ArticleBMC genomic data2023
Reveal key genes and factors affecting athletes performance in endurance sports using bioinformatic technologies.
Article in BMC genomic data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Examining the relationship between genetic polymorphisms (BDKRB2, GNB3, HIF1A, MCT1, NOS3) and endurance athlete status.European journal of applied physiology · 2024Pooled it
- Branched-chain amino acid supplementation and voluntary running have distinct effects on the serum metabolome of rats with high or low intrinsic aerobic capacity.Frontiers in nutrition · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Medium-intensity activities comprise the major proportion of many sorts of sports. The energy consumption of athletes has been a research emphasis for the purpose of improving both training efficiency and competition performance. However, the evidence based on large-scale gene screen has been rarely performed. This is a bioinformatic study revealing the key factors contributed to the metabolic difference between subjects with different endurance activity capacities. A dataset comprised of high- (HCR) and low-capacity running (LCR) rats was used. Differentially expressed genes (DEGs) were identified and analysed. The Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment was obtained. The DEGs' protein-protein interaction (PPI) network was built, and the enriched terms of the PPI network were also analysed. Our findings showed that the GO terms were enriched in lipid metabolism-related terms. The KEGG signalling pathway analysis enriched in the ether lipid metabolism. Plb1, Acad1, Cd2bp2, and Pla2g7 were identified as the hub genes. This study provides a theoretical foundation showing lipid metabolism plays an important role in the performance of endurance activities. Plb1, Acad1, and Pla2g7 may be the key genes involved. The training plan and diet for athletes can be designed based on above results and expecting a better competitive performance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.