Metabolomics Analysis Reveals Molecular Signatures of Metabolic Complexity in Children with Hypercholesterolemia

被引:5
|
作者
Gu, Pei-Shin [1 ,2 ]
Su, Kuan-Wen [3 ]
Yeh, Kuo-Wei [4 ]
Huang, Jing-Long [5 ]
Lo, Fu-Sung [1 ]
Chiu, Chih-Yung [4 ,6 ]
机构
[1] Chang Gung Univ, Chang Gung Mem Hosp Linkou, Dept Pediat, Div Pediat Endocrinol,Coll Med, Taoyuan 333, Taiwan
[2] Chang Gung Univ, Grad Inst Clin Med Sci, Coll Med, Taoyuan 333, Taiwan
[3] Chang Gung Univ, Chang Gung Mem Hosp Keelung, Dept Pediat, Coll Med, Taoyuan 333, Taiwan
[4] Chang Gung Univ, Chang Gung Mem Hosp Linkou, Dept Pediat, Coll Med, Taoyuan 333, Taiwan
[5] Chang Gung Univ, New Taipei Municipal TuCheng Hosp, Chang Gung Mem Hosp, Dept Pediat,Coll Med, Taoyuan 333, Taiwan
[6] Chang Gung Mem Hosp Linkou, Clin Metabol Core Lab, Taoyuan 333, Taiwan
关键词
childhood hypercholesterolemia; glutamic acid; tyrosine; metabolomics; FAMILIAL HYPERCHOLESTEROLEMIA; DIETARY TYROSINE; NATIONAL-HEALTH; ADIPOSE-TISSUE; DYSLIPIDEMIA; CHOLESTEROL; CHILDHOOD; MARKERS; TRENDS; SERUM;
D O I
10.3390/nu15071726
中图分类号
R15 [营养卫生、食品卫生]; TS201 [基础科学];
学科分类号
100403 ;
摘要
Despite the importance of hypercholesterolemia in children, it is overlooked, and there are currently few metabolomics-based approaches available to understand its molecular mechanisms. Children from a birth cohort had their cholesterol levels measured with the aim of identifying the metabolites for the molecular biological pathways of childhood hypercholesterolemia. One hundred and twenty-five children were enrolled and stratified into three groups according to cholesterol levels (acceptable, <170 mg/dL, n = 42; borderline, 170-200 mg/dL, n = 52; and high, >200 mg/dL, n = 31). Plasma metabolomic profiles were obtained by using H-1-nuclear magnetic resonance (NMR) spectroscopy, and partial least squares-discriminant analysis (PLS-DA) was applied using the MetaboAnalyst 5.0 platform. Metabolites significantly associated with different cholesterol statuses were identified, and random forest classifier models were used to rank the importance of these metabolites. Their associations with serum lipid profile and functional metabolic pathways related to hypercholesterolemia were also assessed. Cholesterol level was significantly positively correlated with LDL-C and Apo-B level, as well as HDL-C and Apo-A1 level separately, whereas HDL-C was negatively correlated with triglyceride level (p < 0.01). Eight metabolites including tyrosine, glutamic acid, ornithine, lysine, alanine, creatinine, oxoglutaric acid, and creatine were significantly associated with the different statuses of cholesterol level. Among them, glutamic acid and tyrosine had the highest importance for different cholesterol statuses using random forest regression models. Carbohydrate and amino acid metabolisms were significantly associated with different cholesterol statuses, with glutamic acid being involved in all amino acid metabolic pathways (FDR-adjusted p < 0.01). Hypercholesterolemia is a significant health concern among children, with up to 25% having high cholesterol levels. Glutamic acid and tyrosine are crucial amino acids in lipid metabolism, with glutamic-acid-related amino acid metabolism playing a significant role in regulating cholesterol levels.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Urinary metabolomics reveals unique metabolic signatures in infants with cystic fibrosis
    Kopp, B. T.
