European Journal of Cardiovascular Medicine

The hypothalamic–pituitary–adrenal (HPA) axis plays a central role in the body’s response to stress, orchestrating a cascade of neuroendocrine signals that culminate in the secretion of cortisol from the adrenal cortex. Cortisol, the primary glucocorticoid in humans, follows a circadian rhythm, peaking shortly after waking and gradually declining throughout the day (1). This tightly regulated diurnal secretion is essential for maintaining homeostasis, modulating metabolism, immune function, and cardiovascular activity (2,3).

However, prolonged exposure to psychosocial or physiological stressors may disrupt this rhythmic pattern, leading to altered basal cortisol levels and an overall dysregulation of the HPA axis (4). Chronic stress is associated with either hyperactivation or blunted responsiveness of the HPA axis, manifesting as a flattened diurnal cortisol slope, which has been linked to various physical and mental health conditions, including cardiovascular disease, depression, and impaired cognitive function (5,6).

Beyond endocrine disruption, chronic stress exerts profound effects on the immune system. Elevated levels of pro-inflammatory cytokines such as interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and C-reactive protein (CRP) have been reported in individuals under chronic stress, suggesting a functional link between HPA axis dysregulation and immune activation (7,8). This interaction between the neuroendocrine and immune systems under stress conditions contributes to the pathogenesis of stress-related diseases, including autoimmune and inflammatory disorders (9,10).

Despite growing interest in the neuroimmune consequences of stress, few studies have concurrently evaluated cortisol rhythm disruption and inflammatory biomarkers in chronically stressed individuals. This study was designed to assess the functional status of the HPA axis by examining salivary cortisol profiles and their relationship with key immune markers in individuals experiencing chronic stress. Understanding these associations may provide deeper insights into the physiological impact of long-term stress and identify potential biomarkers for early detection and intervention.

Study Design and Participants
A total of 60 adult participants aged between 25 and 45 years were enrolled. The sample was divided into two groups: 30 individuals experiencing chronic psychological stress and 30 age- and sex-matched healthy controls. Chronic stress was defined based on scores from the Perceived Stress Scale (PSS), with a threshold score of ≥20 indicating high perceived stress levels. Participants with any known endocrine disorders, psychiatric illness, acute infections, or those on corticosteroid or immunosuppressive medications were excluded.

Assessment of Stress
Stress levels were quantified using the 10-item Perceived Stress Scale (PSS-10), a validated psychological instrument that evaluates perceived stress over the past month. Scores range from 0 to 40, with higher values indicating greater stress.

Salivary Cortisol Collection and Analysis
Participants were instructed to collect saliva samples at four predefined time points during a single day: immediately after waking (T1), 30 minutes post-waking (T2), mid-afternoon around 3:00 PM (T3), and before bedtime (T4). Saliva was collected using sterile salivette tubes under standard, non-stimulated conditions. Samples were stored at −20°C until analysis.

Cortisol levels were quantified using a commercially available enzyme-linked immunosorbent assay (ELISA) kit. All samples were analyzed in duplicate to ensure reliability. The diurnal cortisol slope was calculated by plotting cortisol values across the four time points and computing the linear regression slope.

Measurement of Immune Markers
Venous blood samples were collected from each participant in the morning between 8:00 AM and 9:00 AM after an overnight fast. Serum was separated and stored at −80°C. Levels of interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and C-reactive protein (CRP) were measured using high-sensitivity ELISA kits, following the manufacturer’s protocols.

Statistical Analysis
Descriptive data were expressed as mean ± standard deviation (SD). Between-group comparisons were performed using independent sample t-tests for normally distributed data and Mann–Whitney U tests for non-parametric data. Pearson correlation coefficients were calculated to assess relationships between cortisol slopes and immune markers. A p-value <0.05 was considered statistically significant. All analyses were conducted using SPSS software, version 25.0 (IBM Corp., Armonk, NY, USA).

Participant Characteristics
The study included 60 participants, equally divided into a chronic stress group and a healthy control group. The mean age in the stress group was 34.2 ± 5.1 years, while that in the control group was 33.6 ± 4.8 years. There was no significant difference in sex distribution or BMI between the groups (Table 1).

Table 1. Demographic and Baseline Characteristics of Study Participants

*Significant at p < 0.05

As shown in Table 1, participants in the stress group had significantly higher perceived stress scores compared to controls (p < 0.001).

