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Effects of anxiety on TNF-α levels during psychological stress
Journal of Psychosomatic Research 63 (2007) 65 – 69
Effects of anxiety on TNF-a levels during psychological stress S. Chandrashekaraa,4, K. Jayashreeb, H.B. Veerannab, H.S. Vadirajc, M.N. Rameshc, A. Shobhac, Y. Sarvananc, Yeragani K. Vikramc a
Chanre Rheumatology and Immunology Center, Clinical Immunology and Rheumatology, Bangalore, Karnataka, India b Department of Physiology, Bangalore Medical College, Bangalore, India c Department of Immunology, MS Ramaiah Medical College, Bangalore, India Received 25 July 2005
Abstract Objectives: Psychological stress can influence the immune system, which may result in stress-related illnesses. In this study, we investigated the effect of psychological stress and the coping skill on plasma cytokine levels. Materials and methods: One hundred eighty-three students, at different stages of an academic year, participated in this study. Plasma tumor necrosis factor alpha (TNFa), interleukin (IL)-2 soluble receptor alpha, and IL-4 were measured and examined in relation to the measures of anxiety [State Anxiety Inventory (SAI)] and Bell Adjustment Inventory
(BAI) score. Results: SAI scores were significantly higher in both midterm students (MTS) and examination-taking students (ETS), compared with the freshly admitted students (FAS). In addition, TNF-a levels were significantly different between the high- and the low-anxiety groups of ETS but not in MTS or FAS. The correlation between SAI scores and the BAI emotional scores was highest in the ETS group. Conclusions: TNF-a level was significantly lower in the ETS group with high anxiety scores, and it is situation specific. D 2007 Published by Elsevier Inc.
Keywords: Psychological stress; Anxiety; Immunity; Cytokines; Coping
Introduction Psychological stress affects the immune system in different ways. The influence of stress on the immune system is variable and could be individual specific. The most frequently observed response is immune suppression, especially when the stress is chronic and persisting [1–3]. Immune activation occurs when the stress is acute and shortlived [4–6]. In one study, there was a drift from T-helper cell 1 (TH-1) to TH-2 response in an acute stressful situation [7,8]. The heterogeneity of stress is influenced by the situation that generates the stress [9] and other factors such as the personality of the individual [10], the individual’s coping skills [11], preexisting psychological status [12], sociocultural factors [13,14], and gender. For example, an 4 Corresponding author. Chanre Rheumatology and Immunology Center, Clinical Immunology and Rheumatology, Bangalore, Karnataka 560003, India. Tel.:+ 91 80 23368030; fax: +91 80 23368029. E-mail address: [email protected] (S. Chandrashekara). 0022-3999/07/$ – see front matter D 2007 Published by Elsevier Inc. doi:10.1016/j.jpsychores.2007.03.001
inevitable or nonmodifiable situation (when compared with a modifiable situation) has a major influence on the immune system [9]. Stress is related to situations, which depend upon the individual’s coping skills, social support, and emotional factors. There are very few studies addressing the influence of coping skills on the immune system. However, the results are not uniform. In a study on self-hypnosis, which effectively reduced stress generated by an examination, there were no effects observed on the immune system [15]. In another study, Borella et al. [16] observed a reduction in natural killer (NK) cell activity in students with high anxiety and low emotional stability, in contrast to students with low anxiety and high emotional stability. In their study, the overall impact of examination stress on the immune system (NK cell activity) was influenced by emotional stability and the anxiety that was generated. An individual’s coping skill is a modifiable factor that helps the individual to deal with stress effectively [17]. The coping skills adapted by individuals vary substantially,
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S. Chandrashekara et al. / Journal of Psychosomatic Research 63 (2007) 65 – 69
leading to a change in the level of stress generated [17]. Tumor necrosis factor alpha (TNF-a) is a key cytokine, which plays a critical role in tumor immunity as well as in immunity against infection. Impaired response or exaggerated response of TNF is deleterious to the host in regard to coping with infections and other stress-related situations [18,19]. Excessive TNF production can also produce impaired glucose tolerance as well as endothelial dysfunction [20,21]. In order to understand the influence of situation-specific anxiety and various coping skills on the cytokine levels, we designed a simple protocol using a wellaccepted academic student stress medical model [22]. The students, admitted to first year medical school, undergo a series of stresses and rewards [22]. In the first few weeks, the students are in a state of elation or anxiety due to an entirely new situation. The students in the middle period of their first year, whose examinations are 6 months away, are relaxed and composed, without much stress from examination. On the day of the examination, the academic stress perceived by the students is reportedly high. The present study assessed the impact of the stress of taking an examination by measuring the students’ anxiety scores and the influence of coping skills on the immune function by measuring cytokine levels. We hypothesized that the TNF-a levels will be significantly lower in those students with high levels of anxiety and low adaptability skills compared with the less anxious group with high adaptability skills. TNF-a is a TH-1 cytokine, while interleukin (IL)-4 is a TH-2 cytokine [23]. Hence, we studied IL-4 to understand the status of TH-1 and TH-2. IL-2 soluble receptor alpha (IL-2sRa) is a reliable marker of status of T-cell activation and inflammation and was included in this study to assess the activation of T cells [24].
