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. 2024 Dec 18;16(24):4371.
doi: 10.3390/nu16244371.

The Mediating Role of Gut Microbiota on the Association Between Dietary Quality and Cancer-Related Fatigue Among Breast Cancer Patients: A Cross-Sectional Study

Jianyun He  1 , Lan Cheng  1 , Xinxin Cheng  1 , Yuting Wang  1 , Xiaoxia Lin  1 , Shufang Xia  1
Affiliations

The Mediating Role of Gut Microbiota on the Association Between Dietary Quality and Cancer-Related Fatigue Among Breast Cancer Patients: A Cross-Sectional Study

Jianyun He et al. Nutrients. .

Abstract

Objectives: Cancer-related fatigue (CRF) is highly prevalent in patients with breast cancer, resulting in undesirable outcomes and even reduced survival rates. This cross-sectional study investigated the relationship between dietary quality and CRF in patients with breast cancer, and the potential role of gut microbiota (GM) in this association.

Methods: Dietary intake and CRF were evaluated in 342 patients, with 64 fecal samples collected for 16sRNA sequencing and 106 plasma samples for tryptophan (TRP) metabolite determination.

Results: A total of 149 (43.6%) patients experienced CRF, which was significantly associated with low intakes of protein, vitamin A, vitamin E, dietary fiber, phosphorus, magnesium, potassium, iron, and copper (p < 0.05), and a remarkably low Chinese Healthy Eating Index (CHEI) score (p < 0.05). CRF patients had decreased GM diversity, an unhealthier GM composition, lower TRP concentrations, and a higher kynurenine (KYN)/TRP ratio (p < 0.05). Mediation analyses revealed that both the Sobs index (ACME = -0.0005; 95% CI -0.0051, -0.0001; p = 0.034) and the Chao index (ACME = -0.0005; 95% CI -0.0050, -0.0001; p = 0.033) were significant mediators of the correlation between total CHEI score and CRF.

Conclusions: The presence of CRF in patients with breast cancer might be correlated with inadequate nutrient intake and low dietary quality via GM-dependent pathways.

Keywords: breast cancer; cancer-related fatigue; dietary quality; gut microbiota; nutrients.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Gut microbiota structure in breast cancer patients with NCRF and CRF. (A) Rarefaction curves. (B) Venn diagram displaying the shared number of operational taxonomic units (OTUs). (C) Chao index, Shannon index, Sobs index, and Simpson index. The Wilcoxon rank-sum test was used. (D) Weighted UniFrac distance-based principal coordinate analysis (PCoA). The statistical significance was assessed with analysis of similarities (ANOSIM). CRF, cancer-related fatigue (n = 25); NCRF, non-cancer-related fatigue (n = 39). * p < 0.05, ** p < 0.01.
Figure 1
Figure 1
Gut microbiota structure in breast cancer patients with NCRF and CRF. (A) Rarefaction curves. (B) Venn diagram displaying the shared number of operational taxonomic units (OTUs). (C) Chao index, Shannon index, Sobs index, and Simpson index. The Wilcoxon rank-sum test was used. (D) Weighted UniFrac distance-based principal coordinate analysis (PCoA). The statistical significance was assessed with analysis of similarities (ANOSIM). CRF, cancer-related fatigue (n = 25); NCRF, non-cancer-related fatigue (n = 39). * p < 0.05, ** p < 0.01.
Figure 2
Figure 2
Gut microbiota composition in breast cancer patients with NCRF and CRF. The community structures at the phylum (A) and genus (B) levels. CRF, cancer-related fatigue (n = 25); NCRF, non-cancer-related fatigue (n = 39).
Figure 3
Figure 3
Differentiated microbes between breast cancer patients with CRF and NCRF. Differentiated microbes at the phylum (A) and genus (B) levels. (C) Linear discriminatory analysis effect size (LEfSe) was used to distinguish the differential microbes between the CRF and NCRF patients. (D) Linear discriminant analysis (LDA) was performed, and only the microbiota with LDA scores of >4 are shown. CRF, cancer-related fatigue (n = 25); NCRF, non-cancer-related fatigue (n = 39). * p < 0.05, ** p < 0.01.
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