aggressive cancers.
You can also see that about 10 to 15% of these people also have CNS metastases. Again, the
poorest prognosis of the poor. And then you can see about 40% of them
have the LDH level above cutoff.
All of this is to say, we're talking about a group
of patients who have a very high likelihood
of not surviving more than a year.
It would be very unlikely that many of these patients
would survive more than a year.
So basically more than 70% of these people
have visceral metastases.
A third have high LDH and 10,
more than 10% have brain mets.
They've also all progressed through standard therapy.
So...
Radiation chemo.
Yeah, and the chemo for melanoma can be kind of a toxic chemo that really just doesn't really
do anything.
So is it commonplace to use a treatment that failed in clinical trials as a placebo in
these sorts of studies?
Yeah, it's interesting.
I think you're referring obviously to the GP 100.
And I think the thinking was, okay,
it hasn't been effective in other treatments,
for example, when combined with IL-2 or as an adjuvant,
but never before has it been tried
with a checkpoint inhibitor,
which is the technical term for this type of drug.
I think there was also some belief
that it would be easier to enroll patients.
I don't think they stated this, but that's often the case.
It would be easier to enroll patients if they would know
that even in the placebo arm,
they're still getting an active agent.
Got it.
And I suppose there's always the possibility
that the combination of the
failed drug with a new drug would work. And then so you're increasing the probability for novel discovery. For sure. And again, if you go back to the randomization of three to one to one,
it's really only one fifth or 20% of the participants that would get just the GP 100.
So in other words, you're basically telling people
when they come into this study, there's an 80% chance
you're going to get anti-CTLA4.
That's a much better set of odds than, you know,
your typical study where you're gonna be 50%
likely to get the agent of interest.
Right, and people who are literally dying of cancer,
they don't wanna be in the control group.
Right, that's right.
So the primary outcome for this study
actually changed in the study.
Now, they have to get permission to do that.
So the original primary endpoint
was the best overall response rate.
So I have to explain how response rates are measured.
This is a bit complicated.
Remember, all of these patients by definition
have measurable, visible cancer,
by visible either on the surface of their body,
but more likely on an MRI or CT scan.
So all of these patients had to be scanned,
head to toe within 12 weeks of enrollment.
Again, there's another thing I should point out here,
which I know you understand,
but it's always worth reminding people.
When a study like this takes place,
it usually takes place over many years.
And so it's not the case that all 700 of these patients
were enrolled on the same day and finished, you know,
we finished observing them on the same day.
No, no, no, this took place for a very long period of time.
This took place across tens of centers.
I can't remember if this was just globally
or across the world.
It might have been across the world.
And so every center really needs to adhere
to a very strict protocol.
And you have a central organization that is running this.
So you have a drug company.
I think this is Bristol Myers Squibb that makes the drug.
They provide the drug. And then you have a C company, I think this is Bristol, Bristol-Meyersquibb that makes the drug, they provide the drug.
And then you have a CRO, a clinical research organization
that is basically managing the trial.
And the trial is being done at cancer centers
all over the world or all over the country.
And, you know, enrollment, I think, began in 2008 for this.
No, no, I think it completed in 2008.
It probably started in about 2004, 2005.
And therefore you had to kind of have real clear protocols
around this.
So a complete response is the easier of these to understand.
A complete response is everything vanishes completely.
That's very rare in cancer therapy.
So instead what we kind of look for is a partial response.
A partial response, and there are really different ways
to define this, there are different criteria,
but this is the most common way you define a partial response.
A partial response is at least a 50% reduction
by diameter, because remember in this type of imaging,
you're looking at 2D versus 3D.
So if you're looking at a lung lesion and it's this big,
you know, if it's two centimeters long,
it has to go to at least one centimeter in diameter.
So it's a 50% reduction at least of every single lesion
with no new lesions appearing and no lesions growing.
So it's a very strict criteria.
Right. Again, CR means everything vanishes PR means at least a 50% by
diameter, which by the way is a much bigger diameter,
much bigger reduction in terms of tumor volume.
When you consider the linear versus the third power relationship of length and volume of every single lesion with nothing new appearing regardless of how small
and no lesion growing.
So that's a PR.
So you basically have no response, progression.
We talk about those together
and then partial response and complete response.
So initially the authors of this study were going to,
the primary endpoint of this was going to be
the best overall response rate. So what was the proportion of patients study were going to change, the primary endpoint of this was going to be the best overall response rate.
So what was the proportion of patients that hit PR?
What was the proportion that hit a CR?
That's very common in this type of paper
where the outcomes are typically so dire.
However, oh, I think I said that the study was,
I don't remember when the study ended,
but the amendment was made to change the primary endpoint
to overall survival at some point during the study.
So, and by the way, that tends to be the metric
everybody cares most about.
So the overall survival for metastatic melanoma is zero with the exception of people
who respond to interleukin-2, high dose interleukin-2, and that will boost the overall survival
rate to somewhere between 8 and 10 percent. Very, very low. These patients, many of whom had already taken
and progressed through interleukin-2.
