Skin diseases both common and rare can be better diagnosed and treated using genetic fingerprinting based on knowledge gained through a new UC San Francisco study, according to researchers who developed new approaches for using the latest techniques to analyze gene activity in cells obtained from affected skin.

The study, published April 15, 2022, in Science Immunology, was led by Raymond Cho, MD, PhD, and Jeffrey Cheng, MD, PhD, associate professors in the Department of Dermatology at UCSF. This successful “precision medicine” approach is based on analysis of activity of thousands of genes within individual immune cells, profiling 41 different cell types per patient.

“Our study describes how advanced molecular profiling can be used to clearly distinguish different inflammatory skin diseases – including the common diseases psoriasis and atopic dermatitis – and also to better diagnose rarer and much more difficult cases,” Cheng said.

In the study, the researchers also describe the development of an online tool, called RashX, which allows the global clinical research community to enter and match genetic data from rash patients against those in the database, which are linked to specific skin diagnoses.

“Importantly, our work demonstrates how this publicly available framework will allow scientists all over the world to analyze and contribute their own patient-level data, thereby improving the diagnosis of puzzling cases,” Cheng said.

Psoriasis and atopic dermatitis are common and often serious skin diseases requiring different treatments. Psoriasis affects more than 7.5 million people in the United States, and even mild-appearing cases may trigger inflammatory processes that eventually lead to serious co-morbidities such as disabling arthritis. Atopic dermatitis affects about 26 million people in the U.S., and can cause relentless itching, skin oozing and cracking, and insomnia in severe cases.

Both diseases are inflammatory, but research has shown how distinct biochemical pathways trigger inflammation in the two conditions, leading to new biologic treatments specifically targeting different inflammatory pathways and immune cytokine molecules. However, the conditions often cannot be distinguished based on knowledge of symptoms, clinical examination, or even with the aid of tissue analysis, challenging even well-trained and experienced dermatologists, leading to misdiagnosis and inappropriate treatment, according to the authors.

Earlier studies often failed to identify consistent molecular differences between the diseases. Cho and Cheng speculated that a finer analysis of immune cell populations might reveal new cell-type-specific differences in gene activity between inflamed and healthy skin, or between different classes of skin disease.

In the new study, the researchers measured amounts of specific RNA molecules in individual cells. The “transcription” of specific RNA sequences from genes is a step in the cell’s activation and production of specific proteins. The study subjects included cases of classic psoriasis and atopic dermatitis, as well as clinically ambiguous rashes. An analysis of skin biopsies using the researchers’ new protocol revealed both commonalities and differences among the different diseases.

The researchers determined that lymphocytes known as skin-resident memory T cells contained the most distinguishable patterns of transcription between psoriasis and atopic dermatitis. Hundreds of genes were differently expressed in the two conditions and represent a signature that could correctly diagnose other patients.

When the researchers analyzed clinically ambiguous rash cases using the same panel of genes, they found that cases responding well to dupilumab – an atopic dermatitis treatment targeting the interleukin 4 receptor subunit α – exhibited patterns of gene expression more closely resembling atopic dermatitis. In contrast, a poorly responding case more closely resembled psoriasis.

“Our work is a clear example of the way in which a precision medicine approach shows promise for improving clinical outcomes,” Cheng concluded.

Source: University of California San Francisco

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