Gut Microbiota Enterotypes Mediate the Effects of Dietary Patterns on Colorectal Neoplasm Risk in a Chinese Population

Abstract

Colorectal cancer (CRC) risk is influenced by dietary patterns and gut microbiota enterotypes. However, the interaction between these factors remains unclear. This study examines this relationship, hypothesizing that different diets may affect colorectal tumor risk in individuals with varied gut microbiota enterotypes. We conducted a case-control study involving 410 Han Chinese individuals, using exploratory structural equation modeling to identify two dietary patterns, and a Dirichlet multinomial mixture model to classify 250 colorectal neoplasm cases into three gut microbiota enterotypes. We assessed the association between dietary patterns and the risk of each tumor subtype using logistic regression analysis. We found that a healthy diet, rich in vegetables, fruits, milk, and yogurt, lowers CRC risk, particularly in individuals with type I (dominated by Bacteroides and Lachnoclostridium) and type II (dominated by Bacteroides and Faecalibacterium) gut microbiota enterotypes, with adjusted odds ratios (ORs) of 0.66 (95% confidence interval [CI] = 0.48-0.89) and 0.42 (95% CI = 0.29-0.62), respectively. Fruit consumption was the main contributor to this protective effect. No association was found between a healthy dietary pattern and colorectal adenoma risk or between a high-fat diet and colorectal neoplasm risk. Different CRC subtypes associated with gut microbiota enterotypes displayed unique microbial compositions and functions. Our study suggests that specific gut microbiota enterotypes can modulate the effects of diet on CRC risk, offering new perspectives on the relationship between diet, gut microbiota, and colorectal neoplasm risk.

Keywords: colorectal adenoma; colorectal cancer; dietary patterns; enterotypes; gut microbiota.

Figure 1

Gut microbiota composition comparison between type I and type III subtypes in CRC and CRA groups using LEfSe analysis. (A) LEfSe analysis of gut microbiota differences in the CRC group. Left panel: LDA score plot, with red bars representing type I taxa and green bars representing type III taxa. Right panel: cladogram displaying the phylogenetic distribution of differentially abundant taxa in the CRC group. (B) Cladogram illustrating the phylogenetic distribution of differentially abundant taxa between type I and type III subtypes in the CRA group, as analyzed by the LEfSe method. CRA, colorectal adenoma; CRC, colorectal cancer; LDA, linear discriminant analysis; LEfSe, linear discriminant analysis effect size.

Figure 2

Differential metabolites between type I and type III subtypes in CRC and CRA groups identified by LEfSe analysis, with a logarithmic LDA score > 3. (A) LDA score plot for the CRC group comparison. (B) LDA score plot for the CRA group comparison. Red bars on the left represent type I, while green bars on the right indicate type III. Longer bars signify a greater degree of difference between the subtypes for each metabolite. CRA, colorectal adenoma; CRC, colorectal cancer; LDA, linear discriminant analysis; LEfSe, linear discriminant analysis effect size.