The PCSK9 enzyme, LDL cholesterol, and cardiovascular diseases

Cardiovascular diseases are currently the leading cause of death in most developed countries. They are particularly common among seniors; i.e., those aged 65 and older. Part of the reason for this is that infectious diseases do not kill as many people as they used to.

Given the trend toward population aging, with seniors making up an increasingly larger percentage of the population, the market for drugs against cardiovascular diseases is growing. A new class of such drugs is making the news lately; they target the PCSK9 enzyme ().

Enzymes are (usually) proteins that speed up chemical reactions, and are needed in virtually all metabolic processes that occur in cells. Proprotein convertase subtilisin/kexin type 9 (PCSK9) is an enzyme that degrades LDL cholesterol receptors on the surface of liver cells. Fewer LDL cholesterol receptors mean reduced uptake of the particles that carry LDL cholesterol, and thus more LDL particles in circulation. This may be problematic if these are small-dense LDL particles ().

Small-dense LDL particles include particles that are significantly smaller than the gaps in the endothelium (). The endothelium is a thin layer of cells that line the interior of arteries. Those gaps are about 25-26 nanometers (nm) in diameter. Small-dense LDL particles can contribute a lot more to the formation of atheromas (atherosclerotic plaques) in predisposed individuals than large-buoyant LDL particles.

There is evidence of the natural occurrence of low LDL cholesterol in individuals of African descent due to genetic mutations influencing PCSK9 levels (). This leads us to a very important question. By reducing PCSK9 in circulation, can we also reduce the incidence of cardiovascular disease?

The answer to this question depends on whether LDL cholesterol is a causative factor in cardiovascular disease. If it is, then reducing PCSK9 in circulation can indeed reduce the incidence of cardiovascular disease. The problem is that, most of the evidence so far suggests that LDL cholesterol is NOT a causative factor in cardiovascular disease.

Yes, there are studies that show that LDL cholesterol is correlated with cardiovascular disease, but the problem is that LDL cholesterol is a marker of other factors that are better candidates for causes of cardiovascular disease – hence the correlation. For example, LDL cholesterol goes up with mental stress (), and chronic mental stress seems to be a good candidate for a cause of cardiovascular disease.

LDL cholesterol is also a marker of a diet with more saturated fat in it (). In many contexts, a diet with more saturated fat in it is a more nutritious diet, which leads to a negative association between LDL cholesterol and mortality.

The graph below shows the shape of the association between total cholesterol (TOTCHOL) and mortality from all cardiovascular diseases (MVASC), based on an analysis of the China Study II dataset (). LDL cholesterol is the main component of total cholesterol in most people. The values are provided in standardized format; e.g., 0 is the average, 1 is one standard deviation above the mean, and so on. The best-fitting curve was obtained with the software WarpPLS ().

In fact, when we combine the totality of the evidence linking LDL cholesterol and cardiovascular diseases, LDL cholesterol seems to come out as a marker of protective factors. A reflection of this is a widely cited study by Weverling-Rijnsburger and colleagues, of LDL and HDL cholesterol as factors in cardiovascular diseases among people aged 85 and older (). The conclusions of the study were that:

- There was no association between LDL cholesterol level and risk of fatal cardiovascular disease.

- A low HDL cholesterol level was associated with a two-fold higher risk of fatal cardiovascular disease.

- Both low LDL cholesterol and low HDL cholesterol levels were associated with an increased mortality risk from infections.

The results above are particularly interesting because the study participants, given their ages, were at a high risk of mortality from cardiovascular diseases. It seems that the best scenario for these folks would have been a concomitant increase in both LDL and HDL cholesterol levels, which seems to be exactly what happens when one increases his or her intake of foods rich in saturated fat and dietary cholesterol ()!

Should you take a drug that targets the PCSK9 enzyme, to reduce your LDL cholesterol? Maybe you should ask Peter ().

Ischemic heart disease among Greenland Inuit: Data from 1962 to 1964

The traditional Inuit diet is very high in animal protein and fat. It also includes plant matter. Typically it is made up primarily of the following: fish, walrus, seal, whale, berries, and fireweed (of which syrups and jellies can be made).

Kjærgaard and colleagues (see under References, at the end of this post) examined data from an Inuit population in Greenland from 1962 to 1964, prior to the heavy westernization of their diet that is seen today. They investigated 96.9% of the whole population in three areas, including Ammassalik in East Greenland (n = 1,851).

