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Systematic Review

A systematic review and critical evaluation of inflammatory cytokine associations in hidradenitis suppurativa

[version 1; peer review: 2 approved, 1 approved with reservations]
John W. Frew
https://orcid.org/0000-0001-5042-3632
1, Jason E. Hawkes
https://orcid.org/0000-0001-5870-181X
1, James G. Krueger1
John W. Frew
https://orcid.org/0000-0001-5042-3632
1, Jason E. Hawkes
https://orcid.org/0000-0001-5870-181X
1, James G. Krueger1
PUBLISHED 13 Dec 2018
Author details Author details
OPEN PEER REVIEW
REVIEWER STATUS

Abstract

Background: The pathogenesis of hidradenitis suppurativa (HS) remains unclear. In order to develop effective treatment strategies, a deeper understanding of pathophysiology is needed. This is impaired by multiple small studies with inconsistent methodologies and the impact of co-occurring pro-inflammatory conditions such as smoking and obesity.
Methods: This systematic review aimed to collate all published reports of cytokine studies in tissue, blood, serum and exudate. It was registered with PROSPERO (Registration number CRD42018104664) performed in line with the PRISMA checklist.
Results: 19 studies were identified comprising 564 individual HS patients and 198 control patients examining 81 discrete cytokines. Methodology was highly varied and the quality of studies was generally low. There was a large degree of variance between the measured levels of cytokines. 78.2% of cytokines demonstrated heterogeneity by the chi-squared test for homogeneity and hence meta-analysis was not deemed appropriate. However, a strong and significant IL-17 signalling component was identified.
Conclusions: Cytokines consistently elevated in lesional, peri-lesional and unaffected tissue are identified and discussed. Areas for further investigation include the role of dendritic cells in HS; the contribution of obesity, smoking, diabetes and the microbiome to cytokine profiles in HS; and examining the natural history of this disease through longitudinal measurements of cytokines over time.

Keywords

Hidradenitis Suppurativa, Cytokines, Inflammation, Pathogenesis, IL-17, TNF-alpha

Corresponding author: John W. Frew
Competing interests: No competing interests were disclosed.
Grant information: Supported in part by a grant from the National Center for Advancing Translational Sciences (NCATS) [UL1 TR001866], National Institutes of Health (NIH) Clinical and Translational Science Award (CTSA) program
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Copyright:  © 2018 Frew JW et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to cite: Frew JW, Hawkes JE and Krueger JG. A systematic review and critical evaluation of inflammatory cytokine associations in hidradenitis suppurativa [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2018, 7:1930 (https://doi.org/10.12688/f1000research.17267.1) First published: 13 Dec 2018, 7:1930 (https://doi.org/10.12688/f1000research.17267.1) Latest published: 13 Dec 2018, 7:1930 (https://doi.org/10.12688/f1000research.17267.1)

Introduction

Hidradenitis Suppurativa (HS) is a chronic inflammatory disease, the exact pathophysiology of which remains poorly defined1. Dysregulation of the Th17: Treg axis2, IL-36 signalling pathways3 and keratinocyte-mediated inflammatory cytokines4 have been demonstrated in lesional skin, blood, serum, and exudate5–8 although contradictory results exist4,9. Given the variable and incomplete response of patients to treatment, including monoclonal antibodies1, some authors have proposed clinical10,11, and immunological5 subtypes of HS in an effort to better predict treatment outcome and response. Thus far, no current schema accurately predicts treatment efficacy.

In order to develop and implement effective treatment strategies in HS, a deeper understanding of the underlying inflammatory pathophysiology is needed. However, due to the heterogeneity of sampling methods, laboratory processing methods and data analysis, comparison across studies is problematic and potentially biased or inaccruate12. Heterogeneity of tissue sampling and laboratory techniques alone may explain the inconsistent and conflicting results regarding specific cytokines,4,9 however, no systematic analysis of cytokine studies has been undertaken to compare results, methodology, and analytical techniques.

An additional complicating factor is that clinical comorbidities, which are strongly associated with disease activity in HS, such as obesity13, diabetes14, inflammatory bowel disease15, and smoking16, also produce pro-inflammatory cytokines, which affect multiple organ systems including the skin15,17–19. Hence, it remains unclear whether the presence or absence of these conditions confound the findings of cytokine studies in HS, and whether clinical stratification of patients is necessary to identify significant pathogenic pathways, which may be amenable to pharmacological intervention. Critical evaluation and analysis of existing studies may also enable meta-analysis, which may identify cytokines, which, in smaller studies, do not have sufficient power to meet statistical significance when compared to controls.

Objectives

The objectives of this systematic review are:

  • 1) To collate and describe all published reports of human cytokine studies in HS including those in skin, blood, serum and exudate.

  • 2) To critically evaluate the sampling, laboratory and analysis techniques used in each study to assess whether comparisons can be made across individual studies.

  • 3) To analyze the heterogeneity of published studies enable meta-analysis

Methods

This systematic review was registered with PROSPERO20 (Registration number CRD42018104664) and was conducted in line with the PRISMA checklist21

Data sources

Information sources for this review included PubMed (1946-July 1 2018), Scopus (2004- July 1 2018) and Web of Science (1990-July 1 2018) as shown in Figure 1. Search strategy is presented in Table 1

cc04d333-0d74-4f54-9cca-1df8ff58301d_figure1.gif

Figure 1. PRISMA Flowchart.

Table 1. Search Strategy.

Resources:
1)   Pubmed (1946-July 1 2018),
2)   Scopus (2004- July 1 2018)
3)   Web of Science (1990-July 1 2018)
4)   Published Abstracts
5)   Contact with Authors for abstracts without full text for clarification of data and methodology
Pubmed Search Strategy:
acne inversa OR apocrine acne OR apocrinitis OR Fox-den disease OR hidradenitis axillaris OR HS OR
pyodermia sinifica fistulans OR Velpeau’s disease OR Verneuil’s disease OR Hidradenitidis Suppurative
AND
Cytokine OR chemokine OR inflammatory mediator

Study eligibility criteria

Eligibility criteria for this review included cohort studies, case-control studies and other observational studies with no restrictions of patient age, sex, ethnicity or language of publication. Eligible studies included:

  • 1) Studies reporting the results of cytokine investigations (in cutaneous tissue, serum, blood or exudate) in human subjects clinically diagnosed with hidradenitis suppurativa.

Studies deemed not eligible included those which:

  • 1) Provide no new data but a review or summary of previously published data

  • 2) Provide no comparison with controls or non-lesional tissue

Appraisal and synthesis methods

Data collection was performed independently by 2 authors (JWF & JEH), with any disagreements regarding inclusion of citations being referred to a third author (JGK) for mediation. Information was collected using a standardized data collection form (available as Extended data22) with the principal outcomes of interest being the cytokine of interest, measured level of cytokine in lesional HS skin or serum. Comparison data against either peri-lesional, unaffected or control skin or serum was also collated. If data from individual patients was not available then the aggregate data including average change and statistical analyses of the significance of change was collected.

For each individual cytokine, where more than one study reported results, heterogeneity was assessed using the chi-squared tests for homogeneity. Homogeneity was defined as a chi squared value >0.05. All statistical analysis was undertaken using R (version 3.5.1)

Potential sources of bias in the identified studies are acknowledged including the small size of patient cohorts, the variability in sampling, laboratory techniques and the inclusion of patients being treated with a wide-variety of medications including immunosuppressants. Bias was also assessed using the NIH quality assessment tool for observational studies23.

Results

A total of 367 non-duplicated citations were identified in the literature review (Figure 1). 343 of these articles were removed upon review of titles and abstracts against the pre-defined eligibility criteria. Full text review of the remaining 24 articles excluded 5 review articles providing no new data. The remaining 19 studies2–9,24–33 included the results of 564 individual HS patients and 198 control patients, which were included in this systematic review.

