Study design and patient population

We conducted a prospective, observational at the Ophthalmology Department of King Abdullah University Hospital from March 2024 to October 2024. The study adhered to the tenets of the Declaration of Helsinki and was approved by our hospital’s Institutional Review Board (IRB: 6/166/2024). Before the examination, a written consent form was obtained from each participant.

A total of 60 participants from whom hair samples were collected for this study, were recruited from our clinics and aged between 18 and 30 years, were categorized into three groups: healthy controls (n = 20), progressive keratoconus (n = 20), and stable keratoconus (n = 20).

Ethical approval was obtained from the Institutional Review Board of Jordan University of Science and Technology with the ref number (6/166/2024).

Inclusion criteria for the progressive keratoconus group were patients who were diagnosed with keratoconus and showed significant changes in corneal topographic parameters, as determined through corneal topographic analysis using a Pentacam device (Oculus Optikgeräte, Wetzlar, Germany). Significant progression of keratoconus was defined as an increase in the maximum keratometry value at the corneal apex by 1.00 diopter (D) within one year and/or a mean decrease in corneal thickness by 5% or more over the past 12 months. The stable keratoconus group included patients with keratoconus who had undergone corneal cross-linking (CXL) at least one year prior to the study and showed no progression based on the aforementioned criteria.

Participants were excluded for the following reasons: (1) the presence of other corneal pathologies, (2) a history of ocular surgery, uveitis, glaucoma, connective tissue disease, rheumatological disorders, diabetes mellitus, or psychiatric diseases, (3) a history of medications that might affect cortisol levels, including systemic corticosteroids, selective serotonin reuptake inhibitors (SSRIs), tricyclic antidepressants, anxiolytics, and inhaled corticosteroids for asthma; (4) presence of systemic disorders known to affect cortisol metabolism, such as hypertension and thyroid dysfunction (5) and pregnancy.

Hair sample collection and preparation

Hair samples were collected by trained ophthalmology residents. Each sample, consisting of 150–200 strands, was taken from the posterior vertex of the scalp, ensuring proximity to the scalp to include the proximal region. For female patients, only the proximal 3 cm of hair was retained, while for male patients, the entire strands were preserved without further cutting. Samples were stored at room temperature until analysis. Hair strands were carefully cut using sterilized surgical scissors, and approximately 35 mg of hair was weighed and transferred into a clean Eppendorf tube. To eliminate external contaminants, 1.5 mL of hexane was added to each tube, and samples were incubated at room temperature for 2 minutes. The hexane was then carefully removed, and the hair was dried under a gentle nitrogen gas stream. The dried samples were flash-frozen using liquid nitrogen to preserve integrity.

The frozen hair samples were then ground into a fine powder using a homogenizer, with 30-second pauses between cycles to prevent overheating. Subsequently, 1.8 mL of methanol was added, and the samples were thoroughly vortexed. The tubes were placed on a shaker overnight at room temperature to ensure complete cortisol extraction. The methanol extract was transferred to a clean tube and evaporated under a gentle air stream at 37°C. The remaining residue was reconstituted in 400 μL of ELISA Buffer (1X, Cat. No: 400060) and stored at −80°C until analysis.

Cortisol concentrations were quantified using an enzyme-linked immunosorbent assay (ELISA). The assay was performed with a commercially available ELISA kit (Cat. No: 500360) purchased from Cayman (Ann Arbor, Michigan, USA), following the manufacturer’s instructions.

Data collection

Demographic and clinical data were collected for demographic and clinical variables and included age, gender, body-mass index (BMI), occupational status, smoking history, and medical history. Ocular data included baseline ophthalmic assessments such as corneal topography indices (Kmax – maximum keratometry, Kmean and thinnest corneal location). For the Progressive and Stable Keratoconus groups, disease progression status and history of cross-linking procedures were also recorded. Based on existing literature, hair cortisol levels in healthy adults typically range from ~5.1–459.6 pg/mL, although values may vary depending on population differences [14]. The severity of keratoconus in each eye was classified as mild (Kmean <48), moderate (Kmean ≥48 and <53), and severe (Kmean ≥53).

Statistical analysis

To evaluate the adequacy of our sample size, we conducted an a priori power analysis using the pwr.anova.test() function in R. Based on previously reported and observed means and standard deviations of hair cortisol levels among the three groups—progressive keratoconus (M = 624 pg/mg, SD = 160), stable keratoconus (M = 368 pg/mg, SD = 64.7), and healthy controls (M = 351 pg/mg, SD = 89.6)—we calculated a large effect size (Cohen’s f = 1.36) [17]. Using this effect size, with a significance level (α) of 0.05 and a desired power (1–β) of 0.80, the estimated minimum required sample size was 3 participants per group. Our study included substantially larger group sizes, supporting the adequacy of statistical power to detect group differences in cortisol levels.

Descriptive statistics were applied to summarize demographic and clinical characteristics within each group. Continuous variables were reported as medians with interquartile ranges (IQR), while categorical variables were expressed as percentages. The normality of data distribution was assessed using the Shapiro-Wilk test. Group differences were compared using correlation coefficients and linear regression models for continuous variables. A p-value <0.05 was considered statistically significant for any exploratory analysis. Results are presented in tables and figures where appropriate.