Let me refresh my memory on what percentage of those patients,
about a quarter of these patients had already taken
high dose interleukin-2.
And by definition, the fact that they're in this study
means they had already progressed through that.
That treatment had failed.
Just reiterate, just kind of the state these patients are in.
So now let's look at figure one.
So again, I'll describe it because I realize many people are just listening to us.
All of this will be available both in the video and then we'll link to the paper.
So figure one is a figure that probably looks really familiar to people who
look at, you know, any data that deal with survival.
It's called a Kaplan-Meier survival curve.
So on the x-axis for this curve is time and time here is shown in months.
And on the y-axis is the overall survival at the very top 100% at the bottom 0%.
And it has three graphs or three curves that are superimposed on one another for each of the three
groups. Again, the control group, which is the GP100, the anti-CTLA4 group by itself,
and the anti-CTLA4 plus GP100. And one of the characteristics of a Kaplan-Meyer
curve is by definition, they have to be decreasing in a monotonic fashion because it's cumulative
overall survival. That just means it can't like come down and go back up. Nobody comes back to life.
So once a person dies, they are censored from the study and the curve drops and drops and drops.
And you can see that they kind of highlight and I actually think it makes
the graph a little harder to read when they, when they put some of those
marks on there.
But what really becomes clear when you look at this is that there's a key,
there's a clear distinction between the curve for the placebo group,
the GP 100 group and the other group, the GP100 group,
and the other two, the two treatment groups.
Now, you'll note at the very end
that the two treatment groups appear
to separate a little bit.
I'll talk about that in a second.
So when I look at these, Andrew,
the first thing I always turn my attention to,
I can't resist, I have to look at the right hand side
of the graph. Because what is that really telling me?
Right? The tail of this is showing me
the true overall survival.
And I want to sort of figure out what is going on.
So in the GP 100 group, which is the placebo group,
it is kind of amazing to think that there is still one person
who is alive at 44 months.
It's amazing. I mean, it's both sobering and amazing
that like one person made it to 44 months. The next thing I ask myself is, well, how
long did half of the people make it? That's called median survival. And to do that, you
go up to the y-axis and you draw a little line from the 50 over and then you bring that down.
And that's, you know, that's awfully low.
That's about, yeah, in fact the table will tell us exactly what that is because I think it's really hard to eyeball that stuff.
So let's go to, so there's always a table that will accompany these things.
And let's pull up that table.
I've got this paper spread out over so many things.
That's adverse events.
Where's our survival table here?
Your two subgroup analysis of overall survival.
It would probably be helpful if I stapled
these things together because it would be easy.
Well, this is always a trade off.
Actually, since this is a Journal Club episode,
I will say that stapling helps,
but it also prevents one from separating things out,
writing in the margins.
I like these little mini clips.
Yeah.
No financial relationship to the mini clips either.
Just have to state that because I always get,
if you don't say that, people go,
oh, you must have a stake in these mini clips.
I like these little mini clips.
In fact, I'm such a nerd.
I always have one of these Pilot V5, V7s on my pocket,
over my hip, and then my pockets are always filled
with these little mini clips.
And then again, I have a friend who's a musician
and he's always reigning guitar picks.
So, you know, as far as occupational hazards go
of being a nerd, these mini clips are pretty.
I'm a big fan of the mini clip as well, but I, I went without it today.
All right. So thank you. Yes. Table two. All right. So,
so let's look at table two while looking at the Kaplan-Meier curve.
Cause now this allows us to see a couple of things. By the way,
remember how I said there was like that one person who kind of is still alive
in the treatment group. Well,
you can tell that he's not a complete responder.
He or she is not a complete responder
because under evaluation of therapy in table two,
it says best overall response
and it says complete responders, zero.
So there was zero complete responders in the placebo.
There were two partial responders.
Again, a partial responder is some lesions got smaller,
some got bigger, stable disease is,
it didn't really change that much
and progressive disease is obviously it went beyond.
Not without.
And when you say partial response like lesions got smaller,
are they literally just tracing the circumference
of one of these skin lesions and saying,
okay, got bigger smaller?
Literally, we'd had rulers in clinic.
Like just more apology.
Yep, yep.
Gosh, this feels so crude in terms of like,
I mean, it makes total sense,
but like in terms of like modern medicine,
oh, like your lesion grew from like three millimeters
to six millimeters.
And they're literally like drawing little boundaries around little blotches on the skin.
Yeah, you're putting a little measuring tape on them.
Now, again, most of these are happening in the radiology suite because most of the disease
for these patients is inside the body.
Remember, more than 70% of these patients had visceral metastases.
So liver, soft tissue, lung, brain, you know, these are, in fact, if you include
lung, liver, brain and viscera, it's, it's all pretty much all the patients. So most
of this is looking at a CT scan or an MRI for the brain. Got it. Okay, so that's, that's
kind of the first thing that comes up. The median response rate should be shown pretty prominently here. So I'm looking
through this and where is median response? Maybe it's shown in a different table. Let's
see. Not disease control rate, time to progression.
