NEW YORK (GenomeWeb) – A team of scientists from seven institutions has identified a 415-gene expression signature for systemic sclerosis that could be developed into a diagnostic tool to assess the severity of the disease in a patient.
Systemic sclerosis is an autoimmune disease that causes scar-like thickening of a person's internal organs, such as the kidneys and lungs, and skin. The disease affects approximately 100,000 people annually in the US, according to Monique Hinchcliff, paper co-author and associate professor of medicine at Northwestern University Feinberg School of Medicine.
Currently, researchers don't know what causes systemic sclerosis, and the US Food and Drug Administration has not approved any drugs to treat patients diagnosed with the disease. Consequently, many patients are treated with drugs approved for other diseases, but each drug is clinically effective in only a small fraction of patients.
The only way to determine whether a patient is responding to treatment is a test called the modified Rodnan skin score, which requires physicians to pinch their patients' skin in 17 places to determine thickness which is rated on a scale of 0 to 3 in each location. These scores are added together for a maximum score of 51, which indicates the most severe cases.
Because of the nature of the test, it can take up to two years for physicians to determine whether a treatment is having any effect. Researchers agree that a more precise measure of disease progression for systemic sclerosis has been long overdue.
To find a better solution, the researchers downloaded four publicly available gene expression datasets of systemic sclerosis skin biopsies from two clinical centers to identify a set of genes that could be used to mark disease progression.
The team analyzed the genes within the dataset by statistically comparing expression effect, narrowing it down to 415 genes that had a clear expression change pattern that indicated disease severity. The researchers used these patterns to develop the basis for a test that they called the Systemic Sclerosis Skin Severity Score, or 4S.
The research team used existing systemic sclerosis patient data sets from patients from five additional centers to validate the new test. They also included data from healthy participants who served as controls.
"The data for all the healthy skin fell within one bubble," Purvesh Khatri, senior author on the study and assistant professor of medicine at Stanford University, said in a statement, "while all the data for the scleroderma patients fell within another."
Additionally, the researchers looked at data from a cohort of Northwestern University patients who had been repeatedly tested with the modified Rodnan skin score throughout treatment. The team applied the 4S test to these patients and found that they could distinguish patients who were improving with treatment and those who were not.
"In the data from Northwestern, all the patients were getting exactly the same treatment, the same drug," Shane Lofgren, a research associate at Stanford and co-author on the paper, said in a statement. "Yet we were able to predict a year before the clinician which patients were getting better and which were getting worse."
The researchers said that the 4S test needs further validation through clinical trials, but they are hopeful it will become a useful tool to help track disease progression and improve treatment outcomes for patients.
The team also uncovered a gene-activity signal which suggests the involvement of epidermal growth factor receptors in the disease. "We showed that EGFR is consistently upregulated [in systemic sclerosis]," Khatri said. This indicates that drugs approved by the FDA for treating EGFR-related conditions may be a possible treatment option for systemic sclerosis patients, he said.
Khatri and his colleagues plan to begin giving EGFR-inhibiting drugs to mice with conditions similar to systemic sclerosis to see if it might be an effective option.