April 30, 2026 • 33 mins
We start with a simple thought experiment about a high school reunion and end up in a new view of aging where each organ runs its own biological clock. We break down Stanford’s Nature Medicine research showing how a blood test can estimate organ-specific biological age and forecast disease risk years before symptoms appear.
• chronological age as a misleading health metric
• organ-specific biological age across 11 systems
• fat as an active endocrine organ that influences inflammation and metabolism
• UK Biobank approach using 44,498 participants tracked up to 17 years
• proteomics and tissue-specific proteins as a “chemical window” into organs
• machine learning baselines and what extreme deviations mean
• how common “rogue” organs are in the data
• why brain age emerges as the strongest mortality predictor
• organ age predicting organ-linked diseases including Alzheimer’s
• shifting from reactive sick care to proactive healthcare
• using protein signatures to speed up longevity clinical trials
• commercialization path and why early tests may target brain heart and immune system
Keep questioning the biological rules we take for granted.
This podcast is created by Ai for educational and entertainment purposes only and does not constitute professional medical or health advice. Please talk to your healthcare team for medical advice.
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SPEAKER_01 (00:00):
I want you to picture um a high school
reunion.
SPEAKER_00 (00:04):
Oh boy.
SPEAKER_01 (00:05):
Right.
Maybe it's like a tenure, orperhaps you're walking into this
heavily decorated hotel ballroomfor your 30-year reunion.
SPEAKER_00 (00:13):
Yeah, complete with the terrible DJ.
SPEAKER_01 (00:15):
Exactly.
So you walk through the doubledoors, you grab your name tag,
and you start scanning the room.
And almost unconsciously, youstart playing this game we all
participate in, you know,whether we admit it or not.
SPEAKER_00 (00:28):
Oh, absolutely, the scanning game.
SPEAKER_01 (00:30):
Yeah.
You are looking at the guy whoused to sit behind you in
homeroom, and he looks like hehasn't aged a day.
I mean, he's sharp, he'svibrant, he still looks like he
could uh run track.
SPEAKER_00 (00:40):
Right.
SPEAKER_01 (00:41):
But then you look across the punch bow, spot
someone else, and the calculusin your head kicks in.
You process the wrinkles, theposture, the you know, the
hollows under the eyes, and youthink, man, they look like
they've aged three decades.
Trevor Burrus, Jr.
SPEAKER_00 (00:51):
It's harsh, but we all do it.
SPEAKER_01 (00:53):
We do.
But the fascinating part of thiswhole visual assessment is that
everyone in that room has theexact same chronological age.
SPEAKER_00 (01:01):
Aaron Powell Yeah, which is wild to think about.
Aaron Powell Right.
SPEAKER_01 (01:04):
You all graduated the same year.
You've all been on this earthfor the exact same number of
trips around the sun.
SPEAKER_00 (01:09):
Aaron Powell And that right there, um, it really
highlights a massive blind spotin how humanity has historically
understood the passage of time.
Aaron Powell How so Well, Imean, we treat time as this
uniform constant, right?
Like it's an equalizer thataffects all biological matter at
the exact same rate.
SPEAKER_01 (01:26):
Aaron Powell Which makes sense on the calendar,
sure.
Trevor Burrus, Jr.
SPEAKER_00 (01:28):
Right, on a calendar.
But when we look at theunderlying physiology, time is
actually highly subjective.
The physical decay we observevisually, that stuff we see at
the reunion, is just thesuperficial layer of a deeply
localized, uneven biologicalprocess.
SPEAKER_01 (01:43):
Aaron Powell And that uneven process is exactly
what we are decoding in today'sdeep dive.
We are looking at a uh a July2025 study from Stanford
Medicine.
SPEAKER_00 (01:53):
Aaron Powell A really groundbreaking piece of
work.
SPEAKER_01 (01:55):
Truly.
It was led by Dr.
Tony Westcorey and lead authorDr.
Hamilton.
Oh, and published in NatureMedicine.
And it essentially proves thatthe candles on your birthday
cake are just a terrible metricfor your health.
SPEAKER_00 (02:06):
The worst metric, honestly.
SPEAKER_01 (02:07):
Right.
Your chronological age, thatunchangeable number on your
driver's license, is almostmeaningless when stacked up
against your biological age.
SPEAKER_00 (02:16):
Because your biological age is what actually
measures the physical wear andtear on your systems.
SPEAKER_01 (02:20):
Exactly.
But the Stanford team didn'tjust prove that we age
differently from one another,they proved that our bodies do
not even age in unison withthemselves.
SPEAKER_00 (02:28):
And the philosophical shift here, you
know, it really cannot beoverstated.
SPEAKER_01 (02:32):
It's massive.
SPEAKER_00 (02:33):
It is.
I mean, medicine has relied onchronological age for centuries,
simply because it's a binary,easily verifiable fact.
You were born in this year, soyou are this old.
SPEAKER_01 (02:43):
Right.
It's easy math.
SPEAKER_00 (02:45):
Yeah.
But biological age is cryptic.
It is this hidden metric of yourtrue likelihood of developing
aging-associated disorders.
And what Waste Corey's teammanaged to do is, well, they
shattered the whole concept of aunified self.
SPEAKER_01 (02:59):
The unified self, meaning like I am a 45-year-old
person across the board.
SPEAKER_00 (03:03):
Exactly.
You aren't just a 45-year-oldperson.
You are a walking collective of11 distinct organ systems.
And this team developed a methodto look into the blood and
actually assign an individualage to every single one of them.
SPEAKER_01 (03:18):
Okay, let's unpack this.
Because the idea that my livercould be, I don't know, an
entirely different age than mylungs is really difficult to
visualize.
SPEAKER_00 (03:26):
It was a weird concept, yeah.
SPEAKER_01 (03:28):
It makes me think of um buying a vintage car.
SPEAKER_00 (03:32):
Okay, I like where this is going.
SPEAKER_01 (03:33):
So yeah, say you buy a classic 1974 muscle car.
The chassis, the metal frame, is50 years old.
That is the chronological age.
Right.
But over the lifespan of thatcar, the previous owner swapped
out the transmission.
So that part is only 30 yearsold.
SPEAKER_00 (03:47):
Ah, I see.
SPEAKER_01 (03:48):
However, they drove the car incredibly hard, you
know, rode the brakes down steephills, and never replaced the
brake pads.
So those brake pads have enduredthe friction and thermal stress
of an 80-year-old component.
SPEAKER_00 (03:59):
Yeah, that's spot on.
SPEAKER_01 (04:00):
So my body is that car made of parts aging at
wildly different speeds.
SPEAKER_00 (04:05):
That analogy works beautifully.
But um, we have to take it astep further to really
understand the biology here.
SPEAKER_01 (04:11):
Okay, lay it on me.
SPEAKER_00 (04:12):
It's not just that the brake pads are worn down,
it's that as they wear down,they are actively shedding
metallic dust and like chemicalexhaust into the oil stream of
the car.
SPEAKER_01 (04:22):
Oh, wow.
Okay.
SPEAKER_00 (04:24):
And the Stanford researchers mapped this concept
across 11 specific systems.
So we're talking about thebrain, muscle, heart, lung,
arteries, liver, kidneys,pancreas, immune system,
intestine, and fat.
SPEAKER_01 (04:38):
Wait, I need to pause on that list for a second.
Fat.
SPEAKER_00 (04:39):
Yeah, fat.
SPEAKER_01 (04:40):
Fat is considered one of the eleven independently
aging organ systems.
I mean, I think most people viewfat as just like inert storage.
Like a biological backpack wejust carry around.
SPEAKER_00 (04:50):
That is a very common misconception.
But adipose tissue, which iswhat fat is, is actually a
massive, highly active endocrineorgan.
SPEAKER_01 (04:59):
Wait, really?
It's an organ.
SPEAKER_00 (05:00):
Oh, absolutely.
It doesn't just sit there, itconstantly secretes hormones
known as adipokines, and itinteracts with your entire
metabolic system.
It talks to your immune responseand your cardiovascular network.
SPEAKER_01 (05:10):
I had no idea it was that involved.
SPEAKER_00 (05:12):
Yeah, and as adipose tissue ages, it becomes
dysfunctional.
It stops storing lipidsefficiently and starts secreting
these pro-inflammatorymolecules.
So the biological age of yourfat is incredibly relevant to
your overall systemic health.
SPEAKER_01 (05:26):
That completely changes the context of what it
means to be healthy.
SPEAKER_00 (05:29):
It really does.
SPEAKER_01 (05:30):
Because I mean, you could be someone who eats well,
maintains a decent outwardappearance, and just assumes
everything is fine.
You know, you were 50 years old,but inside your heart has
endured the biological stress ofa 75-year-old.
SPEAKER_00 (05:42):
Exactly.
SPEAKER_01 (05:43):
Meanwhile, your immune system might be operating
with the cellular vitality of a30-year-old.
It just makes the concept of anannual physical where they just
take your blood pressure and askhow you feel seem almost
primitive.
SPEAKER_00 (05:55):
Well, it is primitive.
SPEAKER_01 (05:56):
Yeah.
SPEAKER_00 (05:57):
Historically, because we couldn't measure
localized biological aging, wejust treated the body as a
single entity in decline.
SPEAKER_01 (06:04):
Like it all goes downhill together.
SPEAKER_00 (06:06):
Right.
The assumption in a standardmedical clinic is that if you
present as generally robust,well then your internal systems
are uniformly robust.
If you are frail, you are fraileverywhere.
SPEAKER_01 (06:17):
But this study says that's flat out wrong.
SPEAKER_00 (06:19):
Completely wrong.
This research proves that agingis intensely localized.
Your lungs could be undergoingaccelerated, dangerous
senescence.
SPEAKER_01 (06:28):
And senescence is like cellular deterioration.
SPEAKER_00 (06:32):
Aaron Ross Powell Exactly.
And maybe that's due to acombination of genetic
susceptibility and, say, a briefperiod of living in a city with
high particulate air pollution adecade ago.
SPEAKER_01 (06:42):
Oh, interesting.
SPEAKER_00 (06:43):
Right.
So your lungs are old while yourkidneys might remain completely
pristine.
