Personality Basins

Personality basins are the mental model that I use to reason about humans within their environment. They are an elucidating way to think about many concepts: from modelling why people are they way they are, how they change over time, how mental illnesses and addiction function along with how we should look for their cures, and how the attention economy optimizes itself to consume all of your free time.

What is personality?

Your personality is formed by a process conceptually similar to RLHF. You are first born with a set of traits in a given environment. After this, you perform many interactions with your environment. If an interaction goes well, you’re likely to do it more often, and if it goes poorly, you’ll probably do less of it.

See the learning agent? That’s You!
If your interaction with this post goes well, you’re likely to read more of them later.

If you were born tall and with a commanding voice you might find that you get what you want by confidently demanding it, and this will help to result in a confident personality. If you attempt this strategy as someone born small with a soft voice, it will probably have weaker results and encourage you to try something else out instead. Obviously some traits are more genetic, and thus inherent, than others, but that is not the scope of this post as even highly-heritable traits will result in a large distribution of outcomes.

Periods of high social and environmental entropy during adolescence are the most formative because you will learn the most information about which actions perform well in your environment and which don’t (of course, our meta-learning algorithm knows this, and this is why you have higher neuroplasticity and thus a higher learning rate and more energy during this period. It’s time to learn how to succeed in your newfound environment!)

Your personality basin

As you go about your life, you will continue to modify your personality in response to your environment, and eventually you will end up in something that resembles a basin. Maybe you were born tall and attractive and then this led you to engage in a lot of athletic activities and socialization, and at the end of all of the positive feedback you have ended up with a jock personality that goes on to become a professional football player.

This is a landscape of personalities. The black line is your personality over time, and the last point is the person you currently are. Just like in machine learning, the way that you’ve progressed as a person has been by trying out many things and then doing more of the things that worked well.

If instead you grew up scrawny yet intelligent you might have found things go well for you when you adopt a more quiet persona and focus on solving technical problems in programming or mathematics, perhaps eventually leading to a career as a software engineer or academic. Just like training a model in machine learning, the general gist is that you will try out a lot of things and then do more of the things that went well.

The above image is of a loss landscape in machine learning. Since we are discussing personality, all of the points on the landscape represent different personalities you could have, with the lower points being personalities which are more successful. The personality basin that you find yourself in solidifies over time as you find out who you are and choose your friend group, career path, social and aesthetic preferences, and more.

Most personality changes are unconscious

Most of your movement within personality-space happens outside of your conscious awareness. Although there are many times in life you’ll consciously decide to act in a certain way, this is the exception, not the norm. Your brain is always making millions of gradient updates a day based on what is and isn’t going well and often the most you can do is try to be as observant as possible. This is why techniques like nonviolent communication, dialectical behavior therapy, and mindfulness have observation and introspection as a core facet, because it’s something that you have to consciously practice to become good at rather than something you’re born with.

Most addictive behaviors start without us noticing what is happening until we are sufficiently addicted such that the habit is hard to break. Relatedly, if you introspect on many seemingly-innate preferences you will often notice some of the environmental and social gradients that have helped shape them. An interesting thought experiment you can perform on yourself is to pick a random personality trait that you have and try to answer the questions “why am I like this? could I imagine a version of myself that is not like this, and if so, what happened differently to them?”

Many people think their music and fashion preferences are innate to them and are solely based off of how the music sounds and how the outfits look. But if their most hated political party (or often in the case of adolescents, their parents) adopted the same aesthetic preferences, you can imagine they might start to literally like them less!

Your conscious experience of a stimuli is not dictated by a single-variable function f(stimuli), but rather f(stimuli, personality, environment), at least for broad definitions of ‘personality’ and ‘environment’. If you have a favorite song that your friend thinks sounds terrible, this is because they are literally experiencing it differently from you due to the latter two variables given to this function. They don’t think the thing that you hear sounds terrible, they think the thing that they hear sounds terrible, and it is probably very dissimilar from what you hear. For more information on this line of thought I’d suggest reading about signaling theory and checking out The Elephant in the Brain by Robin Hanson and Kevin Simler.

How do you know if you’re in the right basin?

If you’re reading this you probably have a vague idea of what type of personality basin you’re currently in which you can recall by asking yourself the question “What type of person am I?” But an important question remains: how can you find out if this is the right basin to be in?

A simple answer would be that you could try out other basins to see how they feel. Maybe you’re having a great life as a devops programmer, but you could try to become an artist or a woodworker or a stay-at home parent and see how that fares for you.

The reason why this is hard is that the optimal personality for this basin is not immediately accessible to you – to truly test optimality you will need to go through a full RLHF process. If you want to know how good of a life you’d have as a professional pianist, you will have to practice the instrument for a decade to find out.

You may wonder if you could simply try your hand at the piano for a month or two and see how it goes, and of course you can do this too. Your time (and your meta-learning algorithm’s number of epochs and learning rate) is limited, and it’s reasonable to make the trade-off of sacrificing depth-first search in favor of more breadth-first search.

As you progress in life, you will usually perform less exploration for new personalities and more exploiting with your developed personality

Usually this breadth-first search of trying out many different and creative strategies for life (prioritizing exploration over exploitation) automatically happens during your adolescence, but one of the magic things about the modern world is that there are so many societies, cultures, countries, and fields of work one can move into, and for each different environment could exist a slightly-different-you which finds their own distinct personality that maximizes success. Had you been born as a hunter gatherer or within the roman empire or in ancient china, you’d probably have ended up quite different as a person. Similarly, if you decide to move countries or communities or careers, the optimal-you-for-your-environment will change a lot too.

Personality-space is adversarial

One interesting thing to note about personality-space is that it is adversarial. Rather than a static training set to iterate through, your training data consists of other RL agents, many of which are other people, and all of whom want different things from you.

This is what leads to the concept of Personality Capture. Personality capture is when your environment RLHFs you into becoming a personality that benefits other agents rather than yourself.

If a school bully threatens to hurt you unless you do their homework for them, they are attempting to modify your RLHF process so that it results in an agent which is beneficial to them, hopefully resulting in someone who will always give in to their demands.

Those familiar with high school psychology will find high similarity with this concept and that of classical and operant conditioning as well as concept of a Skinner box. The attempted addition to these concepts here is that of modelling the personality as a reinforcement learning process and changes in personality as gradient updates, which then allow us to view personality-space as a high-dimensional area which will give us some interesting tools to think with. As the saying goes, all models are wrong, but some are useful.

Luckily for humans there exist many symbiotic equilibria where multiple parties can find mutually-beneficial feedback loops within the epochs of personality-space. A mother loves her child because it provides her with the reward of feeling good which encourages further love. In response the child gets food, shelter, and care, which further encourages them to continue the relationship.

Personality Capture

It’s easy to become susceptible to various forms of personality capture when your environment changes. When asked why he isn’t on Twitter, Dario Amodei, CEO of Anthropic, responds to Dwarkesh Patel with:

I’ve just seen cases with a number of people I’ve worked with, where attaching your incentives very strongly to the approval or cheering of a crowd can destroy your mind, and in some cases, it can destroy your soul.

I’ve deliberately tried to be a little bit low profile because I want to defend my ability to think about things intellectually in a way that’s different from other people and isn’t tinged by the approval of other people.

