Oct 28, 2022 / Immunology

Single cell researchers develop an open source database to help clinicians diagnose psoriasis

Natalya Ortolano

According to the World Psoriasis Day Consortium, 125 million people worldwide have psoriasis, an incurable chronic inflammatory condition that causes painful, scaly rashes that can make day-to-day life nearly unbearable (1). While there are effective treatments to keep these rashes at bay, up to 50% of patients experience little to no relief from available therapies. The key to helping these patients may not be better treatment, but, rather, better diagnosis using each condition's unique molecular fingerprint.

Clinicians primarily diagnose rashes by eye. But while the underlying cellular dysfunction significantly differs between chronic inflammatory skin diseases, the resulting rashes aren't very distinctive. Rashes caused by atopic dermatitis (AD)—the most common form of eczema which affects nearly 3% of the global population—are sometimes mistaken for psoriasis-induced rashes, and vice versa (2). It’s critical that clinicians differentiate between the two diseases to prescribe the most effective treatment since biological therapies for each condition target different immune pathways.

Researchers from the University of California, San Francisco used single cell RNA-sequencing (scRNA-seq) to dive deeper into the molecular underpinnings of several chronic inflammatory skin diseases. They analyzed skin samples from 31 patients—seven with AD, eight with psoriasis vulgaris, one with another inflammatory skin disorder, six with unidentified rashes, and seven healthy people—and found distinctive differences in immune cell profiles, particularly in T cells (3).

These disease-specific transcriptional profiles enabled them to not only diagnose the unidentified rashes unresponsive to prior treatment, but to predict effective treatments based on the patient’s diagnosis, demonstrating the power of their approach in the clinic. The authors compiled their data in an open-access online database dubbed RashX that researchers and clinicians can use to diagnose their rashes based on scRNA-seq data.

“By placing transcriptomic features of individual rashes in the context of a large, existing dataset, we seek a standardized framework to link molecular features to disease prognosis and drug response based on contributions from clinical centers worldwide,” said the authors.

T cells go rogue during chronic inflammatory skin disease

These UCSF researchers are not the first to use scRNA-seq to understand the molecular underpinnings of chronic inflammatory skin disease. Another group of researchers discovered that specific subsets of cytotoxic and helper T cells and dendritic cells were enriched in rashes from people with psoriasis, and a specific population of cytotoxic T cells correlated with disease severity (4,5). But these findings only emphasized the heterogeneity of immune activity in these diseases.

In the new study, the UCSF researchers focused their scRNA-seq analysis on skin-specific or cutaneous immune cells in an effort to increase analytical resolution and, ultimately, find molecular differences between AD and psoriasis to inform patient diagnosis and treatment.

The researchers analyzed expression of about 1,000 genes in 158,000 immune cells across 31 patient samples. They identified 11 large, distinct clusters in both healthy and diseased samples that aligned with previous scRNA-seq data of immune cells from healthy skin tissue. They hoped more detail would increase their chances of finding clinically relevant molecular differences between healthy and diseased tissue—they dug deeper to define more cell populations and identified 41 distinct immune cell populations.

All of the samples from patients with inflammatory skin disease had enriched populations of certain immune cells compared to samples from healthy people. The researchers noted high levels of exhausted effector or CD8+ T cells, which are less effective at fighting foreign invaders due to prolonged exposure to a particular antigen. They also found increased populations of regulatory and memory T cells. This mix of cells paints a picture of an immune system struggling to control the inflammation it mistakenly initiated.

A subset of memory T cells distinguish psoriasis from AD

The researchers also found distinctive differences between AD and psoriasis patient samples. They identified known genetic markers of psoriasis—IL17F and CXCL13—that encoded pro-inflammatory cytokines. But they also found new psoriasis-specific markers. Psoriasis patient samples had high levels of the genes MAP3K4 and PTPN13 exclusively expressed by skin-specific memory T-cell classes Trm1 and Trm3.

In fact, genes specifically expressed in skin-resident memory T cells were consistently overrepresented in psoriasis patient samples. The researchers could accurately identify AD and psoriasis rashes from a previously published dataset based solely on molecular data from Trm1 cells (5).

To put their Trm1 hypothesis to the test, they tried to use scRNA-seq to diagnose six rashes that did not fit clinical criteria for either AD or psoriasis. Researchers had previously invited patients with the undiagnosed rashes to join a clinical trial on the IL4Rɑ-blocking AD-treatment dupilumab—three joined the trial. Two of the participants responded well to the treatment, and their rashes cleared up in two months. The other participant—who had a history of psoriasis—showed no improvement after three months of treatment.

The participants who responded to dupilumab treatment had Trm1 profiles similar to AD samples while the participant who did not respond well had a Trm1 profile similar to other analyzed psoriasis samples. The Trm1 profiles suggested that only patients with AD responded to the treatment, while those that did not likely had psoriasis.

Since the Trm1 profiles proved predictive, the researchers created an open-source web tool called RashX that allows researchers to upload 10x Genomics scRNA-seq immune cell dataset matrices and see how well their sample’s genetic signature aligns with other known AD or psoriasis samples. This tool is a small but important step toward incorporating elements of personalized medicine into the diagnosis and treatment of chronic inflammatory skin diseases.

A beacon of hope for personalized medicine

Scientists, journalists, and politicians alike have thrown around the terms “personalized medicine” and “precision medicine” for more than 20 years—The Wall Street Journal introduced the public to the term “personalized medicine” when it published the article, “New Era of Personalized Medicine: Targeting Drugs for Each Unique Genetic Profile” in 1999 (6). Researchers and clinicians have made significant progress in developing personalized treatments and high-resolution diagnostics in the oncology field, but precision medicine is in its infancy in many other fields. In particular, non-lethal diseases with a high patient burden are often overlooked in preclinical research (7).

This study is a proof of principle that personalized therapies and high-resolution diagnostics using single cell sequencing for patients with burdensome inflammatory skin disorders, including psoriasis, are within reach. The 50% of people with psoriasis who can’t find relief can find solace in the fact that their individual T-cell profile could help clinicians find a medication that works. If not, their unique profile can guide researchers to develop new and improved therapies that work for all people with inflammatory skin conditions.

Read the full story here and find out more about how single cell technology can strengthen your preclinical research in immune biology from our online resources.


  2. Nutten, S. Atopic Dermatitis: Global Epidemiology and Risk Factors. Ann Nutr Metab 66: 8-16 (2015). doi: 10.1159/000370220
  3. Liu, Y et al. Classification of human chronic inflammatory skin disease based on single-cell immune profiling. Sci Immunol 7: eabl9165 (2022). doi: 10.1126/sciimmunol.abl9165
  4. Liu, J. et al. RNA sequencing of psoriatic skin identifies pathogenic Tc17 cell subsets and reveals distinctions between CD8+ T cells in autoimmunity and cancer. J Allergy Clin Immunol 147: 2370–2380 (2021). doi: 10.1016/j.jaci.2020.11.028
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