Demographics

The summarized demographic data of the patients and controls comprising this review are included in Table 2. The 564 reported cases comprised of 231 males (40.9% reported cases) and 333 females (59.0%). 24 cases were unreported (4.1%). The average age was 38.5 years (n=560, 18 cases unreported). 141 individuals were current smokers (82.4% reported cases), 8 ex-smokers (4.7% reported cases), 22 non-smokers (12.8% reported cases) and 407 unreported. Obesity (BMI>30) was reported in 85 individuals (42.5% reported cases), with 115 (57.5%) individuals non-obese (BMI<30) and unreported in 378 cases. 8 cases reported diabetes mellitus out of 24 reports (33% of reported cases). 12/38 cases reported a positive family history of HS (31.6% reported cases). Hurley Stage was reported as stage 1 in 68 individuals (17.4% reported), stage 2 in 199 individuals (51% reported cases) and stage 3 in 123 individuals (31.6% reported cases) with 188 cases going unreported. The average mHSS (modified hidradenitis suppurativa score) was 78.1 (n=247 cases). Biopsies were largely taken from the axillae (n=32, 43.8%) and groin (n=35, 48.0%), with a minority of samples being taken from the genital and perianal region (n=6, 8.2%). At the time of sampling patients were on treatment including Clindamycin+ Rifampicin (n=18); adalimumab (n=26); Metformin (n=2); levothyroxine (n=1); MABp1 (n=10); tetracyclines (n=12) Infliximab (n=2); other antibiotics (n=4). Treatment was not specified in 74 cases, with no treatment in 86 individuals and treatment withheld in 85 patients.

Table 2. Demographic data of included studies.

Number
of HS
Patients		MaleFemaleMean Age (Years)ComorbiditiesBiopsy SitesHurley
Staging		mHSS Score (Mean)TherapyStudy
Reference
SmokingObesity
(BMI>30)		DiabetesFamily
History		AxillaeGroinGenital
17145ExYNRNRSerum Measurements2NRThyroxine2
139YNNRNR2NRN
124NNNRNR2NRN
141YYNRNR2NRN
123ExYNRNR1NRN
135YYNRNR2NRN
130YNNRNR2NRMetformin
141YYNRNR3NRClindamycin, Rifampicin
135YYNRNR3NRMetformin
147YNNRNR3NRN
119NNNRNR1NRN
134YNNRNR2NRAdalimumab
147NNNRNR3NRAdalimumab, Doxycycline
132YNNRNR2NRAdalimumab
138YNNRNR3NRAdalimumab, Doxycycline
124YYNRNR2NRAdalimumab
126EYNRNR2NRAdalimumab
18117(Range 19–62)NRNRNRNRNRNRNR24
156938.7NRNRNRNRN=9N=4N=2Stage 1=0
Stage 2=10
Stage 3=5		N3
181138NYNRNNRNRNR354N4
142YNNRNNRNRNR356N
130NYNRYNRNRNR357Tetracycline
143YNNRNNRNRNR111Tetracycline
132NYNRYNRNRNR114Tetracycline
114NNNRNNRNRNR365Rifampicin, Clindamycin
147YNNRNNRNRNR344Tetracycline
143YYNRNNRNRNR322N
121YNNRNNRNRNR113Tetracycline
147NNNRNNRNRNR111Tetracycline
127YNNRNNRNRNR27Tetracycline
122NNNRYNRNRNR368N
150YNNRYNRNRNR246N
123NNNRYNRNRNR222N
119YYNRNNRNRNR226N
144YNNRYNRNRNR214N
122YNNRNNRNRNR323N
120NNNRYNRNRNR221Tetracycline
148YNNRN13NRRifampicin, Clindamycin
125YNNRN12NRAmoxicillin+ Clav Acid
120NNNRN12NRN
131NYNRN13NRAdalimumab
140NANANRNA3NRN
146YNNRN13NRTetracycline
126YNNRN12NRAzithromycin
136YNNRN12NRAmoxicillin+ Clav Acid
129NNNRy12NRAmoxicillin+ Clav Acid
2481636.5 (Range 21–51)NRNRNRNRNRNRNRMean=2.29
(SD=0.62)		NRUntreated7
74363837.4 (SD=12.0)NRN=32
(43.2%)		NRNRSerum MeasurementsStage 1= 11
Stage 2=47
Stage 3=16		All on treatment
(Not further elaborated)		8
84441.61 (SD=13.81)N=5
Y=2
Ex=1		NRN=4NRExudate MeasurementsStage 1=0
Stage 2=3
Stage 3=5		68.88 (SD=41.45)NR6
19
19		11845.6 (SD=10.7)N=14
(74%)		N=13
(68.4%)		NRNRSerum MeasurementsStage 1=0
Stage 2=9
Stage 3=10		82.79 (SD 41.0)NR25
34.5 (SD 43.5)Adalimumab
120437737.3 (SD=5.9)NRNRNRNRSerum MeasurementsStage 1=39
Stage2=52.4
Stage 3=44		28.1 (SD=20.2)
52.4 (SD=24.9)
129.3 (SD=79.2)		NR5
44133139.1 (SD=11.4)Y=34
Ex=4		N=16NRNRNRNRNRStage 1=5
Stage 2=27
Stage 3=12		NRN=15 Rifampicin,
Clindamycin
N=1 Minocycline N=2
Adalimumab
n=2 Infliximanb n=24
untreated		31
22101238.2 (Range 19-60)NRNRNRNRNRNRNRNRNRNR30
3154NRNRNRNRNRNRNRNRNRNR9
136NRNRNRNRNRNRNRNRNRNR
159NRNRNRNRNRNRNRNRNRNR
105542 (Range 21–49)NRNRNRNR11NStage 2
(100%)		NRTreatment Withheld32
2081237.5 (Range 21–51)N=18N=10NRNRNRNRNRNRNRTreatment Withheld
(8 weeks prior)		29
2591636 (Range 18–51)NRNRNRNRNRNRNRMean =2.16
(SD=0.55)		NRTreatment Withheld
(3 weeks prior)		28
47192842.3 (Range 22–54)NRSerum Measurements48.3 (Range 8–144)NR27
119239.6 (Range 18–61) NRNRNRNRNRNRNR“Mod-Severe
Disease”		NRNR
2061440 (SD=15)1927.6 (4.1)NRNR7121Stage 1=4
Stage 2=11
Stage 3=5		Treatment withheld
3 weeks prior		26
101938 (SD=15)1028.9 (SD
4.5)		NRNR370Stage1=2
Stage2=7
Stage3=1		Treatment Withheld
3 weeks prior
107346.6 (SD=15.1)1029.4 (4.7)32SerumStage 3=10195.6 (SD=97.9) MABp133
106449.3 (SD=9.8)827.9 (7.1)12Stage 2=2
Stage 3=8		124.9 (SD=73.7)No Treatment
TOTAL:
564		23133338.514185 (0f 200)8 (of 24)1232356Stage 1= 68
Stage 2=199
Stage 3=123		Average =78.1
(n=247)		Clindamycin+
Rifampicin=18;
Adalimumab=26;
Metformin=2; Treatment
withheld= 85;
Thyroxine=1; MABp1=10;
Tetracycylines=12;
No Treatment=86;
Not Specified=74;
Infliximab=2;
Antibiotics=4; Not
Reported=258

BMI= Body Mass Index mHSS= modified Hidradenitis Suppurativa Score (Sartorius Score) NR= Not Reported SD= Standard Deviation Y= Yes N=No Ex= Ex Smoker

Only 5/19 (26.3%) studies analysed both lesional tissue and serum levels of cytokines, enabling direct comparison between these two compartments. 8/19 (42.1%) studies provided age and sex matched controls, 5/15 (33.3%) studies stratified by disease severity and no studies stratified by lesion site or comorbidities. 8/19 (42.1%) studies stratified or accounted for treatment or reported discontinuing treatment up to 3 weeks prior to sample collection (Table 3).

Table 3. Critical evaluation of methodology of studies included in this review.

