Archive for the ‘Uncategorized’ Category

Can we target cancer with ketogenic diets? Can you help?

Posted: August 22, 2016 in Uncategorized
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We have a good deal of enthusiasm in the keto/paleo/low-carb community. We have the real sense that we can we use carbohydrate restriction to take advantage of the characteristic metabolic features of cancer — inflexible reliance on glucose. Enthusiasm may have outstripped the data, however, and several groups are trying to fill the gap. The barrier rests with the difficulty for anybody to obtain funding from NIH or other major government or private agencies. On top of this looms the long-standing resistance to low-carbohydrate diets making things particularly difficult. Our group is carrying out some good experiments and we employ a dedicated technician and we can efficiently use limited funds. Your backing can help.  A $ 15 donation gets us several days of supplies for the in vitro experiments that provide the biochemical underpinnings for attacking cancer in the clinic. Our project at experiment.com provides background, a place for discussion and reports from the lab.

The current metabolic point of view in cancer — emphasizing flexibility of fuel choices —  derives from renewed interest in the Warburg effect. Warburg saw that many cancer cells were producing lactic acid, the product of glycolysis. In other words, the tumors were not using the more efficient aerobic metabolism even when oxygen was present in the environment. The tumor cell’s requirement for glucose suggests the possibility of giving the host an advantage by restricting carbohydrate and offering ketone bodies as an alternative fuel.constant_ATP_UCP2

We showed previously that we could inhibit the growth of 7 different cancer cell lines and repress the production of ATP (the”‘energy molecule” in cell culture by adding acetoacetate (one of the ketone bodies) to the medium.  Control normal cell lines were not affected. In addition, we showed that ATP reduction was associated with the level of a molecule called uncoupling protein-2 (UCP-2).  I explain in other posts what “uncoupling” means and how it figures into energy efficiency. First, the big picture..

What is the context of inhibition by ketone bodies ?
The real context, of course, is human cancer. Our 28 day pilot human trial of 10 subjects with advanced cancers on a very low carbohydrate ketogenic diet (KD) was published in Nutrition (Elsevier) in 2012.  A small study — nominally just to show safety and feasibility, it was nonetheless well received. Of note, is that we found that those patients with the greatest extent of ketosis had stable cancers or partial remission, while those with the least ketosis showed continued progressive cancer. Despite a favorable editorial and the Metabolism Award from the journal. Unfortunately, our proposal to scale up to 65 patients was rejected by the NIH/NCI which we find very discouraging perhaps related to a commitment to drug therapy. In any case, we appeal now for help in supporting dietary cancer research.
You can help. To donate:  Our project ia at experiment.com

Statistics for the Rest of Us

Posted: May 20, 2015 in Uncategorized
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Following up from chapters in The World Turned Upside Down, I will try to provide a guide to getting through the medical literature. I will talk about relative risk first with an excerpt from the book and a quick way to get a feel for what relative risk really is.

It has been frequently pointed out that to succeed at major league baseball all you have to do is screw up no more than 70 % of the time. In fact ,it is almost 75 years since someone was able to come up with a failure rate as low as 60 %. (Ted Williams hit .406 in 1941). The point is that statistics is about interpretation. It is how you describe things. As in Paulos’s Once Upon a Number, mathematics and especially statistics is a story, and how you tell it.  The potential for being misled is obviously great. The idea that statistics is a cut-and-dried standard set of manipulations into which you pour your data and from which you are automatically given significance, importance and truth, is one of the major components in the failure of the medical nutrition literature. (more…)

Soda and the Nanny State

Posted: March 15, 2013 in Fructose, low-carbohydrate diet, Lustig, Occam's Razor, Uncategorized
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Mayor-Bloomberg-The-Littlest-Dictator--99309

My comments in answer to Jonny Bowden’s Huffington Post take on the sugar tax where he suggested that despite it’s flaws, “it’s all we’ve got.” I insisted that It’s not all we’ve got. We have the science and, in one afternoon, Bloomberg could convene a panel of scientists to evaluate presentations by all the players including me who believe that sugar is a smokescreen for not facing the importance of total carbohydrate restriction which you [Jonny Bowden], among others, have explained. Everybody should be heard. What I see is another rush to judgement like the low fat fiasco which we still have with us.