SPEAKER_01 (06:48):
Aaron Powell Okay, but I keep getting stuck on the
mechanics of how you actuallygather that data.
SPEAKER_00 (06:52):
Aaron Powell The methodology.
SPEAKER_01 (06:53):
Right.
Because knowing that the body isa collection of separately aging
parts is a great theory.
But you can't just pop the hoodand inspect a living human's
pancreas to see how much wearand tear it has.
SPEAKER_00 (07:04):
No, definitely not.
SPEAKER_01 (07:06):
So how do they actually prove this in living
people without cutting themopen?
SPEAKER_00 (07:10):
Aaron Ross Powell Well, they turn to one of the
most powerful scientificresources on the planet, which
is the UK Biobank.
SPEAKER_01 (07:15):
Okay, I've heard of that.
SPEAKER_00 (07:16):
Yeah, to prove a paradigm shift like this, you
need a staggering amount of dataover a very long horizon.
And the UK Biobank is thislongitudinal study that has
gathered biological samples anddeep medical records from
roughly half a millionindividuals.
SPEAKER_01 (07:31):
Aaron Powell Okay, and a longitudinal study,
meaning they don't just take asnapshot of someone on a Tuesday
and send them home.
They follow them through time.
SPEAKER_00 (07:38):
Correct.
So for this specific analysis,the Stanford team filtered that
massive database down to exactly44,498 randomly selected
participants.
SPEAKER_01 (07:49):
Aaron Powell Wow, almost 45,000 people.
SPEAKER_00 (07:52):
Yeah.
All between the ages of 40 and70.
And these individuals didn'tjust give one blood sample, they
had multiple samples taken overthe course of up to 17 years.
SPEAKER_01 (08:00):
17 years?
That is a massive commitment.
SPEAKER_00 (08:03):
It is.
The researchers had access tothis continuous feed of updated
medical reports.
They could watch in real timethe evolution of these people's
health status.
Trevor Burrus, Jr.
SPEAKER_01 (08:12):
So they were documenting who developed
chronic diseases and whoultimately died.
Following almost 45,000 peoplefor up to 17 years is a
monumental logisticalachievement.
SPEAKER_00 (08:21):
Unprecedented, really.
SPEAKER_01 (08:23):
But um, I have a serious logistical question
about the testing itself.
You mentioned looking into theblood.
Right.
If a phonotomist pulls a vial ofblood from a vein in my arm,
that blood has been circulatingeverywhere.
Right.
It's a systemic fluid.
SPEAKER_00 (08:38):
It goes everywhere, yes.
SPEAKER_01 (08:39):
Aaron Powell So how on earth do you isolate the
biological age of the intestineor the brain from this totally
random mixture of blood?
SPEAKER_00 (08:47):
Well, to understand that, we really have to look at
what blood actually is.
I mean, it isn't just red andwhite blood cells floating
around in some neutral plasma.
SPEAKER_01 (08:55):
There's more to it than just that.
SPEAKER_00 (08:56):
Exactly.
Blood is actually this vastsuperhighway of molecular
information because, you know,every organ in your body is
constantly undergoing cellularturnover.
Cells are born, they function,they get damaged, and then they
die.
SPEAKER_01 (09:11):
Okay, so it's a constant cycle.
SPEAKER_00 (09:13):
Yeah.
And during this entire lifecycle, organs are just
constantly shedding proteinsinto your bloodstream.
So Weissquarry's team utilizedhighly advanced commercial
technology to detect and countthe concentrations of nearly
3,000 different proteins in theblood of these participants.
SPEAKER_01 (09:28):
Wait, capturing 3,000 distinct proteins from a
single blood draw?
That sounds like finding needlesin a microscopic haystack.
SPEAKER_00 (09:37):
It's incredibly precise.
SPEAKER_01 (09:38):
But even if you can count them, how does that tell
you where they came from?
A protein is a protein, isn'tit?
SPEAKER_00 (09:43):
Actually, it's not.
And this is the crucialbiological mechanism that
underpins the entire study.
Okay.
What's fascinating here istissue-specific gene expression.
This means that a liver cellfunctions entirely differently
than a heart cell.
And because they performcompletely different jobs and
manufacture completely differentproteins.
SPEAKER_01 (10:02):
Oh, I see.
SPEAKER_00 (10:02):
Yeah.
So out of the 3,000 proteins theresearchers analyzed, they
discovered that roughly 15% ofthem could be traced back to
single organ origins.
SPEAKER_01 (10:12):
Ah, okay.
This brings us back to thevintage car analogy.
Yeah.
Specifically, the oil check.
SPEAKER_00 (10:18):
Yes.
Let's go back to that.
SPEAKER_01 (10:19):
Right.
So if a mechanic pulls thedipstick out of your engine and
analyzes the oil, they aren'tjust looking at the color.
If they find very specific typesof, say, brass shavings in the
oil, they know exactly whichsynchretizer ring in the
transmission is grinding down.
Because those specific brassshavings can only logically
originate from that single gear.
SPEAKER_00 (10:40):
That is an exceptionally precise way to
visualize it.
When the researchers see aspecific concentration of a
particular protein, they knowwith absolute certainty that it
originated in, say, the leftventricle of the heart.
Wow.
Right.
If they detect a differentprotein, it is uniquely tied to
the pulmonary tissue in thelung.
So while 85% of the proteinsthey tracked are shared across
(11:03):
multiple systems, that specific15% of single organ proteins
gave them a direct, uncorruptedchemical window into the
distinct status of those 11specific organs.
SPEAKER_01 (11:15):
Aaron Powell That is mind-blowing.
So they have a vial of blood,they identify the single organ
proteins, and they measure theconcentrations.
But um, how does knowing theamount of a protein tell you the
age of the organ?
SPEAKER_00 (11:26):
Good question.
SPEAKER_01 (11:27):
Because I imagine you don't just put a lung
protein under an electronmicroscope and count its rings
like a tree stump.
SPEAKER_00 (11:32):
No, no.
The proteins themselves aren'twhat is old.
I mean, a protein synthesizedyesterday by a 70-year-old liver
is technically a brand newprotein.
SPEAKER_01 (11:39):
Okay, that makes sense.
SPEAKER_00 (11:40):
What changes is the pattern of proteins being
secreted.
As an organ ages, its cellularmachinery degrades.
You get these senescent cells,cells that have basically
stopped dividing but refuse todie and they begin to
accumulate.
SPEAKER_01 (11:55):
Like zombie cells.
SPEAKER_00 (11:56):
Exactly like zombie cells.
And these senescent cellssecrete a very specific toxic
cocktail of inflammatoryproteins.
Additionally, as the tissuestructure breaks down,
intracellular proteins thatshould absolutely remain inside
the organ start to leak into theblood.
So the researchers aren'tlooking for old proteins,
they're looking for the shiftingconcentration profile of
(12:18):
proteins that indicates an organis deteriorating.
SPEAKER_01 (12:21):
Okay, that makes total sense.
It's the signature of theenvironment, not the age of the
individual molecule.
SPEAKER_00 (12:26):
Exactly.
SPEAKER_01 (12:27):
But how do you establish what a normal
signature is?
Like how do they know what thebaseline looks like?
SPEAKER_00 (12:31):
That is where the sheer computing power comes in.
Because they had over 44,000people, they could feed all
those protein levels into amachine learning algorithm.
Oh wow.
Yeah.
The computer analyzed everysingle participant and
established an age-adjustedbaseline.
So it calculated exactly whatthe average healthy mixture of
heart proteins looks like in theblood of a 50-year-old, a
(12:52):
51-year-old, a 52-year-old, andso on.
SPEAKER_01 (12:54):
So they basically built this massive biological
fingerprint catalog.
SPEAKER_00 (12:58):
Precisely.
And once the algorithmestablishes that baseline
fingerprint for everychronological age, the testing
becomes highly individualized.
Right.
You can take a new blood samplefrom a 45-year-old patient,
isolate the proteins, and askthe algorithm, hey, how much
does this individual's kidneyprotein signature deviate from
our baseline of a healthy45-year-old kidney?
SPEAKER_01 (13:19):
Okay, so if my protein signature perfectly
matches the algorithm's averagefor a 45-year-old, my kidney and
I are aging perfectly in sync.
SPEAKER_00 (13:27):
Yes.
Your biological age for thatspecific organ matches your
chronological age.
The clinical value, however, isin the deviations.
SPEAKER_01 (13:35):
When things don't line up.
SPEAKER_00 (13:36):
Right.
These organ-specific proteinsignatures act as highly
sensitive proxies for thephysical state of the organ.
SPEAKER_01 (13:42):
So let's talk about those deviations.
Because the study didn't justfind people whose organs were
like a few months ahead orbehind schedule.
They were looking for extremeoutliers.
SPEAKER_00 (13:53):
They were.
In any vast data set, mostpeople kind of cluster around
the average.
So to identify true dangerousdivergence, the researchers set
a strict mathematical threshold.
Which was a 1.5 standarddeviation from the age-adjusted
mean.
If your organ's proteinsignature crossed that
threshold, it wasn't just aginga little fast, it fell into the
(14:14):
extremely aged category.
SPEAKER_01 (14:16):
And the reverse is true too, right?
SPEAKER_00 (14:18):
Yes.
Crossing the threshold in theother direction placed the organ
in the extremely youthfulcategory.
SPEAKER_01 (14:24):
Okay, and when they applied that 1.5 standard
deviation threshold to those44,000 people, the results were
incredibly alarming.
I mean, one-third of theindividuals in this study had at
least one organ that was agingat an extreme, highly
accelerated rate compared to therest of their body.
SPEAKER_00 (14:39):
One in three.
It completely dispels the myththat accelerated aging is this
rare condition reserved for thevisibly frail.
SPEAKER_01 (14:46):
It actually gets much more severe than that,
though.
One in four participants, 25% ofthe people walking around in
this study had multiple,extremely aged or youthful
organs.
SPEAKER_00 (14:58):
Yeah, the multiple organ divergence is the really
scary part.
SPEAKER_01 (15:01):
Think about the implications of that for a
moment.
If you are sitting in aconference room right now with
three co-workers, the statisticsdictate that at least one of you
has a rogue organ sprintingtoward failure, completely out
of sync with your chronologicalage.
