Cargando…

Effect of dietary protein content shift on aging in elderly rats by comprehensive quantitative score and metabolomics analysis

In the protein nutrition strategy of middle-aged and elderly people, some believe that low protein is good for health, while others believe high protein is good for health. Facing the contradictory situation, the following hypothesis is proposed. There is a process of change from lower to higher rat...

Descripción completa

Detalles Bibliográficos
Autores principales: Zheng, Wenxuan, Li, Ruiding, Zhou, Yang, Shi, Fengcui, Song, Yao, Liao, Yanting, Zhou, Fan, Zheng, Xiaohua, Lv, Jingwen, Li, Quanyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9673908/
https://www.ncbi.nlm.nih.gov/pubmed/36407526
http://dx.doi.org/10.3389/fnut.2022.1051964
_version_ 1784833048461705216
author Zheng, Wenxuan
Li, Ruiding
Zhou, Yang
Shi, Fengcui
Song, Yao
Liao, Yanting
Zhou, Fan
Zheng, Xiaohua
Lv, Jingwen
Li, Quanyang
author_facet Zheng, Wenxuan
Li, Ruiding
Zhou, Yang
Shi, Fengcui
Song, Yao
Liao, Yanting
Zhou, Fan
Zheng, Xiaohua
Lv, Jingwen
Li, Quanyang
author_sort Zheng, Wenxuan
collection PubMed
description In the protein nutrition strategy of middle-aged and elderly people, some believe that low protein is good for health, while others believe high protein is good for health. Facing the contradictory situation, the following hypothesis is proposed. There is a process of change from lower to higher ratio of protein nutritional requirements that are good for health in the human body after about 50 years of age, and the age at which the switch occurs is around 65 years of age. Hence, in this study, 50, 25-month-old male rats were randomly divided into five groups: Control (basal diet), LP (low-protein diet with a 30% decrease in protein content compared to the basal diet), HP (high-protein diet with a 30% increase in protein content compared to the basal diet), Model 1 (switched from LP to HP feed at week 4), and Model 2 (switched from LP to HP feed at week 7). After a total of 10 weeks intervention, the liver and serum samples were examined for aging-related indicators, and a newly comprehensive quantitative score was generated using principal component analysis (PCA). The effects of the five protein nutritional modalities were quantified in descending order: Model 1 > HP > LP > Control > Model 2. Furthermore, the differential metabolites in serum and feces were determined by orthogonal partial least squares discriminant analysis, and 15 differential metabolites, significantly associated with protein intake, were identified by Spearman’s correlation analysis (p < 0.05). Among the fecal metabolites, 10 were positively correlated and 3 were negatively correlated. In the serum, tyrosine and lactate levels were positively correlated, and acetate levels were negatively correlated. MetaboAnalyst analysis identified that the metabolic pathways influenced by protein intake were mainly related to amino acid and carbohydrate metabolism. The results of metabolomic analysis elucidate the mechanisms underlying the preceding effects to some degree. These efforts not only contribute to a unified protein nutrition strategy but also positively impact the building of a wiser approach to protein nutrition, thereby helping middle-aged and older populations achieve healthy aging.
format Online
Article
Text
id pubmed-9673908
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-96739082022-11-19 Effect of dietary protein content shift on aging in elderly rats by comprehensive quantitative score and metabolomics analysis Zheng, Wenxuan Li, Ruiding Zhou, Yang Shi, Fengcui Song, Yao Liao, Yanting Zhou, Fan Zheng, Xiaohua Lv, Jingwen Li, Quanyang Front Nutr Nutrition In the protein nutrition strategy of middle-aged and elderly people, some believe that low protein is good for health, while others believe high protein is good for health. Facing the contradictory situation, the following hypothesis is proposed. There is a process of change from lower to higher ratio of protein nutritional requirements that are good for health in the human body after about 50 years of age, and the age at which the switch occurs is around 65 years of age. Hence, in this study, 50, 25-month-old male rats were randomly divided into five groups: Control (basal diet), LP (low-protein diet with