Regular readers will be well aware of the increasing data supporting the importance of adequate restorative sleep on metabolism and weight management.
Now, a study by Wang Xuewen and colleagues, published in SLEEP, shows just how detrimental sleep deprivation can be during a weight-loss diet.
Their study included thirty-six 35-55 years oldadults with overweight or obesity, who were randomized to an 8-week caloric restriction (CR) regimen alone (n=15) or combined with sleep restriction (CR+SR) (n=21). All participants were instructed to restrict daily calorie intake to 95% of their measured resting metabolic rate. Participants in the CR+SR group were also instructed to reduce time in bed on 5 nights and to sleep ad libitum on the other 2 nights each week.
The CR+SR group reduced sleep by about 60 minutes per day during sleep restriction days, and increased sleep by 60 minutes per day during ad libitum sleep days, resulting in a sleep reduction of about 170 minutes per week.Although both groups lost a similar amount of weight during the study ~3 Kg). However, the proportion of total mass lost as fat was significantly greater in the CR group (80% vs. 16%).
In line with this substantial difference in fat reduction, resting respiratory quotient was significantly reduced only in the CR group.
Importantly, these effects of sleep deprivation on fat loss were observed despite the fact that subjects were allowed to sleep as much as they wanted on the non-restricted days. This suggests that the negative effects of sleep deprivation during weight loss are not made up by “make-up” sleep.
Although overall, the amount of weight lost in this study is modest, it clearly fits with the notion that adequate sleep (in this case, during weight loss), can be an important part of weight management.
Clearly, the role of sleep in energy homeostasis will remain an interesting field of research, as we continue learning more about how sleep (or rather lack of it) affects metabolism.
Regular readers will be quite familiar with the findings that cardiometabolic health appears to be far more related to “fitness” than to “fatness” – in other words, it is quite possible to mitigate the metabolic risks commonly associated with excess body fat by improving cardiorespiratory fitness.
Now, a study by Kathy Do and colleagues from York University, Toronto, published in BMC Obesity, shows that this relationship also holds for people with quite severe obesity.
The researcher studied 853 patients from the Wharton Medical Clinics in the Greater Toronto Area, who completed a clinical examination and maximal treadmill test. Patients were then categorized into fit and unfit based on age- and sex-categories and in terms of fatness based on BMI class.
Within the sample, 41% of participants with mild obesity (BMI<35) had high fitness whereas only 25% and 11% of the participants with moderate (BMI 35-40) and severe obesity (BMI>40), respectively, had high fitness.
Individuals with higher fitness tended to be younger and more likely to be female.
While overall fitness did not appear to be independently associated with most of the metabolic risk factors (except systolic blood pressure and triglycerides), the effect of fitness in patients with severe obesity was more pronounced. Thus, the prevalent relative risk for pre-clinical hypertension, hypertriglyceridemia and hypoalphalipoproteinemia and pre-diabetes was only elevated in the unfit moderate and severe obesity groups, and fitness groups were only significantly different in their relative risk for prevalent pre-clinical hypertension within the severe obesity group.
Similarly, high fitness was associated with smaller waist circumferences, with differences between high and low fitness being larger in those with severe obesity than with mild obesity.
Based on these findings, the researchers conclude that the favourable associations of having high fitness on health may be similar if not augmented in individuals with severe compared to mild obesity.
However, it is also apparent based on the rather low number of “fit” individuals in the severe obesity category (only about 1 in 10), that maintaining a high level of fitness proves to be more challenging the higher the BMI.
The human GLP-1 analogue liraglutide is now approved for the long-term medical treatment of obesity in an ever-increasing number of countries. Its safety and clinical effectiveness is now well established and there is no doubt that this is an important addition to the rather limited number of treatment options available to people living with obesity.
Interestingly, however, liraglutide has also been shown to promote the differentiation of pre-adipocytes or, in other words, promote the formation of new fat cells.
While this may seen worrying or even counter-intuitive, we much remember that having more (smaller) rather than fewer (bigger) fat cells actually has substantial metabolic advantage s- there is indeed ample data showing that large adipocyte cell size and limited capacity to grow fat cells (the extreme case of which is seen in people with lipodystrophy) is actually a key risk factor for metabolic problems including insulin resistance, possible by promoting the accumulation of ectopic fat (e.g. in liver and skeletal muscle).
Now, a paper by Yongmei Liand colleagues, published in Molecular Medicine Reports provides additional insight into the cellular pathways involved in liraglutide’s adipogenic effects.
Using a series of in vitro experiments, the researchers show that liraglutide does indeed promote the adipogenic differentiation of 3T3-L1 cells (a widely used murine preadipocyte cell line) through a process that upregulates the expression of C/EBPα and PPARγ at the early phase of adipogenic differentiation, promots the expression of lipogenesis associated genes including aP2, and enhances the accumulated of lipids.
At the same time, liraglutide appears to suppress cell proliferation via the Hippo‑yes‑associated protein (YAP) signaling pathway, thereby allowing these cells to transform into mature adipocytes sooner.
How relevant these observations are for humans remains to be seen, but certainly the promotion of adipogenic differentiation may hold the potential for improving insulin sensitivity and reducing the metabolic risks associated with excess weight gain.
Disclaimer: I have received speaking and consulting honoraria from Novo Nordisk, the maker of liraglutide.
As one may well imagine, changes in body weight (up or down) can profoundly affect a vast number of hormonal and metabolic pathways.
Now, a team of researchers led by Brian Piening and colleagues, in a paper published in Cell Systems used a broad “omics” based approach to study what happens when people lose ore gain weight.
