Dietary Efficacy Evaluation by Applying a Prediction Model Using Clinical Fecal Microbiome Data of Colorectal Disease to a Controlled Animal Model from an Obesity Perspective.
Hochan SeoCheol-O KwonJoo-Hyun ParkChil-Sung KangTae-Seop ShinEun-Young YangJin Woo JungByoung-Seok MoonYoon-Keun KimPublished in: Microorganisms (2022)
Obesity associated with a Western diet such as a high-fat diet (HFD) is a known risk factor for inflammatory bowel disease (IBD) and colorectal cancer (CRC). In this study, we aimed to develop fecal microbiome data-based deep learning algorithms for the risk assessment of colorectal diseases. The effects of a HFD and a candidate food ( Nypa fruticans , NF) on IBD and CRC risk reduction were also evaluated. Fecal microbiome data were obtained from 109 IBD patients, 111 CRC patients, and 395 healthy control (HC) subjects by 16S rDNA amplicon sequencing. IBD and CRC risk assessment prediction models were then constructed by deep learning algorithms. Dietary effects were evaluated based on fecal microbiome data from rats fed on a regular chow diet (RCD), HFD, and HFD plus ethanol extracts or water extracts of NF. There were significant differences in taxa when IBD and CRC were compared with HC. The diagnostic performance (area under curve, AUC) of the deep learning algorithm was 0.84 for IBD and 0.80 for CRC prediction. Based on the rat fecal microbiome data, IBD and CRC risks were increased in HFD-fed rats versus RCD-fed rats. Interestingly, in the HFD-induced obesity model, the IBD and CRC risk scores were significantly lowered by the administration of ethanol extracts of NF, but not by the administration of water extracts of NF. In conclusion, changes in the fecal microbiome of obesity by Western diet could be important risk factors for the development of IBD and CRC. The risk prediction model developed in this study could be used to evaluate dietary efficacy.
Keyphrases
- high fat diet
- insulin resistance
- deep learning
- weight loss
- adipose tissue
- risk assessment
- metabolic syndrome
- machine learning
- ulcerative colitis
- electronic health record
- signaling pathway
- high fat diet induced
- end stage renal disease
- type diabetes
- ejection fraction
- big data
- oxidative stress
- skeletal muscle
- human health
- artificial intelligence
- newly diagnosed
- lps induced
- chronic kidney disease
- weight gain
- nuclear factor
- pi k akt
- patient reported
- climate change
- cell proliferation
- data analysis
- immune response
- patient reported outcomes
- high glucose
- stress induced