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EvidenceLib · Open-access article · Bones, Joints, Muscles and Skin

Circulating inflammatory cytokines and psoriasis risk: A systematic review and meta-analysis

Xiao-Qing Liu, Pei-Lin Zhou, Xin-Yu Yin, Ai-Xue Wang, Da-Hu Wang, Yun Yang, Qiang Liu, Engin Berber

PLOS ONE 2023 · doi:10.1371/journal.pone.0293327

CC BY 4.0Full textApproximately 27 min read85 references

Table of Contents

AbstractKey pointsIn this articleIntroductionMaterials and methodsResultsDiscussionKey messageSupporting informationData AvailabilityFunding StatementReferencesAssociated DataReferences

Abstract

Background

Psoriasis is a systemic immune-mediated chronic inflammatory skin disease; its systemic manifestations and periodic recurrence negatively affect a patient’s quality of life. Inflammatory cytokines are known to have an important role in the onset and progression of psoriasis, however, data on the association between circulating inflammatory cytokines and psoriasis risk is inconclusive. Here, we explore the relevance of circulating proinflammatory factors to the pathogenesis of psoriasis using a meta-analysis.

Objective

To explore the association between circulating levels of inflammatory factors and psoriasis to elucidate the mechanisms underlying psoriasis and improve clinical diagnosis and treatment.

Methods

We systematically retrieved articles published in PubMed, EMBASE, the Cochrane Library and the Web of Science from the establishment of each database to January 2023. The standard mean difference (SMD) in cytokine levels of individuals with psoriasis and healthy controls was used to check for correlations between circulating inflammatory factor levels and psoriasis.

Results

Fifty-seven studies, with data from 2838 patients, were retrieved and included in the meta-analysis. Eleven inflammatory factors were studied (circulating interleukin-2 (IL-2), IL-4, IL-12, IL-17, IL-18, IL-22, IL-23, IL-35, IL-36, transforming growth factor-beta (TGF-β) and gamma-interferon (IFN-γ)). Of these, IL-2 [SMD = 1.29 (95% CI: 0.61–1.97; P <0.001)], IL-17 [SMD = 0.71 (95% CI: 0.12–1.30; P = 0.018)], IL-18 [SMD = 1.27 (95% CI: 0.64–1.90; P <0.001)], and IFN-γ [SMD = 1.90 (95% CI: 1.27–2.52; P <0.001)] levels had significant correlations with psoriasis.

Conclusion

Increased serum concentrations of the circulating inflammatory cytokines IL-2, IL-17, IL-18 and IFN-γ were significantly correlated with psoriasis.

Key points

  • Fifty-seven studies, with data from 2838 patients, were retrieved and included in the meta-analysis.
  • Eleven inflammatory factors were studied (circulating interleukin-2 (IL-2), IL-4, IL-12, IL-17, IL-18, IL-22, IL-23, IL-35, IL-36, transforming growth factor-beta (TGF-β) and gamma-interferon (IFN-γ)).
  • 001)] levels had significant correlations with psoriasis.
  • Increased serum concentrations of the circulating inflammatory cytokines IL-2, IL-17, IL-18 and IFN-γ were significantly correlated with psoriasis.

Sentences taken unchanged from the authors’ abstract, as a reading aid. Not a new analysis and not medical advice.

In this article

  1. Introduction: Psoriasis is a skin disorder characterized by an inflammatory process mediated by immune cells. Its typical clinical manifestation includes inflammatory erythema, scales and many complications, including metabolic syndrome and cardiovascular disease [1–3].
  2. Discussion: In the complex immune system, inflammatory cytokines and their receptors constitute a comprehensive regulatory framework that can exert significant influence in the onset and progression of disease [66–68]. Inflammatory factors can thus be a crucial part of diagnosis, prognosis and therapy in autoimmune diseases [69, 70].
  3. Key message: Overall, our meta-analysis suggests that circulating inflammatory cytokine IL-2, IL-17, IL-18 and IFN-γ levels may be potent biomarkers of psoriasis in patients. Results indicate that elevated levels of circulating inflammatory cytokines IL-2, IL-17, IL-18, and IFN-γ are related to enhanced risk of psoriasis and may help to predict clinical outcomes in individuals with psoriasis.

Opening sentences of each section, unchanged.

Introduction

Psoriasis is a skin disorder characterized by an inflammatory process mediated by immune cells. Its typical clinical manifestation includes inflammatory erythema, scales and many complications, including metabolic syndrome and cardiovascular disease [1–3]. The disease often presents with systemic or widespread symptoms that are difficult to treat and adversely affect the patient’s quality of life. At present, psoriasis is thought to be caused by various types of cells (including neutrophils, dendritic cells, macrophages, T lymphocytes, mast cells and keratinocytes) and their production of circulating inflammatory factors [4–6]. The resulting circulating inflammatory factors are thought to play a central part in the pathogenesis of psoriasis, and the changes of inflammatory factors in serum are tightly associated with the occurrence of psoriatic lesions and the presence of further aggravation [7–9]. Therefore, as important mediators of psoriasis, inflammatory factors have attracted increased attention among researchers actively searching for possible treatments and diagnostic biomarkers [7, 10–12].