Cytokines MeasuredNumber
of HS
Patients		Number of
Controls		Samples
Analyzed		Age/Sex
Matched
Controls		Timing of
Samples		Stratified
by
severity		Stratified
by lesion
site		Stratified
by Co-
morbidities		Stratified by
Treatment		Sample
Storage
Time		Sample TypesStudy
Reference
IL-17 IL-22 IFNg IL-2 IL-10 GM-CSF179L, PL, U,
C, S		YNRNRNNYNRSkin, Serum2
S100A7 Lysozyme LL37 hBD3 α-MSH
MIF TNF-α IL-8 MHC1		1812LNNRNRNNNNRSkin 24
IL-36α IL-36β IL-36g1515L, PLNRNRNRNNNNRSkin 3
IL-17 IL-22 IFNg CCl20 CCL27
S100A7 S100A8 IL-1B CCL5 IP10 IL-8
IL-6 TNF-α		1818L, PL, SYNRYNNNNRSkin, Serum 4
LL37 IL-17 TNF-α IL-23 IL-1b IL-10
IL-32		249LYNRNRNRNY (untreated)NRSkin 7
IL-6 IL-23 TNF-α R1 IL-1β IL-8 IL-10
IL-12p70 IL17A TNFR2 CRP ESR		7422Serum onlyNNRYNRNNNRSerum 8
IFNg, IL-12p70,IL-1β IL-1α IL-17A
IL-6 TNF-α TNF-β IL-16 IL-12/23p40
IL-10 IL-4 IL-13 IL-2 IL-15 IL-7 IL-5
GM-CSF VEGF		88Wound
Exudate		YNRNNNNNRWound Exudate 6
IL-1B IL-6 IL-8 IL-10 IL-17A IL-23
TNFR1 TNFR2		1919Serum onlyNY
(Fasting)		NNNY (Adalimumab)NRSerum only 25
TNF-α, IL-1B, IL-6 IL-10 IL-17 IL-22
IL-1RA		12024Serum and
Pus		YNYNNY (Etanercept)NRSerum
Pus		 5
IL-17 IL-1B IL-10 TNF-α445L, PL, UNNNNNNNRSkin 31
IL-17 Caspase1 NLRP3 S100A8
S100A9		22Yes (NR)L, PL, U, CNRNRNNNNNRSkin 30
TNF-α IL-1β IL-6 IFNg IL-17A IL-223(Unknown)SYNRNNNNNRSerum 9
IL1-2p70 IL-23p19 IL-17108L, CNNRNNNY (ceased 3/25 prior)NRSkin 32
IL-32 IL-32α IL-32β IL-32d IL-32g
IFNg IL-17 IL-13		2010L, C, SNNRYNNY (ceased 8/52 prior)NRSkin, Serum 29
IL-36α IL-36β IL-36g IL-36RA257L, C, SNNRNNNY (ceased 3/25 prior)NRSkin Serum 28
TNF-α IFNg IL-1β IL-6 IL-10 IL-19,
IL-17A IL-22 IL-36b IL-12/23p40 IL-22
E Selectin P Selectin CXCL6 CXCL11
CX3CL1 CCL2 CCL18 CXCL9
sVEGFR1 MMP2 Cystatin C LCN2		1016LYNRNNNNNRSkin Serum 27
IL-1β IL-2 IL-4 IL-5 IL-6 IL-8 IL-10 IL-
12p70 TNF-α IFNg		206L, PL, CNNRYNNNNRSkin 26
IL-1α, IL-81010SNNRNNNYNRSerum 33

Table 2: Critical Evaluation of Methodology of Studies Included in This Review Key:L= Lesional, PL= Perilesional, U= Uninvolved, C= Control S=Serum, Y=Yes, N=No, NR= Not Reported,

Cytokine analysis

A total of 81 discrete cytokines were analysed over the 19 studies (presented in Table 4). 6 studies provided a total of 78 outcomes from tissue of lesional or peri-lesional biopsies, 4 studies provided a total of 30 results from serum analysis and 1 study provided 15 results from exudate analysis. The remaining 8 studies did not provide quantification of cytokine levels but did provide analysis of the change and significance between lesion and control samples. The degree of change between lesional and control samples varied widely from 1.5 times the control level (IL-1RA p=0.0112) to 149 times the control level (IL-17 p<0.05). 33 cytokines were evaluated in more than one study. Only IL-1β, IL-6, IL-8, IL-17A and TNF-α had data from 5 or more separate studies.

Table 4. Reported cytokine results of studies included in this systematic review.

Target
Cytokine		Mean Level
in Patient
Serum
(pg/mL)		Mean Level in
Control Serum
(pg/mL)		Mean Level in
Lesional Tissue
(pg/mL)		Mean Level
in
Perilesional
Tissue
(pg/mL)		Mean
Uninvolved
Tissue
Levels (pg/mL)		Mean Control
Tissue
Levels (pg/mL)		Fold
Increase		Comparison and
Significance		Comparison and
Significance
Study
Reference
IL-1α11262549Le:CeP= 0.536
0.20.1NRL:CNS26
772.0697.2HSs:CsNS33
IL-1RA44.029.61.5L:CP= 0.011226
IL-1β0.90.4HSs:CsP=0.8018
862.51503Le:CeP= 0.696
L:CNSLpa:CNS25
SERUM ONLYHSs:CsP= 0.0445
100103 1115 foldL:CP= 0.001PL:C0.0531
L:UP= 0.01U:CNS
R=0.7# L:CNS7
1.60.054.4L:CP= 0.002826
IL-46.569.77Le:CeP= 0.546
0.00.1L:CNS7
IL-50.20.2L:CNS7
30.159.314Le:CeP= 0.176
IL-6L:C*
L:C**
L:C***		NS
NS
NS		4
6.20.6HSs:CsP= 0.0018
23775451Le:CeNS6
L:CP= 0.05Lpa:C0.0525
SERUM ONLYHSs:
Cs+++		P= 0.0025
124.4101.9L:CNS7
sIL-6R16.34.43.7L:CP= 0.00287
IL-8NRNRi69.6 / s67.664.9Li:CP<0.01Ls:CP<0.00124
L:C*
L:C**
L:C***		NS
NS
NS		4
27.936.3HSs:CsNS8
L:CP= 0.05Lpa:CNS25
140112.0L:CNS7
10003000L:CP= 0.04933
IL-10L:CP<0.054
3.43.3HSs:CsNS8
19.8534.74Le:CeNS6
L:CP= 0.05Lpa:C0.0525
SERUM ONLYHSs:Cs+P= 0.00015
SERUM ONLYHSs:Cs++P= 0.00015
3.81.10.4 3-4L:CP= 0.01PL:CNS31
L:UP= 0.01U:CNR
32HSs:CsNS27
19.21.314.8L:CP= 0.00287
IL-1178.67.211.0L:CP= 0.00567
IL-12p40488.397.86Le:CeP= 0.076
7575HSs:CsNS27
0.50.4L:CNS7
IL-12p703.40.6HSs:CsP= 0.4278
9.41215.02Le:CeP= 0.6096
0.00.0L:CNS7
IL-1370.9855.61Le:CeP= 0.566
0.00.1L:CNS7
IL-1524.55.61Le:CeP= 0.186
1.92.9L:CNS7
IL-161527715586Le:CeP= 0.976
22.34.25.3L:CP= 0.00287
IL-17S:CP<0.0054
SERUM
ONLY		SERUM ONLYSERUM
ONLY		HSs:Cs+0.0145
SERUM
ONLY		SERUM ONLYSERUM
ONLY		HSs:Cs++0.0055
150451 1149 foldL:CP= 0.05PL:C0.0531
L:PLNSU:C0.05
No QuantificationL:C↑(NS)L:PLNo Diff30
R=0.66#NS27
IL-17AL:CP<0.0054
5.60.3HSs:CsNS8
100632.7Le:CeNS6
L:CP= 0.05Lpa:CNS25
45HSs:CsNS27
8.1NR1.17.3L:CP= 0.005626
IL-22L:CNS4
8.80.0HSs:CsNS8
IL-23L:CNSLpa:C0.0525
R=0.68#NS7
IL-3250ng/mL1ng/mLOnly Normalised Values Provided4 (skin)
50
(serum) 		L:CP= 0.01HSs:
Cs		p<0.0529
IL-32α3 foldL:CP= 0.0129
IL-32β2 foldL:CP= 0.0529
IL-32gNot
elevated		L:CP= 0.00129
IL-32d3 foldL:CNS29
IL-36α0.40.020.02L:CP=0.0174PL:CNS3
2500145.07 foldL:CP= 0.0128
IL-36b4.333.000.51L:CP= 0.0001PL:C0.00353
15411.45 foldL:CP= 0.2528
IL-36g3.640.830.49L:CP= 0.0161PL:L0.03023
1002011.96 foldL:CP= 0.0728
IL-36RA0.460.280.06L:CP= 0.0001PL:C0.00033
50100No QuantificaitonNo
Increase		L:CP= 0.1028
IL-373.2414.71.81PL:LP= 0.0002PL:C0.00013
IL-380.090.190.06L:CP= 0.0230PL:C0.00693
TNF-αi69.466.6sNR65.8NRLi:CNSLs:CNS24
L:C*
L:C**
L:C***		NS
NS
NS		4
83.2665.74Le:CeP= 0.76
SERUM ONLYSERUM
ONLY		HSs:Cs+P=0.0215
2.21.30.60.7L:CP=0.01PL:C0.0131
L:PLNSU:CNS
0.30.21.6L:CP=0.033626
TNF-β9.241.65Le:CeP=0.036
0.40.4NRL:CNS26
sTNFR1879.8325.9HSs:CsP <0.0018
L:CNSLpa:C0.0525
78.040.21.9L:CP= 0.011226
sTNFR2927.9527.4HSs:CsP= 0.0538
L:CP= 0.05Lpa:C0.0525
47.08.15.8L:CP= 0.002826
hBD10.019
0.021
0.018		0.058
0.077
0.095		0.3
0.3
0.2		L:C*
L:C**
L:C***		P= 0.240
P= 0.132
P= 0.026		4
hBD20.013
0.019
0.058		0.011
0.018
0.067		1.1
1.1
0.9		L:C*
>L:C**
L:C***		P= 0.937
P= 0.699
P= 0.937		4
hBD376.9i75.7s72.5NRLi:CP<0.05Ls:CNS24
0.33
0.33
0.379		0.117
0.125
0.203		2.8
2.6
1.9		L:C*
L:C**
L:C***		P= 0.485
P= 0.394
P= 0.485		4
S100A7i84.877.8 s71.5NRLi:CP<0.001Ls:CP<0.0524
1.516
1.625
2.297		0.177
0.354
0.707		8.6
4.6
3.2		L:C*
L:C**
L:C***		P= 0.009
P= 0.180
P= 0.132		4
S100A824.251
25.992
24.251		4.925
11.314
10.556		4.9
2.3
2.3		L:C*
L:C**
L:C***		P= 0.240
P= 0.537
P= 0.393		4
NRL:C↑ (NS)L:PL↑ (NS)30
S100A90.003
0.005
0.003		0.002
0.004
0.006		1.7
1.1
0.6		L:C*
L:C**
L:C***		NS
NS
NS		4
L:C↑ (NS)L:PL↑ (NS)30
LL3784.1i /80.9s75.8Li:CP<0.05Ls:CNS24
Lyzozyme55.2i / 52.7s59.6Li:CNSLs:CP<0.0524
MIF77.8i/ 77.8s70.7Li:CNSLs:CP<0.0124
αMSHNRi74.6i / 73.1sNR70.9Li:CP<0.01Ls:CP<0.0124
MHC175.5i/74.7s74.4Li:CNSLs:CNS24
RNase70.435
0.330
0.574		0.063
0.077
0.109		7.0
4.3
5.3		L:C*
L:C**
L:C***		P= 0.145
P= 0.589
P= 0.179		4
IP10
89.9
12.6		L:C*
L:C**
L:C***		P<0.05
P<0.005
P<0.05		4
CCL30.40.22.0L:CP= 0.019626
CCL5-
46.1
-		-
6.2
-		L:C*
L:C**
L:C***		P<0.05
P<0.05
NS		4
7.61.45.4L:CP= 0.011226
CCL20L:CP<0.0054
CCL27L:CP<0.054
CRP13.41.2HSs:Csp<0.0018
L:CP= 0.05Lpa:C0.0525
ESR29.510.2HSs:Cs<0.0018
L:CP= 0.05Lpa:C0.0525
IFNgR=0.7L:CNS7
<5%
Normal 		HSs:Cs↑ (NS)9
1418102.5Le:CeP= 0.0276
HSs:CsP<0.05L:CP<0.054
GMCSF78.4582.13Le:CeP= 0.966
0.40.0NRL:CNS26
VEGF632.11544Le:CeP= 0.236
sVEGFR16060HSs:CsNS27
Caspase 1No QuantiNo QuantiL:C↑ (NS)L:PL↑ (NS)30
NLRP3No QuantiNo QuantiL:C↑ (NS)L:PLNS30
CAMP4L:CNS7
Uteroglobulin2020HSs:CsNS27
Cystatin C0.850.8HSs:Cs27
LCN290400.50.02HSs:Cs<0.001L:C<0.00127
BD20.91HSs:CsNS27
MMP2200210HSs:Cs<0.0527
BLC8.10.5810.5L:CP= 0.005626
ICAM-198.731.93.1L:CP= 0.002826
Eotaxin0.10.1NRL:CNS26
Eotaxin23.92.5NRL:CNS26
CXCL6160140NS27
CXCL9219.813.816L:CP= 0.002826
CXCL110.40.4NS27
CX3CL10.91NS27
I-3090.40.3NRL:CNS26
MCP147.537.1NRL:CNS26
M-CSF0.40.2NRL:CNS26
MIP1b16.15.8NRL:CNS26
MIP1d0.10.1NRL:CNS26
PDGF0.50.2NRL:CNS26
TIMP1260.1166.2NRL:CNS26
TIMP2989.2997.3NRL:CNS26

