Hormonal and immunological changes under complex stress in patients with different predominant temperamental activity

Full Text

BACKGROUND

Personalized medicine, which tailors diagnostic, therapeutic, and preventive measures to the individual patient, is currently a priority in Russia [1]. Modern personalized medicine involves genome-wide screening for disease prediction, gene therapies, gene expression modification techniques, and information analysis systems to identify individual predictors of drug therapy response [1]. Personalized medicine is only effective when the roles of biomarkers and risk factors are associated with the preferences and needs of the individual patient and their family background, personality, expectations, and doctor–patient relationship [2]. Recent studies have focused on identifying the biological mechanisms behind these factors by assessing the effect of gene polymorphisms in healthy individuals [3, 4]. However, the findings are inconsistent [5] and incomplete [3].

Personalized medicine models shift focus from treating already ill individuals to encouraging active, mindful self-management [1]. This includes the individual’s ability to deal with stress and effectively handle problems while maintaining health and fostering personal development. This ability is called coping intelligence [6]. Temperament traits, which are integral elements of a patient’s personality, are the biological foundation [7, 8] for coping intelligence, which allows for active, mindful self-management [9].

The humoral theory [10], which proposed that a temperament is determined by a combination of bodily fluids [11], was a precursor of modern concepts explaining individual differences in temperament. Ivan Sechenov established the psychophysiology of temperament [12]. Based on Sechenov’s studies, Ivan Pavlov defined temperament as a set of inherent nervous system traits (strength, balance, and mobility) that determine the organism’s interactions with the environment. Strong nervous processes are associated with quick, sustained conditioned reflexes, whereas weak nervous processes cause rapid extreme inhibition even under minor stress. The mobility of nervous processes refers to the time and rate of changes in conditioned reflexes, which are quick and easy in labile individuals and difficult in inert ones [13].

Boris Teplov described nervous system and temperament traits as speed, the ability to maintain speed, and tension. These characteristics are determined by a combination of genetic, physiological, and biochemical factors [14]. Furthermore, Vladimir Nebylitsyn defined temperament as formal–dynamic traits of the psyche determined by nervous system properties. Temperamental activity (TA) is characterized by performance (ergicity), tempo (speed), and ease of switching from one activity to another (plasticity) [15].

Several studies have shown that temperament traits (ergicity, speed, and plasticity) manifest differently in psychomotor, intellectual, and communicative activities [16, 17] and reveal different psychophysiological [18, 19] and biochemical [20–22] correlates. A neurochemical temperament model demonstrates that temperament traits that regulate psychomotor, intellectual, and communicative activities are mediated by different sets of neurotransmitters. In particular, intellectual performance is associated with acetylcholine + norepinephrine, histamine, and serotonin; communicative performance with estrogen, serotonin, histamine, and oxytocin; and psychomotor performance with serotonin, orexins, histamine, and some hypothalamic neuropeptides and hormones [23]. Temperament and psychopathology are a continuum of neurophysiological imbalances [24, 25]. Depression and post-traumatic stress disorders are associated with increased inflammatory markers [26, 27]. However, the model lacks data on immunological parameters associated with specific temperament traits and uses mental disorders as evidence base. These studies do not address other disease areas or neurophysiological imbalances resulting from stress.

Stress triggers inflammation in the central nervous and peripheral immune systems, resulting in increased IL-1β and IL-6 levels [28]. Neurocytokine mechanisms of catatoxic adaptation induce survival under extreme conditions and psychosocial stress by releasing catecholamines, IL-1, IL-4, IL-6, IL-10, adrenocorticotropic hormone, and cortisol [29]. By activating neurocytokine mechanisms, the immune system remembers stressors and provides protection against them in the future [28]. Highly sensitive individuals who struggle to cope with social isolation exhibit increased tumor necrosis factor alpha (TNF-α) and IL-6 levels [30]. Currently, there are no studies on the association between temperament traits and immune status under a complex load. There are few studies on temperament and inflammation in animals [31], and their findings are difficult to generalize to humans. Human studies primarily focused on the relationship between increased risk of diseases and specific temperament traits [32–34].

This study aimed to assess changes in hormonal and immunological parameters in individuals with different temperamental activities under a complex load.

METHODS

The study design was approved by the Local Ethics Committee of the Ural State Medical University (minutes no. 5; June 16, 2023). The study was conducted between October 2023 and July 2024 in Moscow and Yekaterinburg. Participants were informed about the scope and objectives prior to the study. The participants arrived at the laboratory by 7:30 in a fasted state and completed the following forms:

1. Questionnaire confirming the ability to participate in the study
2. Written consent for unpaid participation in the study
3. Consent for biomaterial collection
4. Consent for personal data processing.