The main findings of the study

Our study revealed significant difference in hair cortisol levels between keratoconus groups, with the higher levels observed in the progressive keratoconus (987 pg/ml) group and the lower level in stable keratoconus (300 pg/ml) This suggests that cortisol levels may play a role in distinguishing between stable and progressive cases of keratoconus. The regression model indicated a significant negative association between cortisol levels and stable keratoconus, independent of age and gender, which means lower levels of cortisol are associated with stable keratoconus. We did not observe significant associations in the progressive keratoconus group and healthy controls in the regression model after accounting for age and gender. In addition, our study revealed that corneal parameters in the more severe eye for each patient were not correlated with cortisol levels, and the severity of keratoconus was not associated with cortisol levels in both eyes.

In a prospective study by Stival et al. in Brazil investigated the differences between stable and progressive keratoconus in hair cortisol levels, showing that progressive keratoconus had a significantly higher cortisol levels compared to both stable keratoconus and healthy controls. In addition, they showed a significant correlation between cortisol levels and Kmax [21]. Previous studies have shown a potential role of systemic stress markers, including cortisol, in ocular diseases [22]. Elevated cortisol levels have been associated with oxidative stress and tissue degradation; mechanisms also observed in keratoconus pathogenesis. However, our study contrasts with prior findings by suggesting that stable keratoconus patients exhibit significantly lower cortisol levels. This discrepancy highlights the need for further research to clarify cortisol’s role and its potential as a biomarker. However, our findings were consistent with findings from Lenk et al. study showing that no difference was noted between healthy controls and stable keratoconus patients [23]. This could suggest that the association of cortisol and keratoconus is mostly associated with disease progression which was noted by the significantly higher levels in progressive keratoconus patients compared to stable keratoconus patients. In Shetty et al. study they showed that inflammatory cytokines including metalloproteinase-9, interleukin-6, and tumor necrosis factor-α were significantly overexpressed in keratoconus patients and were significantly reduced after treatment with cyclosporine A with a subsequent reduction in corneal curvature [24]. Progressive keratoconus with marked elevation of inflammatory cytokines such as hair cortisol concentration suggest that upregulation of matrix metalloproteinases produced by the corneal epithelium is a key factor responsible for collagen breakdown, therefore, higher cortisol levels correlates with higher metalloproteinases activity, thereby exacerbating the structural damage observed in progressive keratoconus patients [17]. However, the use of metalloproteinases as a biomarker might not be always feasible because its expression is not consistently continuous, making cortisol levels a more reliable biomarker for monitoring keratoconus progression.

While our study showed no difference in hair cortisol levels between progressive keratoconus and healthy controls, this could be attributed to several factors. Cortisol is a systemic stress hormone, and its levels may not fully reflect localized changes in the corneal tissue. Keratoconus progression may involve localized tissue responses that are not directly influenced by systemic cortisol levels [15]. In addition, due to the small sample size, there may be significant inter-individual variability in cortisol responses to stress, making it challenging to detect differences in small sample sizes.

The observation that stable KC patients exhibited significantly lower hair cortisol concentrations than healthy controls may be explained by a combination of biological and psychosocial mechanisms [24]. This observation could be attributed to the long-term anti-inflammatory effects of CXL, which all patients in the stable group had undergone at least one year prior to the study. Previous research has demonstrated that CXL leads to sustained suppression of pro-inflammatory cytokines such as interleukin-1β, interleukin-6, tumor necrosis factor-α, and matrix metalloproteinase-9, beginning within the first three months post-procedure and persisting beyond one year [24].

Also, demographic and psychosocial factors may have contributed to the lower HCC in the stable KC group. These patients were significantly older and more likely to be employed, which is associated with lower perceived stress and cortisol levels compared to younger individuals or students [25]. By contrast, the healthy control group included a higher proportion of university students—a population known to have elevated HCC due to academic pressure and transitional life stressors [26]. Although body mass index (BMI) was higher in the stable group, existing literature on the relationship between BMI and HCC remains inconclusive. Furthermore, while the study controlled major confounders, it did not assess hair treatment practices, ultraviolet exposure, or hair washing frequency, all of which can affect cortisol measurement accuracy. Given the wide inter-individual variability in HCC and the limited sample size, these findings should be interpreted with caution and validated in larger, longitudinal cohorts.

Clinical implications

Our results suggest that cortisol levels may serve as a potential indicator of disease stability in keratoconus patients. Monitoring cortisol levels could aid clinicians in differentiating between stable and progressive cases, improving early intervention strategies. Increased cortisol levels may contribute to the progression of keratoconus by affecting corneal thickness and biomechanics. Additionally, stress management interventions might be considered as adjunctive therapy for keratoconus management.

Strengths and limitations

A key strength of the study lies in its novel focus on cortisol levels measured from hair samples, providing long-term hormonal data rather than acute fluctuations. However, limitations include the absence of a standardized stress assessment tool (such as the Perceived Stress Scale (PSS) or the State-Trait Anxiety Inventory (STAI), which may have provided complementary information to the biological measures of stress. In addition, the Single-center design, small sample size, and the lack of longitudinal follow-up, which restricts causal inference, and might limit generalizability of our findings.

Future directions

Future studies are needed with a multi-center design, larger sample sizes and longitudinal follow-up to validate our findings. Using validated questionnaires such as the Perceived Stress Scale (PSS) or the State-Trait Anxiety Inventory (STAI), to assess stress levels at the time of the study to provide a more comprehensive analysis of this potential confounding factor. It is also crucial to investigate the molecular mechanisms linking cortisol and corneal changes could further elucidate cortisol’s role in keratoconus progression.