Scientists redefine obesity – Two major subtypes discovered

Scientists distinguish two different types of obesity.

A team led by scientists from the Van Andel Institute discovered two distinct types of obesity with physiological and molecular differences that could have long-term implications for health, disease and drug response.

The results, recently published in the journal Nature Metabolism, provide a more nuanced understanding of obesity compared to existing definitions and could one day help to develop more precise methods of diagnosing and treating obesity and related metabolic disorders.

In addition, the research provides new information about the role of epigenetics and chance in health and sheds light on the link between insulin and obesity.

“Nearly two billion people worldwide are considered overweight and there are more than 600 million people with obesity, but we don’t have a framework for stratifying individuals based on their more precise causes of disease,” said J. Andrew Pospisilik, Ph.D., Chair of Division in Epigenetics from the Van Andel Institute and corresponding author of the study. “Using a purely data-driven approach, we see for the first time that there are at least two different metabolic subtypes of obesity, each with their own physiological and molecular features that affect health. Translating these findings into a clinically useful test could help physicians provide more accurate patient care.”

dr J. Andrew Pospisilik, Chair of the Department of Epigenetics, Van Andel Institute. Photo credit: Van Andel Institute

Currently, body mass index (BMI), an index created by comparing weight and height and correlated to body fat, is used to diagnose obesity. It’s an erroneous measurement, Pospisilik says, because it doesn’t account for underlying biological differences and can be inaccurate when assessing a person’s health status.

Pospisilik and his colleagues discovered four metabolic subtypes that affect individual body types: two tend to be thin and two tend to be obese. They made this discovery using a combination of laboratory studies in mouse models and an in-depth analysis of data from TwinsUK, a pioneering research resource and study cohort developed in the UK.

One obesity subtype is characterized by higher fat mass, while the other was characterized by both greater fat mass and lean muscle mass. Unexpectedly, the researchers discovered that the second form of obesity is also associated with an increase in inflammation, which increases the risk of some cancers and other diseases. Both subtypes have been found in a variety of research populations, including children. These results represent an important step in understanding how these different species affect disease risk and response to treatment.

After identifying the subtypes in the human data, the team verified the results in mouse models. This approach allowed the scientists to compare individual mice that are genetically identical, reared in the same environment, and fed the same amounts of food. The study found that the inflammatory subtype appears to result from epigenetic changes that were triggered purely at random. They also found that there doesn’t seem to be a middle ground – the genetically identical sibling mice either got bigger or stayed smaller, with no gradient between them. A similar pattern was seen in data from more than 150 sets of human twins, each of which was genetically virtually the same.

“Our results in the lab almost duplicated the data from the human twins. We again saw two distinct subtypes of obesity, one of which appeared to be epigenetically ‘triggerable’ and characterized by higher lean mass and fat, strong inflammatory signals, high insulin levels and a strong epigenetic signature,” Pospisilik said.

Depending on the calculation and the traits in question, only 30%-50% of human trait results can be linked to genetic or environmental influences. That means half of us are ruled by something else. Dubbed unexplained phenotypic variation (UPV), this phenomenon offers scientists like Pospisilik and his collaborators both a challenge and untapped potential.

The study points out that the roots of UPV likely lie in epigenetics, the processes that determine when and to what extent instructions are received

” data-gt-translate-attributes=”[{” attribute=””>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 also 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.”

Pospisilik is hopeful that the team’s findings will inform the development of future precision medicine strategies and lead to a version of their method that may be used in doctors’ offices to better understand individual patients’ health and inform care.

Reference: “Independent phenotypic plasticity axes define distinct obesity sub-types” by Chih-Hsiang Yang, Luca Fagnocchi, Stefanos Apostle, Vanessa Wegert, Salvador Casaní-Galdón, Kathrin Landgraf, Ilaria Panzeri, Erez Dror, Steffen Heyne, Till Wörpel, Darrell P. Chandler, Di Lu, Tao Yang, Elizabeth Gibbons, Rita Guerreiro, Jose Bras, Martin Thomasen, Louise G. Grunnet, Allan A. Vaag, Linn Gillberg, Elin Grundberg, Ana Conesa, Antje Körner, PERMUTE and J. Andrew Pospisilik, 12 September 2022, Nature Metabolism.
DOI: 10.1038/s42255-022-00629-2

The study was funded by the Van Andel Institute, Max-Planck-Gesellschaft, the Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie Grant, the Novo Nordisk Foundation and the European Foundation for the Study of Diabetes, the Danish Council for Independent Research, the National Human Genome Research Institute, the NIH Common Fund, through the Office of the NIH Director (OD), and the National Human Genome Research Institute.