Venous blood samples were collected at 8:00 (before complex load) and at 12:00 (after complex load).

Laboratory exercise tolerance tests were performed in the following order:

1. Psychomotor load: a cycle ergometer test for at least 5 min (maximum load: 120 W) to exhaustion
2. Intellectual load: Elementary Logical Operations test [35], Raven’s Progressive Matrices [36], and Unicube game [37]
3. Communicative load: the Rosenzweig Frustration Test [38]; discussing healthy habits and unhealthy habits, stress situations in personal/professional life in the previous 6 months, etc.

Changes in the participant’s condition were monitored using objective data (systolic and diastolic blood pressure). After complex load and repeated blood sampling, participants were fed and interviewed. The interaction between the investigator and participant lasted for 5 h.

The study included 251 participants aged 25–54 years (mean age: 36.80 ± 9.48 years); 46% of participants were males. The majority of participants (89%) were college graduates.

Inclusion criteria: age 18–55 years and no acute respiratory diseases and complaints of feeling unwell on the study day

Exclusion criteria:

• Age <18 or >55 years
• Use of oral contraceptives
• Symptoms of acute respiratory viral infection several days before the study and on the study day
• High/low blood pressure
• Speech impairment (e.g., stuttering)
• Language barrier.

Participants were recruited using snowball sampling. Almost every participant brought 1–2 acquaintances; therefore, new participants were frequently enrolled by referral.

The study sample included three groups of respondents with a predominant psychomotor, intellectual, or communicative TA, respectively. The respondents were stratified using Rusalov’s formal–dynamic individuality traits questionnaire [16]. The participants self-assessed their typical behavior in the psychomotor, intellectual, and communicative domains using a 5-point scale (1, not relevant; 5, extremely relevant).

Comparison groups were formed based on a ratio of various types of temperament activity. The group with predominant psychomotor activity (PA respondents) included participants whose need for movement significantly dominated the other two types of activity (see Table 1). The groups with predominant intellectual activity (IA respondents) and communicative activity (CA respondents) were formed in a similar manner. No significant intergroup differences were noted in age, body mass index, and waist circumference (Table 2). At this stage of the study, respondents with several types of activity that were equally prominent were excluded.

 

Table 1. Mean and standard deviation of temperamental activity parameters in respondent groups

Types of temperamental activity	Means and standard deviations of temperamental activity parameters (points) in the study groups			Kruskal–Wallis H test	p
	Respondents with predominant psychomotor activity, n = 75, 37.26 ± 8.86 years	Respondents with predominant intellectual activity, n = 59, 36.61 ± 8.23 years	Respondents with predominant communicative activity, n = 88, 35.59 ± 8.52 years
Psychomotor	21.76 ± 4.29	16.86 ± 3.94	16.81 ± 4.27	49.825	<0.001
Intellectual	16.47 ± 4.06	22.03 ± 3.88	17.50 ± 4.02	50.932	<0.001
Communicative	16.24 ± 4.51	17.29 ± 3.89	22.70 ± 3.75	76.935	<0.001

Note: Predominance of a specific activity type in the temperament is highlighted in semi-bold.

 

Table 2. Mean and standard deviation of age, body mass index, and waist circumference in respondent groups with different temperamental activity

Parameters	Means and standard deviations of parameters in the study groups			Kruskal–Wallis H test	p
	Respondents with predominant psychomotor activity, n = 75	Respondents with predominant intellectual activity, n = 59	Respondents with predominant communicative activity, n = 88
Age, years	37.26 ± 8.86	36.61 ± 8.23	35.59 ± 8.52	4.285	0.126
Body mass index, kg/m2	24.88 ± 4.63	25.09 ± 4.57	25.98 ± 16.28	1.984	0.371
Waist circumference, cm	83.38 ± 14.26	84.34 ± 20.80	80.34 ± 16.36	3.953	0.139

 

Laboratory assessments of hormonal and immunological parameter changes under a complex load included the following:

• Hormone tests [cortisol, adrenaline, norepinephrine (NE), serotonin (5-HT), and dopamine (DA)] using Abbott Architect i2000 SR (Abbott Diagnostics, USA)
• Immunology tests (IL-4, IL-6, IL-10, and TNFα) using SUNRISE (Tecan, Austria) by enzyme-linked immunosorbent assay and UniCel DXI 800 (Beckman Coulter, USA)
• Genetic tests (genotypes of polymorphic loci of the BDNF and COMT genes).

