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Obesity measures and dietary parameters as predictors of gut microbiota phyla in healthy individuals
Katja Bezek, Ana Petelin, Jure Pražnikar, Esther Nova, Noemi Redondo, Marcos Ascensión, Zala Jenko Pražnikar, 2020, izvirni znanstveni članek

Opis: : The dynamics and diversity of human gut microbiota that can remarkably influence the wellbeing and health of the host are constantly changing through the host%s lifetime in response to various factors. The aim of the present study was to determine a set of parameters that could have a major impact on classifying subjects into a single cluster regarding gut bacteria composition. Therefore, a set of demographical, environmental, and clinical data of healthy adults aged 25%50 years (117 female and 83 men) was collected. Fecal microbiota composition was characterized using Illumina MiSeq 16S rRNA gene amplicon sequencing. Hierarchical clustering was performed to analyze the microbiota data set, and a supervised machine learning model (SVM; Support Vector Machines) was applied for classification. Seventy variables from collected data were included in machine learning analysis. The agglomerative clustering algorithm suggested the presence of four distinct community types of most abundant bacterial phyla. Each cluster harbored a statistically significant different proportion of bacterial phyla. Regarding prediction, the most important features classifying subjects into clusters were measures of obesity (waist to hip ratio, BMI, and visceral fat index), total body water, blood pressure, energy intake, total fat, olive oil intake, total fiber intake, and water intake. In conclusion, the SVM model was shown as a valuable tool to classify healthy individuals based on their gut microbiota composition.
Ključne besede: gut microbiota, nutrition, obesity, lifestyle parameters, clustering
Objavljeno v RUP: 10.09.2020; Ogledov: 1294; Prenosov: 72
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Interactions between person's cognition, food and biological processes over multidisciplinary intervention
Maša Černelič Bizjak, Mojca Stubelj, Zala Jenko Pražnikar, 2015, izvirni znanstveni članek

Opis: The aim of the present study was to explore interactions between food, cognition and biological processes in relation to health. Therefore, we assessenergy intake, total fat, protein and carbohydrate intake and negative cognition about body image and inflammation biomarkers over 6-month multidisciplinary intervention. The participants were evaluated at baseline and after the 6-month of intervention. 33 overweight and 33 obese adults completed a 6-month intervention trial to evaluate the effects of an individual dietary programme based on individual's resting metabolic rate on anthropometry, metabolic profile, and inflammation. Pearson's correlations were performed to investigate the possible associations between reductions in obesity, inflammation, dietary intakes with decrease in body dissatisfaction. Furthermore, hierarchical multiple regression analyses revealed that relative changes in obesity indicators accounted for 23% of the variation in reduction of inflammation biomarker C- reactive protein, changes in composition of diet 13% of variation and changes in negative cognition explained an additional 8% of the variation in inflammation level of CRP. Together the independent variables accounted for 44% of the variance in inflammation level of CRP. The important findings of the present study were that reduction in carbohydrate intake and increase in protein intake in diet, with more positive cognition about body image,significantly predicted a reduction in level of inflammation biomarker, measured with CRP. Changes in energy intake and total fat intake and physical activity did not predicted reduction of inflammation.
Ključne besede: cognition, inflammation, CRP, intervention, image, obesity
Objavljeno v RUP: 14.10.2015; Ogledov: 4034; Prenosov: 120
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