Key: L= Lesional ; PL= Perilesional; C= Control; NS= Not Significant ; HSs= HS Serum; Cs= Control Serum; HSe= HS Exudate; Ce= Control Exudate; I = Inflamed lesional skin, S= Scarred lesional skin, #= Vs CAMP, *= NT (Non-Treated) Samples ,** = Stimulation by Pam2CSK4 Lipopeptide,*** Stimulation by Muramyl Dipeptide (MDP), + Heat Killed Candida Albicans; ++ Heat Killed Staph Aureus, +++ Lipopolysaccharide;

Cytokines and inflammatory proteins which were elevated in more than one study in lesional tissue included IL-1β, IL-6R, IL-10, IL-17A, IL-36α, IL-36β, IL-36γ, IL-36RA, TNF-α, sTNFR2, hBD1, hBD2, hBD3, s100A7, LL37/Cathelicidin, CCL3, CCL5, CCL27 and BLC. Cytokines and inflammatory proteins elevated in peri-lesional tissue included IL-1β, IL-17, IL-36β, IL-36RA, IL-37, IL-38 and TNF-α. IL-37 was the only cytokine identified which showed significant differences between lesional and peri-lesional tissue, with a 1.81 times elevation in lesional compared to peri-lesional tissue (p=0.0002)3. IL-17 was elevated in unaffected HS tissue compared to control patient tissue (p<0.05) in one study31. In HS tissue, S100A9, hBD1 and hBD2 were reduced but this data did not meet statistical significance. Two studies measuring IL-1β levels showed no statistically significant difference between lesional and control skin7,25. No significant elevation of IL-6 was seen in lesional tissue compared to control with the exception of 1 study25. IL-8 levels only just made significance in two studies5,7, with one study showing significant elevation of IL-8 in lesional compared to control tissue24. Two additional studies showed no significant difference4,8. TNF-α levels were significantly elevated compared to control tissue in two studies7,31 but not significantly in 2 additional studies4,24. sTNFR1 was significantly elevated in one study26 whilst showing a non-significant difference in a second study25. CCL5 was significant in 2 studies in lesional tissue compared with controls4,26. One methodology using muramyl dipeptide (MDP) did not reach statistical significance compared to stimulation with Pam2CSK4 Lipopeptide, and non-treated (NT) cells. IFN-γ was elevated in lesional tissue with no significance in one study28 and significance in another4.

Elevated cytokines and inflammatory proteins in HS serum included IL-1β, IL-6, IL-8, IL-10, IL-12p70, IL-17, TNF-α, sTNFR1, CRP, ESR, LC2, and MMP2. TNF-β, and IFN-γ were elevated in wound exudate from active HS lesions. IFN-γ was noted to be decreased in HS patient serum compared to healthy control serum, despite the elevation in wound exudate. Conflicting results were seen in serum findings in IL-10, IL-17 and IFN-γ. One study demonstrated elevated serum IL-10 levels compared to control5 whereas two other studies8,27 showed no significant difference. Whilst two studies4,5 illustrated elevated IL-17 Serum levels in HS patients, one study7 showed no significant difference between patients and controls. IFN-γ showed no statistically significant decrease in the serum of HS patients compared to control in one study9 but a significant difference in a larger, higher powered study4.