Hormonal and immunological parameters were selected based on survey studies as part of the Biochemical Correlates of Individual Differences in Coping Intelligence project [6, 9, 39]. Genetic, hormone, and immunology tests were performed at the DNKOM Laboratory (Moscow).

Subjective assessment of changes in the participant’s condition under a complex load involved the following:

• Borg Rating of Perceived Exertion scale: subjective measure of perceived exertion during physical activity (6–20 scale: 6, no exertion; 20, maximal exertion) [40]
• Leonova’s Scale of States: subjective comfort level during each test (<41, low; 41–47, below average; 48–53, acceptable; and >54, high) [41]
• Statistical analysis was performed in IBM Statistics 28 using the following methods:
• Descriptive statistics (mean, standard deviation, skewness, and kurtosis) for normality testing
• Chi-square test for independence: analysis of differences in the prevalence of genotypes of polymorphic loci of the BDNF and COMT genes
• Wilcoxon signed-rank test: comparison of two linked samples (changes in hormonal and immunological parameters before and after complex load)
• Mann–Whitney U test: comparison of two independent samples
• Kruskal–Wallis H test: identifying differences between three independent samples based on the predominant TA type
• Spearman’s correlation coefficient (rs): assessment of relationships between hormonal and immunological parameters.

The significance level (p ≤ 0.050) indicated significant intergroup differences or significant relationships between parameters.

RESULTS

Prevalence of СОМТ and BDNF genotypes based on the predominant TA type

The majority of participants in each group had the Val/Val genotype of the BDNF gene and G/A genotype of the СОМТ gene. No participants demonstrated a combination of the Met/Met genotype of the BDNF gene and A/A genotype of the СОМТ gene. No significant intergroup differences were found in the prevalence of СОМТ and BDNF genotypes (chi-square = 3.502, p = 0.478; chi-square = 5.233, p = 0.264, respectively).

Lifestyle features in respondents with different predominant TA types

CA respondents revealed more personal difficulties in the previous 6 months (e.g., death of a loved one, divorce, wedding, childbirth, etc.) than did the PA respondents (U = 2589.500; p = 0.026; 1.32 ± 0.243; 1.08 ± 0.146). CA respondents reported unhealthy habits (e.g., smoking, alcohol consumption, social media and Internet addiction, etc.) more frequently than did IA respondents (U = 1935.000; p = 0.009; 22.16 ± 5.610; 16.29 ± 5.398). Participants with a prominent, biologically driven communication need practiced unhealthy habits to relieve stress in challenging situations.

Changes in hormonal and immunological parameters before and after complex load based on the predominant TA type

All groups showed a significant decrease in cortisol levels and significant increase in NE levels (see Figs. 1а and b). There were no significant changes in adrenaline, 5-HT, and DA levels in the study groups (Figs. 1c–e).

 

Fig. 1. Hormonal changes in groups of patients before and after complex stress in respondents with predominant psychomotor activity, predominant intellectual activity, and predominant communicative activity (significant differences are indicated by asterisks: ***р < 0.001, **р < 0.01, *р < 0.05). PMA, respondents with predominant psychomotor activity; IA, respondents with predominant intellectual activity; CA, respondents with predominant communicative activity.

 

All groups exhibited a significant increase in IL-4 levels after complex load (Fig. 2). CA and IA respondents showed the most and least significant increase in IL-4 levels, respectively. Moreover, there was a significant decrease in IL-6 levels after complex load, with the most significant changes observed in PA respondents compared to CA respondents. Additionally, IL-10 levels decreased after complex load, with significant changes noted among IA and CA respondents. No significant differences were noted in TNF-α levels before and after complex load.

 

Fig. 2. Immunological changes (pg/ml) in respondent groups with predominant psychomotor activity, predominant intellectual activity, and predominant communicative activity before and after the complex stress (significant differences are indicated by asterisks: ***р < 0.001, **р < 0.01, *р < 0.05). PMA, respondents with predominant psychomotor activity; IA, respondents with predominant intellectual activity; CA, respondents with predominant communicative activity.

 

Furthermore, no significant intergroup differences were found in the psychomotor test time, systolic and diastolic blood pressure (mmHg) before and after psychomotor load, subjective comfort, and exercise tolerance.

