Now a study by Silje Steinbeckk and colleagues from Norway, published in JAMA Pediatrics, suggests that while genetic factors are important, these may not act through an effect on appetite or eating behaviour.
The longitudinal study was conducted in a representative birth cohort at the Trondheim Early Secure Study, enrolled at age 4 years during 2007 to 2008, with follow-ups at ages 6 and 8 years. Analyses included 652 children with genotype, adiposity, and appetite data.
While there was clear effect of genetic risk (measured as a composite score of 32 genetic variants) on increase in body weight and fat mass), there was no clear relationship to appetite traits measured at age 6 years with the Children’s Eating Behavior Questionnaire.
Thus, the authors conclude that while genetic risk for obesity is associated with accelerated childhood weight gain, appetite traits may not be the most promising target for preventing excessive weight gain.
So if not through appetite, how do these genes increase the risk for weight gain. Obviously there are a number of possibilities ranging from subtle effects on energy metabolism, adipocyte differentiation or other factors that may not directly be related to eating behaviour.
Another possibility may well be that the instrument used to assess appetite traits may simply not be sensitive and reliable enough to capture subtle changes in ingestive behaviour.
Thus, while there is no doubt that genetic risk may well be a key determinant of childhood obesity, exactly how this effect is mediated remains unclear.
To students of human physiology, the commonly held view that obesity is simply a matter of energy in and energy out is nothing short of laughable.
Indeed, there are perhaps no other biological functions of more importance for survival of an organism, than those that regulate energy uptake, storage and expenditure – functions, without any form of life would be impossible.
Thus, the finely tuned complex and often highly redundant pathways that have evolved to optimize energy metabolism have evolved to readily switch from states of feeding to starvation with shifts in substrate use (both qualitative and quantitative) – functions that are controlled by hundreds (if not thousands) of genes.
Getting these genes to work in concert, requires a complex system of gene regulation, by which individual genes are switched on an off (to allow or stop protein synthesis) in various tissues to just the right amount at just the right time – a process known as transcriptional control.
Now, a comprehensive review by Adelheid Lempradl and colleagues, published in Nature Genetics, summarizes the multitude of interlinked processes that control transcription of genes involved in energy homeostasis.
As the authors explain,
“Transcriptional control is the sum of the cellular events that select and dose gene transcription. In simple terms, these events converge on the regulation of gene locus accessibility and polymerase activity (including recruitment, pausing, processivity and termination).”
“Energy homeostasis requires multi-layered regulation via dynamic, often periodic, expression of metabolic pathways to properly anticipate and respond to shifts in energy state.”
“Transcription factors act by binding to specific regulatory DNA sequences, thus controlling the transcriptional output of defined target gene sets. They cooperate with co-regulators, which either promote (co-activators) or inhibit (co-repressors) transcription. Together, they build feedback networks and control the stability and responsiveness of energy homeostasis. Metabolic cells use receptors and metabolic machinery to generate specific signalling responses to endocrine inputs (for example, insulin, glucagon or leptin receptors) or metabolic inputs (for example, the primary energy metabolism machinery itself).”
The papers goes on to discuss at length the various regulator, co-regulators and the plethora of epigenetic modifiers that determine how these factors do their job of activating or deactivating relevant genes throughout the body.
Why is any of this important?
“Rapid progress is currently being made in research on chromatin-based regulation of gene expression. Particular unknowns include the mechanisms that establish long-term set points or priming of gene expression. Identifying the processes that establish activation thresholds and maximal output set points, as well as their self-organizing principles is currently an intriguing area of research, and is important in understanding susceptibility to complex trait disorders, including metabolic and autoimmune diseases. For example, many intergenerational and developmental reprogramming paradigms elicit metabolic disease susceptibility. They highlight the potential impact of subtly divergent transcriptional profiles in any given genetic context.”
In other words, understanding these processes are fundamental for our understanding of everything from the body’s weight set point (and how this is altered) to intergenerational transmission of obesity risk from one generation to the next (perhaps the most important driver of the current obesity epidemic).
But the complexity of these processes also raise important issues for clinicians,
“The seemingly exponential growth in this complexity now poses a major challenge for translational researchers in need of simplified but accurate paradigms for clinical use.”
