Dr. Daniel Johnston

This project seeks to explore the cause of the devasting skin condition hidradenitis suppurativa (HS). People with HS suffer recurring inflamed lesions in areas where skin touches skin, such as under the arms or the groin, causing great unseen pain and wounds with embarrassing odorous discharge causing social reclusion and mental health difficulties. HS disproportionally affects people with lower socioeconomic status, and it has the added affect of further driving people with the condition into further poverty through missed workdays through physical and mental illness. This disease has a great unmet clinical and social need and is an ideal starting point for our new laboratory, which seeks to perform excellent science that benefits society locally and globally in an inclusive and environmentally sustainable way. Biologically, HS is thought to originate in hair follicles " critical skin appendages with many roles in regulating bodily function. Hair follicles in HS appear to become blocked, and then rupture triggering the immune system to cause sustained inflammation and scarring. However, the chain of events is poorly understood despite consensus that hair follicles are the site of disease origin. In this work, we seek to understand how hair follicles in people with HS become so badly disrupted, and whether this information can be used to design a tissue culture model of HS hair follicle breakdown to better understand the disease, and trial potential disease treatments as a first step towards clinical use. To do this, we will take advantage of several collaborations established in recent years to gain access to cutting edge `omics data and rare tissue samples to build a picture of hair follicle vulnerability and model it in a laboratory setting. Firstly, using hair follicle biopsies, the student will be trained in their culture in the lab and learn to employ an existing model of hair follicle disruption used to study alopecia areata. The student will then undertake a systematic review of the HS literature and a computational biology analysis integrating data from collaborators to compare follicles from HS to other skin diseases. In the third aim of the project, we bring together data from our tissue culture model and `omics analysis, with data from the HS literature, with the aim of identifying factors that can cause hair follicle collapse, and determining if hair follicles from HS patients are more vulnerable to stresses. We will seek to reverse any disruption using pharmacological treatment which may inform future HS treatment strategies.

Hidradenitis suppurativa (HS) is a devastating inflammatory skin condition with precise anatomical localisation that is currently unexplained. Overwhelmingly affecting the groin and the axillae, it has been assumed for years that this is due to anatomical differences due to the presence of terminally differentiated apocrine-rich hair follicles in these regions. However, the evidence linking disease onset to these structures is mixed and fails to explain the pathogenesis of disease chronicity. HS research has rapidly accelerated since 2008 but been exclusively the purview of dermatologists in this time. This project will be approached from the perspective of an anatomist to bear on HS, alongside a background in skin biology, immunology and inflammation research. It will allow me to further develop skills in the anatomical sciences, and to bring perspectives of a highly prevalent but understudied and under reported disease to future Anatomical Society summer and winter meetings and publications.

The Discipline of Anatomy is responsible for the education of ~880 undergraduate students across multiple courses. With a small academic staff (five), the process of coordinating, teaching, examining and marking can be overwhelming and leaves less time for interactive small-group teaching and detailed feedback that allows our students thrive1,2. With large student numbers meticulous attention is needed to maintain the quality and integrity of examinations, a process that becomes increasingly difficult as student numbers continue to rise. Innovative solutions are required to address this issue. This proposal aims to reduce the workload on individual academic staff and simultaneously improve the quality of our assessments through a combination of open-source exam-banking software and Retrieval Augmented Generation (RAG) AI.