    Joseloff, E.
    Goetz, D.
    Ingram, B.
    Heltshe, S. L.
    Leung, D. H.
    Ramsey, B. W.
    McCoy, K.
    Borowitz, D.
    JOURNAL OF CYSTIC FIBROSIS, 2019, 18 (04) : 507 - 515
  • [2] Metabolomics Reveals Molecular Signatures for Psoriasis Biomarkers and Drug Targets Discovery
    Song, Qian
    Chen, Ying
    Ma, JianQing
    Zhou, Wei
    Song, JunYan
    Wu, ChunFu
    Liu, Jie
    CLINICAL COSMETIC AND INVESTIGATIONAL DERMATOLOGY, 2023, 16 : 3181 - 3191
  • [3] Identification of Distinct Metabolic Profiles in Childhood Hypercholesterolemia Using Metabolomics Analysis
    Gu, Pei-Shin
    Su, Kuan-Wen
    Chiu, Chih-Yung
    Lo, Fu-Sung
    HORMONE RESEARCH IN PAEDIATRICS, 2023, 96 : 244 - 244
  • [4] Plasma metabolomics study reveals the critical metabolic signatures for benzene-induced hematotoxicity
    Guo, Xiaoli
    Zhang, Lei
    Wang, Jingyu
    Zhang, Wei
    Ren, Jing
    Chen, Yujiao
    Zhang, Yanlin
    Gao, Ai
    JCI INSIGHT, 2022, 7 (02)
  • [5] Metabolomics Reveals Novel Serum Metabolic Signatures in Gastric Cancer by a Mass Spectrometry Platform
    Yu, Jiaying
    Zhao, Jinhui
    Yang, Tongshu
    Feng, Rennan
    Liu, Liyan
    JOURNAL OF PROTEOME RESEARCH, 2023, 22 (03) : 706 - 717
  • [6] Metabolomics reveals new metabolic perturbations in children with type 1 diabetes
    Galderisi, Alfonso
    Pirillo, Paola
    Moret, Vittoria
    Stocchero, Matteo
    Gucciardi, Antonina
    Perilongo, Giorgio
    Moretti, Carlo
    Monciotti, Carlamaria
    Giordano, Giuseppe
    Baraldi, Eugenio
    PEDIATRIC DIABETES, 2018, 19 (01) : 59 - 67
  • [7] Integrative multi-omics analysis reveals molecular signatures of central obesity in children
    Zhao, Chengzhi
    An, Xizhou
    Xiao, Leyuan
    Chen, Jingyu
    Huang, Daochao
    Chen, Lijing
    Fang, Shenying
    Liang, Xiaohua
    PEDIATRIC RESEARCH, 2025,
  • [8] Epitranscriptomic analysis reveals clinical and molecular signatures in glioblastoma
    Glaucia Maria de Mendonça Fernandes
    Wesley Wang
    Saman Seyed Ahmadian
    Daniel Jones
    Jing Peng
    Pierre Giglio
    Monica Venere
    José Javier Otero
    Acta Neuropathologica Communications, 13 (1)
  • [9] NMR metabolomics of human lung tumours reveals distinct metabolic signatures for adenocarcinoma and squamous cell carcinoma
    Rocha, Claudia M.
    Barros, Antonio S.
    Goodfellow, Brian J.
    Carreira, Isabel M.
    Gomes, Ana
    Sousa, Vitor
    Bernardo, Joao
    Carvalho, Lina
    Gil, Ana M.
    Duarte, Iola F.
    CARCINOGENESIS, 2015, 36 (01) : 68 - 75
  • [10] Metabolomics of a cell line-derived xenograft model reveals circulating metabolic signatures for malignant mesothelioma
    Gao, Yun
    Dai, Ziyi
    Yang, Chenxi
    Wang, Ding
    Guo, Zhenying
    Mao, Weimin
    Chen, Zhongjian
    PEERJ, 2022, 9