The Future of Precision Medical Care for Rheumatic Disease

Virginia Pascual, MD, director of the Gale and Ira Drukier Institute for Children’s Health at Weill Cornell Medicine, New York, discusses precision medical care for rheumatic diseases, as well as advancements in biomarker identification in systemic lupus erythematosus (SLE).

A transcript of this interview is available below.

Video Transcript:

My name is Virginia Pascual, and I am a professor of pediatrics and director of the Gale and Ira Drukier Institute for Children’s Health at Weill Cornell Medicine, in New York City. I am a pediatric rheumatologist, interested in understanding what causes chronic inflammatory diseases that start in children and how we can better find new treatments.

Could you provide an overview of your presentation at ACR entitled “Precision Medicine for Rheumatic Disease: Closer Than You Think”?

During my presentation today at the American College of Rheumatology (ACR) annual meeting, I spoke about the role of precision medicine in rheumatology. Precision medicine is an approach that tries to understand what is going on in a patient according to what is the genetic background, genetic make-up of that particular patient and how the environment and the lifestyle of that patient might be modifying the genetic make-up and giving rise to a peculiar kind of disease that might respond better or worse to a particular drug.

What are the goals for providing precision medical care?

There are several goals for providing precision medicine in clinical care. One is to be able to predict that a disease is going to show up. Another very important one is to try to prevent that disease from happening. If we are able to develop tools that will tell us if a particular individual is predisposed with a high probability to develop a particular disease, we might be able to intervene even before the disease has shown up; which is, in the case of rheumatic diseases, before inflammation has taken place. That will lead to a much better outcome for the patient.

What emerging technologies have been developed that will offer opportunities for precision medicine in rheumatic diseases?

The good news about precision medicine today is that there is a tremendous expansion in the number of technologies that allow us to look at patients directly, generate big data, collect these big data, and interpret the data in a way that can make sense about what is happening, what is predisposing the patient to the disease, what are the most important pathways that are responsible for the development of the disease in that individual, and hopefully what might be the best treatments for that particular individual. We realize that diseases that might show up very similarly in individuals might actually be caused by a combination of unique factors in each individual. And only understanding those unique factors is going to lead us to finding the best therapy for each patient.

Can you elaborate on the challenges of precision medicine, specifically with regards to systemic lupus erythematosus?

There are unfortunately many challenges to precision medicine. One of the challenges is how to integrate the enormous amount of data that we are able to generate these days, and how we can better interpret that data toward one goal: that is, understanding disease and finding the unique therapy that a unique patient requires. 

There are different levels of complexity, and one level of complexity that looks very simple but is very important is collection of data. So, systems biology — the genomic, proteomic, metabolomics data, and many other “omics” that we can collect today — is very important but it needs to be placed in the context of the unique clinical symptoms and type of disease that a particular patient has. So, collecting the data from the clinic to the laboratory looks like something very simple but actually is very important.  Reliability of data collection and standardization of data collection are important components that might be challenging, and eventually integration of all the “omic” data and finally interpretation with the right computational biology tools. But again, these will lead us to a change in clinical practice and will be useful for the clinician. This is the ultimate goal of precision medicine.

Could you discuss advancements in biomarker identification in SLE, and how these could be used to stratify patients towards a more rational design of clinical trials?

There are many different sources of potential biomarkers in systemic lupus erythematosus (lupus). We have been relying for many years on autoantibodies and they are used in the clinic and are very good biomarkers, but they might not be useful enough to predict who is going to develop more severe vs milder disease. Definitely, they are not good to tell us who will be responding to one drug vs another. So, there is today a major effort in developing biomarkers in different aspects of systems biology.  

Genetics is very important and there has been a major effort in identifying genetic risk loci that might predispose eventually in the future, maybe stratifying patients according to different genetic make-up.  There are studies today more and more on epigenetics. They are not yet “there,” as the information we have today is not enough to classify patients, but I am sure that integrating this epigenetic data will eventually be very fundamental to understanding the complexity of lupus.

We and others have looked at transcriptional biomarkers, and I think that we have made progress there.  In the field of pediatric lupus, we have been able to classify patients according to what transcriptional pathways best correlate with disease flares. By doing that, we can already stratify approximately 7 major groups of patients. Of course, this is something that will need to be proven in the future and hopefully will be with implementation of clinical trials that take these markers into consideration and will enable us to determine their value. If we are right, we should be able to choose some targets that should be more amenable to some subsets of patients than others. So, transcriptional data, I think, are getting closer to being able to stratify these patients.

There are many other approaches, as we have discussed before, that eventually when they are integrated with genetics, epigenetics, and transcriptomics, will give us much more accuracy. Metabolomics no doubt is going to be one of those. Studies of the microbiome composition of the gut and the mucosal surfaces of the skin of these patients hopefully will also be important clues … and going back to the first one that we were discussing, autoantibodies. Today we have very powerful technologies to dig very deeply into what is the repertoire of autoantibodies that this patient might have, and I am pretty sure that these will also lead us to better stratification.