Previous experimental studies indicate that some circulating inflammatory factors are elevated in patients suffering from psoriasis compared to healthy controls and that these circulating inflammatory factors may be associated with the risk of psoriasis [13, 14]. However, the small sample sizes of previous studies limit confidence in this association. We thus performed a meta-analysis to gain insight into the link between circulating inflammatory factors and psoriasis risk to explore their value for treating psoriasis in clinical practice. In this study, potentially relevant circulating inflammatory factors were systematically and comprehensively tested, including serum inflammatory markers interleukin (IL)-2, IL-4, IL-18, IL-12, IL-17, IL-22, IL-23, IL-35, IL-36, gamma-interferon (IFN-γ) and transforming growth factor-beta (TGF-β) (Table 1). We used the anti-inflammatory factors IL-35 and TGF-β as controls for the generalized elevation of all factors. Our goal was to assess whether levels of systemic markers of inflammation differ in individuals with psoriasis compared to those in healthy subjects and to measure the extent of such changes, thereby providing a clinical reference for the search and clarification of new inflammatory factors.

Table 1 Role of selected circulating inflammatory factors in psoriasis.
factorsdetail
IL-2 The pro-inflammatory factor secreted by Th1 cells is a factor on which the growth and survival of T cells depend, and it can enhance the proliferation of T lymphocytes and the killing activity of NK cells [15, 16].
IL-4 It is a multifunctional and pleiotropic pro-inflammatory factor, mainly produced by activated Th2 cells, which can promote the differentiation and maturation of dendritic cells (DC) [17].
IL-12 An important pro-inflammatory factor that regulates the imbalance of Th1/Th2 ratio, can promote the differentiation of Th0 cells into Th1 cells, and induce Th1 cells to secrete IL-2 and IFN-γ [18, 19].
IL-17 The marker factor of Th17 cells is a pro-inflammatory factor, which can induce the activation of T cells and macrophages to promote inflammation. IL-17 has a synergistic effect with IL-22, and IL-17 can induce the autocrine of IL-22 [20, 21].
IL-18 The pro-inflammatory factors mainly secreted by macrophage cells activate Th1 lymphocytes and macrophages, and promote the production of IL-2, TNF-α, IFN-γ, etc. [22] to inhibit the secretion of IL-4 and IL-10. IL-18 and IL-12 have a synergistic effect and jointly induce, promote and regulate the differentiation and maturation of Th1 cells [23].
IL-22 An important immune pro-inflammatory factor mainly produced by activated Th17 cells and Th22 cells [24]. It can also be produced by Th1 cells, etc., to promote inflammation of psoriasis and thickening of the epidermis [25]. IL-22 and IL-17 synergistically promote keratinization The cells express IL-8 and CCL-20, which induce the infiltration of inflammatory cells [26].
IL-23 The pro-inflammatory factors secreted by Th17 cells enhance and maintain the activity of Th17 cells in the later stage [24]. IL-23 promotes the excessive proliferation and differentiation of keratinocytes, and promotes the secretion of IL-17 and IL-6 [27].
IL-35 The only inhibitory factor specifically produced by Treg cells [28]. Expressed rapidly in the late stage of inflammation, it is necessary for Treg cells to exert their inhibitory function, and can promote the proliferation of Treg cells and inhibit the differentiation of Th17 cells and the secretion of related factors. And can inhibit the expression of pro-inflammatory factors, significantly up-regulate the expression of IL-10 [29].
IL-36 It is a pro-inflammatory factor that can activate CD4+ T lymphocytes, dendritic cells, and keratinocytes, and induce T cell proliferation to produce circulating inflammatory factors [27, 29]. In the skin, keratinocytes are the main effector cells [30].
IFN-γ The main pro-inflammatory factor produced by Th1 cells can activate dendritic cells to produce IL-23 and stimulate Th17 cell responses to produce inflammatory factors [25].
TGF-β It is an inhibitory factor, mainly produced by Treg cells, which affects the differentiation of early Th17 cells and can weaken the proliferation of keratinocytes [31].

Materials and methods

Study registration

This research was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [32] and is registered in the PROSPERO database (CRD42023395263).

Search strategy

We conducted a systematic review of articles released since the creation of the PubMed, EMBASE, Cochrane Library and Web of Science databases up until January 2023. No restrictions were placed on language or source during the initial search of published articles. Medical Subject Headings (MeSH) together with free terms were as keywords for literature searching. the example of the PubMed search strategy, the main search terms were: "Interleukin-2" OR "Interleukin-4", "Interleukin-12" OR "Interleukin-17" OR "Interleukin-18" OR "Interleukin-22" OR "Interleukin-23" OR "Interleukin-35" OR "Interleukin-36", "Transforming Growth Factor β (TGF-β)" OR "interferon-gamma (IFN-γ)" AND "case-control work" OR "cross-sectional work" OR "cohort work" AND "psoriasis. The supplementary material provides comprehensive details of the search strategy employed. Independently manual screening and data collection by multiple researchers to ensure transparency and reproducibility of methods. This rigorous process also serves to validate the qualification of the selected documents.

Selection criteria

Literature sources for the meta-analysis had to meet the following criteria: (a) the case group was patients with clinically confirmed adult psoriasis (>18 years old) who had not received any systematic therapies for a minimum of half a month or patients with other systemic and immune diseases, The inclusion criteria did not impose any restrictions based on gender, disease severity, or medical history; the control group was healthy people without psoriasis, other systemic diseases or other skin diseases; (b) clinical case-control, cross-sectional studies or clinical cohort studies; (c) the outcome/measurement indicators were concentration or plasma level of factors in the peripheral serum of the research subjects, and data were given as mean ± standard deviation or could be converted to mean ± standard deviation; (d) where duplicate data for reports by the same author were found, the most complete and newly published research data were used.

