Journal Club with Dr. Peter Attia | Metformin for Longevity & The Power of Belief Effects

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 first Journal Club episode between

myself and Dr Peter attia for any of you

that are not familiar with Dr Peter

attia he is a medical doctor in MD who

is an expert in all aspects of health

and lifespan he is the author of a

best-selling book entitled outlive which

is a phenomenal resource on all things

Health span and lifespan and he is the

host of the very popular podcast the

drive where he interviews various

experts in all domains of medicine and

scientists as well today Peter and I

hold our first online collaborative

Journal club for those of you that

aren't familiar with what a journal Club

is a journal Club is a common practice

in graduate school and or medical school

whereby students get together to discuss

one or two papers to critique those

papers and to really compare their own

conclusions of those papers with the

conclusions of the authors and to

highlight any key takeaways Peter and I

have been wanting to do a journal club

together are for a very long time and we

decided to do that journal club and to

record it for you so today you will be

sitting in on the first huberman Atia

Journal club by the way it could just

have easily been called the Atia

huberman Journal club and we will

discuss two papers first Peter is going

to discuss a paper on Metformin which is

a drug that many people are interested

in for its potential role in longevity I

want to highlight potential there he's

going to compare that paper to previous

findings on Metformin and by the end of

that discussion he will advise as to

whether or not he himself would take

metformin and whether or not other

people might be well advised or

ill-advised to take Metformin based on

the data in that paper and at this time

then I present a paper which is about

the placebo effect I have to imagine

that most of you have heard of the

placebo effect but what's interesting

about the paper that we discussed today

is that it shows that the placebo effect

can actually follow a dose response so

it's not just all or none it actually is

the case that you can scale the degree

of placebo effect depending on whether

or not you're thinking you're taking low

doses moderate doses or high doses of a

particular drug and the particular drug

that's discussed in the paper that I

cover is nicotine so for those of you

that are interested in cognitive

enhancement by way of pharmacology or

frankly for people who are simply

interested in how our beliefs can shape

our physiology I think you'll find that

discussion to be very interesting so by

the end of today's episode You Will Not

only have learned about two novel sets

of findings one in the realm of

longevity as it relates to metformin and

another in the realm of neurobiology and

placebos or Placebo effects but you will

also learn how a journal Club is

conducted I think you'll see in

observing how we parse these papers and

discuss them even arguing in them at

times that what scientists and

clinicians do is they take a look at the

existing peer-reviewed research and they

look at that peer-reviewed research with

a fresh eye asking does this paper

really show know what it claims to show

or not and in some cases the answer is

yes and in other cases the answer is no

what I know is for certain is that by

the end of today's episode you will

learn a lot of science you'll learn a

lot about health practices some of which

you may want to apply or avoid and

you'll learn a lot about how science and

medicine is carried out 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

Helix sleep Helix sleep makes customized

mattresses to give you the best possible

night's sleep now sleep is the

foundation of mental health physical

health and performance when we are

sleeping well and enough mental health

physical health and performance all

stand to be at their best one of the key

things to getting a great night's sleep

is to make sure that your mattress is

tailored to your unique sleep needs

Helix sleep has a brief two minute quiz

that if you go to their website you take

that quiz and answer questions such as

do you tend to sleep on your back your

side or your stomach do you tend to run

hot or cold in the middle of the night

maybe you don't know the answers to

those questions and that's fine at the

end of that two-minute quiz they will

match you to a mattress that's ideal for

your sleep needs I sleep on the dusk at

the usk mattress and when I started

sleeping on a dust mattress about two

years ago my sleep immediately improved

so if you're interested in upgrading

your mattress go to Helix sleep.com

huberman take their two-minute sleep

quiz and they'll match you to a

customized mattress for you and you'll

get up to 350 off any mattress order and

two free pillows again if interested go

to helixsleep.com huberman for up to 350

off and two free pillows today's episode

is also brought To Us by levels levels

is a program that lets you see how

different foods and behaviors affect

your health by giving you real-time

feedback using a continuous glucose

monitor one of the most important

factors impacting your immediate and

long-term health is the way that your

body manages its blood glucose or

sometimes referred to as blood sugar

levels to maintain energy and focus

throughout the day you want to keep your

blood glucose steady without big Spa

bikes or dips using levels you can

monitor how different types of foods and

different food combinations as well as

food timing and things like exercise

combined to impact your blood glucose

levels I started using levels a little

over a year ago and it gave me a lot of

insight into how specific Foods were

spiking my blood sugar and then leaving

me feeling tired for several hours

afterwards as well as how the spacing of

exercise and my meals was impacting my

overall energy and in doing so it really

allowed me to optimize how I eat what I

eat when I exercise and so on such that

my blood glucose levels and energy

levels are stable throughout the day if

you're interested in learning more about

levels and trying a continuous glucose

monitor yourself go to levels.link

huberman right now levels is offering an

additional two free months of membership

again that's levels.link l-i-n-k slash

huberman to get two free months of

membership and now for my journal Club

discussion with Dr Peter attia Peter so

good to have you here so great to be

here my friend

this is something that you and I have

been wanting to do for a while and it's

basically something that we do all the

time which is to peruse the literature

and find papers that we are excited

about for whatever reason

and oftentimes that will lead to a text

dialogue or a phone call

or both but this time we've opted to

try talking about these papers that we

find particularly exciting in real time

for the first time

as this podcast format first of all so

that people can get some sense of why

we're so excited about these papers we

we do feel that people should know about

these findings

and second of all that it's an

opportunity for people to learn how to

dissect information and think about the

papers they hear about in the news the

papers they might download from PubMed

if they're inclined but also just to

start thinking like scientists and

clinicians and get a better sense of

what it looks like to

pick through a paper The Good The Bad

and The Ugly so we're flying a little

blind here which is fun

um I'm definitely excited for all the

above reasons yeah no this is uh you and

I have been talking about this for some

time and and

um you know actually we used to run a

journal club inside the practice where

once a month one person would um just

pick a paper and you'd go through it in

kind of a formal Journal Club

presentation we've gotten away from it

for the last year just because we've

been a little stretched then I think

it's something we need to resume because

it's uh it's a great way to learn and

it's a skill you know people probably

ask you all the time because I know I

get asked all the time hey what are the

do's and don'ts of interpreting you know

scientific papers is it enough to just

read the abstract

um and you know usually the answer is

well no

um but the how-to is is tougher and I

think the two papers we've chosen today

illustrate two opposite ends of the

spectrum you know you're gonna obviously

talk about something that we're going to

probably get into the technical nature

of the assays the limitations Etc and

the paper ultimately I've chosen to

present although I apologize I'm

surprising you with this up until you

know a few minutes ago is is actually a

very straightforward simple

epidemiologic paper that I think has

important significance I had originally

gone down the rabbit hole on a much more

nuanced paper about ATP binding

cassettes in cholesterol absorption But

ultimately I thought this one might be

more interesting to a broader audience

by the way I got to tell you a funny

story so I had a dream last night about

you

and um in this dream

you were obsessed with making this

certain drink that was like your Elixir

and it had all of these crazy

ingredients in it some tons of

supplements in it but the one thing I

remembered when I woke up because I

forgot most of them I was really trying

so hard to remember them one thing that

you had in it was do

like you had to collect a certain amount

of dew off the leaves every morning to

put into this drink it was so but it was

like just sounds like something that I

would do and and so but here's the best

part you had you had like a thermos of

this stuff that had to be with you

everywhere and all of your clothing had

to be tailored with a special pocket

that you could put the thermos into so

that you were never without the special

Andrew drink and again you know how

dreams when you're having them seem so

logical and real and then you wake up

and you're like

doesn't even make sense like why would

he want the thermos in his shirt like

that I would warm it up like you know

all these but but boy it was a realistic

dream and there were lots of things in

it including Dew special do off the

leaves every morning I love it well it's

not that far from reality I'm a big um

fan of yerba mate I'm drinking it right

now in fact

um in its many forms usually the loose

leaf I don't tend to drink it out of the

gourd my dad's Argentine so that's where

I picked it up I started drinking it

when I was like five years old or

younger which I don't recommend people

do is heavily caffeinated don't drink

the smoked versions either folks I think

those are potentially carcinogenic but

this thing that you describe of of

carrying around the thermos close to the

body

if you are ever in Uruguay or if you

ever spot grown men in a restaurant

anywhere in the world carrying a thermos

with them and to their meals and hugging

it close

chances are they're Uruguayan and

they're drinking yerba mate they drink

it usually after their meals supposed to

be good for your digestion so it's not

that far from from reality I don't carry

the thermos but I do drink mate every

day and um I'm gonna start collecting

dew off the leaves uh just a few drops

every morning

oh my

um some other time we can talk about

dreams recently I've been doing some

dream exploration I've had some

absolutely transformative dreams for the

first time in my life one dream in

particular that has that allowed me to

feel something I've never felt before

and has catalyzed a large number of

important decisions in a way that no

other experience waking or sleep has

ever impacted me and this was drug free

Etc

um and do you think you could have had

that dream we don't have to get into it

if you don't talk about it now but was

there a lot of work you had to do to

prepare for that dream to have taken

place oh yes yeah

um at least uh 18 months of intensive

um analysis type work

um with a very skilled psychiatrist but

I wasn't trying to seed the dream yeah

yeah it was just I I was at a sticking

point with a certain process in my life

and then

I was taking a walk while waking and

realized

that my brain my subconscious was going

to keep working on this I just decided

it's going to keep working on it and

then two nights later I traveled to a

meeting in Aspen and I had the most

profound dream ever where I was able to

sense something and feel something I've

always wanted to feel as so real within

the dream woke up knew it was a dream

and realized this is what people close

to me that I respect have been talking

about but I was able to feel it and

therefore I can actually access this in

my Waking Life it was it was it was

absolutely transformative for me

um anyway sometime I can share more

details with you or the audience but for

now maybe we should talk about these

papers very well

um who should go first

I'm happy to go first this one's this

one's this is a pretty straightforward

paper so so we're going to talk about a

paper titled reassessing the evidence of

a survival advantage in type 2 diabetics

treated with metformin compared with

controls without diabetes a

retrospective cohort study this is by

Matthew Thomas Keyes and colleagues this

was published last fall

um

why is this paper important so this

paper is important because

in 2014 uh banister published a paper

that I think in many ways kind of got

the world very excited about metformin

so it was almost 10 years ago

and I'm sure many people have heard

about this paper even if they're not

familiar with it but they've heard the

concept of the paper and in many ways

it's the paper that has led to the

excitement around the potential for zero

protection with metformin and I should

probably just Define for the audience

what Giro protection means when we think

probably also sorry to interrupt what

metformin is just for the uninformed

that's a great point so I'll start with

the with the latter so metformin is a