Illustration of a monkey being personality captured by excessive twitter usage

Most people around you want to personality-capture you in some way. Your boss might want you to work harder, your children might want you to give them more attention, and political parties want you to vote for them.

One interesting way to frame personality capture is by combining it with the concept of attention economics. All of the apps on your phone want to turn you into the type of person that uses them all day because that is beneficial for their revenue models. In many cases this is mutually beneficial, but it’s nonetheless clear that the cat and mouse game is starting to favor the felines more and more over the last two decades as they have learned to perfect the craft of user acquisition, the art of user retention, and the science of ARPU maximization.

As I discussed in where are the builders, the game becomes particularly skewed when there is a large difference in ability or judgement between counterparties, with one common example being children and adolescents. It’s easy to become personality-captured by minecraft or roblox at the age of 10 – the game is not only fun and addictive, but a child also has little understanding of the level of optimization their counterparty has put in to making sure that they remain a user for life.

How do I leave my personality basin?

Perhaps you have decided that you don’t like your personality basin. Maybe it used to be working out for you but no longer is, or maybe you’ve always been unhappy with it. Or maybe you just have reason to believe you’re trapped in a local maxima which is far inferior to the global one. What should you do?

The first thing you’ll want to do is to change your environment. If both you and your environment are a constant, you shouldn’t expect to end up in a different basin any time soon. For every new environment exists a new optimal-you, and the world offers many environments to choose from.

The second thing you’ll want to do is increase your learning rate. There are a lot of ways to do this. One interesting note is that your learning rate will automatically increase if your environment changes. This may be why so many people find they are able to be more thoughtful and creative while going on long walks in nature rather than sitting in a cubicle.

This is also a reason why it’s good to constantly be trying new things, because new things will likely involve new environments and new people. If you wonder why trying new things is hard, it is likely because this trait was more maladaptive in our ancestral environment than it is today, as we had less control over our surroundings in the past (If anything, we may have too many options in some cases of the present: our society is so large that defection from a group is less costly as you can simply find a new group to join afterwards. This seems to create challenging game-theoretic equilibria in match-making where commitment to a partner is devalued due to the ease of finding alternatives, the effects of which can be seen by how discontent much of the population is with dating apps).

Although you have a general learning rate curve for how quickly your personality adapts to a new environments, different stimuli will also be paired with differing gradient magnitudes. High-magnitude experiences which result in strong gradient updates can move you within personality space much more quickly.

Humans have many sets of learning rate curves which govern different parts of their brain. In addition to the baseline learning curve, our learning curves are heavily modified by our environment.

If someone uses a psychadelic drug which explicitly gives them high-magnitude gradients they will probably move a lot more in personality space than if they had stayed sober. Similarly if someone undergoes a highly traumatic event, it may push them a long distance within personality space as they quickly adapt to ensure that they don’t have to go through the same experience again. Both of these activities involve large gradient updates.

Common activities which seem to give the largest gradient updates to humans are meditation, drug usage, trauma, religious events, love, gambling, and sex.

Some of these concepts are more negatively-coded than others, for example trauma. But the intended purpose of trauma is obvious, which is to avoid really bad things from happening to you in the future. One of the reasons why overcoming trauma isn’t as hard-coded into us as strongly as we might hope for is because our present society is so much larger than that which we evolved in such that there’s more opportunity to change your environment as to remove the potential source of trauma. Trauma was likely more adaptive in our ancestral environment than it was today due to an inability to drastically change your surroundings and social group in the past.

This is why strong psychedelic drugs like ayahuasca can be dangerous: whatever happens to you during your experience will be fed to you via high-magnitude gradients. Because users may experience hallucinations and delusional thinking during usage of such drugs, it’s possible for their location in personality-space to be thrown far out-of-distribution and into an area which has little overlap with the rest of humanity.

This isn’t to say there can’t be high-magnitude positive outcomes as well, but just that there is a high potential for variance when large gradients are involved. Romantic love can be a similarly dangerous force and has pushed thousands to suicide, yet our society near-universally regards it as a good thing! While there are many other reasons for this, high-variance is not inherently bad and is likely necessary at the societal level in order to promote long-term antifragility (this is also the very reason I am so bullish on America).

Personality basins and mental illness

Personality basins are an interesting way to model many mental illnesses. Similar to attractor states or trapped priors, they allow us to have a simple model with which we can plan to manipulate in order to solve our problems. Just as your personality basin decides how introverted you are, how funny you are, and what type of music you enjoy, it also helps to curate which psychiatric conditions affect you.

One of the reasons why curing depression is so hard is because you need a very large gradient update to escape the basin you’re trapped in. This gradient update could come all at once via an excessively strong positive stimuli, for example a drug which explicitly increases your learning rate like ketamine. But this is often hard to reliably induce, and so the gradient updates instead usually have to be small and continual over a long period of time.

This is what most cognitive behavioral therapy techniques are: we find a simple way to make a small positive gradient update to push you ever-so-slightly out of the personality basin you’re trapped in, and then we keep doing it for months or years until we finally push you all the way out of the undesirable basin.

This is also a nice way to model something like drug addictions: drugs personality-capture you into a basin which feeds off of and depends on them, and this basin can become arbitrarily deep due to the high magnitude of gradients drugs can apply to you (and thus be very hard to escape from). The concept of relapsing on a drug is equivalent to falling back down to the bottom of the basin, and the concept of tapering off dosage over time is equivalent to providing small and continual gradient updates over time.

I have a lot of hot takes that society is collectively becoming so efficient at some forms of personality capture that we will end up inducing various psychiatric conditions in the majority of our population. Societies end up with their own hyperdimensional personality basins just as people do, and just like us, the two ways they can move out of their basin are either gradually via many slow updates (e.g. the industrial revolution), or all at once via a very strong update (e.g. the french revolution). It’s worth thinking about the effects that different types of memetic information may have on our society’s collective personality basins as we become more and more efficient at communication.

Can’t I be in multiple personality basins?

One thing you may notice from the above sections is that your personality appears much more malleable and dynamic than one described by a static point: you probably act differently around your family than you do around your friends or your co-workers.

To solve this discrepancy you can simply model personality space and your personality basin with additional dimensions, allowing you to model yourself not as a 1d point, but as a three-dimensional landscape.

I model my own personality basin with an extra dimension (i.e., 4d): at any given point in time there exists a “me” which implements a given personality landscape in a given personality basin, but I also have many sub-basins which implement my different moods. The set of actions I might perform when I’m angry is very different from that when I’m sad, and these are simply different sub-basins within the containing higher-dimensional basin. You could similarly increment the model’s dimensionality in order to model yourself using internal family systems or even dissociative identity disorder.

Further reading

This post was heavily inspired by other posts including Trapped Priors, Dynamical Systems, and Singing The Blues by Scott Alexander and Personality: The Body in Society by Kevin Simler.

I’d strongly suggest reading The Others Within Us, The Arctic Hysterias, Crazy Like Us, and Neurons Gone Wild as an addendum to this post. Other related topics to explore include signal theory, control theory, set point theory, game theory, reinforcement learning, and deep learning.

Although the concepts presented in this post are similar to pre-existing concepts, I find that applying the analogy of loss landscapes, basins, and basic RL and DL concepts to be useful tools for thought and encourage readers to do further exploration with this mental model in case they find other useful analogies (what might a linear transformation on the loss landscape of personality-space look like and compare to? how can we develop a more comprehensive model of learning rate in humans and how would we modify it? are there any mental illnesses we can use this model with to try to come up with novel types of cures? how can we integrate this with bayesian theories of learning and perception? which other ideas in LLMs, RL or ML might we find useful to further analogize with?)

