Hidradenitis suppurativa: new insights into disease mechanisms and an evolving treatment landscape

Setting the Stage for Standardized Reporting of Clinical and Demographic Information in Laboratory-Based Studies of Hidradenitis Suppurativa

Hidradenitis suppurativa (HS) is a complex inflammatory skin condition affecting 0.1-4% of the population that leads to permanent scarring in the axilla, inframammary region, groin, and buttocks. Its complex pathogenesis involves genetics, innate and adaptive immunity, microbiota, and environmental stimuli. Specific populations have a higher incidence of HS, including females and Black individuals and those with associated comorbidities. HS registries and biobanks have set standards for the documentation of clinical data in the context of clinical trials and outcomes research, but collection, documentation, and reporting of these important clinical and demographic variables are uncommon in HS laboratory research studies. Standardization in the laboratory setting is needed because it helps to elucidate the factors that contribute mechanistically to HS symptoms and pathophysiology. The purpose of this article is to begin to set the stage for standardized reporting in the laboratory setting. We discuss how clinical guidelines can inform laboratory research studies, and we highlight what additional information is necessary for the use of samples in the wet laboratory and interpretation of associated mechanistic data. Through standardized data collection and reporting, data harmonization between research studies will transform our understanding of HS and lead to novel discoveries that will positively impact patient care.

Eosinophils in hidradenitis suppurativa patients exhibit pro-inflammatory traits, implicating a potential pathogenic role in the disease

Hidradenitis suppurativa (HS) is an inflammatory skin disease characterized by painful nodules, abscesses and purulent secretions in intertriginous regions. Intense pruritus frequently accompanies HS lesions, adding further discomfort for patients. While Th17 pathway activation is implicated in HS pathogenesis, disease mechanisms are still not fully understood, and therapeutics are lacking. Previous reports raise a potential role for eosinophils in HS, showing a strong association of eosinophil levels with disease severity. To investigate eosinophils in HS, we recruited patients and matched healthy controls and then performed flow-cytometry studies, eosinophil stimulation assays, and lesional skin staining for eosinophils. We found that HS patients reported similar levels of pain and itch. Compared to matched controls, HS blood exhibited decreased mature eosinophils and increased numbers of immature eosinophils, coupled with a significant increase in dermal eosinophilic infiltrates. Additionally, IL-17RA+ eosinophils were highly and significantly correlated with multiple HS-related clinical scores. In both stimulated and unstimulated conditions, HS eosinophils showed an inflammatory phenotype versus controls, including an increase in costimulatory T- and B-cell markers (e.g. CD5 and CD40) following all stimulations (TNFα/IL-17A/IL-17F). These findings highlight the significance of pruritus in HS and suggest a higher turnover of eosinophils in HS blood, potentially due to the consumption of eosinophils in skin lesions. Our data delineate the features and functions of eosinophils in HS and suggest that eosinophils participate in disease pathogenesis, advancing Th17-related inflammation. Further studies are needed to investigate eosinophils' response to current HS treatments and their potential as a therapeutic target in the disease.

Discrepancies in hidradenitis suppurativa lesion characterization by providers and patients

BACKGROUND

The hidradenitis suppurativa (HS) clinical response (HiSCR) has come under scrutiny as several HS clinical trials failed to meet primary endpoints with high placebo responses. This may be due to limitations of the tool and raters' ability to accurately characterize and count lesions, rather than lack of efficacy of the studied drug. Due to HS lesion complexity and potential differences in rater training, it was hypothesized that there would be discrepancies in how providers characterize and count lesions for HS clinical trials.

OBJECTIVE

To evaluate how HS providers and patients name and count HS lesions and to identify discrepancies among providers to initiate the development of consensus-driven guidance for HS rater training.

METHODS

An online survey was distributed to the members of HIdradenitis SuppuraTiva cORe outcomes set International Collaboration (HISTORIC). Respondents were asked to classify lesion images composed of multiple and different morphology types and answer questions regarding inclusion of associated dermatological conditions.