drug that has been used for many years

uh depends you know where it was first

approved I think was in Europe

um but you know call it directionally 50

plus years of use as a first line agent

for patients with type 2 diabetes in the

U.S maybe 40 plus years so this is a

drug that's been around forever trade

name glucophage or brand name and uh but

but again it's you know it's a generic

drug today

the mechanism by which metformin works

is debated hotly but what I think is not

debated is the immediate thing that

metformin does which is it inhibits

complex one of the mitochondria so again

maybe just taking a step back so the

mitochondria as everybody thinks of

those as the cellular engine for making

ATP so the most efficient way that we

make ATP is through oxidative

phosphorylation where we take either

fatty acid pieces or a breakdown product

of glucose once it's partially

metabolized to pyruvate we put that into

an electron transport chain and we

basically trade chemical energy for

electrons that can then be used to make

phosphates onto ADP so it's you know you

think of everything you do eating is

taking the chemical energy and food

taking the energy that's in those bonds

making electrical energy in the

mitochondria those electrons pump a

gradient that allow you to make ATP

to give a sense of how Primal and

important this is if you block that

process completely you die so

everybody's probably heard of cyanide

right cyanide is something that is

incredibly toxic even at the smallest

doses cyanide is a complete Blocker of

this process and if my memory serves me

correctly I think it blocks complex four

of the mitochondria I don't know if you

recall if it complex three are complex

four I know a lot about toxins that

impact the nervous system but I don't

know a lot about poison but if ever you

want to have some fun we can talk about

all the dangerous stuff that animals

make and insects make and how they kill

you yeah

prototoxin and all these things that

blocks

I I really geek out on this stuff

because it allows me to talk about

Neuroscience animals and scary stuff

it's like combines it so we could do

that sometime for fun maybe at the end

if we have a few moments so so you know

something like cyanide that is a very

potent inhibitor of this electron

transport chain will kill you instantly

people understand that of course a drop

of Cyanide and you would you would be

dead literally instantaneously yeah

so metformin works at the first of those

complexes I believe there are four if my

memory serves correctly four electron

transport chain complexes and um but of

course it's not a complete inhibition of

it it's just kind of a weak Blocker of

that and the net effect of that is what

so the net effect of that is that it

changes the ratio of adenosine

monophosphate to adenosine diphosphate

um what's less clear is why does that

have a benefit in diabetics because what

it unambiguously does is reduces the

amount of glucose that the liver puts

out so hepatic glucose output is one of

the fundamental problems that's

happening in type 2 diabetes you may

recall I think we talked about this even

on a previous podcast

you and I sitting here with normal blood

sugar have about five grams of glucose

in our total circulation that's it five

grams think about how quickly the brain

will go through that

within minutes

so the only thing that keeps Us Alive is

our liver's ability to titrate out

glucose and if it puts out too much for

example if the glucose can if the

glucose level was consistently two

teaspoons you would have type 2 diabetes

so the difference between being

metabolically healthy and having you

know profound type 2 diabetes is one

teaspoon of glucose in your bloodstream

so the ability of the liver to Tamp down

on high glucose output is important

metformin seems to do that so can I just

ask oh one question is it fair

um to provide this overly simplified

summary of the biochemistry which is

that when we eat the food is broken down

but the breaking of bonds creates energy

that then our cells can use in the form

of ATP and the mitochondria are

essential of that process and that

metformin is partially short-circuiting

the energy production process and so

even though we are eating when we have

metformin in our system presumably there

is going to be less

net glucose the bonds are going to be

broken down we're chewing we're

digesting but less of that is turned

into blood sugar glucose well sort of I

mean it's not

um

it's not depriving you of ultimately

storing that energy what it's doing is

changing the way the body

um partitions fuel that's probably a

better way to think about it to be a

little bit more accurate so

um for example like it's not depriving

you of the calories that are in that

glucose that would be you know fantastic

but that was the that was the uh Electra

remember the Electra from the 90s

Electra folks for those of you don't

remember

um by the way if you ever ate this stuff

you'd remember because it was a fat that

was not easily digested it had sort of

in sort of analogous to plant fiber or

something like that so it was being put

into potato chips and whatnot and the

idea is that people would

um would simply excrete it

um and I don't know what happened except

that people got a lot of stomach aches

and um

in the world we know that the anal

seepage is what really did that product

only a physician

because after all Peter's a clinician

for physician and MD and I'm not

um could find it a um an appropriate

term to describe yeah when you have that

much when you have that much fat

malabsorption you start to have

accidents wow

and so that did away with that product

right it was either that or the diaper

industry was trying to really take off

okay that's why you don't hear about

Electro that's right so so we've got

this drug we've got this drug metformin

it's considered a perfect First Line

agent for people with type 2 diabetes so

again what's happening when you have

type 2 diabetes uh the primary insult

probably occurs in the muscles and it is

insulin resistance everybody hears that

term what does it mean uh insulin is a

peptide it binds to a receptor on a cell

so let's just talk about it through the

lens of the muscle because the muscle is

responsible for most glucose disposal it

gets glucose out of the circulation high

glucose is toxic we have to put it away

and we want to put most of it into our

muscles that's where we store 75 to 80

percent of it

when insulin binds to the insulin

receptor tyrosine kinase is triggered

inside so just ignore all that but a

chemical reaction takes place inside the

cell that leads to a phosphorylation so

ATP donates a phosphate group and a

transporter just think of like a little

tunnel like a little straw goes up

through the level of the cell and now

glucose can freely flow in so I'm sure

you've talked a lot about this with your

audience things that move against

gradients need pumps to move them things

that move with gradients don't glucose

is moving with its gradient into the

cell it doesn't need active transport

but it does need the transporter put

there that requires the energy

that's the job of insulin

by the way I did not know that I mean I

certainly know active and passive

transport as it relates to like

neurotransmitter and ion flow

um but I'd never heard that when insulin

binds to a cell that literally a little

straw is placed into the membrane

glucose doesn't need a pump to move it

in

um because there's much more glucose

outside the cell than inside so it's

just but the energy required is to move

the straw up to the cell so biology is

so cool yeah it is so so what happens is

as and Gerald Shulman at Yale did the

best work on elucidating this as the

intramuscular fat increases and I by

intramuscular I mean intracellular fat

uh triasil and disoglycerides accumulate

in a muscle cell that signal gets

interrupted and all of a sudden I'm

making these numbers up if you used to

need two units of insulin to trigger the

little transporter now you need three

and then you need four and then you need

five you need more and more insulin to

get the thing up that is the definition

of insulin resistance the cell is

becoming resistant to the effect of

insulin and therefore the early Mark of

insulin resistance the canary in the

coal mine is not an increase in glucose

it's an increase in insulin so normal

glycemia with hyperinsulinemia

especially postprandial meaning after

you eat hyperinsulinemia is the thing

that tells you hey you're five ten years

away from this being a real problem

so fast forward many steps down the line

someone with type 2 diabetes has long

passed that system now not only are they

insulin resistant where they just need a

boatload of insulin which is made by the

pancreas to get glucose out of the

circulation but now that system's not

even working well and now they're not

getting glucose into the cell so now

their glucose level is elevated and even

though it's continually being chewed up

and used up because again the brain

alone would account for most of that

glucose disposal

the liver is now becoming insulin

resistant as well and now the liver

isn't able to regulate how much glucose

to put into circulation and it's

overdoing it so now you have too much

glucose being pumped into the

circulation by the liver and you have

the muscles that can't dispose of it and

it's really a vicious brutal Cascade

because the same problem of fat

accumulating in the muscle is now

starting to happen in the pancreas and

now the relatively few cells in the

pancreas called beta cells that make

insulin are undergoing inflammation due

to the fat accumulation within the

pancreas itself and so now the thing

that you need to make more insulin is

less effective at making insulin so

ultimately way way way down the line a

person with type 2 diabetes might

actually even require insulin

exogenously could you share with us a

few of the causes of type 2 diabetes of

insulin resistance I mean one it sounds

like is accumulating too much fat yeah

so energy imbalance would be an enormous

one inactivity or insufficient activity

is probably the single most of important

so when Gerald Shulman was running

clinical trials at Yale they would be

recruiting undergrads to study obviously

because you're typically recruiting

young people and they would you know be

doing these very detailed mechanistic

studies where they would require actual

tissue biopsies so you know you're going

to biopsy somebody's quadriceps and

actually look at what's happening in the

muscle well I remember him telling me

this when I interviewed him on my

podcast he said the most important

criteria of the people we interviewed is

because they were still lean these

weren't people that were overweight but

they had to be inactive you couldn't

have active people in these studies so

exercising is one of the most important

things you're going to do to ward off

insulin resistance but there are other

things that can cause insulin resistance

sleep deprivation has a profound impact

on insulin resistance I think we

probably talked about this previously

but if you you know some very elegant

mechanistic studies where you sleep

deprive people you know you let them

only sleep for four hours for a week

you'll reduce their glucose disposal by

about half

which is I mean that's a staggering

amount you're basically inducing

profound insulin resistance in just a

week of sleep deprivation

hypercortisolemia is another factor and

then obviously energy imbalance so where

when you're when you're accumulating

excess energy when you're getting fatter

if you start spilling that fat outside

of the subcutaneous fat cells into the

muscle into the liver into the pancreas

all those things are exacerbating and

got it okay so enter metformin

first line drug so most of the drugs so

every drug you give a person with type 2

diabetes is trying to address part of

this chain so some of the drugs tell you

to make more insulin that's that's one

of the strategies so here are drugs like

sulfona ureas they tell the body make

more insulin

other drugs like insulin just give you

more of the insulin thing metformin

tackles the problem elsewhere it tamps

down glucose by addressing the glucose

the hepatic glucose output channel glp-1

agonists are another drug they increase

insulin sensitivity initially causing

you to also make more insulin um so

that's ozempic yes yeah and is it true

that berberine is more or less the poor

man's metformin yep okay yeah it's a

from a tree bark it just happens to have

these same properties yeah and by the

way reducing mtor and reducing blood

glucose yeah and Metformin by the way

occurs from a lilac plant in France like

that's where it was discovered so it's

also metformin is also based on a

substance found in nature so you you

need a prescription for metformin you

don't need a prescription for berberine

correct but yeah we can talk about

berberine a little bit later I had a

couple great experiences with berberine

and a couple bad experiences interesting

or green yeah so um

maybe taking one step back from this in

2011 I became very interested in

metformin personally just reading about

it obsessing over it and just somehow

decided like I should be taking this so

I actually began taking metformin I

still remember exactly when I started I

started it in May of 2011 and I realized

that because I was on a trip with a

bunch of buddies we went to the

Berkshire Hathaway shareholder meeting

which is uh you know the Buffett uh

shareholder meeting and uh you know it

was kind of like a fun thing to do and I

remember being so sick the whole time

because I didn't titrate up the dose of

Metformin I just went straight to two

grams a day which is kind of like the

full dose and we went to this is that

characteristic of your approach to

things

yes I think that's safe to say next time

I'll give you a thermos of this Dew that

I collect in the morning

[Laughter]

