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.

Beyond Ötzi: European Evolutionary History and its Relevance to Diet. Part III

In previous posts, I reviewed some of the evidence suggesting that human evolution has accelerated rapidly since the development of agriculture (and to some degree, before it).  Europeans (and other lineages with a long history of agriculture)  carry known genetic adaptations to the Neolithic diet, and there are probably many adaptations that have not yet been identified.  In my final post in this series, I'll argue that although we've adapted, the adaptation is probably not complete, and we're left in a sort of genetic limbo between the Paleolithic and Neolithic state. 

Recent Genetic Adaptations are Often Crude

It may at first seem strange, but many genes responsible for common genetic disorders show evidence of positive selection.  In other words, the genes that cause these disorders were favored by evolution at some point because they presumably provided a survival advantage.  For example, the sickle cell anemia gene protects against malaria, but if you inherit two copies of it, you end up with a serious and life-threatening disorder (1).  The cystic fibrosis gene may have been selected to protect against one or more infectious diseases, but again if you get two copies of it, quality of life and lifespan are greatly curtailed (2, 3).  Familial Mediterranean fever is a very common disorder in Mediterranean populations, involving painful inflammatory attacks of the digestive tract, and sometimes a deadly condition called amyloidosis.  It shows evidence of positive selection and probably protected against intestinal disease due to the heightened inflammatory state it confers to the digestive tract (4, 5).  Celiac disease, a severe autoimmune reaction to gluten found in some grains, may be a by-product of selection for protection against bacterial infection (6).  Phenylketonuria also shows evidence of positive selection (7), and the list goes on.  It's clear that a lot of our recent evolution was in response to new disease pressures, likely from increased population density, sendentism, and contact with domestic animals.

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Beyond Ötzi: European Evolutionary History and its Relevance to Diet. Part I

In the previous post, I explained that Otzi descended in large part from early adopters of agriculture in the Middle East or nearby.  What I'll explain in further posts is that Otzi was not a genetic anomaly: he was part of a wave of agricultural migrants that washed over Europe thousands of years ago, spreading their genes throughout.  Not only that, Otzi represents a halfway point in the evolutionary process that transformed Paleolithic humans into modern humans.

Did Agriculture in Europe Spread by Cultural Transmission or by Population Replacement?

There's a long-standing debate in the anthropology community over how agriculture spread throughout Europe.  One camp proposes that agriculture spread by a cultural route, and that European hunter-gatherers simply settled down and began planting grains.  The other camp suggests that European hunter-gatherers were replaced (totally or partially) by waves of agriculturalist immigrants from the Middle East that were culturally and genetically better adapted to the agricultural diet and lifestyle.  These are two extreme positions, and I think almost everyone would agree at this point that the truth lies somewhere in between: modern Europeans are a mix of genetic lineages, some of which originate from the earliest Middle Eastern agriculturalists who expanded into Europe, and some of which originate from indigenous hunter-gatherer groups including a small contribution from neanderthals.  We know that modern-day Europeans are not simply Paleolithic mammoth eaters who reluctantly settled down and began farming. 

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Lessons From Ötzi, the Tyrolean Ice Man. Part I

This is Otzi, or at least a reconstruction of what he might have looked like.  5,300 years ago, he laid down on a glacier near the border between modern-day Italy and Austria, under unpleasant circumstances.  He was quickly frozen into the glacier.  In 1991, his slumber was rudely interrupted by two German tourists, which eventually landed him in the South Tyrol Museum of Archaeology in Italy. 

Otzi is Europe's oldest natural human mummy, and as such, he's an important window into the history of the human species in Europe.  His genome has been sequenced, and it offers us clues about the genetic history of modern Europeans.

Otzi's Story

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Eocene Diet Follow-up

Now that WHS readers around the globe have adopted the Eocene Diet and are losing weight at an alarming rate, it's time to explain the post a little more.  First, credit where credit is due: Melissa McEwen made a similar argument in her 2011 AHS talk, where she rolled out the "Cambrian Explosion Diet", which beats the Eocene Diet by about 470 million years.  It was probably in the back of my head somewhere when I came up with the idea.

April Fools day is good for a laugh, but humor often has a grain of truth in it.  In this case, the post was a jumping off point for discussing human evolution and what it has to say about the "optimal" human diet, if such a thing exists.  Here's a preview: evolution is a continuous process that has shaped our ancestors' genomes for every generation since the beginning of life.  It didn't end with the Paleolithic, in fact it accelerated, and most of us today carry meaningful adaptations to the Neolithic diet and lifestyle. 

