Sportomics Analysis: Triad Body Composition, Tumor Necrosis Factor Alpha and Immunometabolism in Athletes
Abstract
The close relationship between changes in body composition and the development of comorbidities was already observed by Hippocrates more than 2000 years ago. The objective was to investigate the acute impact caused by a treadmill running test on high-level athletes. In addition to identifying the acute changes that occurred in different plasma lipoproteins in the plasma concentration of TNF (Tumoral Necrosis Factor) and observing a possible correlation between TNF and body composition in running athletes. This cross-sectional, descriptive, and observational study is based on a sports strategy with high-level young athletes. The sample consisted of 10 male high-performance athletics athletes who are members of the athletics association in Barra do Garças, MT, Brazil. Using a gas analyzer, the treadmill exercise protocol was progressively increased until exhaustion. The variation in TNF levels showed a correlation with the variation of phospholipids (1.0), the variation in total cholesterol (1.0), with the variation of total lipids (1.0), and the variation of Low-Density Lipoprotein (0.9), lipoprotein, which also showed a correlation with the post-exercise TNF value (0.9). In addition, the pre-exercise TNF presented a correlation coefficient with the weight of the individuals (-0.9) and the variation of TNF with the Body Mass Index (-0.928). Using statistical correlation tests and presenting results with heat maps can be a data mining tool for evaluating biomarkers and different variables in immunometabolism studies. The present study also presents new perspectives on the relationship between body composition and immunometabolism.
References
Aggarwal, B.B., Gupta, S.C., e Kim, J.H. (2012). Historical perspectives on tumor necrosis factor and its superfamily: 25 years later, a golden journey. Blood, 119(3), 651-665. https://doi.org/10.1182/blood-2011-04-325225
Akcan, N., Obaid, M., Salem, J., e Bundak, R. (2020). Evidence in obese children: contribution of tri-ponderal mass index or body mass index to dyslipidemia, obesity-inflammation, and insulin sensitivity. Journal of Pediatric Endocrinology & Metabolism, 33(2), 223-231. https://doi.org/10.1515/jpem-2019-0106
Aras, M., Tchang, B.J., e Pape, J. (2021). Obesity and Diabetes. The Nursing clinics of North America, 56(4), 527-541. https://doi.org/10.1016/j.cnur.2021.07.008
Carswell, E.A., Old, L.J., Kassel, R.L., Green, S., Fiore, N., e Williamson, B. (1975). An endotoxin-induced serum factor that causes necrosis of tumors. Proceedings of The National Academy of Sciences of The USA, 72(9), 3666-3670. https://doi.org/10.1073/pnas.72.9.3666
Del Moral, A.M., Calvo, C., e Martinez, A. (2021). Ultra-processed food consumption and obesity-a systematic review. Nutrition Hospitalaria, 38(1), 177-185. https://doi.org/10.20960/nh.03151
Glass, T.A., Goodman, S.N., Hernan, M.A., e Samet, J.M. (2013). Causal inference in public health. Annual Review of Public Health, 34, 61-75. https://doi.org/10.1146/annurev-publhealth-031811-124606
Gonçalves, LCO, Santiago, DDC, Neto, AMM, Ferreira, HSP, Verli, MVA, Muniz-Santos, R., Lopes, JSS, e Andrade, CMB (2020). Sportomics analysis of a high-intensity functional training method, the CrossFit. Europub Journal of Health Research, 1(1), 2-20. https://doi.org/10.54747/ejhrv1n1-001