Exclusion criteria were: (a) research measuring circulating inflammatory factors at post-treatment levels or measuring cytokines in tissues; (b) reviews, animal studies, clinical guidelines, letters to the editor, or cases report; (c) duplicate publications with similar data; (d) studies where original research data were incomplete or outcome data could not be extracted.

Data extraction

The following characteristics of each qualifying research study were noted: name of the first author, year of publication, country, number of patients and control group subjects, sex ratio, age, sample type, Psoriasis type, PASI(psoriasis area and severity index),inflammatory factor detection method and whether the inflammatory indicators are connected to psoriasis.

Quality assessment

Studies enrolled were assessed for their quality using the NIH (National Institutes of Health) [33] observational cohort and a cross-sectional research quality evaluation instrument to evaluate the quality of eligible studies. The scale was designed specifically for different studies; it primarily focuses on the internal validity of research concepts to test for flaws in research methods and implementation protocols. In all cases, quality assessments was done independently by two reviewers for each publication. Disagreements, if present, were discussed and resolved by a third investigator. The NIH total score ranges from 0 to 14 and is classified as poor (0–5), fair (6–10), or good (11–14).

Statistical analysis

The standard mean difference (SMD) in levels of circulating inflammatory factors between psoriasis patients and healthy subjects and its 95% CI were employed to describe the association between factors and psoriasis risk. The heterogeneity between studies was estimated by the Cochrane Q test and the I2 statistic (I2 = 0–25%, data are homogeneous; I2 = 25–50%, mild heterogeneity; I2 = 50–75%, moderate heterogeneity; I2 = 75–100%, high heterogeneity). We found several separate reports had medium or high levels of heterogeneity (I2 ≥50% or P ≤0.10), and thus a random-effects model was employed. When heterogeneity was large, a subgroup analysis was performed to explore underlying causes of heterogeneity and a sensitivity analysis was used to assess the usability and reliability of the results. Publishing bias was examined using Egger’s test and funnel plots. If the two-sided P-value was <0.05, the effect of the circulating proinflammatory mediators on the risk of psoriasis was considered statistically significant. The quantitative meta-analysis was performed using STATA 15.1.

Results

Characterization and quality assessment of incorporated research

The literature was searched in detail (Fig 1). During the initial searches, 3365 articles were identified according to the criteria for selection. After reviewing the titles and abstracts, 601 duplicate articles, 84 reviews, systematic reviews, animal experiments, and 2606 non-relevant papers were eliminated. Following the review of the whole text, we eliminated one review, 10 articles where the full text was not found and six articles where data were not available or were insufficient. Finally, 57 studies were included in the meta-analysis, including 2838 cases and 2283 controls. Most of the projects measured the concentration of infectious cytokines with the use of ELISA, although a few projects utilized alternative approaches. In terms of qualitative scoring, according to the NIH quality score, all 57 studies rated 7 (Table 2).

Fig 1 Preferred Report Items in Systematic Reviews and Meta-Analyses (PRISMA). (Figure not reproduced here; see the original article.)

