Abstract

Pregnancy is a period of major endocrine and metabolic changes which modulate both maternal and child’s health. Pregnancy exposures such as gestational diabetes mellitus (GDM), elevated maternal pre-pregnancy body-mass-index (BMI) and gestational weight gain (GWG) are risk factors for type 2 diabetes, overweight, and metabolic syndrome not only in the mother. Maternal diabetes and obesity to induce marked abnormalities in glucose homeostasis and insulin secretion in the fetus, and are linked to obesity, diabetes, and metabolic disease in the offspring. In recent years, the study of metabolomics has begun to receive increasing international attention, especially as it pertains to medical research. This is due in part to the potential for discovery of new biomarkers in the metabolome and to a new understanding of the “exposome”, which refers to the endogenous and exogenous compounds that reflect external exposures. Consequently, metabolomics research into pregnancy-related issues has increased. Biomarkers discovered through metabolomics may shed some light on the etiology of certain pregnancy-related complications and their adverse effects on future maternal health and infant development and improve current clinical management. The discoveries and methods used in these studies will be compiled and summarized within the following paper. A further focus of this paper is the use of hair as a biological sample, which is gaining increasing attention across diverse fields due to its noninvasive sampling method and the metabolome stability. At the end we have concluded that maternal BMI and glycemia are associated with different components of the new born metabolism, consistent with their independent effects on new born size at birth. Maternal BMI is associated with a new born metabolic signature characteristic of insulin resistance and risk of type 2 diabetes in adults. Thus we can say that metabolomics is a useful tool and it helps to develop targeted therapeutic tool to investigate these complications at early stages.

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