Because adalimumab improves HS through TNF antagonism1,2, this cytokine must be classified as pathogenic. TNF mediates inflammation in a classic “sepsis” cascade in tissues—in this pathway LPS from gram negative bacteria activates TNF release from cells, and then TNF stimulates production of IL-1b, IL-6, and IL-8, leading to neutrophil attraction into sites of infection2,4. Increases in IL-1β and IL-8 measured in HS, as well as neutrophil accumulation, could result from this pathway. Alternatively, in psoriasis, TNF is a major cytokine that acts on the IL-23/Type 17 T-cell pathway at two points. First TNF induces IL-23 synthesis in myeloid (CD11c+) dendritic cells in the skin34. Second, TNF (as well as other cytokines that also activate NF-kB) act synergistically with IL-17A or IL-17F to increase synthesis of many other cytokines, chemokines, and inflammatory molecules in keratinocytes and other cell types. There are several clues that an IL-23/Type17 T-cell pathway may be active in HS which include detection of Th17 T-cells in skin infiltrates, increased production of IL-17A, and increased production of LL-37/cathlecidin, S100A7, S100A8, S100A9, LCN2, IL-8, beta-defensins and IL-36; which are all molecules induced by IL-17 in keratinocytes, as also the presence of psoriasis-like epidermal hyperplasia in some reports. The increased production of CCL204, would be predicted to increase tissue infiltration of both Th17 T-cells and CD11c+ DCs, which have both been observed in HS, and increased production of TGF-β could increase differentiation of Th17 T-cells from precursors and/or influence scarring in skin lesions. If IL-17 is driving inflammation in HS, one would expect to see increased production of additional chemokines that regulate neutrophil chemoattraction (CXCL1, CXCL2, CXCL3). Epidermal hyperplasia is not presently explained in HS, but this could be related potentially to increased expression of IL-19, IL-20 or IL-22, which are associated with the IL-23/Type 17 T-cell axis. If IL-22 is produced in HS lesions, this would implicate Th22 T-cells as a T-cell type also associated with the IL-23/Type 17 T-cell axis. There is an uncertain role for other T-cell subsets in HS. Increased production of CXCL9 and IP-10 (CXCL10) are often linked to production of IFN-γ from Th1 T-cells in inflammatory sites, but IL-26 or IL-29, which are also cytokines produced by Th17 T-cells are alternative activators of STAT1 and CXCL9 production. IL-32 production in HS may also be linked to a T-cell subset that produces this cytokine. Low production of Th2 associated cytokines (IL-4, IL-5, or IL-13) has been measured in HS, suggesting an unlikely role of this T-cell subset. Likewise, the presence and function of T regulatory cells (Tregs) in HS lesions needs further study. IL-10 which is elevated in HS could be produced by either Tregs or the cDC1 (BDCA3+) DC subset, but levels may be inadequate to control tissue inflammation. At present, dendritic cell subsets are also incompletely characterized in HS. Potential sources of IL-12 or IL-23 are CD11c+ DCs, which includes the tissue resident BDCA-1+ (cDC2) subset and less mature inflammatory DCs, which are abundant cells in inflammatory lesions of psoriasis or atopic dermatitis but have not been investigated in HS. Cytokine contributions by other cell types such as innate lymphoid cells, macrophages, mast cells, and other leukocytes also remains to be determined.

Cytokine analysis methods

The methodologies of cytokine analysis varied widely (Table 5). 92 results were produced using electrochemical luminescence (ECL) procedures from three separate systems and manufacturers. 62 results were produced using ELISA. 18 results4 were performed with either ELISA or ECL but not further specified. 15 results were produced using polymerase chain reaction (PCR) with three separate systems from three manufacturers. Four discrete cytokines (IL-10, IL-17, TNF-α and IFN-γ) were analysed using all three techniques (ECL, ELISA and PCR), whilst 15 discrete cytokines (IL-6, IL-8, IL12p40, IL-17A, IL-22, IL-23, S100A7, S100A8, S100A9, RNAse7, IP-10, CCL5, CCL20, CCL27) were analysed using ELISA and ECL only. We note IL-17 levels may well be below the lower limit of quantification with ELC and ELISA based approaches, with only the Singulex platform having the ability to quantify levels of IL-17 present in blood and serum of normal subjects.

Table 5. Cytokine analysis methodology of studies included in this review.

