Two new papers

Pradhan MA1, Blackford JA Jr1, Devaiah BN2, Thompson PS2, Chow CC3, Singer DS2, Simons SS Jr4.  Kinetically Defined Mechanisms and Positions of Action of Two New Modulators of Glucocorticoid Receptor-regulated Gene Induction.  J Biol Chem. 2016 Jan 1;291(1):342-54. doi: 10.1074/jbc.M115.683722. Epub 2015 Oct 26.

Abstract: Most of the steps in, and many of the factors contributing to, glucocorticoid receptor (GR)-regulated gene induction are currently unknown. A competition assay, based on a validated chemical kinetic model of steroid hormone action, is now used to identify two new factors (BRD4 and negative elongation factor (NELF)-E) and to define their sites and mechanisms of action. BRD4 is a kinase involved in numerous initial steps of gene induction. Consistent with its complicated biochemistry, BRD4 is shown to alter both the maximal activity (Amax) and the steroid concentration required for half-maximal induction (EC50) of GR-mediated gene expression by acting at a minimum of three different kinetically defined steps. The action at two of these steps is dependent on BRD4 concentration, whereas the third step requires the association of BRD4 with P-TEFb. BRD4 is also found to bind to NELF-E, a component of the NELF complex. Unexpectedly, NELF-E modifies GR induction in a manner that is independent of the NELF complex. Several of the kinetically defined steps of BRD4 in this study are proposed to be related to its known biochemical actions. However, novel actions of BRD4 and of NELF-E in GR-controlled gene induction have been uncovered. The model-based competition assay is also unique in being able to order, for the first time, the sites of action of the various reaction components: GR < Cdk9 < BRD4 ≤ induced gene < NELF-E. This ability to order factor actions will assist efforts to reduce the side effects of steroid treatments.

Li Y, Chow CC, Courville AB, Sumner AE, Periwal V. Modeling glucose and free fatty acid kinetics in glucose and meal tolerance test. Theor Biol Med Model. 2016 Mar 2;13:8. doi: 10.1186/s12976-016-0036-3.

Abstract:
BACKGROUND:
Quantitative evaluation of insulin regulation on plasma glucose and free fatty acid (FFA) in response to external glucose challenge is clinically important to assess the development of insulin resistance (World J Diabetes 1:36-47, 2010). Mathematical minimal models (MMs) based on insulin modified frequently-sampled intravenous glucose tolerance tests (IM-FSIGT) are widely applied to ascertain an insulin sensitivity index (IEEE Rev Biomed Eng 2:54-96, 2009). Furthermore, it is important to investigate insulin regulation on glucose and FFA in postprandial state as a normal physiological condition. A simple way to calculate the appearance rate (Ra) of glucose and FFA would be especially helpful to evaluate glucose and FFA kinetics for clinical applications.
METHODS:
A new MM is developed to simulate the insulin modulation of plasma glucose and FFA, combining IM-FSIGT with a mixed meal tolerance test (MT). A novel simple functional form for the appearance rate (Ra) of glucose or FFA in the MT is developed. Model results are compared with two other models for data obtained from 28 non-diabetic women (13 African American, 15 white).
RESULTS:
The new functional form for Ra of glucose is an acceptable empirical approximation to the experimental Ra for a subset of individuals. When both glucose and FFA are included in FSIGT and MT, the new model is preferred using the Bayes Information Criterion (BIC).
CONCLUSIONS:
Model simulations show that the new MM allows consistent application to both IM-FSIGT and MT data, balancing model complexity and data fitting. While the appearance of glucose in the circulation has an important effect on FFA kinetics in MT, the rate of appearance of FFA can be neglected for the time-period modeled.

Paper on the effect of food intake fluctuations on body weight

Chow, C. C. & Hall, K. D. Short and long-term energy intake patterns and their implications for human body weight regulation. Physiology & Behavior 134:60–65 (2014). doi:10.1016/j.physbeh.2014.02.044

Abstract: Adults consume millions of kilocalories over the course of a few years, but the typical weight gain amounts to only a few thousand kilocalories of stored energy. Furthermore, food intake is highly variable from day to day and yet body weight is remarkably stable. These facts have been used as evidence to support the hypothesis that human body weight is regulated by active control of food intake operating on both short and long time scales. Here, we demonstrate that active control of human food intake on short time scales is not required for body weight stability and that the current evidence for long term control of food intake is equivocal. To provide more data on this issue, we emphasize the urgent need for developing new methods for accurately measuring energy intake changes over long time scales. We propose that repeated body weight measurements can be used along with mathematical modeling to calculate long-term changes in energy intake and thereby quantify adherence to a diet intervention and provide dynamic feedback to individuals that seek to control their body weight.

The world of Gary Taubes

Science writer Gary Taubes has a recent New York Times commentary criticizing Kevin Hall’s recent paper on the differential metabolic effects of low fat vs low carbohydrate diets. See here for my recent post on the experiment. Taubes is probably best known for his views on nutrition and as an advocate for low carb diets although he has two earlier books on the sociology of physics. The main premise running through his four books is that science is susceptible to capture by the vanity, ambition, arrogance, and plain stupidity of scientists. He is pro-science but anti-scientist.

