How long does it take for a food-related trait to evolve?

Often in discussions about Paleolithic nutrition, and books on the subject, we see speculations about how long it would take for a population to adapt to a particular type of food. Many speculations are way off mark; some think that even 10,000 years are not enough for evolution to take place.

This post addresses the question: How long does it take for a food-related trait to evolve?

We need a bit of Genetics 101 first, discussed below. For more details see, e.g., Hartl & Clark, 2007; and one of my favorites: Maynard Smith, 1998. Full references are provided at the end of this post.

New gene-induced traits, including traits that affect nutrition, appear in populations through a deceptively simple process. A new genetic mutation appears in the population, usually in one single individual, and one of two things happens: (a) the genetic mutation disappears from the population; or (b) the genetic mutation spreads in the population. Evolution is a term that is generally used to refer to a gene-induced trait spreading in a population.

Traits can evolve via two main processes. One is genetic drift, where neutral traits evolve by chance. This process dominates in very small populations (e.g., 50 individuals). The other is selection, where fitness-enhancing traits evolve by increasing the reproductive success of the individuals that possess them. Fitness, in this context, is measured as the number of surviving offspring (or grand-offspring) of an individual.

Yes, traits can evolve by chance, and often do so in small populations.

Say a group of 20 human ancestors became isolated for some reason; e.g., traveled to an island and got stranded there. Let us assume that the group had the common sense of including at least a few women in it; ideally more than men, because women are really the reproductive bottleneck of any population.

In a new generation one individual develops a sweet tooth, which is a neutral mutation because the island has no supermarket. Or, what would be more likely, one of the 20 individuals already had that mutation prior to reaching the island. (Genetic variability is usually high among any group of unrelated individuals, so divergent neutral mutations are usually present.)

By chance alone, that new trait may spread to the whole (larger now) population in 80 generations, or around 1,600 years; assuming a new generation emerging every 20 years. That whole population then grows even further, and gets somewhat mixed up with other groups in a larger population (they find a way out of the island). The descendants of the original island population all have a sweet tooth. That leads to increased diabetes among them, compared with other groups. They find out that the problem is genetic, and wonder how evolution could have made them like that.

The panel below shows the formulas for the calculation of the amount of time it takes for a trait to evolve to fixation in a population. It is taken from a set of slides I used in a presentation (PowerPoint file here). To evolve to fixation means to spread to all individuals in the population. The results of some simulations are also shown. For example, a trait that provides a minute selective advantage of 1% in a population of 10,000 individuals will possibly evolve to fixation in 1,981 generations, or 39,614 years. Not the millions of years often mentioned in discussions about evolution.

I say “possibly” above because traits can also disappear from a population by chance, and often do so at the early stages of evolution, even if they increase the reproductive success of the individuals that possess them. For example, a new beneficial metabolic mutation appears, but its host fatally falls off a cliff by accident, contracts an unrelated disease and dies etc., before leaving any descendant.

How come the fossil record suggests that evolution usually takes millions of years? The reason is that it usually takes a long time for new fitness-enhancing traits to appear in a population. Most genetic mutations are either neutral or detrimental, in terms of reproductive success. It also takes time for the right circumstances to come into place for genetic drift to happen – e.g., massive extinctions, leaving a few surviving members. Once the right elements are in place, evolution can happen fast.

So, what is the implication for traits that affect nutrition? Or, more specifically, can a population that starts consuming a particular type of food evolve to become adapted to it in a short period of time?

The answer is yes. And that adaptation can take a very short amount of time to happen, relatively speaking.

Let us assume that all members of an isolated population start on a particular diet, which is not the optimal diet for them. The exception is one single lucky individual that has a special genetic mutation, and for whom the diet is either optimal or quasi-optimal. Let us also assume that the mutation leads the individual and his or her descendants to have, on average, twice as many surviving children as other unrelated individuals. That translates into a selective advantage (s) of 100%. Finally, let us conservatively assume that the population is relatively large, with 10,000 individuals.

In this case, the mutation will spread to the entire population in approximately 396 years.

Descendants of individuals in that population (e.g., descendants of the Yanomamö) may posses the trait, even after some fair mixing with descendants of other populations, because a trait that goes into fixation has a good chance of being associated with dominant alleles. (Alleles are the different variants of the same gene.)

This Excel spreadsheet (link to a .xls file) is for those who want to play a bit with numbers, using the formulas above, and perhaps speculate about what they could have inherited from their not so distant ancestors. Download the file, and open it with Excel or a compatible spreadsheet system. The formulas are already there; change only the cells highlighted in yellow.

References:

Hartl, D.L., & Clark, A.G. (2007). Principles of population genetics. Sunderland, MA: Sinauer Associates.

Maynard Smith, J. (1998). Evolutionary genetics. New York, NY: Oxford University Press.

Applied evolutionary thinking: Darwin meets Washington

Charles Darwin, perhaps one of the greatest scholars of all time, thought about his theory of mutation, inheritance, and selection of biological traits for more than 20 years, and finally published it as a book in 1859.  At that time, many animal breeders must have said something like this: “So what? We knew this already.”

In fact George Washington, who died in 1799 (many years before Darwin’s famous book came out), had tried his hand at what today would be called “genetic engineering.” He produced at least a few notable breeds of domestic animals through selective breeding. Those include a breed of giant mules – the “Mammoth Jackstock” breed. Those mules are so big and strong that they were used to pull large boats filled with coal along artificial canals in Pennsylvania.

