Immortality is biochemically possible

A look at aging in the context of the 2nd law of Thermodynamics


Biology is a relatively young science, still in its infancy. Unlike Physics or Chemistry much of Biology is reliant upon qualitative theories to explain how things work. Almost all of the major breakthroughs in the biological sciences over the past 150 years have been merely discovering details of biological systems. These useful descriptive facts include the discovery of DNA as the genetic material of the cell, the central dogma of molecular biology, the human genome project, and etc. These are descriptive facts, not theoretical explanations. Biology as a science has yet to reach the point where there is a full and complete mechanistic theoretical framework to explain everything that happens within a biological system.

AN: (for the ecologists or systems biologists who might read this I am sorry but you must work on your PR)

While there are many frameworks to approach questions about biology one of the best hallmarks for how much depth there is to a scientific field of study is to connect its concepts to the 2nd law of thermodynamics. One question that many professionals in the biological sciences have asked that can be explained in the context of the 2nd law is “Why do organisms age?”. Firstly, we need to differentiate between developmental growth vs that of aging. To avoid red herrings around the specific molecular pathways that define aging vs that of growth I am going to invoke a definition of aging as the progression of time for that specific system; leading to a decrease in maintenance quality.

The short answer for why organisms age: if the passage of time is relative, and the 2nd law of thermodynamics explains why time moves in one direction. Then the aging of biological systems is due to the 2nd law of thermodynamics being applied to that system.

If the above explanation makes sense to you then you need not continue reading any further.

The long answer,

The second law of thermodynamics states that the entropy of the universe will always increase.

If you can accept the assumption, or rather the observation, that the entropy of the universe will always increase, you will have a conceptual framework with you that answers many big questions about science. Questions such as:

1.Why does time only move in one direction?

2.Why do we age ?

3.Why do black holes imply that our universe is a hologram?

4.Why is space expanding?

5.Why has nobody ever gotten a 100% yield in chemistry?

6.  (My personal favorite) How do your headphones get so tangled in your pocket that you have to spend hours, possibly days of your lifetime actively trying to untangle them?

Entropy

Entropy is qualitatively observed as subjective apparent disorder, and by extension dissipation of energy. This definition works well pedagogically and for the purposes of answering our questions about aging. It is worth mentioning that entropy is more accurately defined as hidden information within a system, for an in depth explanation on this topic I would highly recommend the works of Brian Greene and Leonard Susskind. For our discussion, entropy as a measurement of disorder works fine.


In this equation we designate entropy as the letter S. The little triangle symbol is the Greek letter delta, which we use to represent change. If the entropy is increasing then the delta S is positive, if the entropy is decreasing then the delta S is negative.
While the 2nd law compels the entropy of the universe to increase, it does not compel individual systems to continuously increase their entropy. Systems can and do, fight the progression of entropy.

So the 2nd law states that the entropy of the universe will always increase, and this increase in entropy is what we call the passage of time. Houses get old and become rundown, food spoils, and objects become worn and decay all because of the 2nd law of thermodynamics. Notice that nowhere in the 2nd law does it state that a system MUST experience an increase in entropy.

To quote The Once and Future King by TH white: “Everything not forbidden is compulsory”.

Certain systems can avoid their increase in entropy at the expense of increasing the entropy of their surroundings, provided that system is what we call an open system. Something that can exchange energy with its surroundings.

One example of this would be the extremely rare occurrence of myself cleaning up my room.

(Note Brian Greene points out this example extremely well in his book The Hidden Reality )

I can decrease the entropy of my room by cleaning it up and putting it back into a state of order. Unfortunately this will require me to move, pick up pieces of trash, push the vacuum across the floor and etc. This work requires energy, which my body will extract from my metabolism. In doing so I will exhale CO2, hydrolyze ATP, breakdown glucose, as well as undergo other various biochemical reactions. It is from these processes that the entropy of the universe will keep increasing. My room may obtain order through my work, but the CO2 I will exhale from performing the soul crushing manual labor of cleaning my room will be released into the surroundings causing the entropy of the universe to increase.

Entropy and Energy (Gibbs free energy)

So if we have energy, and by extension can perform work, we can fight the progression of time (increase in entropy) for a specific system.

How do we explain this relationship?

As previously mentioned In the equations below, the little triangle symbol is the Greek letter delta, which we use to represent change: the final value subtracted from the initial value.

Starting with the first equation for the 2nd law: By looking at the relationships between the changes in the and entropy of the Universe and the changes in values associated with the System. We can see that a change in Gibbs free energy of the system can be used as an indirect measurement of change in the entropy of the Universe.







The top equation expresses the relationship between the change in Gibbs free energy (delta G), Temperature, Change in Enthalpy (delta H, which we can just equate with the flow of heat under constant pressure conditions such inside of cells), and the change in Entropy.

Notice that this top equation is the same as the bottom equation from the previous picture, which we derived from the 2nd law of thermodynamics.