CytokineMethodDetailsStudy
IL-1αECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
IL-1raECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
IL-1βECLxMAP technology (Luminex Corporation, Austin, TX, USA)8
ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ECLxMAP technology (Luminex Corporation, Austin, TX, USA)25
ELISACytokines were measured in duplicate by ELISA (R&D Minneap- olis, USA).5
PCRIL10, IL17A, IL1Β, IL18 and NLRP3 was performed with predesigned Taqman gene expression assays (Applied Biosystems) on a Roche Light Cycler
(Roche, Pleasanton, CA, U.S.A.)		31
PCR(Hs01555410_m1), ABI-Prism 7300 Sequence Detector System (Applied Biosystems7
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
IL-4ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)7
IL-5ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)7
ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
IL-6ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
ECLxMAP technology (Luminex Corporation, Austin, TX, USA)8
ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ECLxMAP technology (Luminex Corporation, Austin, TX, USA). The Milliplex MAP multiplex assay25
ELISACytokines were measured in duplicate by ELISA (R&D Minneap- olis, USA).5
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)7
sIL-6RECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)7
IL-8ELISApABG AHC0881 1:50 rabbit antihuman24
ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
ECLxMAP technology (Luminex Corporation, Austin, TX, USA)8
ECLxMAP technology (Luminex Corporation, Austin, TX, USA)25
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)7
ELISACytokines were measured in duplicate by ELISA (R&D Minneap- olis, USA).33
IL-10ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
ECLxMAP technology (Luminex Corporation, Austin, TX, USA)8
ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ECLxMAP technology (Luminex Corporation, Austin, TX, USA)25
ELISACytokines were measured in duplicate by ELISA (R&D Minneap- olis, USA).5
ELISACytokines were measured in duplicate by ELISA (R&D Minneap- olis, USA).5
PCRIL10, IL17A, IL1Β, IL18 and NLRP3 was performed with predesigned Taqman gene expression assays (Applied Biosystems) on a Roche Light Cycler
(Roche, Pleasanton, CA, U.S.A.)		31
ELISAQuantikine enzyme-linked immunosorbent assay (ELISA) systems from Bio-Techne27
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)7
IL-11ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)7
IL-12p40ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ELISAQuantikine enzyme-linked immunosorbent assay (ELISA) systems from Bio-Techne27
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)7
IL-12p70ECLxMAP technology (Luminex Corporation, Austin, TX, USA)8
ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)7
IL-13ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)7
IL-15ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)7
IL-16ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)7
IL-17ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
ELISACytokines were measured in duplicate by ELISA (R&D Minneap- olis, USA).5
PCRIL10, IL17A, IL1Β, IL18 and NLRP3 was performed with predesigned Taqman gene expression assays (Applied Biosystems) on a Roche Light Cycler
(Roche, Pleasanton, CA, U.S.A.)		31
PCRIL-17 (clone AF-317-NA; R&D Systems, Wiesbaden, Germany),30
PCRIL-17 (Hs00174383_m1), ABI-Prism 7300 Sequence Detector System27
IL-17AELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA). eBioscience, Paris, France4
ECLxMAP technology (Luminex Corporation, Austin, TX, USA)8
ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ECLxMAP technology (Luminex Corporation, Austin, TX, USA)25
ELISAQuantikine enzyme-linked immunosorbent assay (ELISA) systems from Bio-Techne27
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
IL-22ELISAELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA). eBioscience, Paris, France4
ECLxMAP technology (Luminex Corporation, Austin, TX, USA)8
IL-23ECLxMAP technology (Luminex Corporation, Austin, TX, USA)25
PCR(Hs00992441_m1) ABI-Prism 7300 Sequence Detector System (Applied Biosystems7
IL-32PCRIL-32 (Hs00992441_m1), ABI-Prism 7300 Sequence Detector System29
IL-32αPCRIL-32a (Hs04353657_gH), ABI-Prism 7300 Sequence Detector System29
IL-32βPCRIL-32b (Hs04353658_gH), ABI-Prism 7300 Sequence Detector System29
IL-32gPCRIL-32c (Hs04353656_g1), ABI-Prism 7300 Sequence Detector System29
IL-32dPCRIL-32d (Hs04353659_gH), ABI-Prism 7300 Sequence Detector System29
IL-36αELISARabbit polyclonal anti-IL-36a (C-terminal; ab180909), from Abcam, Cambridge, U.K. at 1 : 500 dilution.3
ELISAIL-36a AF1078, RnD28
IL-36βELISARabbit polyclonal anti- IL-36b (C-terminal; ab180890) from Abcam, Cambridge, U.K. at 1 : 500 dilution.3
ELISAAF1099, RnD28
IL-36gELISAMouse monoclonal anti-IL-36c ab156783; (Abcam, Cambridge, U.K.) at 1 : 500 dilution.3
ELISAAF2320, RnD28
IL-36RAELISARabbit polyclonal from Abcam, Cambridge, U.K. at 1 : 500 dilution.3
ELISAAF1275, RnD28
IL-37ELISARabbit polyclonal Abcam, Cambridge, U.K. at 1 : 500 dilution.3
IL-38ELISARabbit polyclonal Abcam, Cambridge, U.K. at 1 : 500 dilution.3
TNF-αELISATNF-alpha: 559071 mABG 1:10 mouse antihuman24
ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ELISACytokines were measured in duplicate by ELISA (R&D Minneap- olis, USA).5
PCRTaqman gene expression assays (Applied Biosystems) on a Roche Light Cycler31
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
TNF-βECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
sTNFR1ECLxMAP technology (Luminex Corporation, Austin, TX, USA)8
ECLxMAP technology (Luminex Corporation, Austin, TX, USA)25
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
sTNFR2ECLxMAP technology (Luminex Corporation, Austin, TX, USA)8
ECLxMAP technology (Luminex Corporation, Austin, TX, USA)25
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
hBD1ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
hBD2ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
hBD3ELISAELISA 1 : 400; rabbit antihuman24
ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
S100A7ELISAPsoriasin HL15-4 mAbG 1:20,000 mouse antihuman24
ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
S100A8ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
ELISAS100A8 and S100A9 (monospecific affinity-purified rabbit antisera to S100A8 and to S100A930
S100A9ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
ELISAS100A8 and S100A9 (monospecific affinity-purified rabbit antisera to S100A8 and to S100A930
LL37ELISACathelicidin ab64892 pAbG 1:1000 rabbit antihuman24
LyzozymeELISALysozyme A0099 pAbG 1:100 rabbit antihuman24
MIFELISAMIF MAB289 mABG 1:100 mouse antihuman24
αMSHELISAalpha MSH M09393 mABG 1:500 rabbit antihuman24
MHC1ELISAMHC1 W6/32 mABG 1:50 mouse antihuman24
RNase7ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
IP10ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
CCL3ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
CCL5ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
CCL20ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
CCL27ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
CRPECLxMAP luminex Luminex Corporation, Austin, TX, USA8
ECLxMAP luminex Luminex Corporation, Austin, TX, USA25
ESRECLxMAP luminex Luminex Corporation, Austin, TX, USA8
ECLxMAP luminex Luminex Corporation, Austin, TX, USA25
IFNgPCR(Hs00174143_m1), ABI-Prism 7300 Sequence Detector System (Applied Biosystems)7
ELISAELISA kits from Sanquin (Amsterdam, The Nether- lands)9
ECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ELISA/
ECL		ELISA (Quantikine; R&D Systems) or Luminex assay (Millipore, Billerica, MA).4
GMCSFECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
ELISAQuantibody Human Inflammation array 3 (RayBiotech Inc., Norcross, GA, U.S.A.).26
VEGFECLMeso Scale Discovery electrochemiluminescent assay (MSD, Meso Scale Diagnostics, Rockville, MD MSD V-Plex cytokine panel 1 and the V-plex
proinflammatory panel 1		6
sVEGFR1ELISAQuantikine enzyme-linked immunosorbent assay (ELISA) systems from Bio-Techne27
Caspase 1ELISAKelly et al. Caspase-1 fluorochrome inhibitor of caspases (FLICA) (ImmunoChemistry Technologies, Bloomington, MN, U.S.A.30
NLRP3PCRKelly IL10, IL17A, IL1Β, IL18 and NLRP3 was performed with predesigned Taqman gene expression assays (Applied Biosystems) on a Roche Light Cycler
(Pleasanton, CA, U.S.A.)		30
CAMPPCR(Hs00189038_m1) ABI-Prism 7300 Sequence Detector System (Applied Biosystems)7
UteroglobELISAQuantikine enzyme-linked immunosorbent assay (ELISA) systems from Bio-Techne27
Cystatin CELISAQuantikine enzyme-linked immunosorbent assay (ELISA) systems from Bio-Techne27
LCN2ELISAQuantikine enzyme-linked immunosorbent assay (ELISA) systems from Bio-Techne27
BD2ELISAQuantikine enzyme-linked immunosorbent assay (ELISA) systems from Bio-Techne27
MMP2ELISAQuantikine enzyme-linked immunosorbent assay (ELISA) systems from Bio-Techne27
BLCECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
ICAM-1ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
EotaxinECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
Eotaxin2ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
CXCL6ELISAQuantikine enzyme-linked immunosorbent assay (ELISA) systems from Bio-Techne27
CXCL9ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
CXCL11ELISAQuantikine enzyme-linked immunosorbent assay (ELISA) systems from Bio-Techne27
CX3CL1ELISAQuantikine enzyme-linked immunosorbent assay (ELISA) systems from Bio-Techne27
I-309ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
MCP1ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
M-CSFECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
MIP1bECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
MIP1dECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
PDGF-BBECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
TIMP1ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26
TIMP2ECL(CBA Human Inflammation kit and CBA Human TH1⁄TH2 Cytokine kit; BD Biosciences, Franklin Lakes, NJ, U.S.A.) Analyssi: FACSCalibur (BD Biosciences)26

Table 4: Antibodies Used for Identification of Cytokines in Studies Included in this Systematic Review. ECL: Electrochemicoluminescence

Assessment of bias

Assessment of bias is presented in Table 6. Two of the 14 questions regarding participation rate and loss to follow up were considered not applicable. All included studies identified clear objectives and a clearly defined study population. No clear inclusion or exclusion criteria were specified for 17 of the 19 studies. Power estimation was made for one study33, and recording of all exposures (disease activity, comorbidities etc) were made prior to assessment of the outcomes (cytokine levels). The timeframe of analysis was sufficient to identify an association, but only 10 of the 19 studies (52.6%) documented different levels of exposures (disease severity, metabolic comorbidities, family history etc). There were no serial measures of cytokine levels in the majority of studies. Only three studies5,25,33, examining cytokine levels after monoclonal antibody administration has measurements at two distinct time points. Outcomes of interest (cytokine levels) were measured consistently within studies, however there was great variance in the methods of measurement and analysis between studies (Table 5). No studies took into account known confounding variables into analysis of their results by stratification or regression analyses.

Table 6. Risk of bias across studies included in this review.

Study
Reference		1. Was
the
research
question
or
objective
in this
paper
clearly
stated?		2. Was
the study
population
clearly
specified
and
defined?		3. Was the
participation
rate of
eligible
persons at
least 50%?		. Were all
the subjects
selected or
recruited
from the
same or
similar
populations
(including
the same
time period)?
Were
inclusion and
exclusion
criteria for
being in
the study
prespecified
and applied
uniformly
to all
participants?		5. Was a
sample size
justification,
power
description,
or variance
and effect
estimates
provided?		6. For the
analyses in
this paper,
were the
exposure(s)
of interest
measured
prior to the
outcome(s)
being
measured?		7. Was the
timeframe
sufficient
so that
one could
reasonably
expect
to see an
association
between
exposure
and outcome
if it existed?		8. For
exposures
that can
vary in
amount or
level, did
the study
examine
different
levels
of the
exposure
as related
to the
outcome
(e.g.,
categories
of
exposure,
or
exposure
measured
as
continuous
variable)?		9. Were the
exposure
measures
(independent
variables)
clearly
defined,
valid,
reliable, and
implemented
consistently
across
all study
participants?		10. Was the
exposure(s)
assessed
more than
once over
time?		11. Were the
outcome
measures
(dependent
variables)
clearly
defined, valid,
reliable, and
implemented
consistently
across
all study
participants?		12 Were the
outcome
assessors
blinded to
the exposure
status of
participants?		13. Was
loss to
follow-
up after
baseline
20% or
less?		14. Were key
potential
confounding
variables
measured
and adjusted
statistically
for their
impact
on the
relationship
between
exposure(s)
and
outcome(s)?
Moran
et al.2 		YYN/ANNYYYYNYNRN/AN
Emelianov
et al.24 		YYN/ANNYYNYNYNRN/AN
Hessam
et al.3 		YYN/ANNYYNYNYNRN/AN
Hotz et al.4 YYN/ANNYYYYNYNRN/AN
Thomi
et al.7 		YYN/ANNYYYYNYNRN/AN
Jimenez-
Gallo
et al.8 		YYN/ANNYYYYNYNRN/AN
Banerjee
et al.6 		YYN/ANNYYNYNYNRN/AN
Jimenez-
Gallo
et al.25 		YYN/AYNYYNYNYNRN/AN
Kanni et al.5 YYN/ANNYYYYYYNRN/AN
Kelly et al.31 YYN/ANNYYNYNYNRN/AN
Lima et al.30 YYN/ANNYYNYNYNRN/AN
Ten Oever
et al.9 		YYN/ANNYYNYNYNRN/AN
Schlapbach
et al.32 		YYN/ANNYYYYNYNRN/AN
Thomi
et al.29 		YYN/ANNYYYYNYNRN/AN
Thomi
et al.28 		YYN/ANNYYYYNYNRN/AN
Wolk et al.27 YYN/ANNYYNYNYNRN/AN
Van der Zee
et al.26 		YYN/ANNYYYYNYNRN/AN
Kanni
et al.33 		YYN/AYYYYYYNYNRN/AN

