The Salivary Alpha-Amylase Response to Moderate Intensity Trap Bar Deadlift

Authors: Asher L. Flynn¹, Jeremy Gentles²,Tyler Langford¹

¹Department of Sport and Exercise Science, Lincoln Memorial University, Harrogate, TN, USA
²Department of Sport, Exercise, Recreation, and Kinesiology, East Tennessee State University, Johnson City, TN, USA

Corresponding Author:
Asher L. Flynn, PhD, CSCS
117 Leopard Ln
Cumberland Gap, TN
AsherLFlynn@gmail.com
4178278827

Asher L Flynn, PhD, CSCS is an Assistant Professor of Exercise Science at Lincoln Memorial University, TN. His research interests focus on fatigue and athlete monitoring in colligate athletes, and aspects of women’s soccer performance.

Jeremy Gentles, PhD, CSCS is currently faculty member at East Tennessee State University, TN.  Jeremy’s areas of research interest include the biochemical response to exercise and sport technology.

Tyler Langford, PhD, is currently faculty member at Lincoln Memorial University, TN. Tyler’s areas of research interest include exercise testing and prescription for special populations (incomplete spinal cord injury and older adults) as well as the use of effort perception for exercise prescription.

The Salivary Alpha-Amylase Response to Moderate Intensity Trap Bar Deadlift

ABSTRACT

The purpose of this study was to investigate the salivary alpha-amylase response to a moderate intensity, moderate volume resistance training protocol. In order to investigate this response, pre-exercise and post-exercise saliva samples were collected from 16 female collegiate soccer players during a team resistance training session with the strength and condition staff. Results: The saliva analysis revealed a significant increase in salivary alpha-amylase concentrations from pre- to post-exercise; 54.7 ± 34.7 U/mL, 100.6 ± 55.1; p = 0.002; d = 0.908; 95% CI: 0.31 – 1.48. These results indicated that a moderate intensity, moderate volume training protocol will elicit an increase in salivary alpha-amylase. Sport scientists and coaches are continually improving their ability to monitor the stress, and the athlete’s response to these stressors. Salivary alpha-amylase is a promising candidate as a rapid, non-invasive method of indicating the magnitude of stress associated with resistance training.

Key Words: Fatigue, Stress, Athlete Monitoring

INTRODUCTION

Sport science initiatives often aim to quantify athlete stressors (i.e., practice, competition, and other life stress) to better manage training, improve sport performance, and reduce the risk of injury or illness (27). Common methods of quantifying training stress include monitoring training load (volume x intensity), self-report questionnaires (RPE, Short Recovery Stress Scale, Soreness charts), and a variety of biomarkers, such as cortisol (C), testosterone, C-reactive protein, and creatine kinase (7, 10, 22, 27, 28).

A new stress biomarker, salivary alpha-amylase (sAA), has recently received more interest due to its reactivity to stress, including aerobic exercise (7,12,14). The sAA response to stress is stimulated by norepinephrine (NE) through the sympathetic-adreno-medullary (SAM) axis. Since sAA is released through the SAM axis, monitoring the sAA response to stressors may provide alternate information regarding the stress response than the typically measured C response (1, 4, 17). Cortisol is released from the hypothalamus-pituitary-adrenal (HPA) axis and can take around 20-30 minutes to reach peak salivary concentration levels (29). During this time many other factors can affect the cortisol response to the stressor applied, such as carbohydrate intake, relaxing music, or yoga (18, 23). While salivary C changes may take time to reach peak concentrations, sAA concentrations increase nearly immediately after a stressor and can return to baseline within 10-minutes (20). With sAA having a more immediate response to stress and fast clearance rates, other factors are not able to alter the sAA response, thus providing a clearer picture of the response to that specific stressor.

