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Diet, Gut Microbiome, and Their End Metabolites Associate With Acute Pancreatitis Risk

Diet and decreased gut microbiome diversity has been associated with acute pancreatitis (AP) risk. However, differences in dietary intake, gut microbiome, and their impact on microbial end metabolites have not been studied in AP. We aimed to determine differences in (i) dietary intake (ii) gut micro...

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Detalles Bibliográficos
Autores principales: Yazici, Cemal, Thaker, Sarang, Castellanos, Karla K., Al Rashdan, Haya, Huang, Yongchao, Sarraf, Paya, Boulay, Brian, Grippo, Paul, Gaskins, H. Rex, Danielson, Kirstie K., Papachristou, Georgios I., Tussing-Humphreys, Lisa, Dai, Yang, Mutlu, Ece R., Layden, Brian T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371326/
https://www.ncbi.nlm.nih.gov/pubmed/37162146
http://dx.doi.org/10.14309/ctg.0000000000000597
Descripción
Sumario:Diet and decreased gut microbiome diversity has been associated with acute pancreatitis (AP) risk. However, differences in dietary intake, gut microbiome, and their impact on microbial end metabolites have not been studied in AP. We aimed to determine differences in (i) dietary intake (ii) gut microbiome diversity and sulfidogenic bacterial abundance, and (iii) serum short-chain fatty acid (SCFA) and hydrogen sulfide (H(2)S) concentrations in AP and control subjects. METHODS: This case-control study recruited 54 AP and 46 control subjects during hospitalization. Clinical and diet data and stool and blood samples were collected. 16S rDNA sequencing was used to determine gut microbiome alpha diversity and composition. Serum SCFA and H(2)S levels were measured. Machine learning (ML) model was used to identify microbial targets associated with AP. RESULTS: AP patients had a decreased intake of vitamin D(3), whole grains, fish, and beneficial eicosapentaenoic, docosapentaenoic, and docosahexaenoic acids. AP patients also had lower gut microbiome diversity (P = 0.021) and a higher abundance of sulfidogenic bacteria including Veillonella sp. and Haemophilus sp., which were associated with AP risk. Serum acetate and H(2)S concentrations were significantly higher in the AP group (P < 0.001 and P = 0.043, respectively). ML model had 96% predictive ability to distinguish AP patients from controls. DISCUSSION: AP patients have decreased beneficial nutrient intake and gut microbiome diversity. An increased abundance of H(2)S-producing genera in the AP and SCFA-producing genera in the control group and predictive ability of ML model to distinguish AP patients indicates that diet, gut microbiota, and their end metabolites play a key role in AP.