so I remember being so sick that the

whole time we were in Nebraska or Omaha

I guess I couldn't we went to Dairy

Queen because you do all the Buffett

things when you're there right like I

couldn't have an ice cream at Dairy

Queen you couldn't I mean I could I'm so

nauseous oh because I would say if

you've got metformin in your system

you're going to buffer glucose you could

have four ice cream cones except I

couldn't put I couldn't keep anything

down I mean I was so nauseous so so

clearly metformin has this side effect

initially which is a little bit of

appetite suppression but regardless

that's the story on Metformin there are

a lot of reasons I was interested in it

um I wasn't thinking true zero

protection that term wasn't in my

vernacular at the time but what I was

thinking is hey this is going to help

you buffer glucose better it's got to be

better and this was sort of my first

foray into you know self-experimentation

do you want to Define zero protection

yeah yeah it's a good term geriatric

Giro yeah so so yeah Jiro from from

geriatric old protection so protection

from aging and when we talk about a drug

like metformin or rapamycin or even NAD

NR these things the idea is we're

talking about them as Giro protective to

signal that they are drugs that are not

targeting a specific disease of Aging

for example a pcsk9 inhibitor is sort of

zero protective but it's targeting one

specific pathway which is cardiovascular

disease and dyslipidemia whereas the

idea is a zero protective agent would

Target Hallmarks of Aging there are nine

Hallmarks of Aging please don't ask me

to recite them I've never been able to

get all nines straight but people know

what we're talking about right so

decreased autophagy increased senescence

decreased nutrient sensing or defective

nutrient sensing uh proteomic

instability genomic instability

methylation all of these things

epigenetic changes those are all the

nine Hallmarks of eight to seven yeah

yeah so a zero protective agent would

Target those deep down biologic

Hallmarks of Aging

and in 2014 a paper came out by banister

that basically got the world focused on

this problem by the world I mean the

world of of anti-aging

so what what banister and colleagues did

was they took a registry from the UK and

they got a set of patients who were on

Metformin with type 2 diabetes but only

metformin so these were people who had

just progressed to diabetes they were

not put on any other drug just metformin

and then they found from the same

registry a group of matched controls so

this is a standard way that

epidemiologic studies are done because

again you don't have the luxury of doing

the randomization so you're trying to

account for all the biases that could

Exist by saying we're going to take

people who look just like that person

with diabetes so can we match them for

age sex socioeconomic status

blood pressure BMI everything we can and

then let's look at what happened to them

over time now again this is all

happening in the future so you're

looking into the past it's retrospect in

that sense

and so let me just kind of pull up the

the sort of table here so I can kind of

walk through and this is not in the

paper we talked about but I think this

is an important background so

they did something that at the time I

didn't really notice I didn't notice

what they did I probably did and I

forgot but I didn't notice this until

about five years ago when I went back

and looked at the paper

and they did something called

um uh informative censoring so the way

the study worked is if you were put on

Metformin we're gonna follow you if

you're not on Metformin we're going to

follow you and we're going to track the

number of deaths from any cause that

occurred this is called all-cause

mortality or ACM and it's really the

gold standard in a trial of this nature

or a study of this nature or even a

clinical trial you want to know how much

are people dying from anything because

we're trying to prevent or delay death

of all causes

informative censoring says

if a person

who's on Metformin

deviates from that inclusion criteria we

will not count them in the final

assessment so how are the ways that that

can happen well one the person can be

lost to follow up

two they can just stop taking their

metformin three and more commonly they

can progress to needing a more

significant drug

so all of those patients were excluded

from the study

so think about that for a moment this is

in my opinion a significant limitation

of this study because what you're

basically doing is saying we're only

going to consider the patients who were

on Metformin stayed on Metformin and

never progressed through it and we're

going to compare those to people who

were not having type 2 diabetes so an

analogy here would be imagine we're

going to do a study of two groups that

we think are almost identical one of

them are smokers and the other are

identical in every way but they're not

smokers and we're going to follow them

to see which ones get lung cancer

but every time somebody dies in The

Smoking group we stop counting them

when you get to the end you're going to

have a less significant view of the

health status of that group

so with that caveat the banister study

found a very interesting result which

was the crude death rate

um was and by the way the way these are

done this is also one of the challenges

of epidemiology is the math gets much

more complicated

you have to normalize death rate for the

amount of time you study the people so

everything is normalized to thousand

person years so the crude death rate in

the group of people with type 2 diabetes

who were on Metformin including the

censoring was 14.4 so

14.4 deaths occurred per thousand

patient years

if you look at the control group it was

15.2

this was a startling result and I

remember reading this in again 2014 and

being like holy crap this is really

amazing is there

um could you explain why because I I

hear those numbers and they don't seem

that striking it's a difference of about

a year and a half now of course

um a difference of about a year and a

half in lifespan is is well it is

remarkable it doesn't even translate to

that so so taking a step back type 2

diabetes on average will shorten your

life by six years I see so that's the

Actuarial difference between having type

2 diabetes and not all comers but you're

right this is not a huge difference it's

only a difference of a little less than

one year of Life per thousand patient

years studied okay and by the way up

here just point out my my math was wrong

when I said about a year and a half but

but the point here is you would expect

the people in the metformin group to

have a far worse outcome I.E to have a

far worse crude death rate

and the fact that it was statistically

significant in the other direction and

it turned out on the What's called the

Cox proportional Hazard which is where

you actually model the difference in

lifespan the people who took metformin

and had diabetes had a 15 one five

fifteen percent relative reduction in

all-cause death over 2.8 years which was

the median duration of follow-up well

that seems to be the number that makes

me go wow yeah right that

um because

could you repeat those numbers again yep

so 15 reduction in all-cause mortality

over 2.8 years

that's a big deal it is and again

there's no clear explanation for it

unless you believe that metformin is

doing something Beyond helping you lower

blood glucose

because the difference in blood glucose

between these two people was still in

favor of the non-diabetics

so again the proponents of Metformin

being a zero protective agent and I put

myself in this category at one point I

would put myself today in the category

of undecided but at the time I very much

believed this was a very good suggestion

that metformin was doing other things

you mentioned a couple already metformin

is a weak inhibitor of mtor Metformin

reduces inflammation metformin

potentially tamps down on senescent

cells and their secretory products you

know there are lots of things metformin

could be doing that are off Target

and it might be that those things are

conferring the advantage

as many of you know I've been taking ag1

daily since 2012. so I'm delighted that

they're sponsoring the podcast ag1 is a

vitamin mineral probiotic drink that's

designed to meet all of your

foundational nutrition needs now of

course I try to get enough servings of

vitamins and minerals through whole food

sources that include vegetables and

fruits every day but oftentimes I simply

can't get enough servings but with ag1

I'm sure to get enough vitamins and

minerals and the probiotics that I need

and it also contains adaptogens to help

buffer stress simply put I always feel

better when I take ag1 I have more focus

and energy and I sleep better and it

also happens to taste great for all

these reasons whenever I'm asked if you

could take Just One supplement what

would it be I answer ag1 if you'd like

to try ag1 go to drinkag1.com huberman

to claim a special offer they'll give

you five free travel packs plus a year

supply of vitamin D3 K2 again that's

drink ag1.com huberman

so fast forward until a year ago and I

think most people took the banister

study as kind of the best evidence we

have for the benefits of metformin and

I'm sure you've had lots of people come

up to you and ask you should I be on

Metformin should I be on Metformin I

mean I probably get asked that question

almost as much as I'm asked any question

outside of do I mean people definitely

want to know if you should be consuming

do but but after that it's metformin

fresh off the leaves has to be while

viewing morning sunlight so okay so

let's so let's kind of fast forward to

now the paper that I wanted to spend a

few more minutes on yeah and thanks for

that background I I'm still uh dazzled

by the uh insertion of the straw by way

of of uh insulin I I don't think I've

ever heard that described I need to I

need to go get a better textbook it's a

pretty Short Straw In fairness you know

it's just it's just a little yeah just

um to give people a sense of why I'm so

dazzled by I am always fascinated by how

quickly

how efficiently and um how specifically

biology can create these little protein

complexes that do something really

important I mean you're talking about an

on-demand creation of a portal right I

mean these are cells engineering their

own Machinery in real time in response

to chemical signals it's great yeah but

I'm I'm sort of Rusty on my Neuroscience

but an action potential Works in reverse

the same way like you need the ATP

gradient to restore the uh to restore

the gradient but once the action

potential fires it's passive outside

right yeah so what peer's referring to

is um the way that neurons become

electrically activist by the flow of

ions across the from the outside the

cell to inside the cell and we have both

active conductances mean they're

triggered by electrical changes in the

gradients Via changes in electrical

potential

um and then their passive gradients

where things can just flow back and

forth until there's a balance equal

inside and outside the cell I think

what's um what's different is that

there's some movement of a lot of stuff

inside of neurons when neurotransmitters

like dopamine bind to its receptor and

then a bunch of you know it's like a

Bucket Brigade that gets kicked off

