Rev Esp Endocrinol Pediatr

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Rev Esp Endocrinol Pediatr 2020;11 Suppl(1):14-14 | Doi. 10.3266/RevEspEndocrinolPediatr.pre2020.Sep.600
Precision nutrition: focus on obesity
Nutrición de precisión: centrada en la obesidad

Sent for review: 8 Sep. 2020 | Accepted: 8 Sep. 2020  | Published: 8 Oct. 2020
José M. Ordovás
JM-USDA-HNRCA at Tufts University, Boston (USA). IMDEA-Food. Madrid (Spain)
Correspondence:José M. Ordovás, JM-USDA-HNRCA at Tufts University, Boston (USA), IMDEA-Food, Madrid, Spain
E-mail: Jose.Ordovas@tufts.edu
Abstract

Child obesity has been a global public health concern worldwide, and there is little evidence that the problem will subside soon. Research related to this problem has been entangled in the dilemma between Nature and Nurture as drivers of obesity. However, progress will be brought by a better understanding of the interactions between genetics (Nature) and non-genetic factors (Nurture; i.e., the exposome). Moreover, it is crucial to tackling obesity at its root. Thus, we know that environmental exposures, such as nutrition, during the early life stages, particularly the in-utero period (or even before conception), infancy, childhood, and puberty, have significant influences on the risk of chronic diseases, including obesity-related conditions that manifest as early as childhood. Nevertheless, the mechanisms underlying these relationships remain unclear. Therefore, we need to carry out studies using the technological advances provided by omics technologies (i.e., genomics, epigenomics, metabolomics), combined with the ability to conduct these measurements non-invasively by using urine and saliva. This approach will facilitate research during sensitive periods of development (i.e., newborns, toddlers). More mechanistic knowledge of the early drivers of obesity and other chronic disorders will facilitate a Precision Medicine approach to achieve lasting success in preventing and even cure such diseases. This will be achieved by tailoring recommendations to the specific genetic and environmental factors surrounding the individual. In this regard, Precision Nutrition has been a "work-in-progress" for several decades; however, the current technological developments, in combination with artificial intelligence and machine learning, offer the opportunity to achieve, shortly, science-based personalized recommendations aimed to prevent and cre obesity and other common diseases at all stages of life.

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