RESULTS

Forty-seven HISTORIC members responded (29 providers; 18 patients). There was variability in how respondents classified HS lesions. Of 12 questions containing images, four had ≥50% of respondents choosing the same answer. With an image of a lesion composed of different morphologies, 45% of providers counted it as a single lesion and 45% counted it as multiple distinct lesions. With an image of multiple interconnected draining tunnels, 7% of providers classified it as a single draining tunnel while 79% categorized it as multiple draining tunnels with the number estimated by visual inspection. There was also variability in deciding whether lesions occurring in associated conditions should be considered separately or included in HS lesion counts. Patient responses were also variable.

CONCLUSIONS

The result of the current study reaffirms the gap in how providers characterize and count HS lesions for clinical trials and the need to develop consensus-driven rater training related to HS outcome measures.

Harnessing artificial intelligence for advancing early diagnosis in hidradenitis suppurativa

This perspective delves into the integration of artificial intelligence (AI) to enhance early diagnosis in hidradenitis suppurativa (HS). Despite significantly impacting Quality of Life, HS presents diagnostic challenges leading to treatment delays. We present a viewpoint on AI-powered clinical decision support system designed for HS, emphasizing the transformative potential of AI in dermatology. HS diagnosis, primarily reliant on clinical evaluation and visual inspection, often results in late-stage identification with substantial tissue damage. The incorporation of AI, utilizing machine learning and deep learning algorithms, addresses this challenge by excelling in image analysis. AI adeptly recognizes subtle patterns in skin lesions, providing objective and standardized analyses to mitigate subjectivity in traditional diagnostic approaches. The AI integration encompasses diverse datasets, including clinical records, images, biochemical and immunological data and OMICs data. AI algorithms enable nuanced comprehension, allowing for precise and customized diagnoses. We underscore AI's potential for continuous learning and adaptation, refining recommendations based on evolving data. Challenges in AI integration, such as data privacy, algorithm bias, and interpretability, are addressed, emphasizing the ethical considerations of responsible AI deployment, including transparency, human oversight, and striking a balance between automation and human intervention. From the dermatologists' standpoint, we illustrate how AI enhances diagnostic accuracy, treatment planning, and long-term follow-up in HS management. Dermatologists leverage AI to analyze clinical records, dermatological images, and various data types, facilitating a proactive and personalized approach. AI's dynamic nature supports continuous learning, refining diagnostic and treatment strategies, ultimately reshaping standards of care in dermatology.

NK and NKT cells in the pathogenesis of Hidradenitis suppurativa: Novel therapeutic strategy through targeting of CD2

Hidradenitis suppurativa (HS) is a chronic debilitating inflammatory skin disease with poorly understood pathogenesis. Single-cell RNAseq analysis of HS lesional and healthy individual skins revealed that NKT and NK cell populations were greatly expanded in HS, and they expressed elevated CD2, an activation receptor. Immunohistochemistry analyses confirmed significantly expanded numbers of CD2+ cells distributed throughout HS lesional tissue, and many co-expressed the NK marker, CD56. While CD4+ T cells were expanded in HS, CD8 T cells were rare. CD20+ B cells in HS were localized within tertiary follicle like structures. Immunofluorescence microscopy showed that NK cells (CD2 + CD56 dim ) expressing perforin, granzymes A and B were enriched within the hyperplastic follicular epidermis and tunnels of HS and juxtaposed with apoptotic cells. In contrast, NKT cells (CD2 + CD3 + CD56 bright ) primarily expressed granzyme A and were associated with α-SMA expressing fibroblasts within the fibrotic regions of the hypodermis. Keratinocytes and fibroblasts expressed high levels of CD58 (CD2 ligand) and they interacted with CD2 expressing NKT and NK cells. The NKT/NK maturation and activating cytokines, IL-12, IL-15 and IL-18, were significantly elevated in HS. Inhibition of cognate CD2-CD58 interaction with blocking anti-CD2 mAb in HS skin organotypic cultures resulted in a profound reduction of the inflammatory gene signature and secretion of inflammatory cytokines and chemokines in the culture supernate. In summary, we show that a cellular network of heterogenous NKT and NK cell populations drives inflammation, tunnel formation and fibrosis in the pathogenesis of HS. Furthermore, CD2 blockade is a viable immunotherapeutic approach for the management of HS.