Associations between habitual diet, metabolic disease, and the gut microbiota using latent Dirichlet allocation

Abstract

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.

Stratification of the Gut Microbiota Composition Landscape Across the Alzheimer’s Disease Continuum in a Turkish Cohort

“…Both parameters continued to partition the community without reaching a clear optimum. This finding is unexpectedly consistent with recent publications using LDA in microbial ecology [46–48]. Bacteria probability distributions (ranked by probability ≥ 1% in descending order) across the subgroups are displayed in Figure 6a.…”

“…We next tested LDA potential to stratify gut microbiota of the cohort participants. This unsupervised machine learning technique is increasingly finding acceptance in the field of microbiome [46–48] for its unique ability to reveal latent or hidden groups within the data cloud. Supplementary Figure S4 shows LDA model’s perplexity parameter and log-likelihood values to find optimal number of clusters.…”

Gut Microbiome-Based Diagnostic Model to Predict Diabetes Mellitus

“…This bacterium has also been reported in diabetes. This conclusion is similar to the structure of this study [31]. The genus Actinomyces is widely distributed in nature and has a wide variety of species.…”

“…and [31]. In our heat map of differential bacteria and biochemical indicators, it is suggested that the genus Gemmiger is surely negatively correlated with the percentage of neutrophils, suggesting that genus Gemmiger is likely to play a role through immune regulation.…”

Altered Fecal Microbiota Composition in Older Adults With Frailty

“…It should be noted that comorbidity was widespread among older adults with frailty and has been considered synonymous with frailty (Fried et al, 2001). However, many frailty-related diseases such as hypertension and diabetes have been reported to be associated with gut microbiota (Breuninger et al, 2021). We recorded the variables of drinking and smoking at present in the healthy control group and frail group.…”