I remember it's about 10 months, but maybe that's just in the text.
Yeah, here it is. So I thought this would be in a table, but it's on page
715 of the paper. It just reports it. So I'm sorry, I misspoke.
The 10 months was for the anti-CTLA4 plus GP100
and 6.4 months for the GP100 alone. That's the control.
And then 10.1 for the anti-CTLA4 alone.
Okay, so again, I'm just always doing this.
I'm kind of going back to the paper to be like,
does that make sense?
And yeah, you kind of called it, right? You said median survival was about eight.
Well, it turns out it's actually like six and change because, because it has that little
ding in it and it's out to a little past 10 on the two others. So the net takeaway here
is again, just to put that in English, because it's so profound, 50% of the patients in the control group were dead in six months.
50% of the patients in the treatment group, both treatment groups were dead in 10 months.
So what that means in cancer speak is these drugs extended median survival by four months.
Now, that's an important concept. You know, when we think about how
has cancer therapy changed over the past 50 years, median survival for
metastatic cancer has increased across the board. So a person today with
metastatic colorectal cancer, or a woman today with metastatic breast cancer, or
a person with metastatic lung cancer,
these people will live longer with those diseases today
thanks mostly to treatments.
This is not an early detection lead time bias issue.
This is treatments are allowing people to live longer.
And that's an important part of the story.
But it's only half of the story, yet
it often gets touted as the story. The other half of the story, and frankly, the story
that I think is more important is what is overall survival doing? And if you go back
to those cancers, the answer is zero. So overall survival hasn't changed for solid epithelial tumors.
It is, it was 0% in 1970 and it's 0% today.
Everyone dies.
Everyone dies from metastatic solid organ tumors.
Now again, there's those niche examples I gave you.
Testicular cancer is now an exception.
GI stromal tumors would be an exception and I'm not including leukemias and lymphomas
where now there are exceptions.
Okay, within not to try and be overly optimistic,
but if I look at the graph in figure one,
and I look out at the tail of the graph.
That's right.
And for those that are just listening, what I see,
and I'm far less familiar with this type of work
and this analyzing these type of data.
But what I see is that people in the placebo group,
they're all dead except that one.
They're basically all dead at 44 months.
But when I look at the number,
how long it takes for everyone to be dead
in the treatment groups.
It's like 50, looks like 53, 54 months or so.
Well, and they're not dead, that's the point.
They're hanging in there, right?
So because, you know, an extra,
as somebody who lost both of my scientific advisors,
two of the three, the other one, the suicide,
we've talked about this before,
but the other two to different cancers both had the Bracka II other one, the suicide. We've talked about this before. But the other two to different cancers
both had the Brackett 2 mutation by the way.
You know, an extra eight to 10 months with your kids
or with your spouse or to quote unquote
get your affairs in order is a big deal.
I mean, it's still depressing in the sense
that nobody survives long term, but you know,
an extra 10 months as long as one is not miserable
in that time, completely miserable.
I mean, that's extra 10 months of living, right?
Well, and what's interesting here is,
the observation period stops
and some of these patients are still going.
So what you're highlighting is kind of the point
I wanna make, which is overall survival is the most important metric.
And it's the highest bar, make no mistake about it.
And it's certainly not the bar any drug company is ever going
to want to talk about for a cancer drug.
But why not?
Because none of them work, right?
Like we don't have, you know, like drugs.
They only want to talk about cures.
They don't want to talk about media and survival.ugs only want to talk about cures. They don't want to talk about media and survival.
They want to, they only want to talk about extending media and survival. And, you know,
there are, you know, lots of people out there that are on this, on this platform. I don't need to
get onto it. But who will say like, look, it's a real racket in oncology today, where drugs
that are extending media and survival by four weeks are being put on the market at a tune of, you know,
50 to $100,000 per treatment.
That's not uncommon in oncology.
There was one drug that was approved for pancreatic cancer,
I believe it extended median survival by nine days,
and it cost $40,000.
And it's being advertised as significantly,
you know, extended survival.
Yes, because that was a statistical significant improvement
in median survival. So I'm just, yeah. So it's Yes, because it was that was a statistical significant improvement in median survival.
I'm just, yeah.
So it's like, it's really understandable why people are very skeptical of the
pharma industry.
And I think, you know, a much more nuanced view is necessary.
Clearly, I don't think pharma is all bad.
But I really understand why people lose faith in pharma when, when, you know,
these types of products somehow make regulatory approval.
Does insurance cover these kinds of drugs?
It can, in fact, it often does.
It depends on the FDA approval, of course,
in the indication, but a lot of times they do, right?
So yeah, there's a societal cost to these things,
but there's also a patient cost, right?
So a lot of times insurance doesn't fully cover it, and a patient has to bear the cost difference. And on top of that, you alluded to this a patient cost, right? So a lot of times insurance doesn't fully cover it and a patient has to bear the cost difference.