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New Obesity Review Paper by Yours Truly

The Journal of Clinical Endocrinology and Metabolism just published a clinical review paper written by myself and my mentor Dr. Mike Schwartz, titled "Regulation of Food Intake, Energy Balance, and Body Fat Mass: Implications for the Pathogenesis and Treatment of Obesity" (1).  JCEM is one of the most cited peer-reviewed journals in the fields of endocrinology, obesity and diabetes, and I'm very pleased that it spans the gap between scientists and physicians.  Our paper takes a fresh and up-to-date look at the mechanisms by which food intake and body fat mass are regulated by the body, and how these mechanisms are altered in obesity.  We explain the obesity epidemic in terms of the mismatch between our genes and our current environment, a theme that is frequently invoked in ancestral health circles.

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What Causes Insulin Resistance? Part IV

So far, we've explored three interlinked causes of insulin resistance: cellular energy excess, inflammation, and insulin resistance in the brain.  In this post, I'll explore the effects on micronutrient status on insulin sensitivity.

Micronutrient Status

There is a large body of literature on the effects of nutrient intake/status on insulin action, and it's not my field, so I don't intend this to be a comprehensive post.  My intention is simply to demonstrate that it's important, and highlight a few major factors I'm aware of.

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What Causes Insulin Resistance? Part I

Insulin is an ancient hormone that influences many processes in the body.  Its main role is to manage circulating concentrations of nutrients (principally glucose and fatty acids, the body's two main fuels), keeping them within a fairly narrow range*.  It does this by encouraging the transport of nutrients into cells from the circulation, and discouraging the export of nutrients out of storage sites, in response to an increase in circulating nutrients (glucose or fatty acids). It therefore operates a negative feedback loop that constrains circulating nutrient concentrations.  It also has many other functions that are tissue-specific.

Insulin resistance is a state in which cells lose sensitivity to the effects of insulin, eventually leading to a diminished ability to control circulating nutrients (glucose and fatty acids).  It is a major contributor to diabetes risk, and probably a contributor to the risk of cardiovascular disease, certain cancers and a number of other disorders. 

Why is it important to manage the concentration of circulating nutrients to keep them within a narrow range?  The answer to that question is the crux of this post. 

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Does High Circulating Insulin Drive Body Fat Accumulation? Answers from Genetically Modified Mice

The house mouse Mus musculus is an incredible research tool in the biomedical sciences, due to its ease of care and its ability to be genetically manipulated.  Although mice aren't humans, they resemble us closely in many ways, including how insulin signaling works.  Genetic manipulation of mice allows researchers to identify biological mechanisms and cause-effect relationships in a very precise manner.  One way of doing this is to create "knockout" mice that lack a specific gene, in an attempt to determine that gene's importance in a particular process.  Another way is to create transgenic mice that express a gene of interest, often modified in some way.  A third method is to use an extraordinary (but now common) tool called "Cre-lox" recombination (1), which allows us to delete or add a single gene in a specific tissue or cell type. 

Studying the relationship between obesity and insulin resistance is challenging, because the two typically travel together, confounding efforts to determine which is the cause and which is the effect of the other (or neither).  Some have proposed the hypothesis that high levels of circulating insulin promote body fat accumulation*.  To truly address this question, we need to consider targeted experiments that increase circulating insulin over long periods of time without altering a number of other factors throughout the body.  This is where mice come in.  Scientists are able to perform precise genetic interventions in mice that increase circulating insulin over a long period of time.  These mice should gain fat mass if the hypothesis is correct. 

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The Case for the Food Reward Hypothesis of Obesity, Part II

In this post, I'll explore whether or not the scientific evidence is consistent with the predictions of the food reward hypothesis, as outlined in the last post.

Before diving in, I'd like to address the critique that the food reward concept is a tautology or relies on circular reasoning (or is not testable/falsifiable).  This critique has no logical basis.  The reward and palatability value of a food is not defined by its effect on energy intake or body fatness.  In the research setting, food reward is measured by the ability of food or food-related stimuli to reinforce or motivate behavior (e.g., 1).  In humans, palatability is measured by having a person taste a food and rate its pleasantness in a standardized, quantifiable manner, or sometimes by looking at brain activity by fMRI or related techniques (2).  In rodents, it is measured by observing stereotyped facial responses to palatable and unpalatable foods, which are similar to those seen in human infants.  It is not a tautology or circular reasoning to say that the reinforcing value or pleasantness of food influences food intake and body fatness. These are quantifiable concepts and as I will explain, their relationship with food intake and body fatness can be, and already has been, tested in a controlled manner. 

1.   Increasing the reward/palatability value of the diet should cause fat gain in animals and humans

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A Roadmap to Obesity

In this post, I'll explain my current understanding of the factors that promote obesity in humans.  

