Clinical Relevance of Platelet-Activating Factor in Chronic Spontaneous Urticaria

1. Introduction

Chronic spontaneous urticaria (CSU) is a chronic inflammatory skin disease characterized by the recurrent occurrence of pruritic wheals, angioedema, or both for at least six weeks in the absence of identifiable external triggers [1,2,3,4]. It is primarily driven by activation and degranulation of skin mast cells, leading to the release of inflammatory mediators responsible for wheal formation, angioedema, and pruritus [4].

CSU is increasingly recognized as a heterogeneous immune-mediated condition involving multiple inflammatory pathways. Skin biopsies demonstrate infiltration of mast cells, basophils, eosinophils, and T lymphocytes, along with increased expression of adhesion molecules and pro-inflammatory cytokines [3,5]. These mechanisms contribute to persistent inflammation and may explain variability in disease activity, clinical presentation, and response to therapy among patients [5,6].

Although histamine is the principal mediator of pruritus via activation of histamine H1 receptors, a substantial proportion of patients show inadequate response to antihistamine therapy, suggesting involvement of additional mediators. These include prostaglandins, leukotrienes, neuropeptides, and platelet-activating factor (PAF) [7]. This has prompted increasing interest in non-histamine pathways that may contribute to disease persistence and therapeutic refractoriness.

PAF is a potent bioactive phospholipid involved in inflammation and immune regulation [8,9]. It is produced by multiple immune cells, including mast cells, basophils, eosinophils, neutrophils, and macrophages, and exerts its effects via the platelet-activating factor receptor (PAFR), promoting leukocyte activation, mediator release, and increased vascular permeability [5,10,11]. These properties suggest that PAF may act as an amplifier of inflammatory responses in CSU [5,12].

Clinical evidence indicates that PAF may be associated with disease activity and treatment response in CSU. Elevated serum PAF levels, together with reduced activity of platelet-activating factor acetylhydrolase (PAF-AH), have been linked to increased disease severity and reduced responsiveness to antihistamine therapy [5,6,12]. Furthermore, PAF has been proposed as a potential predictor of antihistamine refractoriness [6].

Despite these observations, the clinical utility of PAF as a biomarker in CSU remains insufficiently defined. In particular, its relationship with clinical characteristics and laboratory markers of disease activity has not been fully elucidated. Given the need for reliable biomarkers to improve disease stratification and guide treatment decisions in CSU, further investigation of PAF is warranted.

This study aimed to evaluate serum PAF levels in patients with CSU and to investigate their relationship with clinical characteristics, circadian symptom patterns, laboratory and immunological markers, and treatment response.

2. Materials and Methods

2.1. Study Population

The study cohort was identified through the electronic medical records system of Pauls Stradiņš Clinical University Hospital, including patients diagnosed with CSU between January 2016 and May 2023. Additional participants were recruited from the Allergic Diseases Diagnosis and Treatment Center, a specialized referral centre for allergic diseases in Latvia.

CSU was diagnosed according to international guidelines [1,2,3,4].

Adult patients (≥18 years) were invited to participate. All participants received detailed information about the study and provided written informed consent. The study was approved by the Ethics Committee of Rīga Stradiņš University (Approval No. 2-PĒK-4/68/2023).

2.2. Clinical Data Collection

A total of 205 patients were included and evaluated by a board-certified allergologist. During study visits, participants completed validated disease-specific questionnaires, including the chronic urticaria quality of life questionnaire (CU-Q2oL), urticaria control test (UCT), urticaria activity score over 7 days (UAS7), urticaria severity score (USS), and angioedema-related instruments (AE-QoL, AAS, AECT), as well as a visual analogue scale (VAS).

Demographic and clinical data were collected, including age, sex, education, occupational status, smoking, comorbidities, disease duration, symptom distribution, disease severity, circadian variation, triggers, and treatment history.

2.3. Laboratory Data Acquisition

Laboratory test results, including leukocyte subpopulations (Leu, Neu, Ly, Mo, Eo, Ba), inflammatory markers (CRP, D-dimer, IL-6, RF, ASO, ECP), thyroid and metabolic parameters (TSH, FT4, PTH, vitamin D), immunoglobulins (IgG, IgA, IgM, IgE), complement components (C1 inhibitor concentration and activity, C3c, C4), and autoantibodies (IgG-anti-TPO, IgG-anti-TG, IgG-anti-TSH receptor, IgG-anti-C1q, IgG-anti-dsDNA, and anti-cardiolipin IgG/IgM/IgA, ANA, ENA, pANCA, and cANCA), as well as tumour markers (CA 19-9, CEA, CA15-3, CA125), were obtained from the Latvian electronic medical information system, DataMed. This system integrates laboratory and imaging data from multiple certified laboratories across the country, ensuring standardized and reliable measurements.