internally but it's not often that you

hear about receptors getting inserted

into cells very quickly normally you

have to go through a process of of you

know transcribing genes and making sure

that the specific proteins are made and

then those are long slow things that

take place over the course of many hours

or days what you're talking about is a

real on-demand insertion of a channel

and it makes sense as to why that would

be required but it's just oh so very

cool it's cool yeah so keys and

colleagues came along and said we would

like to redo the entire banister

analysis

um and I I think their motivation for it

was the interest in this topic is

through the roof there is a clinical

trial called the tame trial that is I

think pretty much funded now and maybe

getting underway soon the tame trial

which is an important trial is going to

try to ask this question prospectively

and through random assignment so so this

is the targeting aging with metformin

trial that's correct okay near barzilla

uh is probably the senior Pi on that

um and I think in many ways the banister

study along with some other studies

um but of lesser significance probably

provided some of the motivation for the

tame trial so they said okay look we're

going to do this we're going to use a

different cohort of people so the first

study that we just talked about the

banister study used uh I believe it was

like roughly they sampled like 95 000

subjects from a UK biobank here they

used a larger sample they did about half

a million people sampled from a Danish

Health registry and they did something

pretty elegant they created two groups

to study so the first was just a

standard replication of what banister

did which was just a group of people

with and without diabetic that they

tried to match as perfectly as possible

but then they did a second analysis in

parallel with discordant twins so

same-sex twins that only differed in

that one had diabetes and one didn't

I thought this was very elegant because

here you have a degree of genetic

similarity and you have similar

environmental uh factors during

childhood that might give you you know

allow you to see if there's any sort of

difference in signal so now turning this

back into a little bit of a journal Club

virtually any clinical paper you're

going to read table one is the

characteristics of the people in the

study you always want to take a look at

that so when I look at table one here

you can see it's and by the way just for

people watching this we're going to make

all these papers and figures available

so if you're you know don't you know

we'll have nice show notes that'll make

all this clear so table one in the keys

paper shows the Baseline characteristics

and again it's almost always going to be

the first table in a paper usually the

first figure in the paper is a study

design it's usually a flow chart that

says these are the inclusion criteria

these are all the people that got

excluded this is how we randomized Etc

and you can see here that there are four

columns so the the first two are The

Singletons these are people who are not

related and then the second two are the

twins who are matched and you can see

remember how I said they sampled about

500 000 people you can see the numbers

so they got you know

7842 Singletons on Metformin the same

number then they pulled out matched

without diabetes on the twins they got

976 on Metformin with diabetes and then

by definition

976 co-twins without them

and you look at all these

characteristics what was their age upon

entry how many were men what was the

year of indexing when we got them what

medications were they on what was their

highest level of Education marital

status Etc the one thing I want to call

out here that really cannot be matched

in a study like this so this is a very

important limitation is the medication

so look at look at that column Andrew

notice how pretty much everything else

is perfectly matched until you get to

the medication list yeah it's all over

the place yeah it's just you it's not

even close they're not where they're

nowhere near matched right in other

words just to give you a couple of

examples right on the and let's just

talk about The Singletons because it's

basically the same story on the twins if

you look at what fraction of the people

with type 2 diabetes are on lipid

lowering medication it's 45.6 percent

versus 15.4 percent in the Matched

without diabetes it's a 3X difference

what about anti-platelet therapy that's

30 versus 14

antihypertensive 65 percent versus 63

versus 31 because people who have one

health issue and are taking metformin

are likely to have other health issues

exactly so this is again a fundamental

flaw of epidemiology you can never

remove all the confounders this is why I

became an experimental scientist so that

we could control variables that's right

because without random assignment you

cannot control every variable now you'll

see in a moment when we get into the

analysis they go through three levels of

corrections but they can never correct

this medication one so just keep that in

the back of your mind okay so the two

big things that were done in this

experiment or in this survey or you know

study to differentiate it from banister

was one the twin trick which I think is

pretty cool the second thing that they

did

was they did a sensitivity analysis with

and without informative censoring so one

of the things they wanted to know is hey

does it really matter if we don't count

the metformin patients who progress

so

um so let's see kind of what what

transcribed so the next figure figure

two pardon me the next table table two

walks you through the crude uh mortality

rate in each of the groups so the most

important row I think in this table is

the one that says crude mortality per

thousand person years

now you recall that in the previous

study in the banister study those were

on the ballpark of about 15 per okay so

let's look at each of these so in the

um single The Singletons with without so

the non-twins who were not diabetic it

was 16.86 and could you put a little

more Contour on what this thousand

person years what what it is are you

talking about pooling the lifespans of a

of of a bunch of different people until

you get to the number 1000 yeah because

you're normalizing not so it's not who's

going to live a thousand years because

everyone's expecting that

um you're essentially taking so you've

got some people that are going to live

um 76 years 52 years 91 years and you're

pooling all of those until you hit a

thousand and then that becomes kind of a

a a it's like a normalized division

you're basically like so let's say the

the control group

um you're asking if there were a

thousand person years available to live

How likely is it that this person would

live another 15. yeah so a couple ways

to think about it so taking a step back

we always have to have some way of

normalizing so when we talk about the

mortality from a disease is like cancer

in the population we would we report it

as what's the mortality rate per and

it's typically per 100 000 persons

okay that's a much more intuitive way to

express it it is but the reason we can

do it that way is because we're

literally looking at how many people

died this calendar year and we divide it

by the number of people in that age

group so it's typically what you're

doing when you look at aged groups in

buckets of like decades so that's why we

can say the highest mortality is like

people 90 and up even though the

absolute number of deaths is small it's

because there's not that many people

there right the majority of deaths in

absolute terms probably occur in the

seventh decade

but as you go up because the denominator

is shrinking you have to normalize to it

so we just normalized the number of

people here are all the people that

started the year hear all the people

that ended the year what's the death

rate why are these done in a slightly

more complicated way because we we don't

follow these people for their whole

lives we're only following them for a

period of observation in this case

roughly three years

so to say something like you know we

have a crude death rate of five deaths

per thousand person years one way to

think about that is if you had a

thousand people and you followed them

for one year you'd expect five to die

if you had 500 people and you followed

them for two years you expect five to

die

if you have a thousand people and you

follow them for one year you expect five

to die those would all be considered

equivalent mortalities

great thank you for clarifying that no

no this this stuff is I mean like I find

I find epidemiology when you get in the

weeds is way more complicated than

following the basics of

um experimental stuff where you just you

get to push all this stuff into the

garbage bin and just say we're gonna

take this number of people we're gonna

exclude this group we're going to

randomize we're going to see what

happens yeah that's what like the paper

we'll talk about next

so

when you adjust for age and they don't

show it in this table it's only in the

text when you adjust for age a very

important check to do is what is the

crude death rate of the people on

Metformin who are not twins versus who

are twins now in this table

they look different because it's 24.93

for the metformin group and 21.68 for

the twin group in that's on Metformin

when you adjust for age they're almost

identical it's it goes from 29 point

24.93 to 24.7

one other point I'll make here for

people who are going to be looking at

this table is you'll notice there are

parentheses after every one of these

numbers what is that what does that

offer in there those parentheses are

offering the 95 confidence interval so

for example to take the number you know

24.93 is the crude death rate of how

many people are dying who take Metformin

what it's telling you is we're 95

confident that the actual number is

between 23.23 and 26.64

if a 95 confidence interval does not

cross the number zero it's statistically

significant

okay so the first thing that just jumps

out at you I think when you look at this

is there's clearly a difference here

between the people who have diabetes and

those who don't

it complicates the study a little bit

because it's basically two studies in

one but you're comparing

um 95 pardon me uh 24.93 to 16.86 which

by the way remains after age adjustment

when you go to the twin group it's 24.73

to 12.94 so maybe just to zoom out for

that what you're describing if I

understand correctly is this um uh crude

deaths per 1000 person years let's just

talk about The Singletons the non yes is

16.86 so 16.86 people die and some

people probably think how can 0.86 of a

person die well it's not always whole

numbers but

um

there's a there's a bad joke to be made

here but yeah just call it 17 versus 25

right 17 deaths per thousand versus 25

deaths yep and the 25 is in the folks

that took metformin now that to the

naive listener and to me means oh you

know metformin basically kills you right

um not a faster or you know you're more

likely to die but we have to remember

that these people have

another they have a major health issue

that the other group does not have

that's right because people weren't

assigned drug or not assigned drug it

wasn't Placebo drug it's let's look at

people taking this drug for a bad health

issue and compare to everyone else

that's right