Engert et al., (9) reported significant increases in both sAA and C concentrations due to stressor tasks, but also reported poor correlations between sAA and C (r = 0.27). The lack of strong correlations, as shown by Engert et al., (9), may indicate that sAA could be a better measure of the acute stress response to stress rather than C.

Numerous studies have reported an increased sAA concentration in response to various types of aerobic exercise (i.e. 400-meter run, gymnastics, marathon, swimming) (5, 6, 14, 15, 30). While there is a plethora of research regarding aerobic exercise, there is limited evidence related to resistance training (11, 26). Therefore, the purpose of this study was to expand upon prior investigations (11) that only used male participants and assess the sAA response to a moderate-intensity, moderate-volume lower body resistance training session among collegiate female athletes.

METHODS

Participants

Sixteen female soccer athletes participated in this study (age = 20.1 ± 1.7 yr, height = 166.44 ± 7.91 cm, body mass = 62.51 ± 8.18 kg). All participants were cleared for full sport participation and had not reported any injury that would limit their ability to perform their normal training. Participants provided written informed consent as approved by the Lincoln Memorial University Institutional Review Board.

This investigation was performed in conjunction with a normal team resistance training session. Participants were instructed to restrict caffeine intake from 6 hours prior to resistance training sessions. Participants arrived 60 minutes before the start of the resistance training session and were instructed to only drink water ad libitum and refrain from eating. Approximately 10 minutes before the resistance training session, athletes provided a saliva sample (PRE) via a synthetic absorbance swab (Salimetrics, Carlsbad, CA, USA), which was held under their tongue for two minutes. Samples were then immediately placed in an ice filled storage cooler. The athletes then met with strength and conditioning staff who guided the team through their normal warm-up and training session, which consisted of five sets of five repetitions (5×5) of trap-bar deadlift with increasing intensity (60%, 70%, 75%, 80%, 80% of 1RM). Immediately after completing the 5^th and final set of trap-bar deadlifts, athletes provided a second saliva sample (POST) in the same manner as the first sample. All saliva samples were then placed in a commercial freezer (-20 C) for 3 weeks until samples were analyzed. Salivary alpha-amylase samples were mailed overnight to the Salimetric’s SalivaLab (Carlsbad, CA, USA) on ice to ensure samples arrived frozen.

Saliva samples were assayed using the Salimetrics Salivary Alpha-Amylase Assay Kit (Cat. No. 1-1902, Salimetrics, Carlsbad, CA, USA), without modifications to the manufacturers’ protocol. Samples were thawed to room temperature, vortexed, and then centrifuged for 15 minutes at approximately 3,000 RPM (1,500 x g) immediately before performing the assay. Samples were tested for  sAA using a kinetic enzyme immunoassay (Cat. No. 1-1902, Salimetrics, Carlsbad, CA, USA). Samples were tested in duplicate, sample 1 (S1) and 2 (S2), and test volume was 8 µl of 200x diluted saliva per determination. The Salimetrics Salivary Alpha-Amylase Assay Kit (Cat. No. 1-1902, Salimetrics, Carlsbad, CA, USA) has a lower limit of sensitivity of 0.4 U/mL, samples exceeding 400 U/mL needed further dilution and this kit has been reported to have an average intra-assay coefficient of variation of 5.47% and an average inter-assay coefficient of variation of 4.7%, which meets the manufactures’ criteria for accuracy and repeatability in Salivary Bioscience.

Data Analyses

Data were analyzed using JASP (0.13.1.0) and reported as means ± standard deviations. Cohen’s d effect sizes (d) and 95% confidence intervals (95% CI) were also reported. Effect sizes were classified as trivial <0.2, small 0.2-0.6, moderate 0.6-1.2, large 1.2-2.0, and very large 2.0-4.0 (13). After normality was confirmed (Shapiro-Wilk, p = 0.82), a paired samples t-test was performed to assess the change in sAA concentration pre- to post- resistance training. Percent change between mean Pre- and Post-sAA concentrations and coefficients of variation (CV) were calculated between the duplicate trials and were calculated using Excel.