2.4. Sample Collection and Measurement of PAF

Venous blood samples were collected under standardized conditions. Plasma was obtained using EDTA tubes and centrifugation at 1,500 × g for 10 minutes. Samples were aliquoted and stored at −80 °C until analysis.

PAF concentrations were measured using a competitive enzyme-linked immunosorbent assay (ELISA) kit (Platelet Activating Factor ELISA Kit, Antibodies-online, Germany; catalogue no. ABIN6969371) according to the manufacturer’s instructions. Plasma samples were analysed in duplicate, and concentrations were calculated using standard curves. All measurements were performed under standardized laboratory conditions.

2.5. Measurement of HSP70 and Autoantibodies

Serum levels of HSP70 and anti-HSP70 antibodies were measured using commercially available ELISA kits (Enzo Life Sciences, USA; catalogue no. ADI-EKS-715; catalogue no. ADI-EKS-750) according to the manufacturer’s protocols.

IgG autoantibodies against FcεRIα and IgE were measured using ELISA with recombinant human antigens. Serum samples were analyzed in duplicate, and detection was performed using chemiluminescence-based methods.

2.6. Statistical Analysis

Data distribution was assessed using the Shapiro–Wilk test. Continuous variables are presented as mean ± standard deviation (SD) or median (interquartile range, IQR), as appropriate. Categorical variables are expressed as counts and percentages.

Comparisons between groups were performed using Student’s t-test or one-way ANOVA for normally distributed data, and Mann–Whitney U test or Kruskal–Wallis test for non-normally distributed data. Associations between variables were assessed using Spearman’s rank correlation. A p-value < 0.05 was considered statistically significant. All analyses were performed using Jamovi (version 2.7.5).

3. Results

3.1. Clinical and Disease Characteristics

The study included 205 patients with CSU, of whom 77.6% (n = 159) were female. The mean age was 42.6 ± 15.3 years. Detailed clinical characteristics and treatment patterns are presented in Table 1.

3.2. Disease Activity, Severity and Control

Disease activity, severity, and control were assessed using validated patient-reported outcome measures (PROMs), including VAS, UCT, UAS7, CU-Q2oL, AAS7, AECT-3mo, and AE-QoL. The results are summarized in Table 2.

Overall, the study population demonstrated a high disease burden and suboptimal disease control. Based on UCT scores, only 1.4% (n = 2) of patients had completely controlled CSU, 20.8% (n = 29) had well-controlled disease, and 76.9% (n = 107) had uncontrolled CSU.

The median UAS7 score was 14 (IQR 4–28), indicating overall moderate disease activity. While 12.1% (n = 17) of patients were urticaria-free, 28.6% (n = 40) experienced severe disease.

Among patients with angioedema, disease control was generally poor, with only four patients achieving controlled disease according to AECT-3mo.

3.3. Serum PAF Levels Across Patient Subgroups

PAF measurements were available for 171 patients included in the study. Significant differences in PAF levels were observed across circadian symptom patterns (p = 0.018, η² = 0.07) and clinical presentation (p = 0.002, η² = 0.07). Patients with symptoms predominantly during the night and early morning exhibited higher PAF levels (median 17.3 [15.8–19.2] ng/mL) compared with other circadian symptom pattern subgroups, especially patients who were asymptomatic on waking (13.1 [8.9–17.0] ng/mL) (Figure 1).

PAF levels also differed across CSU clinical presentations (p = 0.002). Patients with both urticaria and angioedema (17.2 [15.1–18.8] ng/mL) and those with angioedema only (17.1 [14.3–17.9] ng/mL) had higher PAF levels than patients with urticaria alone (14.1 [10.6–17.4] ng/mL) (Figure 2).

No significant associations were observed between PAF levels and demographic or clinical variables, including sex, place of residence, allergic comorbidity, disease-triggering factors, accompanying symptoms, or treatment effectiveness (all p > 0.05).

Comparisons of serum PAF levels across patient subgroups are presented in Table 3.

Higher levels were observed in patients with predominantly night and early morning symptoms compared with other circadian symptom pattern subgroups. Abbreviations: PAF – platelet-activating factor

Higher PAF levels were observed in patients with angioedema (alone or with urticaria) compared with those with urticaria alone. Abbreviations: PAF – platelet-activating factor, CSU – chronic spontaneous urticaria, AE – angioedema.

3.4. Correlation of PAF Levels with Clinical and Laboratory Parameters

Serum PAF levels showed significant positive correlations with age (r = 0.202, p = 0.008), age at symptom onset (r = 0.208, p = 0.007), IgG anti-IgE (r = 0.186, p = 0.015), IgM (r = 0.215, p = 0.012), HSP70 (r = 0.171, p = 0.029), and the CD4/CD8 index (r = 0.369, p < 0.001).