That you “have to do something” comes right out of Senator McGovern’s mouth as in Fat Head. And “deadly white substance that literally creates hormonal havoc and appetite dysregulation … promoting metabolic syndrome, diabetes, obesity and heart disease” is way outside of the bounds of science. I am not the only one to point out that Lustig’s population study represented the return of Ancel Keys.

We go with science or we don’t.

(more…)

MedicineBall*: Harvard School of Public Health steps up to the Plate.

Posted: October 3, 2011 in Dietary Fiber, Evidence Based Medicine, Lipophobes, low-carbohydrate diet, Observational Studies, Protein, The Nutrition Story, Uncategorized, USDA Dietary Guidelines
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First published in October of 2011, this post announced a Q&A on line with Harvard’s Eric Rimm to answer question about the School of Public Health’s new  “Healthy Eating Plate,” its own version of nutritional recommendations to compete with the USDA’s MyPlate. A rather  limited window of one hour  was allotted for the entire country to phone in our questions.  Unfortunately HSPH was not as good at telecommunications as it is at epidemiology and the connection did not start working for a while.  The questions that I wanted to ask, however, still stand and this post is a duplicate of the original with the notice about the Q&A removed.  Harvard has been invited to participate in a panel discussion at the Ancestral Health Symposium, and we will see how these questions can be answered.

— adopted from Pops (at Louder and Smarter), the anonymous brilliant artist and admitted ne’er do well.

One of the questions surrounding USDA Nutrition Guidelines for Americans was whether so-called “sunshine laws,” like the Freedom of Information Act, were adhered to. Whereas hearings were recorded, and input from the public was solicited, there is the sense that if the letter of the law was followed, the spirit was weak.  When I and colleagues testified at the USDA hearings, there was little evidence that their representatives were listening; there was no discussion. We said our piece and then were heard no more.  In fact, at the break, when I tried to speak to one of the panel, somebody came out from backstage, I believe unarmed, to tell me that I could not discuss anything with the committee.

Harvard School of Public Health, home of  “odds ratio = 1.22,” last month published their own implementation of the one size-fits-all approach to public nutrition, the”Healthy Eating Plate.”  Their advice is full of  “healthy,” “packed with” and other self-praise that makes this mostly an infomercial for HSPH’s point of view. Supposedly a correction of the errors in MyPlate from the USDA, it seems to be more similar than different. The major similarity is the disdain for the intelligence of the American public. Comparing the two plates (below), they have exchanged the positions of fruits and vegetables.  “Grains” on MyPlate is now called “Whole Grains,” and “Protein” has been brilliantly changed to “Healthy Proteins.”  How many NIH grants were required to think of this is unknown.  Harvard will, of course, tell you what “healthy” is:, no red meat and, of course watch out for the Seventh Egg.

 

 

 

 

 

 

 

So here are the  questions that I wanted to ask:

