Biologic insights from single-cell studies of psoriasis and psoriatic arthritis. (2nd December 2022)

• Record Type: Journal Article
• Authors: Jin, Joy Q; Wu, David; Spencer, Riley; Elhage, Kareem G; Liu, Jared; Davis, Mitchell; Hakimi, Marwa; Kumar, Sugandh; Huang, Zhi-Ming; Bhutani, Tina; Liao, Wilson
• Is Part Of: Expert opinion on biological therapy. Volume 22:Number 12(2022)
• Page Start: 1449
• Page End: 1461
• Publication Date: 2022-12-02
• Subjects: Biologic therapy -- inflammatory skin disease -- psoriasis -- psoriatic arthritis -- single-cell RNA-sequencing -- skin; Gene therapy -- Periodicals; Protein drugs -- Periodicals; Peptide drugs -- Periodicals; Immunotherapy -- Periodicals; Drug delivery systems -- Periodicals; 615.5
• DOI: 10.1080/14712598.2022.2142465
• Languages: English
• ISSNs: 1471-2598

Abstract

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.