so now you have to go into and and I'll

just sort of skip the next figure but

the next figure is a Kaplan Meyer curve

I I think it's actually worth looking at

it because they show up in all sorts of

studies so if you look at figure one

it's a Kaplan Meyer curve

which is a mortality curve so you'll see

these in any study that is looking at

death and this can be prospective

randomized this can be retrospective but

these are always going to show up and I

think it's really worth understanding

what a kaplan-meyer curve shows you so

when the x-axis is always time and on

the y-axis is always the cumulative

survival so it's a curve that always

goes from zero to one one or one hundred

percent and it's always decreasing

monotonically meaning it can only go

down or stay flat it can never go back

up so that's what a cumulative mortality

curve looks like now we're looking at

you're starting at alive and you're

looking at how many people die for every

year that passes that's right

and in each curve there's one on the

left which is the Matched Singletons and

there's a one on the right which are the

discordant twins you have two lines you

have those that were on Metformin with

type 2 diabetes and you have their

matched controls

and in this figure the Matched controls

are the darker lines and the people with

type 2 diabetes on Metformin that's the

lighter line

you'll also notice and I like the way

they've done it here they've got shading

around each one and we should mention

for those that are just listening that

in both of these graphs the downward

trending line from the controls so again

non-diabetic not taking metformin is

above the line corresponding to the

diabetics who are taking metformin

um put

crudely

um

the people who are taking metformin that

have diabetes are dying at a faster rate

for every single year exam and the two

lines do not overlap except at the

beginning when everyone's alive it's

like a foot race where basically the

people with metformin and diabetes are

falling behind and dying as they fall

that's right and I'm glad you brought up

a good point

it's not uncommon in treatments uh to

see kaplan-meyer curbs cross they don't

have to it's not a requirement that they

never cross it's only a a requirement

that they're monotonically decreasing or

staying flat so I've seen cancer

treatment drugs where they have like two

drugs going head-to-head in a cancer

treatment and like one starts out

looking really really bad but then all

of a sudden it kind of flattens well the

other one goes bad and then it actually

crosses and goes underneath but that's

not the case here so to your point the

people with diabetes taking metformin in

both the match Singletons and the

discordants are dropping much faster and

they always stay below and I was just

going to say that the shading is just

showing you a 95 confidence interval so

you're just putting basically error bars

along this so if this were experimental

data if you were doing an experiment

with

a group of mice and you were watching

their survival and you were you know

what you'd have error bars on this which

you're actually measuring so this is

because you have much more data here

you're just showing this in this fashion

for those that haven't um been

familiarized statistics no problem um

error bars correspond to like if you're

just going to measure the heights of a

room full of 10th graders there's going

to be a range right you'll have the very

tall kid and the and the Very uh shorter

kid and you know the short kid and the

medium kit and you'll and so there's a

range there's gonna be an average a mean

and then there'll be standard deviations

and standard errors and um uh so these

confidence intervals just give a sense

of how much range you know some people

um die die early some people dilate

within a given year they're going to be

different ages

um so it these error bars can account

for a lot of different forms of

variability here you're talking about

the variability is how many people in

each group die we're not tracking one

diabetic taking metformin versus a

control I I should have asked this

earlier earlier but well and it's also a

mathematical model at this point too

that's smoothing it out because notice

it's running for the full eight years

even though they're only following

people for you know typically I think

the median was like three or four years

at a time so they're using this quite

complicated type of mathematics called A

Cox proportional Hazard which is what

generates Hazard ratios and basically

any model has to have some error in it

and so they're basically saying this is

the error so you could argue when you

look at that figure we don't know

exactly where the line is in there but

we know it's in that shaded area

if those shaded areas overlapped you

couldn't really make the conclusion you

wouldn't know for sure that one is

different from the other yeah that's

actually a good opportunity to um to uh

raise a common myth which is a lot of

people when they look at a paper let's

say it's a bar graph you know

um and they see these error bars and

they will say people often think oh if

the error bars overlap it's not a

significant difference but if the error

bars don't overlap meaning there's

enough separation then that's a real and

meaningful difference and that's not

always the case it depends a lot on the

form of the experiment

um I often see some of the the more

robust Twitter battles over you know how

people are reading graphs and I think

it's important to remember that

um you run the statistics hopefully the

correct statistics for the for the

sample but determining significance

whether or not the the result could be

due to something other than chance of

course

your confidence in that increases as it

becomes typically p-values P less than

point zero zero zero zero one percent

chance that it's due

um chance right so very low probability

P less than 0.05 tends to be the kind of

gold standard cut off

um but when you're talking about data

like these which are repeated measures

over time people are dropping out

literally

um over time you're saying they've

modeled it to make predictions as to

what would happen we're not necessarily

looking at you know raw data points here

yeah the raw data was in the previous

table that's now taken and run through

this Cox model and it's smoothed out got

it and to your point about the bar

graphs yeah I think the other thing you

always want to understand is just

because something doesn't achieve

statistical significance

the only way you can say it's not

significant is you have to know what it

was powered to detect

um and statistical power is a very

important concept that probably doesn't

get discussed enough but before you do

an experiment you have to have an

expectation of what you believe the

difference is between the groups and you

have to determine the number of samples

you will need to assess whether or not

that difference is there or not so you

use something it's called a power table

and you you would go to the power table

so if you if you're doing treatment a

versus treatment B and you say look I

think treatment a is going to have a 50

response and I think treatment B will

have a 65 percent response you literally

go to a power table that says 50

response 15 difference that gives you a

place on the grid and I want to be 90

sure that I'm right so 90 power I'm

being a little bit so there's going to

be a statistician listening to this

who's going to want to kill me but this

is directionally the way we would

describe it and that tells you this is

how many animals or people you would

need in this study you're going to need

147 in each group and by the way if you

now do the experiment with 147 and you

fail to find significance you can

comfortably say there is no statistical

difference at least up to that 15

percent there may be a difference at 10

but you weren't powered to look at 10

percent yeah and um very important point

that you're making another Point that's

just uh more General one about

statistics in general the way to reduce

variability in a data set is to increase

sample size and that kind of makes sense

right if you if I just walk into a 10th

grade class and okay I'm going to

measure height and I'd buy the first

three kids that I see and I happen to

look over there and it's the three that

all play on the volleyball team together

I my sample size is small and I'm likely

to get a skewed representation in this

case taller than average so increasing

sample size tends to decrease variation

so the that's why when you hear about a

study from the UK biobank or from you

know half a million Danish citizens like

for instance in this study that's those

are enormous sample sizes so even though

this is uh not an experimental study

it's an epidemiological observational

study

um there's tremendous Power by way of

the enormous number of subjects and

that's the way that epidemiology will

make up for its deficit so you could

never do a randomized assignment study

on half a million people

um you know so so

epidemiology makes up for its biggest

limitation which is it can never

compensate for inherent biases by saying

we can do infinite duration if we want

like we could we could survey people

over the course of their lives and we

can have the biggest sample size

possible because this is relatively

cheap the cost of actually doing an

experiment where you have tens of

thousands of people is prohibitive I

mean if you look at the women's health

initiative which was a five-year study

on I don't know what was it 50 000 women

I mean was a billion dollar study so

this is this is The Balancing Act

between epidemiology and randomized

prospective experiments and uh they so

they both offer something but you just

have to know their blind spots of each

one

I'd like to take a quick break and

acknowledge our sponsor inside tracker

inside tracker is a personalized

nutrition platform that analyzes data

from your blood and DNA to help you

better understand your body and help you

meet your health goals I'm a big

believer in getting regular blood work

done for the simple reason that many of

the factors that impact your immediate

and long-term Health can only be

analyzed from a quality blood test

however with a lot of blood tests out

there you get information back about

blood lipids about hormones and so on

but you don't know what to do with that

information with inside tracker they

have a personalized platform that makes

it very easy to understand your data

that is to understand what those lipids

what those hormone levels etc mean and

behavioral supplement nutrition and

other protocols to adjust those numbers

to bring them into the ranges that are

ideal for your immediate and long-term

Health Insight tracker's ultimate plan

now includes measures of both APO B and

of insulin which are key indicators of

cardiovascular health and energy

regulation if you'd like to try inside

tracker you can visit insidetracker.com

huberman to get 20 off any of inside

trackers plans again that's inside

tracker.com huberman to get 20 off

so let's just kind of wrap this up I

mean I think let's just go to table four

which I think is the most important

table

um in in here which now lays out the the

final results in terms of the hazard

ratio so this is this is the way we want

to really be thinking about this so

again Hazard ratios

um these are important things to