Washington learned the basic principles of animal breeding from others, who learned it from others, and so on. Animal breeding has a long tradition.

So, not only did animal breeders, like George Washington, had known about the principles of mutation, inheritance, and selection of biological traits; but they also had been putting that knowledge into practice for quite some time before Darwin’s famous book “The Origin of Species” was published.

Yet, Darwin’s theory has applications that extend well beyond animal breeding. There are thousands of phenomena that would look very “mysterious” today without Darwin’s theory. Many of those phenomena apply to nutrition and lifestyle, as we have been seeing lately with the paleo diet movement. Among the most amazing and counterintuitive are those in connection with the design of our brain.

Recent research, for instance, suggests that “surprise” improves cognition. Let me illustrate this with a simple example. If you were studying a subject online that required memorization of key pieces of information (say, historical facts) and a surprise stimulus was “thrown” at you (say, a video clip of an attacking rattlesnake was shown on the screen), you would remember the key pieces of information (about historical facts) much better than if the surprise stimulus was not present!

The underlying Darwinian reason for this phenomenon is that it is adaptively advantageous for our brain to enhance our memory in dangerous situations (e.g., an attack by a poisonous snake), because that would help us avoid those situations in the future (Kock et al., 2008; references listed at the end of this post). Related mental mechanisms increased our ancestors’ chances of survival over many generations, and became embedded in our brain’s design.

Animal breeders knew that they could apply selection, via selective breeding, to any population of animals, and thus make certain traits evolve in a matter of a few dozen generations or less. This is known as artificial selection. Among those traits were metabolic traits. For example, a population of lambs may be bred to grow fatter on the same amount of food as leaner breeds.

Forced natural selection may have been imposed on some of our ancestors, as I argue in this post, leading metabolic traits to evolve in as little as 396 years, or even less, depending on the circumstances.

In a sense, forced selection would be a bit like artificial selection. If a group of our ancestors became geographically isolated from others, in an environment where only certain types of food were available, physiological and metabolic adaptations to those types of food might evolve. This is also true for the adoption of cultural practices; culture can also strongly influence evolution (see, e.g., McElreath & Boyd, 2007).

This is why it is arguably a good idea for people to look at their background (i.e., learn about their ancestors), because they may have inherited genes that predispose them to function better with certain types of diets and lifestyles. That can help them better tailor their diets to their genetic makeup, and also understand why certain diets work for some people but not for others. (This is essentially what medical doctors do, on a smaller time scale, when they take a patients' parents health history into consideration when dispensing medical advice.)

By ancestors I am not talking about Homo erectus here, but ancestors that lived 3,000; 1,000; or even 500 years ago. At times when medical care and other modern amenities were not available, and thus selection pressures were stronger. For example, if your no-so-distant ancestors have consumed plenty of dairy, chances are you are better adapted to consume dairy than people whose ancestors have not.

Very recent food inventions, like refined carbohydrates, refined sugars, and hydrogenated fats are too new to have influenced the genetic makeup of anybody living today. So, chances are, they are bad for the vast majority of us. (A small percentage of the population may not develop any hint of diseases of civilization after consuming them for years, but they are not going to be as healthy as they could be.) Other, not so recent, food inventions, such as olive oil, certain types of bread, certain types of dairy, may be better for some people than for others.

References:

Kock, N., Chatelain-Jardón, R., & Carmona, J. (2008). An experimental study of simulated web-based threats and their impact on knowledge communication effectiveness. IEEE Transactions on Professional Communication, 51(2), 183-197.

McElreath, R., & Boyd, R. (2007). Mathematical models of social evolution: A guide for the perplexed. Chicago, IL: The University of Chicago Press.

Often acquired tastes are acquired genes: Probiotics and prebiotics

Gut flora is found in many areas of our digestive tract, particularly in the colon. Whenever we eat anything we feed the microbes that make up our gut flora and/or add new microbes. Much of this flora is made up of bacteria. Not all of it is made up of bacteria though. The much talked about Candida albicans (a.k.a. “the American parasite”) is a fungus that is found predominantly in our digestive tract and mouths.

Candida’s recent fame is more a testament to the power of well-orchestrated Internet campaigns to sell products than to the actual importance of the fungus in determining the health of non-immunodepressed individuals. Claims about Candida, including dubious ones, have been made many times in the past ().

The relationship between the human gut flora and health was a topic of much interest to Élie Metchnikoff (photo below from Wikipedia), who received the Nobel Prize in Medicine in 1908 for his research on phagocytosis (). Metchnikoff was also a pioneer in the study of aging.

Gut flora discussions often refer to foods and supplements that fall into one of two main categories: probiotics and prebiotics (). Probiotics are generally defined as foods and supplements that include health-promoting live microbes. Prebiotics are non-digestible foods and supplements that feed health-promoting microbes living primarily in the human colon.

Food fermentation, under the appropriate conditions, leads to the formation of natural probiotics. This applies to both animal foods (e.g., cheese, cured meats) and plant foods (e.g., sauerkraut, pickles). Prebiotics occur naturally in many raw plant foods as fiber and resistant starch, and can also be produced through starch retrogradation ().

Again, whenever we eat anything we feed our gut flora. This gut flora is reportedly made up of 10 to the power of 14 cells of bacteria, 10 times more cells than the human body (), plus other types of microbes (e.g., fungi). Different species of microbes in our gut have genomes that are markedly different from ours. Thus we carry in our gut significantly more genes than our own; and genes are selfish.

