Elucidation: Better Biomarkers Could Power Precision Medicine for Autoimmune Disease

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Precision medicine has long been a tantalizing goal for the pharmaceutical and healthcare industries. Fields such as oncology and rare diseases have benefited greatly from implementation of genome-guided care. Drug developers likewise have made strides with biomarker-aided discovery programs and stratification for clinical trials. Current indications suggest that autoimmune diseases will be the next major focus of personalized medicine.

The goal of precision medicine often is described as “getting the right drug to the right patient at the right time.” Through this model, patients would enjoy better outcomes and fewer side effects than in the traditional “blockbuster medicine” model. In practice, the biopharmaceutical industry increasingly has taken significant steps toward this goal. As early success stories in precision medicine, targeted cancer therapies have shown remarkable success in the small proportion of patients for whom they are appropriate. Proponents of precision medicine often do not mention the advantages offered by clinical trials, but such studies are important to transform healthcare. Careful stratification of patients enrolled in clinical trials can increase the likelihood of success for targeted drug candidates.

Mounting evidence suggests that similar benefits soon will be translated to the autoimmune disease community thanks to new efforts in drug development and diagnostics. This would be a sorely needed development because autoimmune diseases affect more than 23 million people in the United States and represent an annual healthcare cost of US$100 billion.

DNA and RNA Biomarkers: To effectuate precision medicine, the most pressing step involves discovery and validation of clinically actionable biomarkers. Again, we can look to cancer for examples: DNA and protein biomarkers have made it possible to stratify tumors for targeted therapies, develop companion diagnostics for those treatments, select patients for clinical trials, and monitor patient responses to therapy and disease progression.

Identifying useful biomarkers for autoimmune diseases requires progressing beyond DNA variations. Such diseases are dynamic, with patients suffering unpredictable flares and wide-ranging symptoms. A DNA biomarker can provide a simple yes-or-no answer about whether a patient has an autoimmune disease, but only RNA biomarkers can reveal the current status of gene activity and provide insight into a disease state at a given time. Proper interpretation of those biomarkers requires longitudinal monitoring to understand what is “normal” for each patient and assess changes in response to treatment.

Modular Genomics: Although biomarker development for autoimmune diseases is in early stages, promising candidates already have emerged. For instance, some immune-pathway–specific biomarkers have been shown to correlate with disease activity and progression as well as therapy response. New treatments for autoimmune diseases include drugs that target autoimmune-related disease mechanisms such as the Jak/STAT signaling pathway and expression levels of specific cytokines within relevant pathways.

Those immune-pathway biomarkers were developed using an innovative approach known as modular transcriptome repertoire analysis, or simply modular genomics. The idea is to analyze collections of transcriptome data generated from a particular biological system (e.g., blood) to identify sets of genes that appear to be coregulated and correlated with a specific physical trait, clinical condition, therapeutic response, or biological pathway. This method is useful particularly for evaluating interactions among key elements in a biological system.

Because modular genomics is a relatively new approach, scientists have yet to agree on methods to select sets of genes (or modules) that best represent a given pathway. So opinions about any given biomarker’s utility run the gamut. In more mature fields (e.g,, cancer), critical biomarkers are widely agreed upon. But gene-expression biomarkers vary significantly from study to study (type 1 interferon is a classic example), making it more difficult for scientists to reach consensus on RNA-based biomarkers. In this uncertain landscape, pharmaceutical and biotechnology companies run the risk of using different gene signatures that select the same group of patients, leading to a chaotic situation for developing diagnostics and drugs. Clearly, more in-depth studies of biomarker candidates are needed to reach industrywide agreement about their utility and specificity for development of standardized tests.

Still, scientists have an enormous opportunity for RNA-based biomarkers to inform development of diagnostics and drugs for patients with autoimmune diseases. Scientists in academia and industry should come together to address the challenges of standardization and consensus-building around biomarkers derived from modular genomic studies. The results will improve general understanding of autoimmune disease and accelerate creation of new diagnostics and therapies for this large and diverse patient community.

Robert Terbrueggenis CEO and founder of DxTerity, 19500 South Rancho Way Suite 116, Rancho Dominguez, CA 90220; 1-310-537-7857; info@dxterity.com, https://dxterity.com. DxTerity is a molecular diagnostic and information company bringing the power of precision medicine to autoimmune diseases with from-home RNA monitoring.

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