Key: Y = Yes; N= No, NR= Not Reported N/A = Not Applicable

Assessment of heterogeneity

36 of the 81 identified cytokines or inflammatory proteins were assessed by more than 1 study. 23 of those cytokines had raw data available. No studies had sufficient measures of spread in order to calculate I2measure of heterogeneity and so chi-squared statistic was used as an alternate marker of heterogeneity (Table 7) along with a funnel plot (Figure 3). In total, 18 individual cytokines (78.2%) were found to demonstrate heterogeneity. Only eight cytokines (Serum IL-10, Lesional IL-1α, IL-12p70, hBD1, hBD2, hBD3, S100A9 and GMCSF) illustrated homogeneity. Due to this high level of heterogeneity and concerns regarding the methodological quality of included studies, meta-analysis was not deemed appropriate to perform.

Table 7. Table of heterogeneity of cytokine studies by chi-squared tests for homogeneity.

CytokineChi SquaredP
IL1a Lesional0.3525p=0.552705
IL1b Lesional153.5947p<0.00001
IL4 Lesional4.3992P=0.035955
IL5 Lesional15.1692P=0.000098
IL6 Lesional461.9724P<0.00001
IL8 Lesion846.6251P<0.0001
IL8 Serum94.4212P<0.0001
IL10 Lesion90.3211P<0.0001
IL10 Serum0.1595P=0.689624
IL12p40 Lesional4.9618P=0.025913
IL12p70 Lesional 2.2116 P=0.136973
IL13 Lesional5.4163P=0.019949
IL15 Lesional39.2837P<0.00001
IL16 Lesional126.1959P<0.00001
IL17A Lesional22.6668P<0.00001
IL17A Serum19.1621P=0.000012
TNFa Lesional6.9761P=0.030561
TNFb Lesional7.4004P=0.006521
hBD1 Lesional 2.3317 P=0.311656
hBD2 Lesional 0.6488 P=0.722954
hBD3 Lesional 1.0314 P=0.597084
S100A7 Lesional621.2537P<0.00001
S100A8 Lesional19.6371P=0.000054
S100A9 Lesional 1.27 P=0.529927
RNAse 76.7263P=0.034626
GMCSF Lesional 1.9405 P=0.163611

Discussion

The overall quality of reporting in the identified studies was low with little consistency between methodologies and cytokines examined. There was also great variability in the ages, genders, comorbidities, associated conditions and treatments of the patients included in these studies. This was again reflected in the high number of cytokines with statistical heterogeneity (Table 7). The studies presenting conflicting data are often those studies with lower numbers of patients as well as lack of matched controls and/or lack of stratification by treatment. Meta-analysis using individual patient data would be required in order to account for these factors and re-assess the relationship between lesional and control cytokine levels.

In assessing the relationship between lesional and peri-lesional tissue, it has been demonstrated by many authors that different cytokines are present in peri-lesional tissue as opposed to lesional tissue. The definition of peri-lesional tissue is fairly consistent in the studies examined being 2cm from an active HS nodule on unaffected skin. However, no studies reported ultrasound examination of the peri-lesional skin to ensure that subclinical extension of the adjacent nodule (either in the dermis or the subcutaneous tissue) was being inadvertently sampled. This is an important differentiation to make in terms of identifying the subclinical pathogenic processes that precipitate this disease.

The raw data collated illustrates a number of paradoxically elevated levels of control cytokines (IL-15, IL-16) (Table 4). Many of these control readings lie near the lower detection limit of specific assays in individual papers, and thus the possibility of erroneously elevated control readings cannot be excluded. The wide interquartile ranges of studies which did report individual patient data7, suggest that analyzing aggregate data is not optimal and is prone to misrepresentation of the relationship between clinical disease, comorbidities and cytokine levels. Furthermore, high levels of heterogeneity within the measurements of individual cytokines suggest that examination of and correction for other variables or confounders is required.

Methodological quality

Regarding methods of cytokine analysis, a number of authors have identified variability in cytokine levels measured with different forms of multiplex assays as well as traditional ELISA methods35–39. Different methods of cytokine analysis are known to be prone to variability, with some cytokines more sensitive than others. For example, IFN-γ and IL-1β were overestimated compared with ELISA methods37, whilst IL-6 levels were underestimated37. IL-6 levels when compared across four different multiplex assays showed significant variation in detectable range, accuracy and responsiveness36. The correlation of TNF-α between ELISA and Multiplex assays was also poor (r=0.31)36. Issues also exist with minimum detectable levels of cytokines with specific bead-based arrays36 As an example, minimal detectable dose readings reported for IL-12p70 using some multiplex arrays39 are higher than the levels reported in lesional HS samples6. Therefore, whilst the general trends in the level of consistently elevated or suppressed cytokines in HS are reliable, the quantification of individual cytokines as well as the relationship between comorbidities and cytokine levels requires further research with consistent, reliable and accurate methodologies in order to further dissect the inflammatory cascade in this disease.

Keratinocyte mediated inflammatory pathways

The majority of elevated cytokines and inflammatory proteins identified in lesional skin of HS (TNF-α, IL-1β, IL-6, IL-8, IL-11, IL-23, IL-17A, IL-33, IL-36, LL-37, S100A7, S100A8, S100A9, GM-CSF, TGF-β, hBD2, hBD3, CCL3, CXCL9, CXCL11, PDGF, CCL5, CCL-20, MIF, GM-CSF and LCN2) are those known to be produced by keratinocytes, as well as perpetuating a self-amplification pathway34 (Figure 2). Additionally T-cells produce IL-17A, IL-17F, IL-26, IL-29, and IFN-γ; dendritic cells produce IL-12, IL-23 and possibly IL-39; neutrophils produce S100A8 and S100A9 (calgranulin); and innate lymphoid cells also contribute IFN-γ, IL-17A and IL-17F. This inflammatory model has been well documented and explored in both psoriasis and atopic dermatitis34,40. The psoriasiform epidermal hyperplasia seen in HS (mediated by IL-17 and maintained by IL-23-mediated Th17 stimulation)34 reflects this common inflammatory pathway.

cc04d333-0d74-4f54-9cca-1df8ff58301d_figure2.gif

Figure 2. Inflammatory pathways in hidradenitis suppurativa, a schematic representation of the results identified in this systematic review.

Immunological ‘priming’ occurs due to the contribution of adipose tissue, genetic susceptibility, smoking-related inflammatory mediators and obesity related pro-inflammatory signals and the composition of the microbiome. Increased activity of cDC1, cDC2 and T cells lead to both keratinocyte hyperplasia via the actions of IL-12 and IL-23, as well as a Th17 predominant immune response. Alterations of antimicrobial peptides (AMP’s) also occur throughout the epidermis. The dermal inflammation interacting with the hyperplastic epidermis result leads to a self-perpetuating inflammatory feed forward mechanism mediated by IL-36, Il-1B and TNF-a. The development of scarring and sinus tracts is associated with MMP2, ICAM-1 and TGF-Beta, with possible augmentation of ICAM-1 and TGF-B signaling via specific components of the microbiome. TNF-a, PGE2 and CXCL2 then lead to additional feed forward mechanisms perpetuating the inflammatory cycle.

cc04d333-0d74-4f54-9cca-1df8ff58301d_figure3.gif

Figure 3. Funnel plot of selected cytokine in lesional and control samples of hidradenitis suppurativa.

IL-1a = Red, IL-10 = Blue, IL-12p70 = Green, hBD1 = Purple, hBD2 = light purple, hBD3 = Black, S100A9 = White, GMCSF = Yellow.