  1. Dr. Rimm, you are recommending a diet for all Americans but even within the pattern of general recommendations, I don’t know of any experimental trial that has tested it.  Aren’t you just recommending another grand experiment like the original USDA recommendations which you are supposedly improving on?
  2. Dr. Rimm, given that half the population is overweight or obese shouldn’t there be at least two plates?
  3. Dr. Rimm, I think the American public expects a scientific document.  Don’t you think continued use of the words “healthy,” “packed with nutrients,” makes the Plate more of  an informercial for your point of view?
  4. Dr. Rimm, the Plate site says “The contents of this Web site are not intended to offer personal medical advice,” but it seems that is exactly what it is doing. If you say that you are recommending a diet that will “Lower blood pressure; reduced risk of heart disease, stroke, and probably some cancers; lower risk of eye and digestive problems,” how is that not medical advice?  Are you disowning responsibility for the outcome in advance?
  5. Dr. Rimm, more generally, how will you judge if these recommendations are successful? Is there a null hypothesis? The USDA recommendations continue from year to year without any considerations of past successes or failures.
  6. Dr. Rimm, “healthy” implies general consensus but there are many scientists and physicians with good credentials and experience who hold to different opinions. Have you considered these opinions in formulating the plate? Is there any room for dissent or alternatives?
  7. Dr. Rimm, the major alternative point of view is that low-carbohydrate diets offer benefits for weight loss and maintenance and, obviously, for diabetes and metabolic syndrome. Although your recommendations continually refer to regulation of blood sugar, it is not incorporated in the Plate.
  8. Dr. Rimm, nutritionally, fruits have more sugar, more calories, less potassium, fewer antioxidants than vegetables.  Why are they lumped together? And how can you equate beans, nuts and meat as a source of protein?
  9. Dr. Rimm, looking at the comparison of MyPlate and your Plate, it seems that all that is changed is that “healthy” has been added to proteins and “whole” has been added to grains.  If people know what “healthy” is, why is there an obesity epidemic? Or are you blaming the patient?
  10. Dr. Rimm, you are famous for disagreeing on lipids with the DGAC committee yet your name is on their report as well as on this document is supposed to be an alternative.  Do we know where you stand?
  11. Dr. Rimm, the Healthy Plate “differences” page says “The Healthy Eating Plate is based exclusively on the best available science and was not subjected to political and commercial pressures from food industry lobbyists.” This implies that the USDA recommendations are subject to such pressures.  What is the evidence for this? You were a member of the USDA panel. What pressures were brought to bear on you and how did you deal with them
  12. Dr. Rimm, the Healthy Plate still limits saturated fat even though a study from your department showed that there was, in fact, no effect of dietary saturated fat on cardiovascular disease.  That study, moreover, was an analysis of numerous previous trials, the great majority of which individually showed no risk from saturated fat. What was wrong with that study that allows you to ignore it?

*Medicineball, (colloq) a game that derives from Moneyball, in which an “unscientific culture responds, or fails to respond, to the scientific method ” in order  to stay funded.

Damned statistics and the nutrition literature

Posted: January 3, 2011 in Uncategorized
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A guide for consumers and the media

For Mark Twain’s hierarchy of lies, damned lies and statistics, we should really add epidemiological lies, those reports showing that brown rice or trans-palmitoleic acid will prevent diabetes and diet soda will make you fat, which appear every week or so in ABCNews.  (I mean the generic media, but ABCNews and I have a close relationship: sometimes they even print what I tell them).  If you’ve been eating white rice instead of brown rice and you develop diabetes ten years later, it is the fault of your choice of rice. Everybody knows that this is ridiculous but the data are there showing an almost 4-fold increased risk, so how can you argue with the numbers.

These kinds of studies are always based on associations and the authors are usually quick to tell you that association doesn’t mean causality even as they interpret the data as a clear guide to action (“Substitution of whole grains, including brown rice, for white rice may lower risk of type 2 diabetes.”)   In fact, to most scientists, association can be a strong argument for causality.  That is not what’s wrong with them. Philosophically speaking, there are only associations.  All we really know is that there is a stream of particles and there is an association between the presence of a magnet and the appearance of a spot on a piece of photographic paper (anybody remember photographic paper?).  God does not whisper in your ear that the particle has a magnetic moment.  It is the strength of the idea behind the association and the presentation of the idea that determines whether the association implies causality.  What most people really mean is that “association does not necessarily imply causality.  You may need more information.” What’s wrong with the rice story is that the idea is lacking in common sense.  The idea that the type of rice you eat has any meaningful impact by itself, or even whether one can guess whether it has a positive or negative impact on a general lifestyle, is absurd.  But what about the statistics? Here the problem is really presentation of the data.  The number of papers in the literature pointing out the errors in interpretation of statistics is very large although it is still less than the number of papers making those errors.  There are numerous problems and many examples but let’s look at the simplest case: limitations of reporting relative risk and alternatives.

images-1Here’s a good example cited in a highly recommended popular statistics books, Gerd Gigerenzer’s “Calculated Risks.” He discusses a real case, the West of Scotland Coronary Prevention Study (WOSCOPS) comparing the statin drug, pravastatin to placebo in people with high cholesterol.  The study was started in 1989 and went on for about 5 years.  (These days, I think you can only compare different statins; everybody is so convinced that they are good that a placebo would be considered unethical):

1. First, the press release: “People with high cholesterol can rapidly reduce… their risk of death by 22 per cent by taking…pravastatin.”