Table 2 Global features of 57 papers on the relationship between circulating inflammatory cytokines and psoriasis risks.
First authorYearCountry/cityCasesControlsAge, years(mean±SD)Psoriasis typePASI (mean±SD)Sample typeMeasurement methodStudy typeQuality score
nPMFnCMFCasesControls
IL-2 Mannangi,N.B. [34]2022India110__110___39.4±11.13Mild: 38.8±8.5Moderate: 39.9±12.7Severe: 41.4±11.1serumELISA16
Khandpur,S. [35]2018India3018121510529.67±10.2229.42±9.8835.78±4.56serumELISA211
Takahashi,H. [36]2010Japan122814178542447.5 ± 7.638.637.3 ± 4.2serumELISA15
Kaur,S. [37]2012Tartu58352358283041.7 ± 12.041.4 ± 12.129.5±5.6serumHigh-sensitivity array18
el Barnawi, N.Y. [38]2001Benghazi25101525111433± 1231±111_serumELISA211
Choe,Y.B. [39]2012Seoul, Korea71413015__36.3±14.034.2±12.637.9±5.2serumELISA18
IL-4 Chen,J. [40]2014Shanghai1587168846.13±16.2442.31±13.6117.4 ±3.3serumELISA111
Khandpur,S. [35]2018India3018121510529.67±10.2229.42±9.8835.78±4.56serumELISA211
el Barnawi,N. Y. [38]2001Benghazi25101525111433± 1231±111_serumELISA211
Verghese,B. [41]2011India30171330__34.5 ± 13.3_3_serumELISA18
IL-12 Takahashi,H. [36]2010Japanese122814178542447.5 ± 7.638.637.3 ± 4.2serumELISA15
Michalak-Stoma,A. [42]2013Poland60501030__45.6±13.2_315.7 ± 9.7serumELISA18
Kyriakou,A. [43]2014Greece3292332__44.53±15.60_2_SerumELISA28
Arican,O. [44]2005Turkey30181223__35 ± 15.5_39.3 ± 8.15SerumELISA211
Brito-Luna,M. J. [45]2016Mexico241113146844 ± 18.0639 ± 9.442_SerumELISA111
IL-17 Elbana,A.M. [46]2022Egypt40221840172345.48±14.3540.85±13.64319.4 ± 8.11SerumELISA17
Xuan,M.L. [47]2015China62__20___37.25±12.78312.84 ± 7.60SerumELISA17
Takahashi,H. [36]2010Japan122814178542447.5 ± 7.638.637.3 ± 4.2SerumELISA15
Michalak-Stoma, A. [42]2013Poland60501030__45.6±13.2_315.7 ± 9.7SerumELISA18
Kyriakou,A. [43]2014Greece3292332__44.53±15.60_2_SerumELISA28
Fotiadou,C. [48]2015Greece3528720__47.0 ± 16.048.55±14.24216.1 ± 7.2Serumflow cytometry27
Choe,Y.B. [39]2012Korea71413015__36.3± 14.034.2±12.627.9 ± 5.2SerumELISA18
Chhabra,S. [49]2016India342772416837.5± 13.527.4± 5.524.87±3SerumELISA17
Akşan,B. [50]2022Germany1886612237613224444.08±14.1747.61 ± 12.03_SerumELISA211
Arican,O. [44]2005Turkey30181223__35 ± 15.5_29.3 ± 8.15SerumELISA110
Nassar,A.A. [51]2022Egypt40281240251542.3 ± 13.740.8 ± 11.9215.7± 10.4SerumELISA17
IL-18 Takahashi,H. [36]2010Japan122814178542447.5 ± 7.638.637.3 ± 4.2serumELISA15
Pietrzak,D. [52]2018Poland858506565047 ± 1444 ± 13317 ± 9serumELISA211
Pietrzak,A. [53]2003Poland1266105529.9± 11.2_3_serumELISA28
Gangemi,S. [54]2003Italy16106169741.75±16.5939.88± 15.53335.81±18.80serumELISA26
Arican,O. [44]2005Turkey30181223__35 ± 15.5_29.3 ± 8.15serumELISA110
IL-22 Michalak-Stoma, A. [42]2013Poland60501030__45.6±13.2_315.7 ± 9.7SerumELISA18
Fotiadou,C. [48]2015Greece3528720__47.0 ± 16.048.55±14.24216.1 ± 7.2Serumflow cytometry27
Sobhan,M. R. [55]2016Iran2821728__46.7±17.444.5±16.8310.02±7.8SerumELISA27
Hofny,E.R.M. [56]2017Egypt25__25____1_SerumELISA19
Brito-Luna,M. J. [45]2016Mexico241113146844 ± 18.0639 ± 9.442_SerumELISA111
IL-23 Michalak-Stoma, A. [42]2013Poland60501030__45.6±13.2_315.7 ± 9.7SerumELISA18
Kyriakou,A. [57]2014Greece3292332__44.53±15.60_2_SerumELISA28
Fotiadou,C. [48]2015Greece3528720__47.0 ± 16.048.55±14.24216.1 ± 7.2Serumflow cytometry27
Filiz,B. [58]2019Turkey67373067313640.55±14.8336.00±13.07310.49±1.34SerumELISA111
Chhabra,S. [49]2016India342772416837.5± 13.527.4± 5.524.87±3SerumELISA17
Brito-Luna,M. J. [45]2016Mexico241113146844 ±18.0639 ± 9.442_SerumELISA111
IL-35 Elbana,A.M. [46]2022Egypt40221840172345.48±14.3540.85±13.64319.4 ± 8.11SerumELISA17
Chen,J. [59]2021China30171330181233.24±11.8334.35±13.05110. 48 ± 3. 37SerumELISA111
IL-36 Sehat,M. [60]2022Iran47__47__33.83±11.9330.17±4.821_SerumELISA17
Chen,J. [59]2021China30171330181233.24±11.8334.35±13.08110.48±3.37SerumELISA111
IFN-γ Khandpur,S. [35]2018India3018121510529.67±10.2229.42±9.8835.78±4.56SerumELISA211
Mannangi,N. B. [34]2022India110__110___39.4±11.13_SerumELISA16
Elbana,A.M. [46]2022Egypt40221840172345.48±14.3540.85±13.64319.4 ± 8.11SerumELISA17
Arican,O. [44]2005Turkey30181223__35 ± 15.5_29.3 ± 8.15SerumELISA110
Abdallah,M. A. [61]2009Egypt21101115____325.8±15.1SerumELISA27
Mawla, M. Y. M. A. [62]2022_28151328151340.11±15.9223.29±7.61311.64±8.07SerumELISA17
el Barnawi,N. Y. [38]2001Benghazi25101525111433± 1231±111_SerumELISA211
TGF-β Ahmed, B. T. [63]2020Iraq100524850193142.4±14.846.3(±19.5)1_SerumELISA110
Elbana,A.M. [46]2022Egypt40221840172345.48±14.3540.85±13.64319.4 ± 8.11SerumELISA17
Meki, A. R. [64]2014Arabia58362222111130.17±1.40629.36±1.881_SerumELISA27
Zaher, H. [65]2009Egypt22139103747.2 ± 15.840.7 ± 9.5112.7 ± 8.4SerumELISA17

Circulatory inflammation factors and risks of psoriasis

Forest plot of the correlation between circulating inflammatory factors and the risk of psoriasis