RESULTS

The paired samples t-test revealed a significant increase from pre- to post-training concentrations (PRE: 54.7 ± 34.7 U/mL, Range: 10.3 – 135.8; POST: 100.6 ± 55.1 U/mL, Range: 11.2 – 190.6; p = 0.002; d = 0.908, 95% CI: 0.31 – 1.48). The CV of all samples was 3%.

Thirteen participants had pre-training sAA concentrations between 24.9– 76.1 U/mL, with two participants having noticeable higher values of 123.0 and 135.8 U/mL and one participant with a lower pre-training sAA concentrations at only 10.3 U/mL. Individual pre- and post-training sAA concentrations are reported in Table 1 and Figure 1.

Table 1: Individual and group values of PRE- and POST-training sAA concentrations (U/mL).

	PRE				POST
Participant	S1	S2	Mean	CV%	S1	S2	Mean	CV%
1	25.9	23.9	24.9	5.6	85.9	83.3	84.6	2.2
2	128.9	117.1	123.0	6.8	138.4	134.2	136.3	2.2
3	141.0	130.5	135.8	5.5	89.5	83.0	86.3	5.4
4	10.5	10.2	10.3	2.2	11.2	11.2	11.2	0.0
5	59.4	56.1	57.7	4.0	99.4	93.2	96.3	4.6
6	38.7	37.4	38.0	2.4	52.8	52.2	52.5	0.9
7	71.2	70.8	71.0	0.3	167.9	165.0	166.5	1.3
8	42.3	42.0	42.1	0.6	89.2	87.6	88.4	1.3
9	47.2	46.2	46.7	1.5	193.5	187.6	190.6	2.2
10	38.0	37.4	37.7	1.2	64.0	62.6	63.3	1.5
11	64.3	59.7	62.0	5.2	118.1	106.3	112.2	7.4
12	64.3	61.0	62.6	3.7	129.9	122.7	126.3	4.0
13	30.8	28.2	29.5	6.3	38.4	37.1	37.7	2.5
14	33.5	30.5	32.0	6.5	146.6	144.0	145.3	1.3
15	76.8	75.4	76.1	1.2	187.6	184.0	185.8	1.4
16	26.6	25.3	25.9	3.6	26.6	25.9	26.2	1.8
GROUP				54.7 ± 34.7				100.6 ± 55.1

FIGURE 1:

Eleven of the 16 participants exhibited a substantial increase in sAA concentration of at least 67% (Range: 67 – 354%) while four of the remaining five participants exhibited less substantial increases, ranging from 8 – 38%. One of the 16 participants exhibited the opposite response and decreased sAA concentration by 36% from pre- to post-training (-36%). Individual percent changes are reported in Figure 2.

Figure 2:

DISCUSSION

Previous research has shown that sAA increases in response to acute stressors such as pain (3, 32), public speaking (17), and high intensity (above lactate threshold) exercise (14, 19). This study indicates that a moderate intensity and moderate volume resistance exercise consisting of 5×5 with progressive intensities from 60 – 80% 1RM trap bar deadlift is sufficiently stressful to stimulate sAA secretion in trained female athletes. This data concurs with previously reported trends observed from high-volume and high-intensity training (5×10 barbell back squat and bench press) in males (Pre 34.33 U/mL, Post: 63.79 U/mL) (11) and provides additional evidence that sAA concentrations have a measurable increase in response to resistance training (intermittent exercise/stress) as well as steady state exercise.

The observed increase in sAA to resistance training is interesting because, unlike previously studied aerobic training modes, there likely was not an increase in lactate with the 5-repetition protocol. It has been established that sAA concentrations are strongly correlated with blood lactate (r = 0.81, p < 0.05) during aerobic exercise (2), and there was likely a lactate response in the study by Flynn (11) using a 5×10 to failure resistance training protocol. This study provides evidence that the sAA response to exercise may be correlated with the creation of lactate, but possibly due to the high correlation of NE and lactate (r = 0.71, p value not reported) (31).

