Metabolomics in Pediatrics

During the week leading up to Christmas, Wishart’s node published a paper titled “Noninvasive testing for mycophenolate exposure in children with renal transplant using urinary metabolomics” Its objective is to develop a novel urine test to quantify Mycophenolic acid (MPA) exposure for children with a kidney transplant. Urinary metabolite classifiers are good MPA exposure estimators and associate with allograft inflammation. It’s a promising start, but larger studies are needed to validate and assess its clinical application.

The next research, “Development of a predictive algorithm to identify pre-school children at risk for behavior changes associated with sleep-related breathing disorders” was submitted to the Sleep Medicine Journal. Its aim is to study the increased risk of behavior problems in Children with late-onset (2–5 years) or persistent (3 months–5 years) sleep-related breathing disorder (SRBD). The authors developed a predictive algorithm via machine learning, using a combination of urine metabolites and questionnaires.

The Childhood Acute Illness and Nutrition (CHAIN) Network Nested Case-Cohort Study (CNCC) used an integrated multi-omics approach to look into the biological processes that lead to mortality of acutely ill children both during hospitalization and post-discharged. The objective of this study is to further minimize mortality, it may be helpful to have a firm grasp on the underlying mechanisms at play. Dr. Wishart’s team was involved in this research and the result is published as the article “The Childhood Acute Illness and Nutrition (CHAIN) network nested case-cohort study protocol: a multi-omics approach to understanding mortality among children in sub-Saharan Africa and South Asia

Another large cohort study related to the infants from Wishart’s node is “Childhood body mass index and associations with infant gut metabolites and secretory IgA: findings from a prospective cohort study”. This research comprises of the measurement on fecal metabolites and sIgA of 647 infants from the CHILD Cohort Study [sIgA, or secretory IgA – a prevalent type of antibody presents in the intestinal lumen of humans and other mammals.]

This study involved the linear regression that was adjusted for prenatal and postnatal variables, namely breastfeeding, birthweight-for-gestational age, birth mode and IAP, and solid food introduction. They investigated whether or not there was a relation between the metabolites, IgA, and child BMI z scores at the ages of 1 and 3 years. [IAP– Intrapartum Antibiotic Prophylaxis, BMI– Body Mass Index].

If you are interested in the pre-natal factors, we also reported some works from a different angle, from the mother’s metabolites. One of them is about the association of non-dietary factors with serum metabolite concentrations in pregnant women, by Dr. Philip Britz-McKibbin ‘s node at McMaster University, “Sources of Variation in Food-Related Metabolites during Pregnancy” 

The subsequent investigation is also related to the gut. The effect of diet on the gut microbiota and the serum metabolome in adults was evident, but this correlation has yet to be thoroughly investigated in infants. It is essential to gain a deeper understanding of the impact because infancy is a crucial developmental period that might influence a person’s long-term health.

This study counted in the derived dietary patterns of 182 infants aged one year who participated in the Canadian South Asian Birth Cohort (START) study. The result is published as an open-access article in the Journal of Nutrition, “The Relationship Between Diet, Gut Microbiota, and Serum Metabolome of South Asian Infants at 1 Year

Summarized by Juan Darius

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