All three equations express different ways of measuring the change in Gibbs free energy.



These equations demonstrate the relationship between the change in Gibbs free energy (the energy of a chemical reaction that we can use to do work) symbolized as delta G, and the change in entropy, delta S.

You don’t need to understand all the details of this equation, just the basic concept:

When the change in Gibbs free energy is negative (energy is being released) the entropy increases.

What causes the change in Gibbs free energy to be positive or negative? For Biochemistry there are three major things that can affect the delta G (change in Gibbs free energy): Temperature, the concentration of molecules in our reaction, and the relative energy states of reactants vs that of the products.


At face value what this equation means is that if I supply enough free energy to my cells (by flooding them with glucose for example), then the change in Gibbs free energy would become positive. If the change in Gibbs free energy is positive, then my change in entropy can be negative (entropy is decreasing), and thus my cells would not age and could even have the aging process reversed.

The details matter

The previous example showed how a system can fight the progression of entropy if free energy is available, because energy is the capacity to do work. In the case of my hikikomori-esque room the energy required for me to clean up the mess comes from my own metabolic processes, and there in lies the problem.

Just how I can do the work of cleaning up my room our cells have the capacity to maintain order at the expense of increasing the entropy of their surroundings, and by extension, increasing the entropy of the universe.

However, there is a finite amount of energy I can devote into cleaning my room. I can not take a broken bottle of glass and push the shards together at a high enough pressure that it melts the shards into a glass molt that I can reshape into a bottle. It does not matter how much food I eat or caffeine I consume. I cannot physically unbreak a broken bottle because my puny human muscles are physically incapable of doing so.

Likewise, there is also a finite amount of energy my cells can devote to maintenance and repair and this limit cannot be overcome. Even if I were to flood my cells with a massive amount of glucose (free energy), the excess glucose consumed will just be stored as fat, it wont be used to prevent the increase of entropy for my cells.

Probability and Entropy

The best way to explain entropy and the passage of time is that as entropy increases there is a higher number of disordered states or outcomes than ordered states or outcomes that the system can acquire. I can grab a box of Legos and just randomly throw them on the floor and the outcome will be a messy pile of Legos. The pieces do not just magically arrange themselves into a Lego replica of Minas Tirith because there is astronomically more disordered paths for the Legos to fall through than ordered ones. Let’s combine this reasoning with our room example: there is a finite amount of energy that we can devote to maintain order in our system. If a bottle of glass in my room is broken, I cannot physically unbreak the bottle.

As the entropy of the room increases the probability of “bottle breaks” increases and as such the number of irreversible disorder events occur and the system as a whole progresses forward in time.

In the graph above we see that as age of a population increases, so too does their rate of cancer, which we can view as irreversible disorder events. Figure taken from CDC MMWR

This explains why cells age and are effected by the progression of time despite the fact that we keep supplying them with free energy in the form of various reduced carbon species such as glucose.

As biological systems are subjected to entropy they are physically moving forward in time and progressing to a state of disorder. The more entropy one is subjected to the faster the relative rate of time travel is for that particular system.

Every biological system is being pushed forward through time at some unspecified rate via their own oxidative metabolism. The “speed” of time travel can be sped up by putting that system under more oxidative stress and by doing so: increasing the amount of irreversible disorder events (bottle breaks, in our messy room example). This implies that people who suffer from chronic diseases or smokers who put their body under excessive oxidative stress dont just die sooner than a hypothetical identical twin (a control group) without those characteristics. They are traveling relatively faster through time than their hypothetical nonsmoking twin. This plays into the common colloquial observation that one can make regarding “smokers face”.

the relative life expectancy of smokers vs non smokers. You can find the full text here from the NEJM


Lifespan and animal size.

As previously stated all forms of life are being pushed forward through time via their own oxidative metabolism at their respected relative rates. In the class of mammals, they all have extremely similar metabolism pathways, the only difference is the relative metabolic rate per unit of body mass. This is why we can do experiments that investigate obesity on mice and apply the results to humans with confidence.

Hemmingsen, 1960

According to Kleibers law when we scale small animal metabolism to large animal metabolism, it increases by a 3/4 power law. This means that whales need less energy per unit of body mass than smaller animals such as shrews. Therefore whales have a more efficient metabolism than shrews do. Being larger and more efficient metabolically implies two things:

  1. That larger biological systems such as whales are subjected to less entropy via their own oxidative metabolism per terminal unit (cell) than other classes of life with a similar metabolism.
  2. It means that larger systems have access to more free energy to devote to maintenance and repair than smaller lifeforms of the same class, and by extension, they are subjected to less entropy than shrews are, which is why they live significantly longer lives.