Like the results reported by Gill (12) and Flynn (11), this study found large inter-individual responses to the same training protocol. Variable interpersonal responses may be due to differences in genetic copies of the AMY1 gene, given that a higher copy number of AMY1 increase sAA enzyme synthesis and secretion in response to starch ingestion (16). The comparatively low levels of sAA observed in several participants may be due to having fewer AMY1 gene copies. The relatively small increase in sAA concentrations in some participants may be due to high levels of stress/anxiety at the pre-testing that may have caused high sAA concentrations at the pre-testing among some participants. Additionally, since this research was conducted during a normal resistance training session and athletes were provided autonomy (intensity/weight is not verified by the S&C staff), exercise intensity may have been lower than prescribed, and the sAA response smaller than expected if training was performed as prescribed. Ultimately, it is likely that a combination of these factors, AMY1 copy number, anxiety, and training intensity, explain most of the individual variance in sAA responses to training.

There are several limitations of this investigation. These limitations include no measure of global stress or anxiety at pre-test, training age was not considered, training intensity was not verified, and rest between sets was not controlled.

Since salivary-alpha amylase is a relatively new biomarker for athlete monitoring, there are several areas of research that should be investigated. First, the effect of AMY1 copies on the sAA response to stress should be established. Second, the dose-response relationship between intensity and volume of resistance training should be further addressed. Some research has reported an intensity dependent increase in sAA concentration, where sAA increases as exercise intensity (2), while other studies have shown that sAA concentrations are similar between low intensity (50W) and moderate intensity (ventilatory threshold) continuous cycling (21), and between steady state cycling (60% VO2max) and interval training (100% VO2max) (26). Lastly, future research should aim to investigate whether sAA or cortisol is better related to fatigue resulting from exercise.

CONCLUSIONS

Interest in sAA as an indicator of stress is rapidly increasing but there remains much to  understand about the relationship between sAA and acute and chronic stress. Data from this study provides evidence that moderate intensity, moderate volume resistance training is a stressor sufficient to increase sAA concentrations.  

APPLICATIONS IN SPORT

Resistance training is a substantial component of an athlete’s training and development, but there are currently few practical biochemical assessments stress resulting from resistance training. As interest in sAA has increased, companies have started developing point-of-care devices that are reportedly able to provide sAA measurement results in less than 5-minutes (8, 24, 25). With the development of these devices and the continued agreement between investigations reporting the sAA response to resistance training, sAA may provide a practical and objective method of monitoring of resistance training and other exercise related stress. This may help coaches and sport science staff to better manage training loads and improve sport performance.

