While much has been written on how the current obesity epidemic is not limited to humans but also includes house hold pets and zoo animals, some species appear to be more obesity prone than others.
Among dogs, which for centuries have been selectively bred to transform the wild type into all shapes, sizes and temperaments, some breeds likewise appear more prone to weight gain than others – these include labrador retrievers.
Now, a study by Eleanor Raffan and colleagues from Cambridge University, UK, in a paper published in Cell Metabolism, have identified a common deletion within the POMC gene that enhances appetite and feeding behaviour.
The 14 bp deletion in pro-opiomelanocortin (POMC) with an allele frequency of 12% disrupts the β-MSH and β-endorphin coding sequences and is associated with body weight (mean effect size 1.90 kg per deletion allele, equivalent to 0.33 SDs), adiposity, and greater food motivation.
Among another 39 dog breeds, the deletion was only found in the closely related flat-coat retriever (FCR), where it is similarly associated with body weight and food motivation.
The influence of this mutation on feeding behaviour is likely complex:
“It has been reported that owners of more highly food-motivated dogs make greater efforts to limit their dogs’ access to food. However, there is evidence to suggest dogs are able to influence both the type and quantity of food offered to them by their owners. It is possible that behavior changes related to the mutation are sufficient to lead to increased food intake (either by scavenging or soliciting owner-provided food).”
Interestingly, the mutation was found to be significantly more common in Labrador retrievers that had been selected to become assistance dogs than pets suggesting that there may be something about this deletion that positively influences temperament, making them best suited for this kind of work.
“Temperament and “trainability” are the main drivers for selection of assistance dogs, and “positive reinforcement” with food reward is a mainstay of puppy training. We therefore hypothesize that dogs carrying the POMC deletion may be more likely to be selected as assistance dogs.”
Overall, and this should come as no surprise, these findings show that mutations in the same system that regulates human weight and appetite (and perhaps temperament?) is found in obesity prone canines.
Which, incidentally, brings up the issue of selective breeding in humans – but that’s another story.
As this year’s Congress President, together with World Obesity Federation President Dr. Walmir Coutinho, it will be our pleasure to welcome delegates from around the world to what I am certain will be a most exciting and memorable event in one of the world’s most beautiful and livable cities.
The program committee, under the excellent leadership of Dr. Paul Trayhurn, has assembled a broad and stimulating program featuring the latest in obesity research ranging from basic science to prevention and management.
I can also attest to the fact that the committed staff both at the World Obesity Federation and the Canadian Obesity Network have put in countless hours to ensure that delegates have a smooth and stimulating conference.
The scientific program is divided into six tracks:
Track 1: From genes to cells
- For example: genetics, metagenomics, epigenetics, regulation of mRNA and non–coding RNA, inflammation, lipids, mitochondria and cellular organelles, stem cells, signal transduction, white, brite and brown adipocytes
Track 2: From cells to integrative biology
- For example: neurobiology, appetite and feeding, energy balance, thermogenesis, inflammation and immunity, adipokines, hormones, circadian rhythms, crosstalk, nutrient sensing, signal transduction, tissue plasticity, fetal programming, metabolism, gut microbiome
Track 3: Determinants, assessments and consequences
- For example: assessment and measurement issues, nutrition, physical activity, modifiable risk behaviours, sleep, DoHAD, gut microbiome, Healthy obese, gender differences, biomarkers, body composition, fat distribution, diabetes, cancer, NAFLD, OSA, cardiovascular disease, osteoarthritis, mental health, stigma
Track 4: Clinical management
- For example: diet, exercise, behaviour therapies, psychology, sleep, VLEDs, pharmacotherapy, multidisciplinary therapy, bariatric surgery, new devices, e-technology, biomarkers, cost effectiveness, health services delivery, equity, personalised medicine
Track 5: Populations and population health
- For example: equity, pre natal and early nutrition, epidemiology, inequalities, marketing, workplace, school, role of industry, social determinants, population assessments, regional and ethnic differences, built environment, food environment, economics
Track 6: Actions, interventions and policies
- For example: health promotion, primary prevention, interventions in different settings, health systems and services, e-technology, marketing, economics (pricing, taxation, distribution, subsidy), environmental issues, government actions, stakeholder and industry issues, ethical issues
I look forward to welcoming my friends and colleagues from around the world to what will be a very busy couple of days.