Heritability

To a large degree, obesity is a heritable condition.  Various studies indicate that roughly two-thirds of the differences in body fatness between individuals is explained by heredity*, although estimates vary greatly (1).  However, we also know that obesity is not genetically determined, because in the US, the obesity rate has more than doubled in the last 30 years, consistent with what has happened to many other cultures (2).  How do we reconcile these two facts?  By understanding that genetic variability determines the degree of susceptibility to obesity-promoting factors.  In other words, in a natural environment with a natural diet, nearly everyone would be relatively lean, but when obesity-promoting factors are introduced, genetic makeup determines how resistant each person will be to fat gain.  As with the diseases of civilization, obesity is caused by a mismatch between our genetic heritage and our current environment.  This idea received experimental support from an interesting recent study (3).

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We share an ancestor who probably lived no more than 640 years ago

We all evolved from one single-celled organism that lived billions of years ago. I don’t see why this is so hard for some people to believe, given that all of us also developed from a single fertilized cell in just 9 months.

However, our most recent common ancestor is not that first single-celled organism, nor is it the first Homo sapiens, or even the first Cro-Magnon.

The majority of the people who read this blog probably share a common ancestor who lived no more than 640 years ago.

You and I, whoever you are, have each two parents. Each of our parents have (or had) two parents, who themselves had two parents. And so on.

If we keep going back in time, and assume that you and I do not share a common ancestor, there will be a point where the theoretical world population would have to be impossibly large.

Assuming a new generation coming up every 20 years, and going backwards in time, we get a theoretical population chart like the one below. The theoretical population grows in an exponential, or geometric, fashion.

As we move back in time the bars go up in size. Beyond a certain point their sizes go up so fast that you have to segment the chart. Otherwise the bars on the left side of the chart disappear in comparison to the ones on the right side (as several did on the chart above). Below is the section of the chart going back to the year 1371.

The year 1371 is a mere 640 years ago. And what is the theoretical population in that year if we assume that you and I have no common ancestors? The answer is: more than 8.5 billion people. We know that is not true.

Admittedly this is a somewhat simplistic view of this phenomenon, used here primarily to make a point. For example, it is possible that a population of humans became isolated 15 thousand years ago, remained isolated to the present day, and that one of their descendants just happened to be around reading this blog today.

Perhaps the most widely cited article discussing this idea is this one by Joseph T. Chang, published in the journal Advances in Applied Probability. For a more accessible introduction to the idea, see this article by Joe Kissell.

Estimates vary based on the portion of the population considered. There are also assumptions that have to be made based on migration and mating patterns, as well as the time for each generation to emerge and the stability of that number over time.

Still, most people alive today share a common ancestor who lived a lot more recently than they think. In most cases that common ancestor probably lived less than 640 years ago.

And who was that common ancestor? That person was probably a man who, due to a high perceived social status, had many consorts, who gave birth to many children. Someone like Genghis Khan.

Swine and Mankind

Nancy and I have been enjoying some locally-produced, hazelnut-finished, red wattle pork. We purchased it from Heritage Farms Northwest. The oil in the hazelnuts results in a pork fat that’s significantly softer than other pork, indicating a lower saturated fat content. The red wattle is a relatively rare breed of hog, and definitely NOT a producer of “the other white meat.” Last Sunday we enjoyed a breakfast of scrambled eggs with some diced grilled pork chop (including the thick layer of fat, of course!) and caramelized onions. Very rich. This one meal carried us both until well past our usual dinner time. Each of us finally ate something later that evening, more because we felt it was time than feeling all that hungry. Fat satisfies. Fat “sticks to your ribs.” Carbohydrates do not satisfy. The sensation of hunger returns more quickly on carbohydrate-based diets than on fat-based ones. Swine have been the source of dietary fat and protein for some time.

Archaeological evidence indicates that swine were first domesticated about 9000 BCE in the East Indies and southeastern Asia. Swine have been especially amenable to human selection. Many different breeds have been developed over the years. Interestingly, pigs can change back just as easily. When given the opportunity, pigs promptly revert within only a few generations to a wild or feral state in which they acquire the body form and characteristics of their wild progenitors many generations removed.

Swine were introduced to North America by Hernando De Soto in 1539. Their importance to the subsequent history of this continent (and the rest of the world) is hard to over-state. Beginning with their unforeseeable role as a vector for zoonotic diseases (diseases transmissible from animals to humans) that decimated the native American population, continuing through their subsequent role in sustaining the mostly-rural population of the developing nation, and ultimately forming the foundation of Midwestern US agriculture. And the pig’s importance is not limited to North America, which is home to less than 12% of the world’s hogs.