Materials and methods One hundred eighty-three undergraduate medical students in their first year (age range, 18–24 years) participated in the study. The study was approved by the institutional ethical committee at the Bangalore Medical College, and a written informed consent was obtained from each participant prior to their participation in the study. We used meanFS.D. to describe the data throughout this article. Of the 183 students, 58 were in the middle of their term [midterm students (MTS); age=18.4F0.54 years], 60 were about to take the examinations [examination-taking students (ETS); age=18.6F0.65 years], and 65 were freshly admitted students (FAS; age=17.9F0.61 years). We included only those students who had complete data of TNF-a level as this was central to our hypothesis. All participants were healthy and had no diseases associated with abnormal immunological function. None of the students was on any medication, including nonprescription drugs. We administered the Bell Adjustment Inventory (Student Form of BAI) [25] and the State Anxiety Inventory (SAI) [26] just before the students took the examination, especially in the ETS group, and the blood
samples were collected at that point. The BAI is a selfadministered, 140-item questionnaire, which yields separate scores for home, health, social, and emotional adjustment. Questions retained in the scale were those that were found to differentiate between students—those known to be maladjusted and those considered to be normal [26]. The SAI is also a self-administered questionnaire of 20 statements that evaluates how the respondents feel dright nowT. The weighted scores for each of the 20 items are added to obtain the total score that ranges from 20 to a maximum of 80. Cytokine assay Blood samples were collected from students between 8:00 and 9:00 a.m. Plasma separated from the blood was used to estimate the cytokine levels. Enzyme-linked immunosorbent assay (ELISA) was performed using DuoSet ELISA development system according to the manufacturer’s instructions (R & D Systems, Minneapolis, MN, USA). Briefly, polystyrene microtiter plates (NUNC, U16 Maxisorp type, Roskilde, Denmark) were coated with monoclonal capture antibody (antihuman TNF-a, antihuman IL-2sRa, and antihuman IL-4) obtained from mouse (R & D Systems) and incubated at 48C overnight. The following day, the plates were blocked and then incubated for 2 h with plasma. This was followed by the addition of corresponding biotinylated detection antibody obtained from goat (R & D Systems) and incubated for 2 h. Streptavidin horseradish peroxidase (R & D Systems) and, then, tetramethylbenzidine substrate (Bangalore Genei, Bangalore, India) treatment followed this incubation. The reaction was stopped using 2 N sulfuric acid, and optical density reading was taken at 450 nm (ELISA reader: Organon Teknika Microwell system, Reader 230 s, Eppelheim, Germany). All the experiments were conducted in duplicate. A standard curve was obtained based on the standards provided by the manufacturer. The results were expressed as concentration of cytokines (in pg/ml) read from the standard curve. Statistical analysis We used BMDP statistical software (Berkeley, CA, USA) to perform the analyses. We used a two-way analysis of Table 1 Behavioral and immunological measures of the three groups of students (meanFS.D.) Measure
MTS
ETS
FAS
SAI BAI: total BAI: home BAI: health BAI: social BAI: emotional IL-2sRa (pg/ml) IL-4 (pg/ml) TNF-a (pg/ml)
42.3F10.7 47.1F19.8 7.9F5.8 9.6F6.0 15.3F6.2 14.5F7.4 5.0F0.6 1.5F0.8 2.7F1.0
42F11.4 47.6F15.3 8.2F5.5 8.7F4.5 16.1F5.9 14.7F6.1 5.2F0.7 1.5F0.7 2.6F1.1
37.1F10.5 48.0F16.0 8.7F5.6 8.2F4.2 17.1F6.7 13.9F6.0 5.2F0.3 2.0F1.1 2.8F0.8