The least we can do is to stop pretending that there is anything easy about energy in and energy out.
As Canada’s national representative in the World Obesity Federation (formerly IASO), the Canadian Obesity Network is proud to co-host the 13th International Congress on Obesity in Vancouver, 1-4 May 2016.
The comprehensive scientific program will span 6 topic areas:
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
Early-bird registration is now open – click here
Abstract submission deadline is November 30, 2015 – click here
For more information including sponsorship and exhibiting at ICO 2016 – click here
I look forward to welcoming you to Vancouver next year.
Nevertheless, for what it is worth, a publication by Ruth Brown and colleagues from York University, Toronto, published in Obesity Research and Clinical Practice, suggests that people today may be more susceptible to obesity than just a few decades ago.
The study looks at self-reported dietary from 36,377 U.S. adults from the National Health and Nutrition Survey (NHANES) between 1971 and 2008 and physical activity frequency data from 14,419 adults between 1988 and 2006 (no activity data was available from earlier years).
Between 1971 and 2008, BMI, total caloric intake and carbohydrate intake increased 10-14%, and fat and protein intake decreased 5-9%.
Between 1988 and 2006, frequency of leisure time physical activity increased 47-120%.
However, for a given amount of caloric intake, macronutrient intake or leisure time physical activity, the predicted BMI was up to 2.3kg/m2 higher in 2006 that in 1988.
So unless there was some major systematic shift in what people were reporting (which seems somewhat unlikely) it is clear that factors other than diet and physical activity may be contributing to the increase in BMI over time – or in other words, it appears that people today, for the same caloric intake and physical activity, are more likely to have a higher BMI than people living a few decades ago.
There are of course several plausible biological explanations for these findings including epigenetics, obesogenic environmental toxins, alterations in gut microbiota to name a few.
If nothing else, these data support the notion that there is more to the obesity epidemic than just eating too much and not moving enough.
While I took a month off from blogging, an international group of researchers published what may well become a landmark paper on the genetics of obesity in the New England Journal of Medicine.
As regular readers may be well aware, a number of previous genetic studies have pointed to the importance of the FTO gene for human obesity – however, what exactly this gene does to effect body weight was largely unclear.
The rs1421085 single-nucleotide variant of this gene has both a high frequency and a strong effect size, which suggests positive selection or bottlenecks (e.g., 44% frequency in European populations vs. 5% in African populations).
In the present paper, that included examination of epigenomic data, allelic activity, motif conservation, regulator expression, and gene coexpression patterns in mice and humans, the researchers showed that the FTO allele associated with obesity represses mitochondrial energy production in adipocyte precursor cells in a tissue-autonomous manner.
To be precise, the rs1421085 variant of this gene apparently disrupts a conserved motif for the ARID5B repressor, which leads to derepression of a potent preadipocyte enhancer and a doubling of IRX3 and IRX5 expression during early adipocyte differentiation. These molecules play key roles in thermogenic dissipation both through UCP-1 and UCP-1-independent pathways.
This change leads to a persistent and cell-autonomous developmental shift from energy-dissipating beige (brite) adipocytes to energy-storing white adipocytes, with a reduction in mitochondrial thermogenesis by a factor of 5. It is also associated with an increase in lipid storage and adipocyte cell size.
Inhibition of Irx3 in adipose tissue in mice reduced body weight and increased energy dissipation without a change in physical activity or appetite.
Knockdown of IRX3 or IRX5 in primary adipocytes from human subjects with the risk allele restored thermogenesis, increasing it by a factor of 7, and overexpression of these genes had the opposite effect in adipocytes from nonrisk-allele carriers.
Finally, repair of the ARID5B motif in primary cultured adipocytes from a patient with the risk allele restored IRX3 and IRX5 repression, activated browning expression programs, and restored thermogenesis, increasing it by a factor of 7.
These deep insights into the function of what is apparently a key pathway in human susceptibility (or resistance) to obesity, offers a number of potential targets for pharmacological interventions for obesity – something that we desperately need for patients struggling with this issue.
However, as an accompanying editorial is quick to point out,
“As yet, there is still no simple path to an anti-obesity drug that can be derived from this research.”
Then again, who expects finding new treatments for obesity to be simple?