And on top of that, you alluded to this a second ago,
which is what if your quality of life
is dramatically compromised as a result of this treatment?
And yes, statistically you're gonna live nine days longer
or three weeks longer,
but at what cost to your health
in those final remaining days?
And by the way, you're potentially straddling
your loved ones with enormous debt in your absence.
So it's a super complicated topic.
There's a dignity component too.
I mean, I've seen this in people dying, you know,
at some point they become such a diminished version
of their former selves that they don't want to be seen
by people that way.
So what is exciting about this drug, although it's this paper is not the one that shows it, the reason I chose this paper Andrew is because it was the first approval. A second drug came along
that is an anti-PD1 drug, that drug is called K-truda, that drug turned out to be even better
and has even a greater response rate
both in terms of median survival and overall survival.
But this was the landmark paper.
I also have a slight bias here
and I'll disclose in a moment why.
But I think it just talks about very interesting biology.
So let's talk about a couple of things
that stuck out to me in this paper.
The first thing that stuck out to me,
and the authors didn't comment on it
unless they did and I missed it,
is look at Figure Two.
So Figure Two is the subgroup analyses
where you're sort of showing a similar graph to the one you showed earlier,
right, where you show the response rate or the change in response between the groups,
and then you put the error bars on it. And this is where we talk about how, well, it's a 95%
confidence interval, so does it touch the unity line? So these are called like tornado plots typically. And what you'll notice is that in the top, you're looking at sort of
it's comparing the anti-CTLA4 with GP100 versus the GP100. And in the bottom, you're looking
at the anti-CTLA4 versus the GP 100. So at
a glance, you can see GP 100 is not doing anything. I mean, that's the, that's the
first takeaway of comparing A to B. What I find most interesting is look at the subgroup
analysis of females. Notice that in females, while there's a trend towards risk reduction,
and this is risk reduction for overall mortality.
So again, I just want to restate that.
The primary outcome of this trial was changed
to overall survival, which I think is the better outcome,
by the way.
And overall for all patients,
when you compare anti-CTLA4 plus placebo versus placebo,
there was a 31% risk reduction in overall mortality.
That's what, that's the mathematical interpretation
of what you're seeing at the tail end
of that Kaplan-Meier curve.
Living longer.
Living longer.
And it sounds like a big difference.
And in some sense it is a big difference.
Well, it is for those people
because you're really looking at basically
zero percent surviving in the placebo
group versus 20% of people are still alive at 56 months in the treatment group.
But look, that means 80% have died.
But notice that, and sorry, when you just look at the
anti-CTLA4 plus GP100 in the subgroup B,
that hazard ratio is even showing more compression.
It's a 36% reduction in risk of death.
But notice that the females did not reach significance.
So in the first group, they barely do,
and you can see that because the
confidence interval runs from 0.55 to 0.92, and notice the error bar almost touches the
line. And in the second one, it does not reach significance at all. So I actually went and
kind of did a little reading on this after and I said, hey, you know, how much did this
study, was this an outlier study? And it turned out
it wasn't. And that about half the studies of anti-CTLA4 did indeed find that the drug
was less effective in women than men. Which I found interesting. Now, I couldn't find
any great explanation for it, but the most plausible explanations fit into two categories.
The first are maybe there are
differences in the immune response to the drug if you're a man or a woman. The second comes down
to dosing. I should have said this at the outset, but of course these drugs are not like a pill where
it's like everybody gets you know 50 milligrams of this. They're all dosed based on weight. So
this study is dosed I believe at three milligrams per kilogram.
And because most men are heavier than women, men are getting a higher dose than women.
And weight and body surface area and immune system, like these things are not all perfectly
linear. So I kind of wonder if this difference is simply explained by men on average getting a higher dose than women.
Interesting.
Last thing I want to talk about here is in table three. So table three, always an important table to look at in any paper is what are the adverse outcomes, right?
Where are the adverse effects of the drug?
Yeah, I spent a little bit of time with this
and I confess it, you know, I definitely don't want cancer
to the extent that I can avoid it,
but this table made me wonder whether or not
I would also want to just avoid cancer treatment
given the life extension provided.
I mean, these adverse events are pretty uncomfortable.
They sound like it, you know.
Yeah, so just to put in perspective,
and you always have to kind of be mindful
of how many of these adverse events are occurring in people
just because their disease is progressing.
So the first thing I always wanna look at is
total adverse events in all three groups, not just grade.
So grade three and grade four are real toxicities, right?
Grade four toxicity is life-threatening toxicity, by the way.
Grade three is pretty significant toxicity.
Grade one and two, we typically just, you know,
that's not that severe, right?
The little rash that puts some corticosteroids on it,
it went away, kind of thing.
Okay, so in the treatment plus GP 100 group,
98.4% of people reported some event.
So all but 1.6%.
In the NTC-TLA-4 group alone, it was 96.7%.