Gonçalves, L.C.O., Neto, A.M.M., e Andrade, C.M.B. (2022a). Correlation between acid-base balance and the immunometabolism after a Crosscombat™ session in MMA Athletes. MedCrave Online Journal of Public Health, 11(3), 71-73. https://doi.org/10.15406/MOJPH.2022.11.00378
Gonçalves, LCO, Neto, AMM, Bassini, A., Prado, ES, Muniz-Santos, R., Verli, MVA, Jurisica, L., Lopes, JSS, Jurisica, I., Andrade, CMB, e Cameron, LC (2022b) Sportomics suggests that albuminuria is a sensitive biomarker of hydration in cross combat. Scientific Reports, 12(8150), 1-12. https://doi.org/10.1038/s41598-022-12079-7
Grau, G.E., Lambert, P.H., Vassali, P., e Piguet, P.F. (1989). Tumor necrosis factor (TNF) and pathology, its relationships with other cytokines. Schweizerische Medizinishe Wochenschrift, 119(49), 1756-1761. https://pubmed.ncbi.nlm.nih.gov/2482541/
Green, S., Chiasson, M.A., e Shah, R.G. (1979). Evidence for the presence of an antitumor factor in serum of normal animals. Cancer Letters, 6(4-5), 235-240. https://doi.org/10.1016/s0304-3835(79)80039-7
Hong, M., Jacobucci, R., e Lubke, G. (2020). Deductive data mining. Psychological Methods, 25(6), 691-707. https://doi.org/10.1037/met0000252
Iannone, F., Praino, E., Rotondo, C., Natuzzi, C., Bizzoca, R., Lacarpia, N., Fornaro, M., e Cacciapaglia, F. (2021). Body mass index and adipokines/cytokines dysregulation in systemic sclerosis. Clinical and Experimental Immunology, 206(2), 153-160. https://doi.org/10.1111/cei.13651
Idriss, H.T., e Naismith, J.H. (2000). TNF alpha and the TNF receptor superfamily: structure-function relationship(s). Microscopy Research and Technique, 50(3), 184-195. https://doi.org/10.1002/1097-0029(20000801)50:3%3C184::aid-jemt2%3E3.0.co,2-h
Kalkan, C., Karakaya, F., Toruner, M., Cetinkaya, H., e Soykan, I. (2016). Anti-TNF-α agents and serum lipids in inflammatory bowel diseases. Clinics and Research in Hepatology and Gastroenterology, 40(4), 46-47. https://doi.org/10.1016/j.clinre.2015.12.009
Morishita, R., Franco, M.C., Suano-Souza, F.I., Sole, D., Puccini, R.F., e Strufaldi, M.W.L. (2016). Body mass index, adipokines and insulin resistance in asthmatic children and adolescents. The Journal of Asthma, 53(5), 478-484, 2016. https://doi.org/10.3109/02770903.2015.1113544
Oettgen, HF, Carswell, EA, Kassel, RL, Fiore, N., Williamson, B., Hoffmann, MK, Haranaka, K., e Old, LJ (1980). Endotoxin-induced tumor necrosis factor. Recent Results in Cancer Research, 75, 207-212. https://doi.org/10.1007/978-3-642-81491-4_32
Oliver, T.R. (2006). The politics of public health policy. Annual Review of Public Health, 27, 195-233. https://doi.org/10.1146/annurev.publhealth.25.101802.123126
Romagnani, S. (2000). T-cell subsets (Th1 versus Th2). Annals of Allergy, Asthma & Immunology, 85(1), 9-18, 2000. https://doi.org/10.1016/s1081-1206(10)62426-x
Steinkamp, R.C. (1968). Body composition in relation to disease. American Journal of Public Health and the Nation’s Health, 58(3), 473-476. https://doi.org/10.2105/ajph.58.3.473
Wu, W.T., Li, Y.J., Feng, A.Z., Li, L., Huang, T., Xu, A.D., e Lyu, J. (2021). Data mining in clinical big data: the frequently used databases, steps, and methodological models. Military Medical Research, 8(1), 44. https://doi.org/10.1186/s40779-021-00338-z
Yang, J., Li, Y., Liu, Q., Li, L., Feng, A., Wang, T., Zheng, S., e Xu, A., Lyu, J. (2020). Brief introduction of medical database and data mining technology in big data era. Journal of Evidence-Based Medicine, 13(1), 57-69. https://doi.org/10.1111/jebm.12373
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