Of those, only 181 adults, or 9.7 percent, had anything that looked like an abnormality that could suggest ischemia. This included ventricular hypertrophy (an enlargement of the heart chambers), leading to an overestimation because benign ventricular hypertrophy is induced by continuous physical exertion. These 181 adults were then selected for further screening.

Benign ventricular hypertrophy is also known as athlete's heart, because it is common among athletes. A prevalence of ventricular hypertrophy at a relatively young age, and declining with age, would suggest benign hypertrophy. The opposite would suggest pathological hypertrophy, which is normally induced by chronic hypertension.

As you can see from the figure below, from Kjærgaard et al. (2009), the pattern observed among the Inuit was of benign hypertrophy, suggestive of strong physical exertion at a young age.

A pattern of benign hypertrophy induced by robust physical activity is also consistent with reports by Stefansson (1958) about the life of the Eskimos in Northern Alaska. It is reasonable to assume that these Eskimos had a diet and lifestyle similar to the Greenland Inuit.

Back to Kjærgaard et al.’s (2009) study. The 181 adults selected for further screening then had a 12-lead ECG performed (this is a widely used test to check for heart abnormalities). The results suggested that only two men, aged 62 and 63 years, had ischemic heart disease. All in all, this suggests a prevalence of ischemic heart disease of 0.11 percent, which is very low.

(The authors of the article estimated the prevalence of ischemic heart disease at 1.1 percent, because they used the n = 181, as opposed to the original n = 1,851, in their calculation. The latter is the correct baseline sample size, in my opinion. Still, the authors present the 1.1 percent number as quite low as well, which it is.)

The prevalence of ischemic heart disease in the US of approximately 6.8 percent. That is, the prevalence in the US is 63 times higher than among the Inuit studied (using the 0.11 percent as the basis for comparison). And, it should be noted that there are many countries with a higher prevalence of ischemic heart disease than modern US.

It is possible that the low prevalence of ischemic heart disease among the Inuit was partly due to a higher mortality of those with the disease than in modern US, where medical intervention can prolong one's life in the presence of almost any disease. That is, perhaps many of those Inuit with ischemia would die quickly, and thus would not be captured by a study like this.

It is doubtful, however, that this would explain a difference as large as the one observed. Moreover, if many Inuit were dying due to ischemia, there would probably be plenty of evidence suggesting that. (I would imagine that the mysterious deaths associated with chest pain, and other related symptoms, would be a constant topic of conversation.) Reports from early explorers, however, suggest the opposite (e.g., Stefansson, 1958), and are consistent with the study described here.

In conclusion, this study suggests that the diet and lifestyle of the Greenland Inuit prior to the 1960’s (i.e., not their traditional diet and lifestyle, but approaching it) could be seen today as heart-healthy (at least for them), even though the Greenland Inuit ate a lot of animal protein and fat.

References:

Kjærgaard, M., Andersen, S., Holten, M., Mulvad, G., Kjærgaard, J.J. (2009). Low occurrence of ischemic heart disease among Inuit around 1963 suggested from ECG among 1851 East Greenland Inuit. Atherosclerosis, 203(2), 599-603.

Stefansson, V. (1958). Eskimo longevity in Northern Alaska. Science, 127(3288), 16-19.

A viral cure for cancer only a few years away?

Adopting an evolutionarily sound lifestyle may reduce the probability that one will develop cancer, but there will be those who will nevertheless have cancer. As we live longer lives, cancer diagnoses are likely to become more and more common.

There are viruses that cause the formation and growth of cancer tumors: oncoviruses. However, and quite interestingly, there are also viruses that seek and kill cancer cells: oncolytic viruses. The video below discusses emerging treatments based on oncolytic viruses.



This Penn Medicine YouTube video is about 6 minutes in length. (A previous HBO video was about 40 minutes in length, and it was worth watching in full. However it became unavailable soon after I linked it here. Its title on YouTube was "Vice Special Report: Killing Cancer".)

Cancer treatment via oncolytic viruses had a promising start in the mid-1990s. However, due to technical complications it has been sidelined for years. Interest has been picking up dramatically in recent years. Could it be foundation for the long promised cure for cancer, as the video implies?

Only time and research will tell …

What is the probability that you are NOT diabetic if your fasting blood glucose is 110-126 mg/dl?