Genes are selfish in the sense that they seek to propagate themselves. From the perspective of our gut microbes, this can be achieved by inducing the secretion of chemicals that will make us crave foods that will also feed the microbes, whether this will lead to an improvement in our health or not. Even unhealthy human hosts can live long enough to sustain a large number of generations of microbes.

Killing the host human organism may seem like a suicidal strategy for gut microbes, but not if the host organism passes the microbes to other host organisms before the microbes themselves die. Microbes can pass from one human to another through many mechanisms.

So how can we improve our gut flora?

Supplementation or transplantation of microbes have been attempted with mixed but generally positive results ().

Few approaches combine the effectiveness and simplicity of avoiding highly processed industrialized foods. The emphasis here is on inhibiting the growth of unnatural gut flora; flora that has not been carried regularly by our Paleolithic ancestors.

Having done that for a while, which can be difficult due to cravings induced by unnatural gut flora, your own body may become very effective at telling you what is good for you and what is not.

As a side note, just because a food is fermented one cannot assume that it is health-promoting. Bread is a fermented food.

Over the years I have noticed that I prefer eating certain meat dishes cold, and several days after they have been prepared. I wonder if this has anything to do with a small amount of fermentation bringing to life probiotic microbes.

Could we have evolved traits that are detrimental to our survival?

Let us assume that we collected data on the presence or absence of a trait (e.g., propensity toward risky behavior) in a population of individuals, as well as on intermediate effects of the trait, downstream effects on mating and survival success, and ultimately on reproductive success (a.k.a. “fitness”, in evolutionary biology).

The data would have been collected over several generations. Let us also assume that we conducted a multivariate analysis on this data, of the same type as the analyses employing WarpPLS that were discussed here in previous posts (). The results are summarized through the graph below.



Each of the numbers next to the arrows in the graph below represents the strength of a cause-effect relationship. The number .244 linking “a” and “y” means that a one standard deviation variation in “a” causes a .244 standard deviation increase in “y”. It also means that a one standard deviation variation in “a” causes a 24.4 percent increase in “y” considering the average “y” as the baseline.

This type of mathematical view of evolution may look simplistic. This is an illusion. It is very general, and encompasses evolution in all living organisms, including humans. It also applies to theoretical organisms where multiple (e.g., 5, 6 etc.) sexes could exist. It even applies to non-biological organisms, as long as these organisms replicate - e.g., replicating robots.

So the trait measured by “a” has a positive effect on the intermediate effect “y”. This variable, “y” in turn has a negative effect on survival success (“s”), and a strong one at that: -.518. Examples: “a” = propensity toward risky behavior, measured as 0 (low) and 1 (high); and “y” = hunting success, measured in the same way. (That is, “a” and “y” are correlated, but “a”=1 does not always mean “y”=1.) Here the trait “a” has a negative effect on survival via its intermediate effect on “y”. If I calculate the total effect of “a” on “w” via the 9 paths that connect these two variables, I will find that it is .161.

The total effect on reproductive success is positive, which means that the trait will tend to spread in the population. In other words, the trait will evolve in the population, even though it has a negative effect on survival. This type of trait is what has been referred to as a “costly” trait ().

Say what? Do you mean to say that we have evolved traits that are unhealthy for us? Yes, I mean exactly that. Is this a “death to paleo” post? No, it is not. I discussed this topic here before, several years ago (). But the existence of costly traits is one of the main reasons why I don’t think that mimicking our evolutionary past is necessarily healthy. For example, many of our male ancestors were warriors, and they died early because of that.

What type of trait will present this evolutionary pattern – i.e., be a costly trait? One answer is: a trait that is found to be attractive by members of the other sex, and that is not very healthy. For example, a behavior that is perceived as “sexy”, but that is also associated with increased mortality. This would likely be a behavior prominently displayed by males, since in most species, including humans, sexual selection pressure is much more strongly applied by females than by males.

Examples would be aggressiveness and propensity toward risky behavior, especially in high-stress situations such as hunting and intergroup conflict (e.g., a war between two tribes) where being aggressive is likely to benefit an individual’s group. In warrior societies, both aggressiveness and propensity toward risky behavior are associated with higher social status and a greater ability to procure mates. These traits are usually seen as male traits in these societies.

Here is something interesting. Judging from our knowledge of various warrior societies, including American plains Indians societies, the main currency of warrior societies were counts of risky acts, not battle effectiveness. Slapping a fierce enemy warrior on the face and living to tell the story would be more valuable, in terms of “counting coup”, than killing a few inexperienced enemy warriors in an ambush.

Greater propensity toward risky behavior among men is widespread and well documented, and is very likely the result of evolutionary forces, operating on costly traits. Genetic traits evolved primarily by pressure on one sex are often present in the other (e.g., men have nipples). There are different grades of risky behavior today. At the high end of the scale would be things that can kill suddenly like race car driving and free solo climbing (, ). (If you'd like to know the source of the awesome background song of the second video linked, here it is: Radical Face's "Welcome Home".)

One interesting link between risky behavior and diet refers to the consumption of omega-6 and omega-3 fats. Risky behavior may be connected with aggressive behavior, which may in turn be encouraged by greater consumption of foods rich in omega-6 fats and avoidance of foods rich in omega-3 fats (, ). This may be behind our apparent preference for foods rich in omega-6 fats, even though tipping the balance toward more foods rich in omega-3 fats would be beneficial for survival. We would be "calmer" though - not a high priority among most men, particularly young men.