S. Chandrashekara et al. / Journal of Psychosomatic Research 63 (2007) 65 – 69 Table 2 Results of two-way ANOVA [student group (S) as one factor and high anxiety (z40) vs. low anxiety (b40) on the SAI (A) as the other factor] Measure
F
df
P
BAI: total BAI: home BAI: health BAI: social BAI: emotional IL-2sRa (pg/ml) IL-4 (pg/ml)
A: 20.1 A: 13.1 A: 5.2 NS A: 27.5 NS S: 2.9 A: 3.0 SA: 3.3
1, 177 1, 177 1, 177
.00001 .0004 .02
1, 177
.00001
2, 98 1, 98 2, 177
.06 .09 .04
TNF-a (pg/ml)
variance (ANOVA) with student group as one factor and high versus low anxiety as the other grouping factor. This was done using a cutoff score of b40 (low) or z40 (high) on the SAI. A score of 40 was chosen to include an almost equal number of people in each group. Significant effects on the ANOVA were followed up with a post hoc Tukey’s studentized range statistic to identify significant differences among the three groups. When there was a significant student type versus anxiety interaction effect, the three groups were compared separately for high versus low anxiety levels. We also used a stepwise regression analysis including the SAI score as the dependent variable and BAI scores (using all subscores) as the independent variables to find out the association between anxiety levels and adaptability. This was followed up using Pearson Product– Moment Correlation statistic between variables of interest to examine the association of SAI and BAI scores in each group of students. All tests were two tailed, and a P value of b.05 was used to identify significant effects.
Results Table 1 shows the data for all the variables for the three groups of students. As expected, high-anxiety groups were associated with significantly higher scores on BAI (higher scores on BAI indicate a lower level of adaptability; Table 2). There was a trend toward a significant difference for IL-4 among the groups, and post hoc tests revealed a significant difference only between the FAS compared to the other two groups (FAS group had higher values of IL-4). Table 3 Comparison of ETS group with high anxiety (z40) versus low anxiety (b40) on the SAI as the grouping factor (meanFS.D.) Measure
High anxiety
Low anxiety
t
P
BAI: total BAI: home BAI: health BAI: social BAI: emotional IL-2sRa (pg/ml) IL-4 (pg/ml) TNF-a (pg/ml)
51.6F15.3 9.2F5.6 9.2F4.4 16.6F6.3 16.6F5.7 5.2F0.3 1.1+0.9 2.4F0.9
42.8F15.2 7.1F5.4 8.2F4.6 16.1F5.5 11.5F6.0 5.2F1.0 1.3F0.9 3.1F1.4
2.4 NS NS NS 3.7 NS NS 2.5
.02
.0005
.016
67
Table 4 Comparison of FAS and MTS groups with high (z40) versus low anxiety on the SAI (b40) as the grouping factor for the immunological variables (meanFS.D.) FAS
MTS
Measure
High anxiety
Low anxiety
High anxiety
Low anxiety
IL-2sRa (pg/ml) IL-4 (pg/ml) TNF-a (pg/ml)
5.2F0.3 2.1F0.9 2.8F0.7
5.2F0.3 1.9F1.2 2.9F0.8
5.0F0.4 1.6F1.0 3.0F1.3
5.2F0.8 1.3F0.3 2.6F1.1
There was a significant interaction effect between the student group and anxiety level only for TNF-a. Post hoc tests revealed a significant difference in TNF-a between high- and low-anxiety groups only for the ETS (Table 3). Table 4 shows the values for these measures for the FAS and MTS (between high- and low-anxiety groups). There were no significant differences between the high- and the lowanxiety groups for the immunological measures in FAS or MTS. Stepwise regression analyses showed that the SAI score was associated most with the emotional subscale of BAI (r=.45; P b.001), and the rest of the items did not contribute much further. Correlations in each group of students have shown that the BAI-emotional scale scores significantly correlated with the SAI scores in the ETS (r=.60; P=.00001) and the MTS (r=.48; P=.0009) groups. In the FAS group, this was not significant (r=.27).