Often I hear from readers who have changed their diets and lifestyles toward a more evolutionarily sound direction () that their fasting blood glucose (FBG) readings have gone up. Frequently numbers in the range 110-126 mg/dl (6.1-7 mmol/l) are mentioned.

If you have a FBG reading of 110-126 mg/dl (6.1-7 mmol/l) very likely your doctor will tell you that you are either diabetic or well on your way be becoming diabetic.

Diabetes is a condition that in humans is most frequently associated with damage to the beta cells in the pancreas, significantly impairing insulin secretion. With limited insulin, glucose levels tend to go up, leading to high FBG levels and high glucose peaks after consumption of carbohydrates. The latter, high glucose peaks, appear to be particularly damaging when happening regularly over time.

What is the probability that you are NOT diabetic with this FBG reading?

I put together the table below, based on data from a widely cited meta-analysis () conducted by the research group called The Emerging Risk Factors Collaboration. It shows the distribution of FBG levels in urban settings among individuals who do not have diabetes.

The numbers in this table are fairly consistent with those from various other surveys of large numbers of individuals in urban settings.

The study mentioned above also tells us that the incidence of diabetes in urban populations is in the neighborhood of 6.8 percent. This may not sound like much, but as disease incidences goes, it is very high – approximately 1 in every randomly selected group of 15 people has diabetes.

The vast majority of those diagnosed will have diabetes mellitus type 2, which tends to develop over time and be associated with the metabolic syndrome ().

We know from Bayes' theorem, which is a fundamental element of the increasingly popular Bayesian statistics, that the probability of an event A given that an event B has occurred [denoted P(A|B)] is given by:

P(A|B)=P(B|A)*P(A)/P(B).

In the equation above, P(B|A) is the probability of event B given A, P(A) is the probability of event A, and P(B) is the probability of event B.

To answer the question posed in the title of this blog post, we need to calculate the probability that a person will have no diabetes given that he or she has a fasting blood glucose of 110-126 mg/dl.

Replacing A and B in the equation above with “NoDiabetes” (short for not having diabetes) and “FBG=110-126 mg/dl” respectively, we arrive at the formula to calculate the probability that answers the question:

P(NoDiabetes|FBG=110-126 mg/dl)=P(FBG=110-126 mg/dl|NoDiabetes)*P(NoDiabetes)/P(FBG=110-126 mg/dl).

From the table above we know that P(FBG=110-126 mg/dl|NoDiabetes)=7 percent. From our previous discussion, we know that P(NoDiabetes)=(100-6.8)/100 =93.2 percent.

Finally, the study tells us that P(FBG=110-126 mg/dl) is 9.1 percent. This includes individuals with diabetes (2.1 percent) and without diabetes (7 percent).

With these numbers, we can calculate the probability that a person will have no diabetes given that he or she has a FBG of 110-126 mg/dl:

P(NoDiabetes|FBG=110-126 mg/dl)=0.07*(1-0.068)/0.091=0.72.

That is, if your fasting blood glucose is in the 110-126 mg/dl range (6.1-7 mmol/l) then the probability that you DO NOT have diabetes is 72 percent. It would be much safer to bet that you do not have diabetes than that you do, even at that relatively high range.

Surprising eh!?

The above discussion not only highlights the lack of reliability of fasting blood glucose levels for diabetes diagnoses in the 110-126 mg/dl range (6.1-7 mmol/l), but also begs the question – what could cause high fasting blood glucose levels in healthy individuals?

Some of the folks I heard from have gone through insulin sensitivity tests (see, e.g., ), and were found to be insulin sensitive (in at least one case, highly sensitive), even though their baseline glucose levels are generally high. This goes against the possible speculation that they are prediabetics well on their way to becoming diabetic.

One possibility has been discussed in a previous post, which also mentions what could happen with HbA1c levels ().

How much protein does one need to be in nitrogen balance?

The figure below, from Brooks et al. (2005), shows a graph relating nitrogen balance and protein intake. A nitrogen balance of zero is a state in which body protein mass is stable; that is, it is neither increasing nor decreasing. It seems that the graph was taken from this classic study by Meredith et al. The participants in the study were endurance exercisers. As you can see, age is not much of a factor for nitrogen balance in this group.