Right.
One out of every four people inthat room has multiple organs
doing it.
You could be sitting next tosomeone whose liver is
(15:23):
biologically 20 years older thanthey are, and neither they nor
their doctor has any idea.
SPEAKER_00 (15:28):
And that silent divergence is the most dangerous
aspect of human health.
An extremely aged organ isbasically a ticking clock.
SPEAKER_01 (15:35):
Because it's a weak link.
SPEAKER_00 (15:36):
Exactly.
It represents a localizedvulnerability that standard
metabolic panels and annualcheckups are completely blind
to.
A standard blood test looks forfunctional failure.
You know, it tells you when theorgan has already broken.
SPEAKER_01 (15:48):
Like your enzymes are off the charts.
SPEAKER_00 (15:50):
Right.
But this protein algorithm looksfor the structural degradation
that occurs years before thefailure ever actually happens.
SPEAKER_01 (15:59):
Now, while having an old liver or an old intestine is
obviously a massive health risk,the Stanford team found a
hierarchy within these 11systems.
And here's where it gets reallyinteresting.
SPEAKER_00 (16:10):
Yes, it really does.
SPEAKER_01 (16:11):
Because not all organs carry the same weight
when it comes to keeping thehuman body alive.
SPEAKER_00 (16:15):
They definitely do not.
When the researchers analyzedthe mortality data over that
15-year monitoring period, oneorgan separated itself entirely
from the pack.
Dr.
Weiss Corey explicitly labeledthe brain as the gatekeeper of
longevity.
SPEAKER_01 (16:31):
The gatekeeper of longevity.
That implies that the braindoesn't just, you know, manage
its own health, but activelydictates the survival of the
entire organism.
SPEAKER_00 (16:40):
The data supports that conclusion overwhelmingly.
They cross-reference thebiological ages of the 11 organs
against the all-cause mortalityof the participants.
And the numbers are staggering.
SPEAKER_01 (16:50):
Let's hear them.
SPEAKER_00 (16:51):
Having an extremely aged brain, meaning crossing
that 1.5 standard deviationthreshold into accelerated
aging, increases a subject'srisk of dying by 182%.
SPEAKER_01 (17:03):
Wait, a 182% increase in the risk of
mortality?
SPEAKER_00 (17:07):
Yes.
SPEAKER_01 (17:07):
The odds of you dying almost triple simply
because this single organ'sprotein signature is reading
older than your chronologicalage.
SPEAKER_00 (17:15):
And the protection offered by the opposite extreme
is equally potent.
Individuals whose bloodindicated an extremely youthful
brain experience a 40% reductionin their overall risk of dying
over that same 15-year window.
SPEAKER_01 (17:27):
So a young brain slashes your mortality risk
almost at half, and an old brainnearly triples it.
SPEAKER_00 (17:33):
Exactly.
SPEAKER_01 (17:34):
But how large is the demographic we are talking about
at these extremes?
Like, is half the populationwalking around with a
biologically old brain?
SPEAKER_00 (17:40):
No, no.
Because of that strict 1.5standard deviation threshold,
the extremes are relativelyexclusive.
The extremely aged brains madeup only six to seven percent of
the total study participants.
SPEAKER_01 (17:50):
Okay, so a small slice.
SPEAKER_00 (17:52):
Right.
Those are the individuals whoseprotein signatures fell at the
absolute worst end of thedistribution.
The extremely youthful brainsaccounted for another six to
seven percent at the highlyoptimized end of the spectrum.
SPEAKER_01 (18:05):
Aaron Powell I want to push back on the philosophy
of the brain as the ultimategatekeeper for a second.
Sure.
Because I understand that thebrain is essential, obviously.
But if my heart stops beating, Idie instantly.
If my lungs stop processingoxygen, I die.
Why does the brain specificallyexert such a disproportionate
gravitational pull on overallmortality?
SPEAKER_00 (18:26):
Well, it requires looking at the body as an
integrated network rather thanlike isolated silos.
The brain does not simply sit inthe skull and think.
Right.
It is the central command centerfor the autonomic nervous system
and the neuroendocrine system.
Through the hypothalamus and thepituitary gland, the brain
regulates systemic inflammation.
It manages your metabolic rate,it dictates the release of
(18:47):
stress hormones like cortisol.
SPEAKER_01 (18:49):
So it's pulling all the levers.
SPEAKER_00 (18:51):
Exactly.
It even controls the vagusnerve, which directly influences
your heart rate and gutmotility.
So if the brain undergoesaccelerated aging, its
regulatory signaling degrades.
An aged brain might uminappropriately signal systemic
inflammation, which thenactively damages the heart, the
blood vessels, and the kidneys.
SPEAKER_01 (19:12):
Wow.
So an aging brain doesn't justfail in isolation.
It literally drags the rest ofthe organs down with it by
sending chaotic degradingsignals.
SPEAKER_00 (19:20):
Furthermore, we really cannot ignore the
behavioral component.
SPEAKER_01 (19:23):
Oh, true.
SPEAKER_00 (19:24):
An aging brain leads to cognitive decline, which
changes how a person interactswith their environment.
It can lead to poor dietarychoices, a reduction of physical
movement, disrupted sleeparchitecture, or even just the
inability to manage medications.
SPEAKER_01 (19:36):
All of which compound mortality risks
rapidly.
SPEAKER_00 (19:39):
Absolutely.
When the Stanford researcherslooked at the raw predictive
power, brain age was the singlemost accurate predictor of
mortality out of every organthey tested.
SPEAKER_01 (19:47):
Aaron Powell But you know, mortality is the final
step.
People rarely just drop deadstrictly from an old brain
without a preceding clinicalevent.
Before mortality, there isdisease.
How accurately can this proteinalgorithm predict the specific
illnesses a person will develop?
SPEAKER_00 (20:03):
This is where the algorithm transitions from a
theoretical measurement of agingto a highly practical clinical
tool.
The researchers tracked 15 majorchronic disorders across the
cohort over those 17 years.
SPEAKER_01 (20:15):
What kind of disorders are we talking about?
SPEAKER_00 (20:17):
We are talking about the diseases that fundamentally
define human aging (20:19):
Alzheimer's, Parkinson's, chronic liver
disease, chronic kidney disease,type 2 diabetes, atrial
fibrillation, heart failure,chronic obstructive pulmonary
disease, rheumatoid arthritis,osteoarthritis, and several
others.
SPEAKER_01 (20:36):
So they took the biological age of the eleven
organs and mapped them againstwho developed those 15 diseases.
What did that web of connectionslook like?
SPEAKER_00 (20:44):
Well, the associations weren't a messy
overlapping rabit all.
What emerged was a remarkablyclear one-to-one correlation.
One-to-one.
Yes.
An aged organ perfectlypredicted a future disease
associated exclusively with thatspecific organ.
SPEAKER_01 (20:59):
Give me an example of how that plays out in the
data.
SPEAKER_00 (21:01):
Okay, so if the blood test revealed an extremely
aged heart protein signature,that specific finding strongly
predicted a high risk of thepatient developing atrial
fibrillation or heart failure inthe years that followed.
Okay.
If the blood test showedextremely aged lungs, it
predicted a heightened risk ofdeveloping COPD.
The localized biological ageacted as this specific localized
(21:24):
crystal ball.
SPEAKER_01 (21:25):
That makes perfect sense mechanically.
The tissue degrades, it shedsexhaust into the blood, the
algorithm flags the aged organ,and then years later, the
clinical symptoms of thatspecific organ's failure finally
appear.
SPEAKER_00 (21:37):
Exactly right.
SPEAKER_01 (21:38):
But the most terrifying disease on that list
of 15 is Alzheimer's.
Let's look at the Alzheimer'sdata, because the math here is
the most powerful association inthe entire study.
SPEAKER_00 (21:47):
The predictive correlation between biological
brain age and Alzheimer'sdisease is truly profound.
If an individual falls into thatsix to seven percent demographic
with an extremely aged brain,their risk of developing
Alzheimer's Alzheimer's is 3.1times higher than a person whose
brain is aging normally.
SPEAKER_01 (22:04):
So you literally triple your risk of Alzheimer's
just by crossing into that agedthreshold.
SPEAKER_00 (22:09):
Yes.
SPEAKER_01 (22:09):
But what happens on the protective side?
What about the six to sevenpercent with the extremely
useful brains?
SPEAKER_00 (22:15):
The protection is immense.
For those with an extremelyyouthful brain, their risk of
developing Alzheimer's is only0.25 times the risk of a person
with a normally aged brain.
SPEAKER_01 (22:26):
Wait, really?
SPEAKER_00 (22:27):
Yeah, their risk is slashed to barely one-fourth of
the baseline.
SPEAKER_01 (22:31):
What's fascinating here is what happens when you
synthesize those two extremes.
Let's lay this out clearly,because this is kind of the
pivot point of the entire deepdive.
Let's do it.
You have the biologically oldbrains carrying a 3.1x risk
multiplier.
You have the biologically youngbrains carrying a 0.25x risk
multiplier.
If you contrast someone at thetop of that curve with someone
(22:52):
at the bottom, it means anindividual with a biologically
old brain is approximately 12times as likely to be diagnosed
with Alzheimer's over the nextdecade as someone the exact same
chronological age with abiologically young brain.
SPEAKER_00 (23:05):
12 times the risk.
It is an astronomical delta.
And what is vital to understandis that this prediction is made
entirely by analyzing invisibleproteins floating in a vial of
blood years, potentially a fulldecade before the patient ever
experiences a single clinicalsymptom of memory loss.
SPEAKER_01 (23:24):
That level of foresight changes everything.
I mean, imagine two 55-year-oldindividuals walking into a
clinic.
From the outside, they lookidentical.
They might even score exactlythe same on a standard cognitive
memory test that day.
SPEAKER_00 (23:37):
Right, they pass with flying colors.
SPEAKER_01 (23:38):
Exactly.
A neurologist would tell both ofthem they are perfectly healthy.
But this Stanford blood test canlook 10 years into their
biological future anddefinitively state that patient
A has a 12fold higherprobability of developing
Alzheimer's than patient B.