2. Now, ask yourself what this means? If 1000 people with high cholesterol take pravastatin, how many people will be saved from a heart attack that might have otherwise killed them?  Think about this, then look at the data, the data that should have  been reported in the media.

3. The data:

Treatment        deaths during 5 years (per 1000 people with high cholesterol)

pravastatin             32

placebo                  41

Right off, it doesn’t look as good as you might have thought.  Overall, death from a heart attack is a major killer, but if you take a thousand people and watch them for five years, not that many people die from a heart attack. Now there are three standard ways of representing the data.

4. Data presentation – Relative risk reduction.

Risk is the number of cases divided by total number of people in the trial (or risk per total number). So you calculate a risk for 1000 people on the drug = 32/1000 = 03.2 % and similarly for people on the statin. Risk reduction for comparing treatments is\ the difference between the two risks.  The relative risk reduction here  is just the reduction in risk divided by the risk for the placebo:

Risk reduction (number of people saved per thousand)  = 41-32 = 9. Saving 9 lives doesn’t sound that great but lets get the per cent as reported.

Relative risk reduction = 9/41 = 22 % as indicated, and it does sound like a big deal but there are other ways to look at the data.

5.  Data presentation – Absolute risk reduction.  Again, you start with risk, the number of cases divided by total number but you calculate the actual fraction.  The absolute risk reduction is the difference between these two fractions.

For pravastatin, risk = 32/1000

For placebo, risk = 41/1000

Absolute risk reduction = (41/1000) – (32/1000) = 9/1000 = 0.9 % (less than 1 %)

6.  Data presentation – Number needed to treat (NNT): This is a good indicator of outcomes.  If you treat 1000 people, 9 will survive who might have otherwise died. So,

number that you have to treat  to save one life = NNT  =  1000/9 = 111 people .

7. Conclusion: 22 % risk reduction is true enough but it seems like it didn’t really tell you what you want to know.  Cutting to the chase, would you take a statin if you had high cholesterol (more than about 250 mg/dl) and, as in WOSCOPS, no history of heart attacks. On the basis of this study alone, it’s not clear.  First, the risk is low.  There is clearly a benefit but how predictable is that benefit?  In the study, 99 % of the people had no benefit.  Of course, if you are the one out of a hundred, the drug would be a good thing.  The question is not easy to answer but the point of what’s written here is that the statistics as reported in the media might have led you to jump to conclusions.  Before you jump, though, you might ask about side-effects.  This is a complicated subject because although the side-effects are rare, their incidence is not zero and they can be severe but this post is only about the statistics.


The Seventh Egg.

Posted: October 22, 2010 in Uncategorized
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Stepping back and looking at the recent scientific literature, I am struck with how life is a miracle.  How could humans have evolved in the face of threats from red meat, from eggs, even from the dangers of shaving?  (If you write about nutrition you have to create a macro that types out “I’m not making this up:” the Caerphilly Study [1] shows you the dangers of shaving… or is it the dangers of not shaving?).  With 28% greater risk of diabetes here, 57 % greater risk of heart disease there how could our ancestors have ever come of child-bearing age?  With daily revelations from the Harvard School of Public Health showing the Scylla of saturated fat and the Carybdis of sugar between which our forefathers sailed, it is amazing that we are here.

These studies that the media writes about, are they real?  They are certainly based on scientific papers.  If the media is not always able to decipher them, reporters do generally talk to the researchers. And the papers must have gone through peer review and yet many actually defy common sense.   Can the medical literature have such a high degree of error?  Could there be a significant number of medical researchers who are not doing credible science?  How can the consumer decide?  I am going to try to answer these questions.  When people ask questions like “could the literature be wrong?,” the answer is usually “yes” and I will try to explain what’s wrong and how to read the nutritional literature in a practical way. I am going to try to make it simple.  It is science, but it is pretty simple science.  I am going to illustrate the problem with the example of a paper by Djoussé [2].  But first, a joke.

It was a dumb joke. In my childhood, there was the idea, probably politically incorrect, that Indians, that is, Native Americans, always said “how” as a greeting.  The joke was about an Indian with a great memory who is asked what he had for breakfast on New Years day the previous year.  He says “eggs.”  They are then interrupted by an earthquake or some natural disaster and the interviewer and the Indian don’t meet again for ten years.  When they meet, the interviewer says “how.”  The Indian answers “scrambled.”

