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Metabolomics in Early Life and the Association with Body Composition at Age 2 years

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Journal Pediatr Obes
Date 2021 Oct 13
PMID 34644810
Citations 6
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Abstract

Background And Objectives: Early life is a critical window for adiposity programming. Metabolic-profile in early life may reflect this programming and correlate with later life adiposity. We investigated if metabolic-profile at 3 months of age is predictive for body composition at 2 years and if there are differences between boys and girls and between infant feeding types.

Methods: In 318 healthy term-born infants, we determined body composition with skinfold measurements and abdominal ultrasound at 3 months and 2 years of age. High-throughput-metabolic-profiling was performed on 3-month-blood-samples. Using random-forest-machine-learning-models, we studied if the metabolic-profile at 3 months can predict body composition outcomes at 2 years of age.

Results: Plasma metabolite-profile at 3 months was found to predict body composition at 2 years, based on truncal: peripheral-fat-skinfold-ratio (T:P-ratio), with a predictive value of 75.8%, sensitivity of 100% and specificity of 50%. Predictive value was higher in boys (Q  = 0.322) than girls (Q  = 0.117). Of the 15 metabolite variables most strongly associated with T:P-ratio, 11 were also associated with visceral fat at 2 years of age.

Conclusion: Several plasma metabolites (LysoPC(22:2), dimethylarginine and others) at 3 months associate with body composition outcome at 2 years. These results highlight the importance of the first months of life for adiposity programming.

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References
1.
Breij L, Kerkhof G, De Lucia Rolfe E, Ong K, Abrahamse-Berkeveld M, Acton D . Longitudinal fat mass and visceral fat during the first 6 months after birth in healthy infants: support for a critical window for adiposity in early life. Pediatr Obes. 2016; 12(4):286-294. PMC: 6186414. DOI: 10.1111/ijpo.12139. View

2.
Chambers M, MacLean B, Burke R, Amodei D, Ruderman D, Neumann S . A cross-platform toolkit for mass spectrometry and proteomics. Nat Biotechnol. 2012; 30(10):918-20. PMC: 3471674. DOI: 10.1038/nbt.2377. View

3.
Landim M, Casella Filho A, Chagas A . Asymmetric dimethylarginine (ADMA) and endothelial dysfunction: implications for atherogenesis. Clinics (Sao Paulo). 2009; 64(5):471-8. PMC: 2694252. DOI: 10.1590/s1807-59322009000500015. View

4.
Chang H, Inoue K, Bruni A, Boarato E, Toffano G . Stereoselective effects of lysophosphatidylserine in rodents. Br J Pharmacol. 1988; 93(3):647-53. PMC: 1853839. DOI: 10.1111/j.1476-5381.1988.tb10322.x. View

5.
Jialal I, Kaur H, Devaraj S . Toll-like receptor status in obesity and metabolic syndrome: a translational perspective. J Clin Endocrinol Metab. 2013; 99(1):39-48. DOI: 10.1210/jc.2013-3092. View