a 30% decrease in protein content compared to the basal diet), HP (high-protein diet with a 30% increase in protein content compared to the basal diet), Model 1 (switched from LP to HP feed at week 4), and Model 2 (switched from LP to HP feed at week 7). After a total of 10 weeks intervention, the liver and serum samples were examined for aging-related indicators, and a newly comprehensive quantitative score was generated using principal component analysis (PCA). The effects of the five protein nutritional modalities were quantified in descending order: Model 1 > HP > LP > Control > Model 2. Furthermore, the differential metabolites in serum and feces were determined by orthogonal partial least squares discriminant analysis, and 15 differential metabolites, significantly associated with protein intake, were identified by Spearman’s correlation analysis (p < 0.05). Among the fecal metabolites, 10 were positively correlated and 3 were negatively correlated. In the serum, tyrosine and lactate levels were positively correlated, and acetate levels were negatively correlated. MetaboAnalyst analysis identified that the metabolic pathways influenced by protein intake were mainly related to amino acid and carbohydrate metabolism. The results of metabolomic analysis elucidate the mechanisms underlying the preceding effects to some degree. These efforts not only contribute to a unified protein nutrition strategy but also positively impact the building of a wiser approach to protein nutrition, thereby helping middle-aged and older populations achieve healthy aging. Frontiers Media S.A. 2022-11-03 /pmc/articles/PMC9673908/ /pubmed/36407526 http://dx.doi.org/10.3389/fnut.2022.1051964 Text en Copyright © 2022 Zheng, Li, Zhou, Shi, Song, Liao, Zhou, Zheng, Lv and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Nutrition
Zheng, Wenxuan
Li, Ruiding
Zhou, Yang
Shi, Fengcui
Song, Yao
Liao, Yanting
Zhou, Fan
Zheng, Xiaohua
Lv, Jingwen
Li, Quanyang
Effect of dietary protein content shift on aging in elderly rats by comprehensive quantitative score and metabolomics analysis
title Effect of dietary protein content shift on aging in elderly rats by comprehensive quantitative score and metabolomics analysis
title_full Effect of dietary protein content shift on aging in elderly rats by comprehensive quantitative score and metabolomics analysis
title_fullStr Effect of dietary protein content shift on aging in elderly rats by comprehensive quantitative score and metabolomics analysis
title_full_unstemmed Effect of dietary protein content shift on aging in elderly rats by comprehensive quantitative score and metabolomics analysis
title_short Effect of dietary protein content shift on aging in elderly rats by comprehensive quantitative score and metabolomics analysis
title_sort effect of dietary protein content shift on aging in elderly rats by comprehensive quantitative score and metabolomics analysis
topic Nutrition
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9673908/
https://www.ncbi.nlm.nih.gov/pubmed/36407526
http://dx.doi.org/10.3389/fnut.2022.1051964
work_keys_str_mv AT zhengwenxuan effectofdietaryproteincontentshiftonaginginelderlyratsbycomprehensivequantitativescoreandmetabolomicsanalysis
AT liruiding effectofdietaryproteincontentshiftonaginginelderlyratsbycomprehensivequantitativescoreandmetabolomicsanalysis
AT zhouyang effectofdietaryproteincontentshiftonaginginelderlyratsbycomprehensivequantitativescoreandmetabolomicsanalysis
AT shifengcui effectofdietaryproteincontentshiftonaginginelderlyratsbycomprehensivequantitativescoreandmetabolomicsanalysis
AT songyao effectofdietaryproteincontentshiftonaginginelderlyratsbycomprehensivequantitativescoreandmetabolomicsanalysis
AT liaoyanting effectofdietaryproteincontentshiftonaginginelderlyratsbycomprehensivequantitativescoreandmetabolomicsanalysis
AT zhoufan effectofdietaryproteincontentshiftonaginginelderlyratsbycomprehensivequantitativescoreandmetabolomicsanalysis
AT zhengxiaohua effectofdietaryproteincontentshiftonaginginelderlyratsbycomprehensivequantitativescoreandmetabolomicsanalysis
AT lvjingwen effectofdietaryproteincontentshiftonaginginelderlyratsbycomprehensivequantitativescoreandmetabolomicsanalysis
AT liquanyang effectofdietaryproteincontentshiftonaginginelderlyratsbycomprehensivequantitativescoreandmetabolomicsanalysis