Discussion The present study used a reliable academic examination stress model, employing scores on the SAI to evaluate the effects of stress and coping mechanisms on the immune system. The SAI scores were most significantly related to the BAI-emotional subscores in the ETS group, which was expected. The most important finding in this study is that TNF-a levels were significantly lower in the ETS group with high anxiety scores compared to those with lower scores. In the MTS group, the level of TNF-a was not significantly different between high- and low-anxiety groups. The other finding was that there was a trend toward significantly higher values of IL-4 in the FAS group compared with the other two groups. The SAI scores were higher in the ETS and MTS groups compared with the FAS group, but the two-way ANOVA did not reveal a significant group effect. The more significant positive correlation between the SAI score and the BAI-emotional score in the ETS group compared with the other groups may be due to the situation-specific anxiety, which is differentially influenced by the coping skills in different individuals. Decreased TNF-a levels during examination-induced stress in students who had higher anxiety scores in the present study are not in agreement with previous studies [6,27]. The amount of anxiety developed during examination
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directly correlated with the BAI score, suggesting that better coping skill was associated with less anxiety, as observed previously [28]. In another study, a nonacademic stressful task such as color–word interference or glass tracing was used, and there was a delayed rise in the levels of TNF-a, IL-6, and IL-1Ra following the execution of the task [6]. The anxiety in the MTS group on the whole was similar to that in the ETS group, and this could be due to the chronic nature of the stress. As the anxiety was not situation specific in this group, the TNF-a levels may not have been different between high- and low-anxiety groups. This observation suggests that TNF-a level changes could be situation specific and not just related to a particular state. Studies do demonstrate that the impact of stress generated by a situation on the response of immune system differs depending on factors like coping skill [29] and personality [17]. In contrast to other studies, the current study examined SAI scores as well as cytokine levels prior to the examination, which is associated with different degrees of anxiety, which also may have been influenced by the individual coping mechanisms. It is easy to cope with anticipated and inevitable stressors, and the impact of these stressors on the immune system may be less severe. In a rat model employing the prewarning foot shock as a stressor, immune suppression was demonstrated to be less remarkable in rats with prewarning when compared to groups that did not receive such warning [30]. Hence, late stages of stress may be associated with immune suppression, especially when the coping skills are inadequate [31,32]. The changes in immunological activities observed in earlier studies were either during or after execution of the task. This could explain why the immunological activities could have been different in the present study. Examination is an inevitable natural stressor in a student’s life. In addition, TNF-a has been demonstrated to impair the endothelial function and could trigger a series of inflammatory responses [33,34]. However, we found that students in the ETS group with higher anxiety scores and low coping skills had a significantly lower TNF-a level. As we found in this study, the response of raised TNF-a is situation specific. This finding is rather counterintuitive, and hence, we speculate that the decrease in TH-1 function in anxiety in certain situations may adversely affect the individual’s immune function. The neurotransmitter Substance P induces the synthesis of TNF and IL-1 in macrophages. IL-1 and IL-6 stimulate the synthesis of ACTH (corticotrophin) in the pituitary. Glucocorticoids, which are synthesized in response to ACTH, inhibit the synthesis of IL-6, IL-1, and TNF-a in vivo, thus establishing a negative feedback loop between the immune system and neuroendocrine functions. TNF-a, in turn, promotes thrombosis as well endothelial dysfunctions [35]. Stress can be associated with an increased cortisol level, and this may lead to decreased TNF-a level in situation-specific anxiety states. Future prospective studies should address this issue
using follow-up data, especially in relation to the outcome of the particular stressful situation as well as how well the individual copes with it at a later stage. It is also important to examine the relative changes in endocrine and immune function in different stressful situations.
