The community of microbes living in the human gut varies based on where a person lives, in part because of differences in diets but also due to factors still incompletely understood. In turn, this ‘microbiome’ may have wide-ranging effects on health and diseases such as obesity and diabetes.
Many scientists want to understand how differences in the microbiome emerge between people, and whether this may explain why certain diseases are more common in specific populations. Self-identified race or ethnicity can be a useful tool in that effort, as it can serve as a proxy for cultural habits (such as diets) or genetic information.
In the United States, self-identified East Asian Americans often have worse ‘metabolic health’ (e.g. levels of sugar or certain fat molecules in the blood) at a lower weight than those identifying as White. Ang, Alba, Upadhyay et al. investigated whether this health disparity was linked to variation in the gut microbiome. Samples were collected from 46 lean and obese individuals living in the San Francisco Bay Area who identified as White or East Asian.
The analyses showed that while the gut microbiome of White participants changed in association with obesity, the microbiomes of East Asian participants were distinct from their White counterparts even at normal weight, with features mirroring what was seen in White individuals in the context of obesity. Although these differences were connected to people’s current address, they were not attributable to dietary differences.
Ang, Alba, Upadhyay et al. then transplanted the microbiome of the participants into genetically identical mice with microbe-free guts. The differences between the gut microbiomes of White and East Asian participants persisted in recipient animals. When fed the same diet, the mice also gained different amounts of weight depending on the ethnic identity of the microbial donor.
These results show that self-identified ethnicity may be an important variable to consider in microbiome studies, alongside other factors such as geography. Ultimately, this research may help to design better, more personalized treatments for an array of conditions.