Metabolomics Study of Isocaloric Different Dietary Patterns on the Life Span in Healthy Population

Abstract

Cong Zhang,1,2,* Qingna Yan,1,* Qiushuang Zhu,1,* Jinxiao Liu,1,* Yuanjie Dong,1 Yuqiao Li,1 Ruohua Wang,1 Xuanfeng Tang,1 Xinyi Lv,1 Xiaoqing Li,1 Yunjiang Cai,3 Yucun Niu1 1Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, 150086, People’s Republic of China; 2Center of Disease Control and Prevention of Xishan District, Wuxi, 214000, People’s Republic of China; 3Nursing College of Daqing Campus of Harbin Medical University, Daqing, 163319, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yucun NiuDepartment of Nutrition and Food Hygiene, College of Public Health, Harbin Medical University, 157 Baojian Road, Nangang District, Harbin, 150081, People’s Republic of ChinaTel [phone]Fax [phone]Email [email protected]: How to prolong life by diet has been widely concerned. There are many reports about the effects of different dietary patterns on life span, but the results are not consistent. The main reason may be that total energy intake has not been considered. This study aims to explore the effects of isocaloric different dietary patterns on population life span.Materials and Methods: From the data of the follow-up population, eligible participators were divided into normal control (NC) group (28.31% fat, 12.37% protein, 62.30% carbohydrate), isocaloric high-fat (IHF) group (38.39% fat, 12.21% protein, 51.32% carbohydrate), isocaloric high-protein (IHP) group (33.41% fat, 17.10% protein, 52.67% carbohydrate) and isocaloric high-carbohydrate (IHC) group (22.23% fat, 10.52% protein, 70.13% carbohydrate) according to the dietary structure and the age stratification. Global serum metabolic profiling analysis by UPLC−Q-TOF-MS/MS technology, fatty acid and amino acid profiles in serum were determined by GC-MS and UPLC-TQ-MS technology. One-way ANOVA followed by Dunnett post hoc test and receiver operating characteristic (ROC) curve analysis were used to statistical analysis.Results: Non-targeted metabolomics was to identify 18 potential metabolites related to longevity. ROC curve analysis to identify biomarkers indicated that the areas under the ROC (AUC) of the 12 of 18 biomarkers are above 0.9. The 12 biomarkers were mainly enriched in three metabolic pathways: lipid metabolism, amino acid metabolism and tricarboxylic acid cycle. Compared to control, 11 and 10 of 12 biomarkers showed the same trend with aging in IHP and IHC groups, respectively. Conversely, no differences were observed between IHF group and NC group.Conclusion: Without consideration of the nature of carbohydrates, fats and proteins, IHP and IHC diets might shorten life span by influencing amino acid metabolism, lipid metabolism and tricarboxylic acid cycle metabolism, while the isocaloric IHF diet has no effects on longevity.Keywords: amino acid, fatty acid, biomarkers, metabolomics

Keywords

• amino acid
• fatty acid
• biomarkers
• metabolomics