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Effects of anxiety on TNF-a levels during psychological stress S. Chandrashekaraa,4, K. Jayashreeb, H.B. Veerannab, H.S. Vadirajc, M.N. Rameshc, A. Shobhac, Y. Sarvananc, Yeragani K. Vikramc a
Chanre Rheumatology and Immunology Center, Clinical Immunology and Rheumatology, Bangalore, Karnataka, India b Department of Physiology, Bangalore Medical College, Bangalore, India c Department of Immunology, MS Ramaiah Medical College, Bangalore, India Received 25 July 2005
Abstract Objectives: Psychological stress can influence the immune system, which may result in stress-related illnesses. In this study, we investigated the effect of psychological stress and the coping skill on plasma cytokine levels. Materials and methods: One hundred eighty-three students, at different stages of an academic year, participated in this study. Plasma tumor necrosis factor alpha (TNFa), interleukin (IL)-2 soluble receptor alpha, and IL-4 were measured and examined in relation to the measures of anxiety [State Anxiety Inventory (SAI)] and Bell Adjustment Inventory
(BAI) score. Results: SAI scores were significantly higher in both midterm students (MTS) and examination-taking students (ETS), compared with the freshly admitted students (FAS). In addition, TNF-a levels were significantly different between the high- and the low-anxiety groups of ETS but not in MTS or FAS. The correlation between SAI scores and the BAI emotional scores was highest in the ETS group. Conclusions: TNF-a level was significantly lower in the ETS group with high anxiety scores, and it is situation specific. D 2007 Published by Elsevier Inc.
Keywords: Psychological stress; Anxiety; Immunity; Cytokines; Coping
Introduction Psychological stress affects the immune system in different ways. The influence of stress on the immune system is variable and could be individual specific. The most frequently observed response is immune suppression, especially when the stress is chronic and persisting [1–3]. Immune activation occurs when the stress is acute and shortlived [4–6]. In one study, there was a drift from T-helper cell 1 (TH-1) to TH-2 response in an acute stressful situation [7,8]. The heterogeneity of stress is influenced by the situation that generates the stress [9] and other factors such as the personality of the individual [10], the individual’s coping skills [11], preexisting psychological status [12], sociocultural factors [13,14], and gender. For example, an 4 Corresponding author. Chanre Rheumatology and Immunology Center, Clinical Immunology and Rheumatology, Bangalore, Karnataka 560003, India. Tel.:+ 91 80 23368030; fax: +91 80 23368029. E-mail address: [email protected] (S. Chandrashekara). 0022-3999/07/$ – see front matter D 2007 Published by Elsevier Inc. doi:10.1016/j.jpsychores.2007.03.001
inevitable or nonmodifiable situation (when compared with a modifiable situation) has a major influence on the immune system [9]. Stress is related to situations, which depend upon the individual’s coping skills, social support, and emotional factors. There are very few studies addressing the influence of coping skills on the immune system. However, the results are not uniform. In a study on self-hypnosis, which effectively reduced stress generated by an examination, there were no effects observed on the immune system [15]. In another study, Borella et al. [16] observed a reduction in natural killer (NK) cell activity in students with high anxiety and low emotional stability, in contrast to students with low anxiety and high emotional stability. In their study, the overall impact of examination stress on the immune system (NK cell activity) was influenced by emotional stability and the anxiety that was generated. An individual’s coping skill is a modifiable factor that helps the individual to deal with stress effectively [17]. The coping skills adapted by individuals vary substantially,
66
S. Chandrashekara et al. / Journal of Psychosomatic Research 63 (2007) 65 – 69
leading to a change in the level of stress generated [17]. Tumor necrosis factor alpha (TNF-a) is a key cytokine, which plays a critical role in tumor immunity as well as in immunity against infection. Impaired response or exaggerated response of TNF is deleterious to the host in regard to coping with infections and other stress-related situations [18,19]. Excessive TNF production can also produce impaired glucose tolerance as well as endothelial dysfunction [20,21]. In order to understand the influence of situation-specific anxiety and various coping skills on the cytokine levels, we designed a simple protocol using a wellaccepted academic student stress medical model [22]. The students, admitted to first year medical school, undergo a series of stresses and rewards [22]. In the first few weeks, the students are in a state of elation or anxiety due to an entirely new situation. The students in the middle period of their first year, whose examinations are 6 months away, are relaxed and composed, without much stress from examination. On the day of the examination, the academic stress perceived by the students is reportedly high. The present study assessed the impact of the stress of taking an examination by measuring the students’ anxiety scores and the influence of coping skills on the immune function by measuring cytokine levels. We hypothesized that the TNF-a levels will be significantly lower in those students with high levels of anxiety and low adaptability skills compared with the less anxious group with high adaptability skills. TNF-a is a TH-1 cytokine, while interleukin (IL)-4 is a TH-2 cytokine [23]. Hence, we studied IL-4 to understand the status of TH-1 and TH-2. IL-2 soluble receptor alpha (IL-2sRa) is a reliable marker of status of T-cell activation and inflammation and was included in this study to assess the activation of T cells [24].