For more information on the International Congress on Obesity click here
For more information on the World Obesity Federation click here
For more information on the Canadian Obesity Network click here
This is once again demonstrated in a fascinating series of experiments by Stefano Guidotti and colleagues from the University of Groningen, The Netherlands, in a paper published in Physiology and Behaviour.
The researchers performed their experiments in mice that were selectively bred over 50 generations to voluntarily spend hours in running wheels. Interestingly, the female “runner” mice remain resistant to becoming obese as adults when exposed to a high-fat diet even when they don’t have access to a running wheel.
Thus, these mice are resistant to developing obesity whether they run or just sit around.
What the researchers now show is that this “resistance” to gaining excess weight (bred over generations) can be fully cancelled out simply by exposing the mice to a high-fat diet for a couple of days shortly after birth.
With this exposure, these mice (and even their offspring) are suddenly no longer resistant to weight gain later in life and in fact gain as much weight on high-calories diets as normal mice.
Even more interestingly, the short term perinatal exposure to the high-energy diet does not cancel out their love for running. When given a wheel, they continue running just as much as before but even this no longer prevents them from gaining weight.
Thus it appears that exposure to a high-energy diet during the perinatal period can have profound effects on the risk of developing adult obesity even in animals bred to be obesity resistant – and, the love for running, does not appear to protect against weight gain.
Or, as the authors put it,
“..resistance to high-energy diet-induce obesity in adult female mice from lines selectively bred over ~ 50 generations for increased wheel running behavior was blocked by additional perinatal high-energy diet exposure in only one cycle of breeding. An explanation for this effect is that potential allelic variants underlying the trait of diet-induced obesity proneness were not eliminated but rather silenced by the selection protocol, and switched on again by perinatal high-energy diet exposure by epigenetic mechanisms”
Moreover, this effect of perinatal high-energy diet exposure and its “reversal effect” on obesity resistance can be passed on to the next generation.
Reason enough to wonder just how much the rather dramatic changes in perinatal feeding of infants over the last few decades may be contributing to the obesity epidemic.
Shortly after a meal, there is a spike in the cerebrospinal fluid concentration of nutrients with direct access to various nutrient-sensitive sites in the brain.
Now a paper by Olof Lagerlöf and colleagues, published in SCIENCE, shows that in mice, the glycosylation enzyme O-GlcNAc transferase (OGT), present in a wide range of neurons involved in energy regulation and feeding behaviours, may play an important role in the satiety response.
Genetic and molecular manipulation of this enzyme in adult mice resulted in marked effects on feeding and weight gain.
Reducing the activity of the enzyme resulted in animals eating much larger meals (but not more often) with substantial gain in fat (but not lean) mass.
In contrast, increasing the activity of this enzyme resulted in reduced food intake during eating episodes.
Not only does it make sense that a molecule known to play a role as a nutrient-sensor would play a role in the central regulation of food intake, but the authors are optimistic that this enzyme may be a target for finding new anti-obesity medications.
This, however, does not mean that genetic risk is not modifiable.
Thus, a paper by Carlos Celis-Morales and colleagues, published in OBESITY, suggests that physical activity may attenuate some of the weight gain attributable to the FTO gene, one of the more common obesity risk alleles.
Their study includes data from 1,280 participants in the European Food4Me trial.
Overall, the FTO (rs9939609) genotype was associated with a higher body weight of about 1 Kg per risk allele, 0.5 Kg/m2 higher BMI, and 1.1 cm greater waist circumference.
While these “effects” were higher among inactive individuals (BMI by 1.06 kg/m2 per allele and waist circumference by 2.7 cm per allele), they were lower in individuals with moderate to high physical activity (BMI by 0.16 kg/me and Waist circumference by 0.5 cm).
Thus, it appears that increased physical activity may attenuate (but not fully prevent) the effect of FTO genotype on BMI and WC.
Exactly how clinically relevant these findings are and whether they would have any effect at all on public health messages or individual counselling, where increased physical activity is likely to be recommended irrespective of any “genetic markers” (or at least should be) is pretty doubtful.
Currently, we have yet to await any practical consequences of genotyping individuals for obesity “risk” alleles.