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Environmental Factors Affect the Heritability of Obesity

sharma-obesity-dna_molecule9To anyone, who understands genetics, this heading is simply common sense.

Unfortunately, most people have rather simplistic views of genetics – either you have a gene for disease X and you get it, or you don’t have the gene for disease X and so you’re safe.

In reality, this is not at all how genetics works (with the few rare exceptions of single-gene disorders – and even there is not at all as straightforward as most people imagine).

In fact, whether or not a gene (or group of genes) actually results in a specific phenotype is highly dependent on the environment.

As a simple example: I could be genetically highly predisposed to salt-sensitivity (i.e. having a blood pressure increase on a high-salt diet) – but unless I am actually exposed to a high-salt diet, I can go my entire life without ever developing high blood pressure.

This is pretty much the case for all complex (and even some single-gene) disorders – it is only when you put the susceptible “disease gene(s)” in the wrong environment, that the gene does what it does. This is why most “nature vs. nurture” debates lead nowhere – it is virtually never one OR the other – it is mostly BOTH!

A good example of how changing environments may be important when studying the genetics of diseases is suggested in a new study by James Niel Rosenquist and colleagues, published in the PNAS.

The researchers examines the association between the FTO gene and BMI using longitudinal data from the Framingham Heart Study collected over 30 y from a geographically relatively localized sample in the US.

What they found was that the well-documented association between the rs993609 variant of the FTO (fat mass and obesity associated) gene and body mass index (BMI) varies substantially across birth cohorts, time period, and the lifecycle, with a apparently increasing impact of this gene for those born after 1942.

As the authors point out,

“Such cohort and period effects integrate many potential environmental factors, and this gene-by-environment analysis examines interactions with both time-varying contemporaneous and historical environmental influences.”

Thus,

“These results suggest genetic influences on complex traits like obesity can vary over time, presumably because of global environmental changes that modify allelic penetrance.”

In other words, as the environment changes, certain genetic “phenotypes” may become more (or less) common.

It is however important to remember in this context that the term “environment” is rather broad and may include biological drivers that include changes in the epigenome, bacteriome or even virome, all of which will have substantially changed over time (and continue to change as we we speak).

On a more practical level, this is also why genetic testing for complex genetic diseases (and so-called “personalized” medicine) will likely be nothing more than a pipe dream and a money grab, at least for the foreseeable future.

@DrSharma
Edmonton, AB

ResearchBlogging.orgRosenquist JN, Lehrer SF, O’Malley AJ, Zaslavsky AM, Smoller JW, & Christakis NA (2015). Cohort of birth modifies the association between FTO genotype and BMI. Proceedings of the National Academy of Sciences of the United States of America, 112 (2), 354-9 PMID: 25548176

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Social Network Analysis of the Obesity Research Boot Camp

bootcamp_pin_finalRegular readers may recall that for the past nine years, I have had the privilege and pleasure of serving as faculty of the Canadian Obesity Network’s annual Obesity Research Summer Bootcamp.

The camp is open to a select group of graduate and post-graduate trainees from a wide range of disciplines with an interest in obesity research. Over nine days, the trainees are mentored and have a chance to learn about obesity research in areas ranging from basic science to epidemiology and childhood obesity to health policy.

Now, a formal network analysis of bootcamp attendees, published by Jenny Godley and colleagues in the Journal of Interdisciplinary Healthcare, documents the substantial impact that this camp has on the careers of the trainees.

As the analysis of trainees who attended this camp over its first 5 years of operation (2006-2010) shows, camp attendance had a profound positive impact on their career development, particularly in terms of establishing contacts and professional relationships.

Thus, both the quantitative and the qualitative results demonstrate the importance of interdisciplinary training and relationships for career development in obesity researcher (and possibly beyond).

Personally, participation at this camp has been one of the most rewarding experiences of my career and I look forward to continuing this annual exercise for years to come.

To apply for the 2015 Bootcamp, which is also open to international trainees – click here.