REFERENCES

1. Ali, N., behavior, J. P.-P. &, & 2012, undefined. (2012). The salivary alpha amylase over cortisol ratio as a marker to assess dysregulations of the stress systems. Elsevier, 106(1), 65–72.
2. Bocanegra, O. L., Diaz, M. M., Teixeira, R. R., Soares, S. S., & Espindola, F. S. (2012). Determination of the lactate threshold by means of salivary biomarkers: Chromogranin A as novel marker of exercise intensity. European Journal of Applied Physiology, 112(9), 3195–3203.
3. Campos, M. J. D. S., Raposo, N. R. B., Ferreira, A. P., & Vitral, R. W. F. (2011). Salivary alpha-amylase activity: a possible indicator of pain-induced stress in orthodontic patients. Pain Medicine, 12(8), 1162-1166.
4. Capranica, L., Lupo, C., Cortis, C., Chiodo, S., Cibelli, G., & Tessitore, A. (2012). Salivary cortisol and alpha-amylase reactivity to taekwondo competition in children. European Journal of Applied Physiology, 112(2), 647–652.
5. Chennaoui, M., Bougard, C., Drogou, C., Langrume, C., Miller, C., Gomez-Merino, D., & Vergnoux, F. (2016). Stress biomarkers, mood states, and sleep during a major competition:“Success” and “failure” athlete’s profile of high-level swimmers. Frontiers in Physiology, 7, 94.
6. de Pero, R., Cibelli, G., Cortis, C., Sbriccoli, P., Capranica, L., & Piacentini, M. F. (2016). Stress related changes during TeamGym competition. Journal of Sports Medicine and Physical Fitness, 56(5), 639–647.
7. Deneen, W. P., & Jones, A. B. (2017). Cortisol and Alpha-amylase changes during an Ultra-Running Event. International Journal of Exercise Science, 10(4), 531–540.
8. Dunbar, J., Jehanli, A., & Hazell, G. (2015). 7 Evaluation of a new point of care quantitative cube reader for salivary analysis in the english premier league soccer environment. British Journal of Sports Medicine, 49(Suppl 2), A2.3-A3.
9. Engert, V., Vogel, S., Efanov, S. I., Duchesne, A., Corbo, V., Ali, N., & Pruessner, J. C. (2011). Investigation into the cross-correlation of salivary cortisol and alpha-amylase responses to psychological stress. Psychoneuroendocrinology, 36(9), 1294–1302.
10. Fathi, M., Azarbayjani, M., Peeri, M., Saiedi, A., & Fatollahi, H. (2012). The effects of a three-week resistance exercise plus whole body vibration (WBV) on the testosterone-free cortisole ratio differences and activity of the α-salivary amylase enzyme. The Scientific Journal Of Rehabilitation Medicine, 1(4), 20-26.
11. Flynn, A. (2019). The Salivary Alpha-Amylase Response to Resistance Training. https://dc.etsu.edu/etd/3625
12. Gill, S. K., Teixeira, A. M., Rama, L., Rosado, F., Hankey, J., Scheer, V., Robson-Ansley, P., & Costa, R. J. S. (2013). Salivary antimicrobial protein responses during multistage ultramarathon competition conducted in hot environmental conditions. Applied Physiology, Nutrition and Metabolism, 38(9), 977–987.
13. Hopkins, W. (2002). New view of statistics: Effect magnitudes. Sportscience. http://www.sportsci.org/resource/stats/effectmag.html
14. Kivlighan, K. T., & Granger, D. A. (2006). Salivary α-amylase response to competition: Relation to gender, previous experience, and attitudes. Psychoneuroendocrinology, 31(6), 703–714.
15. Ljungberg, G., Ericson, T., Ekblom, B., & Birkhed, D. (2007). Saliva and marathon running. Scandinavian Journal of Medicine & Science in Sports, 7(4), 214–219.
16. Mandel, A. L., Des Gachons, C. P., Plank, K. L., Alarcon, S., & Breslin, P. A. S. (2010). Individual differences in AMY1 gene copy number, salivary α-amylase levels, and the perception of oral starch. PLoS ONE, 5(10).
17. Maruyama, Y., Kawano, A., Okamoto, S., Ando, T., Ishitobi, Y., Tanaka, Y., Inoue, A., Imanaga, J., Kanehisa, M., Higuma, H., Ninomiya, T., Tsuru, J., Hanada, H., & Akiyoshi, J. (2012). Differences in salivary alpha-amylase and cortisol responsiveness following exposure to electrical stimulation versus the trier social stress tests. PLoS ONE, 7(7).