SPEAKER_00 (23:54):
And if we connect this to the bigger picture, this
capability forces the completedismantling of our current
medical framework.
unknown (24:00):
Dr.
SPEAKER_00 (24:00):
Weiss Corrier articulated this perfectly.
He pointed out that modernmedicine does not actually
practice health care.
We practice sick care.
SPEAKER_01 (24:07):
Oh, I think anyone who has ever navigated the
medical system deeplyunderstands that distinction.
SPEAKER_00 (24:12):
Right.
In a sick care model, the entiresystem is reactionary.
You do not seek interventionuntil something is broken.
You wait until you feel atightness in your chest, or you
develop a chronic, painfulcough, or you realize you cannot
remember how to drive home fromthe grocery store.
SPEAKER_01 (24:30):
And only then do you go to a physician?
SPEAKER_00 (24:33):
Only then.
And they just run tests toconfirm the damage that has
already occurred.
SPEAKER_01 (24:37):
It's the equivalent of waiting for the engine block
to crack on the highway beforeyou pull over and check the oil.
You are literally waiting forcatastrophic failure before
initiating maintenance.
SPEAKER_00 (24:47):
Exactly.
And with neurodegenerativeconditions like Alzheimer's, the
sick care model is utterlydevastating.
By the time outward symptomsappear, by the time a patient is
failing memory tests, thephysical decay of the neural
networks is already extensive.
SPEAKER_01 (25:03):
The damage is done.
SPEAKER_00 (25:04):
Millions of neurons have already died.
The structural damage is largelyirreversible, which is exactly
why Alzheimer's drug trials havehistorically had such a dismal
success rate.
We are trying to put out a fireafter the house has already
burned down.
SPEAKER_01 (25:17):
But if we deploy this 11-organ blood test, we
shift the paradigm to truehealthcare.
SPEAKER_00 (25:22):
True healthcare is proactive intervention before
the manifestation of symptoms.
If a 50-year-old takes thisblood test and discovers their
brain is biologically 65, thatextreme brain age serves as a
biological proxy for impendingAlzheimer's.
SPEAKER_01 (25:37):
So they have a head start.
SPEAKER_00 (25:38):
Exactly.
The physician can initiateaggressive interventions,
whether pharmacological,dietary, or lifestyle-based,
while the brain's structuralintegrity is still intact.
We are detecting the smolderingembers instead of the inferno.
SPEAKER_01 (25:51):
Aaron Powell That fundamentally alters the
timeline of human longevity.
Yeah.
But um it also raises a massivequestion about how we figure out
which interventions actuallywork.
SPEAKER_00 (26:00):
What do you mean?
SPEAKER_01 (26:01):
Well, right now, if I want to know if a specific
diet or a new longevity compoundprotects the brain, the clinical
trial process is excruciatinglyslow.
Researchers have to putthousands of people on a
protocol and then just sit backand wait 20 years to see who
gets dementia and who dies.
SPEAKER_00 (26:16):
Aaron Powell Yeah, the sheer length of traditional
clinical trials is the primarybottleneck in longevity
research.
It is incredibly inefficient andoverwhelmingly expensive.
However, this organ-agingalgorithm provides a
revolutionary shortcut.
SPEAKER_01 (26:29):
How so?
SPEAKER_00 (26:30):
Because the protein signatures in the blood change
as the tissue environmentchanges, the feedback loop
becomes incredibly tight.
SPEAKER_01 (26:37):
So instead of waiting for a patient to develop
a disease or pass away, you canuse the protein signatures as
like a real-time trackingdashboard.
SPEAKER_00 (26:45):
Precisely.
In a modern clinical trial,scientists will test a patient's
blood on day one to establishthe biological age of their 11
organs.
Then they implement theintervention.
Maybe it's a new synolytic drugdesigned to clear out senescent
cells or a rigorouscardiovascular exercise
protocol.
Six months later, they draw theblood again.
They do not have to wait adecade to see if the patient
(27:07):
survives.
They simply look to see if theprotein exhaust has shifted.
SPEAKER_01 (27:10):
They can literally watch the biological clock
rewind in the data.
Yes.
They can definitively prove inreal time if a specific
intervention actually restoresorgan youth.
SPEAKER_00 (27:20):
It replaces guesswork with granular,
organ-specific data.
We'll be able to answerincredibly nuanced questions
very quickly.
Does this specific class ofstatin lower the biological age
of the arteries or does it onlymask cholesterol numbers?
Right.
Does a sustained ketogenic dietgenuinely reverse the aging
signature of the brain?
(27:40):
The speed of scientificdiscovery will accelerate
exponentially.
SPEAKER_01 (27:44):
Which naturally leads to the question every
single person listening isasking right now.
SPEAKER_00 (27:48):
I can guess what it is.
SPEAKER_01 (27:49):
This is groundbreaking science, but is
it trapped in a Stanfordlaboratory forever, or is it
going to see the light of day?
When can an average personactually get this blood test?
SPEAKER_00 (27:59):
Aaron Powell It is rapidly moving out of the
laboratory.
Dr.
Weisscore is activelyspearheading commercialization.
He has already co-founded twoseparate companies, TLOMics and
Virobioscience, with theexplicit goal of bringing this
diagnostic technology to thepublic market.
SPEAKER_01 (28:13):
Aaron Powell Usually when we cover experimental
medical technology, the timelineis accompanied by a heavy caveat
of, you know, maybe in a decadeif it passes phase three trials.
What is the realistic timelinefor TL omics or virobioscience?
Aaron Powell Dr.
SPEAKER_00 (28:26):
Weiss Corey has publicly stated that this test
could be available to consumersin the next two to three years.
SPEAKER_01 (28:31):
Two to three years.
In the realm of medicaldiagnostics, that is practically
tomorrow morning.
SPEAKER_00 (28:37):
The timeline is aggressive, but it is supported
by the immense credibility ofthe institutions involved.
I mean, this research wasn'tconducted in a vacuum, it was
funded by heavyweights.
We're talking massive grantsfrom the National Institutes of
Health, the Milky WayFoundation, the Knight
Initiative for Brain Resilience,and the Stanford Alzheimer's
(28:58):
Disease Research Center.
SPEAKER_01 (28:59):
So the money is there.
SPEAKER_00 (29:00):
The financial and institutional momentum required
to push this into the commercialsphere is fully secured.
SPEAKER_01 (29:06):
But let's talk about the practical reality of scaling
this up.
Analyzing 3,000 distinctproteins using mass spectrometry
or advanced of tamer arrayssounds incredibly resource
intensive.
SPEAKER_00 (29:17):
It is.
SPEAKER_01 (29:18):
So is this going to be a boutique diagnostic that
only tech billionaires canafford, or will it actually be
accessible to the generalpublic?
SPEAKER_00 (29:25):
Cost is undeniably the primary hurdle for mass
commercialization.
To solve this, the researchersare refining the scope of the
consumer test.
The initial commercial rolloutwill likely not map all 11
organs simultaneously.
Okay.
To drastically reduce the cost,they plan to focus on a highly
targeted panel of the organsthat exhibit the strongest
(29:46):
predictive links to majormortality drivers.
Specifically, the commercialtest will likely focus on just
three systems the brain, theheart, and the immune system.
SPEAKER_01 (29:56):
Strategically, that makes perfect sense.
You have the brain, which is theultimate gatekeeper of
longevity, you have the heart,which is the mechanical engine
responsible for vast amounts ofsudden mortality.
Right.
And you have the immune system,which is the defense network
responsible for managingsystemic inflammation and
clearing out damaged cells.
If I can get high resolutiondata on those three systems for
a few hundred dollars, that is amap of my biological future.
SPEAKER_00 (30:19):
Exactly.
By filtering out the noise ofthe other 2,000 plus proteins
and focusing solely on thespecific markers for those three
critical systems, they canincrease the diagnostic
resolution while democratizingthe price point.
SPEAKER_01 (30:32):
That's brilliant.
SPEAKER_00 (30:33):
It transforms the technology from a luxury
biohacking tool into a routinestaple of preventative primary
care.
SPEAKER_01 (30:40):
It is truly staggering to think about the
journey of discovery we justwalked through.
For our entire lives, we havebeen conditioned to view our
chronological age as this rigid,inescapable definition of who we
are.
SPEAKER_00 (30:53):
Yeah, a number we can't escape.
SPEAKER_01 (30:54):
But the reality inside our bodies is far more
complex and ultimately far morehopeful.
Your chronological age isnothing more than a superficial
suggestion.
Beneath the surface, you are acomplex ecosystem running on
eleven distinct hiddenbiological clocks.
SPEAKER_00 (31:10):
That's a great way to summarize it.
SPEAKER_01 (31:11):
Your liver, your lungs, your adipose tissue, your
brain, they are all travelingthrough time at different
velocities, shedding theirunique protein exhaust into your
bloodstream.
And by reading that exhaust, wecan perfectly predict localized
health risks a full decadebefore a single symptom emerges.
SPEAKER_00 (31:31):
And you know, the most valuable aspect of this
deep dive is what it allows usto do next.
Knowledge of this magnitude isonly useful when it is applied.
Right.
Understanding that our organsage independently provides us
with unprecedented agency.
We are no longer blindpassengers just waiting for an
inevitable breakdown.
SPEAKER_01 (31:49):
We can do something about it.
SPEAKER_00 (31:50):
We have the capability to build a dashboard.
We can identify the precisebiological vulnerabilities
within our own bodies andintervene strategically.
We can specifically protect ourindividual gatekeepers of
longevity before the damage isdone.
SPEAKER_01 (32:03):
It fundamentally shifts the power dynamic of
human aging.
But um, I want to leave you witha final thought to mull over as
you step away from this deepdive today.
SPEAKER_00 (32:10):
Let's hear it.
SPEAKER_01 (32:11):
We just established that this test will likely hit
the commercial market in thenext two to three years.
Soon you will have the abilityto walk into a clinic, give a
simple vial of blood, andreceive an incredibly accurate
projection of exactly when yourbrain or your heart is scheduled
to fail.
SPEAKER_00 (32:27):
It's a heavy thought.
SPEAKER_01 (32:29):
You can access a definitive biological timer for
your most vital organs yearsbefore you experience a single
physical ache or a momentaryslip in memory.