Nitrogen balance is greater than zero (i.e., an anabolic state) for the vast majority of the participants at 1.2 g of protein per kg of body weight per day. To convert lbs to kg, divide by 2.2. A person weighing 100 lbs (45 kg) would need 55 g/d of protein; a person weighing 155 lbs (70 kg) would need 84 g/d; someone weighing 200 lbs (91 kg) would need 109 g/d.

The above numbers are overestimations of the amounts needed by people not doing endurance exercise, because endurance exercise tends to lead to muscle loss more than rest or moderate strength training. One way to understand this is compensatory adaptation; the body adapts to endurance exercise by shedding off muscle, as muscle is more of a hindrance than an asset for this type of exercise.

Total calorie intake has a dramatic effect on protein requirements. The above numbers assume that a person is getting just enough calories from other sources to meet daily caloric needs. If a person is in caloric deficit, protein requirements go up. If in caloric surplus, protein requirements go down. Other factors that increase protein requirements are stress and wasting diseases (e.g., cancer).

But what if you want to gain muscle?

Wilson & Wilson (2006) conducted an extensive review of the literature on protein intake and nitrogen balance. That review suggests that a protein intake beyond 25 percent of what is necessary to achieve a nitrogen balance of zero would have no effect on muscle gain. That would be 69 g/d for a person weighing 100 lbs (45 kg); 105 g/d for a person weighing 155 lbs (70 kg); and 136 g/d for someone weighing 200 lbs (91 kg). For the reasons explained above, these are also overestimations.

What if you go well beyond these numbers?

The excess protein will be used primarily as fuel; that is, it will be oxidized. In fact, a large proportion of all the protein consumed on a daily basis is used as fuel, and does not become muscle. This happens even if you are a gifted bodybuilder that can add 1 lb of protein to muscle tissue per month. So excess protein can make you gain body fat, but not by protein becoming body fat.

Dietary protein does not normally become body fat, but will typically be used in place of dietary fat as fuel. This will allow dietary fat to be stored. Dietary protein also leads to an insulin response, which causes less body fat to be released. In this sense, protein has a fat-sparing effect, preventing it from being used to supply the energy needs of the body. As long as it is available, dietary protein will be favored over dietary or body fat as a fuel source.

Having said that, if you were to overeat anything, the best choice would be protein, in the absence of any disease that would be aggravated by this. Why? Protein contributes fewer calories per gram than carbohydrates; many fewer when compared with dietary fat. Unlike carbohydrates or fat, protein almost never becomes body fat under normal circumstances. Dietary fat is very easily converted to body fat; and carbohydrates become body fat when glycogen stores are full. Finally, protein seems to be the most satiating of all macronutrients, perhaps because natural protein-rich foods are also very nutrient-dense.

It is not very easy to eat a lot of protein without getting also a lot of fat if you get your protein from natural foods; as opposed to things like refined seed/grain products or protein supplements. Exceptions are organ meats and seafood, which generally tend to be quite lean and protein-rich.

References

Brooks, G.A., Fahey, T.D., & Baldwin, K.M. (2005). Exercise physiology: Human bioenergetics and its applications. Boston, MA: McGraw-Hill.

Wilson, J., & Wilson, G.J. (2006). Contemporary issues in protein requirements and consumption for resistance trained athletes. Journal of the International Society of Sports Nutrition, 3(1), 7-27.

Can salmon be a rich source of calcium?

Removing the bones from cooked fish, before eating the flesh, is not only a waste of mineral nutrients. In some cases it can be difficult, and lead to a lot of waste of meat.

We know that many ancestral cultures employed slow-cooking techniques and tools, such as earth ovens (a.k.a. cooking pits; see ). Slow-cooking fish over a long time tends to soften the bones to the point that they can be eaten with the flesh.

The photo below shows the leftovers of a whole salmon that we cooked recently. We baked it with vegetables on a tray covered with aluminum foil. We set the oven at 300 degrees Fahrenheit, and baked the salmon for about 5 hours.

The end result is that we can eat the salmon, a rich source of omega-3 fat, with the bones. No need to remove anything. Just take a chunk, as you can see in the photo, and eat it whole.

It is a good idea to marinate the salmon for a few hours prior to baking it. This will create enough moisture to ensure that the salmon does not dry up during the baking process.

If you are a carnivore, you can make a significant contribution to sustainability by eating the whole animal, or as much of the animal as possible. This applies to fish, as I discussed here before (, , ).