This evolved preference may also be behind the appeal of industrial foods that are very rich in omega-6 fats. These foods seem to be particularly bad for us in the long term. But when the sources of omega-6 fats are unprocessed foods, the negative effects seem to become "invisible" to statistical tests.

Familial hypercholesteromia: Why rely on cholesterol levels when more direct measures are available?

There are two forms of familial hypercholesteromia (FH), namely heterozygous and homozygous FH. In heterozygous FH only one copy of the gene that causes it is present, inherited either from the father or the mother. In homozygous FH, which is the most lethal form, two copies of the gene are present. FH is associated with early-onset cardiovascular disease (CVD).

Homozygous FH may happen if both the father and mother have heterozygous or homozygous FH. If both the father and mother have heterozygous FH, the likelihood that at least one in four children will have homozygous FH will be high. If both parents have homozygous FH the likelihood that all children will have homozygous FH will be high.

In fact, in the latter case, homozygous FH in the children is almost certain. One case in which it won’t occur is if the combining FH gene from the father or mother mutates into a non-FH gene before it is used in the assembly of the genome of the child. A gene mutation in a specific locus, only for the father or mother, is an unlikely event, and would lead to heterozygous FH. Two gene mutations at once in the same locus, for the father and mother, is a very unlikely event.

By the way, despite what many are led to believe based on fictional characters in movies and series like the X-Men and Hulk, mutations in functional genes usually lead to harmful traits. In our evolutionary past, those traits would have been largely removed from the gene pool by selection, making them rare or nonexistent in modern humans. Today we have modern medicine; a double-edged sword.

Mutations leading to super-human traits are very, very unlikely. The myostatin gene, for example, suppresses muscle growth. And yet the mutations that lead to little or no secretion of the related myostatin protein are very uncommon. Obviously they have not been favored by selection, even though their holders are very muscular – e.g., Germany’s “Incredible Hulky” ().

Okay, back to FH. Xanthelasmas are relatively common among those who suffer from FH (see photo below, from Globalskinatlas.com). They are skin deposits of cholesterol, have a genetic basis, and are NOT always associated with FH. This is important – several people have xanthelasmas but not FH.

FH is a fairly rare disease, even in its heterozygous form, with an overall incidence of approximately 0.2 percent. That is, about 1 in 500 people in the general population will have it. Genetically related groups will see a much higher or lower rate of incidence, as the disease is strongly influenced by a genetic mutation. This genetic mutation is apparently in the LDL receptor gene, located on the short arm of chromosome 19.

The table below, from a study by Miltiadous and colleagues (), paints a broad picture of the differences one would typically see between heterozygous FH sufferers and non-FH controls.

The main difference is in total cholesterol and in the relatively large contribution of LDL to total cholesterol. A large difference is also seen in Apolipoprotein B (indicated as "Apo B"), which acts as a LDL transporter (not to be confused with a LDL receptor). The LDL cholesterol shown on the table is calculated through the Friedewald equation, which is notoriously imprecise at low triglyceride levels ().

Looking at the total cholesterol row on the table, and assuming that the numbers after the plus/minus signs are standard deviations, we can conclude that: (a) a little more than two-thirds of the heterozygous FH sufferers had total cholesterol levels falling in between 280 and 446; and (b) a little more than two-thirds of the non-FH controls had total cholesterol levels falling in between 135 and 225.

Keep in mind that about 13.5 percent {calculated as: (95-68)/2} of the non-FH controls had total cholesterol levels between 225 and 270. This is a nontrivial percentage; i.e., these may be a minority but are not rare individuals. Heterozygous FH sufferers are rare, at 0.2 percent of the general population. Moreover, about 2 percent of the non-FH controls had non-pathological total cholesterol levels between 270 and 315. That is not so rare either, amounting to an “incidence” 10 times higher than heterozygous FH.

What would happen if people with heterozygous FH were to replace refined carbohydrates and sugars with saturated fat and cholesterol in their diets? Very likely their already high total cholesterol would go up higher, in part because their HDL cholesterol would go up (). Still, how could they be sure that CVD progression would accelerate if they did that?

According to some studies, the higher HDL cholesterol would either be generally protective or associated with protective factors, even among those with FH (). One of those protective factors may be a more nutrient-dense diet, as many foods rich in cholesterol are very nutrient-dense – e.g., eggs, organ meats, and seafood.

This brings me to my main point in this post. It is mainstream practice to diagnose people with FH based on total and/or LDL cholesterol levels. But the main problem with FH is that it leads to early onset of CVD, which can be measured more directly through simple tests, such as intima-media thickness and related ultrasound plaque tests (). These are noninvasive tests, done in 5 minutes or so, and often covered by insurance.

Even if simple direct tests are not perfect, it seems utterly nonsensical to rely on cholesterol measures to diagnose and treat FH, given the possible overlap between pathological and non-pathological high total cholesterol levels.

How come evolution hasn’t made us immortal? Death, like sex, helps animal populations avoid extinction

Genes do not evolve, nor do traits that are coded for our genes. We say that they evolve to facilitate discourse, which is alright. Populations evolve. A new genotype appears in a population and then either spreads or disappears. If it spreads, then the population is said to be evolving with respect to that genotype. A genotype may spread to an entire population; in population genetics, this is called “fixation”.