The explicit goal of this post is to help RLHF you into a personality basin which more easily allows for both thoughtful analogies and practical tools for thought. If you liked this post consider checking out my home page or twitter. Feedback is welcome!

Blueprint 1.0 Review

I spent $343 for one month of blueprint. this post shares what I got and what my thoughts on it are!

overall I’m a fan of most ingredients and the overall composition. I came up with many of them on my own a few years ago, many of which are listed here. the doses are pretty reasonable and I trust the sourcing to at least be above average

this post is not sponsored or paid for in any way, but I’ve met BJ and think he is reasonably smart and funny. below I include images, nutritional information, and plenty of links and side notes to share what I’ve learned!

Apr 13 2024 edit: Added response comments from Bryan Johnson / Blueprint: ctrl+F “BP” to find them
May 7th 2024 edit: Blueprint now allows for the purchase of individual components. I’ve added a new Market Comparisons section near the bottom as a result

Everything I got for one month at a cost of $343

Nutty pudding

Ingredients for the nutty pudding mix
  • mostly plant protein, giving you 26g of protein per serving
  • allulose as a sweetener is great and I’m happy to see it becoming more common (see my post on allulose for why). may want to note to consumers what it does and why they might notice it
  • cinnamon and grape seed both great inclusions
  • no opinion on pomegranate and monk fruit extract. I’m assuming the latter is as a sweetener and flavor enhancer (BP: pomegranite included to improve metabolic panel markers)
  • the taste is… alright. some people definitely like it more than I do, but I’d probably only rate it a 5/10 myself. I substituted whole milk in instead of nut milk as suggested and added the blueberry mix (below) to it to finish it. it tastes like a rather bland pudding, but a bit more dense and with little sugar or fat (BP: adding EVOO for taste may help)

Blueberry mix

Blueberry mix!
  • it’s literally just dried blueberries, macadamia nuts, and walnuts
  • tastes great no matter what do you with it really. I’d suggest adding it to the above pudding or combining it with some milk
  • blueberries are great for you and a good snack to have around
  • with that said, this mix is so simple that I’m not sure I gain much from having someone else prepare it for me (BP: mix replaces 2kg of berries and helps not having to acquire them frequently)

Longevity mix

Nutrition info for the longevity mix
  • simple mix that you add to water
  • creatine, glucosamine, taurine, glycine, the gang’s all here
  • allulose again chosen as the primary sweetener
  • I’d increase the amount of glycine (1.5g), especially due to this being earlier in the day so it’s unlikely to be too much to disrupt sleep (this dose would be fine before bed and likely benefit sleep but the instructions online suggest to have this mix in the morning). for more information on why I’m in favor of macrodosing glycine check out the glycine section on my supplements page (hint: it extends lifespan in mice!)
  • sodium hyaluronate is an interesting choice and I wonder why they chose it + this form of it (BP: intended to reduce inflammation and restore HA levels which decline with age)
  • i’m a big fan of ashwagandha, with the note that it can cause digestive distress for some. great for lipid profile and often improves anxiety too
  • there could be a bit more creatine (2.5g) for those lifting, especially since calcium alpha-ketoglutarate was added (BP: amount chosen to be tolerable for mass market while covering omnivores average diet intake)
  • the taste is decent and comparable to most ‘vitamin’ drink mixes that you add to water. I’d probably rate it a 6.5/10, nothing to complain about but not particularly exciting


The four bottles that I got along with what the pills from each look like. The daily suggested dosage is 3 pills from each of the larger bottles and 1 from each of the smaller, for a daily total of 8. Certainly not as bad as what was featured on my supplements page!

NAC, ginger, curcumin

Nutrition info for the NAC, ginger, and curcumin capsules
  • NAC is reasonably popular in the longevity community and pretty interesting
  • not 100% sure what the reasoning behind ginger was – I wonder if it was due to its ability to ameliorate potential gastrointestinal side effects of other supplements? (BP: intention is to improve metabolic panel, reduce inflammation, improve mood)
  • circumin is generally a good choice, although I have concerns about lower bioavailability here. does one of the other supplements included notably modify this? (BP: curcumin bioavailability 4x higher in this case due to being bio-enhanced)

Essential capsules

Nutrition info for the essential capsules
  • not going to list all the vitamins as they’re all reasonable choices
  • glad to see a higher amount of vitamin D (2,000 IU). could go even higher but the average blueprint consumer probably gets more sunlight than I do
  • I don’t know what the benefits of including e.g. iodine, calcium, manganese, and selenium are. would these be missed at all if excluded? feel free to enlighten me if you’re a reader! (BP: these deficienties are moderately common so worth including, calcium as excipient of CaAKG)
  • lithium is interesting at 1mg but I’m not sure that’s high enough to do very much (although perhaps this is the intention to keep it on the safe side)
  • I didn’t know that the body converts glucoraphanin into sulforaphane via myrosinase. good supplement!
  • fisetin at100mg daily is an interesting choice. curious how they decided daily was the correct increment and 100mg was the correct dose – I found this one hard to decide on myself (BP: dosage most studied wrt fisetin)
  • spermidine 10mg is perhaps one of the most promising supplements here due to directly improving lifespan in mice! how did they source this? see more info in the spermadine section on my supplements page
  • genistein is an interesting choice as it is pretty estrogenic. there are a lot of gender-ambiguous benefits to this, but i’m curious what the specific reasoning was and how the dose of 300mg was decided. it has affinity for α estrogen receptors, but not as much as β. if it was easier to source and include 17α-estradiol, would that have been included instead? was this included for entirely different reasons, of which there could be many? see also: does 17α-estradiol/estrogen extend male human lifespan? (BP: genistein does not increase blood estrogen levels in men, 17α generally requires Rx)

Essential softgel

Nutrition info from the essential softgels
  • nothing particularly exciting here, nice to see the better forms of vitamin k (k1, k2 mk4, k2 mk7) all included
  • astaxanthin is a nice inclusion
  • less excited over lycopene, lutein, and zeaxanthin, but I don’t know anything bad about them. would like to research them more later

Garlic, red yeast rice

Nutrition info for the garlic and red yeast rice pills
  • unsure why these are in their own pill instead of included within one of the larger mixes (from which you take 3 daily from)
    (BP: pills were grouped to reduce amount. water soluable actives went into longevity RTM, fat soluble into softgel, bitter tasting into capsules, and small amounts into essentual. RYR and NAC were separate SKUs due to regulatory concerns.
  • garlic is great if we give them the benefit of the doubt on the 12:1 exact including enough allicin
  • does the red yeast rice (500mg) actually contain a lot of monacolin k? some countries like the US dislike this due to it being bioidentical to e.g. lovastatin (BP: no, this is why CoAs are shared)
  • interesting side note: when you research a lot of natural compounds (roots, vegetable extracts, etc), it’s very interesting how many of them are bioidentical to actual pharmaceuticals. when I was young I didn’t understand why ‘vegetables’ or such should be good for me: adults would tell me they had “vitamins and minerals” in them, but I could obviously both a) test myself for vitamin and mineral deficiencies and b) supplement them if I was deficient in them. it wasn’t until many, many years later that I learned how amazingly complex everything we eat is and how many biologically active ingredients are in dishes. think of a dish with many vegetables, spices, roots, meat, etc, as basically having 20 different drugs in it, but with all of them in very small doses. many of them are also very slightly psychoactive too! just as you can get high on nutmeg and sweet potatoes inhibit α-glucosidase and are thus anti-diabetic like the drug acarbose and red yeast rice is literally the same as a statin medication and berberine found in plants like barberry is a mimetic of the anti-diabetic drug metformin, the foods we eat on a daily basis have an astoundingly large amount of downstream effects in the body which have nothing to do with the vitamins or minerals in them. the cases we tend to know about like marajuana or opium are not rare in that they have strong biological effects, but rather are only rare in the dose response curves that are common with consumption. the present epistemic milieu we reside in with respect to nutrition doesn’t talk about this much primarily because we know so little about the topic and actually learning what is going on enough to have high confidence and rigor is extremely tedious and slow

