Mapping the Genetics of Brown Fat: insitro's Presentation at Keystone Symposium

Summary

Share How insitro unlocked population-scale human genetics in a tissue that has resisted measurement for decades – and what it reveals about peripheral approaches to metabolic disease The Furnace We Couldn’t See The human body contains a type of fat tissue engineered to burn energy rather than store it. Brown adipose tissue – dense with mitochondria, rich in uncoupling proteins – converts glucose and lipids into heat through non-shivering thermogenesis. For years, researchers have documented this tissue’s role in energy expenditure, its associations with favorable metabolic profiles, its potential as a therapeutic target for obesity and cardiometabolic disease. What they have not been able to do is map its genetic architecture. The genetic variation was there, distributed across the genomes of hundreds of thousands of biobank participants. The barrier was measurement itself. Brown fat, sparse and anatomically diffuse, concentrated in small depots around the neck and upper chest, resists the standardized quantification that genetic discovery requires. The gold standard for detection – PET-CT scans with radioactive tracers – involves radiation exposure and cannot scale to the many thousands of participants required for genome-wide association. Without scalable measurement, the genetic programs governing this tissue remained inaccessible to systematic investigation. Research presented this week by instiro at the Keystone Symposia on Obesity Therapeutics demonstrates that this constraint can be resolved – and that resolving it opens a therapeutic frontier that has been structurally closed to drug discovery. Why Human Genetics Matters Translating brown fat biology into therapies has proven difficult. Many targets derived from rodent studies have failed to produce meaningful weight loss in human trials, despite showing BAT activation in mice. FGF21 agonists, orexin antagonists, β-adrenergic receptor agonists – each effective in rodents, each disappointing in humans. This translation gap underscores the need for discovery anchored in human genetics from day one. “To power human genetics, you need tens of thousands of people – but brown fat measurements have historically required expensive approaches such as PET scans, which is hard to acquire at scale,” said Daphne Koller, Ph.D., founder and CEO of insitro. “AI enables these measurements to be derived from MRIs, u…