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Highlights of Hope Spring/Summer 23

This is the 2023 Spring/Summer edition of Van Andel Institute's Highlights of Hope donor publication.

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RESEARCH<br />

Study reveals two major obesity<br />

subtypes linked to random chance<br />

How does random chance — the same kind that governs a roll <strong>of</strong><br />

the dice — impact our health?<br />

Quite a lot, it turns out.<br />

A team led by VAI scientist Dr. J. Andrew Pospisilik has identified<br />

two distinct types <strong>of</strong> obesity with physiological and molecular<br />

differences that may have lifelong consequences for health, disease<br />

and response to medication. Importantly, it appears that random<br />

chance plays a role in an individual’s predisposition to one type <strong>of</strong><br />

obesity versus the other.<br />

The findings, published in the journal Nature Metabolism, <strong>of</strong>fer a<br />

more nuanced understanding <strong>of</strong> obesity than current definitions<br />

and reveal new insights into the link between insulin and obesity.<br />

“Nearly two billion people worldwide are considered overweight<br />

and there are more than 600 million people with obesity, yet we<br />

have no framework for stratifying individuals according to their<br />

more precise disease etiologies,” Pospisilik said. “Using a purely<br />

data-driven approach, we see for the first time that there are at<br />

least two different metabolic subtypes <strong>of</strong> obesity, each with their<br />

own physiological and molecular features that influence health.<br />

Translating these findings into a clinically usable test could help<br />

doctors provide more precise care for patients.”<br />

Currently, obesity is diagnosed using body mass index (BMI), an<br />

index correlated to body fat that is generated by comparing weight<br />

in relation to height. It is an imperfect measure, Pospisilik says,<br />

because it doesn’t account for underlying biological differences and<br />

can misrepresent an individual’s health status.<br />

The findings also reveal the role chance plays in predisposing<br />

a person to one <strong>of</strong> the two obesity subtypes. Only 30%–50% <strong>of</strong><br />

human trait outcomes can be linked to genetics or environmental<br />

influences. That means as much as half <strong>of</strong> who we are is governed<br />

by something else. This phenomenon is called unexplained<br />

phenotypic variation (UPV), and it <strong>of</strong>fers both a challenge and<br />

untapped potential to scientists like Pospisilik and his collaborators.<br />

The study indicates that the roots <strong>of</strong> UPV likely lie in epigenetics,<br />

the processes that govern when and to what extent the<br />

instructions in DNA are used. Epigenetic mechanisms are the<br />

reason that individuals with the same genetic instruction manual,<br />

such as twins, may grow to have different traits, such as eye<br />

color and hair color. Epigenetics also <strong>of</strong>fer tantalizing targets for<br />

precision treatment.<br />

“This unexplained variation is difficult to study, but the pay<strong>of</strong>f <strong>of</strong><br />

a deeper understanding is immense,” Pospisilik said. “Epigenetics<br />

can act like a light switch that flips genes ‘on’ or ‘<strong>of</strong>f,’ which can<br />

promote health or, when things go wrong, disease. Accounting<br />

for UPV doesn’t exist in precision medicine right now, but it looks<br />

like it could be half the puzzle. Our findings underscore the power<br />

<strong>of</strong> recognizing these subtle differences between people to guide<br />

more precise ways to treat disease.”<br />

Read more at vai.org/obesity-subtypes.<br />

Research reported in this publication was supported by Van Andel Institute; Max Planck<br />

Gesellschaft; the European Union’s Horizon 2020 Research and Innovation Program under<br />

Marie Skłodowska-Curie grant agreement no. 675610; the Novo Nordisk Foundation and<br />

the European Foundation for the Study <strong>of</strong> Diabetes; the Danish Council for Independent<br />

Research; the National Human Genome Research Institute <strong>of</strong> the National Institutes <strong>of</strong> Health<br />

under award no. R21HG011964 (Pospisilik); and the NIH Common Fund, through the Office<br />

<strong>of</strong> the NIH Director (OD), and the National Human Genome Research Institute <strong>of</strong> the National<br />

Institutes <strong>of</strong> Health under award no. R01HG012444 (Pospisilik and Nadeau). The content is<br />

solely the responsibility <strong>of</strong> the authors and does not necessarily represent the <strong>of</strong>ficial views <strong>of</strong><br />

the National Institutes <strong>of</strong> Health or other granting organizations. Approximately 5% ($50,000)<br />

<strong>of</strong> funding for this study is from federal sources; approximately 95% ($950,000) is from non-<br />

U.S. governmental sources.<br />

DR. J. ANDREW POSPISILIK<br />

12 | VAN ANDEL INSTITUTE HIGHLIGHTS OF HOPE

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