The night matters: sleep quality and evening chronotype associated with clinical severity of psoriasis

Psoriasis is a chronic immune-mediated inflammatory skin disease affecting approximately 2–3% of the adult population worldwide (1). Beyond its cutaneous manifestations, psoriasis is increasingly recognized as a systemic condition associated with metabolic comorbidities, including obesity, insulin resistance, dyslipidemia, metabolic-associated fatty liver disease, and cardiovascular risk (1). Excess adiposity, particularly visceral fat accumulation, plays a key role in sustaining low-grade systemic inflammation through the release of pro-inflammatory cytokines and adipokines, thereby contributing to both the development and severity of psoriasis (2).

Sleep disturbances are common in patients with chronic inflammatory diseases, and growing evidence suggests that individuals with psoriasis experience poorer sleep quality compared with the general population (3–5). Pruritus, pain, psychological distress, and systemic inflammation may disrupt sleep architecture, leading to impaired sleep duration and efficiency (6). In turn, poor sleep quality has been linked to metabolic dysregulation, increased inflammatory burden, and exacerbation of immune-mediated diseases, suggesting a bidirectional relationship between sleep and psoriasis activity (6). However, sleep quality has often been considered in isolation, without accounting for broader circadian factors that may influence disease severity (3–5).

Chronotype, defined as an individual’s circadian preference for morning or evening activity, reflects endogenous circadian rhythms and behavioral patterns related to sleep–wake timing (7). The evening chronotype has been associated with adverse metabolic profiles, including obesity, insulin resistance, visceral adiposity, and systemic inflammation. Moreover, circadian misalignment and evening preference have been implicated in immune dysregulation and heightened inflammatory responses (7), which are central to psoriasis pathophysiology (1). Despite these mechanistic links, the role of chronotype in psoriasis has received limited attention, and its potential contribution to disease severity remains largely unexplored (8–10).

Adiposity, sleep quality, and circadian preference are closely interconnected and may synergistically influence inflammatory pathways (11). Individuals with overweight or obesity are more likely to exhibit poor sleep quality and evening chronotype, which may further aggravate metabolic dysfunction and inflammatory load (12). In the context of psoriasis, this interplay may help explain the heterogeneity in disease severity observed among patients with similar levels of adiposity. However, few studies have simultaneously examined these factors within a single analytical framework, particularly in populations at high metabolic risk.

Therefore, the present study aimed to evaluate sleep quality and chronotype in adults with psoriasis compared with healthy matched controls and to investigate their associations with psoriasis clinical severity.

Characteristics of patients with psoriasis and matched controls are shown in Table 1.

By design, sex and age did not differ between groups. Compared with controls, patients with psoriasis showed a higher prevalence of current smoking (59.2% vs 44.6%; p = 0.001). No significant differences in physical activity were observed (p = 0.606).

Patients with psoriasis had significantly higher WC (108.8 ± 18.9 vs 97.4 ± 20.5 cm; p < 0.001), CRP levels (4.1 ± 4.5 vs 1.2 ± 0.9 mg/L; p < 0.001), FLI score (69.3 ± 28.5 vs 55.7 ± 32.5 score; p < 0.001), and VAI score (3.4 ± 2.6 vs 2.3 ± 1.3 score; p < 0.001). BMI did not differ significantly between groups (p = 0.410).

Patients with psoriasis had PASI scores ranging from 0.20 to 28.0; accordingly, 143 (67.1%) had mild disease, 56 (26.3%) moderate disease, and 14 (6.6%) severe psoriasis.

Sleep characteristics and chronotype of patients with psoriasis and controls are reported in Table 2.

PSQI scores were significantly higher in patients with psoriasis compared with controls (9.3 ± 4.9 vs 6.8 ± 4.7 score; p < 0.001), reflecting poorer sleep quality. Accordingly, the proportion of good sleepers was significantly lower in patients with psoriasis (24.9% vs 48.8%; p < 0.001), while poor sleepers were more prevalent (75.1% vs 51.2%).

Patients with psoriasis had a lower MEQ score than controls (39.2 ± 19.8 vs 43.1 ± 19.2 score; p = 0.032), indicating a tendency toward an evening chronotype. However, the overall distribution of chronotype categories (morning, intermediate, and evening) did not differ significantly between patients and controls (p = 0.187).