Taking the correlation between IL-2 and the risk of psoriasis as an example, the meta-analysis uses SMD as the effect size; the Q test for heterogeneity (I2 = 93.1% >50%, P <0.001) indicates high heterogeneity among studies and thus a random effect analysis was performed. The pooled SMD from the meta-analysis was 1.29 (95% CI: 0.61–1.97; P < 0.001), showing that the levels of IL-2 in external serum were significantly greater in patients with psoriasis compared to healthy controls (Fig S1 in S1 File). Likewise, for the index of IL-17, the pooled efficacy of large and small SMD was 0.68 (95% CI: 0.14–1.23; P = 0.018), indicating that circulating IL-17 levels were slightly higher in individuals with psoriasis than in controls (Fig S2 in S1 File). Serum levels of IL-18 were provided in five studies and pooled SMD was 1.27 (95% CI: 0.64–1.90; P < 0.001), indicating elevated levels of IL-18 in peripheral blood were associated with psoriasis risk (Fig S3 in S1 File). Seven studies included data on the outcome index of IFN-γ; the SMD was 1.90 (95% CI: 1.27–2.52; P <0.001), again showing increased circulating levels of IFN-γ in psoriasis patients compared to the control groups (Fig S4 in S1 File). We found no apparent association between levels of IL-4, IL-12, IL-22, IL-23, IL-35, IL-36 and TGF-β in circulation and the risk of psoriasis. The pooled effect size for serum IL-4, IL-12, IL-22, IL-23, IL-35, IL-36, and TGF-β levels were: -0.35 (95% CI: -1.69–1.00; P = 0.612); 0.58 (95% CI: -0.15–1.32; P = 0.119), -0.07 (95% CI: -1.41–1.26; P = 0.913); -0.70 (95% CI: -1.95–0.55; P = 0.271); -2.60 (95% CI: -6.34–1.14; P = 0.172); 1.82 (95% CI: -0.56–4.20; P = 0.134); and -0.85 (95% CI:-2.45–0.76;P = 0.301), respectively.

Heterogeneity test for the association with circulating inflammatory elements and the risks of psoriasis

Since forest plots showed significant heterogeneity across all circulating inflammatory factors, meta-regression analysis was performed including age, sex, study type, number of patients groups (Cases nP), and severity of psoriasis (Table 3) to explore sources of heterogeneity. Subgroup analysis by region, measurement method, psoriasis type, and study type (Table 4) was employed to analyze sources of heterogeneity. The statistically significant and highly heterogeneous outcome indicators IL-2, 17, 18, and IFN-γ were subjected to sensitivity analysis to find the source of heterogeneity (Fig 2a–2d).