So only 3.1% did not.
But in the placebo group, it's 97%.
So it's more than to keep in mind,
like, you know, everybody's having some adverse effect.
Okay. Well, what if you say, well, let's just limit it to the most severe events?
Well, let's just talk about grade four toxicities.
There were 6.1% of those in the placebo group, 8.4% in the anti-CTLA4 group and 6.8% in the
combined group. So not a huge difference in grade four toxicity.
Meaning that whatever adverse events are occurring
may not be related to the treatment.
They may not be related to the treatment.
Again, these are, if you think about it,
and it's a very awful, sad, morbid thought to imagine,
these are, you're looking at the adverse responses
of people more than 80% of whom died
during the course of a very, very short study. And so, you know, it's very difficult to disentangle what effects
or what side effects a person is having just from that process as they are from the actual
treatment. But if there is an area where there's a really clear difference, It's down in the autoimmune category.
So if you look at any immune related events,
you can see that in the anti-CTLA4 plus GP 100 group,
it's about 60% in both of those treatment groups versus 30%.
And if you look at the grade three and four toxicities,
it's 10% in the anti-CTLA-4, 15% in the anti-CTLA-4 alone group, and only 3% in the treatment. So that's a real difference.
It makes sense that people getting this drug plus placebo or just the drug would have autoimmune
issues because this is an immunotherapy.
It's an immunomodulator.
In fact, what is it doing?
It is taking the breaks off the immune system.
But then again, the things that they list out,
peridus, is that a irritation of the skin?
Yeah, irritation of the skin.
I'm not a physician, but I know that any idus
is gonna be like an inflammation.
And OMA, unfortunately, likely a cancer or cell replication.
Look at the difference in vitiligo.
Ration, vitiligo.
I mean, wow.
Yeah.
So very little.
Sorry.
Sorry.
Look at the gastrointestinal differences.
Yeah.
And the vitiligo, right?
So 3.7%, 2.3%, 0.8%.
The GI stuff is the most common stuff you're going to see there. Those are the really big ones. Now, of course, there's diarrhea and there's diarrhea. Oh, 0.8 percent. The GI stuff is the most common stuff you're going to see there.
Those are the really big ones. Now, of course, there's diarrhea and there's
diarrhea. Like there's travelers' diarrhea, there's, you know, over the spicy large meal
that I mean, for diarrhea. And then there's like, can't really do anything besides make
trips back and forth to the bathroom. Well, there's, there's, there's put it this
way. There's, you know, colitis here is diarrhea so significant, these patients require IV fluids.
Now, what, what you don't see here is how many of these patients actually required corticosteroids
to reverse the autoimmunity.
So a lot of times what will happen here in these studies or with these drugs is the autoimmunity
becomes so significant that you have to stop the drug and give corticosteroids.
Do the exact opposite.
You now have to shut the immune system down.
So you just took the brakes off it with the drug and now you need to shut it down with
corticosteroids. When I was, was I in med school? No, when I was in my fellowship,
I wrote a paper about autoimmunity correlating with response rate in anti-CTLA-4 early on.
This was during the phase two work.
So the NCI was a very early adopter of participating in these trials.
And it was observed that, or at least hypothesized,
this is what the paper basically wrote about,
which was, is there any correlation
between autoimmunity and response?
And it turned out the answer was yes.
There was a very strong correlation.
So there was no difference in autoimmunity
between the doses.
And so the paper we wrote was two dosing schedules.
So it was basically the full dose,
the three milligrams per kilogram versus a low dose,
one milligram per kilogram.
This is a phase two trial.
Those are your two arms.
There turned out to be no difference
in autoimmunity between them,
but there was a big difference between
the response rate that tied to autoimmunity.
In other words, autoimmunity predicted response.
Now, I think over time, these investigators,
the doctors who administer these treatments
are getting better and better
at catching these things earlier
because these autoimmune conditions
can actually be devastating.
So on a very personal note,
when Kytruda came out,
I wanna say it was around 2011, no, no, no, gosh,
it must have been 2013, 2014, thereabouts.
Again, it was for treatment of metastatic melanoma.
I wanna come back and explain why melanoma
gets all of the attention in autoimmune condition,
in immunotherapy conditions, I'll state that. I want to come back and explain why melanoma gets all of the attention in autoimmune condition in
immunotherapy conditions. I'll state that but
But anyway a friend of mine
got pancreatic cancer and
he got the bad type of pancreatic cancer, so this is and like the
Adenocarcinoma the pancreas right so this is a non-survivable type of cancer. Furthermore, his was unresectable.
So-
Can you explain what that is?
Yeah, so about 20% of people who have pancreatic cancer
technically have it in a way where you could still take out
the head of the pancreas.
Right, the Whipple procedure.
The Whipple procedure.
Right.
Now tragically, most of those patients will still recur.
My understanding is that pancreatic cancer progresses
from anterior to posterior in the pancreas,
and that the Whipple is a removal of the front
and the anterior, that's the Whipple procedure.