Olive oil

  • it’s olive oil. it is made from olives
  • the branding of ‘snake oil‘ is honestly pretty funny given how most supplement marketing is basically fraudulent


  • no cards or instructions were included in the box. this is missing out on a gigantic free lunch!
  • I’d strongly suggest adding instructions, a thank-you card, and a discount code for future purchases
  • the discount code should be notable as user retention may be more challenging than other monthly supplements due to the tediousness of consumption (8 pills, one drink mix, one pudding mix, olive oil, and another mix, every single day!)
  • given the higher price point it would be great if the bags could be redone to have a high-quality zipper on them as sealing them is annoying
  • the supplement bottles should be shinier. this will increase conversion as this product is offered at a ‘premium’ price point. I’d look into making a bespoke logo for blueprint as well or otherwise refining the font and decor around it. you will be surprised how much of a return you can get by spending $0.10 more on shiny paper and branding!
  • I would move supplements with the highest probability of causing digestive distress into their own pill so that users can modulate dosage or ablate it themselves for e.g. supplements like ashwaganda and curcumin. this should be included in the instructions as otherwise users who feel unwell may simply never try blueprint again
  • current marketing paradigm likely favors a cohort of more males than females and more adolescents than the elderly. this is reasonable and likely the correct choice to make early on, but I’d consider long-term strategies on how to improve this. encouraging gifting to the elderly (e.g. one’s parents) is likely a great idea here for obvious reasons
  • (BP: agreed on much of the above, some are already being implemented)

Research and sourcing

  • most of what is included is good, but I’m not told why it was included! if there was so much money spent on research and reviewing studies, it would be great if some of it could be shared to me as a lowly and uninformed end-user
  • why does the blueprint page advertise ‘non-gmo’, and what does ‘no artificial ingredients’ mean? generally the latter means next to nothing, but I don’t actually care if something as simple to synthesize as e.g. glycine is ‘artificial’ or not as long as it is the right chemical and without contaminants or impurities! modify labels for your intended audience accordingly
  • similarly to sharing research the website states that you “test the ingredients” yourselves. I assume this means more than just eating them and making sure you don’t die, but this seems like a great thing to share more about, especially because this is very tedious to do (BP: manufacturers are asked for CoA and then we test the individual ngredients ourselves)
  • having users share metrics before and after a few months of blueprint consumption would be great (BJ told me isn’t necessary as the individual ingredients already have sufficient evidence on their own. but if you ask me, there is never enough science being done and there is never enough data, so I’d prefer we continue to learn all that we can even if it only confirms our priors) (BP: a few thousand people are on it and sharing biomarkers, we will share this data)
  • relatedly I’m concerned that some of the supplements may inhibit various enzymes that then cause unknown and/or undesired changes of bioavailability in other supplements or drugs. both curcumin and ginger inhibit CYP3A4 and this may be suboptimal if combined with other longevity drugs like rapamycin (which, similarly, could block astaxanthin which blueprint includes as well). this is challenging as we have limited knowledge on this topic for most supplements and drugs, but is worth at least being aware of
  • fortunately i’ve written from-scratch personal tracking software that I can throw all of this data into in order to solve a few of the questions (those which are easily answerable via blood tests at least), but this is costly and tedious and I am tired of getting blood tests. I may try A/B testing all of blueprint RCT-style to see if I can notice any other variables it effects that I wouldn’t have otherwise predicted

Market Comparisons

  • As of May 7th 2024, Blueprint now allows for the purchase of individual items listed above instead of only all of them as a bundle.
  • If you only buy the four pill bottles, the cost comes to $146 for a month ($139 if you subscribe)
  • I did a rough but incomplete analysis of competitors on amazon, building up the ingredients myself from reasonable sources, attempting to find a cheaper alternative to blueprint
  • I failed at this task. In other words, if I try to get everything in the blueprint pills from reasonable alternatives on Amazon, I ended up spending more money, not less
  • Because I think most of the ingredients in the blueprint pill bottles are desirable and I trust their sourcing to be at least average (hopefully above-average), I’ve decided to replace some of my supplement stack with blueprint
  • I am not publishing my full spreadsheet as it could be done with more rigor, but the numbers I got were close to break-even for the essential softgels ($49), notably over for the essential capsules (~$75 to $110 rather than $59), break-even for the nac+ginger+curcumin capsules ($27), and under for the red yeast rice and garlic capsules (which are by far the cheapest at $11 currently)
  • This is impressive for a consumer product!
  • Compared to most mass-marketed supplement products (e.g. athletic greens/AG1, blueprint basically murders them in cold blood and is probably ‘better for you’ by a factor of 5-10x. I have unusually high standards compared to the typical consumer here, but this is worth stating explicitly for those that come across this post but aren’t used to this.

Final thoughts

  • overall this is a decent purchase if you find the price range affordable. It saves you a lot of time, logistics, planning, research, and so on, and a lot of the ingredients are top-notch and actually do things that you won’t otherwise get the effects of from even a good diet. It is certainly better than the rest of what is out there.
  • with that said, there’s secondary effects to note: a) the substitution effect of having something decent rather than what you’d have had instead (this is why most ‘diets’ are always an improvement: the typical American diet is so bad that basically anything that is not insane is likely to be a net-benefit), and b) the psychological effect of causing you to consciously think more about optimizing for your health. I would strongly bet that there is a ‘healthy user bias’ among blueprint users that results in them having e.g. better lipid and glycemic profiles than non-blueprint users even if they stopped taking blueprint as they probably get more exercise than average
  • the largest benefits in longevity may still be things that we cannot easily sell in a bag or bottle, whether that is because it is intangible like exercise, or because of excessive regulation (e.g. the revolutionary weight-loss drug semaglutide requires a prescription and often insurance, although notably can also be purchased online regardless from parties which are not fans of the US patent system. even so, clinical trials for it began 15 years ago which likely resulted in the early death of millions of americans due to obesity. other longevity drugs like rapamycin are also challenging to distribute to the average consumer for similar reasons (and that one is FDA-approved too!). the FDA is excessively conservative in what they allow, with drugs requiring a decade and ~$600M to be later slowly distributed to the general public, and this is before we even bring in talk of gene therapies or anything newer
  • alpha in longevity (both personal and scientific) still remains in copious quantities for those who are willing to search for it!
  • I have currently decided to continue to purchase the pill section of blueprint, but I’m not subscribed to the other components at this time.
  • If you enjoyed this post you might like my website (see also: supplements) or my twitter
  • feedback (especially any potential corrections) is very welcome! DM me on twitter or submit anonymously here

Pascalian Longevity: Why not?

