Paediatric obesity: a systematic review and pathway mapping of metabolic alterations underlying early disease processes

被引:22
作者
De Spiegeleer, Margot [1 ]
De Paepe, Ellen [1 ]
Van Meulebroek, Lieven [1 ]
Gies, Inge [2 ]
De Schepper, Jean [2 ,3 ]
Vanhaecke, Lynn [1 ,4 ]
机构
[1] Univ Ghent, Dept Translat Physiol Infectiol & Publ Hlth, Lab Chem Anal, Salisburylaan 133, B-9820 Merelbeke, Belgium
[2] Vrije Univ Brussel, Univ Ziekenhuis Brussel, KidZ Hlth Castle, Laarbeeklaan 101, B-1090 Brussels, Belgium
[3] Univ Ghent, Fac Med & Hlth Sci, Dept Internal Med & Pediat, Corneel Heymanslaan 10, B-9000 Ghent, Belgium
[4] Queens Univ, Sch Biol Sci, Inst Global Food Secur, Univ Rd, Belfast BT7 1NN, Antrim, North Ireland
关键词
Metabolomics; Lipidomics; Childhood obesity; Metabolic disease; Diabetes; Impaired glucose tolerance; CHAIN AMINO-ACIDS; CHILDHOOD OBESITY; INSULIN-RESISTANCE; GLUCOSE-TOLERANCE; ASSOCIATION; BIOMARKERS; CHILDREN; RISK; ACYLTRANSFERASE; CERAMIDES;
D O I
10.1186/s10020-021-00394-0
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Background The alarming trend of paediatric obesity deserves our greatest awareness to hinder the early onset of metabolic complications impacting growth and functionality. Presently, insight into molecular mechanisms of childhood obesity and associated metabolic comorbidities is limited. Main body of the abstract This systematic review aimed at scrutinising what has been reported on putative metabolites distinctive for metabolic abnormalities manifesting at young age by searching three literature databases (Web of Science, Pubmed and EMBASE) during the last 6 years (January 2015-January 2021). Global metabolomic profiling of paediatric obesity was performed (multiple biological matrices: blood, urine, saliva and adipose tissue) to enable overarching pathway analysis and network mapping. Among 2792 screened Q1 articles, 40 met the eligibility criteria and were included to build a database on metabolite markers involved in the spectrum of childhood obesity. Differential alterations in multiple pathways linked to lipid, carbohydrate and amino acid metabolisms were observed. High levels of lactate, pyruvate, alanine and acetate marked a pronounced shift towards hypoxic conditions in children with obesity, and, together with distinct alterations in lipid metabolism, pointed towards dysbiosis and immunometabolism occurring early in life. Additionally, aberrant levels of several amino acids, most notably belonging to tryptophan metabolism including the kynurenine pathway and its relation to histidine, phenylalanine and purine metabolism were displayed. Moreover, branched-chain amino acids were linked to lipid, carbohydrate, amino acid and microbial metabolism, inferring a key role in obesity-associated insulin resistance. Conclusions This systematic review revealed that the main metabolites at the crossroad of dysregulated metabolic pathways underlying childhood obesity could be tracked down to one central disturbance, i.e. impending insulin resistance for which reference values and standardised measures still are lacking. In essence, glycolytic metabolism was evinced as driving energy source, coupled to impaired Krebs cycle flux and ss-oxidation. Applying metabolomics enabled to retrieve distinct metabolite alterations in childhood obesity(-related insulin resistance) and associated pathways at early age and thus could provide a timely indication of risk by elucidating early-stage biomarkers as hallmarks of future metabolically unhealthy phenotypes.
引用
收藏
页数:20
相关论文
共 101 条
[91]   Predictors of changes in glucose tolerance status in obese youth [J].
Weiss, R ;
Taksali, SE ;
Tamborlane, WV ;
Burgert, TS ;
Savoye, M ;
Caprio, S .
DIABETES CARE, 2005, 28 (04) :902-909
[92]  
Wideman TH., 2013, ENCY BEHAV MED, P249
[93]   Validated Ultra-High-Performance Liquid Chromatography Hybrid High-Resolution Mass Spectrometry and Laser-Assisted Rapid Evaporative Ionization Mass Spectrometry for Salivary Metabolomics [J].
Wijnant, Kathleen ;
Van Meulebroek, Lieven ;
Pomian, Beata ;
De Windt, Kimberly ;
De Henauw, Stefaan ;
Michels, Nathalie ;
Vanhaecke, Lynn .
ANALYTICAL CHEMISTRY, 2020, 92 (07) :5116-5124
[94]   HMDB 4.0: the human metabolome database for 2018 [J].
Wishart, David S. ;
Feunang, Yannick Djoumbou ;
Marcu, Ana ;
Guo, An Chi ;
Liang, Kevin ;
Vazquez-Fresno, Rosa ;
Sajed, Tanvir ;
Johnson, Daniel ;
Li, Carin ;
Karu, Naama ;
Sayeeda, Zinat ;
Lo, Elvis ;
Assempour, Nazanin ;
Berjanskii, Mark ;
Singhal, Sandeep ;
Arndt, David ;
Liang, Yonjie ;
Badran, Hasan ;
Grant, Jason ;
Serra-Cayuela, Arnau ;
Liu, Yifeng ;
Mandal, Rupa ;
Neveu, Vanessa ;
Pon, Allison ;
Knox, Craig ;
Wilson, Michael ;
Manach, Claudine ;
Scalbert, Augustin .
NUCLEIC ACIDS RESEARCH, 2018, 46 (D1) :D608-D617
[95]  
World Health Organization, 2020, The Top 10 Causes of Death
[96]   Lactate, a Neglected Factor for Diabetes and Cancer Interaction [J].
Wu, Yong ;
Dong, Yunzhou ;
Atefi, Mohammad ;
Liu, Yanjun ;
Elshimali, Yahya ;
Vadgama, Jaydutt V. .
MEDIATORS OF INFLAMMATION, 2016, 2016
[97]   MetPA: a web-based metabolomics tool for pathway analysis and visualization [J].
Xia, Jianguo ;
Wishart, David S. .
BIOINFORMATICS, 2010, 26 (18) :2342-2344
[98]  
Zhang XB, 2019, J ADOLESCENT HEALTH, V65, P337, DOI 10.1016/j.jadohealth.2019.01.030
[99]   Carbohydrate and Amino Acid Metabolism as Hallmarks for Innate Immune Cell Activation and Function [J].
Zhao, Haoxin ;
Raines, Lydia N. ;
Huang, Stanley Ching-Cheng .
CELLS, 2020, 9 (03)
[100]   Using Metabolomic Profiles as Biomarkers for Insulin Resistance in Childhood Obesity: A Systematic Review [J].
Zhao, Xue ;
Gang, Xiaokun ;
Liu, Yujia ;
Sun, Chenglin ;
Han, Qing ;
Wang, Guixia .
JOURNAL OF DIABETES RESEARCH, 2016, 2016