title: The programming effects of nutrition-induced catch-up growth on gut microbiota and metabolic diseases in adult mice.
abstract: Substantial evidence indicated that catch-up growth could increase the susceptibility to obesity, insulin resistance, and type 2 diabetes mellitus in adulthood. However, investigations into the "programming" effects of catch-up growth on gut microbiota in the offspring are limited. C57/BL6 mice were fed on either low protein (LP) or normal chow (NC) diet throughout gestation and lactation. Then, the offspring were randomly weaned to either NC or high fat (HF) diet until 32 weeks of age, generating four experimental groups: NC-NC, NC-HF, LP-NC, and LP-HF. Metabolic parameters and gut microbiota were examined in the offspring. It showed that the NC-HF and LP-HF offspring displayed higher body weight (P < 0.05), impaired glucose tolerance (P < 0.001), and elevated serum lipids (P < 0.05) at 32 weeks of age. Both the operational taxonomic units (OTUs) and the Shannon indexes (P < 0.05) showed significantly lower microbial diversity in NC-HF and LP-HF offspring. There were significant variations in the compositions of gut microbiota in the NC-HF and LP-HF offspring, compared with NC-NC offspring (P < 0.05). Furthermore, it indicated Lactobacillus percentage was negatively associated with blood glucose concentrations of intraperitoneal glucose tolerance test (r = -0.886, P = 0.019). In conclusion, catch-up growth predisposes the offspring to gut microbiota perturbation, obesity, impaired glucose tolerance, insulin resistance, and dyslipidemia. Our study is novel in showing the "programming" effects of nutrition-induced catch-up growth on gut microbiota and metabolic diseases in later life.
authors.affiliation: Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Diabetes Research Center of Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
authors.forename: Jia
authors.initials: J
authors.lastname: Zheng
authors.affiliation: Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Diabetes Research Center of Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
authors.forename: Xinhua
authors.initials: X
authors.lastname: Xiao
authors.affiliation: Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Diabetes Research Center of Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
authors.forename: Qian
authors.initials: Q
authors.lastname: Zhang
authors.affiliation: Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Diabetes Research Center of Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
authors.forename: Miao
authors.initials: M
authors.lastname: Yu
authors.affiliation: Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Diabetes Research Center of Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
authors.forename: Jianping
authors.initials: J
authors.lastname: Xu
authors.affiliation: Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Diabetes Research Center of Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
authors.forename: Cuijuan
authors.initials: C
authors.lastname: Qi
authors.affiliation: Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Diabetes Research Center of Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
authors.forename: Tong
authors.initials: T
authors.lastname: Wang
mesh_terms: D000818:Animals; D044822:Biodiversity; D001835:Body Weight; D016000:Cluster Analysis; D059305:Diet, High-Fat; D004195:Disease Models, Animal; D000069196:Gastrointestinal Microbiome; D005951:Glucose Tolerance Test; D007333:Insulin Resistance; D008055:Lipids / Q000097:blood; D008297:Male; D008659:Metabolic Diseases / Q000209:etiology* / Q000378:metabolism; D054892:Metagenome; D056186:Metagenomics; D051379:Mice; D009753:Nutritive Value
chemical_list: D008055:Lipids
keywords: Gut microbiota; maternal imbalanced nutrition; metabolism; offspring