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Post-Weight Loss Fat Gain in US Rangers

army-rangersAnd finally, to conclude this week’s discussion of evidence to support the notion that weight cycling predicts weight (fat) gain especially in normal weight individuals, I turn back to the paper by Dulloo and colleagues published in Obesity Reviews, which quotes these interesting findings in US Rangers:

“…U.S. Army Ranger School where about 12% of weight loss was observed following 8–9 weeks of training in a multi-stressor environment that includes energy deficit. Nindl et al. reported that at week 5 in the post-training recovery phase, body weight had overshot by 5 kg, reflected primarily in large gains in fat mass, and that all the 10 subjects in that study had higher fat mass than before weight lost. Similarly, in another 8 weeks of U.S. Army Ranger training course that consisted of four repeated cycles of restricted energy intake and refeeding, Friedl et al. showed that more weight was regained than was lost after 5 weeks of recovery following training cessation, with substantial fat overshooting (∼4 kg on average) representing an absolute increase of 40% in body fat compared with pre-training levels. From the data obtained in a parallel group of subjects, they showed that hyperphagia peaked at ∼4 weeks post-training, thereby suggesting that hyperphagia was likely persisting over the last week of refeeding, during which body fat had already exceeded baseline levels.”

Obviously, association (even in a prospective cohort) does not prove causality or, for that matter, provide insights into the physiological mechanisms underlying this observation.

All we can conclude, is that these observations in US Rangers (and the other studies cited in Dulloo’s article) are consistent with the notion that weight loss in normal weight individuals can be followed by significant weight gain, often overshooting initial weight.

Incidentally, these findings are also consistent with observational studies in women recovering from anorexia nervosa, famine, cancer survivors and other situations resulting in significant weight loss in normal weight individuals.

Certainly enough evidence to consider a work of caution against “recreational” weight loss, especially in individuals of normal weight.

@DrSharma
Edmonton, AB

ResearchBlogging.orgDulloo AG, Jacquet J, Montani JP, & Schutz Y (2015). How dieting makes the lean fatter: from a perspective of body composition autoregulation through adipostats and proteinstats awaiting discovery. Obesity reviews : an official journal of the International Association for the Study of Obesity, 16 Suppl 1, 25-35 PMID: 25614201

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Are Weight-Cycling Elite Athletes Predisposed To Weight Gain?

powerliftingMy recent reading of the paper by Dulloo and colleagues on post-dieting weight gain in non-obese individuals, reminded me of my clinical observation that a surprisingly large proportion of patients I see in our bariatric clinic report a history of competitive sports.

When I have previously discussed this observation with colleagues, the answer I often get is that this weight gain is simply due to the fact that active athletes are used to eating a lot, which they continue to do after their activity levels decline, thus resulting in weight gain – a theory, I don’t quite buy largely because it appears far too simplistic (and I have yet to see any evidence to support it).

Rather, if the phenomenon of weight-cycling induced weight gain is real, one would assume that not all athletes are at risk, but rather that this phenomenon would be limited to athletes in disciplines where weight cycling (e.g. to meet certain weight criteria), often referred to as “weight cutting”, is part of the culture of that sport. Examples of such sports include wrestling, boxing, and weight lifting.

It turns out that this very issue has been studied by Saarni and colleagues, who, in a paper published in the International Journal of Obesity, report their findings on a large national cohort of 1838 male elite athletes who had represented Finland in major international sport competitions in 1920-1965.

This cohort included 370 men engaged in sports in which weight-related performance classes are associated with weight cycling (boxers, weight lifters and wrestlers) and 834 matched control men with no background in athletics.

Over the 20+ years of follow-up, the weight-cycling gained a whooping 5.2 BMI units from age 20 years to their maximum mean weight (at around age 60) conpared to only 3.3 BMI units in non-weight-cycling athletes or just 4.4. BMI units in the non-athletic controls.

Indeed, weight-cycling athletes were about three times as likely to develop obesity (defined as a BMI > 30), than their non-weight cycling colleagues or controls.

This enhanced risk of developing obesity in weight-cycling athletes remained significant even after correction for a number of potential confounders including health habits (smoking, alcohol use, use of high-fat milk or physical activity) or weight at age 20 years.