Materials and methods One hundred eighty-three undergraduate medical students in their first year (age range, 18–24 years) participated in the study. The study was approved by the institutional ethical committee at the Bangalore Medical College, and a written informed consent was obtained from each participant prior to their participation in the study. We used meanFS.D. to describe the data throughout this article. Of the 183 students, 58 were in the middle of their term [midterm students (MTS); age=18.4F0.54 years], 60 were about to take the examinations [examination-taking students (ETS); age=18.6F0.65 years], and 65 were freshly admitted students (FAS; age=17.9F0.61 years). We included only those students who had complete data of TNF-a level as this was central to our hypothesis. All participants were healthy and had no diseases associated with abnormal immunological function. None of the students was on any medication, including nonprescription drugs. We administered the Bell Adjustment Inventory (Student Form of BAI) [25] and the State Anxiety Inventory (SAI) [26] just before the students took the examination, especially in the ETS group, and the blood
samples were collected at that point. The BAI is a selfadministered, 140-item questionnaire, which yields separate scores for home, health, social, and emotional adjustment. Questions retained in the scale were those that were found to differentiate between students—those known to be maladjusted and those considered to be normal [26]. The SAI is also a self-administered questionnaire of 20 statements that evaluates how the respondents feel dright nowT. The weighted scores for each of the 20 items are added to obtain the total score that ranges from 20 to a maximum of 80. Cytokine assay Blood samples were collected from students between 8:00 and 9:00 a.m. Plasma separated from the blood was used to estimate the cytokine levels. Enzyme-linked immunosorbent assay (ELISA) was performed using DuoSet ELISA development system according to the manufacturer’s instructions (R & D Systems, Minneapolis, MN, USA). Briefly, polystyrene microtiter plates (NUNC, U16 Maxisorp type, Roskilde, Denmark) were coated with monoclonal capture antibody (antihuman TNF-a, antihuman IL-2sRa, and antihuman IL-4) obtained from mouse (R & D Systems) and incubated at 48C overnight. The following day, the plates were blocked and then incubated for 2 h with plasma. This was followed by the addition of corresponding biotinylated detection antibody obtained from goat (R & D Systems) and incubated for 2 h. Streptavidin horseradish peroxidase (R & D Systems) and, then, tetramethylbenzidine substrate (Bangalore Genei, Bangalore, India) treatment followed this incubation. The reaction was stopped using 2 N sulfuric acid, and optical density reading was taken at 450 nm (ELISA reader: Organon Teknika Microwell system, Reader 230 s, Eppelheim, Germany). All the experiments were conducted in duplicate. A standard curve was obtained based on the standards provided by the manufacturer. The results were expressed as concentration of cytokines (in pg/ml) read from the standard curve. Statistical analysis We used BMDP statistical software (Berkeley, CA, USA) to perform the analyses. We used a two-way analysis of Table 1 Behavioral and immunological measures of the three groups of students (meanFS.D.) Measure
MTS
ETS
FAS
SAI BAI: total BAI: home BAI: health BAI: social BAI: emotional IL-2sRa (pg/ml) IL-4 (pg/ml) TNF-a (pg/ml)
42.3F10.7 47.1F19.8 7.9F5.8 9.6F6.0 15.3F6.2 14.5F7.4 5.0F0.6 1.5F0.8 2.7F1.0
42F11.4 47.6F15.3 8.2F5.5 8.7F4.5 16.1F5.9 14.7F6.1 5.2F0.7 1.5F0.7 2.6F1.1
37.1F10.5 48.0F16.0 8.7F5.6 8.2F4.2 17.1F6.7 13.9F6.0 5.2F0.3 2.0F1.1 2.8F0.8