No significant correlations were observed with disease duration, BMI, PROMs, or other laboratory parameters (all p > 0.05).

Correlations between serum PAF levels and clinical and laboratory parameters are shown in Table 4.

4. Discussion

This study shows that circulating PAF levels are associated with clinical characteristics and selected immunological markers in CSU, supporting a role for PAF as a marker of immune activation and disease heterogeneity.

PAF is a pro-inflammatory phospholipid mediator involved in allergic inflammation and immune signaling and is produced by multiple cell types relevant to CSU pathogenesis, including mast cells and basophils [5,9,10]. Given its role in inflammatory processes, PAF has been explored as a biomarker in chronic inflammatory diseases [5,8].

CSU is a heterogeneous disease with distinct autoimmune endotypes, including type I (autoallergic) and type IIb (autoimmune) CSU, defined by different autoantibody profiles and immune mechanisms [1,3,4]. In this context, the observed correlation between PAF levels and anti-IgE IgG antibodies may suggest an association with type IIb autoimmune CSU. This interpretation is consistent with previously reported features of type IIb CSU, such as nocturnal symptoms, eosinopenia, and reduced IgA levels [13,14,15].

We also identified associations between PAF levels and IgM antibodies, HSP70, and the CD4/CD8 ratio. Although direct evidence linking these markers to PAF in CSU is limited, these findings may reflect broader immune dysregulation. IgM autoantibodies have been described in CSU, although their specificity remains unclear [13], while alterations in the CD4/CD8 ratio and increased HSP70 levels have been associated with chronic immune activation and inflammatory stress responses [14,15]. These observations support the concept that PAF may be linked to multiple overlapping immune pathways rather than a single pathogenic mechanism.

In a large study by Ulambayar et al., PAF and PAF-acetylhydrolase levels were evaluated in CSU, with no association observed with age or disease activity, although correlations with metabolic parameters and antihistamine refractoriness were reported[6]. In contrast, we observed positive associations between PAF levels and age, age at symptom onset, circadian symptom patterns, and clinical presentation, but not with antihistamine response. These differences may be explained by differences in population characteristics (e.g., demographic or clinical profiles), variations in study design and sample size, as well as underlying biological heterogeneity of CSU.

Consistent with previous reports demonstrating elevated PAF levels in CSU and in severe allergic reactions [6,16,17], we found higher PAF levels in patients with angioedema, either alone or in combination with urticaria, compared with those with urticaria alone. This pattern suggests that increased PAF levels may be associated with more severe or systemic disease manifestations. Given the established role of PAF in vascular permeability and inflammatory signaling, these findings may have implications for identifying patients who could benefit from targeted anti-PAF strategies.

Circadian variation is a recognized feature of CSU, with symptoms often worsening during the evening and night [18,19,20,21,22]. In our study, higher PAF levels were observed in patients with predominantly nocturnal and early morning symptoms, suggesting a potential contribution of PAF to circadian disease activity. Although direct evidence for circadian regulation of PAF synthesis is limited [23,24,25], indirect data suggest that PAF-related pathways may be influenced by circadian mechanisms [24,25,26]. This may reflect circadian variation in mast cell activity and mediator release, including histamine and potentially PAF, as well as fluctuations in upstream immunological processes. In addition, circadian patterns in immune regulation, including possible variation in autoantibody-mediated activation, may further contribute to the observed symptom patterns.

Despite the high disease burden observed in our cohort, PROMs did not correlate with PAF levels. This may suggest that circulating PAF reflects underlying biological activity that is not directly aligned with patients’ subjective perception of symptoms. Patient-reported outcomes are influenced by multiple factors, including symptom perception, psychological burden, and individual variability, whereas PAF may capture specific pathophysiological processes that do not translate proportionally into perceived disease severity.

Several limitations should be considered that may have influenced the observed associations. Although the overall sample size was adequate, subgroup analyses were limited by unequal group sizes and small numbers in some subgroups, which may have affected the robustness of the findings. In addition, the sex distribution was unbalanced. Some clinical data were based on patient-reported history, and not all laboratory parameters were available for all participants. PAF levels were assessed at a single time point, precluding evaluation of their temporal dynamics. PAF measurements were available for only a subset of the study population (n = 171).

5. Conclusions

Circulating PAF levels were associated with clinical phenotype, circadian symptom patterns, and selected immunological markers in CSU, suggesting a potential role for PAF in disease heterogeneity and immune activation.

Higher PAF levels in patients with predominantly night and early morning symptoms, as well as in those with angioedema, point to an association with specific clinical phenotypes rather than overall disease severity.

The absence of correlations with patient-reported outcomes suggests that PAF may reflect underlying biological processes not fully captured by subjective measures.