Background The gut microbiome impacts human health through various mechanisms and is involved in the development of a range of non-communicable diseases. Diet is a well-known factor influencing microbe-host interaction in health and disease. However, very few findings are based on large-scale analysis using population-based studies. Our aim was to investigate the cross-sectional relationship between habitual dietary intake and gut microbiota structure in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 study. Results Fecal microbiota was analyzed using 16S rRNA gene amplicon sequencing. Latent Dirichlet allocation (LDA) was applied to samples from 1992 participants to identify 20 microbial subgroups within the study population. Each participant’s gut microbiota was subsequently described by a unique composition of these 20 subgroups. Associations between habitual dietary intake, assessed via repeated 24-h food lists and a Food Frequency Questionnaire, and the 20 subgroups, as well as between prevalence of metabolic diseases/risk factors and the subgroups, were assessed with multivariate-adjusted Dirichlet regression models. After adjustment for multiple testing, eight of 20 microbial subgroups were significantly associated with habitual diet, while nine of 20 microbial subgroups were associated with the prevalence of one or more metabolic diseases/risk factors. Subgroups 5 (Faecalibacterium, Lachnospiracea incertae sedis, Gemmiger, Roseburia) and 14 (Coprococcus, Bacteroides, Faecalibacterium, Ruminococcus) were particularly strongly associated with diet. For example, participants with a high probability for subgroup 5 were characterized by a higher Alternate Healthy Eating Index and Mediterranean Diet Score and a higher intake of food items such as fruits, vegetables, legumes, and whole grains, while participants with prevalent type 2 diabetes mellitus were characterized by a lower probability for subgroup 5. Conclusions The associations between habitual diet, metabolic diseases, and microbial subgroups identified in this analysis not only expand upon current knowledge of diet-microbiota-disease relationships, but also indicate the possibility of certain microbial groups to be modulated by dietary intervention, with the potential of impacting human health. Additionally, LDA appears to be a powerful tool for interpreting latent structures of the human gut microbiota. However, the subgroups and associations observed in this analysis need to be replicated in further studies.

The 24-h food list represents a promising new dietary assessment tool that can be used as part of a blended approach combining multiple data sources for valid estimation of usual dietary intake in large-scale cohort studies.

Background: Estimation of usual dietary intake poses a challenge in epidemiological studies. We applied a blended approach that combines the strengths provided by repeated 24-h food lists (24HFLs) and a food frequency questionnaire (FFQ).Methods: At least two web-based 24HFLs and one FFQ were completed by 821 participants in the KORA FF4 study. Consumption probabilities were estimated using logistic mixed models, adjusting for covariates and the FFQ data on consumption frequency. Intake amount of a consumed food item was predicted for each participant based on the results of the second Bavarian Food Consumption Survey (BVS II). By combining consumption probability and estimated consumption amount, the usual food intake for each participant was estimated. These results were compared to results obtained without considering FFQ information for consumption probability estimation, as well as to conventional FFQ data.Results: The results of the blended approach for food group intake were often higher than the FFQ-based results. Intraclass correlation coefficients between both methods ranged between 0.21 and 0.86. Comparison of both methods resulted in weighted kappa values based on quintiles ranging from fair (0.34) to excellent agreement (0.84). Omission of FFQ information in the consumption probability models distinctly affected the results at the group level, though individual intake data were slightly affected, for the most part.Conclusions: Usual dietary intake data based on the blended approach differs from the FFQ-based results both in absolute terms and in classification according to quintiles. The application of the blended approach has been demonstrated as a possible tool in nutritional epidemiology, as a comparison with published studies showed that the blended approach yields reasonable estimates. The inclusion of the FFQ information is valuable especially with regard to irregularly consumed foods. A validation study including biomarkers of dietary intake is warranted.

The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19–74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2–3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4–5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years.