Specifically, the goal of this study was to:
(1) assemble a comprehensive map of the molecular changes in humans (in circulating blood as well as the microbiome) that occur over the course of a carefully controlled weight gain and their reversibility with weight loss; and
(2) determine whether inulin sensitive (IS) and insulin resistant (IR) individuals who are matched for degree of obesity demonstrate unique biomolecular signatures and/or pathway activation during similar weight gain.
The study included 23 carefully selected healthy participants with BMI 25–35 kg/m2, were studied. Samples were collected at baseline. They then underwent a 30-day weight gain period (average 2.8 kg), followed by an eucaloric diet for 7 days, at which point a second fasted sample of blood and stool was collected. Each participant then underwent a caloric-restricted diet under nutritionist supervision for a subsequent 60-day period designed to return each participant back to his/her initial baseline weight, at which point a third set of fasted samples of blood and stool were collected. A subset of participants returned for a follow-up sampling approximately 3 months after the end of the perturbation.Insulin resistance was assessed at baseline using a modified insulin suppression test.
The large-scale multi-omics assays performed at all time points on each participant included genomics, proteomics, metabolomics and microbiomics.
Despite some differences between the IS and IR group (particularly in differential regulation of inflammatory/immune response pathways), overall, molecular changes were dominated by inter-personal variation (i.e. changes within the same individual), which accounted for more than 90% of the observed variance in some cases (e.g., cytokines). The most striking changes with weight gain were in inflammation response pathways (despite the rather modest weight gain) and were (fortunately) reversed by weight loss.
As the authors note,
“Comparing the variation in cytokine levels between multiple baselines in a single individual versus across individuals, we observed a striking difference: for almost all cytokines, the within-individual coefficient of variation was under 20%, whereas the variation across individuals was 40%–60%. This shows that our baseline cytokine profiles are unique to the individual, a point that has significant implications for one-size-fits-all clinical cytokine assays for the detection and/or monitoring of disease.”
On the opposite side of the spectrum, proteomics and metabolomics measurements had a substantial unexplained component (30% and 35%, respectively), highlighting the presence of unaccounted factors (e.g., food, exercise, and other changing environmental factors) or a subject-specific reaction to the perturbation.
Notably, not all of the responses we observed were consistent across IR and IS participants.
“In particular, for the microbiome, we observed that the microbe A. muciniphila was weight gain responsive only in insulin-sensitive participants. The abundance of this particular microbe in IR individuals did not change across perturbations and was barely or not detectable in most IR individuals.”
Clearly, these findings highlight the fact that each individual is biochemically unique, which the authors note, makes a strong case for personalized analysis in medicine.
Perhaps more importantly for researchers, nearly all of the data are publicly available, enabling exploration of inter-omic relationships and alterations across a longitudinal perturbation, thus providing a valuable resource for the development and validation of bioinformatic tools and pipelines integrating disparate data types.
If there is one article in the 2018 special issue of JAMA on obesity that we could have well done without, it is surely the one by Eve Guth promoting the age-old notion that simply counting calories is a viable and effective means to manage body weight.
As the author suggests:
“It is better for physicians to advise patients to assess and then modify their current eating habits and then reduce their caloric ingestion by counting calories. Counseling patients to do this involves provision of simple handouts detailing the calorie content of common foods, suggested meal plan options, an explanation of a nutrition label, and a list of websites with more detailed information. Patients should be advised that eating about 3500 calories a week in excess of the amount of calories expended results in gaining 1 lb (0.45 kg) of body weight. If a patient reduces caloric ingestion by 500 calories per day for 7 days, she or he would lose about 1 lb of body weight per week, depending on a number of other factors. This is a reasonable and realistic place to start because this approach is easily understood and does not ask a patient to radically change behavior.”
There is so much wrong with this approach, that it is hard to know exactly where to start.
For one, this advise is based on the simplistic assumption that obesity is simply a matter of managing calories to achieve and sustain long-term weight loss.
Not only, do we have ample evidence that these type of approaches rarely result in long-term sustained weight-loss but, more importantly this type of advice comfortably ignores the vast body of scientific literature that tells us that body weight is a tightly regulated physiological variable and that there are a host of complex neuroendocrine responses that will defend our bodies against long-term weight loss – mechanisms that most people (irrespective of whether they have obesity or not) will find it exceedingly hard to overcome with “will-power” alone.
No doubt, caloric “awareness” can be an eye-opener for many patients and there is good evidence that keeping a food journal can positively influence dietary patterns and even reduce “emotional” eating. But the idea that cognitively harnessing “will-power” to count calories (a very “unnatural” behaviour indeed), thereby creating and sustaining a long-term state of caloric deficit is rather optimistic at best.
In fact, legions of people who have been battling obesity all their lives can attest to the fact that encouragement to simply “eat less and move more” (ELMM) as a viable strategy to achieve and sustain significant weight loss is about as effective as reminding people with depression to focus on the brighter side of things and cheer up.
Not to mention the debunked 3500 calorie deficit a week = 1 lb weight loss (week after week after week till a so called “healthy” weight is achieved) myth, which is simply not how bodies work.
Continuing to propagate this antiquated and simplistic idea of what it takes to manage a complex chronic disease like obesity, is exactly what is holding the field back.
There is no reason to assume why more of the same should produce results that are any different from those in the past.
It is time we recognise that restricting caloric intake by willpower alone (irrespective of the dietary strategy) simply does not change the biology of the underlying physiology that effectively defends our bodies against long-term weight loss.
Reading an article like this in 2018 in a reputable journal that promises to “reimagine” obesity is both disappointing and a stark reminder of just how far we have to go to change widely held beliefs that obesity is simply a matter of calories in and calories out – if only life (and human biology) was that simple!