18. Meier, M., Wirz, L., Dickinson, P., & Pruessner, J. C. (2021). Laughter yoga reduces the cortisol response to acute stress in healthy individuals. Stress, 24(1), 44–52.
19. Monje, C., Rada, I., Castro-Sepulveda, M., Peñailillo, L., Deldicque, L., & Zbinden-Foncea, H. (2020). Effects of A High Intensity Interval Session on Mucosal Immune Function and Salivary Hormones in Male and Female Endurance Athletes. Journal of Sports Science & Medicine, 19(2), 436.
20. Nater, U. M., Rohleder, N., Gaab, J., Berger, S., Jud, A., Kirschbaum, C., & Ehlert, U. (2005). Human salivary alpha-amylase reactivity in a psychosocial stress paradigm. International Journal of Psychophysiology, 55(3), 333–342.
21. Radel, R., Tempest, G. D., & Brisswalter, J. (2018). The long and winding road: Effects of exercise intensity and type upon sustained attention. Physiology and Behavior, 195, 82–89.
22. Robertson, R. J., Goss, F. L., Rutkowski, J., Lenz, B., Dixon, C., Timmer, J., Frazee, K., Dube, J., Andreacci, J., Robertson, A., Goss, F. L., Rutkowski, J., Lenz, B., Dixon, C., Timmer, J., Frazee, K., Dube, J., & Andreacci, J. (2003). Concurrent Validation of the OMNI Perceived Exertion Scale for Resistance Exercise. Medicine and Science in Sports and Exercise, 35(2), 333–341.
23. Robinson, D. N., Hopke, T., & Massey-Abernathy, A. (2021). Learning to relax: The impact of brief biofeedback training and gentle yoga on salivary cortisol reduction. Current Psychology.
24. Robles, T. F., Sharma, R., Harrell, L., Elashoff, D. A., Yamaguchi, M., & Shetty, V. (2013). Saliva sampling method affects performance of a salivary α-amylase biosensor. American Journal of Human Biology, 25(6), 719–724.
25. Shetty, V., Zigler, C., Robles, T. F., Elashoff, D., & Yamaguchi, M. (2011). Developmental validation of a point-of-care, salivary α-amylase biosensor. Psychoneuroendocrinology, 36(2), 193–199.
26. Souza, A. v., Giolo, J. S., Teixeira, R. R., Vilela, D. D., Peixoto, L. G., Justino, A. B., Caixeta, D. C., Puga, G. M., & Espindola, F. S. (2019). Salivary and Plasmatic Antioxidant Profile following Continuous, Resistance, and High-Intensity Interval Exercise: Preliminary Study. Oxidative Medicine and Cellular Longevity, 2019.
27. Taylor, K.-L., Chapman, D. W., Cronin, J. B., Newton, M. J., & Gill, N. (2012). Fatigue monitoring in high performance sport: a survey of current trends. Journal of Australian Strength and Conditioning, 20(1), 12–23.
28. Utter, A. C., Robertson, R. J., Green, J. M., Suminski, R. R., McAnulty, S. R., & Nieman, D. C. (2004). Validation of the adult OMNI Scale of Perceived Exertion for walking/running exercise. Medicine and Science in Sports and Exercise, 36(10), 1776–1780.
29. VanBruggen, M. D., Hackney, A. C., McMurray, R. G., & Ondrak, K. S. (2011). The relationship between serum and salivary cortisol levels in response to different intensities of exercise. International Journal of Sports Physiology and Performance, 6(3), 396–407.
30. Walsh, N. P., Blannin, A. K., Clark, A. M., Cook, L., Robson, P. J., & Gleeson, M. (1999). The effects of high-intensity intermittent exercise on saliva IgA, total protein and α-amylase. Journal of Sports Sciences, 17(2), 129–134.
31. Weltman, A., Wood, C. M., Womack, C. J., Davis, S. E., Blumer, J. L., Alvarez, J., … & Gaesser, G. A. (1994). Catecholamine and blood lactate responses to incremental rowing and running exercise. Journal of Applied Physiology, 76(3), 1144-1149.
32. Wittwer, A., Krummenacher, P., La Marca, R., Ehlert, U., & Folkers, G. (2016). Salivary alpha-amylase correlates with subjective heat pain perception. Pain Medicine, 17(6), 1131-1136.