If the interviewer had been an epidemiologist he might have asked if he had developed diabetes.   Djoussé, et al. [2] asked participants about how many eggs they ate and then ten years later, if they developed diabetes it was assumed to be because of the eggs.  Is this for real?  Do eggs cause changes in your body that accumulate until you develop a disease, a disease that is, after all, primarily one of carbohydrate intolerance?  The condition is due either to the inability of the pancreas to produce insulin in response to carbohydrate (type 1) or to impaired response of the body to the insulin produced and a deterioration of the insulin-producing cells of the pancreas (type 2).  Common sense says that there is something suspicious about the idea that eggs would play a major role.  It is worth trying to understand the methodology and see if there is a something beyond common sense, and whether this is a problem in other studies besides   Djoussé’s.

What did the experimenters actually do.  First, people were specifically asked “to report how often, on average, they had eaten one egg during the past year,” and “classified each subject into one the following categories of egg consumption: 0, < 1 per week, 1 per week, 2-4 per week, 5-6 per week, and 7+ eggs per week.”  They collected this data every two years for ten years.  With this baseline data in hand they then followed subjects “from baseline until the first occurrence of a) type 2 diabetes, b) death, or c) censoring date, the date of receipt of the last follow-up questionnaire” which for men was up to 20 years.  Thinking back over a year: is there any likelihood that you might not be able to remember whether you had 1 vs. 2 eggs on average during the year?  Is there any possibility that some of the men who were diagnosed with diabetes ten years after their report on eggs changed their eating pattern in the course of ten years?  Are you eating the same food you ate ten years ago?  Quick, how many eggs/week did you eat last year?

Reading a scientific paper: the Golden Rule.

Right off, there is a problem in people reporting what they ate but this is a limitation of many nutritional studies and, while a source of error, it is depends on how you interpret the data.  All scientific measurements have error.  It is not a matter of ignoring the data but rather not interpreting results beyond measurement.  So, here’s how I read a scientific paper.   First, I look for the pictures.  What? A professor of biochemistry looks for the pictures first?  In a scientific paper, of course, they are called figures but it’s not just saving a thousand words.  (I get a thousand emails every couple of weeks). It’s about presentation of the data.

The principle is that a scientific paper is supposed to explain. The principle is laid out in what I call the golden rule of scientific papers.  It comes from the Book PDQ Statistics by Geoffrery Norman and David Streiner.  PDQ stands for Pretty Darned Quick and some of the humor is pretty sophomoric (e.g. it has Convoluted Reasoning or Anti-intellectual Pomposity detectors) but it is an excellent introductory statistics book.  Here’s the Golden Rule:

“The important point…is that the onus is on the author to convey to the reader an accurate impression of what the data look like, using graphs or standard measures, before beginning the statistical shenanigans.  Any paper that doesn’t do this should be viewed from the outset with considerable suspicion.”

— Norman & Streiner, PDQ Statistics [3]

In other words: teach.  Make it clear.  Eye-balling Djoussé, et al., we see that there are no figures.     A graph of number of eggs consumed vs number of cases of diabetes is what would be expected of the golden rule.  The results, instead are stated in the Abstract of the paper as the following mind-numbing statistics. (You don’t really have to read this)::

“Compared with no egg consumption, multivariable adjusted hazard ratios (95% CI) for type 2 diabetes were 1.09 (0.87-1.37), 1.09 (0.88-1.34), 1.18 (0.95-1.45), 1.46 (1.14-1.86), and 1.58 (1.25-2.01) for consumption of <1, 1, 2-4, 5-6, and 7+ eggs/week, respectively, in men (p for trend <0.0001). Corresponding multivariable hazard ratios (95% CI) for women were 1.06 (0.92-1.22), 0.97 (0.83-1.12), 1.19 (1.03-1.38), 1.18 (0.88-1.58), and 1.77 (1.28-2.43), respectively (p for trend <0.0001).”

What does all this mean? I will just state what the statistics mean because it is worth considering the conclusion as stated by the authors.