Scott Alexander of SlateStarCodex / AstralCodexTen recently wrote Pascalian Medicine, in which he looks at various substances purported to improve covid outcomes, but which have relatively low amounts of evidence in their favor, likening administration of all of them to patients to a Pascal’s wager-type argument: if there is a small probability of a potential treatment helping with covid, and if it’s also very unlikely that this treatment is harmful, should we just give it to the patient regardless of if the quality of evidence is low and uncertain, as it would clearly have a positive expected outcome regardless?

The naive answer to this could simply be to attempt to calculate an expected value (note: I use the term expected value often here, but in some cases the terms hazard ratio, relative risk, or odds ratio would be more appropriate) for each treatment, and administer it if it’s positive. But there could be some unintended consequences of using this methodology over the entire set of potential treatments: we could end up suggesting treatments of 10 or 100+ pills for conditions, and apart from something just feeling off about this, it could magnify potential drug interactions, some treatments could oppose others directly, the financial cost could start to become prohibitive, and it could decrease patient confidence and have many other undesirable second-order effects.

Pascalian Longevity

There are many counter-arguments presented to the above concept which become less salient when the goal is changed from ‘find drug treatments to prescribe to all covid patients’ to ‘find personal health interventions that increase your own lifespan/longevity’.

I am fortunate enough that I am able to evaluate potential longevity interventions myself, pay for them myself, administer them myself, and review their potential effects on me myself. I might not do a perfect job of this – research is difficult, time-consuming, and lacking in rigor and quantity, and finding appropriate longevity biomarkers to quantitatively asses the effects of interventions is also difficult. But uncertainty is a given here, and that is why we incorporate it into our frameworks when deciding if something is worth doing or not by calculating an expected value. Furthermore, any harm that I may accidentally incur will only be done to myself, reducing the ethical qualms of this framework to near-zero (I would strongly oppose arguments that I should not have the right to take drugs which I think may significantly improve my own health, although some may disagree here).

My modus operandi with respect to longevity may have many uncertainties in its output, but still operates with a very strong (in my opinion) positive expected value: If a substance significantly and consistently increases the lifespan of organisms similar to humans (ideally in humans), and is also very safe in humans, then it is something that I want to take

This is how I operate personally with longevity, and it does result in me taking quite a few things (currently I’m at around 15). I do still try to minimize what I take as a meta-principle (for example, setting a minimum threshold of expected value that a substance must provide to warrant inclusion, rather than simply accepting any positive expected value) for a few reasons: firstly, to reduce potential drug interactions (which we do attempt to asses on a per-substance basis, rather than account for as an unknown, but unknowns are unfortunately a very large component of messing with biology regardless). Secondly, to keep my costs relatively sane, although I am not too worried about this as there are few ways to spend money more effectively than on trying to improve your health. Thirdly, to reduce the occurrence of interventions that may have the same or opposing mechanisms of action (taking two things with the same mechanism of action may be okay, but sometimes dose-response curves are less favorable, and taking >~2x of something will result in diminished or even negative returns). Lastly, to minimize potential secondary side-effects that could be cumulative over large classes of substances (for example, effects on the liver).

I don’t intend to promote any specific substances or interventions here as I don’t give medical advice, nor do I want anything specific to be the focus of this post, but I do want to remind us that just as we can calculate expected values in a utilitarian fashion and get effective altruism as a result, we can do the same for longevity interventions and get a very strong chance at notably increasing our lifespan/healthspan as a result. I do have a list of some of what I take here, but it is definitely not intended to promote anything specific to others.

Why Not?: Potential counter-arguments

Algernon’s Law

Algernon’s Law is sometimes brought up, suggesting that evolution has already put a lot of effort into optimizing our body, and thus we are unlikely to find improvements easily. But, as Gwern notes in the above link, there’s at least three potential ways around this reasoning: interventions may be complex (and/or too far away in the evolutionary plane) and could not have easily been found, they may be minor or only work in some individuals, or they may have a large trade-off involved and cause harm to reproductive fitness.

Although some areas of future longevity treatments may fall under exception one and be complex enough that evolution could not have found them, I would suggest that the majority of today’s potential treatments fall under exception three: evolution optimizes for reproductive fitness, not for longevity, and for this reason there are many interventions which will improve our longevity that it has not given to us already (this is part of why I am more optimistic about longevity interventions than I am about intelligence interventions/nootropics).

For an extreme example of this, it has been noted that castrated males often live longer, and that this is obviously something evolution would not be very interested in exploring. Although this has been found with median lifespan in male mice (maybe in females too?), there is also purported historical data on Korean eunuchs suggesting that they may have lived a full 14-19 years longer (there are definitely potential confounding variables and/or bad data here, but we don’t have RCTs on this in humans for obvious reasons..), and a more recent study in sheep that is also highly relevant: Castration delays epigenetic aging and feminizes DNA methylation at androgen-regulated loci, where epigenetic aging clocks that look at DNA methylation are used in castrated sheep. There are other traits that seem to improve longevity as well, for example decreased height. It seems quite plausible that there are a lot of trade-offs that optimize for strong reproductive fitness early in the lifespan of organisms, which end up costing the organism dearly in terms of longevity. These trade-offs may be involved in many areas such as testosterone, estrogen, growth hormone, IGF-1, caloric restriction, mtor activation, and many others.

Large error in estimating unknown risks

One other counter-argument here is often along the lines of “you are messing with things you don’t understand, and you could be hurting yourself but be unaware of this; the damage may also be difficult to notice, or perhaps only become noticeable at a much later time”

It is true that our understanding of biology is lacking, and therefore also that we are operating in highly uncertain environments. I would be open to evidence that suggests reasoning for why we may be systemically underestimating the unknown risks of longevity interventions, but given how strong the potential upside is, these would have to be some pretty terrible mistakes that are being made. It is often noted how curing cancer may only extend human lifespan by a few years, whereas a longevity improvement of 5% for everyone would provide much more value (and is also much easier to find in my opinion). One could make an argument here that even if I was doing something that notably increased my risk of e.g. cancer, if the expected lifespan increase of this intervention was as much as 1-5%, this could still be a huge net positive for my health! I don’t take approaches that are this extreme regardless, and I try to keep the risk side of my risk/reward ratio low independently of the level of potential reward in attempt to account for this uncertainty. I am also not aware of many interventions that seem to have very high numbers in both the numerator and denominator here, although I am pretty certain that they do exist; I don’t currently take anything that I think has notably detrimental side-effects for the time being.

Is it fair to call this approach Pascallian?

The original nature of Pascal’s wager is that of extreme probabilities resulting in positive expected values, but the numbers that we are operating with are nowhere near as extreme as they could be. It is probably not a good idea to take 10,000 supplements, each of which have a 0.1% chance of extending your lifespan by a year for many reasons (similarly, if 10,000 people that claimed to be God all offered me immortality for a small fee, I would hope to decline all of their offers unless sufficient evidence was provided by one).