His first book on nutrition – Good Calories, Bad Calories, was about how the medical establishment and in particular nutritionists have provided wrong and potentially dangerous advice on diets for decades. He takes direct aim at Ancel Keys as one of the main culprits for pushing the reduction of dietary fat to prevent heart disease. The book is a great read and clearly demonstrates Taubes’s sharp mind and gifts as a story teller. In the course of researching the book, Taubes also discovered the biological mechanisms of insulin and this is what has mostly shaped his thinking about carbohydrates and obesity. He spells it out in more detail in his subsequent book – Why We Get Fat. I think that these two books are a perfect demonstration of why having a little knowledge and a high IQ can be a dangerous thing.

Most people know of insulin as the hormone that goes awry in diabetes. When we fast, our insulin levels are low and our body, except for our brain, burns fat. If we then ingest carbohydrates, our insulin levels rise, which induces our body to utilize glucose (the main source of fuel in carbs) in favour of insulin. Exercise will also cause a switch in fuel choice from fat to glucose. What is less well known is that insulin also suppresses the release of fat from fat cells (adipocytes), which is something I have modeled (see here). This seems to have been a revelation to Taubes – Clearly, if you eat lots of carbs, you will have lots of insulin, which will sequester fat in fat cells. Ergo, eating carbs makes you fat! Nutritionists were so focused on their poorly designed studies that they missed the blatantly obvious. This is just another example of how arrogant scientists get things wrong.

Taubes then proposed a simple experiment – take two groups of people and put one group on a high carb diet and the other on a low carb diet with the same caloric content, and see who loses weight. Well, Kevin Hall anticipated this request with basically the same experiment although for a different purpose. What Kevin noticed in his model was that if you cut carbs and keep everything else the same, insulin goes down and the body responds by burning much more fat. However, if you cut fat, there is nothing in the model that told the body that the fat was missing. Insulin didn’t change and thus the body just burned the same amount of carbs as before. He found this puzzling. Surely there must be a fat detector that we don’t know about so he went about to test it. I remember he and his fellows labouring diligently for what seemed like years writing the protocol and getting the necessary approval and resources to do the experiment. The result was exactly as the model predicted. We really don’t have a fat sensor. However, the subjects lost more fat on the low fat diet then they did on the low carb diet.  This is not exactly the experiment Taubes wanted to do, which was to change the macronutrient composition but keep the calories the same. He then hypothesized that those on the low carb diet would lose weight and those on the low fat, high carb diet would gain weight. Kevin and a consortium of top obesity researchers has since done that experiment and the results will come out shortly.

Now is this surprising? Well not really, for while Taubes is absolutely correct in that insulin suppresses fat utilization the net outcome of insulin reduction is a quantitative and not a qualitative question. You cannot deduce the outcome with formal logic. The reason is that insulin cannot be elevated all the time. Even a continuous grazer must sleep at some point where upon insulin falls. You then must consider the net effect of high and low insulin over a day or longer to assess the outcome. This can only be determined empirically and this is what Taubes fails to see or accept. He also commits a logical fallacy –  Just because a scientist is stupid doesn’t mean he is wrong.

Taubes’s recent commentary criticizes Kevin’s experiment by saying that it 1) is a diet that is impossible to follow and 2) it ignores appetite. The response to the first point is that the experiment was meant to test a metabolic hypothesis and was not meant to test the effect of a diet. My response to his second point is to stare agape. When Taubes visited NIH a few years ago after his Good Calories, Bad Calories book came out I offered the hypothesis that low carb diets could suppress appetite and this could be why they may be effective in reducing weight. However, he had no interest in this idea and Kevin has told me that he has repeatedly shown no interest in it. (I don’t need to give details on how people have been interested in appetite for decades since it is well done in this post.) I came to the conclusion that appetite control was the primary driver of the obesity epidemic shortly after arriving at NIH. In fact my first BSC presentation was on this topic. The recommendation by the committee was that I should do something else and that NIH was a bad fit for me. However, I am still here and I still believe appetite control is the key.

Paper on new myopia associated gene

The prevalence of near sightedness or myopia has almost doubled in the past thirty years from about 25% to 44%. No one knows why but it is probably a gene-environment effect, like obesity. This recent paper in PLoS Genetics: APLP2 Regulates Refractive Error and Myopia Development in Mice and Humans, sheds light on the subject. It reports that a variant of the APLP2 gene is associated with myopia in people if they read a lot as children. Below is a figure of the result of a GWAS study showing the increase in myopia (more negative is more myopic) with age for those with the risk variant (GA) and for time spent reading. The effect size is pretty large and a myopic effect of APLP2 is seen in monkeys, mice, and humans. Thus, I think that this result will hold up. The authors also show that the APLP2 gene is involved in retinal signaling, particularly in amacrine cells. It is thus consistent with the theory that myopia is the result of feedback from the retina during development.  Hence, if you are constantly focused on near objects, the eye will develop to accommodate for that. So maybe you should send your 7 year old outside to play instead of sitting inside reading or playing video games.