The meaning of the statistics is that there was no risk of consuming 1 egg/week compared to eating none.  Similarly, there was no risk in eating 2-4 eggs/week or 5-6 eggs/week.  But when you up your intake to 7 eggs or more per week, that’s it.  Now, you are at risk for diabetes.  The relative risk is small but there it is. You are now at greater risk.

Since I like pictures, I will try to illustrate this with a modified still from the movie, The Seventh Seal directed by Ingemar Bergman.  Very popular in the fifties and sixties, these movies had a captivating if pretentious style: they sometimes seemed to be designed for Woody Allen’s parodies.  One of the famous scenes in The Seventh Seal is the protagonist’s chess game with Death.  A little PhotoShop and we have a good feel for what happens if you go beyond 5-6 eggs/week.

 

1. Ebrahim S, Smith GD, May M, Yarnell J: Shaving, coronary heart disease, and stroke: the Caerphilly Study. Am J Epidemiol 2003, 157(3):234-238.

2. Djoussé L, Gaziano JM, Buring JE, Lee IM: Egg consumption and risk of type 2 diabetes in men and women. Diabetes Care 2009, 32(2):295-300.

3. Norman GR, Streiner DL: PDQ statistics. 3rd edition. Hamilton, Ont.: B.C. Decker; 2003.

The benefit in replacing dietary carbohydrate with protein

Posted: September 12, 2010 in Uncategorized
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The study of metabolic pathways provides an insight into chemical reactions and the way they function in living systems but, in the end, even a biochemistry professor still has to answer the question  “What should I eat.”  Adam Cambell, an editor at Men’s Health magazine once asked me: “You’ve just had a meal that conforms to your idea of good nutrition and satisfying portions of food but you’re still hungry.  What should you do?”

“Think of a perfectly-cooked juicy steak or perfectly-prepared fish, or some similar high protein food that you usually like,” I suggested.  “If that sounds good, you’re hungry and you should eat something.  If it doesn’t sound good, you’re not hungry.  You may want desert.  You may want something feeling good in your mouth, but you’re not hungry.” What I meant, of course, is that foods that are high in protein, and lower in carbohydrate, tend to be more filling. This satiating effect of protein is well-known in the biochemical literature and is one of the advantages of diets that restrict carbohydrates and keep protein high.  The fact that protein is satisfying also means that it provides its own control over intake and, for that reason, “concerns” about high protein intake that you hear from nutritional expert are not usually a real problem.  In the obesity epidemic where there was a large increase in carbohydrate consumption and a general decline in fat consumption, protein stayed about the same.  When nutritionists carry out experiments in which people can eat freely, they generally do not change their protein consumption.  In fact, it now seems likely that most people are not getting enough protein.  Recent studies show that people benefit from replacing carbohydrate in their diet with protein, the benefit is in better weight control, in an improved ratio to lean body mass compared to fat and in better control of blood insulin and glucose.  I will describe some of the features of this problem with references to papers in the scientific literature that are either open access or have been made publicly available and public and do not require a subscription.

Nutritionists who study protein think that we need modification of official recommendations for protein consumption.  Donald Layman at the University of Illinois has reviewed some of the important research on this question and he came up with several important points:

•    Protein is a critical part of the adult diet. Beyond physical growth which is only important for a brief period in your life, there is a continuing need to repair and remodel muscle and bone

•    Protein needs for adults relate to body weight not, as you sometimes see, as a per cent of total calories. So, if you are reducing calories, protein needs to stay high and may be a higher percentage of total calories. In choosing a diet, you should establish the grams of protein first.

•    The amount of protein at each meal can be important.  Research indicates that an ideal is 30 g of protein per meal although this may not be practical for everybody. It is recommended that breakfast be high in protein.

•    Most adults benefit from protein intakes above the minimum RDA (recommended daily allotment) and this is especially true for an aging population with increased risks of poor health.  The RDA represents a minimum daily intake for active healthy adults but most people will benefit from replacing at lest some carbohydrate in the diet with protein.

The full story on protein recommendations can be found at Nutrition & Metabolism (no subscription required.