The other elevated non-keratinocyte produced cytokines in HS (IL-4, IL-5, IL-10, IL-16, IL-17A, IL-22, IL-32, IL-36, hBD1), are produced by a combination of dendritic cells, monocytes, neutrophils and CD4+ T cells. IL-4 and IL-5 as key cytokines in the Th2 axis are consistent with the findings of Mast cells in HS41, as well as the pruritus, which is frequently reported by patients. IL-10 in HS is produced by Treg cells2 (although dendritic cells may also be a source), and whilst quantitatively the IL-10 signal appears paradoxically elevated, it can be explained by the up-regulation of T cells including Treg cells, which although significantly elevated from baseline, are not elevated enough in comparison to TH17/IL-17/IL-22 signal to counteract this strong pro-inflammatory cascade2. Further exploration of these cytokines may reveal the initial trigger(s) of the inflammatory cascade in HS, or correlations with known pro-inflammatory comorbidities.

Insights into pathogenesis of HS

In light of investigations in psoriasis and atopic dermatitis, the role of dendritic cells in HS needs to be clarified, as dendritic cell influx has been reported in histological studies41,42, and they may contribute to the high IL-10 and IL-15 levels reported. IL-32 is a second cytokine produced by dendritic cells, but has only been reported in one study29. Further research into the functional role of IL-32 in the activity of dendritic cells in HS would be of value. The role of IL-20, IL-22, IL-24 and IL-26 needs further clarification. IL-19, TSLP and CCL17 (TARC) have not yet been examined in HS and this is required in order to further explore the role of dendritic cell, monocyte and T cell activation and migration in this disease.

It is well established that smoking, obesity and diabetes are strongly associated with HS13–19,42,43. The immunological effects of smoking include increase in number and responsiveness of dendritic cells, altered function of Treg cells and activation of Th17 pathways44, whilst obesity and diabetes can result in production of IL-1β, IL-6 and TNF-α through activated macrophages in adipose tissue45,46. These potential mechanistic pathways (which may prime or contribute towards inflammation in HS) require validation in functional studies. However, if they are a significant contributor to inflammation, the presence or absence of these comorbidities need to be considered in future cytokine studies as confounding variables in order to identify significant biochemical markers independent of these other pro-inflammatory states that reflect the pathogenesis of HS.

The role of the microbiome42,43 in stimulating chronic inflammation has parallels in diabetes47 and colonic inflammation48 and the presence of Porphyromonas and Peptoniphilus species has been associated with a subpopulation of patients with HS42. Porphyromonas has been associated with systemic inflammation and atherosclerosis through aberrant toll-like-receptor 4 signalling48 and is not part of the natural cutaneous flora43. Altered cutaneous and gastrointestinal microbiome can also act via microbiome metabolites (including lipopolysaccharides, short chain fatty acids and bile salts)49 through stimulation of myeloid dendritic cells via G Protein Coupled Receptors (including GPR41, GPR43 and GPR109A)49,50. The microbiome may be implicated as a trigger factor for the initial inflammatory cascade in HS in a proportion of patients. Similarly, the presence of genetic polymorphisms as reported in HS51 have the potential to up-regulate inflammatory activity through shedding of IL-6R, IL-15R, TNF-α52 as well as up-regulating the response of dendritic cells to LPS stimulation via ADAM17 (which has been demonstrated to be elevated in a published gene expression study of HS)53. These pathways may be involved prior to the activation of keratinocyte-mediated inflammation, and hence, may reveal novel targets for new interventions to control the disease prior to the onset of destructive inflammation.

Limitations, interpretation and generalisability

The limitations to this study include the high degree of methodological variability (Table 5) and high impact of bias (Table 6) within the included studies. The lack of individual patient data has also prevented any further analysis into the contribution of comorbidities such as smoking and obesity to variable levels of cytokines in lesional tissue and/or serum. This, along with the high level of heterogeneity in many cytokines (Table 7), has resulted in analyses of the collated data being limited to descriptive analyses only and limited the generalisability of results.

Conclusions

Through this review we have catalogued the various cytokines that have been reported as elevated in lesional, peri-lesional tissue, serum or exudate of HS patients. We have also identified those cytokines with inconsistent results and identified methodological factors that may explain variability in findings. We have identified a number of missing links in disease pathogenesis with respect to cytokine actions and pathways that must be addressed in future work. Areas for further investigation include the role of dendritic cells in HS, the contribution of obesity, smoking, diabetes and the microbiome to cytokine profiles in HS, and examining the natural history of the disease through longitudinal measurements of cytokines over time.

Data availability

All data underlying the results are available as part of the article and no additional source data are required.

Extended data

OSF: Extend data. Data Collection Sheet Cytokine. Review HS. https://doi.org/10.17605/OSF.IO/N2E7A22

License: CC0 1.0 Universal

Reporting guidelines

OSF: PRISMA checklist for ‘A systematic review and critical evaluation of inflammatory cytokine associations in hidradenitis suppurativa’. https://doi.org/10.17605/OSF.IO/N2E7A22

License: CC0 1.0 Universal

Grant information

Supported in part by a grant from the National Center for Advancing Translational Sciences (NCATS) [UL1 TR001866], National Institutes of Health (NIH) Clinical and Translational Science Award (CTSA) program.

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Frew JW, Hawkes JE and Krueger JG. A systematic review and critical evaluation of inflammatory cytokine associations in hidradenitis suppurativa [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2018, 7:1930 (https://doi.org/10.12688/f1000research.17267.1)
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ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions
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Reviewer Report 04 Mar 2019
Evangelos J. Giamarellos-Bourboulis, Attikon University Hospital, Athens, Greece;  National and Kapodistrian University of Athens, Athens, Greece 
Approved with Reservations
VIEWS 10
https://doi.org/10.5256/f1000research.18879.r43994
This is a long time needed review trying to shed light in the pathogenesis of hidradenitis suppurativa (HS). My concerns are coming from the biggest hurdle the authors had to overcome from the very beginning of their attempt i.e. the ... Continue reading
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Giamarellos-Bourboulis EJ. Reviewer Report For: A systematic review and critical evaluation of inflammatory cytokine associations in hidradenitis suppurativa [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2018, 7:1930 (https://doi.org/10.5256/f1000research.18879.r43994)
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https://f1000research.com/articles/7-1930/v1#referee-response-43994
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Reviewer Report 25 Feb 2019
Aude Nassif, Institut Pasteur, Medical Center, Paris, France 
Approved
VIEWS 8
https://doi.org/10.5256/f1000research.18879.r43995
This very instructive study aims at analyzing previous cytokine studies in HS patients, in skin tissue, blood, serum and exudates, to assess relevancy and reliability of these studies.

The authors have performed an extensive work, methods seem ... Continue reading
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Nassif A. Reviewer Report For: A systematic review and critical evaluation of inflammatory cytokine associations in hidradenitis suppurativa [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2018, 7:1930 (https://doi.org/10.5256/f1000research.18879.r43995)
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https://f1000research.com/articles/7-1930/v1#referee-response-43995
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Reviewer Report 07 Feb 2019
Barbara Horváth, Department of Dermatology, University of Groningen, Groningen, The Netherlands 
Lisette Prens, Department of Dermatology, University of Groningen, Groningen, The Netherlands 
Approved
VIEWS 13
https://doi.org/10.5256/f1000research.18879.r43493
Thank you for the opportunity to review this manuscript and congratulations to the authors for their great efforts in putting this systematic review together. Research on the role of cytokines in HS is important, as it may lead to new ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Horváth B and Prens L. Reviewer Report For: A systematic review and critical evaluation of inflammatory cytokine associations in hidradenitis suppurativa [version 1; peer review: 2 approved, 1 approved with reservations]. F1000Research 2018, 7:1930 (https://doi.org/10.5256/f1000research.18879.r43493)
The direct URL for this report is:
https://f1000research.com/articles/7-1930/v1#referee-response-43493
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Alongside their report, reviewers assign a status to the article:

Approved
The paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations
A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approved
Fundamental flaws in the paper seriously undermine the findings and conclusions

Reviewer Reports

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  1. Barbara Horváth, University of Groningen, Groningen, The Netherlands
    Lisette Prens, University of Groningen, Groningen, The Netherlands
  2. Aude Nassif, Institut Pasteur, Medical Center, Paris, France
  3. Evangelos J. Giamarellos-Bourboulis, Attikon University Hospital, Athens, Greece; National and Kapodistrian University of Athens, Athens, Greece

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    Alongside their report, reviewers assign a status to the article:
    Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested
    Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
    Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions
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