Interview
David Zeevi on Personalized Nutrition Based on Your Gut Microbiome
- Personalized diets integrating dietary habits, physical activity, and gut microbiota data may successfully lower post-meal blood glucose and its long-term metabolic consequences.
- Obesity rates among U.S. adults may have increased from approximately 1 in 10 during the 1980s to 4 in 10 at the time of the conversation.
- Annual spending on diabetes and related costs reached $250 billion in 2012, implying a continuing significant burden on healthcare systems.
- Nutrition interventions may restore healthy eating patterns if metabolic causes of the obesity and diabetes epidemics are addressed.
- Sugar intake may primarily replace fat in diets following reductions in fat consumption from about 20% of calories to about 15%.
- Human evolution may not have equipped the species to handle the current volume of sugar entering the system.
- CRISPR technology will probably alter human genetics to modify genetic traits affecting glucose response.
- Healthy and active lifestyle factors are recognized as effective methods for modifying glucose responses.
- The microbiome may be modified to improve health if deleterious effects are identified, though a single ideal microbiome for everyone is not certain.
- Future studies will probably determine the exact effect size of the microbiome on human health.
- High microbiome diversity is associated with a healthy host, suggesting that exposure to dirt or dogs may contribute to this diversity.
- Fecal transplants have been proven effective for a percentage of people suffering from Clostridium difficile infections.
- Companies are currently generating significant revenue by collecting stool from professional athletes for transplantation purposes.
- Postprandial glucose response is linked to weight changes via insulin secretion signaling the body to store fat.
- Detecting differences in weight resulting from dietary interventions requires following individuals for months, if not years.
- Choosing foods tailored to an individual could provide an advantage by steering people away from becoming pre-diabetic.
- The company Day Two is developing a product where users complete a questionnaire and provide a microbiome sample to receive food-specific predictions.
- The prediction algorithm was expected to reach an R value of 0.7, representing the theoretical upper bound for consistency within the same person.
- The prediction model is expected to be generalizable at least for the Israeli public.
- Universal dietary recommendations are likely suboptimal due to significant individual differences in glucose responses.
- Long-term studies are being conducted by Ron Segal's group on 200 to 300 people for periods of six months to a year.
- The author intends to analyze oceanic microbiota and combine data from oil refineries, oil wells, and NASA to investigate basic questions.
- Research will seek genes capable of metabolizing compounds from oil refineries or plastics in Pacific garbage patches.
- Bacteria with specific genomic regions may metabolize host-consumed compounds to produce butyrate, which would benefit the host.
- Direct supplementation with butyrate would probably have a poor taste profile.
- People may gain more benefits from bacteria that metabolize fiber into butyrate compared to consuming butyrate directly.
- It is possible to supplement people with specific genomic regions or utilize CRISPR technology to introduce them.
- An intervention study was designed to demonstrate that predicted diets can effectively reduce blood glucose levels.
- The microbiome may be stabilized by factors such as the appendix re-inoculating the gut after food poisoning.
- The author will publish a separate study analyzing the human microbiome by examining microbial genome regions.