understand a hazard ratio is a number

and you always subtract one from the

hazard ratio and that tells you if it's

a positive number if it's a number sorry

if it's a number greater than one you

subtract one and that tells you the

relative harm so if it has a ratio is

1.5 you subtract 1.5 is a 50 increase in

Risk

um if the number is negative you may

recall on the banister paper the hazard

ratio was 0.85 so if it's nothing so

that means it's a 15 reduction in

relative risk and here you can see all

the hazard ratios are positive so what

it's telling you here is and I'm going

to walk through this because it's

there's a lot of information packed here

you've got Singletons you've got twins

they're showing you three different ways

that they do it they do an unadjusted

model if you just look at The Singletons

with and without metformin and you make

no adjustments the hazard ratio is 1.48

meaning the people on Metformin had a 48

greater chance of dying in any given

year than their non-diabetic counterpart

the only reason I'm smiling it's not

because I enjoy people dying quite quite

to the contrary is that

um this is novel for me that I've read

some epidemiological studies before but

it's not normally where I spend the

majority of my time but up until now I

was thinking okay people taking

metformin are dying more more than those

that aren't I just and I I'm just

relieved to know that I wasn't um

looking at all this backwards okay so

they're dying more but of course we

don't have a group that's taking

metformin who doesn't have diabetes and

we don't have a group

um who uh

has diabetes and you know is taking

metformin plus something else so again

we're only dealing with these

constrained yeah now there's a lot of

other arm to this study that I'm not

getting into because it adds more

complexity which is they also have

another group that's got diabetes takes

metformin and takes sulfona ureas which

is a bigger drug and those people die

even more whoa so which again speaks to

the point right the more you need these

medications they're never able to erase

the effect of diabetes but in this case

it seems that they might be accelerating

possibly accelerating death due to

diabetes possible we could never know

that from this because we're we don't

see we would need to see diabetics who

don't take Metformin who take nothing

and I would bet that they would do even

worse

so my intuition is that the metformin is

helping but not helping nearly as much

as we thought before so my point is they

make another set of adjustments they say

okay well look in the first one in the

unadjusted model we only matched for age

and gender

okay that's pretty crude what if we

adjust for the medications they're on

the cardiovascular psychiatric pulmonary

dementia meds and marital status I don't

know why they threw marital status in

there but they did I don't know maybe

being married or unmarried I'm sure but

it just seems like a random thing to

throw in with all their meds I would

have personally done that adjustment

higher up but nevertheless if you do

that all of a sudden the uh Hazard ratio

drops from 1.48 to 1.32 which means yep

you still have a 32 percent greater

chance of dying in any given year

all right what if we also adjust for the

highest level of Education along with

any of the other covariates well that

doesn't really change it at all it ends

up at 1.33 or a 33 chance increase in

depth okay I always knew that more

school wasn't going to save me was it's

not doing jack so now let's do it for

the twins if you do the twin study which

you could argue is a slightly pure study

because you at least have one genetic

and environmental thing that you've

attached the unadjusted model is brutal

2.15 that's a hundred and fifteen

percent think about this these are twins

who in theory are the same in every way

except one has diabetes and one doesn't

and the one with diabetes on Metformin

still has 115 percent greater chance of

dying than the non-diabetic co-twin when

you make that first adjustment of all

the meds and marital status you bring it

down to a 70 increase in risk and when

you throw education in it goes up to an

80 chance of risk

now they did this really cool thing

which was they did the analysis on with

and without censoring so everything I

just said here was based on no censoring

tell me about censoring censoring is

when you stop counting the metformin

people who have died

Okay so

in the Singleton group

when you unadjust it and the reason I'm

doing the unadjusted is that's where

they did the sensitivity analysis I

don't think it really matters that much

it's you just have to draw a line in the

sand somewhere you'll recall that that

was a 48 chance of increased mortality

all-cause mortality if you stop counting

if you if you apparently if you don't

censor meaning if you include everybody

including when people on Metformin with

diabetes die if you censor them it comes

down to 1.39

in other words this is a very important

finding it did not undo the benefits

that we saw in the banister study

banister saw a 15 reduction in mortality

when they censored

when Keys censored

it got better but not that much better

it went from 48 to 39 in the twins it

went from a hundred and fifteen percent

down to only 97 percent

so in some ways this presents a little

bit of an enigma

because it's not entirely clear to me

having read these papers many times

exactly why banister found such an

outlined like such a different response

there's another there's another

technical detail of this paper which is

they you can see on the right side of

table four they did something called a

nested case control

but you'll see and I was going to go

into a long explanation of what nested

case controls are it's another pretty

elegant way to do case control studies

where you sample by year and you you you

sort of normalize you you don't count

all the cases at the end you count them

one by one I don't think it's worth

getting into Andrew because it doesn't

change the answer you can see it changes

it just slightly but it doesn't change

the point the point here is the keys

paper makes it undeniably clear that in

that population there was no Advantage

offered by metformin that undid the

disadvantage of having type 2 diabetes

this does not mean that metformin wasn't

helping them because we don't know what

these people would have been like

without metformin it could be that this

bought them a 50 reduction in relative

mortality to where they'd been but what

it says is

in my way this is what you would have

expected this is what you would have

expected 10 years ago before the

banister paper came out or maybe even

before metformin was used because in

some ways it's saying

um what is the likelihood that sick

people who are on a lot of medication

are going to die compared to not sick

people who aren't on a lot of medication

yep wanna you know it's not quite that

simple in the in the sense that as you

said there are ways to

um try and isolate the metformin

contribution somewhat

um because they're on a bunch of other

meds

um and presumably that was done and

analyzed in in other figures that where

they they can sort of try and they can

never attach the results specifically to

metformin right but um there must be

some way of waiting the percentage that

are on psychiatric meds or not on

psychiatric medicine some way to tease

out whether or not there's actually some

contribution to metformin to this result

well that's what they're doing in in be

in the in the partial adjustment is

they're actually com they're actually

doing their best to say oh right married

or not married they're going variable

drug by drug all the way through high

blood pressure non-high blood pressure

smoking non-smoking Etc right and the

way they would do that presumably is

um by saying okay married not married

that's why that's a simple one

um are you on lipid lowering meds yes or

no okay you are not you are not they and

then comparing those groups yeah yeah

okay so no no differences jumping out

that can be purely explained by these

other variables yes although again this

is a this is a great opportunity to talk

about why no matter how slick you are no

matter how slick your model is you can't

control for everything there's a reason

that to my knowledge virtually every

study that compares meat eaters to

non-meat eaters finds an advantage

amongst the non-meat eaters

and we can talk about lifespan Advantage

yes and we can or disease you know

incidence uh studies and yeah it might

be tempting to say well therefore eating

meat is bad

um Until you realize that it takes a lot

of work to not eat meat that's a very

very significant decision that a person

for most people that's a very

significant decision a person makes and

for a person to make that decision they

probably have a very high conviction

about the benefit of that to their

health

and it is probably the case that they're

making other changes with respect to

their health as well that are a little

more difficult to measure now there's a

million other problems with that I

picked a silly example because the whole

meat discussion then gets into well you

know when when we say eating meat what

do we mean like this document is like

deli meat versus grass-fed exactly you

know a deer that you hunted with your

bow how do we get into all those things

but my point is it's very difficult to

quantify some of the intangible

differences and I think that even a

study that goes to Great Lengths as this

one does epidemiologically to make these

Corrections can never make the

corrections and so for me the big

takeaway of this study is one

this makes much more sense to me than

the banister paper which never really

made sense to me and again I was first

critical of the banister paper in 2018

about four years after it came out

that's about the time I stopped taking

metformin by the way I stopped taking it

for a different reason which we can talk

about in a sec but

um that was the first time I went back

and said wait a minute this information

this this informative censoring thing is

that's a little fishy and I think we

weren't looking at a true group of real

type 2 diabetics now that said maybe it

doesn't matter in other words maybe and

even the keys paper doesn't tell us that

metformin wouldn't be beneficial because

it could be that those people if they

were on nothing as their matched cohorts

were on nothing would have been dying at

you know a hazard ratio of three and

this brought it down to 1.5 in which

case you would say there is some zero

protection there it is putting the

brakes on this process

all of this is to say absent a

randomized control trial we will never

know the answer

has there been a randomized control

trial

not when it comes to a hard outcome now

there has been in the ITP so the

interventions testing program uh which

is kind of the gold standard for animal

uh studies which is run out of three

Labs so it's it's an nih-funded program

that's run out of three labs they

um they basically test molecules for

zero protection

um the ITP was the first study that

really put rapid mice on the map in 2009

that was the study that's fortuitously

demonstrated that even when ravamycin

was given very very late in life it was

given to 60 month old mice it still

afforded them a 15 uh lifespan extension

has a similar style you've been done in

humans I mean it's hard I mean it's a

