Biologic insights from single-cell studies of psoriasis and psoriatic arthritis

ABSTRACT

Introduction

Psoriasis (PSO) and psoriatic arthritis (PSA) represent a large burden of global inflammatory disease, but sustained treatment response and early diagnosis remain challenging. Both conditions arise from complex immune cell dysregulation. Single-cell techniques, including single-cell RNA sequencing (scRNA-seq), have revolutionized our understanding of pathogenesis by illuminating heterogeneous cell populations and their interactions.

Areas covered

We discuss the transcriptional profiles and cellular interactions unique to PSO/PSA affecting T cells, myeloid cells, keratinocytes, innate lymphoid cells, and stromal cells. We also review advances, limitations, and future challenges associated with single-cell studies.

Expert opinion

Following analyses of 22 single-cell studies, several themes emerged. A small subpopulation of cells can have a large impact on disease pathogenesis. Multiple cell types identified via scRNA-seq play supporting roles in PSO pathogenesis, contrary to the traditional paradigm focusing on IL-23/IL-17 signaling among dendritic cells and T cells. Immune cell states are dynamic, with psoriatic subpopulations aberrantly re-activating and differentiating into inflammatory phenotypes depending on surrounding signaling cues. Comparison of circulating immune cells with resident skin/joint cells has uncovered specific T cell clonotypes associated with the disease. Finally, machine learning models demonstrate great promise in identifying biomarkers to diagnose clinically ambiguous rashes and PSA at earlier stages.

KEYWORDS:

• Biologic therapy
• inflammatory skin disease
• psoriasis
• psoriatic arthritis
• single-cell RNA-sequencing
• skin

Article highlights

• Single-cell RNA sequencing (scRNA-seq) has transformed our ability to understand cellular heterogeneity and more precisely reveal cell populations involved in disease pathogenesis. This has implications for psoriasis (PSO) treatment selection and development, as well as earlier diagnosis of psoriatic arthritis (PSA)

• A small subset of cells (e.g. Tc17/T17 cells) can have a large impact on PSO/PSA pathogenesis. Multiple immune cell types (myeloid cells, keratinocytes, innate lymphoid cells, and stromal cells) play a supporting role, contrary to the traditional paradigm focusing on IL-23/IL-17 signaling among dendritic cells and T cells

• Immune cell states are dynamic. Psoriatic cell subpopulations can aberrantly re-emerge and mirror prenatal states, differentiating into an inflammatory phenotype based on environmental signaling cues

• Comparison of circulating immune cells and resident skin/joint cells have uncovered specific T cell clonotypes that home to peripheral locations associated with disease

• Machine learning models using data from skin and blood samples have demonstrated great promise in identifying molecular profiles for diagnosing clinically ambiguous rashes with PSO and identifying PSA at earlier stages

Declaration of interest

JQ Jin is funded by the National Psoriasis Foundation and an Institutional Research Fellowship from UCSF School of Medicine. J Liu is supported by NIH grant T32AR007175. T Bhutani is currently a principal investigator for studies being sponsored by Abbvie, Castle, CorEvitas, Dermavant, Galderma, Mindera, and Pfizer. She has also received research funding from Novartis and Regeneron. She has served as an advisor for Abbvie, Arcutis, Boehringer-Ingelheim, Bristol Myers Squibb, Janssen, Leo, Lilly, Pfizer, Novartis, Sun, and UCB, none of which are relevant to this paper. W Liao has received research grant funding from Abbvie, Amgen, Janssen, Leo, Novartis, Pfizer, Regeneron, and TRex Bio. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This paper was not funded.