It is not uncommon for a Blue whale to live past 100 years of age, mice and shrews on the other hand tend to only make it past 2 years before they die. (Note: Geoffrey West outlines scaling laws along with introducing the science of complexity in his excellent book: Scale. )

Aging and networks.
G
ulio Tunoni and Chrisoph Koch are famous for the development of an idea known as “integrated information theory” (IIT). While IIT usually comes up in conversations about consciousness I want to point out that it illustrates that we can mathematically model how integrated something is within a system and how quantitative changes in the degree to which the information is integrated can lead to breakdowns within a system. IIT assigns a coefficient value to how integrated the information is within a system is, and based off of the degree of integration IIT can be used to determine if something is conscious or not. IIT has done incredibly well in demonstrating its numerous applications in a clinical setting. For example, a patient who suffers from a severed corpus collosum, alzheimers disease, or some other neurodgerative disease may develop “alien hand syndrome“, in which a person experiences their limbs acting seemingly on their own, without conscious control over the actions. Said patients would have an IIT coefficient less than that of a phenotypically normal patient without alien hand syndrome. This is because there would be more integration of information within the normal “healthy” persons nervous system.

If we apply the concept of IIT (or any analogous metric of integration) to every cell in your body we would have a quantitative value that can deduce useful measures such as if our organs, organ systems, or even cells are: “normal”, “healthy”, and “young”. VS “old” “abnormal”, and “diseased”.

As previously mentioned, there are limits to how much energy can be devoted to repair both in practice and in principle. There are also limits to how much energy can be delivered to our cells at one time, and how much cellular waste can be removed at one time (which is relevant to the former via le-chataliers principle). The threshold for how much energy (and other compounds such as signals or metabolite removal for that matter ) that can be delivered to your cells is set by your body’s energy delivery network: your blood vessels. As you age these networks break down via the 2nd law circa shear stress and viscous drag forces (decreased vascular compliance). As your networks breakdown, the extent to which your cells are said to be “integrated” declines.

When cells collectively cannot maintain the same level of integration that they previously had, survival signals decline. (see trophic hypothesis for a breakdown of this) and the entire organism as a whole starts to break down.


Predation, division of labor, networks and lifespan

Humans, like all mammals are a walking furnace constantly burning calories to supply our muscles, heart, and allegedly advanced central nervous system with the energy they need to perform their functions. Specifically us humans have sacrificed a lot in terms of our evolutionary biology to have the brains that we have, so it is worth emphasizing just how much we have lost biologically in order to obtain our higher level cognition which allows us to watch YouTube and comment on Instagram posts for hours every day.

Unlike reptiles or plants, humans needed to produce massively larger quantities of ATP(energy) to keep our brains running. A key component to accomplishing this task was to become energy efficient enough for our cells to perform their biological function without consuming too much energy. In order to reach this optimum point of energy efficiency, more compartmentalization and more precise signaling was required to allow for better division of labor among our cells. There were major biological consequences of doing this.

The demand for metabolic efficiency meant we had less energy to devote to maintenance and repair. Division of labor, and by extension more precise signaling made us more prone to diseases both genetic and infectious.

Only through division of labor were we able to become energetically efficient enough to have the necessary fuel to run our brains. One of the ways in which we were able to divide our labor efficiently was by developing many hyperspecialized cell types that fully differentiate into mature cells. By fully differentiating into the various cell types, our tissues were able to devote certain specific tasks to certain cells which enabled our bodies to spend less energy on signaling, repair, and multi-task performance. This increased our energy yield, but in doing so we had to sacrifice much of our stem cell population as well as cellular repair mechanisms. This lowered stem cell population and investment in repair, in turn, cost us much of our regenerative capacity.

Predation

One of the more elaborate details that emerges from R vs K selection theory is the link between lifespan and predation.

Animals that have similar size and metabolism who deviate based on their ancestral predation have significantly different repair mechanisms and different amounts of energy invested in repair.

Naked mole rats, for example dont have many predators, as such their average lifespan is around 30 years of age. Mice, which have a similar size, however, only live for about 3 years.

The reason naked mole rats have evolved the means to live significantly longer than mice is that by lacking predators, natural selection favors longevity via cellular repair investment. By living longer, they will have more opportunities to mate and produce viable young.

Mice on the other hand, who are constantly victims of predation have no reason to invest in cellular repair since the probability of them being eaten is so high they will never live long enough to reap the benefits of repair.

By studying the biochemical differences between mice and naked mole rats, I believe that we can discover hithero unknown means of improving our own longevity.

What all of this means is that it is not impossible for us to someday develop the ability to engineer biological systems that can reverse the aging process or extend their lifespan indefinitely. Just that the energy required to do so exceeds the limits that natural selection placed on our metabolism. Nowhere in the laws of physics and chemistry does it state that a system is compelled to degrade into a state of disorder, ergo it is possible for us to live forever like the elves of lord of the rings. It is my optimistic prediction that we will someday be able to metabolically engineer our cells to devote more energy to repair and maintenance and perhaps even use nanotechnology to manually do so with external power sources.


If you have read to the end of this, may I say thank you for doing so.


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