A low cardiorespiratory fitness (CRF) is a strong and independent predictor of cardiometabolic, cancer and all-cause mortality. To date, the mechanisms linking CRF with reduced mortality remain largely unknown. Metabolomics, which is a powerful metabolic phenotyping technology to unravel molecular mechanisms underlying complex phenotypes, could elucidate how CRF fosters human health.
This study aims at systematically reviewing and meta-analysing the literature on metabolites of any human tissue sample, which are positively or negatively associated with CRF. Studies reporting estimated CRF will not be considered. No restrictions will be placed on the metabolomics technology used to measure metabolites. PubMed, Web of Science and EMBASE will be searched for relevant articles published until the date of the last search. Two authors will independently screen full texts of selected abstracts. References and citing articles of included articles will be screened for additional relevant publications. Data regarding study population, tissue samples, analytical technique, quality control, data processing, metabolites associated to CRF, cardiopulmonary exercise test protocol and exercise exhaustion criteria will be extracted. Methodological quality will be assessed using a modified version of QUADOMICS. Narrative synthesis as well as tabular/charted presentation of the extracted data will be included. If feasible, meta-analyses will be used to investigate the associations between identified metabolites and CRF. Potential sources of heterogeneity will be explored in meta-regressions.
No ethics approval is required. The results will be published in a peer-reviewed journal and as conference presentation.
CRD42020214375.