DESTIN, FLA. – Personalized medicine – picking the right patient for the right drug – is a hot topic in medicine in general, but the approach is challenging for rheumatoid arthritis because of its heterogeneity, according to Dr. Arthur Kavanaugh.
"How do we get to personalized medicine? Do we have a biomarker for any of our treatments? Well, ‘biomarker’ is sort of a generic term. We actually don’t want a biomarker – anything is a biomarker. What we want are surrogate markers. We want something that is so strong, that we can measure that and predict what’s going to happen," Dr. Kavanaugh, professor of medicine and director of the Center for Innovative Therapy at the University of California, San Diego, said at the annual Congress of Clinical Rheumatology.
Dr. Arthur F Kavanaugh
He used the example of CD4 count in HIV infection and dual-energy x-ray absorptiometry scans for fragility fractures as useful surrogate markers.
"Some people would say ‘cholesterol for atherosclerotic disease.’ Well, you don’t care about the cholesterol – you care about whether you’re going to have a heart attack. So a surrogate marker is a much higher standard," he explained.
In rheumatology, there is a lack of such surrogate markers.
"We have lots of biomarkers, but there’s really nothing that’s a surrogate marker in rheumatology that will allow us to pick one treatment over another. It’s something we would love to see, and it’s been looked at in a number of ways," he said.
For example, the genomic approach was expected to be the answer.
"For those of us who were around before the human genome was sequenced – that was going to be the answer. Go to the doctor, swab your cheek, turn that in to the nurse, walk out with a prescription based on your genes – that was going to be it. It hasn’t worked out that way; humans are complicated," he said.
Proteomics, glycomics, immunomics – all kinds of things have been looked at, Dr. Kavanaugh pointed out.
For awhile, geneticists were promising that if they could just get enough samples, they would be able to figure out which patients should get which drug.
"Well, they kind of failed, and now I think a very interesting article that just came out in Nature is just sort of them surrendering and saying, ‘OK, what we’ve done now is take the treatments you know work, and we will figure out which genes predict that,’" he said.
The paper is a meta-analysis of genome-wide association studies, and it looks at how RA genetics can contribute to drug discovery (Nature 2014;506: 376-81).
The authors found about 100 loci that seemed to be informative, Dr. Kavanaugh said. "It’s very interesting, because ... a lot of the loci map to therapies that we have now."
So maybe this backwards "bedside-to-bench" approach will prove useful for providing more personalized medicine.
Epigenetics might also have promise for advancing personalized medicine for RA.
"It’s fascinating. We don’t know so much about it, but of course they are heritable alterations that don’t change the DNA sequence," he said.
Examples include DNA methylation, micro-RNAs, which affect the expression of genes, and histone modification.
These can be inherited, and while the concept opens up some politically charged and socioeconomic issues with respect to how epigenetic modifications might affect an individual, it’s an area that may have some relevance in personalized medicine, Dr. Kavanaugh said.
In some ways, the progress with personalized medicine in RA has been hampered by the results in other fields.
"There’s been so much progress in oncology, but they have more monogenic disease," he said, explaining that a single abnormality can predict whether a drug will work in 0% or 80% of cases. "That’s personalized medicine, but I don’t think we have that for rheumatic disease. It would be great if we did, but I don’t think we’re there yet."
In the rheumatic diseases, it may be that things have to be considered in a different, more complex way, by using combinations of biomarkers, for example.
In a poster presented at EULAR in 2013, based on the ADACTA study, he and his colleagues reported that none of a number of single biomarkers predicted response, but that patterns of biomarkers – in this case serum markers that correlated with immunologic phenotypes in the synovium from previous studies – appeared to have predictive value.
"Of course, this is predicting the past ... we have to see if this kind of stuff holds up. We would all love to have it. This is the next challenge – using it in a more rational way so that we can get our patients to the best possible place," he said.