While this paper does not prove causality, or for that matter, provide any insights into possible biological mechanisms that would promote weight gain, it is certainly consistent with the hypothesis that repeated cycles of weight loss and regain in people who start out with a normal weight (in this case elite athletes) strongly predicts subsequent weight gain and the development of obesity.

Or, as the authors put it,

“The weight cycling behavior of the former athletes engaged in power sports at a young age resembles that of young dieters who lose weight temporarily and soon regain it. The present observations concerning the enhanced weight gain of these athletes raise the concern that the repeated cycles of weight loss and regain caused by dieting at a young age could similarly affect weight in the long term.”

@DrSharma
Edmonton, AB

ResearchBlogging.orgSaarni SE, Rissanen A, Sarna S, Koskenvuo M, & Kaprio J (2006). Weight cycling of athletes and subsequent weight gain in middleage. International journal of obesity (2005), 30 (11), 1639-44 PMID: 16568134

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Did Dieting Make You Fat? Blame Your ‘Proteinstat’

Skeletal muscle

Skeletal muscle

Yesterday, I posted on the intriguing finding (now documented in 15 prospective studies) that dieting can make you fat – especially if you start out with a normal weight.

In the paper by Dulloo and colleagues published in Obesity Reviews, the authors attribute part of this effect to the so far elusive “proteinstat” – a system, similar but different from the “adipostat” – that is designed to protect your lean body mass.

As the paper nicely delineates, the problem with post-dieting weight regain is that the fat comes back first but that the drive to eat does not cease till you have also regained the lost lean body mass (muscle).

It appears as though there are two complimentary biological systems that regulate weight regain.

The better known system is the “adipostat” that worries about protecting and restoring fat mass – the neuroendocrine players include leptin and perhaps other signals derived from fat tissue that signal fat stores to the brain. This system works (primarily through dropping metabolic rate but also through effects on appetite) to very quickly and effectively restore the depleted fat mass after dieting.

The less known system is the “proteinstat”, that apparenty worries about restoring lean body mass. The system works slower than the “adipostat” but continues its activity (often reaching its peak) even after all the lost fat has been regained and you are back to your original weight. In fact, it continuous working (primarily through appetite and cravings) till lean body mass is restored, even if this means gaining even more fat in the process.

In their careful reanalysis of starvation studies, Dulloo and colleagues also come up with an explanation why this process of “weight overshoot” results in more gain the skinnier the individual is to begin with.

“…the lower the initial adiposity, the greater the proportion of energy mobilized as body protein (referred to as P-ratio) during weight loss. The steep part of the negative exponential curve lies between 8–20% body fat, and a shift from the upper to the lower values in this range, generally considered to reflect a ‘normal’range of adiposity for men living in affluent societies, results in 2.5- to 3-fold increase in the P-ratio; the latter constitutes a proxy of the fraction of weight that is lost as FFM since protein belongs to the FFM compartment. This extremely high sensitivity of the P-ratio with regard to the initial body composition emphasizes the critical importance of even small differences in the initial percentage body fat in dictating the individual’s energy-partitioning characteristic and, hence, the pattern of lean and fat tissue deposition during weight loss and subsequent
weight regain, in turn, determining the extent of fat overshooting.”

In other words, lean dieters are far more susceptible to mobilising energy (and thus losing mass) from their muscle than from their fat stores, resulting in a much greater likelihood of overshooting their original weight.

Eventually, as these dieters get fatter with every diet cycle, they get less and less susceptible to this effect, which matches well with the finding that dieting is a far better predictor of long-term weight gain in people with lower fat percentages than in those who already have overweight or obesity).

As for exactly how the “proteinstat” works, much remains unclear. Early work focussed on the notion that certain amino acids may serve as signals of protein stores, however, now work is focussing on the far more plausible theory that some of the over 100 molecules now known to be secreted by skeletal muscle (myokines) may play a role in this system.

Certainly a topic that will be interesting to watch develop over the coming years.

@DrSharma
Calgary, AB

ResearchBlogging.orgDulloo AG, Jacquet J, Montani JP, & Schutz Y (2015). How dieting makes the lean fatter: from a perspective of body composition autoregulation through adipostats and proteinstats awaiting discovery. Obesity reviews : an official journal of the International Association for the Study of Obesity, 16 Suppl 1, 25-35 PMID: 25614201

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When Identical Twins Are Different

Professor Aila Rissanen, University of Helsinki, Finland

Professor Aila Rissanen, University of Helsinki, Finland

This year’s prestigious Fredrich Wassermann Award of the European Association for the Study of Obesity presented at the 22nd European Congress on Obesity goes to Helsinki’s Aila Rissanen, Europe’s grande dame of obesity research.

