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Exploring the interactions between serum free fatty acids and fecal microbiota in obesity through a machine learning algorithm

AuthorsFernández-Navarro, Tania; Díaz, Irene ; Gutiérrez-Díaz, Isabel; Rodríguez-Carrio, Javier; Suárez, Ana; González de los Reyes-Gavilán, Clara ; Gueimonde Fernández, Miguel ; Salazar, Nuria ; González, Sonia
KeywordsFree fatty acids
Issue DateJul-2019
CitationFood Research International 121: 533-541 (2019)
AbstractSerum free fatty acids (FFA) are generally elevated in obesity. The gut microbiota is involved in the host energy metabolism through the regulation of body fat storage, and a link between diet, FFA and the intestinal microbiota seems to exist. Our aim was to explore the interaction among serum FFA levels, gut microbiota, diet and obesity through a model regression tree in 66 subjects (age 52.7 ± 11.2 y) classified according to Body Mass Index (BMI). Total and individual FFA were analyzed by colorimetric enzymatic assay and methyl-tert-butylether-based extraction protocol (MTBE), respectively. Microbiota was determined by qPCR and diet through a food frequency questionnaire. Statistical analyses were performed, and predictive factors for obesity were obtained via classification by decision trees using machine learning methods. An obese-linked FFA profile was characterized by decreased eicosapentaenoic (EPA) and increased linoleic, gamma-linolenic and palmitic acids levels simultaneously. Serum EPA and gender were identified as the most significant variables with 100% and 80% of importance, respectively. Palmitic acid, Bifidobacterium and Faecalibacterium explained >30%, followed by Bacteroides group with 20% and docosahexaenoic acid (DHA) almost with 15% of importance. Also, the regression tree model obtained for predicting obesity, showed a non-obese-linked profile, independently of gender, with serum EPA > 0.235 μg/mL and Bacteroides > 9.055 log n° cells per g of feces. Moreover, Faecalibacterium and Bifidobacterium seemed to play an important role by complementing the levels of FFA in predicting obesity in males and females, respectively.
Publisher version (URL)http://dx.doi.org/10.1016/j.foodres.2018.12.009
Identifiersdoi: 10.1016/j.foodres.2018.12.009
issn: 1873-7145
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