(Human chromosomes capped by telomeres, the white areas at the ends. Telomere shortening is caused by oxidative stress, and seems to be associated with death of cells and organisms. Source: Wikipedia.)

Asexual reproduction is very uncommon among animals. The most accepted theory to explain this is that animal populations live in environments that change very quickly, and thus need a great deal of genetic diversity within them to cope with the change. Otherwise they disappear, and so do their genes. Asexual reproduction leads to dramatically less genetic diversity in populations than sexual reproduction.

Asexual reproduction is similar to cloning. Each new individual looks a lot like its single parent. This does not work well in populations where individuals live relatively long lives. And even 1 year may be too long in this respect. It is just too much time to wait for a possible new mutation that will bring in some genetic diversity. To complicate matters, genetic mutation does not occur very often, and most genetic mutations are neutral with respect to the phenotype (i.e., they don’t code for any trait).

This is not so much of a problem for species whose members reproduce extremely fast; e.g., produce a new generation in less than 1 hour. A fast-reproducing species usually has a short lifespan as well. Accordingly, asexual reproduction is common among short-lived and fast-reproducing unicellular organisms and pathogens that have no cell structure like viruses.

Bacteria and viruses, in particular, form a part of the environment in which animals live that require animal populations to have a large amount of genetic diversity. Animal populations with low genetic diversity are unlikely to be able to cope with the barrage of diseases caused by these fast-mutating parasites.

We make sex chiefly because of the parasites.

And what about death? What does it bring to the table for a population?

Let us look at the other extreme – immortality. Immortality is very problematic in evolutionary terms because a population of immortal individuals would quickly outgrow its resources. That would happen too fast for the population to evolve enough intelligence to be able to use resources beyond those that were locally available.

In this post I assume that immortality is not the same as indestructibility. Here immortality is equated to the absence of aging as we know it. In this sense, immortals can still die by accident or due to disease. They simply do not age. For immortals, susceptibility to disease does not go up with age.

One could argue that a population of immortal individuals who did not reproduce would have done just fine. But that is not correct, because in this case immortality would be akin to cloning, but worse. Genetic diversity would not grow, as no mutations would occur. The fixed population of immortals would be unable to cope with fast-mutating parasites.

There is so much selection pressure against immortality in nature that it is no surprise that animals of very few species live more than 60 years on average. Humans are at the high end of the longevity scale. They are there for a few reasons. One is that our ancestors had offspring that required extra care, which led to an increase in the parents’ longevity. The offspring required extra care chiefly because of their large brains.

That increase in longevity was likely due to genetic mutations that helped our ancestors extend a lifespan that was programmed to be relatively short. Immortality is not a sound strategy for population survival, and thus there are probably many mechanisms through which it is prevented.

Death is evolution’s main ally. Sex is a very good helper. Both increase genetic diversity in populations.

We can use our knowledge of evolution to live better today. The aging clock can be slowed significantly via evolutionarily sound diet and lifestyle changes, essentially because some of our modern diet and lifestyle choices accelerate aging a lot. But diet and lifestyle changes probably will not make people live to 150.

If we want to become immortal, as we understand it in our current human form, ultimately we may want to beat evolution. In this sense, only very intelligent beings can become immortal.

Maybe we can achieve that by changing our genes, or by learning how to transfer our consciousness “software” into robots. In doing so, however, we may become something different; something that is not human and thus doesn’t see things in the same way as a human does. A conscious robot, without the hormones that so heavily influence human behavior, may find that being alive is pointless.

There is another problem. What if the only natural way to achieve some form of immortality is through organic death, but in a way that we don’t understand? This is not a matter of faith or religion. There are many things that we don’t know for sure. This is probably the biggest mystery of all; one that we cannot unravel in our current human state.

Human traits are distributed along bell curves: You need to know yourself, and HCE can help

Most human traits (e.g., body fat percentage, blood pressure, propensity toward depression) are influenced by our genes; some more than others. The vast majority of traits are also influenced by environmental factors, the “nurture” part of the “nature-nurture” equation. Very few traits are “innate”, such as blood type.

This means that manipulating environmental factors, such as diet and lifestyle, can strongly influence how the traits are finally expressed in humans. But each individual tends to respond differently to diet and lifestyle changes, because each individual is unique in terms of his or her combination of “nature” and “nurture”. Even identical twins are different in that respect.

When plotted, traits that are influenced by our genes are distributed along a bell-shaped curve. For example, a trait like body fat percentage, when measured in a population of 1000 individuals, will yield a distribution of values that will look like a bell-shaped distribution. This type of distribution is also known in statistics as a “normal” distribution.

Why is that?

The additive effect of genes and the bell curve

The reason is purely mathematical. A measurable trait, like body fat percentage, is usually influenced by several genes. (Sometimes individual genes have a very marked effect, as in genes that “switch on or off” other genes.) Those genes appear at random in a population, and their various combinations spread in response to selection pressures. Selection pressures usually cause a narrowing of the bell-shaped curve distributions of traits in populations.

The genes interact with environmental influences, which also have a certain degree of randomness. The result is a massive combined randomness. It is this massive randomness that leads to the bell-curve distribution. The bell curve itself is not random at all, which is a fascinating aspect of this phenomenon. From “chaos” comes “order”. A bell curve is a well-defined curve that is associated with a function, the probability density function.