Relationship between hormonal and immunological parameters under a complex load

In PA respondents, changes in serum cortisol levels were significantly associated with changes in NE levels (r_s = 0.318; p = 0.006) (see Fig. 3a). In IA respondents, changes in adrenaline levels were significantly associated with changes in NE (r_s = 0.382; p = 0.003) and DA levels (r_s = 0.325; p = 0.012) (Fig. 3b). In CA respondents, changes in adrenaline levels were significantly correlated with changes in NE (r_s = 0.215; p = 0.045) and cortisol levels (r_s = 0.239; p = 0.026) (Fig. 3c). The findings indicate group-specific relationships for changes in hormonal parameters:

In PA respondents, a decrease in serum cortisol levels was associated with a proportional increase in NE levels (Figs. 1а and b).

IA respondents demonstrated more complex relationships between hormonal parameters: a decrease in adrenaline levels was associated with a proportional increase in NE levels and a decrease in serum DA levels (Figs. 1b and d).

In CA respondents, minor changes in adrenaline levels were associated with a disproportional increase in NE levels and sharp decrease in cortisol levels (Figs. 1а and b).

A significant correlation between immunological parameters was only observed in PA respondents: a decrease in IL-6 was associated with a decrease in serum TNF-α levels (r_s = 0.424; p < 0.001) (Fig. 3а).

 

Fig. 3. Relationship between immunological changes (pg/ml) and hormonal changes in respondent groups with predominant psychomotor activity (а), predominant intellectual activity (b), and predominant communicative activity (c) before and after the complex stress (significant differences are indicated by asterisks: ***p < 0.001, **p < 0.01, *p < 0.05). E, epinephrine; NE, norepinephrine; S-Cort, cortisol; DA, dopamine; 5-HT, serotonin; IL-4, interleukin-4; IL-6, interleukin-6; IL-10, interleukin-10; TNFα, tumor necrosis factor.

 

A negative correlation was noted between changes in IL-6 and serotonin levels in PA respondents (r_s = −0.324, p = 0.005): the greater the increase in serotonin levels, the greater the decrease in serum IL-6 levels (Fig. 3а). Minor changes in serotonin levels in IA respondents correlated with an increase in serum IL-4 levels (r_s = 0.264; p = 0.044) (Fig. 3b). There were no significant relationships between the levels of assessed hormonal and immunological parameters in CA respondents (Fig. 3c).

DISCUSSION

Temperament is formed during life [7, 8, 16] through interactions between the individual’s morphological, biochemical, neurophysiological, and other biological systems. The findings of the present study indicate shared and specific changes in hormonal and immunological parameters under a complex load based on the predominant TA type. The study groups showed decreased cortisol levels and increased NE levels, which is consistent with exam stress studies in healthy volunteers [42].

Complex load caused an increase in IL-4 levels in all the study groups. There were specific changes in immunological parameters based on the predominant TA type; CA respondents showed a decrease in serum IL-6 and IL-10 levels, whereas PA respondents only had a decrease in IL-6 levels and CA respondents in IL-10 levels.

The dynamic interactions between cytokines, aimed at maintaining physiological balance, may be interconnected, wherein an increase or a decrease in one cytokine immediately leads to up- or downregulation of several others. Various cytokines are counterbalanced by inhibitors or other cytokines with contrary effects [43]. The effects of cytokines are systemic and can be associated with a high interindividual genetic variability of plasma cytokine levels [43] and with TA, thus determining specific, dynamic interactions of neurotransmitters in individuals with predominant psychomotor, intellectual, or CA.

Of note are intergroup differences in changes in serotonin and some interleukin levels. Complex load increased 5-HT levels and decreased IL-6 levels in PA respondents, whereas it decreased 5-HT levels and increased IL-6 levels in IA respondents. No relationships were found between the assessed hormonal and immunological parameters in CA respondents, indicating a different mechanism behind their interactions or more independent hormonal and immune systems.

The findings of the current study are unique, because this study modeled a complex load, including motor, intellectual, and communication tasks, within a single experiment and assessed hormonal and immunological parameter changes. Published studies typically addressed biochemical changes in parameters by the type of load [44] or individually for hormones [45] and interleukins [46].

Mindful self-management of health and load is associated with the patient’s coping intelligence. The body’s complex response is determined by the psychological assessment of the stressor; a negative perception may result in inhibited immune system function, whereas a positive perception promotes its activity [46]. Understanding the relationships between stress, inflammation, mental health, and behavior is crucial for the health of individual patients and groups of patients [48].

The limitations of this study may be attributed to the sample’s regional specificity (well-educated patients from Moscow and Yekaterinburg, with comparable climatic and socioeconomic conditions). Changes in hormonal and immunological parameters were compared in respondents with a single predominant TA type; however, most of the examined participants demonstrated two or more TA types that were equally prominent. Further research is required to determine whether the observed patterns are incidental or typical for apparently healthy adults and patients with various medical conditions.

