Slater, Robyn Elis (2025) Detection and Correlation of Salivary Biomarkers to Burnout in Athletes. Masters thesis, York St John University.
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Abstract
Competition is an important part of an athlete’s career, creating opportunities for advancement and income. Research indicates that this can increase an athlete’s risk of burnout. With its major diagnostic symptoms emotional and physical exhaustion, depersonalisation and reduced sense of accomplishment being measured using the self-reported athlete burnout questionnaire, false positives are common. Past studies have identified immune biomarkers as possible targets for more accurate detection of burnout. For more research to be performed to identify the optimal biomarker a
simple analytical method for detecting these biomarkers is needed. Therefore, this study set out to develop enzyme-linked immunosorbent assays (ELISAs) for the subclasses IgA1, IgA2 and IgAsc. Optimisation methods exhibited high specificity and low cross-reactivity with other biomarkers in the saliva. Validation results showed that the IgAsc ELISA was optimised for use within an athlete population and
the IgA2 ELISA could accurately measure all samples with future testing on larger populations desirable, showing all reagents were optimised. The IgA1 ELISA was too sensitive for the range of concentrations found in the saliva samples and requires further optimisation. Once the saliva samples were paired with self-reported questionnaires both IgA2 and IgAsc showed weak, non-significant correlations with
total burnout and all three dimensions measured. Reduced sense of accomplishment showed the strongest correlation with both markers, highlighting the future research uses of the IgA2 and IgAsc ELISAs for identifying whether they are useful for early burnout detection once larger sample sizes can be investigated. Overall, the ELISAs developed in this study show a promising initial step in developing a reliable
detection method for IgA subclasses, especially with further optimisation of the IgA1 ELISA.
| Item Type: | Thesis (Masters) |
|---|---|
| Status: | Published |
| Subjects: | Q Science > Q Science (General) |
| School/Department: | School of Science, Technology and Health |
| URI: | https://ray.yorksj.ac.uk/id/eprint/12444 |
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