As I’m not arguing in favor of taking hundreds or thousands of supplements in the hopes that I strike gold with a few of them, it may be worth noting that ‘Pascallian Longevity’ would be a poor label for my strategy. Regardless, taking just 5-10 longevity interventions with a strong upside potential seems to be significantly more than almost everyone is doing already, so I still stand by my claim that there are many free lunches (free banquets, if you ask me) in this area, and I am very optimistic about the types of longevity interventions we’ll find in the coming decades.

Open to any corrections/comments on Twitter or any medium on my about page


This page lists many of my favorite blog posts, organized by author. Much of my most-cherished knowledge is from blog posts or internet comments, so I hope to share some of that with others here. Last updated: Apr 17, 2024

Scott Alexander (Twitter): As the author behind SlateStarCodex (now AstralCodexTen) and many great LessWrong posts, Scott is among one of the best written content creators of the last decade. He writes about psychiatry, rationality, and meta-science. Here’s some writing of his that I love, with my favorites bolded:

Gwern Branwen (Twitter – currently private): Well-known for having quality deep dives in diverse areas such as statistics, technology, machine learning, genetics, psychology, and many others. Also often recognized as an amazingly aesthetic, verbose, and highly-usable website. Favorite posts:

  • About Gwern: About Gwern; who he is, what he has done, and links to other mediums
  • It Looks Like You’re Trying To Take Over The World: An eloquently-written and humorous short story about AI alignment and paperclipping, featuring our good friend Clippy alongside a multitude of entertaining references, both to Internet history and many arxiv machine learning papers
  • Generating Anime Faces: An overview of GANs in machine learning, with focus on Stylegan2 and anime art generation including ThisWaifuDoesNotExist and its follow-up ThisAnimeDoesNotExist, both trained from a large Danbooru dataset
  • Death Note Anonymity: Using information theory to quantify the magnitude of Light Yagami’s mistakes in Death Note (absolutely worth watching, even if you’re not into anime), offering insightful analysis and constructive criticism
  • The Scaling Hypothesis: Discussion of the scaling hypothesis in machine learning (essentially how much better models get with significantly more data+compute), with obligatory emphasis on GPT-2 and GPT-3
  • Melatonin: Detailed information on melatonin, a simple endogenous hormone that notably improves sleep in many individuals when supplemented just before bedtime
  • Nicotine: An analysis on the benefits of nicotine as a nootropic, with attention given to the fact that it is often incorrectly assumed to be a dangerous and addictive drug due to its inclusion in cigarettes and consequently significantly-confounded research claims
  • Modafinil: Discussion of modafinil, a prescription stimulant drug that appears to have a relatively favorable cost/benefit profile for productivity and alertness
  • Embryo Selection for Intelligence: A cost-benefit analysis of the marginal cost of IVF-based embryo selection for intelligence and other traits
  • Why Correlation Usually ≠ Causation: A meta-scientific discourse and analysis on the age-old adage that correlation does not imply causation
  • The Melancholy of Subculture Society: A brief analysis on the cultural effects of the Internet allowing niche subcultures to easily form
  • Newsletters: Links to Gwern’s past ~monthly newsletters
  • My Anime List: Gwern’s top-rated anime

Andrej Karpathy: (Twitter) A bright AI researcher who has spent time both at OpenAI and as the chief AI officer at Telsa. He has a popular Youtube channel with machiune learning content as well.

  • The Unreasonable Effectiveness of Recurrent Neural Networks: Back in 2015 Andrej trained a 10M-parameter RNN on some interesting text datasets like the source code for the Linux kernel and Shakespeare. Performance was surprisingly good!
  • Biohacking Lite: It’s always fun to read content from people from fields like computer science when they later deep dive into biology, often for their own personal health. This post has some high-SNR content on the basics of metabolism and energy in humans as well as some quantified-self demonstrations and simple dietary advice.

Scott Aaronson: A theoretical computer scientist with a focus on quantum computing and complexity theory. Although his posts on quantum computational complexity theory research go over my head, I’ve enjoyed some great content from him in other categories. Favorites:

Matt Levine (Twitter): An ex-Goldman Bloomberg opinion columnist with some wonderfully insightful and hilarious posts (offered as a free newsletter, generally ~4x a week) on the happenings in our modern yet often-insane financial world. Posts are generally centered around current events and are best read as they come out. Some examples:

Nintil (Twitter): A wonderful blog by Jose Luis Ricón with a focus on longevity, economics, and meta-science. Favorite posts:

Patrick Collison (Twitter): The CEO and co-founder of Stripe, often with focuses involving meta-science, individual and societal productivity, and economics

  • Fast: Examples of people quickly accomplishing ambitious things together
  • Questions: A short list of interesting questions
  • Advice: Advice, particularly for young and ambitious individuals
  • Book Recommendations: A well-sized list of suggested reading

Sam Altman (Twitter): The CEO of OpenAI and former president of Y Combinator, his posts often focus on startups, artificial intelligence, productivity, and science. Favorites:

  • How to be Successful: Thirteen thoughts on how to achieve long-term successful outcomes: learn a lot, compound yourself, work hard, and be ambitious
  • Productivity: Various productivity tips, such as ‘Picking the right thing to work on is the most important element of productivity and usually almost ignored. So think about it more!’
  • Advice for Ambitious 19 Year Olds: Advice for young and ambitious individuals, such as ‘The best people always seem to be building stuff and hanging around smart people’
  • How to Invest In Startups: Advice about being a good startup investor
  • Super successful companies: Notes some salient commonalities between many very successful companies
  • The Strength of Being Misunderstood: You should trade being short-term low-status for being long-term high-status

Paul Graham (Twitter): The founder of Y Combinator, with many posts focusing on startups, ideas and frameworks for everyday life, as well as advice and reflections for people that fit the founder/builder/nerd stereotype. Some favorites:

  • Do Things That Don’t Scale: An amazing tip on gaining initial traction and leverage by doing high-impact activities that won’t scale, but that will work effectively for the time being
  • What You Can’t Say: Reflections on that which exists outside of the Overton window
  • How to Make Wealth: An essay on effectively building wealth over time
  • Keep Your Identity Small: On why politics and religion yield such uniquely useless discussions due to excessive involvement with personal identity
  • Having Kids: Personal experiences and thoughts on having kids
  • It’s Charisma, Stupid: A 2004 essay arguing that charisma is the most important trait for elected politicians, using the US presidency as an example
  • What I worked on: A personal and emotional memoir on pg’s professional and personal history

Alexey Guzey (Twitter): Currently working on New Science, Alexey has some great blog posts with a focus on properly using the Internet for social leverage (reach out to people more, cold email people more, initiate conversations more, and create content more!), meta-science, productivity, biology, and more. Some favorites:

Melting Asphalt (Twitter): Written by Kevin Simler (along with Robin Hanson (Twitter), co-author of The Elephant in the Brain), Melting Asphalt has a wonderful collection of posts on evolutionary psychology, game theory, and novel and introspective takes on what makes us human. Favorites:

  • Neurons Gone Wild: A beautifully speculative post that suggests a recursively selfish model of biological neurons which enables selfish sub-agents and networks to co-exist in an evolutionary semi-competitive environment within our own minds. Probably my favorite post on this blog for several reasons. Also see Hallucinated Gods
  • Music in Human Evolution: A great book review of Why Do People Sing?: Music in Human Evolution by Joseph Jordania, involving predatory defense mechanisms, disposition of the dead, battle trances, and the audio-visual intimidation display
  • Crony Beliefs: On beliefs that stick around when they shouldn’t
  • Personality: The Body in Society:
    What is personality? ‘Nature and nurture work together to create a prototype, which then negotiates with the external world. The result is a strategy for getting along and getting ahead — a strategy we call “personality”, in other words, ‘Personality is a strategy for making the most of one’s particular lot in life.’ See also: part two and part three
  • Ads Don’t Work That Way: On ‘cultural imprinting’ and signaling in advertising
  • Doesn’t Matter, Warm Fuzzies: Discusses many interesting aspects of human ecology and society, with a focus on rituals, culture, confabulation, mimicry, and more
  • Social Status: Down the Rabbit Hole: On social status in humans, including an analysis of two proposed separate status systems: dominance/submission and prestige/admiration. See also: Social Status II: Cults and Loyalty
  • Border Stories: Borders are a necessary precondition for agency within a hostile ecosystem

Telescopic Turnip: Reads like type of cross-over between scott alexander and gwern, which means it’s good

Qualia Computing: With a subtitle of ‘revealing the computational properties of consciousness’, Qualia Computing is a great blog for anyone interested in the neurology, phenomenology, and interesting attempts at quantifications and explanations behind our own conscious experiences (qualia)

Patrick Mckenzie (Twitter): An entrepreneur and writer that lives in Japan and currently works at Stripe with a focus on startups and outreach, Patrick has many invaluable posts about finance, startups, marketing and professional communication, and highly-regarded SaaS and entrepreneurial advice. Favorite posts:

Nat Friedman (Twitter): Great personal website!

Fantastic Anachronism (Twitter): todo, see Recommended Reading

Applied Divinity Studies: todo

Peter Attia (Twitter): todo

Vitalik Buterin (Twitter): todo, see The bulldozer vs vetocracy political axis

Lesswrong: todo

Overcoming Bias: todo, ‘This is a blog on why we believe and do what we do, why we pretend otherwise, how we might do better, and what our descendants might do, if they don’t all die’, from Robin Hanson.

Tim Ferris: 11 Reasons Not to Become Famous

Dynomight (Twitter): todo, see Better air is the easiest way not to die by The impact of air pollution on health is often significantly underrepresented, and working on improving the quality of air in your dwelling can result in a very high ROI for your health

Marginal Revolution: todo

Does 17α-estradiol/estrogen extend male human lifespan?

17α-estradiol is a relatively (or completely) non-feminizing form of estradiol (E2), or estrogen. It is a naturally occurring enantiomer of 17β-estradiol (the much more common form of estradiol, usually just referred to as ‘estradiol’) which is found in both male and female humans. This post a a brief essay that discusses the prospect of it extending lifespan in humans. There are two primary types of estrogen receptors, ERα and Erβ, and as you may expect, 17α-estradiol appears to show a stronger binding affinity for ERα. It has a very low binding affinity in locations that generally induce feminization (which appear to be sometimes be both ERα and ERβ), so it’s also possible to take as a male without significantly altering one’s appearance towards the opposite gender. Although we can definitively point to a plethora of effects of regular estrogen, it is difficult to tell what the true purpose of 17α-estradiol is in humans, with Stout et al. (2016) stating “the physiological functions of endogenous 17α-E2 are unclear”. There is evidence it has neuroprotective properties, can help treat Parkinson’s disease, cerebrovascular disease, and much more. This likely involves ER-X, which in turn activates MAPK/ERK and many, many other things down the line (as usual..), but it’s difficult to know for certain. Although these reasons were among the reasons that researchers took into account when deciding to dedicate funding to testing 17α-estradiol in mice for longevity effects, subsequent papers have found more exciting mechanisms of action which are elaborated upon below. For some interesting further reading on this topic that goes into more detail exploring possible mechanisms of action here I’d also suggest reading the following papers: Castration delays epigenetic aging and feminizes DNA methylation at androgen-regulated loci, Hypermethylation of estrogen receptor-alpha gene in atheromatosis patients and its correlation with homocysteine.

17α-estradiol has been found to consistently and significantly extend the median lifespan of male mice, including by the NIH’s Intervention Testing Program, the closest thing we have to a gold standard of longevity RCT experimentation in mice, where three studies are rigorously performed at three separate locations, allowing the results to be instantly compared and reproduced by the two other parties and locations upon completion. Strong et al. (2016) find that 17α-estradiol extends median lifespan of male mice by an average of 19% (26%, 23%, and 9% from the three independent testing sites), and increased the maximum age by an average of 12% (21%, 8%, and 8% from the three testing sites, using the 90th percentile). Harrison et al. (2014) similarly find that median male lifespan was increased by 12%, but did not find an increase in maximum lifespan, and these results have been replicated even more in recent years.

These are some impressive results for such a common and simple endogenous substance! One of the first things we notice is that this effect only applies to males, with female lifespan (both median and maximum) being unaffected. As the substance in question is an estrogen, we can assume that this is either due to female mice already having this benefit, as they already have a sufficient level of it, or that something more complex is at play, and there is a different downstream pathway that is only being activated in males for some reason (more on this later). I had initially assumed the former hypothesis was at least a partial explanation, having known that females consistently live longer than males when it comes to humans, and that this was obviously biological in nature. However, it’s much more complicated in mice as females do not always outlive males, and in fact many times the opposite is true. One meta-analysis (good overview, original book source) finds 65 studies where males lived longer and 51 where females lived longer, with this often depending on the strain of mice used, which varies greatly depending on the type of reseasrch and time period. Regardless, it’s clear there is much more at play in this scenario, and perhaps something special about 17α-estradiol in particular.

Although the ITP studies initially included 17α-estradiol due to the reasons mentioned in the first paragraph, later research such as Stout et al. (2016) has now found that 17α-estradiol not only increased AMPK levels (as some other notable longevity substances such as Metformin also do), but also reduced mTOR activity (complex 1!) in visceral adipose tissue, which is rather reminiscent of Rapamycin, which has extended the lifespan of every organism we have performed an RCT with thus far (and likely can in humans too, if you ask me). In a way, this is significantly more exciting, because it gives us a much more plausible way to explain the lifespan extension effects we are noticing. However, it is also partially a disappointment: if these effects are the real reasons why 17α-estradiol extends male mice lifespan, then this substance may offer us nothing that we do not already have via rapamycin and metformin, among others. The paper also noted that fasting glucose, insulin, and glycosylated hemoglobin were reduced along with inflammatory markers improving. These are similar to the types of positive side effects we would expect from a longevity agent, and the study also notes that no feminization nor cardiac dysfunction occurred.

How do these effects (such as AMPK and mTOR modulation) occur? I don’t know, and apparently neither does anyone else. As is often the unfortunate case in biology, the paper has this to say: “The signaling mechanism(s) by which 17α-E2 elicits downstream effects remains elusive despite having been investigated for several decades”. Perhaps just a few more decades to go and this section will be updated with more information, then. Mann et al (2020) find that male mice without ERα do not benefit from 17α-estradiol, which helps us narrow down the first step by excluding Erβ, ER-X and other less-predictable initial mechanisms. Interestingly, they also note that “both 17α-estradiol and 17β-estradiol elicit similar genomic binding and transcriptional activation of ERα”, which would leave us with the question of why we are focusing on 17α-estradiol specifically, if 17β-estradiol (which is much more common) suffices as well. Importantly, they also seem to think changes in the liver might be involved. Garratt et al. (2018) add that distinct sex-specific changes in the metabolomic profile of the liver and plasma were found, and also notes that the longevity benefit for males disappears post-castration. They first supplement males and females, showing many differences related to metabolism including with amino acids. Then they use castrated males and notice that their profiles are the same as the control group, and thus conclude that they are no longer being positively affected by 17α-estradiol. I am unsure if we should be focusing on the AMKP/mTOR effects (which are very relevant to longevity) or on the liver/metabolic effects (which are also very relevant), or if these are in fact just two different temporal points on the same biological pathway which we don’t yet fully understand, but this helps us connect at least a few more dots.