Baseline characteristics of patients with psoriasis and controls stratified by sleep quality (PSQI score ≤ 5 vs > 5) are shown in Table 3.

Among patients with psoriasis, poor sleepers were more frequently female (48.8% vs 28.3%; p = 0.009) and current smokers (73.1% vs 17.0%; p < 0.001), less physically active (19.4% vs 60.4%; p < 0.001), and showed higher BMI (30.8 ± 5.8 vs 28.5 ± 4.8 kg/m²; p = 0.008), WC (111.9 ± 18.5 vs 99.4 ± 17.0 cm; p < 0.001), FLI score (73.8 ± 27.2 vs 55.7 ± 28.2 score; p < 0.001), and VAI score (3.8 ± 2.8 vs 2.2 ± 1.3 score; p < 0.001). Physical activity was also higher among good sleepers (60.4% vs 19.4%; p < 0.001).

Among controls, poor sleepers were older (38.0 ± 6.5 vs 34.3 ± 6.2 years; p < 0.001), more frequently current smokers (59.6% vs 28.8%; p < 0.001), less physically active (21.1% vs 44.2%; p < 0.001), and had higher BMI (34.9 ± 6.3 vs 24.3 ± 3.1 kg/m²; p < 0.001), WC (110.1 ± 18.0 vs 84.0 ± 13.0 cm; p < 0.001), FLI score (79.1 ± 21.9 vs 31.1 ± 21.8 score; p < 0.001), VAI score (2.8 ± 1.4 vs 1.8 ± 0.8 score; p < 0.001), and CRP levels (1.4 ± 0.9 vs 1.1 ± 1.0 mg/L; p = 0.035).

Characteristics of patients with psoriasis and controls stratified by chronotype are shown in Table 4.

Among patients with psoriasis, evening chronotype was associated with a higher prevalence of current smoking (90.3%; p < 0.001) and lower physical activity (15.6%; p < 0.001) compared with morning and intermediate chronotypes. Evening chronotype was also associated with higher BMI (31.4 ± 5.9 kg/m²), WC (113.3 ± 17.9 cm), CRP levels (4.8 ± 4.7 mg/L), FLI score (76.8 ± 24.9 score), and VAI score (4.0 ± 2.8 score) compared with morning chronotype (p < 0.001, Bonferroni post-hoc) and with intermediate chronotype for CRP levels, FLI score, and VAI score (p < 0.001, Bonferroni post-hoc).

Among controls, evening chronotype was similarly associated with a higher prevalence of current smoking (56.6%; p < 0.001) and lower physical activity (20.2%; p < 0.001) compared with morning and intermediate chronotypes. Post-hoc comparisons indicated significantly higher CRP levels (evening vs morning, p = 0.002), FLI score (evening vs morning and evening vs intermediate, p < 0.001), and VAI score (evening vs morning, p < 0.001) in evening chronotypes.

Figure 2 shows PASI scores in patients with psoriasis according to sleep quality and chronotype.

Poor sleepers (PSQI score > 5) had significantly higher PASI scores than good sleepers (PSQI score ≤ 5; 10.3 ± 6.5 vs 2.3 ± 1.6 score; p < 0.001).

When stratified by chronotype, evening chronotypes had the highest PASI score (11.1 ± 6.3 score), significantly higher than both morning (1.7 ± 1.1 score) and intermediate chronotypes (3.9 ± 1.2 score; both p < 0.001, Bonferroni post-hoc). No significant difference was observed between morning and intermediate chronotypes (p = 0.369).

Correlation analysis between PASI score and study parameters are shown in Table 5.

PASI score was positively correlated with BMI (r = 0.383, p < 0.001), WC (r = 0.478, p < 0.001), PSQI score (r = 0.766, p < 0.001), CRP levels (r = 0.435, p < 0.001), FLI score (r = 0.457, p < 0.001), and VAI score (r = 0.627, p < 0.001), and inversely correlated with MEQ score (r = −0.781, p < 0.001).

A stepwise multiple linear regression was performed with PASI score as the dependent variable (Table 6).