Cortisol Rhythmicity
Salivary cortisol measurements across four time points revealed a blunted diurnal slope in the chronic stress group. Morning cortisol (T1) was significantly lower in the stress group (8.2 ± 1.1 ng/mL) compared to controls (13.6 ± 1.3 ng/mL; p < 0.001). The bedtime cortisol (T4) was slightly elevated in stressed participants (2.9 ± 0.5 ng/mL) versus controls (1.8 ± 0.4 ng/mL; p < 0.01), indicating impaired suppression in the evening (Table 2).

Table 2. Salivary Cortisol Levels (ng/mL) at Different Time Points

*Significant at p < 0.05

As illustrated in Table 2, the expected morning-to-evening decline in cortisol was significantly blunted in the stress group, suggesting dysregulation of the HPA axis.

Inflammatory Marker Profile
Participants with chronic stress had elevated levels of all measured immune markers compared to controls. IL-6 levels were significantly higher in the stress group (4.8 ± 0.6 pg/mL) than in controls (2.3 ± 0.4 pg/mL; p < 0.001). Similar elevations were observed for TNF-α and CRP (Table 3).

Table 3. Circulating Inflammatory Biomarkers

*Significant at p < 0.05

Correlation Analysis
Pearson’s correlation revealed a strong negative association between cortisol slope and IL-6 levels (r = −0.62, p < 0.01), as well as between cortisol slope and TNF-α (r = −0.55, p = 0.02). These findings support a direct relationship between HPA axis dysregulation and immune system activation.

This study demonstrated that individuals experiencing chronic psychological stress exhibited significant alterations in HPA axis function, as reflected by a flattened diurnal cortisol rhythm, and showed concurrent elevations in systemic inflammatory markers including IL-6, TNF-α, and CRP. These findings support the hypothesis that chronic stress disrupts the neuroendocrine–immune balance, potentially contributing to a pro-inflammatory internal environment.

The observed cortisol profiles in the stressed group deviated markedly from the typical diurnal rhythm, which is characterized by a sharp rise shortly after awakening followed by a gradual decline throughout the day (1). A blunted cortisol awakening response (CAR) and elevated evening cortisol are hallmarks of HPA axis dysregulation and have been linked to allostatic load and maladaptive stress coping mechanisms (2,3). Our findings are consistent with previous research that reported similar flattening of the cortisol slope in individuals with chronic work stress, caregiving responsibilities, and post-traumatic stress disorder (4–6).

The elevated morning and bedtime cortisol concentrations in the stress group also suggest a loss of physiological cortisol suppression, which has been implicated in reduced hippocampal feedback sensitivity to glucocorticoids (7). Such dysregulation may lead to impaired stress recovery, sleep disturbances, and metabolic dysfunction over time (8). Importantly, this disruption in HPA axis activity may not only be a marker of stress but also an active contributor to pathophysiological changes in peripheral systems.

Simultaneous elevations in IL-6, TNF-α, and CRP further highlight the inflammatory consequences of chronic stress. Numerous studies have shown that persistent activation of the HPA axis and sympathetic nervous system can result in low-grade systemic inflammation (9,10). IL-6 and TNF-α, in particular, are well-recognized mediators of immune system priming and play a role in the development of chronic diseases including cardiovascular disorders, diabetes, and depression (11,12). The strong inverse correlation between cortisol slope and these inflammatory markers in our study supports a mechanistic link between stress-related endocrine dysfunction and immune dysregulation.

Moreover, psychological stress has been shown to shift immune responses from a Th1-dominant to a Th2-dominant profile, promoting humoral over cellular immunity and increasing vulnerability to infections and inflammatory conditions (13). CRP, an acute-phase reactant regulated by IL-6, is a sensitive marker of systemic inflammation and is frequently elevated in individuals with stress-related psychiatric disorders such as major depression and anxiety (14).

Our study reinforces previous observations by suggesting that chronic stress not only alters cortisol secretion patterns but also engages immune pathways that may have downstream clinical implications. These findings underline the importance of early detection of stress-induced HPA axis alterations and advocate for integrating psychosocial interventions in clinical practice to mitigate long-term health risks (15).

Limitations of the study include its cross-sectional nature, which restricts causal interpretations. Additionally, self-reported measures of stress, although validated, are subjective. Future longitudinal studies with larger cohorts and integrated neuroimaging may help elucidate the directionality of HPA–immune interactions and identify targets for therapeutic modulation.

This study highlights the significant impact of chronic psychological stress on HPA axis dysregulation, demonstrated by a blunted diurnal cortisol rhythm and elevated inflammatory biomarkers. The strong correlation between altered cortisol patterns and immune activation suggests a bidirectional link between neuroendocrine function and systemic inflammation. Early identification and management of stress-related physiological changes may be essential in preventing long-term health consequences associated with chronic stress exposure.