Table 3 Regression analysis of the association between circulating inflammatory cytokines and the risk of psoriasis.
Inflammmatory factorsAgeSexPASIStudy typeCases nP
P>|t|Coef [95% Coef.Interval]P>|t|Coef [95% Coef.Interval]P>|t|Coef [95% Coef.Interval]P>|t|Coef [95%Coef.Interval]P>|t|Coef [95%Coef.Interval]
IL-2 0.24-0.16(-0.59,0.26)0.480.06(-0.24, 0.36)//0.161.43(-0.88, 3.75)0.60-0.01(-0.05,0.03)
IL-4 0.910.02(-1.64, 1.68)0.43-0.13(-1.47, 1.21)//0.84-0.42(-8.26, 7.41)0.87-0.03(-0.67,0.62)
IL-12 0.970.00(-0.44, 0.45)0.98-0.00(-0.10, 0.10)//-0.47-0.34(-2.66, 1.98)0.360.01(-0.02,0.04)
IL-17 0.030.21(0.03, 0.38)0.05-0.07(-0.14, 0.00)0.36-0.06(- 0.22, 0.11)0.77-0.28(-2.38, 1.83)0.580.00(-0.01,0.02)
IL-18 0.490.04(-0.16, 0.24)0.2-0.03(-0.10, 0.04)//0.02-1.08(-1.82, -0.34)0.900.00(-0.02,0.02)
IL-22 0.58-0.62(-10.68, 9.44)0.99-0.00(-0.87, 0.87)//0.10-2.66(-6.42,1.11)0.780.02(-0.23,0.27)
IL-23 0.790.10(-1.25, 1.44)0.940.00(-0.19, 0.20)//0.640.93(-4.72,6.58)0.10-0.06(-0.14,0.02)
TGF-β 0.89-0.05(-3.77, 3.67)0.790.18(-6.31, 6.67)//0.581.80(-9.96,13.56)0.870.01(-0.18,0.20)
IFN-γ 0.480.09(-0.35, 0.53)0.770.03(-0.30, 0.36)//0.82-0.18(-2.13,1.77)0.83-0.00(-0.04,0.03)
Table 4 Subgroup analysis of the association between circulating inflammatory cytokines and psoriasis risk.
Inflammatory factorssubgroup analysisNumber of studiesI2PhSMD(95%CI)P-value
IL-2 Region
Asia492.60%0.0001.575(0.767,2.384)0.000
Other continents290.60%0.0010.711(-0.452,1.874)0.231
Method
ELISA590.10%0.0001.516(0.854,2.177)0.000
Other methods1//0.144(-0.221,-0.508)0.44
Types
Psoriasis vulgaris1//1.332(0.717,1.947)0.000
Plaque psoriasis1//0.144(-0.221,0.508)0.44
Other psoriasis types492.60%0.0001.575(0.767,2.384)0.000
Study type 1493.8%0.0000.864(0.134,1.594)0.020
Study type 2292.3%0.0002.337(0.303,4.371)0.024
IL-4 Region
Asia393.50%0.000-0.862(-2.370,0.645)0.262
Other continents1//1.178(0.576, 1.781)0.000
Method
ELISA498.20%0.000-0.348(-1.691, 0.996)0.612
Other methods0
Types
Psoriasis vulgaris292.80%0.0000.298(-1.448, 2.045)0.738
Plaque psoriasis0
Other psoriasis types296.70%0.000-1.008(-3.613, 1.597)0.448
Study type 1275.4%0.044-0.113(-0.999,0.773)0.803
Study type 2297.9%0.000-0.579(-4.042,2.884)0.743
IL-12 Region
Asia281.30%0.0211.145(0.401, 1.888)0.003
Other continents373.20%0.0240.181(-0.410,0.773)0.548
Method
ELISA597.20%0.0000.585(-0.151,1.320)0.119
Other methods0
Types
Psoriasis vulgaris
Plaque psoriasis274.80%0.0460.435(-0.406,1.276)0.311
Other psoriasis types394.90%0.0000.666(-0.434,1.766)0.236
Study type 1394.8%0.0000.719(-0.447,1.886)0.227
Study type 2269.3%0.0710.370(-0.303,1.042)0.281
IL-17 Region
Asia596.80%0.0010.520(-0.721,1.761)0.412
Other continents592.50%0.0000.883(0.238,1.528)0.007
Method
ELISA1095.00%0.0000.713(0.123,1.304)0.018
Other methods0
Types
Psoriasis vulgaris0
Plaque psoriasis50%0.8370.377(0.149,0.605)0.001
Other psoriasis types597.5%0.0001.064(-0.018,2.145)0.054
Study type 1896.0%0.0000.770(-0.096,1.636)0.081
Study type 2260.9%0.1100.554(0.154,0.953)0.007
IL-18 Region
Asia20%0.8511.775(1.479,2.071)0.000
Other continents329.80%0.240.764(0.353,1.175)0.000
Method
ELISA595.90%0.0001.269(0.637,1.901)0.000
Other methods0
Types
Psoriasis vulgaris0
Plaque psoriasis1//1.830(1.181,2.479)0.000
Other psoriasis types488.60%0.0001.133(0.404,1.862)0.002
Study type 120.0%0.8511.775(1.479,2.071)0.000
Study type 2329.8%0.2400.764(0.353,1.175)0.000
IL-22 Region
Asia1//-2.069(-2.722,-1.416)0.000
Other continents381.60.0040.587(-0.181,1.354)0.134
Method
ELISA498.50%0.000-0.075(-1.412,1.263)0.913
Other methods0
Types
Psoriasis vulgaris1//1.348(0.731,1.964)0.000
Plaque psoriasis1//-0.168(-0.828,0.492)0.618
Other psoriasis types297.60%0.000-0.743(-3.320,1.834)0.572
Study type 1381.6%0.0040.587(-0.181,1.354)0.134
Study type 21//-2.069(-2.722,-1.416)0.000
IL-23 Region
Asia298.80%0.000-1.549(-4.840,1.742)0.356
Other continents343.60%0.17-0.170(-0.571,0.231)0.406
Method
ELISA598.80%0.000-0.702(-1.953,0.548)0.271
Other methods0
Types
Psoriasis vulgaris20%0.90.109(-0.300,0.519)0.601
Plaque psoriasis1//0.040(-0.450,0.530)0.871
Other psoriasis types298.40%0.000-1.869(-4.526,0.788)0.618
Study type 1497.1%0.000-0.888(-2.441,0.665)0.262
Study type 21//0.040(-0.450,0.530)0.871
TGF-β Region
Asia288.50%0.0030.020(-0.868,0.907)0.964
Other continents298.50%0.000-1.763(-6.173,2.647)0.433
Method
ELISA499.10%0.000-0.846(-2.447,0.755)0.301
Other methods0
Types
Psoriasis vulgaris381.60%0.0040.147(-0.539,0.832)0.675
Plaque psoriasis0
Other psoriasis types1//-4.014(-4.781,-3.246)0.000
Study type 1397.6%0.000-1.304(-3.577,0.968)0.261
Study type 21//0.492(-0.005,0.989)0.052
IFN-γ Region
Asia386.40%0.0011.556(0.715–2.397)0.000
Other continents486.60%0.0002.158(1.222–3.094)0.000
Method
ELISA787.30%0.0001.897(1.275,2.519)0.000
Other methods0
Types
Psoriasis vulgaris1//1.252(0.644,1.860)0.000
Plaque psoriasis1//0.708(0.147,1.268)0.013
Other psoriasis types586.60%0.0002.281(1.532,3.030)0.000
Study type 1372.0%0.0281.780(0.983,2.577)0.000
Study type 2492.5%0.0001.981(1.009,2.953)0.000

Fig 2 Sensitivity analysis of the association between circulating inflammatory factors and psoriasis risk.Sensitivity analysis of the correlation between IL-2 and the risk of psoriasis(a). Sensitivity analysis of the correlation between IL-17 and the risk of psoriasis(b). Sensitivity analysis of the correlation between IL-18 and the risk of psoriasis(c). Sensitivity analysis of the correlation between IFN-γ and the risk of psoriasis(d). (Figure not reproduced here; see the original article.)

For regression analysis based on age, sex, study type, psoriasis severity, and number of psoriasis patients, the age of IL-17 was P = 0.03<0.05, suggesting that age may be a significant source of heterogeneity in IL-17 serum levels. The study type of IL-18 P = 0.02<0.05, indicating that the study type may be a significant source of heterogeneity in serum levels of IL-18. In the analysis of the other variables, the P values were greater than 0.05, and none of them reduced heterogeneity.

Based on subgroup analysis of psoriasis types, study types, regions, and laboratory measurements, we know that IL-17 has P = 0.001<0.05 for plaque psoriasis and P = 0.054 >0.05 for other types of psoriasis, indicating that the serum level of IL-17 in plaque psoriasis is more different than other types of psoriasis. As expected, psoriasis types further reduce heterogeneity because plaque types have higher serum concentrations compared to other types. The P values for IL-18 in Asia and elsewhere, study type 1 and study type 2 were all 0.000, indicating that there was no significant difference in serum levels of IL-18 between study types and regions. The remaining negative results did not explain the high level of heterogeneity between studies (all I2 >50%). These suggest that the type of study in the article had no significant effect on SMD for any of the inflammatory markers studied, nor did they differ significantly between studies.