So if the cancer has progressed far enough,
caudal into the posterior pancreas,
then there's nothing left to cut out, basically. Well, can we into the posterior pancreas, then there's nothing left to cut out basically. Well, we survive
without a pancreas for any amount of time. Oh, yeah,
absolutely. So why don't they just remove the whole pancreas?
Oh, that's my point. It's already micromatastasized. So
it's not the surgical procedure is not the challenge anymore.
It used to be. So, you know, at Johns Hopkins, which is one of
the hospitals where this was pioneered, like the 30-day mortality for a Whipple procedure was, I don't know, 80%. And the reason was to
figure out how to suture a pancreas to the bowel without the... So the pancreas is such an awful
organ to operate on because its enzymes are designed
to digest anything and everything. So imagine now you have to cut the pancreas in half,
take out the head of the pancreas with the duodenum, and then somehow sew that open half
of a raw pancreas to the end of the jejunum and not let it digest itself.
Someone at Hopkins figured this out?
No, the first one was actually done by AO Whipple,
but yes, at Hopkins is where they figured out the way
to put drains in, the surgical technique,
how to do it in two layers, what type of stitches to use,
like all of the nuances of this were worked out
in a few places,
but I would say Hopkins more than any place else.
And are there physicians who like try this on non-human primates
or something, or is this always just done on patients?
Well, nowadays, I mean, put it this way,
even 25 years ago, at a major center like Hopkins,
the mortality of that procedure was less than 1%.
Amazing.
Yeah, it totally-
So there have been some victories.
Well, yes, but here's my point.
That's no longer the bottleneck, right?
Taking out the pancreas safely,
as complicated and challenging as that is,
and if you need a whip procedure,
you only wanna have it done by someone
who just does that night and day,
because you don't want weekend warriors doing it.
That's not why people are living or dying.
They're dying because the cancer just comes back.
It was already spread to the liver by the time you did it,
you just didn't realize it yet.
So whether you took out the whole pancreas
or the head of the pancreas or the tail of the pancreas,
the location of the tumor is predictive of survival,
only in the extent that it basically is a window into how soon did symptoms occur.
So pancreatic cancers in the tail tend to be more fatal even though they're way easier
surgically to take out because by the time you develop symptoms of a tail pancreas cancer,
it's a big cancer.
I was going to ask this question later, but I'll just ask it now.
Given the link between the immune system and these cancers,
is there an idea in mind that people who are, let's say,
40 and older or 50 and older who don't yet,
they're not diagnosed with any cancer, would periodically
just stimulate their immune system
to wipe out whatever early cancers might be cropping up.
Just take a drug to just ramp up the immune system,
even to the point where you start having a little diarrhea,
maybe a few skin rashes, and then come off the drug.
Just basically to fight back whatever little cell growths
are starting to take place in skin or liver,
you know, maybe for, you know, three weeks out of each year.
I mean, why not?
Yeah, that's an interesting question.
I've never thought of it through that lens.
I suppose the question is,
what can we do to keep our immune systems
as healthy as possible as we age because-
Stay on a normal circadian schedule.
There's evidence for that.
Sure, no, there's evidence that certainly
if it promotes sleep, anything that promotes better rest
is going to promote immune health.
Because if you ask the macro question,
which is like why does the prevalence of cancer
increase so dramatically with age?
There are certain diseases where it's really obvious why the prevalence of the disease increases with age. There are certain diseases where it's really obvious
why the prevalence of the disease increases with age.
Yeah, like age-relay immaculate degeneration.
Sure, more cardiovascular disease is by far the most obvious
because it's an area under the curve exposure problem.
The more exposure to lipoproteins
and the more the endothelium gets damaged,
the more likely you are to accumulate plaque.
And again, it totally makes sense
why 10-year- olds don't have heart attacks
and 80 year olds do.
But when you sort of acknowledge that, well, hey,
you know, anybody's accumulating genetic mutations,
we're always surrounded and being bombarded by things
that are altering the genome of ourselves.
Is it simply a stochastic process
where the longer you live,
the more of these mutations you're gonna occur
until at some point one of them just wins?
I think that's gotta be a big part of it.
But I think another part of it,
and I clearly am not alone in thinking this,
is that our immune system is getting weaker and weaker
as we age, right?
I mean, people become more susceptible to infections
as they get
older. And I think that that's equally playing a role in our susceptibility to cancer. So,
yeah, I think the question is, how do you modulate immunity as you age? And to me, that's one of the
most interesting things about rapamycin, potentially, is that when taken the right way, it seems to
enhance cellular immunity.
Which again, that's potentially a really big deal.
Again, at least in short-term human experiments
in response to vaccination,
it's enhancing vaccine response.
So the question is, would that translate into cancer?
Nobody knows.
Could that be one of the reasons
why animals treated with rapamycin live longer
and get less cancer.
