Investigating Diet and Gut Microbiota Composition in an Obese Population using Shotgun Metagenomic Sequencing (InDiGO)

• Applicant: Dr. Taylor Breuninger
• Subject Area: Nutritional Sciences
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 523020916

The composition of the human gut microbiota is associated with a huge number of disease states, including obesity in particular. At the same time, diet is among the modifiable factors that affect the gut microbiome. As a result, substantial resources have been invested into understanding the role the human gut microbiome may play in human health. However, several basic questions remain unanswered, such as how to best describe dietary intake in microbiome studies (food groups vs. nutrients vs. dietary patterns), to what extent long-term diet is associated with microbiota composition and what significance this relationship has to human health, how to define a “healthy” microbiome, which microbial taxa or microbial subgroups are associated with obesity, and to what extent functional profiling, blood and urine metabolomics data, and high-resolution taxonomic identification is useful in microbiome studies. In this proposal, we aim to address these questions using data from the MeGA (Metabolic Health Augsburg) study, a well-characterized study population of 238 adults who are either obese or normal-weight. In addition to a host of other parameters, metabolomics data, high-quality dietary data based on repeated 24-hour food lists and a food frequency questionnaire, and deep whole genome shotgun metagenomic sequencing data in stool samples were gathered over the 9-month study period. Thus, the MeGA study provides an excellent opportunity to continue our previous research on identifying latent microbial subgroups within the human microbiome using machine learning (Task 2.1). We will also assess the relationship between microbiota composition (at the species- and, where possible, strain-level), functional profiling, and metabolomics data with habitual diet in Tasks 3.1-3.3. In these analyses, habitual diet will be analyzed at the nutrient, food group, and dietary pattern level. The MeGA study presents a unique opportunity for replication within the study population. Therefore, all main analyses will be replicated with all participants who provided a second stool sample nine months after the first sample (n=200). Additionally, all significant results will be replicated in a sensitivity analysis in obese subjects to evaluate the impact of body weight on the associations.

• DFG Programme: Research Grants
• Co-Investigators: Professor Dr. Jakob Linseisen; Professorin Dr. Christine Meisinger