The sensitivity analysis based on literature sources showed that Khandpur (2018) was the primary source of IL-2 heterogeneity, Elbana (2022) and Takahashi (2010) were the primary sources of IL-17 heterogeneity, Pietrzak (2018) was the main source of IL-18 heterogeneity, and Elbana (2022) was the main source of IFN-γ heterogeneity. Removing these sources of heterogeneity gives the forest plot shown in Fig 3. We conclude that Pietrzak (2018) is the main source of heterogeneity of the inflammatory factor IL-18, but for IL-2, IL-17 and IFN-γ significant heterogeneity remained.

Fig 3 Forest plot of publication bias test for the correlation between IL-2, IL-17, IL-18, IFN-γ and the risk of psoriasis after removing studies that may cause heterogeneity. (Figure not reproduced here; see the original article.)

Publication bias test for the association of circulating inflammatory factors with the risk of psoriasis

A meta-analysis of the association of expression levels for each inflammatory factor with the risks of psoriasis was performed to check for bias. The funnel plot and Egger test results (all P-values >0.05 for all factors) do not indicate publication bias (Table 5).

Table 5 Egger’s results of bias analysis of the association between circulating inflammatory factors and psoriasis risk.
indexstudyP>|t|[95% Conf.Interval]
IL-2 60.586-10.4615716.11826
IL-4 40.241-58.0913125.89655
IL-18 50.809-10.5851312.49414
IL-12 50.43-25.2519614.02665
IL-17 100.826-8.093256.621735
IL-22 50.459-49.1640628.48783
IL-23 60.762-48.5800161.43118
IFN-γ 70.319-4.18943610.51678
TGF-β 40.629-49.0808637.67439

The main limitations of this study were significant heterogeneity between the included studies and the authors’ different methods of expressing effect sizes. We therefore investigated publication bias to look for sources of heterogeneity. In addition, we performed sensitivity analyses, subgroup analyses, and regression analyses to locate studies that differed significantly from other studies. Finally, the age of IL-17 and the classification parameters of IL-18 study type and region can explain heterogeneity. Despite all these efforts to account for heterogeneity, heterogeneity for most inflammatory factors remained high in studies. The main reasons for this question remain differences in design and quality, measurement methods, measurement of outcome indicators, and the genetic background of participants in these studies.

Discussion

In the complex immune system, inflammatory cytokines and their receptors constitute a comprehensive regulatory framework that can exert significant influence in the onset and progression of disease [66–68]. Inflammatory factors can thus be a crucial part of diagnosis, prognosis and therapy in autoimmune diseases [69, 70]. In psoriasis, however, the relevant biomarkers remain unclear. This meta-analysis summarized and analyzed data from 57 studies to explore the association between circulating inflammatory factors and psoriasis risk. Elevated circulating levels of the inflammatory cytokines IL-2, IL-17, IL-18 and IFN-γ were statistically significantly correlated with the risk of psoriasis, while no significant correlation was found for the levels of circulating inflammatory factors IL-4, IL-12, IL-22, IL-23, IL-35, IL-36 and TGF-β.

IL-2 is a cell growth factor with various immunoregulatory functions and biological characteristics, secreted mostly by activated helper T lymphocytes [71, 72]. Elevated serum IL-2 levels are associated with significant disease progression in many autoimmune diseases and cancers, including melanoma, autoimmune hepatitis, and systemic lupus erythematosus [73, 74]. Our findings suggest that psoriasis is associated with higher IL-2 levels, possibly because IL-2 is engaged in its initiation and development [75, 76].

The role of IL-17 in autoimmune diseases has gained interest in recent years. IL-17 is mostly generated by activated Th17, which can, directly and indirectly, induce various cells to produce inflammatory cytokines and chemokines that mediate inflammatory responses [8]. Clinical studies have demonstrated that anti-IL-17 biologics (such as secukinumab and ixekizumab) can have a good curative effect on autoimmune diseases [77]. Our meta-analysis results suggest that IL-17 is linked to the risk of psoriasis and indicate that IL-17 is likely to be a biomarker for psoriasis in patients.

Previous studies have demonstrated elevated levels of circulating factor IL-18 in the serum of individuals with psoriasis. IL-18 is a complex inflammatory factor with multiple immunomodulatory effects [78]. In its own immune regulation, IL-18 is a cytokine secreted by helper T cell 1 (Th1) that then induces Th1 cells and NK cells to secrete IL-2, IFN-γ and other inflammatory factors, inhibits the production of IL-4 and IL-10, and promotes the proliferation of Th1 cells [79]. IL-18 is also implicated in the modulation of Th2 cytokines and inflammatory agents, as are IL-4 and IL-13 [54]. Further, IL-18 can be secreted by keratinocytes and is involved in psoriasis development [80], which is in line with our findings. Therefore, the function of IL-18 in psoriasis development is likely important.

IFN-γ is associated with a variety of autoimmune diseases in humans, ranging from psoriasis to systemic lupus erythematosus to rheumatoid arthritis [24]. In the pathogenesis of psoriasis, IFN-γ is the primary circulating inflammatory factor produced by Th1 cells, which inhibits the differentiation of helper T cells Th0 and Th1 into Th2 cells [25]. IFN-γ mediates the contact between T cells and keratinocytes, promotes the migration of T cells to the lesion epidermis, and promotes the proliferation of keratinocytes through the expression of anti-apoptotic proteins in psoriatic skin tissues, thereby participating in psoriasis disease pathogenesis [26, 81]. Together with our meta-analysis, these observations suggest IFN-γ may be a useful biomarker for evaluating the risk of psoriasis.