Don't know. You know, it could also be that it's at a fundamental level that's targeting
nutrient sensing. Where I was going with that story was that maybe I'll back up for a moment.
Why melanoma? So we didn't really know this like 30, 40 years ago in the early days of immunotherapy.
But what we know now is that most cancers probably have about 40 mutations in them.
That's like ballpark 40, 50 mutations is standard fare for a cancer.
But melanoma happens to be one of the cancers that has many, many more mutations.
And the more mutations a cancer has,
the more likelihood that it will produce an antigen
that's recognized as non-self.
And that's why in the early days of immunotherapy,
the only things that worked were IL2
against metastatic melanoma and kidney cancer,
because kidney cancer turned out to also be
one of those cancers that, for reasons that are not clear,
produced hundreds of mutations.
And so it's no surprise that the early studies
of checkpoint inhibitors were also done
in metastatic melanoma,
where you basically have more shots on goal.
Again, if I'm gonna take the breaks off my immune system,
I might as well do it in an environment
where there are more chances for my T cells to find something to go nuts against.
So it's 2013, 2014, and this friend of mine who has something called Lynch syndrome, which
is one of those few hereditary or germline mutations that results in a huge increase in the risk
of cancer. He had already had colon cancer at about the age of 40 and had survived that. It was a
stage three cancer, but he had survived it. Well, now five years later had developed pancreatic cancer.
And when he went to see the surgeon, they said, yeah, there's nothing we can do.
Like it's too advanced.
So that's, you know, to put that in perspective,
that is a death sentence.
And that's not, that's a six month survival.
And at around that time, there was a study that had come out
in the New England Journal of Medicine
that had talked about how patients with Lynch syndrome
had lots of mutations. And so we, you know, talked with his doctors
about the possibility of enrolling him in one of the Kytruda trials. There was one
going on, I think, at Stanford. And, you know, the thinking being, well, you know,
you would want to target a checkpoint inhibitor against somebody who has a lot
of mutations.
And even though typically we don't see that in pancreatic cancer, his is a unique variant of it because it's based on this.
And so sure enough, he was tested for these mismatch repair genes. He had them enrolled in the trial and amazingly had not only a complete regression of his cancer,
and he's still alive and cancer-free today,
10 years later. But the treatment worked so well at activating his immune system that
his immune system completely destroyed his pancreas. So now he is effectively had a pancreatectomy
based on his immune system. So now he actually has type one diabetes. He has no pancreas.
He injects insulin to do with it.
Yeah, yeah.
Or it increased.
No, no, he has to use insulin
just like some type one diabetes.
Okay, but he had to pick being alive
with type one diabetes.
Yeah, of course, no comparison.
But it's just an interesting example of how,
you know, remarkable this treatment was able to work
when you were, you know, you could completely
unleash the immune system of a person
and you eradicate the cancer and the rest of the cells around it. And, you know, there are many
organs we could live without. You know, there are certain organs you can't live without. I can't live
without your heart, lungs, liver, kidneys. But many things that kill people arise from organs,
the breast, you could live without all breast tissue,
prostate, prostate, you can live without all prostate.
Would choose to live without these.
Right. But I'm saying if you had metastatic cancer and you had a bullet that could
selectively target a tissue, you would take it. And right now the only tissue we
can do that against is a CD19 B cell. And that's what those CAR T cells are. So right now these are not
tissue specific treatments, but they're mutation specific. What the last thing I'll
say by this paper that I found interesting and I was looking for it and I was
surprised they didn't at all comment on if there was any correlation between
autoimmunity and response. So they obviously acknowledge the autoimmunity in table three,
but I would have loved to have seen a statistical analysis
that said, hey, is there any correlation
between response rate and autoimmunity?
But they didn't comment to that effect.
So we're left kind of wondering what the current state
of that is.
And I guess in summary, I'll say that the reason
I thought this was an interesting paper to present
is that I still believe that immunotherapy
is probably the most important hope we have
for treating cancer.
And well, I think we're still only scratching
the surface of it.
So collectively, the overall survival increase
for patients with metastatic solid organ tumors
is about 8% better than it was 50 years ago.
And virtually all of that has come from
some form of immunotherapy.
I think is promising.
And I think the holy grail is that,
meaning the next step,
if you go back to where we started the discussion,
is coming up with ways to engineer T cells
to be even better recognizers of antigens.
And there's many ways to do that.
One is to directly engineer them.
Another is to find T cells
that have already migrated into tumors.
Those are called tumor infiltrating lymphocytes or TIL and expanding those and engineering
them to be better and younger.
Is it possible to engineer our own T cells to be more pH variant tolerant?
Meaning, since this cloaking of a local area by changing the pH, could we pull some T cells?
I'm always saying about the inoculation stuff, like pull some T cells as part of our standard
exam when we're 30 and grow some up in an environment that the pH is slightly more acidic than normal
and then reintroduce them to the body. I mean, after all,
they are our T cells. In other words, give them a little opportunity to evolve
that the conditions they can thrive in, right? Or even just keep them in the freezer in case we
use them. Yes. So the interesting thing is, I don't know that if you just got them to be
comfortable in a lower pH, it would be sufficient because there are still so many other things that the
cancer is doing as far as using other secreting factors.