A look at the science

Proteins are generally more complicated molecules than fat or carbohydrate.  Like starch, they are polymers (think chain of beads).  Most starches are homopolymers (all the beads are the same, glucose in this case), but protein molecules are made of 20 different kinds of beads (amino acids).  About half are interchangeable or can be made from other nutrients and are said to be non-essential.  The other half are required in the diet and are said to be essential amino acids, or, for some reason, the more modern term is indispensable.  Now your body is continually breaking down and re-synthesizing its own proteins, the most obvious function of dietary protein is supplying amino acids to replenish body proteins so high quality dietary proteins will be those that supply all the essential amino acids.  Meat, fish and eggs are high quality proteins but combinations of vegetables can also supply the full complement of amino acids.  Many web sites and other sources will give you information about how vegetables can be combined to supply amino acids, but there is another aspect of protein nutrition that should be considered.  Amino acids, like carbohydrate are not just sources of cell material but may have a signaling function.  Remember that it is not just that glucose supplies energy but that it stimulates the release of insulin which further controls metabolism.  Amino acids also perform this function and stimulate insulin release and trigger other physiologic processes, in particular, synthesis of new body protein and provide control over blood glucose.  One essential amino acid in particular, leucine, is of greatest importance in this role.  In comparative studies, diets that are high in leucine improve the ratio of lean body mass to fat. Whey and other milk proteins are particularly high in leucine; red meat is also a good source.

The benefit in substituting protein for carbohydrate is greatest for people with diabetes.  The studies from the laboratories of Mary Gannon and Frank Nuttall are pretty remarkable and I show you a picture of the actual results from their experiments.  They studied the effect of reducing dietary carbohydrate on responses of people with diabetes.  The figure shows that after 5 weeks on a diet with 20 % available glucose (circles in the figure), the response to meals is drastically improved compared to the response if the traditional diet is continued (triangles).  As the diet proceeded, hemoglobin A1c was also reduced.  Gannon and Nuttall have also showed that diets with slightly higher glucose may be effective but the response depends on how much glucose is in the diet.  A very important feature of the studies of this study is that the diets were designed so that patients maintained their weight, in other words, benefit accrued even though no weight was lost.  Given how hard it is to lose weight, this has to be considered a real plus for the higher protein, lower carbohydrate diet.  You can see the whole study, again, without subscription here.

Is there a danger of too much protein?

How many times have you read an article in the media, or even in the medical literature, warning you about the dangers of high protein diets for your kidneys, or for kidney stones, or whatever.   Probably quite a few.  Are they for real?  To answer that question, think of how often you have read an article in the media describing somebody who actually had kidney problems or stones due to a high protein diet? That number is zero or close (there’s always a case study someplace with an isolated patient).

To understand the danger in a high protein diet for people with normal kidneys, consider the following conversation I had with an expert on kidney disease when I was the editor of Nutrition & Metabolism.

RF: I received a manuscript today that rather strongly and categorically says that there is no danger in high protein diets for people with normal kidneys.

Nephrologist: That’s right.

RF: It is?  Can we document that?

N: How do you document that there are no people with three eyes.  We have looked very hard for it and we never found it.

So, what’s wrong.  Mostly what’s wrong is that we never got around to agreeing on what high protein is.  Diets that encourage you to replace carbohydrate with protein are only trying to counteract the high carbohydrate message. Few people actually eat huge amounts of protein.  As discussed above, protein tends to be more satisfying than carbohydrate and what might be considered high protein is pretty average.

In other words, there is common sense.  A healthy high protein diet is currently estimated to have a daily intake of about 1 to 4 g of protein for every kg (2.2 lbs) of body weight while the USDA recommendation is only 0.8 g/kg).  So, if you weigh 175 lbs., an optimal level of protein will be at least 80.  The diet shown below is actually quite a bit higher. Is this really unusual?  In fact, if you ate 3 eggs or even bigger portion of  brisket, do you think something terrible will happen.  Is this dangerous?  To say that normal eating, even with occasional over-indulgence, is dangerous requires real proof and that’s what’s always been missing.

Finally, it is likely that for people with diabetes, there is great danger to kidneys from continued high blood sugar and most physicians would say that this risk is real while any risk from high protein is conjecture.

The bottom line: Substituting protein for carbohydrate in the diet improves blood glucose and insulin control.  As part of a weight loss diet, higher protein preserves lean mass compared to higher carbohydrate diets but the benefits of higher protein, lower carbohydrate diets provide benefit even in the absence of weight loss.