Add eating less to this habit, and your health will benefit greatly.

Will the aluminum pan and foil give you Alzheimer’s?

Aluminum (or aluminium) is a silvery metal that is both ductile and light. It is abundant in nature. These characteristics make it a favorite in many industries. Food utensils, such as pans and pots, are often made of aluminum. This use is dwarfed by aluminum’s widespread use in the canning of foods and drinks (e.g., sodas and beers).

Based on a systematic literature review published in 2008, Ferreira et al. argued that there is credible evidence of an “association” between Alzheimer’s disease and aluminum intake (). This argument has been challenged by other researchers, but has nevertheless gained media attention. Positive and negative associations will always be found where there are nonzero correlations, but correlation does not guarantee causation.

A research report commissioned by the U.S. Environmental Protection Agency, authored by Krewski et al. and published in 2007, reviewed a number of studies on the health effects of aluminum (). Several interesting findings emerged from this extensive review of the literature.

For example, a targeted study published in the late 1980s and early 1990s suggested that the daily intake of aluminum of a 14-16 year old male in the U.S. was about 11.5 mg; the main sources being additives to the following refined foods: cornbread (36.6% of total intake), American processed cheese (17.2%), pancakes (9.0%), yellow cake with icing (8%), taco/tostada (3.5%), cheeseburger (2.7%), tea (2.0%); hamburger (1.8%), and fish sticks (1.5%).

The meat that goes into the manufacturing of industrial hamburgers is not a significant source of aluminum. The same goes for the fish in the fish sticks. It is the industrial refining that makes the above-mentioned foods non-negligible sources of aluminum. One could argue that processed cheese should not be called “cheese”, as it is far removed from “real” cheese in terms of nutrient composition – particularly aged raw milk cheese.

Aluminum-treated water is widely believed to be a major source of aluminum to the body, with the potential of leading to health-detrimental accumulation. It appears that this is a myth based on several of the studies reviewed by Krewski et al.

One study concluded that humans drinking aluminum-treated water over a period of 70 to 80 years would have a total accumulation of approximately 1.5 mg of aluminum in their brain (1 mg/kg, the average adult human brain weighs 1.5 kg). At the high end of normal levels, and not much compared to the 34 mg found in some of those exposed to the Camelford water pollution incident (). And here is something else to consider. The study made two unlikely assumptions for emphasis: that all the ingested aluminum was absorbed, and that those exposed suffered from a condition that entirely prevented excretion from excess ingested aluminum.

Krewski et al.’s report and virtually all empirical studies I reviewed for this post suggest that the intake of aluminum from cooking utensils is negligible.

Is aluminum intake via food additives, arguably one of the main sources for most people living in urban environments today, likely to cause neurological diseases such as Alzheimer's disease?

My review of the evidence left me with the impression that most of the studies suggesting that aluminum intake can lead to neurological diseases make causal mistakes. One representative example is Rifat et al.’s study published in 1990 in The Lancet ().

This old study is interesting because it looked at the effects of ingestion of finely ground aluminum between 1944 and 1977 by miners, where the aluminum was ingested because it was believed to be protective against silicotic lung disease (caused by inhalation of crystalline silica dust).

As a side note, I should say that the intake levels reported in Rifat et al.’s study seem lower than what one would expect to see from a modern diet of refined foods. This seems odd. The levels may have been underestimated by Rifat et al. Or, what is more worrying, they may be quite high in a modern diet of refined foods.

Having said that, Rifat et al.’s article reports “… no significant differences between exposed and non-exposed miners in reported diagnoses of neurological disorder …” However, the tables below from their article show significant differences between exposed and non-exposed miners in their performance in cognitive tests. Those exposed to aluminum performed worst.

Two major variables that one would expect Rifat et al. to have controlled for are age and lung disease. They did control for age and a few other factors, with the corresponding results indicated as “adjusted” in the tables. However, they did not control for lung disease – the very factor that motivated aluminum intake.

Lung disease is likely to limit the supply of oxygen to the brain, and thus cause cognitive problems in the short and long term. Therefore, the cognitive impairments suggested by Rifat et al.'s study may have been caused by lung disease, and not by exposure to aluminum. This type of problem is a common feature of studies of the health effects of aluminum.

Will cooking in aluminum pans and aluminum foils give you Alzheimer’s? I doubt it.