The underlying mathematical reason for the bell shape is the central limit theorem. The genes are combined in different individuals as combinations of alleles, where each allele is a variation (or mutation) of a gene. An allele set, for genes in different locations of the human DNA, forms a particular allele combination, called a genotype. The alleles combine their effects, usually in an additive fashion, to influence a trait.

Here is a simple illustration. Let us say one generates 1000 random variables, each storing 10 random values going from 0 to 1. Then the values stored in each of the 1000 random variables are added. This mimics the additive effect of 10 genes with random allele combinations. The result are numbers ranging from 1 to 10, in a population of 1000 individuals; each number is analogous to an allele combination. The resulting histogram, which plots the frequency of each allele combination (or genotype) in the population, is shown on the figure bellow. Each allele configuration will “push for” a particular trait range, making the trait distribution also have the same bell-shaped form.

The bell curve, research studies, and what they mean for you

Studies of the effects of diet and exercise on health variables usually report their results in terms of average responses in a group of participants. Frequently two groups are used, one control and one treatment. For example, in a diet-related study the control group may follow the Standard American Diet, and the treatment group may follow a low carbohydrate diet.

However, you are not the average person; the average person is an abstraction. Research on bell curve distributions tells us that there is about a 68 percentage chance that you will fall within a 1 standard deviation from the average, to the left or the right of the “middle” of the bell curve. Still, even a 0.5 standard deviation above the average is not the average. And, there is approximately a 32 percent chance that you will not be within the larger -1 to 1 standard deviation range. If this is the case, the average results reported may be close to irrelevant for you.

Average results reported in studies are a good starting point for people who are similar to the studies’ participants. But you need to generate your own data, with the goal of “knowing yourself through numbers” by progressively analyzing it. This is akin to building a “numeric diary”. It is not exactly an “N=1” experiment, as some like to say, because you can generate multiple data points (e.g., N=200) on how your body alone responds to diet and lifestyle changes over time.

HealthCorrelator for Excel (HCE)

I think I have finally been able to develop a software tool that can help people do that. I have been using it myself for years, initially as a prototype. You can see the results of my transformation on this post. The challenge for me was to generate a tool that was simple enough to use, and yet powerful enough to give people good insights on what is going on with their body.

The software tool is called HealthCorrelator for Excel (HCE). It runs on Excel, and generates coefficients of association (correlations, which range from -1 to 1) among variables and graphs at the click of a button.

This 5-minute YouTube video shows how the software works in general, and this 10-minute video goes into more detail on how the software can be used to manage a specific health variable. These two videos build on a very small sample dataset, and their focus is on HDL cholesterol management. Nevertheless, the software can be used in the management of just about any health-related variable – e.g., blood glucose, triglycerides, muscle strength, muscle mass, depression episodes etc.

You have to enter data about yourself, and then the software will generate coefficients of association and graphs at the click of a button. As you can see from the videos above, it is very simple. The interpretation of the results is straightforward in most cases, and a bit more complicated in a smaller number of cases. Some results will probably surprise users, and their doctors.

For example, a user who is a patient may be able to show to a doctor that, in the user’s specific case, a diet change influences a particular variable (e.g., triglycerides) much more strongly than a prescription drug or a supplement. More posts will be coming in the future on this blog about these and other related issues.

The evolution of costly traits: Competing for women can be unhealthy for men

There are human traits that evolved in spite of being survival handicaps. These counterintuitive traits are often called costly traits, or Zahavian traits (in animal signaling contexts), in honor of the evolutionary biologist Amotz Zahavi (Zahavi & Zahavi, 1997). I have written a post about this type of traits, and also an academic article (Kock, 2009). The full references and links to these publications are at the end of this post.

The classic example of costly trait is the peacock’s train, which is used by males to signal health to females. (Figure below from: animals.howstuffworks.com.) The male peacock’s train (often incorrectly called “tail”) is a costly trait because it impairs the ability of a male to flee predators. It decreases a male’s survival success, even though it has a positive net effect on the male’s reproductive success (i.e., the number of offspring it generates). It is used in sexual selection; the females find big and brightly colored trains with many eye spots "sexy".

So costly traits exist in many species, including the human species, but we have not identified them all yet. The implication for human diet and lifestyle choices is that our ancestors might have evolved some habits that are bad for human survival, and moved away from others that are good for survival. And I am not only talking about survival among modern humans; I am talking about survival among our human ancestors too.

The simple reason for the existence of costly traits in humans is that evolution tends to maximize reproductive success, not survival, and that applies to all species. (Inclusive fitness theory goes a step further, placing the gene at the center of the selection process, but this is a topic for another post.) If that were not the case, rodent species, as well as other species that specialize in fast reproduction within relatively short life spans, would never have evolved.

Here is an interesting piece of news about research done at the University of Michigan. (I have met the lead researcher, Dan Kruger, a couple of times at HBES conferences. My impression is that his research is solid.) The research illustrates the evolution of costly traits, from a different angle. The researchers argue, based on the results of their investigation, that competing for a woman’s attention is generally bad for a man’s health!

Very romantic ...

References:

Kock, N. (2009). The evolution of costly traits through selection and the importance of oral speech in e-collaboration. Electronic Markets, 19(4), 221-232.

Zahavi, A. & Zahavi, A. (1997). The Handicap Principle: A missing piece of Darwin’s puzzle. Oxford, England: Oxford University Press.

