Major research study unveils a new definition of obesity

[Apr. 10, 2023: JD Shavit, The Brighter Side of News]

A new study led by scientists at the Van Andel Institute has identified two distinct types of obesity, each with their own unique physiological and molecular features that can impact an individual's health and response to medication. The study, which was published in the journal Nature Metabolism, also sheds new light on the role of epigenetics and chance in health, providing insights into the link between insulin and obesity.

Currently, obesity is diagnosed using body mass index (BMI), a measure that correlates weight in relation to height. However, BMI does not account for underlying biological differences, which can misrepresent an individual's health status. The study's findings offer a more nuanced understanding of obesity than current definitions, potentially leading to more precise ways to diagnose and treat obesity and associated metabolic disorders.

"Nearly two billion people worldwide are considered overweight, and there are more than 600 million people with obesity, yet we have no framework for stratifying individuals according to their more precise disease etiologies," said J. Andrew Pospisilik, Ph.D., chair of Van Andel Institute's Department of Epigenetics and corresponding author of the study. "Translating these findings into a clinically usable test could help doctors provide more precise care for patients."

Using a combination of laboratory studies in mouse models and deep analysis of data from TwinsUK, a pioneering research resource and study cohort developed in the United Kingdom, Pospisilik and his collaborators discovered four metabolic subtypes that influence individual body types: two prone to leanness and two prone to obesity. The researchers identified two subtypes of obesity, one characterized by greater fat mass while the other by greater fat and lean muscle mass.

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Surprisingly, the team found that the second obesity type was associated with increased inflammation, which can elevate the risk of certain cancers and other diseases. Both subtypes were observed across multiple study cohorts, including in children. These insights are an important step toward understanding how these different types impact disease risk and treatment response.

After identifying the subtypes in human data, the team verified the results in mouse models. By comparing individual mice that are genetically identical, raised in the same environment, and fed the same amounts of food, the study revealed that the inflammatory subtype appears to result from epigenetic changes triggered by pure chance.

The researchers found that there seems to be no middle ground — the genetically identical sibling mice either grew to a larger size or remained smaller, with no gradient between them. A similar pattern was seen in data from more than 150 human twin pairs, each of whom were virtually the same genetically.

"Our findings in the lab almost carbon copied the human twin data. We again saw two distinct subtypes of obesity, one of which appeared to be epigenetically 'triggerable,' and was marked by higher lean mass and higher fat, high inflammatory signals, high insulin levels, and a strong epigenetic signature," Pospisilik said.

The study indicates that the roots of unexplained phenotypic variation (UPV) likely lie in epigenetics, the processes that govern when and to what extent the instructions in DNA are used. Epigenetic mechanisms are the reason that individuals with the same genetic instruction manual, such as twins, may grow to have different traits, such as eye color and hair color.

Epigenetics offer tantalizing targets for precision treatment. "This unexplained variation is difficult to study, but the payoff of a deeper understanding is immense," Pospisilik said. "Epigenetics can act like a light switch that flips genes 'on' or 'off,' which can promote health or, when things go wrong, disease. Accounting for UPV doesn't exist in precision medicine right now, but it looks like it could be half the puzzle. Today's findings underscore the power of recognizing these subtle differences between people to guide more precise ways to treat disease."

The study's findings have significant implications for the future of precision medicine, which aims to tailor medical treatment to an individual's specific genetic makeup, environment, and lifestyle. By identifying these two distinct types of obesity, researchers are one step closer to developing more targeted and effective treatments for the condition.

Currently, the most common treatment for obesity is weight loss through lifestyle changes, such as diet and exercise. In some cases, medications or surgery may be recommended for severe obesity. However, these treatments are not always effective, and there is a growing need for more personalized approaches to obesity treatment.

The study's authors suggest that by understanding an individual's specific subtype of obesity, doctors may be able to recommend more targeted treatments, such as medications or lifestyle changes that are specifically tailored to their subtype. For example, individuals with the inflammatory subtype may benefit from anti-inflammatory medications, while those with the other subtype may benefit more from interventions focused on reducing overall body fat.

Furthermore, the study's findings highlight the importance of understanding the role of epigenetics in disease development and progression. By identifying the epigenetic mechanisms that contribute to the development of specific subtypes of obesity, researchers may be able to develop new targeted therapies that modulate these mechanisms and prevent or treat obesity and associated metabolic disorders.

The study's results are also relevant to the broader field of precision medicine, which seeks to develop treatments that are tailored to an individual's unique genetic makeup, environment, and lifestyle. As Pospisilik noted, the study's findings underscore the importance of accounting for unexplained phenotypic variation in precision medicine.

While the study's findings are promising, there is still much work to be done before the results can be translated into clinical practice. Further research is needed to validate the study's findings in larger populations and to identify the epigenetic mechanisms that underlie the different subtypes of obesity.

The study represents a significant step forward in our understanding of obesity and associated metabolic disorders. By identifying two distinct subtypes of obesity with unique physiological and molecular features, the study provides a more nuanced understanding of the condition that may one day inform more precise ways to diagnose and treat obesity.

Furthermore, the study highlights the importance of understanding the role of epigenetics in disease development and progression and underscores the potential for targeted therapies that modulate these mechanisms. The study's findings have significant implications for the future of precision medicine and offer hope for more effective treatments for obesity and associated metabolic disorders.

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