So if that test becomesavailable to you tomorrow, would
you actually want to take it?
Would you want to know theprecise speed at which your
brain is aging?
And more importantly, if youreceive that data and realized
(32:51):
your biological clock wasrunning far faster than you
thought, how would that singleterrifying piece of knowledge
change the exact way you chooseto live your life tomorrow
morning?
Thank you for joining us on thisdeep dive into the hidden clocks
inside us all.
SPEAKER_00 (33:06):
It has been a privilege exploring the future
of medicine with you.
Keep questioning the biologicalrules we take for granted.
I want you to picture um a high school
reunion.
SPEAKER_00 (00:04):
Oh boy.
SPEAKER_01 (00:05):
Right.
Maybe it's like a tenure, orperhaps you're walking into this
heavily decorated hotel ballroomfor your 30-year reunion.
SPEAKER_00 (00:13):
Yeah, complete with the terrible DJ.
SPEAKER_01 (00:15):
Exactly.
So you walk through the doubledoors, you grab your name tag,
and you start scanning the room.
And almost unconsciously, youstart playing this game we all
participate in, you know,whether we admit it or not.
SPEAKER_00 (00:28):
Oh, absolutely, the scanning game.
SPEAKER_01 (00:30):
Yeah.
You are looking at the guy whoused to sit behind you in
homeroom, and he looks like hehasn't aged a day.
I mean, he's sharp, he'svibrant, he still looks like he
could uh run track.
SPEAKER_00 (00:40):
Right.
SPEAKER_01 (00:41):
But then you look across the punch bow, spot
someone else, and the calculusin your head kicks in.
You process the wrinkles, theposture, the you know, the
hollows under the eyes, and youthink, man, they look like
they've aged three decades.
Trevor Burrus, Jr.
SPEAKER_00 (00:51):
It's harsh, but we all do it.
SPEAKER_01 (00:53):
We do.
But the fascinating part of thiswhole visual assessment is that
everyone in that room has theexact same chronological age.
SPEAKER_00 (01:01):
Aaron Powell Yeah, which is wild to think about.
Aaron Powell Right.
SPEAKER_01 (01:04):
You all graduated the same year.
You've all been on this earthfor the exact same number of
trips around the sun.
SPEAKER_00 (01:09):
Aaron Powell And that right there, um, it really
highlights a massive blind spotin how humanity has historically
understood the passage of time.
Aaron Powell How so Well, Imean, we treat time as this
uniform constant, right?
Like it's an equalizer thataffects all biological matter at
the exact same rate.
SPEAKER_01 (01:26):
Aaron Powell Which makes sense on the calendar,
sure.
Trevor Burrus, Jr.
SPEAKER_00 (01:28):
Right, on a calendar.
But when we look at theunderlying physiology, time is
actually highly subjective.
The physical decay we observevisually, that stuff we see at
the reunion, is just thesuperficial layer of a deeply
localized, uneven biologicalprocess.
SPEAKER_01 (01:43):
Aaron Powell And that uneven process is exactly
what we are decoding in today'sdeep dive.
We are looking at a uh a July2025 study from Stanford
Medicine.
SPEAKER_00 (01:53):
Aaron Powell A really groundbreaking piece of
work.
SPEAKER_01 (01:55):
Truly.
It was led by Dr.
Tony Westcorey and lead authorDr.
Hamilton.
Oh, and published in NatureMedicine.
And it essentially proves thatthe candles on your birthday
cake are just a terrible metricfor your health.
SPEAKER_00 (02:06):
The worst metric, honestly.
SPEAKER_01 (02:07):
Right.
Your chronological age, thatunchangeable number on your
driver's license, is almostmeaningless when stacked up
against your biological age.
SPEAKER_00 (02:16):
Because your biological age is what actually
measures the physical wear andtear on your systems.
SPEAKER_01 (02:20):
Exactly.
But the Stanford team didn'tjust prove that we age
differently from one another,they proved that our bodies do
not even age in unison withthemselves.
SPEAKER_00 (02:28):
And the philosophical shift here, you
know, it really cannot beoverstated.
SPEAKER_01 (02:32):
It's massive.
SPEAKER_00 (02:33):
It is.
I mean, medicine has relied onchronological age for centuries,
simply because it's a binary,easily verifiable fact.
You were born in this year, soyou are this old.
SPEAKER_01 (02:43):
Right.
It's easy math.
SPEAKER_00 (02:45):
Yeah.
But biological age is cryptic.
It is this hidden metric of yourtrue likelihood of developing
aging-associated disorders.
And what Waste Corey's teammanaged to do is, well, they
shattered the whole concept of aunified self.
SPEAKER_01 (02:59):
The unified self, meaning like I am a 45-year-old
person across the board.
SPEAKER_00 (03:03):
Exactly.
You aren't just a 45-year-oldperson.
You are a walking collective of11 distinct organ systems.
And this team developed a methodto look into the blood and
actually assign an individualage to every single one of them.
SPEAKER_01 (03:18):
Okay, let's unpack this.
Because the idea that my livercould be, I don't know, an
entirely different age than mylungs is really difficult to
visualize.
SPEAKER_00 (03:26):
It was a weird concept, yeah.
SPEAKER_01 (03:28):
It makes me think of um buying a vintage car.
SPEAKER_00 (03:32):
Okay, I like where this is going.
SPEAKER_01 (03:33):
So yeah, say you buy a classic 1974 muscle car.
The chassis, the metal frame, is50 years old.
That is the chronological age.
Right.
But over the lifespan of thatcar, the previous owner swapped
out the transmission.
So that part is only 30 yearsold.
SPEAKER_00 (03:47):
Ah, I see.
SPEAKER_01 (03:48):
However, they drove the car incredibly hard, you
know, rode the brakes down steephills, and never replaced the
brake pads.
So those brake pads have enduredthe friction and thermal stress
of an 80-year-old component.
SPEAKER_00 (03:59):
Yeah, that's spot on.
SPEAKER_01 (04:00):
So my body is that car made of parts aging at
wildly different speeds.
SPEAKER_00 (04:05):
That analogy works beautifully.
But um, we have to take it astep further to really
understand the biology here.
SPEAKER_01 (04:11):
Okay, lay it on me.
SPEAKER_00 (04:12):
It's not just that the brake pads are worn down,
it's that as they wear down,they are actively shedding
metallic dust and like chemicalexhaust into the oil stream of
the car.
SPEAKER_01 (04:22):
Oh, wow.
Okay.
SPEAKER_00 (04:24):
And the Stanford researchers mapped this concept
across 11 specific systems.
So we're talking about thebrain, muscle, heart, lung,
arteries, liver, kidneys,pancreas, immune system,
intestine, and fat.
SPEAKER_01 (04:38):
Wait, I need to pause on that list for a second.
Fat.
SPEAKER_00 (04:39):
Yeah, fat.
SPEAKER_01 (04:40):
Fat is considered one of the eleven independently
aging organ systems.
I mean, I think most people viewfat as just like inert storage.
Like a biological backpack wejust carry around.
SPEAKER_00 (04:50):
That is a very common misconception.
But adipose tissue, which iswhat fat is, is actually a
massive, highly active endocrineorgan.
SPEAKER_01 (04:59):
Wait, really?
It's an organ.
SPEAKER_00 (05:00):
Oh, absolutely.
It doesn't just sit there, itconstantly secretes hormones
known as adipokines, and itinteracts with your entire
metabolic system.
It talks to your immune responseand your cardiovascular network.
SPEAKER_01 (05:10):
I had no idea it was that involved.
SPEAKER_00 (05:12):
Yeah, and as adipose tissue ages, it becomes
dysfunctional.
It stops storing lipidsefficiently and starts secreting
these pro-inflammatorymolecules.
So the biological age of yourfat is incredibly relevant to
your overall systemic health.
SPEAKER_01 (05:26):
That completely changes the context of what it
means to be healthy.
SPEAKER_00 (05:29):
It really does.
SPEAKER_01 (05:30):
Because I mean, you could be someone who eats well,
maintains a decent outwardappearance, and just assumes
everything is fine.
You know, you were 50 years old,but inside your heart has
endured the biological stress ofa 75-year-old.
SPEAKER_00 (05:42):
Exactly.
SPEAKER_01 (05:43):
Meanwhile, your immune system might be operating
with the cellular vitality of a30-year-old.
It just makes the concept of anannual physical where they just
take your blood pressure and askhow you feel seem almost
primitive.
SPEAKER_00 (05:55):
Well, it is primitive.
SPEAKER_01 (05:56):
Yeah.
SPEAKER_00 (05:57):
Historically, because we couldn't measure
localized biological aging, wejust treated the body as a
single entity in decline.
SPEAKER_01 (06:04):
Like it all goes downhill together.
SPEAKER_00 (06:06):
Right.
The assumption in a standardmedical clinic is that if you
present as generally robust,well then your internal systems
are uniformly robust.
If you are frail, you are fraileverywhere.
SPEAKER_01 (06:17):
But this study says that's flat out wrong.
SPEAKER_00 (06:19):
Completely wrong.
This research proves that agingis intensely localized.
Your lungs could be undergoingaccelerated, dangerous
senescence.
SPEAKER_01 (06:28):
And senescence is like cellular deterioration.
SPEAKER_00 (06:32):
Aaron Ross Powell Exactly.
And maybe that's due to acombination of genetic
susceptibility and, say, a briefperiod of living in a city with
high particulate air pollution adecade ago.
SPEAKER_01 (06:42):
Oh, interesting.
SPEAKER_00 (06:43):
Right.
So your lungs are old while yourkidneys might remain completely
pristine.
SPEAKER_01 (06:48):
Aaron Powell Okay, but I keep getting stuck on the
mechanics of how you actuallygather that data.
SPEAKER_00 (06:52):
Aaron Powell The methodology.
SPEAKER_01 (06:53):
Right.
Because knowing that the body isa collection of separately aging
parts is a great theory.
But you can't just pop the hoodand inspect a living human's
pancreas to see how much wearand tear it has.
SPEAKER_00 (07:04):
No, definitely not.
SPEAKER_01 (07:06):
So how do they actually prove this in living
people without cutting themopen?