1. Herman JP, McKlveen JM, Ghosal S, Kopp B, Wulsin A, Makinson R, et al. Regulation of the hypothalamic-pituitary-adrenocortical stress response. Compr Physiol. 2016 Mar 15;6(2):603–21. doi:10.1002/cphy.c150015. PMID: 27065163
2. Meaney MJ, Diorio J, Francis D, Widdowson J, LaPlante P, Caldji C, et al. Early environmental regulation of forebrain glucocorticoid receptor gene expression: implications for adrenocortical responses to stress. Dev Neurosci. 1996;18(1–2):49–72. doi:10.1159/000111395. PMID: 8840086
3. Herman JP, Nawreen N, Smail MA, Cotella EM. Brain mechanisms of HPA axis regulation: neurocircuitry and feedback in context Richard Kvetnansky lecture. Stress. 2020 Nov;23(6):617–32. doi:10.1080/10253890.2020.1859475. PMID: 33345670
4. Pacak K, Palkovits M, Kopin IJ, Goldstein DS. Stress-induced norepinephrine release in the hypothalamic paraventricular nucleus and pituitary-adrenocortical and sympathoadrenal activity: in vivo microdialysis studies. Front Neuroendocrinol. 1995 Apr;16(2):89–150. doi:10.1006/frne.1995.1004. PMID: 7621982
5. Herman JP, Prewitt CM, Cullinan WE. Neuronal circuit regulation of the hypothalamo-pituitary-adrenocortical stress axis. Crit Rev Neurobiol. 1996;10(3–4):371–94. doi:10.1615/critrevneurobiol.v10.i3-4.50. PMID: 8978987
6. Swaab DF, Bao AM, Lucassen PJ. The stress system in the human brain in depression and neurodegeneration. Ageing Res Rev. 2005 May;4(2):141–94. doi:10.1016/j.arr.2005.03.003. PMID: 15996533
7. Jankord R, Herman JP. Limbic regulation of hypothalamo-pituitary-adrenocortical function during acute and chronic stress. Ann N Y Acad Sci. 2008 Dec;1148:64–73. doi:10.1196/annals.1410.012. PMID: 19120092
8. Herman JP, McKlveen JM, Solomon MB, Carvalho-Netto E, Myers B. Neural regulation of the stress response: glucocorticoid feedback mechanisms. Braz J Med Biol Res. 2012 Apr;45(4):292–8. doi:10.1590/s0100-879x2012007500041. PMID: 22450375
9. Herman JP, Mueller NK, Figueiredo H. Role of GABA and glutamate circuitry in hypothalamo-pituitary-adrenocortical stress integration. Ann N Y Acad Sci. 2004 Jun;1018:35–45. doi:10.1196/annals.1296.004. PMID: 15240350
10. Yang Q. [Central control of the hypothalamic-pituitary-adrenocortical axis for stress response]. Sheng Li Ke Xue Jin Zhan. 2000 Jul;31(3):222–6. PMID: 12545708. Chinese.
11. Gądek-Michalska A, Tadeusz J, Rachwalska P, Bugajski J. Cytokines, prostaglandins and nitric oxide in the regulation of stress-response systems. Pharmacol Rep. 2013;65(6):1655–62. doi:10.1016/s1734-1140(13)71527-5. PMID: 24553014
12. Herman JP, Figueiredo H, Mueller NK, Ulrich-Lai Y, Ostrander MM, Choi DC, et al. Central mechanisms of stress integration: hierarchical circuitry controlling hypothalamo-pituitary-adrenocortical responsiveness. Front Neuroendocrinol. 2003 Jul;24(3):151–80. doi:10.1016/j.yfrne.2003.07.001. PMID: 14596810
13. Pacák K. Stressor-specific activation of the hypothalamic-pituitary-adrenocortical axis. Physiol Res. 2000;49 Suppl 1:S11–7. PMID: 10984067
14. Thrivikraman KV, Nemeroff CB, Plotsky PM. Sensitivity to glucocorticoid-mediated fast-feedback regulation of the hypothalamic-pituitary-adrenal axis is dependent upon stressor specific neurocircuitry. Brain Res. 2000 Jul 7;870(1–2):87–101. doi:10.1016/s0006-8993(00)02405-7. PMID: 10869505
15. Girotti M, Weinberg MS, Spencer RL. Differential responses of hypothalamus-pituitary-adrenal axis immediate early genes to corticosterone and circadian drive. Endocrinology. 2007 May;148(5):2542–52. doi:10.1210/en.2006-1304. PMID: 17303667