Sportomics: Building a new concept in metabolic studies and exercise science

•We explain a sportomics approach to mimic the real challenges faced during sports.•Sportomics is holistic and top-down; generating data treated in a systemic way.•We analyze cell metabolism as an integrated system and molecules relationships.•We reviewed the history, problems, benefits and outcomes of Sportomics.•Sportomics is translational and a bench to the field approach. For more than a decade, we have used alternative approaches to understand metabolic responses to physical stress. In addition to classic laboratory studies (cell and animal models), we have used elite athletes and sports to examine metabolic stress. Our central question involves the ability of the body to protect the central nervous system from high and toxic ammonemia during acute and chronic exercise. Information about this problem can aid in understanding important signaling pathways, which may yield better ways to protect people who suffer from diseases that lead to hyperammonemia, such as liver failure, or to hypermetabolic states, such as cancer or thermal injury. We proposed a Sportomics approach to mimic the real challenges and conditions that are faced during sports training and competition. Sportomics is non-hypothesis-driven research on an individual’s metabolite changes during sports and exercise. It is similar to metabolomics and other “-omics” approaches, but Sportomics focuses on sports as a metabolic challenge. Our study is holistic and top-down; we treat the data systematically and have generated a large computer-searchable database. We also propose that in-field metabolic analyses are important for understanding, supporting and training elite athletes. In this review, we discuss Sportomics history, problems, benefits and results. We included different weather conditions, such as temperature, wind and humidity, and diverse metabolic responses due to uneven sleep and eating behaviors near the time of the experiment. We are currently generating databases as well as data-mining principles and procedures to improve metabolomics and proteomics studies as well as adding genomics and transcriptomics studies to the Sportomics approach. We believe that this approach can fill a methodological gap between systems biology and translational medicine similar as a bench to the field approach.