It seems that by far the most potent thing comes down to expanding the number
of T cells that recognize the antigen and making sure
that you can get that number big enough
without aging them too much.
So in some senses, it has become a longevity problem
of T cells.
The way to think about it is you want an army of soldiers
who are wise enough to recognize the bad guys,
which comes with age, but young enough to go and kill.
And right now, both extremes seem to be unhelpful, right?
When you go and find tumor infiltrating lymphocytes
in a tumor, they're very wise.
They know which one, they've demonstrated
that they can do everything.
They can outmaneuver the cancer,
but they're too old to do anything about it.
And when you take them out to try to expand them
by three logs, which is typically what you need to do,
expand them by a thousand fold, they can't do anything.
Got it.
And what about avoiding melanoma altogether?
I mean, obviously avoiding sunburn.
You know, somehow I got couched as anti-sunscreen
and that is absolutely not true.
I said some sunscreens contain things that are clearly immune
disrupt, endocrine, excuse me, disruptors.
And we're going to do a whole episode on sunscreen.
Maybe we could do some general questions on them.
It's funny, I think I'm actually planning something on that as well.
I want to do that.
Yeah.
I mean, and some dermatologists reached out some very, very skilled dermatologists
reached out and said that indeed some sunscreens are downright dangerous.
But of course melanoma is super dangerous
Physical barrier no one disputes physical barriers for sunscreen right everyone everyone agrees that that is unlikely to have endocrine disruption
So physical barriers are undisputed, but aside from limiting
Sunlight exposure to the skin
What are some other risks for melanoma?
I mean, I think that's the biggest one.
I do not believe that smoking poses a risk for melanoma.
And if it does, it's going to be very small.
There are hereditary cases.
So one needs to be pretty mindful
when taking a family history.
And by the way, there are really weird genetic conditions
that link melanoma to other cancers,
such as pancreatic cancer, by the way.
So whenever I'm taking somebody's family history and I hear about somebody that had melanoma
and someone that had pancreatic cancer, there's a couple of genetics, genetic tests we'll
look at to see if that's a person that's particularly sensitive, just from a genetic
predisposition.
But I do think that first and foremost,
and by the way, I think with melanoma,
although it's not completely agreed upon,
I think it's less about sun exposure
and more about sunburn, right?
So, and again, I'm sure there's somebody listening to this
who will chime in and apply a more nuanced response to that.
But I think there's a fundamental difference
between a mountain in the sun getting sun,
making some vitamin D versus I'm getting scorched
and undergoing significant UV damage.
There might also be something to be said
for the time in one's life.
And I've certainly seen things that suggest
that early repeated sun burns would be more of a risk.
So look, I think that's not a controversial point in the sense that like who wants to be sunburned,
right? So it's like, whatever one needs to do to be sunburned, whether it's, you know, you know,
being mindful of what the UV index is, wearing the appropriate cover, wearing the appropriate
sunscreen, I also find the whole anti-sunscreen establishment
to be a little bit odd.
Well, the anti-sunscreen establishment is odd.
I'm trying to open the door for a nuanced discussion
about the fact that some sunscreens really do
contain things like oxybenzines and things that are real.
Yeah, but when you're spraying them on kids.
Yeah, yeah, yeah, but when you just look at the straight,
the good old fashioned mineral sunscreens.
Yeah, perfectly safe.
Yeah, yeah.
As far as we know, I mean, I also dare we cross the seed oil debate into this.
Some of the folks who are really anti seed oil also claim that seed oils increase risk for sunscreen.
screen. Peter and I are smiling because we have teed up a debate soon with some, you know, anti-seed oil and less anti-seed oil experts. So that's forthcoming. That's going to be
a fun one. We'll be doing all of that with our shirts on.
I really appreciate you walking us through this paper, Peter. I have never looked at a paper on cancer,
and certainly not one like this.
I learned a lot, and it's such an interesting field,
obviously because of the importance of getting people
with cancer to survive longer and lead better lives,
but also because of the interaction with the immune system.
So we learned some really important immunology.
Yeah, and this was great.
I feel much more confident now in the belief
that the exposure to light early and late in the day
can actually have benefits.
And as I said, I think that there's,
I think there's some causality here
and I think it shouldn't be ignored.
Cool, well, this was our second Journal Club.
I look forward to our third.
Next time you'll go first, we'll just keep alternating.
And we've also switched venues,
but we both wore the correct shirt.
And I hope people are learning,
and not just learning the information,
but learning how to parse and think about papers.
And I certainly learned from you, Peter.
Thank you so much. Yeah, thanks Andrew from you, Peter. Thank you so much.
Yeah, thanks Andrew, this is great.
Thank you for joining me for today's
Journal Club discussion with Dr. Peter Atia.
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