“World distribution of swine, by major areas. (Based on estimates from the FAO Production Yearbook, FAO/UN, Rome, Italy, 1994, pp. 192-194, Table 90).” From Ensminger, M.E. and R.O. Parker.

When one compares the modern pig with its ancestor, the European wild boar, it is obvious how much “gentic manipulation” has taken place! Not through some high-tech approach, obviously, but by a long process of selecting for desirable traits and against negative ones. Disposition would be an obvious criteria!

The European wild boar. From Ensminger, M.E. and R.O. Parker.

But body structure and the degree of “finish” or fat would be others. Through the 19th century, lard-type hogs were favored because of the value of lard. This is reflected in the type of animal that was preferred in the livestock show-rings of that era.

“A Poland China gilt of the chuffy type. Small, refined animals of this type dominated the American show-ring from 1890-1919.” From Ensminger, M.E. and R.O. Parker.

But tastes changed and soon a taller animal was preferred. Fashion is fickle in the breed ring as well as on the designers' runways. It's interesting to note that this trend precedes the low-fat-is-the-healthy-diet message of the last half of the 20th century. Data from 1929 indicated that one average hog carcass provided enough meat for two people for a year, but enough for three people for a year. This over-production of lard was a significant problem, depressing hog prices.

“A Poland China boar pig of the rangy type. Long legged, weak loined, “cat hammed” animals of this type dominated the American show-ring from 1915-1925.” From Ensminger, M.E. and R.O. Parker.

Today’s animal has been selected to produce a maximum of lean meat with even less fat, in part as a response to the market’s demands (which, of coarse, is responding the “conventional wisdom” that animal fat is bad for us).

“1994 World Expo top placing Poland China boar.” From Ensminger, M.E. and R.O. Parker.

For anyone who doubts that genetics can make some constitutionally lean and others constitutionally heavy, look at the differences that genetics can play in the leanness of swine.

“Breeding made the difference! The hogs received the same ration and were slaughtered at the same weight. Not the difference in the amount of lean meat, with the hog on the left being superior.” From Ensminger, M.E. and R.O. Parker.

Consider the implications for humans! Some of us, due to our genetic inheritance, will tend to be leaner than others. Biology isn't fair. And an impaired metabolism may mean that we will carry more fat than if we had not incurred this metabolic damage. What we need to understand is what we must do to be as lean as we're capable of being.

Finally, I’ve heard that these lean hogs have to be raised in confinement with some degree of climate control because their lack of fat makes them susceptible to heat and cold. If we're going to raise livestock, we need to be aware of the conditions the various breeds were selected for.We'll need to choose breeds that match our conditions and management goals.

Next posts:
Lard, Glorious Lard! (the uses and benefits of lard)
Try, Try Again (rendering lard at home)

Reference
Ensminger, M.E. and R.O. Parker. 1997. Swine Science. Interstate Publishers, Inc.

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.

Obesity and the Brain

Nature Genetics just published a paper that caught my interest (1). Investigators reviewed the studies that have attempted to determine associations between genetic variants and common obesity (as judged by body mass index or BMI). In other words, they looked for "genes" that are suspected to make people fat.

There are a number of gene variants that associate with an increased or decreased risk of obesity. These fall into two categories: rare single-gene mutations that cause dramatic obesity, and common variants that are estimated to have a very small impact on body fatness. The former category cannot account for common obesity because it is far too rare, and the latter probably cannot account for it either because it has too little impact*. Genetics can't explain the fact that there were half as many obese people in the US 40 years ago. Here's a wise quote from the obesity researcher Dr. David L. Katz, quoted from an interview about the study (2):

Let us by all means study our genes, and their associations with our various shapes and sizes... But let's not let it distract us from the fact that our genes have not changed to account for the modern advent of epidemic obesity -- our environments and lifestyles have.

Exactly. So I don't usually pay much attention to "obesity genes", although I do think genetics contributes to how a body reacts to an unnatural diet/lifestyle. However, the first part of his statement is important too. Studying these types of associations can give us insights into the biological mechanisms of obesity when we ask the question "what do these genes do?" The processes these genes participate in should be the same processes that are most important in regulating fat mass.

So, what do the genes do? Of those that have a known function, nearly all of them act in the brain, and most act in known body fat regulation circuits in the hypothalamus (a brain region). The brain is the master regulator of body fat mass. It's also the master regulator of nearly all large-scale homeostatic systems in the body, including the endocrine (hormone) system. Now you know why I study the neurobiology of obesity.


* The authors estimated that "together, the 32 confirmed BMI loci explained 1.45% of the inter-individual variation in BMI." In other words, even if you were unlucky enough to inherit the 'fat' version of all 32 genes, which is exceedingly unlikely, you would only have a slightly higher risk of obesity than the general population.

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.

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.

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.