@DrSharma
Toronto, ON

ResearchBlogging.orgGodley J, Glenn NM, Sharma AM, & Spence JC (2014). Networks of trainees: examining the effects of attending an interdisciplinary research training camp on the careers of new obesity scholars. Journal of multidisciplinary healthcare, 7, 459-70 PMID: 25336965

 

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Can Education Offset The Genetic Risk For Obesity?

sharma-obesity-dna_molecule9Obesity is a highly heritable condition with considerable penetrance, especially in our obesogenic enviroment.

However, as I have pointed out before, having a genetic predisposition for obesity (like having a genetic predisposition for other diseases such as diabetes or high blood pressure) does not mean your fate is chiseled in stone. Lifestyle changes can significantly reduce the risk, but those with a stronger genetic predisposition will have to work a lot harder at not gaining weight than those who are naturally slender.

That said, a new study by Liu and colleagues from Harvard University, published in Social Science & Medicine, shows that better education may offset a substantial proportion of the genetic risk for obesity and/or diabetes.

The researchers created genetic risk scores for obesity and diabetes based on single nucleotide polymorphism (SNPs) confirmed as genome-wide significant predictors for BMI (29 SNPs) and diabetes risk (39 SNPs) in over 8000 participants in the Health and Retirement Study.

Linear regression models with years of schooling indicate that the effect of genetic risk on both HbA1c and BMI was smaller among people with more years of schooling and larger among those with less than a high school (HS) degree compared to HS degree-holders.

As one may expect, estimates from the quantile regression models consistently indicated stronger associations for years of schooling and genetic risk scores at the higher end of the outcome distribution, where individuals are at actual risk for diabetes and obesity.

In other words, the greater the genetic risk for diabetes or obesity, the greater the positive impact of finishing high-school or college.

In contrast, having less than a high-school education augmented the genetic risk for these conditions.

From these findings the authors conclude that,

“Our findings provide some support for the social trigger model, which speculates that the social environment can attenuate or exacerbate inherent genetic risks. Furthermore, it suggests social stratification may shape how genetic vulnerability is expressed. Social hierarchies based on socioeconomic status determine the health status of individuals. According to fundamental cause theory, policies and interventions must address social factors directly to have a population-level impact on disease risk . Our results show how education, a fundamental cause of health and disease, can serve as a valuable resource that offsets even innate biological risk. Education increases an individual’s ability to adapt, modify, and use surrounding resources. As such, polices that reduce disparities in education may help offset underlying genetic risk.”

This study strongly supports my view that one cannot (and should not) ignore genetic risk when studying the effect of environmental or behavioural factors in populations or individuals. Indeed, the greatest benefit of these interventions clearly appear to be found in those with the highest genetic risk.

@DrSharma
Ottawa, ON

ResearchBlogging.orgLiu SY, Walter S, Marden J, Rehkopf DH, Kubzansky LD, Nguyen T, & Glymour MM (2014). Genetic vulnerability to diabetes and obesity: Does education offset the risk? Social science & medicine (1982) PMID: 25245452

 

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Call For Abstracts: Canadian Obesity Summit, Toronto, April 28-May 2, 2015

COS2015 toronto callBuilding on the resounding success of Kananaskis, Montreal and Vancouver, the biennial Canadian Obesity Summit is now setting its sights on Toronto.

If you have a professional interest in obesity, it’s your #1 destination for learning, sharing and networking with experts from across Canada around the world.

In 2015, the Canadian Obesity Network (CON-RCO) and the Canadian Association of Bariatric Physicians and Surgeons (CABPS) are combining resources to hold their scientific meetings under one roof.

The 4th Canadian Obesity Summit (#COS2015) will provide the latest information on obesity research, prevention and management to scientists, health care practitioners, policy makers, partner organizations and industry stakeholders working to reduce the social, mental and physical burden of obesity on Canadians.

The COS 2015 program will include plenary presentations, original scientific oral and poster presentations, interactive workshops and a large exhibit hall. Most importantly, COS 2015 will provide ample opportunity for networking and knowledge exchange for anyone with a professional interest in this field.

Abstract submission is now open – click here

Key Dates

  • Notification of abstract review: January 8, 2015
  • Call for late breaking abstracts open: Jan 12-30, 2015
  • Notification of late breaking abstracts and handouts and slides due : Feb 27, 2015
  • Early registration deadline: March 3, 2015

For exhibitor and sponsorship information – click here

To join the Canadian Obesity Network – click here

I look forward to seeing you in Toronto next year!