Candidate predictors included age, BMI, WC, MEQ score, PSQI score, CRP levels, FLI score, VAI score, smoking status, and physical activity. In the fully adjusted multivariable model, MEQ score, PSQI score, FLI score, VAI score, CRP levels, WC, and smoking status emerged as independent predictors of PASI score, whereas age, BMI, and physical activity were not significantly associated.

The model explained approximately 81% of the variance in PASI score (adjusted R² = 0.806). MEQ score showed the strongest independent inverse association with PASI score (p < 0.001). PSQI score (p < 0.001), VAI score (p < 0.001), CRP levels (p < 0.001), WC (p = 0.049), and smoking status (p = 0.009) were positively associated with PASI score, while FLI score showed a modest inverse association (p = 0.019).

ROC curve analysis (Figure 3) showed that a PSQI score > 10 predicted a moderate-to-severe PASI score with 75.7% sensitivity and 83.9% specificity (AUC 0.856, 95% CI 0.801–0.900, p < 0.001), while a MEQ score ≤ 25 predicted a moderate-to-severe PASI score with 98.6% sensitivity and 90.9% specificity (AUC 0.979, 95% CI 0.949–0.993, p < 0.001).

In this cross-sectional case-control study, we investigated the relationships among psoriasis clinical severity, sleep quality, chronotype, and cardiometabolic indices in a well-characterized cohort of patients with mild-to-severe psoriasis and healthy controls.

In our cohort, despite comparable BMI between groups, patients with psoriasis exhibited significantly higher waist circumference, CRP levels, FLI, and VAI scores, suggesting greater visceral adiposity and systemic inflammation compared to controls. This finding supports the notion that psoriasis is not only a skin disease but also a systemic inflammatory condition, often accompanied by metabolic dysregulation (20). The positive correlations of PASI score with WC, CRP levels, FLI, and VAI scores reinforce the link between visceral adiposity, hepatic steatosis, and disease clinical severity.

Patients with psoriasis also had significantly poorer sleep quality, as reflected by higher PSQI scores, and a tendency toward evening chronotype, with lower MEQ scores compared with controls. Correspondingly, the proportion of poor sleepers and evening chronotypes was more prevalent among patients with psoriasis. These findings suggest that sleep disturbances and an evening circadian preference are common in psoriasis and should be assessed alongside traditional metabolic risk factors. Several mechanisms may underlie these observations. Chronic systemic inflammation, characteristic of psoriasis, can disrupt circadian regulation and alter melatonin and cortisol rhythms, contributing to sleep disturbances and a preference for evening activity (21). Nocturnal symptoms such as pruritus and pain may further impair sleep (22), while metabolic dysregulation, including increased visceral adiposity, may exacerbate circadian misalignment (11). Behavioral factors, including higher prevalence of smoking and lower physical activity among evening chronotypes, may reinforce these patterns (23). Additionally, psychological stress and altered light exposure can modulate sleep–wake cycles, creating a bidirectional relationship whereby disrupted sleep may also worsen psoriatic inflammation, perpetuating a cycle of poor sleep and increased disease severity (11).

Focusing on patients with psoriasis, poor sleepers were more frequently female and current smokers and exhibited higher BMI, WC, FLI score, and VAI score compared with good sleepers, indicating that sleep disruption clusters with adverse metabolic and inflammatory profiles. Similarly, patients with an evening chronotype exhibited higher BMI, WC, CRP levels, FLI score, and VAI score compared to those with morning or intermediate chronotypes, indicating clustering of adverse metabolic and inflammatory profiles. Evening chronotype was also associated with higher prevalence of smoking and lower physical activity. These findings are in line with previous evidence showing that sleep disturbances and chronodisruption are linked to obesity, visceral adiposity, insulin resistance, dyslipidemia, and elevated inflammatory markers (12, 24, 25). Mechanistically, sleep disruption and evening chronotype can alter hypothalamic–pituitary–adrenal (HPA) axis activity (26, 27) and increase and promote pro-inflammatory cytokine release (e.g., interleukin-6, tumor necrosis factor-α, and CRP levels) (28, 29). Chronodisruption can also impair glucose and lipid metabolism, disrupt appetite regulation, and favor adiposity accumulation, collectively contributing to an adverse metabolic-inflammatory profile (30).

