Gut microbial communities from patients with anorexia nervosa do not influence body weight in recipient germ-free mice.
Elaine M GlennyFarnaz FouladiStephanie A ThomasEmily C Bulik-SullivanQuyen TangZorka DjukicYesel S Trillo-OrdonezAnthony A FodorLisa M TarantinoCynthia M BulikIan M CarrollPublished in: Gut microbes (2022)
Anorexia nervosa (AN) is a psychiatric disorder that presents with profound weight dysregulation, metabolic disturbances, and an abnormal composition of gut microbial communities. As the intestinal microbiota can influence host metabolism, the impact of enteric microbial communities from patients with AN on host weight and adiposity was investigated. Germ-free (GF) mice were colonized with fecal microbiotas from either patients with AN (n = 4) prior to inpatient treatment (AN T1, n = 50 recipient mice), the same 4 patients following clinical renourishment (AN T2, n = 53 recipient mice), or age- and sex-matched non-AN controls (n = 4 human donors; non-AN, n = 50 recipient mice). Biological and fecal microbiota data were analyzed with linear mixed-effects models. Body weight did not differ significantly between AN recipient mice (T1 and T2) and non-AN recipient mice following 4 weeks of colonization. Enteric microbiotas from recipient mice colonized with AN T1 and AN T2 fecal microbiotas were more similar to each other compared with enteric microbiotas from non-AN recipient mice. Specific bacterial families in the Actinobacteria, Bacteroidetes, and Firmicutes phyla were significantly associated with body weight, fat mass, and cecum weight irrespective of the donor group. These data suggest that body weight, fat mass, and cecum weight of colonized GF mice are associated with human fecal microbes and independent of donor AN status, although additional analyses with larger cohorts are warranted.
Keyphrases
- body weight
- high fat diet induced
- body mass index
- physical activity
- endothelial cells
- anorexia nervosa
- adipose tissue
- weight loss
- metabolic syndrome
- machine learning
- autism spectrum disorder
- chronic kidney disease
- newly diagnosed
- type diabetes
- end stage renal disease
- intellectual disability
- deep learning
- high resolution
- big data
- skeletal muscle
- combination therapy
- pluripotent stem cells
- neural network