@DrSharma
Montreal, QC

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Healthy Obesity: More Questions Than Answers?

sharma-obesity-visceral-fat-mriRegular readers will be well aware of the evidence that a subset of people living with obesity can be remarkably healthy despite carrying a rather large amount of body fat.

This issue of “healthy obesity” was the topic of the 13th Stock Conference of the International Association of the Study of Obesity, the proceeding of which are now published in Obesity Reviews.

As the authors note,

“The ‘healthy obese’ phenotype was described in the 1980s, but major advancements in its characterization were only made in the past five years. During this time, several new mechanisms that may be involved in health preservation in obesity were proposed through the use of transgenic animal models, use of sophisticated imaging techniques and in vivo measurements of insulin sensitivity. However, the main obstacle in advancing our understanding of the metabolically healthy obese phenotype and its related long-term health risks is the lack of a standardized definition.”

The latter is a real problem because finding people with obesity, who are truly metabolically and otherwise healthy becomes harder the higher the BMI gets – this makes the study of this phenomenon rather challenging.

Nevertheless,

“One of the most consistent characteristics of metabolic health in obesity across studies in humans is reduced liver lipid. This is likely the consequence of increased capacity for storing fat coupled with improved mitochondrial function in adipose tissue and decreased de novo lipogenesis in liver. This can also result in decreased deposition of lipids, including bioactive species, in skeletal muscle. Decreased adipose tissue inflammation with decreased macrophages and a unique T-cell signature with an anti-inflammatory circulating milieu were also suggested to characterize metabolic health in obesity. Anecdotal data support a possible role for healthier lifestyle, including increased level of physical activity and healthier diet. It remains to be established whether a favourable metagenomic signature is a characteristic of metabolic health in obesity.”

Finland’s, Dr Kirsi Pietiläinen explained that,

“..three energy dissipation pathways, oxidative phosphorylation, fat oxidation and amino acid catabolism showed preserved pathway activities in subjects who are MHO at a level similar to their lean counterparts. In contrast, these pathways were significantly down-regulated in adipose samples from obese twins with metabolic disturbances. Another potential hallmark of metabolic health, a favourable inflammatory profile of the adipose tissue was also observed in the MHO twins. Also, the fat cells of the MHO twins were smaller with evidence of more active differentiation processes within the fat tissue. As multiple mitochondrial pathways are vital in adipocyte differentiation [29], it is possible that mitochondrial malfunction impairs the development of new fat cells, which in turn results in an inability of the adipose tissue to expand under conditions of energy excess. This failure of fat cell proliferation has long been suspected to constitute the framework for ectopic fat storage, insulin resistance and type 2 diabetes.”

Other speakers discussed other aspects including immune function and microbiata in this phenomenon.

Finally, the authors concluded that,

“identifying underlying factors and mechanisms associated with this phenotype will eventually be invaluable in helping the scientific and medical community understand factors that predispose, delay or protect obese individuals from metabolic disturbances. It is essential to underscore that the MHO concept presently only address the cardio-metabolic risks associated with obesity; it is therefore important that patients who are MHO are still very likely to present many other obesity-related complications such as altered physical and/or physiological functional status, sleep problems, articulation and postural problems, stigma, etc. Importantly, the MHO concept supports the fact that classification based on excess adiposity per se (e.g. BMI or body composition if available) should be supplemented with obesity-related comorbidities, e.g. with fasting insulin as proposed by the Edmonton obesity classification system.”

Certainly a space to watch as we learn more and more about the “healthy obesity” phenotype.

@DrSharma
Edmonton, AB

ResearchBlogging.orgSamocha-Bonet D, Dixit VD, Kahn CR, Leibel RL, Lin X, Nieuwdorp M, Pietiläinen KH, Rabasa-Lhoret R, Roden M, Scherer PE, Klein S, & Ravussin E (2014). Metabolically healthy and unhealthy obese – the 2013 Stock Conference report. Obesity reviews : an official journal of the International Association for the Study of Obesity PMID: 25059108

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