These sleep and circadian factors were associated with differences in clinical severity. Poor sleepers (PSQI score > 5) exhibited significantly higher PASI scores than good sleepers (PSQI score ≤ 5), while evening chronotypes had the highest PASI score, significantly exceeding both morning and intermediate chronotypes. These observations are consistent with evidence that sleep disruption and circadian misalignment are linked to systemic inflammation and immune dysregulation, key drivers of psoriasis pathophysiology (12, 29). In addition, in an experimental model of psoriasis, it has been suggested that sleep disturbance may contribute to the exacerbation of psoriasis via the dysregulation of the immune mechanisms in the epidermal barrier (31). Moreover, evening chronotypes often exhibit behavioral patterns—such as later meal timing, reduced physical activity, and higher rates of smoking—that may be associated with greater metabolic and inflammatory stress, thereby potentially contributing to greater disease severity (12).

A major finding of our study is that sleep quality and chronotype were the strongest independent variables associated with PASI score, even compared with other factors retained in the stepwise regression model, including sleep quality (PSQI score), visceral adiposity (VAI score), systemic inflammation (CRP levels), WC, and smoking. In particular, it is plausible that chronotype reflects an underlying circadian predisposition linked to physiological systems relevant to psoriasis, such as immune function, hormonal rhythms, and inflammatory cytokine secretion (7). Chronotype can be modulated by environmental and lifestyle factors but also represents a relatively stable, individual-level circadian tendency, which may exert cumulative effects on metabolic and inflammatory pathways (7). In contrast, PSQI score, VAI score, CRP levels, and WC capture specific but potentially more transient aspects of sleep quality, adiposity, and systemic inflammation, which may partly explain why their independent predictive value for PASI score was lower than that of chronotype in our cohort.

ROC curve analysis further supported the clinical relevance of these parameters. A PSQI score > 10 and a MEQ score ≤ 25 predicted moderate-to-severe PASI, confirming the potential utility of sleep and circadian metrics for clinical risk stratification. Importantly, both questionnaires are simple, non-invasive, and easy to implement in routine clinical practice (16, 17), making them practical tools for identifying patients at higher risk of severe psoriasis.

This study has several important strengths. First, it is among the first to comprehensively examine the interrelationships between psoriasis clinical severity, sleep quality, chronotype, visceral adiposity, and systemic inflammation within a single, well-characterized cohort. The integrated assessment of sleep–circadian parameters (PSQI and MEQ scores), validated surrogate indices of visceral adiposity and hepatic steatosis (VAI and FLI scores), and inflammatory markers provides a robust and clinically meaningful framework for understanding psoriasis as a systemic disorder extending beyond its cutaneous manifestations.

Second, psoriasis clinical severity was assessed using the PASI score by a qualified dermatologist, ensuring high clinical accuracy and reducing inter-observer variability. Importantly, sleep quality and chronotype questionnaires were administered by trained and qualified nutritionists rather than being self-completed by patients, minimizing reporting bias and enhancing the reliability and consistency of the collected data. This methodological approach represents a notable strength compared with many previous studies relying solely on self-reported assessments.

Third, all participants were recruited from the same geographical area (Naples, Italy), thereby sharing similar cultural, dietary, and lifestyle habits. This geographical homogeneity reduces potential confounding related to dietary patterns and environmental factors and strengthens the internal validity of the observed associations between sleep–circadian characteristics, cardiometabolic indices, and psoriasis clinical severity.

Furthermore, the inclusion of matched controls and the careful phenotyping of patients across a wide spectrum of disease clinical severity enhance the robustness of the findings. Notably, the demonstration of increased visceral adiposity and inflammatory burden in patients with psoriasis despite comparable BMI underscores the importance of using WC and adiposity indices beyond BMI alone.

The application of multivariable regression models and ROC curve analysis allowed the identification of sleep quality and chronotype as independent and clinically relevant predictors of PASI score, beyond traditional metabolic and inflammatory risk factors. The finding that chronotype emerged as the strongest independent predictor of psoriasis clinical severity is novel and carries significant translational implications. Moreover, the use of simple, non-invasive, and validated questionnaires supports the feasibility of integrating sleep and chronotype assessment into routine outpatient clinical practice.