hard no I mean you can't really control

with rapper mice no

um but when the ITP studied metformin it

did not succeed

so the the there have not been that many

drugs that have worked in the ITP the

IDP is very rigorous right it's a it

doesn't use an inbred strain of mice it

is done concurrently in three Labs with

very large sample sizing and so when

something works in the ITP it's pretty

exciting rapamycin has been studied

several times it's always worked another

one we should talk about at a subsequent

time is 17 Alpha estradiol this

continues to work in male mice and it

produces comparable effects to rapamycin

estrogen doesn't work in female rights

but this is Alpha not beta

so this is 17 Alpha estradiol not beta

estradiol which is the estradiol that we

all that is bioavailable in all of us

and and uh just as a brief aside

um I think you and I

basically agree that

um unless it's a problem

males we're talking post-puberty

um should try and have their estrogen as

high as possible without having negative

symptomology because of the importance

of estrogen for libido for brain

function tissue bone health bone health

body because this idea of crushing

estrogen and raising testosterone is

just silly right there's not and let's

just leave raising testosterone out of

it but

many of the approaches to raising

testosterone that are pharmacologic in

nature also raise estrogen a lot of

people try and push down on estrogen and

that is just again unless people are

getting um hyperestrogenic effects like

gynecomastia or other issues is the

exact wrong direction to go you want

estrogen estrogen is a very important

hormone for men and women

um canaga flows in an sglt2 inhibitor

also very successful in the ITP but

again interestingly rapid metformin not

so metformin has failed in the ITP so

you no longer taking metformin I stopped

five years ago I mean you're not a

diabetic so presumably you're taking I

was taking it for a durable protection

to buffer blood glucose yeah and

ultimately potentially live longer yes

exactly and the reason I stopped and

this will be the last thing before we

move on well because you couldn't go to

the Dairy Queen at the Buffett event no

finally the nausea went away after a few

weeks or a month maybe

um but once I got really into lactate

testing I noticed how high my lactate

was

uh at rest so a resting fasted lactate

should be in a healthy person should be

below one like somewhere between 0.3.6

millimole and only when you start to

exercise should lactate go up and in

2018 was when I started blood testing

for my zone two so previously when I was

doing zone two testing I was just going

off my power meter and heart rate but

this is when this is after I met Inigo

San Milan and I started

like wanting to use the lactate

threshold of two millimole as my as my

determinant of where to put my wattage

on the bike

and I'm like

doing finger Pricks before I start and

I'm like 1.6 millimole and I'm like what

the hell is going on I can't be 1.6 but

ran the a flight of stairs up the back

of the Empire State Building well no

that would put me a lot higher right but

but and and being generous to your

Fitness no but but but that's when I

started digging a little digging and

realized oh you know what this totally

makes sense if you have a weak

mitochondrial toxin what are you going

to do you're gonna shunt more glucose

into pyruvate and more pyruvate into

lactate I'm I'm anaerobic yeah fuel

source that's right

so and then my zone two numbers just

seemed off my lactation could you feel

it sorry I didn't know can you feel it

in your body because maybe now I'll just

briefly describe I took berberine

um

I um During the period of maybe

somewhere in the 2012 to 2015 stretch I

don't recall what are you taking it for

well I'll tell you so I I was and I

still am a big fan of Tim ferriss's uh

slow carbohydrate diet because I like to

eat meat and vegetables and starches I'm

an omnivore

um and I found that it worked very

quickly got me very lean I could

exercise I could think I could sleep all

you know a lot of my rationale for

following one eating regimen or another

what I eat is to enjoy myself but also

have mental energy I mean because if I

can't sleep at night I'm not going to

replenish I'm not I don't replenish I'm

gonna feel like garbage I don't care how

lean I am or what you know

um so I found the Slow Carb Diet to be

um which was in the four hour body to be

a very good plan for me it's pretty easy

you drop some things like bread Etc you

don't drink calories except after a

resistance training session Etc but one

day a week you have this so-called cheat

day and on the cheat day anything goes

and so I would eat you know eight

croissants and then I'd alternate to

sweet stuff and then I go to a piece and

by the end of the day you don't want to

look at an item of food at all so the

only modification I made to this slow

carb diet for our body thing was the day

after the cheat day I wouldn't eat I

would just fast and I had no problem

doing that because it was just basically

well since you said um uh what was it

anal um analc was I did not have that

but since you said that I um I won't up

the ante here but I'll at least match

your anal seepage comment by saying I

had let's just call it profound gastric

distress after eating like that the next

day so the last thing you want to do is

eat any food I'll just hydrate and

oftentimes to try and get some exercise

um and what I read was that berberine

Poor Man's metformin could buffer blood

glucose and in some ways make me feel

less sick when ingesting all these

calories in in many cases um spiking my

my blood sugar and Insulin

um because you're having ice cream and

you know Etc and indeed it worked so if

I took berberine and I don't recall the

milligram count and then I ate you know

12 donuts I felt fine it was as if I had

eaten one donut wow I felt sort of okay

in my body and I felt much much better

now

um presumably because it's buffering the

spikes in blood sugar I wasn't crashing

in the afternoon nap and that whole

thing

and do you remember how much you were

taking I think it was a couple hundred

milligrams does that sound about right

um there's a bright yellow capsule

um I forget the source but in any case

one thing I noticed was that if I took

berberine and I did not ingest a

profound number of carbohydrates very

soon afterwards I got brutal headaches I

think I was hypoglycemic I didn't

measure it but I just felt I had

headaches I didn't feel good and then I

would eat a pizza or two and feel fine

and so I realized that berberine was

putting me on this kind of lower blood

sugar state that was the logic anyway

and it allowed me to eat these cheat

Foods

um but when I cycled off of the the four

out because I I don't follow the slow

carbide anymore although I might again

at some point

um when I stopped doing those cheat days

uh I didn't have any reason to take the

berberine and I feared that I wasn't

ingesting enough carbohydrates in order

to really justify trying to buffer my

blood glucose also my blood glucose

tends to be did you ever did you ever

try a carbos no what is that so A carbos

is another glucose disposal yeah it's

actually a drug that but it works more

in the gut and it just prevents glucose

absorption uh a carbos is another one of

those drugs that actually found a

survival benefit in the ITP and it was a

very interesting finding because the

the thesis for testing it the ITP is a

very clever system anybody can nominate

a candidate to be tested then the you

know the panel over there reviews it and

they decide Yep this is interesting

we'll go ahead and study it so when I

think David Allison

nominated uh a car bus to be studied the

rationale was it would be a caloric

restriction mimetic because you would

literally just fail to absorb I don't

know make up some number right 15 to 20

percent of your carbohydrates would not

be absorbed and therefore you would the

mice would effectively be calorically

restricted it would pass them out that's

right and

what happened was really interesting one

the mice lived longer on a carbos but

two they didn't weigh any less

so it what it they lived longer but not

through calorie restriction that's

interesting yes and it the the

speculation is they lived longer because

they had lower glucose in lower insulin

and I don't want to send this down some

rabbit holes here but there are all

sorts of interesting ideas about

um for instance that some forms of

dementia might be so-called type 3

diabetes the diabetes of the brain and

so things like berberine metformin

lowering blood glucose ketogenic diets

Etc might be beneficial there I mean

there's a lot to explore here and I know

you've explored a lot of that on your

podcast I've done far less of that but

well at least it seems that we know the

following things for sure one you don't

want insulin too high nor too low you

don't want blood glucose too high nor

too low if the buffering systems for

that are disrupted clearly exercise

meaning regular exercise is the best way

to keep that system in check but in the

absence of that tool or I would say in

addition to that tool is there any

glucose disposal agent because that's

what we're talking about here metformin

berberine a carbocy etc that you take on

a regular basis because you have that

much confidence in it the only one that

I take is an sglt2 inhibitor

um so this is a class of drug that is

used by people with type 2 diabetes but

which I don't have but because of my

faith in the mechanistic studies of this

drug coupled with its results in the ITP

coupled with the human trial results

that show profound benefit in

non-diabetics taking it even for heart

failure I think there's something very

special about that drug I've actually

that was another paper I was thinking

about presenting this time maybe we'll

do that the next time but do you believe

in caloric

restriction as a way to extend life or

are you more of the

do the right behaviors and that's

covered in your book outlive and

Elsewhere on your podcast

um and buffer blood glucose is do you

still obviously you believe in buffering

blood glucose in addition to just doing

all the right behaviors yeah I think you

can uncouple a little bit the buffering

of blood glucose from the caloric

deficit so

um I think you can be in a reasonable

energy balance and buffer glucose with

good sleep hygiene lots of exercise and

just thoughtful eating without having to

go into a calorie deficit so you know

it's not entirely clear if profound

caloric restriction would offer a

survival advantage to humans even if it

were tolerable to most which it's not

right so for most people it's just kind

of off the table right like if I said

Andrew you need to eat 30 fewer calories

for the rest of your life I'll live 30

fewer Years thank you yeah like there's

just not many people who are willing to

sign up for that so it's kind of a moot

point

um but the question is you know do you

need to be fasting all the time do you

need to be doing all of these other

things and the answer appears to be

outside of using them as tools to manage

energy balance it's not clear right an

energy balance probably plays a greater

role in glucose homeostasis then from a

nutrition standpoint then the individual

constituents of the meal

um now that's not entirely true like I

can imagine a scenario where a person

