Hidradenitis suppurativa (HS) is characterized by a high inflammatory burden—often presenting with irritated nodules, abscesses, and fistulas in intertriginous areas. As such, lab markers such as c-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) can be useful indicators of degree of inflammation in HS.1 Protein gap, another laboratory measure of inflammation, is defined as the difference between serum total protein and albumin levels.2 Protein gap, like ESR and CRP, is often elevated in inflammatory conditions due to hypergammaglobulinemia.3–5 However, little is known regarding the relationship between protein gap and the severity of hidradenitis suppurativa. Since late-stage HS is associated with plasma and B cell signatures and elevated immunoglobulin levels, we hypothesized that protein gap would positively correlate with HS severity and could be a useful marker of inflammatory burden.
In this study, we characterized the association between disease severity and protein gap levels for HS patients through retrospective chart review. Patients were included if diagnosed with HS (ICD code: ICD-10 code L73.2) and seen in the Duke Dermatology HS clinic with at least 1 follow-up appointment between July 1, 2018 and July 1, 2021. Patient demographics, disease characterization, and inflammatory markers were recorded. Severity of disease was measured by the International Hidradenitis Suppurativa Severity Score System (IHS4). Protein gap is reported from patients’ initial visit and was obtained through comprehensive metabolic panel.
The association between IHS4 and protein gap was assessed using univariable and multivariable linear regression models using log (IHS4) due to the violation of the normality assumption of raw IHS4 score. Additional covariates in the multivariable model included age, sex, smoking, body mass index (BMI), race, insulin resistance, hormone therapy, oral antibiotics, and immunomodulatory therapy. Model results are presented as the geometric mean ratio (GMR) with 95% confidence interval (CI). Pearson’s correlation coefficient (
The final analysis consisted of 113 patients, with 82.3% self-reported female participants and 63.1% self-reporting as Black. Most of the patients included were never-smokers (54.1%) and did not have diabetes or prediabetes (56.4%). Full demographic characterization of the included patients is listed in Table 1. At their initial visit, included patients had a median (Q1-Q3) IHS4 score of 8 (2-28) and protein gap of 3.6 g/dL (3.2-4.5). We found that protein gap has a moderate to strong positive correlation with disease severity as measured by log (IHS4) (
Overall demographic data for included patients.
Total (N=113)
Mean (SD)
37.6 (14.9)
Median (Q1, Q3)
35.1 (24.8, 48.1)
Range
(0.0-75.5)
93 (82.3%)
Missing
2
Black or African-American
70 (63.1%)
Caucasian/White
34 (30.6%)
Other
7 (6.3%)
Missing
3
Mean (SD)
34.9 (8.5)
Median (Q1, Q3)
33.9 (28.5, 39.4)
Range
(18.6-66.6)
Missing
2
Current/former smoker
51 (45.9%)
Never smoked
60 (54.1%)
49 (43.4%)
Stage I
17 (15.0%)
Stage II
45 (39.8%)
Stage III
51 (45.1%)
Missing
1
Clear
12 (10.7%)
Minimal
10 (8.9%)
Mild
27 (24.1%)
Moderate
35 (31.3%)
Severe
3 (2.7%)
Very severe
25 (22.3%)
Mean (SD)
22.2 (33.2)
Median (Q1, Q3)
8.0 (2.0, 28.0)
Range
(0.0-175.0)
9 (8.0%)
13 (11.5%)
37 (32.7%)
Mean (SD)
3.8 (1.2)
Median (Q1, Q3)
3.6 (3.2, 4.5)
Range
(0.0-7.0)
Multivariable regression analysis demonstrating the relationship between each covariate and disease severity, calculated as log-transformed IHS4.
Covariate
GMR (95% CI)
P-value
Protein gap (
2.24 (1.69, 2.96)
<0.001
Age, years (
1.01 (0.99, 1.03)
0.44
Sex
Male
0.89 (0.39, 2.06)
0.79
Female
reference
Race
Black
0.76 (0.37, 1.55)
0.45
Other
0.99 (0.27, 3.68)
0.99
White
reference
BMI, kg/m2 (
1.03 (0.98, 1.07)
0.22
Smoker
Former/current
0.86 (0.44, 1.67)
0.65
Never smoked
reference
Insulin resistance
Pre-diabetes/diabetes
1.79 (0.87, 3.68)
0.11
No diabetes
reference
Hormonal therapy
Yes
0.69 (0.21, 2.29)
0.54
No
reference
Immunomodulatory therapy
Yes
1.67 (0.61, 4.57)
0.32
No
reference
Oral antibiotics
Yes
1.87 (0.95, 3.67)
0.069
No
reference
Our study determined that, upon initial presentation to the clinic, patients with more severe HS also had increasingly large protein gaps in their blood work. Severe HS is associated with B cell and plasma cell signatures at bulk and single-cell transcriptomic levels, potentially due to immunoglobulin production and complement activation.4,6 A recent study found that patients with severe HS who did not respond to therapy with the anti-TNF-alpha antibody adalimumab at week 12 had enriched pathways in complement and B cell activation.6 Given the contribution of hypergammaglobulinemia to protein gap, we propose that this laboratory measurement could be an indicator of B cell and plasma cell enrichment and useful predictor of treatment response that is routinely obtained and has a relatively low cost. Future studies should compare baseline values of protein gap among patients receiving adalimumab therapy, perhaps through analysis of the PIONEER I and II trials.7
The main limitation of this study is the small sample size. Given this is a single center study, further exploration is needed to ensure generalizability despite the statistically significant relationship between disease severity and protein gap. Further, there is a lack of longitudinal data to identify if there is a change over time in the levels of protein gap due to changes in severity or treatment response. Future research should focus on trending protein gap levels over time to determine the possibility of protein gap as a marker of disease prognosis and treatment response.
In conclusion, protein gap has the potential to become a useful biomarker in evaluating the severity of HS, and with further exploration, may have potential to guide treatment and appraise prognosis in HS.
Tarannum Jaleel M.D., MSc
Duke University Health System
Department of Dermatology
40 Duke Medicine Circle Clinic 3K
Durham, NC, 27705 919-681-8276
T.J. is an investigator for UCB, Abbvie, Sonoma, and Eli Lilly. She reports consulting for Eli Lilly and Novartis and receiving honoraria. She has received funds from Pfizer and UCB for research fellow support. She also has received funds from Dermatology Foundation, and Skin of Color Society, Duke Strong Start Award, and NIH K12 (grant number: K12HD043446). She is also a board member of the Skin of Color Society. SWJ is a resident ambassador for the American Academy of Dermatology and has received honoraria. The remaining authors declare that the research was conducted in the absence of any financial relationships that could be construed as a potential conflict of interest.
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