Overall, the strengths of this study—particularly its rigorous clinical assessment, standardized data collection, geographical homogeneity, and integrated analytical approach—provide a solid foundation for the interpretation of the findings and support the need for future longitudinal and interventional studies in this emerging area.

Our study also has several limitations. First, its cross-sectional design precludes causal inference, and therefore the directionality of the associations between sleep–circadian factors and psoriasis clinical severity cannot be established. Furthermore, although ROC analysis identified specific PSQI and MEQ thresholds associated with moderate-to-severe psoriasis, these findings were derived from the same sample used to build the models and were not externally validated. As such, the reported cut-offs and their diagnostic performance may reflect cohort-specific characteristics and should be confirmed in independent populations before clinical implementation. Second, although validated questionnaires were used to assess sleep quality and chronotype, these assessments, while administered by trained nutritionists, were self-reported and may be subject to recall or reporting bias. Direct objective measures of sleep and circadian rhythms, such as actigraphy, polysomnography, or hormonal profiling, were not performed, which may limit the precision of the observed associations. Future studies incorporating objective sleep and circadian monitoring are warranted to confirm and extend our findings. Third, direct imaging-based assessment of visceral adiposity and hepatic steatosis (e.g., magnetic resonance imaging, computed tomography, or ultrasound) was not available; however, the FLI and VAI scores are widely validated surrogate markers and provide reliable estimates of metabolic risk (18, 19).

Additionally, the study population was predominantly characterized by excess body weight, with mean BMI values in the overweight/obesity range in both patients and controls, which, while enhancing relevance in metabolically high-risk populations, may limit the generalizability of the findings to lean individuals with psoriasis. Residual confounding from unmeasured lifestyle, environmental, or psychosocial factors cannot be entirely excluded, despite adjustment for major metabolic and inflammatory variables.

Moreover, the exclusion of patients with psoriatic arthritis and those receiving systemic therapies or phototherapy may limit the generalizability of our findings to these important clinical subgroups. While this approach was adopted to reduce treatment-related confounding and isolate disease-related associations, patients with joint involvement or more severe psoriasis often represent a substantial proportion of the psoriatic population. Future studies including these patients are needed to determine whether sleep quality and chronotype play a similar role in modulating disease clinical severity in the context of systemic inflammation and advanced disease.

Furthermore, psychiatric symptoms (e.g., depression, anxiety) and sleep disorders such as obstructive sleep apnea were not assessed, and their potential confounding or mediating effects on the relationships between sleep quality, chronotype, and psoriasis clinical severity cannot be excluded. Future studies should incorporate screening for mood disorders and sleep disorders to clarify the direct impact of sleep and circadian disruption on psoriasis outcomes.

Finally, while self-reported data were complemented by administration from trained nutritionists and PASI scoring by a qualified dermatologist, some measurement variability and bias inherent to questionnaire-based data collection cannot be completely ruled out.

In conclusion, this study provides the first evidence that sleep quality and chronotype are independently associated with the clinical psoriasis severity, irrespective of adiposity and traditional metabolic risk markers. Beyond their association with visceral adiposity and systemic inflammation, poor sleep quality and an evening chronotype emerged as clinical correlates of disease clinical severity, underscoring the relevance of circadian preference as a novel and clinically meaningful factor in psoriasis. These findings primarily apply to patients with psoriasis with increased adiposity and metabolic burden, and further studies are warranted to determine whether similar associations are present in lean individuals with psoriasis.

The author(s) declared that financial support was received for this work and/or its publication. The authors declare that financial support was received for the research, authorship and/or publication of this article. The research leading to these results has received funding from PRIN n.2022BASPYN.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving humans were approved by University of Naples Federico II. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

LV: Writing – review & editing, Writing – original draft. MG: Writing – review & editing. GA: Writing – review & editing. MM: Writing – review & editing. LG: Writing – review & editing. LP: Writing – review & editing. AC: Writing – review & editing, Supervision. LB: Conceptualization, Supervision, Writing – review & editing, Data curation. GM: Supervision, Conceptualization, Writing – review & editing.

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author author GM declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

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