Pretty faces are average faces: Genetic diversity and health

Many people think that the prettiest faces are those with very unique features. Generally that is not true. Pretty faces are average faces. And that is not only because they are symmetrical, even though symmetry is an attractive facial trait. Average faces are very attractive, which is counterintuitive but makes sense in light of evolution and genetics.

The faces in the figure below (click to enlarge) are from a presentation I gave at the University of Houston in 2008. The PowerPoint slides file for the presentation is available here. The photos were taken from the German web site Beautycheck.de. This site summarizes a lot of very interesting research on facial attractiveness.

The face on the right is a composite of the two faces on the left. It simulates what would happen if you were to morph the features of the two faces on the left into the face on the right. That is, the face on the right is the result of an “averaging” of the two faces on the left.

If you show these photos to a group of people, like I did during my presentation in Houston, most of the people in the group will say that the face on the right is the prettiest of the three. This happens even though most people will also say that each of the three faces is pretty, if shown each face separately from the others.

Why are average faces more beautiful?

The reason may be that we have brain algorithms that make us associate a sense of “beauty” with features that suggest an enhanced resistance to disease. This is an adaptation to the environments our ancestors faced in our evolutionary past, when disease would often lead to observable distortions of facial and body traits. Average faces are the result of increased genetic mixing, which leads to increased resistance to disease.

This interpretation is a variation of Langlois and Roggman’s “averageness hypothesis”, published in a widely cited 1990 article that appeared in the journal Psychological Science.

By the way, many people think that the main survival threats ancestral humans faced were large predators. I guess it is exciting to think that way; our warrior ancestors survived due to their ability to fight off predators! The reality is that, in our ancestral past, as today, the biggest killer of all by far was disease. The small organisms, the ones our ancestors couldn’t see, were the most deadly.

People from different populations, particularly those that have been subjected to different diseases, frequently carry genetic mutations that protect them from those diseases. Those are often carried as dominant alleles (i.e., variations of a gene). When two people with diverse genetic protections have children, the children inherit the protective mutations of both parents. The more genetic mixing, the more likely it is that multiple protective genetic mutations will be carried. The more genetic mixing, the higher is the "averageness" score of the face.

The opposite may happen when people who share many genes (e.g., cousins) have children. The term for this is inbreeding. Since alleles that code for diseases are often carried in recessive form, a child of closely related parents has a higher chance of having a combination of two recessive disease-promoting alleles. In this case, the child will be homozygous recessive for the disease, which will increase dramatically its chances of developing the disease.

In a nutshell: gene mixing = health; inbreeding = disease.

Finally, if you have some time, make sure to take a look at this page on the Virtual Miss Germany!

Genetic clustering of metabolic disorders: Meet your relatives

As noted in this post, it is possible for a food-related trait to evolve to fixation in an entire population in as little as 396 years; not the millions of years that some believe are necessary for mutations to spread.

Moreover, evolution through fixation can occur in the absence of any selective pressure. That is, traits that are neutral with respect to fitness may evolve by chance, particularly in small populations. (A group of 100 individuals who made it to the Americas after a long and grueling trek would fit the bill.) This rather counterintuitive phenomenon is known as genetic drift (Hartl & Clark, 2007; Maynard Smith, 1998).

Fast evolution of traits certainly applies to polygenic traits, such as traits associated with nutrient metabolism. Polygenic traits are traits that are influenced by multiple genes, with those genes acting together to influence the expression of the trait.

Moreover, a mutation in one single pleiotropic gene (a gene that influences various traits) can lead to dramatic changes in interconnected phenotypic traits. This includes traits associated with complex processes involving multiple body tissues, such as glucose and fat metabolism.

Some disagree, arguing that complex traits need much longer to evolve. I wish I could be convinced of that; it would make our understanding of health issues and related predictions a lot easier. For example, we could zero in on Homo erectus as our target for an ideal Paleolithic diet.

Unfortunately, when you look around, you see people with food allergies, metabolic disorders, and other food- and lifestyle-related complications; and those problems cluster among people who seem to share recent common ancestors. Interestingly, in many cases those people do not look alike, in spite of sharing common ancestors.

For example, here in South Texas, it is clear that people from Amerindian ancestry (like me, although mine is from South America) are a lot more predisposed to diabetes than others. There are exceptions, of course; we are talking about probabilities here. Especially common here in South Texas are people with South and Central American Indian ancestry; less common but also represented are descendants of North American Indian tribes such as the Kickapoos.

Very recent food inventions, such as refined carbohydrates, refined sugars, omega-6-rich vegetable oils, and hydrogenated fats are too new to have influenced the genetic makeup of anybody living today. So, chances are, they are bad for the vast majority of us. Sure, a small percentage of the population may not develop any hint of diseases of civilization after consuming them for years, but chances are they are not going to be as healthy as they could be.

Other not so recent food inventions, such as olive oil, certain types of bread, certain types of dairy etc. may be better, in terms of overall health effects, for some people than for others. In fact, they may be particularly health-promoting for certain groups of individuals. The reason may be found in inherited metabolic traits. Learning about your ancestors could be helpful in this respect. The problem is that many people's ancestry is quite mixed; again, I give myself as an example - South American Indian, German, Italian, Portuguese ... and who knows what else.

Another, easier and perhaps more effective, way to figure out what particular foods, and in what quantities, may be healthy for you is to keep in touch with close and distant biological relatives; e.g., grandparents, parents, siblings, cousins (family gathering photo below from: www.lega.co.uk). It is likely that you share genes with them. If several of them developed a particular disease, and they consumed a lot of a certain type of food prior to that, then maybe that food should not be part of your diet.

