A newly identified genetic signature may provide clues into the mechanisms underlying systemic lupus erythematosus (SLE), and open new potential avenues to personalized treatments.
The research, “Integrated, multi-cohort analysis reveals unified signature of systemic lupus erythematosus,” was published in the journal JCI Insight.
Gene expression studies measure which genes are ‘turned on,’ and to what extent. Collectively, this is called the transcriptome. Such studies can be useful for understanding processes involved in diseases like SLE, but they are often limited by small groups of patients that cannot accurately reflect the diversity of SLE in different people.
Researchers at Stanford University School of Medicine had previously developed a program called MetaIntegrator to help overcome these limitations. Put simply, this program is designed to extract and analyze data from multiple different datasets in order to identify gene expression signatures.
The research included 40 datasets with data covering 7,471 people with SLE, other autoimmune diseases or infections, and healthy volunteers. Importantly, these datasets included information from 17 centers across five countries, and were based on multiple tissue types (such as blood, skin, and kidney samples). Data were also generated using diverse technologies.
Six of these datasets with 370 samples were initially fed into MetaIntegrator, which identified a 93-gene signature that the researchers defined as the “SLE MetaSignature.” Most of the genes (82) were up-regulated — meaning higher activity, or greater production of RNA – while the rest were down-regulated (lower activity) in people with SLE compared to healthy volunteers.
The signature was validated using the remaining datasets. Then, it was used to calculate the “SLE MetaScore” for each sample.
This score was highly effective at distinguishing people with SLE from those without it in the six datasets used in the primary analysis, and in the eight datasets (with 2,407 samples) used to validate the results.
Notably, these scores were higher in SLE patients regardless of the type of tissue analyzed, suggesting that the altered gene expression occurs systemically. SLE MetaScores also correlated closely with inflammatory markers (such as the erythrocyte sedimentation rate) and measures of disease activity like the SLE Disease Activity Index (SLEDAI).
These findings were then tested in a group of children with SLE, leading to similar results.
Most genes in the SLE MetaSignature have known functions in immunity. A total of 46 of the 93 genes had been linked previously to SLE, but 47 had not.
Many of the genes were involved in responses to interferons, a potent inflammatory signaling molecule with known roles in SLE. Some of the other genes were linked to the activity of immune cells called neutrophils, which have also been implicated in SLE.
Yet, 14 of the identified genes were not related to either interferon or neutrophil-related pathways. As such, they “provided an opportunity to explore new disease mechanisms that underlie SLE,” the team wrote.
Among their roles were oxidative stress — when the generation of toxic reactive oxygen molecules outweighs the body’s antioxidant defenses — and immune function. But six of the 14 genes have not been well characterized, and have no known role in autoimmune diseases.
“Scientists often fall prey to the ‘streetlight effect’ — looking for answers where the light is better rather than where the truth is more likely to lie,” the researchers wrote. “While many of the Under-appreciated SLE MetaSignature genes ‘make mechanistic sense’, we should not lose sight of the six genes which had previously been in the shadows but are now illuminated.”
The investigators suggested that such genetic studies may help in developing personalized medicines. They might “lead to identification of multiple drug targets and corresponding therapies, increasing the number of drugs available to treat SLE patients,” they added.
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