In a new study from the Institute for Systems Biology, researchers found gut microbiota influences the ability to lose weight in humans, according to new research.
They found the gut microbiome can help or cause resistance to weight loss, and this opens up the possibility to try to alter the gut microbiome to impact weight loss.
In the study, the team focused on a large cohort of individuals who were involved in a lifestyle intervention study.
Instead of a specific diet or exercise program, this intervention involved a commercial behavioral coaching program paired with advice from a dietician and nurse coach.
The researchers focused on 48 individuals who lost more than 1% of their body weight per month over a 6 to 12 month period, and 57 individuals who did not lose any weight and had a stable body mass index (BMI) over the same period.
They identified 31 baseline stool metagenomic functional features that were linked to weight loss responses.
These included complex polysaccharide and protein degradation genes, stress-response genes, respiration-related genes, cell wall synthesis genes and gut bacterial replication rates.
A major finding was that the ability of the gut microbiome to break down starches was increased in people who did not lose weight.
Another key finding was that genes that help bacteria grow faster, multiply, replicate and assemble cell walls were increased in people who lost more weight.
The team says the gut microbiome is a major player in modulating whether a weight loss intervention will have success or not.
The factors that dictate obesity versus non-obesity are not the same factors that dictate whether you will lose weight on lifestyle intervention.
Research has already shown that if you change your diet, you can alter the composition of bacteria in your gut.
According to the team, if someone has a composition of gut bacterial genes that confers resistance to weight loss, then perhaps they can alter their diet to shift to a composition that would help them lose weight.
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The study is published in mSystems. One author of the study is Christian Diener, Ph.D.
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