S. Chandrashekara et al. / Journal of Psychosomatic Research 63 (2007) 65 – 69 Table 2 Results of two-way ANOVA [student group (S) as one factor and high anxiety (z40) vs. low anxiety (b40) on the SAI (A) as the other factor] Measure
F
df
P
BAI: total BAI: home BAI: health BAI: social BAI: emotional IL-2sRa (pg/ml) IL-4 (pg/ml)
A: 20.1 A: 13.1 A: 5.2 NS A: 27.5 NS S: 2.9 A: 3.0 SA: 3.3
1, 177 1, 177 1, 177
.00001 .0004 .02
1, 177
.00001
2, 98 1, 98 2, 177
.06 .09 .04
TNF-a (pg/ml)
variance (ANOVA) with student group as one factor and high versus low anxiety as the other grouping factor. This was done using a cutoff score of b40 (low) or z40 (high) on the SAI. A score of 40 was chosen to include an almost equal number of people in each group. Significant effects on the ANOVA were followed up with a post hoc Tukey’s studentized range statistic to identify significant differences among the three groups. When there was a significant student type versus anxiety interaction effect, the three groups were compared separately for high versus low anxiety levels. We also used a stepwise regression analysis including the SAI score as the dependent variable and BAI scores (using all subscores) as the independent variables to find out the association between anxiety levels and adaptability. This was followed up using Pearson Product– Moment Correlation statistic between variables of interest to examine the association of SAI and BAI scores in each group of students. All tests were two tailed, and a P value of b.05 was used to identify significant effects.
Results Table 1 shows the data for all the variables for the three groups of students. As expected, high-anxiety groups were associated with significantly higher scores on BAI (higher scores on BAI indicate a lower level of adaptability; Table 2). There was a trend toward a significant difference for IL-4 among the groups, and post hoc tests revealed a significant difference only between the FAS compared to the other two groups (FAS group had higher values of IL-4). Table 3 Comparison of ETS group with high anxiety (z40) versus low anxiety (b40) on the SAI as the grouping factor (meanFS.D.) Measure
High anxiety
Low anxiety
t
P
BAI: total BAI: home BAI: health BAI: social BAI: emotional IL-2sRa (pg/ml) IL-4 (pg/ml) TNF-a (pg/ml)
51.6F15.3 9.2F5.6 9.2F4.4 16.6F6.3 16.6F5.7 5.2F0.3 1.1+0.9 2.4F0.9
42.8F15.2 7.1F5.4 8.2F4.6 16.1F5.5 11.5F6.0 5.2F1.0 1.3F0.9 3.1F1.4
2.4 NS NS NS 3.7 NS NS 2.5
.02
.0005
.016
67
Table 4 Comparison of FAS and MTS groups with high (z40) versus low anxiety on the SAI (b40) as the grouping factor for the immunological variables (meanFS.D.) FAS
MTS
Measure
High anxiety
Low anxiety
High anxiety
Low anxiety
IL-2sRa (pg/ml) IL-4 (pg/ml) TNF-a (pg/ml)
5.2F0.3 2.1F0.9 2.8F0.7
5.2F0.3 1.9F1.2 2.9F0.8
5.0F0.4 1.6F1.0 3.0F1.3
5.2F0.8 1.3F0.3 2.6F1.1
There was a significant interaction effect between the student group and anxiety level only for TNF-a. Post hoc tests revealed a significant difference in TNF-a between high- and low-anxiety groups only for the ETS (Table 3). Table 4 shows the values for these measures for the FAS and MTS (between high- and low-anxiety groups). There were no significant differences between the high- and the lowanxiety groups for the immunological measures in FAS or MTS. Stepwise regression analyses showed that the SAI score was associated most with the emotional subscale of BAI (r=.45; P b.001), and the rest of the items did not contribute much further. Correlations in each group of students have shown that the BAI-emotional scale scores significantly correlated with the SAI scores in the ETS (r=.60; P=.00001) and the MTS (r=.48; P=.0009) groups. In the FAS group, this was not significant (r=.27).