I have personally known Aila for as lo as I have been involved in obesity and there is much in her work and approach to obesity that has stimulated my own thoughts on this issue.

In her acceptance address, Aila chose to focus on her work in BMI-discordant twins (among the many topics she has worked on) due to the remarkable insights into the “natre-nurture” discussion that this model offers.

Indeed, it is extremely rare to find genetically identical twins, who differ in body weight (demonstarting just how highly heritable body weight actually is). Thus, body weight in identical twins is remarkably homogeneous not only because of the heritability of weight per se but also due to heritability of weight gain.

Cining the work of her wildly successful trainee Kirsi Pietilainen, Aila described the efforts it took to identify just 30 obesity discordant (weight difference of >10 Kg) identical twins from well over 500 identical twin pairs.

These discordant twin pairs have now been extensively phenotyped with every imaginable laboratory test, measurement and tissue biopsies.

The most consistent difference between the discordant twins appears to be a greater level of physical activity in the leaner twin, which appears to precede the onset of weight gain.  In addition to voluntary physical exertion, there also appears to be a significant difference in fidgeting between the twins.

Compared to their co-twins, the obese twins had greater pro-inflammatory lipid profiles, lower antioxident activity and higher pro-coagulation markers. The reasons for these differences remains unclear.

Finally, Aila provided a brief overview of some of the exciting work that is now going on to further study the differences between these genetically identical but obesity disparate twins – metabolomics, lipidomics, epigenomics and even bacteriomics.

Although any of this has yet to translate to better obesity prevention or management, you never know where these fundamental insights into human biology may lead you.

For know, this is certainly a space I intend to watch.

@DrSharma
Prague, Czech Republic

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Epigenetic Obesity In The Fruit Fly

sharma-obesity-drosophila1Regular readers are well aware of the considerable evidence now supporting the notion that inter-generational transmission of obesity risk through epigenetic modification may well be a key factor in the recent global rise in obesity rates (over the past 100 years or so).

Now a brief review article by Susan Ozanne from the University of Cambridge, UK, published in the New England Journal of Medicine, describes how researchers have now identified a clear and conserved epigenetic signature that is associated with obesity across species (from the fruit fly all the way to humans).

The article discusses how the transmission of susceptibility to obesity can occur as a consequence of “developmental programming,” whereby environmental factors (e.g. a high-fat diet) encountered at the point of conception and during fetal and neonatal life can permanently influences the structure, function, and metabolism of key organs in the offsprin, thus leading to an increased risk of diseases such as obesity later in life.

There is now evidence that such intergenerational transmission of disease can occur through environmental manipulation of both the maternal and paternal lines – thus, this is not something that is just a matter of maternal environment.

Thus, as Ozanne points out,

“Epigenetic mechanisms that influence gene expression have been proposed to mediate the effects of both maternal and paternal dietary manipulation on disease susceptibility in the offspring (these mechanisms include alterations in DNA methylation, histone modifications, and the expression of microRNAs).”

Work in the fruit fly has linked the effect of paternal sugar-feeding on the chromatin structure at a specific region of the X chromosome and transcriptome analysis of embryos generated from fathers fed a high-sugar diet, revealed dysregulation of transcripts encoding two proteins (one of them is called Su(var)) known to change chromatin structure and gene regulation.

Subsequent analyses of microarray data sets from humans and mice likewise revealed a depletion of the Su(var) proteins in three data sets from humans and in two data sets from mice.

Thus,

“This finding is consistent with the possibility that the depletion of the Su(var) pathway may be brought about by an environmental insult to the genome that is associated with obesity.”

Not only do these studies provide important insights into just how generational transmission of obesity may work but it may also lead to the development of early tests to determine the susceptibility of individuals to the future development of conditions like obesity or diabetes based on epigenetic signatures.

All of this may be far more relevant for clinical practice than most readers may think – indeed, a focus on maternal (and now paternal?) health as a target to reduce the risk of childhood (and adult) obesity is already underway.

This issue will certainly be a “hot topic” at the Canadian Obesity Summit in Toronto later this month.

@DrSharma
Edmonton, AB

 

 

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