SPEAKER_00 (07:10):
Aaron Ross Powell Well, they turn to one of the
most powerful scientificresources on the planet, which
is the UK Biobank.
SPEAKER_01 (07:15):
Okay, I've heard of that.
SPEAKER_00 (07:16):
Yeah, to prove a paradigm shift like this, you
need a staggering amount of dataover a very long horizon.
And the UK Biobank is thislongitudinal study that has
gathered biological samples anddeep medical records from
roughly half a millionindividuals.
SPEAKER_01 (07:31):
Aaron Powell Okay, and a longitudinal study,
meaning they don't just take asnapshot of someone on a Tuesday
and send them home.
They follow them through time.
SPEAKER_00 (07:38):
Correct.
So for this specific analysis,the Stanford team filtered that
massive database down to exactly44,498 randomly selected
participants.
SPEAKER_01 (07:49):
Aaron Powell Wow, almost 45,000 people.
SPEAKER_00 (07:52):
Yeah.
All between the ages of 40 and70.
And these individuals didn'tjust give one blood sample, they
had multiple samples taken overthe course of up to 17 years.
SPEAKER_01 (08:00):
17 years?
That is a massive commitment.
SPEAKER_00 (08:03):
It is.
The researchers had access tothis continuous feed of updated
medical reports.
They could watch in real timethe evolution of these people's
health status.
Trevor Burrus, Jr.
SPEAKER_01 (08:12):
So they were documenting who developed
chronic diseases and whoultimately died.
Following almost 45,000 peoplefor up to 17 years is a
monumental logisticalachievement.
SPEAKER_00 (08:21):
Unprecedented, really.
SPEAKER_01 (08:23):
But um, I have a serious logistical question
about the testing itself.
You mentioned looking into theblood.
Right.
If a phonotomist pulls a vial ofblood from a vein in my arm,
that blood has been circulatingeverywhere.
Right.
It's a systemic fluid.
SPEAKER_00 (08:38):
It goes everywhere, yes.
SPEAKER_01 (08:39):
Aaron Powell So how on earth do you isolate the
biological age of the intestineor the brain from this totally
random mixture of blood?
SPEAKER_00 (08:47):
Well, to understand that, we really have to look at
what blood actually is.
I mean, it isn't just red andwhite blood cells floating
around in some neutral plasma.
SPEAKER_01 (08:55):
There's more to it than just that.
SPEAKER_00 (08:56):
Exactly.
Blood is actually this vastsuperhighway of molecular
information because, you know,every organ in your body is
constantly undergoing cellularturnover.
Cells are born, they function,they get damaged, and then they
die.
SPEAKER_01 (09:11):
Okay, so it's a constant cycle.
SPEAKER_00 (09:13):
Yeah.
And during this entire lifecycle, organs are just
constantly shedding proteinsinto your bloodstream.
So Weissquarry's team utilizedhighly advanced commercial
technology to detect and countthe concentrations of nearly
3,000 different proteins in theblood of these participants.
SPEAKER_01 (09:28):
Wait, capturing 3,000 distinct proteins from a
single blood draw?
That sounds like finding needlesin a microscopic haystack.
SPEAKER_00 (09:37):
It's incredibly precise.
SPEAKER_01 (09:38):
But even if you can count them, how does that tell
you where they came from?
A protein is a protein, isn'tit?
SPEAKER_00 (09:43):
Actually, it's not.
And this is the crucialbiological mechanism that
underpins the entire study.
Okay.
What's fascinating here istissue-specific gene expression.
This means that a liver cellfunctions entirely differently
than a heart cell.
And because they performcompletely different jobs and
manufacture completely differentproteins.
SPEAKER_01 (10:02):
Oh, I see.
SPEAKER_00 (10:02):
Yeah.
So out of the 3,000 proteins theresearchers analyzed, they
discovered that roughly 15% ofthem could be traced back to
single organ origins.
SPEAKER_01 (10:12):
Ah, okay.
This brings us back to thevintage car analogy.
Yeah.
Specifically, the oil check.
SPEAKER_00 (10:18):
Yes.
Let's go back to that.
SPEAKER_01 (10:19):
Right.
So if a mechanic pulls thedipstick out of your engine and
analyzes the oil, they aren'tjust looking at the color.
If they find very specific typesof, say, brass shavings in the
oil, they know exactly whichsynchretizer ring in the
transmission is grinding down.
Because those specific brassshavings can only logically
originate from that single gear.
SPEAKER_00 (10:40):
That is an exceptionally precise way to
visualize it.
When the researchers see aspecific concentration of a
particular protein, they knowwith absolute certainty that it
originated in, say, the leftventricle of the heart.
Wow.
Right.
If they detect a differentprotein, it is uniquely tied to
the pulmonary tissue in thelung.
So while 85% of the proteinsthey tracked are shared across
(11:03):
multiple systems, that specific15% of single organ proteins
gave them a direct, uncorruptedchemical window into the
distinct status of those 11specific organs.
SPEAKER_01 (11:15):
Aaron Powell That is mind-blowing.
So they have a vial of blood,they identify the single organ
proteins, and they measure theconcentrations.
But um, how does knowing theamount of a protein tell you the
age of the organ?
SPEAKER_00 (11:26):
Good question.
SPEAKER_01 (11:27):
Because I imagine you don't just put a lung
protein under an electronmicroscope and count its rings
like a tree stump.
SPEAKER_00 (11:32):
No, no.
The proteins themselves aren'twhat is old.
I mean, a protein synthesizedyesterday by a 70-year-old liver
is technically a brand newprotein.
SPEAKER_01 (11:39):
Okay, that makes sense.
SPEAKER_00 (11:40):
What changes is the pattern of proteins being
secreted.
As an organ ages, its cellularmachinery degrades.
You get these senescent cells,cells that have basically
stopped dividing but refuse todie and they begin to
accumulate.
SPEAKER_01 (11:55):
Like zombie cells.
SPEAKER_00 (11:56):
Exactly like zombie cells.
And these senescent cellssecrete a very specific toxic
cocktail of inflammatoryproteins.
Additionally, as the tissuestructure breaks down,
intracellular proteins thatshould absolutely remain inside
the organ start to leak into theblood.
So the researchers aren'tlooking for old proteins,
they're looking for the shiftingconcentration profile of
(12:18):
proteins that indicates an organis deteriorating.
SPEAKER_01 (12:21):
Okay, that makes total sense.
It's the signature of theenvironment, not the age of the
individual molecule.
SPEAKER_00 (12:26):
Exactly.
SPEAKER_01 (12:27):
But how do you establish what a normal
signature is?
Like how do they know what thebaseline looks like?
SPEAKER_00 (12:31):
That is where the sheer computing power comes in.
Because they had over 44,000people, they could feed all
those protein levels into amachine learning algorithm.
Oh wow.
Yeah.
The computer analyzed everysingle participant and
established an age-adjustedbaseline.
So it calculated exactly whatthe average healthy mixture of
heart proteins looks like in theblood of a 50-year-old, a
(12:52):
51-year-old, a 52-year-old, andso on.
SPEAKER_01 (12:54):
So they basically built this massive biological
fingerprint catalog.
SPEAKER_00 (12:58):
Precisely.
And once the algorithmestablishes that baseline
fingerprint for everychronological age, the testing
becomes highly individualized.
Right.
You can take a new blood samplefrom a 45-year-old patient,
isolate the proteins, and askthe algorithm, hey, how much
does this individual's kidneyprotein signature deviate from
our baseline of a healthy45-year-old kidney?
SPEAKER_01 (13:19):
Okay, so if my protein signature perfectly
matches the algorithm's averagefor a 45-year-old, my kidney and
I are aging perfectly in sync.
SPEAKER_00 (13:27):
Yes.
Your biological age for thatspecific organ matches your
chronological age.
The clinical value, however, isin the deviations.
SPEAKER_01 (13:35):
When things don't line up.
SPEAKER_00 (13:36):
Right.
These organ-specific proteinsignatures act as highly
sensitive proxies for thephysical state of the organ.
SPEAKER_01 (13:42):
So let's talk about those deviations.
Because the study didn't justfind people whose organs were
like a few months ahead orbehind schedule.
They were looking for extremeoutliers.
SPEAKER_00 (13:53):
They were.
In any vast data set, mostpeople kind of cluster around
the average.
So to identify true dangerousdivergence, the researchers set
a strict mathematical threshold.
Which was a 1.5 standarddeviation from the age-adjusted
mean.
If your organ's proteinsignature crossed that
threshold, it wasn't just aginga little fast, it fell into the
(14:14):
extremely aged category.
SPEAKER_01 (14:16):
And the reverse is true too, right?
SPEAKER_00 (14:18):
Yes.
Crossing the threshold in theother direction placed the organ
in the extremely youthfulcategory.
SPEAKER_01 (14:24):
Okay, and when they applied that 1.5 standard
deviation threshold to those44,000 people, the results were
incredibly alarming.
I mean, one-third of theindividuals in this study had at
least one organ that was agingat an extreme, highly
accelerated rate compared to therest of their body.
SPEAKER_00 (14:39):
One in three.
It completely dispels the myththat accelerated aging is this
rare condition reserved for thevisibly frail.
SPEAKER_01 (14:46):
It actually gets much more severe than that,
though.
One in four participants, 25% ofthe people walking around in
this study had multiple,extremely aged or youthful
organs.
SPEAKER_00 (14:58):
Yeah, the multiple organ divergence is the really
scary part.
SPEAKER_01 (15:01):
Think about the implications of that for a
moment.
If you are sitting in aconference room right now with
three co-workers, the statisticsdictate that at least one of you
has a rogue organ sprintingtoward failure, completely out
of sync with your chronologicalage.
Right.
One out of every four people inthat room has multiple organs
doing it.
You could be sitting next tosomeone whose liver is
(15:23):
biologically 20 years older thanthey are, and neither they nor
their doctor has any idea.
SPEAKER_00 (15:28):
And that silent divergence is the most dangerous
aspect of human health.
An extremely aged organ isbasically a ticking clock.
SPEAKER_01 (15:35):
Because it's a weak link.
SPEAKER_00 (15:36):
Exactly.
It represents a localizedvulnerability that standard
metabolic panels and annualcheckups are completely blind
to.