could be in a negative energy balance

eating Twix bars all day and drinking

you know big gulps but I also don't

think that's a very sustainable thing to

do because if by definition I'm going to

put you in negative energy balance

consuming that much crap I'm gonna

destroy you like you're gonna feel so

miserable you're going to be starving

right you're not going to be satiated

eating pure garbage and being in caloric

deficit you're going to end up having to

go into caloric excess so that's why

it's an interesting thought experiment I

don't think it's a very practical

experiment for a person to be generally

satiated and an energy balanced they're

probably eating about the right stuff

but I don't think that the specific

macros matter as much as I used to think

I'm a Believer in getting most of my

nutrients from

unprocessed or minimally processed

sources simply because it allows me to

eat Foods I like yeah and more of them

and I just love to eat I I so physically

enjoy the sensation of chewing that you

know I'll just eat cucumber slices for

prefer fun yeah right you know that's I

mean that's not my only form of fun

fortunately

um this is an amazing paper

um for the simple reason that it

provides a wonderful tutorial of the

benefits and drawbacks of this type of

work and I think it's also wonderful

because we hear a lot about metformin

rapamycin and um these anti-aging

approaches but

I was not aware that there was any study

of such a large population of people so

it's pretty interesting yeah so I think

it remains to be seen if and my patients

often ask me hey should I be on

Metformin and I give them a much much

much much shorter version of what we

just talked about and I say look if the

tame study which should answer this

question more definitively right this is

taking a group of non-diabetics and

randomizing them to Placebo versus

metformin and studying for specific

disease outcomes if the tame study ends

up demonstrating that there is a zero

protective benefit of Metformin I'll

reconsider everything right so I think

that's you know we just have to I think

all walk around with an appropriate

degree of humility around what we know

and what we don't know but but I would

say right now the epidemiology the

animal data my own personal experience

with its impact on my lactate production

and exercise performance we could

there's a whole other rabbit hole we

could go down another time which is the

impact on hypertrophy and strength which

appears to be attenuated as well by

metformin

um you know I'll I'll

I still prescribe it to patients all the

time if they're insulin resistant for

sure it's still a valuable drug but I

don't think of it as a great tool for

the person who's insulin sensitive and

exercising a lot

can't help but ask this question

do you think there's any longevity

benefit to short periods of caloric

restriction

um you know so for instance I decide to

by the way I haven't done this but let's

say I were to decide to you know fast

and do a one meal a day type thing where

I'm going to be in a slight caloric

deficit you know 500 to 1000 calories

for a couple of days and then go back to

eating

um the way that I eat before that short

caloric restriction slash fast is there

any benefit to it in terms of cellular

Health can you you know so reset the

system is there any idea that the the

changes the clearing of senescent cells

that we hear about autophagy that we you

know that in the short term you can

glean a lot of benefits and then go back

to to your regular pattern of eating and

then periodically you know once every

couple of weeks or once a month just you

know fast for a day or two is there any

benefit to that that's that's purely in

the domain of longevity not because

there's all discipline function there

there's a flexibility function there's

probably an insulin sensitivity function

but is there any evidence that it can

help us live longer I think the short

answer is no

um

for two reasons one I don't think that

that duration would be sufficient if if

one is going to take that approach but

two

um even if you went with something

longer like what I used to do right I

used to do seven days of water only per

quarter three days per month so I was

but I was basically always like it would

be three day fast three day fast seven

day fast just imagine doing that all

year rotating rotating routing for many

years I did that

um now I certainly believed and to this

day I would say I have no idea if that

provided a benefit but my thesis was the

downside of this is relatively

circumscribed which is

profound misery for a few days and what

I didn't appreciate the time which I

obviously now look back at and realize

is muscle mass lost you're just it's

very difficult to gain back the muscle

cumulatively after all of that loss but

my thought was exactly as you said like

there's got to be a resetting of the

system here this must be sufficiently

long enough to trigger all of those

systems but

you're getting at a bigger problem with

geoscience which I'm really hoping the

epigenetic field comes to the rescue on

it has not come close to it to date

which is we don't have biomarkers around

true metrics of Aging

everything we have to date stinks so

we're really good at using molecules or

interventions for which we have

biomarkers right like when you lift

weights

you can look at how much weight you're

lifting you can look at your dexa scan

and see how much muscle mass you're

generating like those are biomarkers

those are giving you outputs that say my

input is good or my input needs to be

modified when you take a sleep

supplement you can look at your eight

sleep and go oh my sleep is getting

better like there's a biomarker

um

when you take Metformin when you take

rapamycin when you fast we don't have a

biomarker that gives us any insight into

whether or not we're moving in the right

direction and if we are are we taking

enough

just don't know

so I I often get asked like what's the

single most important topic you would

want to see more research dollars put to

in terms of this space and it's

unquestionably this as unsexy as it is

like who cares about biomarkers but like

without them I don't think we're going

to get great answers because you can't

do

most of the experiments you and I would

dream up

got it well

I'm grateful that you're sitting across

the table for me telling me all this and

that um everyone can hear this but again

we will put a link to the papers plural

that Peter just described and for those

of you that are listening and not

watching

um hopefully you were able to track the

the general themes and takeaways and it

is fun to go to these papers you see

these big stacks of numbers and and it

can be a little bit overwhelming but

um my uh additional suggestion on

parsing papers is

notice that Peter said that he spent you

know he's read it several times

unlike a newspaper article or or a

Instagram post with a paper you're not

necessarily going to get it the first

time you certainly won't get everything

so that I I think spending some time

with papers for me means reading it and

then reading it again a little bit later

or tell me yeah I was just about to say

what's your because because I kind of

have a way that I do it but I'm curious

as to how you do it like if you're if

you're encountering a paper for the

first time what do you have an order in

which you like to go through the do you

want do you read it sequentially or do

you look at the figures first I mean how

do you how do you go through it yeah

unless it's an area that I know very

very well where I can

you know Skip to some things um before

reading it the whole way through

um my process is always the same and

actually this is fun because I used to

teach a class when I was a professor at

UC San Diego

um called neural circuits and health and

disease and it was an evening course

that grew very quickly from 50 students

to 400 plus students and we would do

exactly this we would parse papers and

um and I had everyone ask

what I called the four questions

um and it wasn't exactly four questions

but I have a little three by five card

next to me or a piece of main map by 11

paper typically and when I sit down with

a paper I want to figure out what is the

question they're asking what's the

general question what's the specific

question and I write down the question

then what was the approach you know how

did they test that question and

sometimes that can get a bit detailed

you can get into immunos chemistry and

they did a you know PCR for this it it's

not so important for most people that

they understand every method but it is

worthwhile that if you encounter a

method like PCR or

um you know chromatography or fmri that

you at least look up on the Internet

what its purpose is okay that will help

a lot and then it was what they found

and there you can usually figure out

what they believe they found Anyway by

reading the figure headers right what

are you know figure one here's the

header that typically if it's an

experimental paper it will tell you what

they want you to to think they found and

then I tend to want to know the

conclusion of the study and then this is

really the key one and this is the one

that would really distinguish the high

performing students from the others

you have to go back at the end and ask

whether or not the conclusions the major

conclusions drawn in the paper are

really substantiated by what they found

and what they did and that involves some

thinking it involves really you know

spending some time thinking about what

what they identified now this isn't

something that anyone can do straight

off the bat it's a skill that you

develop over time and different papers

require different formats but those four

questions really form the Cornerstone of

teaching undergraduates and I think

graduate students as well of how to read

a paper and um again it's something that

can be cultivated

um and it's still how I approach papers

so what I do typically is I'll read

title abstract

ice usually then we'll skip to the

figures and see how much of it I can

digest without reading the text and then

go back and read the text but In

fairness journals great journals like

science like nature oftentimes will pack

so much information in the cell press

journals too into each figure and it's

coded with no definition of the acronyms

that almost always I'm into the

introduction and results within a couple

of minutes wondering what the hell This

Acronym is or that acronym is and it's

um it's just yeah it's just wild how

much

um how much nomenclature there really is

I can't remember was it you or was it

our friend Paul Conte when he was here

um who said that oh no I'm sorry it was

neither it was chair of Ophthalmology at

Stanford uh Dr Jeffrey Goldberg who is a

guest on the podcast recently who off

camera I think it was told us that if

you look at the total number of words

and terms that a physician leaving

Medical School owns in their mind and

their vocabulary it's the equivalent of

like 2 two additional full languages of

fluency beyond their native language so

you're trilingual at least I don't know

do you speak a language other than

English poorly okay so you're you're at

least trilingual and probably more so no

one is expected to be able to parse

these papers the first time through

without you know substantial training

yeah no I I I think that's a that's a