All of the above sounds exciting, but it’s also all in mice. Sometimes this is useful, as mice are actually quite similar to humans (more so than many may expect), but a lot of it is also less useful or outright misleading. I cannot find a way to take only 17α-estradiol in a safe way as a human, however there is a topical cream of it (alfatradiol) which is used to treat pattern hair loss.

Luckily, one thing that the ITP study found was that 17α-estradiol was among one of the substances that seems to perform well with respect to longevity (if not fully) when given later in life (this has replicated afterwards as well), contrary to some others which have the best effect when started in youth and continued until death. In theory I wouldn’t mind waiting a decade or two until we have a better idea of what is going on here, after which point I would hope we have more fruitful and actionable results (especially in humans); although at the same time there’s likely many reasonable and safe ways we can go about achieving this (hopeful) effect in human males (assigned at birth) already, either via a type of estrogen or an estrogenic drug such as a SERM.

It is worth reminding ourselves that 17α-estradiol is already present in humans, and in both sexes, with women generally having significantly higher levels, as one expects of estrogen. Similarly, regular estrogen binds to both estrogen receptors, including our target, which we now know to be the alpha receptor. Given this, is it possible that just taking regular estradiol (for example, estradiol valerate, which for most purposes ends up biologically equivalent to endogenous estradiol and thus also binds to both primary estrogen receptors) to increase the levels of estrogen is a potential longevity intervention?

This is a difficult question to answer with the data currently available, although there are millions of persons assigned male at birth that are already on various forms of estradiol for various reasons, one of them being to assist in gender transition from male to female. As the lifespan benefit only applied to male (assigned at birth) mice, there would be benefits to analyzing these cohorts for more information, especially if we were able to have DNA methylation clocks used on these groups alongside a control (although this would not be a true RCT, as which persons decide to undergo feminizing HRT would not be random, I suspect we could still get the information we’d want with a good sample size).

There are other potential avenues of statistical analysis that could be attempted here, although they prove to be difficult for various reasons. Most male to female transgender individuals decide to transition earlier in their life, and this was also a particularly uncommon choice to make many decades ago in comparison to the present, so we have very few deaths due to age-related causes that we would be able to analyze to attain a proper hazard ratio. Even if we waited a long time for this (or had this data already), it would be terribly confounded due to the lack of randomization and many potential selection effects. Even so, one of the following must be true:

  • 17α-estradiol does not extend male (assigned at birth) human lifespan
  • 17α-estradiol does extend male (assigned at birth) human lifespan, however this does not apply to most/any transgender (m->f) individuals. This could be due to insufficient dosage, insufficient affinity for the alpha receptor, the inclusion of 17β-estradiol, the common addition of other substances such as anti-androgens, or another unknown factors/confounders
  • 17α-estradiol does extend male (assigned at birth) human lifespan, and this effect therefore does apply to most transgender (m->f) individuals, however we have either failed to notice it completely, or other effects/confounding variables ablate this, for example an increased risk of blood clots from estrogen supplementation (which depends greatly on the route of administration as well as type of estrogen used) or various potential side-effects from anti-androgen usage

Option one is certainly a possibility, as it always is in longevity when all of our studies are only in mice. We could differ too much from mice for the mechanism of action to apply to us (perhaps if it is related to metabolism or some newer subset of liver functionality), or if the mechanism of action is indeed the AMPK/mTOR pathways, perhaps 17α-estradiol does not modulate these in humans as it does in mice. This could have implications for other potential longevity agents such as metformin and rapamycin in humans as well, which also heavily involve these pathways, which could cause these agents to interplay synergistically or perhaps cancel one another out, as there may be no further benefit that can be gained after one of these agents is already taken at the optimal dosage. It is worth noting that many aspects related to AMPK/mTOR and DNA methylation are heavily evolutionary conserved as well (mTOR quite strongly, which is another reason why rapamycin likely extends human lifespan). We also already know that human females have longer lifespans than males for biological reasons, and that there are quite a few reports that the lifespan of castrated males is significantly increased. If 17α-estradiol (or estradiol valerate perhaps) does not extend human male lifespan, I would have to believe there is some other similar route that likely does, and we just have to find the best way to go about pursuing it.

Option two is, in my opinion, moderately plausible. It could the case that when we do have groups that supplement estradiol, the dosage taken is nowhere near sufficient for a noticeable longevity improvement, and that if we would simply increase it by some factor, longevity benefits would become apparent. There does seem to be a dose-dependent relationship for the longevity benefits in mice, and it may be possible that estrogen receptor alpha simply isn’t being agonized nearly enough. This may depend on the type of estrogen and route of administration used, as well as other drugs that may be taken (for example, most male to female transgender individuals take an anti-androgen as well as an estrogen, and this could potentially ablate benefits). My personal conjecture would be that estrogen monotherapy via injections would have the best probability of a longevity benefit for those assigned male at birth, although modulating or combining this with SERMs may also be of interest, although much more experimental and difficult to get right (I may add more to this later as this is a pretty interesting avenue to me for multiple reasons).

As for option three, it may seem difficult at first glance to think that millions of male to female transgender individuals are all currently supplementing a substance that may increase their lifespan by 5-20%, but yet none of us (or them) have noticed this yet. However, there are no preventative reasons for why this couldn’t be the case, nor statistical evidence against this possibility. It could even be that suppressing testosterone and activating estrogen receptor alpha are additive in nature, and we end up with a particularly impressive lifespan extension effect from conventional feminizing HRT.

Although I obviously cannot be sure of any specifics, I do think there is likely some hormonal intervention that should significantly increase male (assigned at birth) human lifespan, but that we just may need another decade or two to get the optimal intervention figured out properly. It would be great to have substances like 17α-estradiol in human trials already, as the potential ROI for successful longevity interventions is massive both in terms of billions of additional QALYs and trillions of dollars saved in healthcare expenditure.

In conclusion, 17α-estradiol might notably extend human lifespan for those assigned male at birth. There are many potential mechanisms of action that could cause this, with the most interesting one perhaps being activation of the mTOR and AMPK pathways, resulting in more ‘feminine’ DNA methylation. This longevity benefit, if it exists, may apply to many male to female transgender individuals, or could also be weaker or stronger for various reasons, such as due to the common usage of anti-androgens. If this longevity benefit does not apply to these groups, there may be alternative hormonal interventions that work instead, such as supplementing 17α-estradiol directly, using a SERM with a strong binding affinity in the right areas, or other modifications to the HPG axis that reduce some potential negative longevity effects of testosterone.

Disclaimer: I’m a random person on the Internet and none of this is medical advice. I’d like to rewrite and expand on the potential mechanisms of actions in this post and talk a bit more about what I do myself in this area some time too. Feel free to mention any corrections or comments to me (see: About page).