Uric acid, high density lipoprotein cholesterol levels and their ratio are related to microbial enterotypes and serum metabolites in females with a blood stasis constitution.

BACKGROUND: Blood stasis constitution in traditional Chinese medicine (TCM) is believed to render individuals more susceptible to metabolic diseases. However, the biological underpinnings of this constitutional imbalance remain unclear. METHODS: This study explored the association between blood stasis constitution, serum metabolic markers including uric acid (UA), high-density lipoprotein cholesterol (HDLC), their ratio (UHR), serum metabolites, and gut microbiota. Clinical data, fecal and serum samples were acquired from 24 individuals with a blood stasis constitution and 80 individuals with a balanced constitution among healthy individuals from Guangdong. Gut microbiota composition analysis and serum metabolomics analysis were performed. RESULTS: Females with a blood stasis constitution had higher UA levels, lower HDLC levels, and higher UHR in serum, suggesting a higher risk of metabolic abnormalities. Analysis of the gut microbiome revealed two distinct enterotypes dominated by Bacteroides or Prevotella. Intriguingly, blood stasis subjects were disproportionately clustered within the Bacteroides-rich enterotype. Metabolomic analysis identified subtle differences between the groups, including lower phenylalanine and higher trimethylaminoacetone levels in the blood stasis. Several differential metabolites displayed correlations with HDLC, UA, or UHR, unveiling potential new markers of metabolic dysregulation. CONCLUSIONS: These findings elucidate the intricate interplay between host constitution, gut microbiota, and serum metabolites. The concept of blood stasis offers a unique perspective to identify subtle alterations in microbiome composition and metabolic pathways, potentially signaling underlying metabolic vulnerability, even in the presence of ostensibly healthy profiles. Continued investigation of this TCM principle may reveal critical insights into the early biological processes that foreshadow metabolic deterioration.

The impact of Traditional Chinese Medicine on mouse gut microbiota abundances and interactions based on Granger causality and pathway analysis.

Objectives: The intestinal microbiota is essential in absorbing nutrients and defending against pathogens and is associated with various diseases, including obesity, type 2 diabetes, and hypertension. As an alternative medicine, Traditional Chinese Medicine (TCM) has long been used in disease treatment and healthcare, partly because it may mediate gut microbiota. However, the specific effects of TCM on the abundance and interactions of microbiota remain unknown. Moreover, using TCM ingredients and data detailing changes in the abundance of gut microorganisms, we developed bioinformatic methods that decipher the impact of TCM on microorganism interactions. Methods: The dynamics of gut microorganisms affected by TCM treatments is explored using a mouse model, which provided the abundance of 70 microorganisms over time. The Granger causality analysis was used to measure microorganism interactions. Novel "serial connection" and "diverging connection" models were used to identify molecular mechanisms underlying the impact of TCM on gut microorganism interactions, based on microorganism proteins, TCM chemical ingredients, and KEGG reaction equations. Results: Codonopsis pilosula (Dangshen), Cassia twig (Gui Zhi), Radices saussureae (Mu Xiang), and Sijunzi Decoction did not cause an increase in the abundance of harmful microorganisms. Most TCMs decreased the abundance of Bifidobacterium pseudolongum, suggesting a Bifidobacterium pseudolongum supplement should be used during TCM treatment. The Granger causality analysis indicated that TCM treatment changes more than half the interactions between the 70 microorganisms, and "serial connection" and "diverging connection" models suggested that changes in interactions may be related to the reaction number connecting species proteins and TCM ingredients. From a species diversity perspective, a TCM decoction is better than a single herb for healthcare. The Sijunzi Decoction only significantly increased the abundance of Bifidobacterium pseudolongum and did not cause a decrease in the abundance of other species but was found to improve the alpha diversity with the lowest replacement rate. Conclusions: Because most of the nine TCMs are medicinal and edible plants, we expect the methods and results presented can be used to optimize and integrate microbiota and TCMs into healthcare processes. Moreover, as a control study, these results can be combined with future disease mouse models to link variations in species abundance with particular diseases.