A standard blood test looks forfunctional failure.
You know, it tells you when theorgan has already broken.
SPEAKER_01 (15:48):
Like your enzymes are off the charts.
SPEAKER_00 (15:50):
Right.
But this protein algorithm looksfor the structural degradation
that occurs years before thefailure ever actually happens.
SPEAKER_01 (15:59):
Now, while having an old liver or an old intestine is
obviously a massive health risk,the Stanford team found a
hierarchy within these 11systems.
And here's where it gets reallyinteresting.
SPEAKER_00 (16:10):
Yes, it really does.
SPEAKER_01 (16:11):
Because not all organs carry the same weight
when it comes to keeping thehuman body alive.
SPEAKER_00 (16:15):
They definitely do not.
When the researchers analyzedthe mortality data over that
15-year monitoring period, oneorgan separated itself entirely
from the pack.
Dr.
Weiss Corey explicitly labeledthe brain as the gatekeeper of
longevity.
SPEAKER_01 (16:31):
The gatekeeper of longevity.
That implies that the braindoesn't just, you know, manage
its own health, but activelydictates the survival of the
entire organism.
SPEAKER_00 (16:40):
The data supports that conclusion overwhelmingly.
They cross-reference thebiological ages of the 11 organs
against the all-cause mortalityof the participants.
And the numbers are staggering.
SPEAKER_01 (16:50):
Let's hear them.
SPEAKER_00 (16:51):
Having an extremely aged brain, meaning crossing
that 1.5 standard deviationthreshold into accelerated
aging, increases a subject'srisk of dying by 182%.
SPEAKER_01 (17:03):
Wait, a 182% increase in the risk of
mortality?
SPEAKER_00 (17:07):
Yes.
SPEAKER_01 (17:07):
The odds of you dying almost triple simply
because this single organ'sprotein signature is reading
older than your chronologicalage.
SPEAKER_00 (17:15):
And the protection offered by the opposite extreme
is equally potent.
Individuals whose bloodindicated an extremely youthful
brain experience a 40% reductionin their overall risk of dying
over that same 15-year window.
SPEAKER_01 (17:27):
So a young brain slashes your mortality risk
almost at half, and an old brainnearly triples it.
SPEAKER_00 (17:33):
Exactly.
SPEAKER_01 (17:34):
But how large is the demographic we are talking about
at these extremes?
Like, is half the populationwalking around with a
biologically old brain?
SPEAKER_00 (17:40):
No, no.
Because of that strict 1.5standard deviation threshold,
the extremes are relativelyexclusive.
The extremely aged brains madeup only six to seven percent of
the total study participants.
SPEAKER_01 (17:50):
Okay, so a small slice.
SPEAKER_00 (17:52):
Right.
Those are the individuals whoseprotein signatures fell at the
absolute worst end of thedistribution.
The extremely youthful brainsaccounted for another six to
seven percent at the highlyoptimized end of the spectrum.
SPEAKER_01 (18:05):
Aaron Powell I want to push back on the philosophy
of the brain as the ultimategatekeeper for a second.
Sure.
Because I understand that thebrain is essential, obviously.
But if my heart stops beating, Idie instantly.
If my lungs stop processingoxygen, I die.
Why does the brain specificallyexert such a disproportionate
gravitational pull on overallmortality?
SPEAKER_00 (18:26):
Well, it requires looking at the body as an
integrated network rather thanlike isolated silos.
The brain does not simply sit inthe skull and think.
Right.
It is the central command centerfor the autonomic nervous system
and the neuroendocrine system.
Through the hypothalamus and thepituitary gland, the brain
regulates systemic inflammation.
It manages your metabolic rate,it dictates the release of
(18:47):
stress hormones like cortisol.
SPEAKER_01 (18:49):
So it's pulling all the levers.
SPEAKER_00 (18:51):
Exactly.
It even controls the vagusnerve, which directly influences
your heart rate and gutmotility.
So if the brain undergoesaccelerated aging, its
regulatory signaling degrades.
An aged brain might uminappropriately signal systemic
inflammation, which thenactively damages the heart, the
blood vessels, and the kidneys.
SPEAKER_01 (19:12):
Wow.
So an aging brain doesn't justfail in isolation.
It literally drags the rest ofthe organs down with it by
sending chaotic degradingsignals.
SPEAKER_00 (19:20):
Furthermore, we really cannot ignore the
behavioral component.
SPEAKER_01 (19:23):
Oh, true.
SPEAKER_00 (19:24):
An aging brain leads to cognitive decline, which
changes how a person interactswith their environment.
It can lead to poor dietarychoices, a reduction of physical
movement, disrupted sleeparchitecture, or even just the
inability to manage medications.
SPEAKER_01 (19:36):
All of which compound mortality risks
rapidly.
SPEAKER_00 (19:39):
Absolutely.
When the Stanford researcherslooked at the raw predictive
power, brain age was the singlemost accurate predictor of
mortality out of every organthey tested.
SPEAKER_01 (19:47):
Aaron Powell But you know, mortality is the final
step.
People rarely just drop deadstrictly from an old brain
without a preceding clinicalevent.
Before mortality, there isdisease.
How accurately can this proteinalgorithm predict the specific
illnesses a person will develop?
SPEAKER_00 (20:03):
This is where the algorithm transitions from a
theoretical measurement of agingto a highly practical clinical
tool.
The researchers tracked 15 majorchronic disorders across the
cohort over those 17 years.
SPEAKER_01 (20:15):
What kind of disorders are we talking about?
SPEAKER_00 (20:17):
We are talking about the diseases that fundamentally
define human aging (20:19):
Alzheimer's, Parkinson's, chronic liver
disease, chronic kidney disease,type 2 diabetes, atrial
fibrillation, heart failure,chronic obstructive pulmonary
disease, rheumatoid arthritis,osteoarthritis, and several
others.
SPEAKER_01 (20:36):
So they took the biological age of the eleven
organs and mapped them againstwho developed those 15 diseases.
What did that web of connectionslook like?
SPEAKER_00 (20:44):
Well, the associations weren't a messy
overlapping rabit all.
What emerged was a remarkablyclear one-to-one correlation.
One-to-one.
Yes.
An aged organ perfectlypredicted a future disease
associated exclusively with thatspecific organ.
SPEAKER_01 (20:59):
Give me an example of how that plays out in the
data.
SPEAKER_00 (21:01):
Okay, so if the blood test revealed an extremely
aged heart protein signature,that specific finding strongly
predicted a high risk of thepatient developing atrial
fibrillation or heart failure inthe years that followed.
Okay.
If the blood test showedextremely aged lungs, it
predicted a heightened risk ofdeveloping COPD.
The localized biological ageacted as this specific localized
(21:24):
crystal ball.
SPEAKER_01 (21:25):
That makes perfect sense mechanically.
The tissue degrades, it shedsexhaust into the blood, the
algorithm flags the aged organ,and then years later, the
clinical symptoms of thatspecific organ's failure finally
appear.
SPEAKER_00 (21:37):
Exactly right.
SPEAKER_01 (21:38):
But the most terrifying disease on that list
of 15 is Alzheimer's.
Let's look at the Alzheimer'sdata, because the math here is
the most powerful association inthe entire study.
SPEAKER_00 (21:47):
The predictive correlation between biological
brain age and Alzheimer'sdisease is truly profound.
If an individual falls into thatsix to seven percent demographic
with an extremely aged brain,their risk of developing
Alzheimer's Alzheimer's is 3.1times higher than a person whose
brain is aging normally.
SPEAKER_01 (22:04):
So you literally triple your risk of Alzheimer's
just by crossing into that agedthreshold.
SPEAKER_00 (22:09):
Yes.
SPEAKER_01 (22:09):
But what happens on the protective side?
What about the six to sevenpercent with the extremely
useful brains?
SPEAKER_00 (22:15):
The protection is immense.
For those with an extremelyyouthful brain, their risk of
developing Alzheimer's is only0.25 times the risk of a person
with a normally aged brain.
SPEAKER_01 (22:26):
Wait, really?
SPEAKER_00 (22:27):
Yeah, their risk is slashed to barely one-fourth of
the baseline.
SPEAKER_01 (22:31):
What's fascinating here is what happens when you
synthesize those two extremes.
Let's lay this out clearly,because this is kind of the
pivot point of the entire deepdive.
Let's do it.
You have the biologically oldbrains carrying a 3.1x risk
multiplier.
You have the biologically youngbrains carrying a 0.25x risk
multiplier.
If you contrast someone at thetop of that curve with someone
(22:52):
at the bottom, it means anindividual with a biologically
old brain is approximately 12times as likely to be diagnosed
with Alzheimer's over the nextdecade as someone the exact same
chronological age with abiologically young brain.
SPEAKER_00 (23:05):
12 times the risk.
It is an astronomical delta.
And what is vital to understandis that this prediction is made
entirely by analyzing invisibleproteins floating in a vial of
blood years, potentially a fulldecade before the patient ever
experiences a single clinicalsymptom of memory loss.
SPEAKER_01 (23:24):
That level of foresight changes everything.
I mean, imagine two 55-year-oldindividuals walking into a
clinic.
From the outside, they lookidentical.
They might even score exactlythe same on a standard cognitive
memory test that day.
SPEAKER_00 (23:37):
Right, they pass with flying colors.
SPEAKER_01 (23:38):
Exactly.
A neurologist would tell both ofthem they are perfectly healthy.
But this Stanford blood test canlook 10 years into their
biological future anddefinitively state that patient
A has a 12fold higherprobability of developing
Alzheimer's than patient B.
SPEAKER_00 (23:54):
And if we connect this to the bigger picture, this
capability forces the completedismantling of our current
medical framework.
unknown (24:00):
Dr.
SPEAKER_00 (24:00):
Weiss Corrier articulated this perfectly.
He pointed out that modernmedicine does not actually
practice health care.
We practice sick care.
SPEAKER_01 (24:07):
Oh, I think anyone who has ever navigated the
medical system deeplyunderstands that distinction.
SPEAKER_00 (24:12):
Right.
In a sick care model, the entiresystem is reactionary.
You do not seek interventionuntil something is broken.
