Tien S Dong1,2,3,4, Emeran A Mayer1,2,3,4,5, Vadim Osadchiy4,5, Candace Chang3, William Katzka3, Venu Lagishetty1,3,4, Kimberly Gonzalez1,4,5, Amir Kalani1,4, Jean Stains1,2,4,5, Jonathan P Jacobs1,2,3,4,5,6, Valter D Longo7, Arpana Gupta1,2,3,4,5. 1. Vatche and Tamar Manoukian Division of Digestive Diseases, University of California, Los Angeles, Department of Medicine, Los Angeles, California, USA. 2. David Geffen School of Medicine, University of California, Los Angeles, Department of Medicine, Los Angeles, California, USA. 3. UCLA Microbiome Center, University of California, Los Angeles, Department of Medicine, Los Angeles, California, USA. 4. University of California, Los Angeles, California, USA. 5. G. Oppenheimer Center for Neurobiology of Stress and Resilience, University of California, Los Angeles, Los Angeles, California, USA. 6. VA Greater Los Angeles Healthcare System, Division of Gastroenterology, Hepatology and Parenteral Nutrition, Los Angeles, California, USA. 7. USC Longevity Institute, University of Southern California, Los Angeles, CA, USA.
Abstract
BACKGROUND: Alterations in brain-gut-microbiome interactions have been implicated as an important factor in obesity. This study aimed to explore the relationship between food addiction (FA) and the brain-gut-microbiome axis, using a multi-omics approach involving microbiome data, metabolomics, and brain imaging. METHODS: Brain magnetic resonance imaging was obtained in 105 females. FA was defined by using the Yale Food Addiction Scale. Fecal samples were collected for sequencing and metabolomics. Statistical analysis was done by using multivariate analyses and machine learning algorithms. RESULTS: Of the females with obesity, 33.3% exhibited FA as compared with 5.3% and 0.0% of females with overweight and normal BMI, respectively (P = 0.0001). Based on a multilevel sparse partial least square discriminant analysis, there was a difference in the gut microbiome of females with FA versus those without. Differential abundance testing showed Bacteroides, Megamonas, Eubacterium, and Akkermansia were statistically associated with FA (q < 0.05). Metabolomics showed that indolepropionic acid was inversely correlated with FA. FA was also correlated with increased connectivity within the brain's reward network, specifically between the intraparietal sulcus, brain stem, and putamen. CONCLUSIONS: This is the first study to examine FA along the brain-gut-microbiome axis and it supports the idea of targeting the brain-gut-microbiome axis for the treatment of FA and obesity.
BACKGROUND: Alterations in brain-gut-microbiome interactions have been implicated as an important factor in obesity. This study aimed to explore the relationship between food addiction (FA) and the brain-gut-microbiome axis, using a multi-omics approach involving microbiome data, metabolomics, and brain imaging. METHODS: Brain magnetic resonance imaging was obtained in 105 females. FA was defined by using the Yale Food Addiction Scale. Fecal samples were collected for sequencing and metabolomics. Statistical analysis was done by using multivariate analyses and machine learning algorithms. RESULTS: Of the females with obesity, 33.3% exhibited FA as compared with 5.3% and 0.0% of females with overweight and normal BMI, respectively (P = 0.0001). Based on a multilevel sparse partial least square discriminant analysis, there was a difference in the gut microbiome of females with FA versus those without. Differential abundance testing showed Bacteroides, Megamonas, Eubacterium, and Akkermansia were statistically associated with FA (q < 0.05). Metabolomics showed that indolepropionic acid was inversely correlated with FA. FA was also correlated with increased connectivity within the brain's reward network, specifically between the intraparietal sulcus, brain stem, and putamen. CONCLUSIONS: This is the first study to examine FA along the brain-gut-microbiome axis and it supports the idea of targeting the brain-gut-microbiome axis for the treatment of FA and obesity.
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