Discussion The present study used a reliable academic examination stress model, employing scores on the SAI to evaluate the effects of stress and coping mechanisms on the immune system. The SAI scores were most significantly related to the BAI-emotional subscores in the ETS group, which was expected. The most important finding in this study is that TNF-a levels were significantly lower in the ETS group with high anxiety scores compared to those with lower scores. In the MTS group, the level of TNF-a was not significantly different between high- and low-anxiety groups. The other finding was that there was a trend toward significantly higher values of IL-4 in the FAS group compared with the other two groups. The SAI scores were higher in the ETS and MTS groups compared with the FAS group, but the two-way ANOVA did not reveal a significant group effect. The more significant positive correlation between the SAI score and the BAI-emotional score in the ETS group compared with the other groups may be due to the situation-specific anxiety, which is differentially influenced by the coping skills in different individuals. Decreased TNF-a levels during examination-induced stress in students who had higher anxiety scores in the present study are not in agreement with previous studies [6,27]. The amount of anxiety developed during examination
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directly correlated with the BAI score, suggesting that better coping skill was associated with less anxiety, as observed previously [28]. In another study, a nonacademic stressful task such as color–word interference or glass tracing was used, and there was a delayed rise in the levels of TNF-a, IL-6, and IL-1Ra following the execution of the task [6]. The anxiety in the MTS group on the whole was similar to that in the ETS group, and this could be due to the chronic nature of the stress. As the anxiety was not situation specific in this group, the TNF-a levels may not have been different between high- and low-anxiety groups. This observation suggests that TNF-a level changes could be situation specific and not just related to a particular state. Studies do demonstrate that the impact of stress generated by a situation on the response of immune system differs depending on factors like coping skill [29] and personality [17]. In contrast to other studies, the current study examined SAI scores as well as cytokine levels prior to the examination, which is associated with different degrees of anxiety, which also may have been influenced by the individual coping mechanisms. It is easy to cope with anticipated and inevitable stressors, and the impact of these stressors on the immune system may be less severe. In a rat model employing the prewarning foot shock as a stressor, immune suppression was demonstrated to be less remarkable in rats with prewarning when compared to groups that did not receive such warning [30]. Hence, late stages of stress may be associated with immune suppression, especially when the coping skills are inadequate [31,32]. The changes in immunological activities observed in earlier studies were either during or after execution of the task. This could explain why the immunological activities could have been different in the present study. Examination is an inevitable natural stressor in a student’s life. In addition, TNF-a has been demonstrated to impair the endothelial function and could trigger a series of inflammatory responses [33,34]. However, we found that students in the ETS group with higher anxiety scores and low coping skills had a significantly lower TNF-a level. As we found in this study, the response of raised TNF-a is situation specific. This finding is rather counterintuitive, and hence, we speculate that the decrease in TH-1 function in anxiety in certain situations may adversely affect the individual’s immune function. The neurotransmitter Substance P induces the synthesis of TNF and IL-1 in macrophages. IL-1 and IL-6 stimulate the synthesis of ACTH (corticotrophin) in the pituitary. Glucocorticoids, which are synthesized in response to ACTH, inhibit the synthesis of IL-6, IL-1, and TNF-a in vivo, thus establishing a negative feedback loop between the immune system and neuroendocrine functions. TNF-a, in turn, promotes thrombosis as well endothelial dysfunctions [35]. Stress can be associated with an increased cortisol level, and this may lead to decreased TNF-a level in situation-specific anxiety states. Future prospective studies should address this issue
using follow-up data, especially in relation to the outcome of the particular stressful situation as well as how well the individual copes with it at a later stage. It is also important to examine the relative changes in endocrine and immune function in different stressful situations.
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