This may also help you avoid making serious mistakes regarding health issues by acting too fast in response to laboratory test results. Relatives may share some quirky metabolic responses, which could be indicative of a disease at first glance and actually have no negative long term effects, and perhaps some positive ones.

For example, let us assume that a person, let us call her Mary, is in her early 50s and has been consuming a diet rich in refined carbohydrates and sugars for her entire life. Her fasting blood glucose looks pretty good at around 82 mg/dL.

Mary then adopts a diet that includes only vegetables and animal fat and protein. This new diet induces mild ketosis. She then notices that her fasting blood sugar is now 113 mg/dL, much higher than the previous 82 mg/dL. Mary’s doctor tells her that she may be pre-diabetic.

Mary knows that the change in diet was associated with the increase in fasting blood sugar, and reverts back to her diet rich in refined carbohydrates and sugars. Her fasting blood sugar goes down to 82 mg/dL, and she is happy. Her doctor congratulates her. However, she becomes obese and develops the metabolic syndrome in her late 50s, and several related diseases soon after.

Let us now look at a different scenario. After getting the 113 mg/dL fasting blood sugar reading on a mildly ketogenic diet, Mary talks to as many of her living relatives as she can. She asks many questions and finds out that a few of them were big meat and veggie eaters and had the same metabolic response. They are in their 60s and 70s and have no hint of diabetes. In fact, they are relatively lean and fairly healthy. She then sticks to her diet of only vegetables and animal fat and protein for life, and never develops the metabolic syndrome.

This fictitious case is based on the idea that low carbohydrate diets that induce mild ketosis may also induce physiological (not pathological) insulin resistance, leading to a version of the much talked about dawn phenomenon. This phenomenon, in this context, seems to be related to our good friend, but much maligned, palmitic acid. Several bloggers discussed it in excellent posts. Peter at Hyperlipid blogged about it here and here; Stephan at Whole Health Source blogged about it here.

Now, going back to keeping in touch with close and distant relatives. It is important to check your relatives’ lifestyle patterns as well, because diet is not everything, even though it is a major contributor to health outcomes. By lifestyle patterns I mean things like level and type of physical activity, sunlight exposure (which strongly influences vitamin D levels), and frequency and quality of social interactions (which reduce stress).

Regarding social interactions, it is worth noting that humans are highly social beings, and social isolation is almost universally detrimental to both mental and physical health.

References:

Hartl, D.L., & Clark, A.G. (2007). Principles of population genetics. Sunderland, MA: Sinauer Associates.

Maynard Smith, J. (1998). Evolutionary genetics. New York, NY: Oxford University Press.

Lucy was a vegetarian and sapiens an omnivore: Plant foods as natural supplements

Early hominid ancestors like the Australopithecines (e.g., Lucy) were likely strict vegetarians. Meat consumption seems to have occurred at least occasionally among Homo habilis, with more widespread consumption among Homo erectus, and Homo sapiens (i.e., us).

The figure below (from: becominghuman.org; click on it to enlarge) shows a depiction of the human lineage, according to a widely accepted theory developed by Ian Tattersall. As you can see, Neanderthals are on a different branch, and are not believed to have been part of the human lineage.

Does the clear move toward increased meat consumption mean that a meat-only diet is optimal for you?

The answer is “perhaps”; especially if your ancestors were Inuit and you retained their genetic adaptations.

Food specialization tends to increase the chances of extinction of a species, because changes in the environment may lead to the elimination of a single food source, or a limited set of food sources. On a scale from highly specialized to omnivorous, evolution should generally favor adaptations toward the omnivorous end of the scale.

Meat, which naturally comes together with fat, has the advantage of being an energy-dense food. Given this advantage, it is possible that the human species evolved to be exclusively meat eaters, with consumption of plant foods being mostly optional. But this goes somewhat against what we know about evolution.

Consumption of plant matter AND meat – that is, being an omnivore – leads to certain digestive tract adaptations, which would not be present if they were not absolutely necessary. Those adaptations are too costly to be retained without a good reason.

The digestive tract of pure carnivores is usually shorter than that of omnivores. Growing a longer digestive tract and keeping it healthy during a lifetime is a costly proposition.

Let us assume that an ancient human group migrated to a geographical area that forced them to adhere to a particular type of diet, like the ancient Inuit. They would probably have evolved adaptations to that diet. This evolution would not have taken millions of years to occur; it might have taken place in as little as 396 years, if not less.

In spite of divergent adaptations that might have occurred relatively recently (i.e., in the last 100,000 years, after the emergence of our species), among the Inuit for instance, we likely have also species-wide adaptations that make an omnivorous diet generally optimal for most of us.

Meat appears to have many health-promoting and a few unhealthy properties. Plant foods have many health-promoting properties, and thus may act like “natural supplements” to a largely meat-based diet. As Biesalski (2002) put it as part of a discussion of meat and cancer:

“… meat consists of a few, not clearly defined cancer-promoting and a lot of cancer-protecting factors. The latter can be optimized by a diet containing fruit and vegetables, which contain hundreds of more or less proven bioactive constituents, many of them showing antioxidative and anticarcinogenic effects in vitro.”

Reference:

Biesalski, H.K. (2002). Meat and cancer: Meat as a component of a healthy diet. European Journal of Clinical Nutrition, 56(1), S2-S11.