CONCLUSION

This study aimed to form the basis for a hypothesis of specific changes in hormonal and immunological parameters under a complex load in patients with different predominant TA types. A significant decrease was found in serum IL-6 levels in respondents with predominant psychomotor activity. Changes in cortisol levels correlated with changes in norepinephrine levels; IL-6 levels positively correlated with changes in TNF-α levels and negatively with changes in 5-HT levels. Respondents with predominant IA showed significantly decreased IL-10 levels. Changes in adrenaline levels correlated with changes in norepinephrine and dopamine levels, whereas a decrease in 5-HT levels was significantly associated with an increase in serum IL-4 levels. Respondents with predominant CA showed a significant decrease in IL-6 and IL-10 levels. Changes in adrenaline levels correlated with changes in serum norepinephrine and cortisol levels.

ADDITIONAL INFORMATION

Author contributions: V.E.V.: conceptualization, securing funding, formal analysis, supervision, writing—original draft, writing—review & editing; K.I.O.: conceptualization, investigation, writing—review & editing; V.A.V.: investigation, formal analysis; V.N.E.: investigation, formal analysis; D.D.A.: investigation, formal analysis. All the authors approved the version of the manuscript to be published and agree to be accountable for all aspects of the work, ensuring that issues related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Ethics approval: The study was approved by the local Ethics Committee of the Ural State Medical University (Minutes No. 5 dated June 16, 2023). For the study protocol, visit https://ipran.ru/notice/ethic/.

Consent for publication: All participants provided written informed consent prior to enrollment in the study. The authors did not use any personal data in writing the manuscript; the results have been generalized.

Funding sources: The study was supported by grant No. 23-18-00293 (https://rscf.ru/project/23-18-00293/) awarded by the Russian Science Foundation.

Disclosure of interest: The authors have no relationships, activities, or interests for the last three years related to for-profit or not-for-profit third parties whose interests may be affected by the content of the article.

Statement of originality: No previously obtained or published material (text, images, or data) was used in this study or article.

Data availability statement: The data obtained in this study cannot be made publicly available under the agreement with the Russian Science Foundation.

Generative AI: No generative artificial intelligence technologies were used to prepare this article.

Provenance and peer review: This paper was submitted unsolicited and reviewed following the fast-track procedure. The peer review process involved three external reviewers, a member of the editorial board, and the in-house scientific editor.

About the authors

Elena V. Volkova

Institute of Psychology of the Russian Academy of Sciences

Email: volkovaev@ipran.ru
ORCID iD: 0000-0003-3809-3639
SPIN-code: 8375-5018

Dr. Sci. (Psychology), Chief Research Associate, Head, V.N. Druzhinin Laboratory of Psychology of Abilities and Mental Resources

Russian Federation, Moscow

Irina O. Kuvaeva

Institute of Psychology of the Russian Academy of Sciences; Ural Federal University named after the first President of Russia B.N. Yeltsin

Author for correspondence.
Email: irina.kuvaeva@urfu.ru
ORCID iD: 0000-0001-5451-0725
SPIN-code: 7244-9678

Cand. Sci. (Psychology), Research Associate, V.N. Druzhinin Laboratory of Psychology of Abilities and Mental Resources, Assistant Professor, Depart. of Developmental and Educational Psychology of the Department of Psychology

Russian Federation, Moscow; Ekaterinburg

Andrey V. Varlamov

Institute of Psychology of the Russian Academy of Sciences; Ryazan State Medical University

Email: andrey.varlamov.62@gmail.com
ORCID iD: 0000-0002-6144-6036
SPIN-code: 1397-5213

Specialist, Centre of Practical Psychology, Junior Research Associate, Druzhinin Laboratory of Psychology of Abilities and Mental Resources

Russian Federation, Moscow; Ryazan

Natalia E. Volkova

Institute of Psychology of the Russian Academy of Sciences

Email: volkovane@ipran.ru
ORCID iD: 0000-0001-6225-6288
SPIN-code: 5318-5587

Junior Research Associate, Druzhinin Laboratory of Psychology of Abilities and Mental Resources

Russian Federation, Moscow

Denis A. Dokuchaev

Institute of Psychology of the Russian Academy of Sciences

Email: dokuchaevda@ipran.ru
ORCID iD: 0000-0003-3432-0056
SPIN-code: 1257-9376

Junior Research Associate, Druzhinin Laboratory of Psychology of Abilities and Mental Resources

Russian Federation, Moscow

References

Supplementary files