NINE-GENE BIOMARKER PAVES WAY FOR TAILORED PSORIASIS TREATMENTS

Psoriasis is a common inflammatory skin disease linked to several long-term health conditions, such as heart disease, arthritis and type 2 diabetes, and has a substantial impact on sufferers' quality of life. Although the World Health Organization has highlighted the need for more personalized care for patients, progress has been limited by the lack of reliable biomarkers to guide clinical decision making.

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Now, a major new study has uncovered gene clues that could pave the way to personalized psoriasis treatments. The research is published in the journal Communications Medicine.

New gene patterns offer fresh insight

Experts from Newcastle University, UK, and Queen Mary University of London led an analysis of clinical and biological data from a large cohort of patients who have started biological therapies. Researchers used state-of-the-art computational and AI techniques to unravel hidden patterns in the complex gene expression relationships in both skin and blood, linking these to clinical features.

The findings reveal new molecular signatures of disease severity, metabolic factors and genetic variants, offering the potential for improved disease management and personalized care.

Nick Reynolds, Professor of Dermatology and Director of Diagnostics at Newcastle University and Honorary Consultant Dermatologist at Newcastle Hospitals NHS Foundation Trust, is senior author on the study.

He said, "This research represents the most comprehensive and integrated look at gene expression in blood, lesional, and non-lesional skin in psoriasis to build a clearer picture of how the severity of the disease relates to underlying genetics and environmental influences, including being overweight with a high BMI.

"By analyzing data from more than 700 samples, we've uncovered new molecular patterns that deepen our understanding of how psoriasis varies from person to person and responds to powerful biologic drugs. These insights bring us a step closer to recognizing distinct groups within the condition and, ultimately, to supporting more personalized approaches to care."

The researchers identified a 9-gene biomarker linked to psoriasis severity, along with specific genetic variants (HLADQA101 and HLADRB115) associated with more severe baseline disease. They also found a 14-gene signature connected to BMI in unaffected skin and to disease severity in affected lesional skin, highlighting the role of metabolic factors.

Additionally, a blood-based signal linked to white blood cell activity was seen only after the medication adalimumab was administered, suggesting these immune cells play an important role in driving psoriatic inflammation and may be a target for adalimumab.

Professor Mike Barnes, Queen Mary University of London, one of the other senior authors, said, "This is one of the largest, highly curated, multi-modal studies of psoriasis to date. To maximize the value of our data for the research community, we have made it possible to directly explore through a web portal to evaluate genes and pathways of interest in psoriasis disease pathology."

Lifelong condition affecting many

Psoriasis is a skin condition that causes inflammation in the skin resulting in well-defined scaly plaques (patches) which can be itchy and painful. Importantly, the inflammation is more than skin deep and can affect internal organs, leading to conditions such as arthritis. It affects around two in 100 people in the UK. It can start at any age, but most often develops in adults between 20 and 30 years old and between 50 and 60 years old. It affects men and women equally.

Melinda Spencer, Research Manager from the Psoriasis Association, said, "This study brings us another step closer to personalized care for people living with psoriasis. The discoveries from this research provide real hope for treatments that will make a meaningful difference to Psoriasis Association members and the wider public affected by the condition."

More information: Ashley Rider et al, Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity, Communications Medicine (2026). DOI: 10.1038/s43856-025-01325-4

Provided by Newcastle University

This story was originally published on Medical Xpress.

2026-02-04T21:49:07Z