The results of this meta-analysis suggest that circulating levels of IL-2, IL-17, IL-18, and IFN-γ may serve as biomarkers of psoriasis risk. A large number of clinical and experimental studies have shown that modulated biologic drugs that block inflammatory mediators are more effective in controlling disease and reducing the risk of adverse disease in patients compared with broad-spectrum immunosuppressants. Therefore, more and more researchers are actively looking for possible biomarkers of psoriasis for treatment and diagnosis, providing more reliable strategies for the treatment of psoriasis. Existing experimental studies have shown a very significant correlation between IL-2 cytokine levels and autoimmune diseases, especially psoriasis [15, 82] Therefore, therapies based on IL-2 regulatory T cells have been proposed. There are also many cytokines that have been shown to be associated with psoriasis, such as IL-17, which is considered to be the main pathogenic regulator in the regulation of activated T cells [8]. In the current clinical application, IL-17 inhibitors (e.g., sekukizumab, eccilizumab) have a good effect on psoriasis. IL-18 has also been found to be the initiator of the cytokine cascade, and the concentration of IL-18 in serum correlates with the severity index (PASI) of psoriasis [22, 83]. Recent data suggest that IFN-γ can sustain the progression of skin diseases [84]. Moreover, it has been proposed that the IL-23/IL-17 axis, as the central mechanism of the pro-inflammatory cycle of psoriasis, may transform into a major driver of disease caused by Th1 cells and IFN-γ [85]. The evidence provided by this meta-analysis suggests that these inflammatory factors are involved in the progression of psoriasis and play an important role in it. Therefore, the results of this analysis are expected to provide a more reliable strategy for the treatment and diagnosis of targeted circulating inflammatory cytokines for psoriasis.

We do not see a statistically meaningful correlation between circulating levels of IL-4, IL-12, IL-22, IL-23, IL-35, IL-36 and TGF-β with the development of psoriasis. This result was unexpected as these circulating inflammatory factors are thought to play a part in the psoriasis cascade, which suggests their levels in psoriasis patients should deviate from normal levels. However, in our sample collections, we have observed that the degree of change in circulating inflammatory factors is often not obvious, and we suggest this is the reason for our results. Second, the amount of circulating inflammatory cytokines released is not necessarily proportional to their function. Furthermore, the finding may be attributed to the limited availability of included research on circulating inflammatory factors and the low sample sizes of individual studies. Thus, additional research with larger sample sizes is warranted to better assess the role of these cytokines and elaborate on the distinct pathogenesis of psoriasis.

Several aspects of this meta-analysis are limited and deserve additional consideration. First, the regions, populations and psoriasis types covered in this research are restricted. Second, the kits and manufacturing units used to measure inflammatory factors varied among the enrolled studies, which may add to the heterogeneity among studies. Finally, we performed preliminary sub-group analyses of the risks for various types of psoriasis but were unable to reach more comprehensive conclusions due to incomplete data in the original studies. Lastly, despite the regression and subgroup analyses we performed to investigate potential sources of heterogeneity, inflammatory factors remained highly heterogeneous.

Key message

Overall, our meta-analysis suggests that circulating inflammatory cytokine IL-2, IL-17, IL-18 and IFN-γ levels may be potent biomarkers of psoriasis in patients. Results indicate that elevated levels of circulating inflammatory cytokines IL-2, IL-17, IL-18, and IFN-γ are related to enhanced risk of psoriasis and may help to predict clinical outcomes in individuals with psoriasis. Moreover, based on the regression and subgroup analysis results of different psoriasis subtypes, different inflammatory factors may be involved in different types of psoriasis. Studying this question in depth requires research with larger sample sizes from a broad geographic and cultural area and for different types of psoriasis. Given the relatively simple method of blood sample collection and measurement, we suggest that testing of circulating inflammatory factors should be done on a broad scale and the data used for intensive research on the mechanistic action of cytokines in autoimmune diseases. This may provide new insights into ways to reduce the risk of psoriasis and offer additional indicators helpful for assessing prognosis in psoriasis patients.

Statement of ethics

The report was carried out in adherence with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) group standards for reporting meta-analysis of observational studies.

Supporting information

Data Availability

All relevant data are within the paper and its Supporting information files.

Funding Statement

The author(s) received no specific funding for this work.

References

Associated Data

Supplementary Materials

Data Availability Statement

All relevant data are within the paper and its Supporting information files.

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Attribution. Xiao-Qing Liu, Pei-Lin Zhou, Xin-Yu Yin, Ai-Xue Wang, Da-Hu Wang, Yun Yang et al.. Circulating inflammatory cytokines and psoriasis risk: A systematic review and meta-analysis. PLOS ONE (2023);18(10):e0293327. doi:10.1371/journal.pone.0293327 © 2023 Liu et al Licensed under CC BY 4.0. Reproduced from the open-access article via Europe PMC (PubMed 37883350). Text, tables and references reproduced from the open-access article; figures and images are not reproduced and no wording was changed.

About this article

Journal
PLOS ONE
Year
2023
Licence
CC BY 4.0
Source
Europe PMC
PubMed
37883350
Field
Bones, Joints, Muscles and Skin

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