You wait until you feel atightness in your chest, or you
develop a chronic, painfulcough, or you realize you cannot
remember how to drive home fromthe grocery store.
SPEAKER_01 (24:30):
And only then do you go to a physician?
SPEAKER_00 (24:33):
Only then.
And they just run tests toconfirm the damage that has
already occurred.
SPEAKER_01 (24:37):
It's the equivalent of waiting for the engine block
to crack on the highway beforeyou pull over and check the oil.
You are literally waiting forcatastrophic failure before
initiating maintenance.
SPEAKER_00 (24:47):
Exactly.
And with neurodegenerativeconditions like Alzheimer's, the
sick care model is utterlydevastating.
By the time outward symptomsappear, by the time a patient is
failing memory tests, thephysical decay of the neural
networks is already extensive.
SPEAKER_01 (25:03):
The damage is done.
SPEAKER_00 (25:04):
Millions of neurons have already died.
The structural damage is largelyirreversible, which is exactly
why Alzheimer's drug trials havehistorically had such a dismal
success rate.
We are trying to put out a fireafter the house has already
burned down.
SPEAKER_01 (25:17):
But if we deploy this 11-organ blood test, we
shift the paradigm to truehealthcare.
SPEAKER_00 (25:22):
True healthcare is proactive intervention before
the manifestation of symptoms.
If a 50-year-old takes thisblood test and discovers their
brain is biologically 65, thatextreme brain age serves as a
biological proxy for impendingAlzheimer's.
SPEAKER_01 (25:37):
So they have a head start.
SPEAKER_00 (25:38):
Exactly.
The physician can initiateaggressive interventions,
whether pharmacological,dietary, or lifestyle-based,
while the brain's structuralintegrity is still intact.
We are detecting the smolderingembers instead of the inferno.
SPEAKER_01 (25:51):
Aaron Powell That fundamentally alters the
timeline of human longevity.
Yeah.
But um it also raises a massivequestion about how we figure out
which interventions actuallywork.
SPEAKER_00 (26:00):
What do you mean?
SPEAKER_01 (26:01):
Well, right now, if I want to know if a specific
diet or a new longevity compoundprotects the brain, the clinical
trial process is excruciatinglyslow.
Researchers have to putthousands of people on a
protocol and then just sit backand wait 20 years to see who
gets dementia and who dies.
SPEAKER_00 (26:16):
Aaron Powell Yeah, the sheer length of traditional
clinical trials is the primarybottleneck in longevity
research.
It is incredibly inefficient andoverwhelmingly expensive.
However, this organ-agingalgorithm provides a
revolutionary shortcut.
SPEAKER_01 (26:29):
How so?
SPEAKER_00 (26:30):
Because the protein signatures in the blood change
as the tissue environmentchanges, the feedback loop
becomes incredibly tight.
SPEAKER_01 (26:37):
So instead of waiting for a patient to develop
a disease or pass away, you canuse the protein signatures as
like a real-time trackingdashboard.
SPEAKER_00 (26:45):
Precisely.
In a modern clinical trial,scientists will test a patient's
blood on day one to establishthe biological age of their 11
organs.
Then they implement theintervention.
Maybe it's a new synolytic drugdesigned to clear out senescent
cells or a rigorouscardiovascular exercise
protocol.
Six months later, they draw theblood again.
They do not have to wait adecade to see if the patient
(27:07):
survives.
They simply look to see if theprotein exhaust has shifted.
SPEAKER_01 (27:10):
They can literally watch the biological clock
rewind in the data.
Yes.
They can definitively prove inreal time if a specific
intervention actually restoresorgan youth.
SPEAKER_00 (27:20):
It replaces guesswork with granular,
organ-specific data.
We'll be able to answerincredibly nuanced questions
very quickly.
Does this specific class ofstatin lower the biological age
of the arteries or does it onlymask cholesterol numbers?
Right.
Does a sustained ketogenic dietgenuinely reverse the aging
signature of the brain?
(27:40):
The speed of scientificdiscovery will accelerate
exponentially.
SPEAKER_01 (27:44):
Which naturally leads to the question every
single person listening isasking right now.
SPEAKER_00 (27:48):
I can guess what it is.
SPEAKER_01 (27:49):
This is groundbreaking science, but is
it trapped in a Stanfordlaboratory forever, or is it
going to see the light of day?
When can an average personactually get this blood test?
SPEAKER_00 (27:59):
Aaron Powell It is rapidly moving out of the
laboratory.
Dr.
Weisscore is activelyspearheading commercialization.
He has already co-founded twoseparate companies, TLOMics and
Virobioscience, with theexplicit goal of bringing this
diagnostic technology to thepublic market.
SPEAKER_01 (28:13):
Aaron Powell Usually when we cover experimental
medical technology, the timelineis accompanied by a heavy caveat
of, you know, maybe in a decadeif it passes phase three trials.
What is the realistic timelinefor TL omics or virobioscience?
Aaron Powell Dr.
SPEAKER_00 (28:26):
Weiss Corey has publicly stated that this test
could be available to consumersin the next two to three years.
SPEAKER_01 (28:31):
Two to three years.
In the realm of medicaldiagnostics, that is practically
tomorrow morning.
SPEAKER_00 (28:37):
The timeline is aggressive, but it is supported
by the immense credibility ofthe institutions involved.
I mean, this research wasn'tconducted in a vacuum, it was
funded by heavyweights.
We're talking massive grantsfrom the National Institutes of
Health, the Milky WayFoundation, the Knight
Initiative for Brain Resilience,and the Stanford Alzheimer's
(28:58):
Disease Research Center.
SPEAKER_01 (28:59):
So the money is there.
SPEAKER_00 (29:00):
The financial and institutional momentum required
to push this into the commercialsphere is fully secured.
SPEAKER_01 (29:06):
But let's talk about the practical reality of scaling
this up.
Analyzing 3,000 distinctproteins using mass spectrometry
or advanced of tamer arrayssounds incredibly resource
intensive.
SPEAKER_00 (29:17):
It is.
SPEAKER_01 (29:18):
So is this going to be a boutique diagnostic that
only tech billionaires canafford, or will it actually be
accessible to the generalpublic?
SPEAKER_00 (29:25):
Cost is undeniably the primary hurdle for mass
commercialization.
To solve this, the researchersare refining the scope of the
consumer test.
The initial commercial rolloutwill likely not map all 11
organs simultaneously.
Okay.
To drastically reduce the cost,they plan to focus on a highly
targeted panel of the organsthat exhibit the strongest
(29:46):
predictive links to majormortality drivers.
Specifically, the commercialtest will likely focus on just
three systems the brain, theheart, and the immune system.
SPEAKER_01 (29:56):
Strategically, that makes perfect sense.
You have the brain, which is theultimate gatekeeper of
longevity, you have the heart,which is the mechanical engine
responsible for vast amounts ofsudden mortality.
Right.
And you have the immune system,which is the defense network
responsible for managingsystemic inflammation and
clearing out damaged cells.
If I can get high resolutiondata on those three systems for
a few hundred dollars, that is amap of my biological future.
SPEAKER_00 (30:19):
Exactly.
By filtering out the noise ofthe other 2,000 plus proteins
and focusing solely on thespecific markers for those three
critical systems, they canincrease the diagnostic
resolution while democratizingthe price point.
SPEAKER_01 (30:32):
That's brilliant.
SPEAKER_00 (30:33):
It transforms the technology from a luxury
biohacking tool into a routinestaple of preventative primary
care.
SPEAKER_01 (30:40):
It is truly staggering to think about the
journey of discovery we justwalked through.
For our entire lives, we havebeen conditioned to view our
chronological age as this rigid,inescapable definition of who we
are.
SPEAKER_00 (30:53):
Yeah, a number we can't escape.
SPEAKER_01 (30:54):
But the reality inside our bodies is far more
complex and ultimately far morehopeful.
Your chronological age isnothing more than a superficial
suggestion.
Beneath the surface, you are acomplex ecosystem running on
eleven distinct hiddenbiological clocks.
SPEAKER_00 (31:10):
That's a great way to summarize it.
SPEAKER_01 (31:11):
Your liver, your lungs, your adipose tissue, your
brain, they are all travelingthrough time at different
velocities, shedding theirunique protein exhaust into your
bloodstream.
And by reading that exhaust, wecan perfectly predict localized
health risks a full decadebefore a single symptom emerges.
SPEAKER_00 (31:31):
And you know, the most valuable aspect of this
deep dive is what it allows usto do next.
Knowledge of this magnitude isonly useful when it is applied.
Right.
Understanding that our organsage independently provides us
with unprecedented agency.
We are no longer blindpassengers just waiting for an
inevitable breakdown.
SPEAKER_01 (31:49):
We can do something about it.
SPEAKER_00 (31:50):
We have the capability to build a dashboard.
We can identify the precisebiological vulnerabilities
within our own bodies andintervene strategically.
We can specifically protect ourindividual gatekeepers of
longevity before the damage isdone.
SPEAKER_01 (32:03):
It fundamentally shifts the power dynamic of
human aging.
But um, I want to leave you witha final thought to mull over as
you step away from this deepdive today.
SPEAKER_00 (32:10):
Let's hear it.
SPEAKER_01 (32:11):
We just established that this test will likely hit
the commercial market in thenext two to three years.
Soon you will have the abilityto walk into a clinic, give a
simple vial of blood, andreceive an incredibly accurate
projection of exactly when yourbrain or your heart is scheduled
to fail.
SPEAKER_00 (32:27):
It's a heavy thought.
SPEAKER_01 (32:29):
You can access a definitive biological timer for
your most vital organs yearsbefore you experience a single
physical ache or a momentaryslip in memory.
So if that test becomesavailable to you tomorrow, would
you actually want to take it?
Would you want to know theprecise speed at which your
brain is aging?
And more importantly, if youreceive that data and realized
(32:51):
your biological clock wasrunning far faster than you
thought, how would that singleterrifying piece of knowledge
change the exact way you chooseto live your life tomorrow
morning?
Thank you for joining us on thisdeep dive into the hidden clocks
inside us all.
SPEAKER_00 (33:06):
It has been a privilege exploring the future
of medicine with you.
Keep questioning the biologicalrules we take for granted.
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