The Future of Treatment for Psoriatic Arthritis
The Future of Treatment for Psoriatic Arthritis
Treatment response cannot be accurately predicted, nor can an individual's susceptibility to potential treatment-related adverse events. In PsA, treatment is selected empirically, based on the severity of disease, the presence of contraindications, patient preference and cost. As prescribers, we assign the potential for treatment success or failure based on statistics garnered from clinical trial data, yet individuals with disease can never be assured that they will be among the fortunate proportion to attain therapeutic benefit or avoid potentially serious side effects.
Biomarkers are biological factors that can be objectively measured and represent markers of physiological, pathological and/or pharmacological response. To date, a biomarker with the prognostic and diagnostic significance of rheumatoid factor or anticitrullinated protein antibodies used in RA has not been identified in PsA, nor has a biomarker that will predict response to targeted biological treatments, such as TNFi or IL-12/-23 blockade.
Our research group identified four serum biomarkers from a panel of 12 (high-sensitivity CRP, osteoprotegerin, MMP-3 and the ratio of C-propeptide of type II collagen to collagen fragment neoepitopes Col2–3/4long mono (C2C) that were independently associated with PsA. We have also found that serum MMP-3 levels predict response to therapy with TNFi. However, their role in diagnosis, prognosis and treatment response, as with other putative biomarkers requires study in longitudinal prospective studies.
Data from the GO-REVEAL trial have shown that a panel of serum-based biomarkers may have clinical application in predicting therapeutic response to golimumab (n = 100). In total, 11 markers (including MMP-3, CRP, VEGF, IL-16 and ICAM-1 from a panel of 92 measured at baseline were shown to be predictive of an ACR20 and/or improvement in DAS28 by week 14, while a smaller group of four proteins was predictive of a PASI75. Models of these predictor biomarkers were constructed to identify the combination that provides the greatest predictive strength, with adiponectin and factor VII appearing in the models for all three clinical end points.
The identification of sensitive and specific biomarkers for PsA in patients with cutaneous manifestations only would allow early identification and treatment of PsA which, as outlined above, could significantly decrease morbidity and disability through preservation of joint function. Villanova et al. present an informative review on the role of biomarkers in assessing prognosis and treatment response in psoriatic disease, and describe genetic, blood, tissue and transcriptional biomarkers that have been explored in psoriatic disease. These authors suggest that a 'molecular signature' that incorporates biomarker data from these four sources is more likely to yield diagnostic and prognostic results, than use of a single biomarker, or that from a single source.
The application of pharmacogenetics, or the use of genetic markers to predict efficacy and toxicity, will increase prescribers' and patients' certainty that a medication will safely ameliorate the disease process. While pharmacogenetic research in PsA is in its infancy, studies in MTX have shown that genetic polymorphisms in the folate pathway enzymes were associated with treatment response. Similarly, genetic variance in the TNF apparatus has been shown to be predictive of response to TNFi.
While these findings are of interest to rheumatologists, their confirmation in large, controlled, prospective studies is required, along with the pursuit of other single nucleotide polymorphisms and genetic variants.
Biomarkers & Pharmacogenetics
Treatment response cannot be accurately predicted, nor can an individual's susceptibility to potential treatment-related adverse events. In PsA, treatment is selected empirically, based on the severity of disease, the presence of contraindications, patient preference and cost. As prescribers, we assign the potential for treatment success or failure based on statistics garnered from clinical trial data, yet individuals with disease can never be assured that they will be among the fortunate proportion to attain therapeutic benefit or avoid potentially serious side effects.
Biomarkers are biological factors that can be objectively measured and represent markers of physiological, pathological and/or pharmacological response. To date, a biomarker with the prognostic and diagnostic significance of rheumatoid factor or anticitrullinated protein antibodies used in RA has not been identified in PsA, nor has a biomarker that will predict response to targeted biological treatments, such as TNFi or IL-12/-23 blockade.
Our research group identified four serum biomarkers from a panel of 12 (high-sensitivity CRP, osteoprotegerin, MMP-3 and the ratio of C-propeptide of type II collagen to collagen fragment neoepitopes Col2–3/4long mono (C2C) that were independently associated with PsA. We have also found that serum MMP-3 levels predict response to therapy with TNFi. However, their role in diagnosis, prognosis and treatment response, as with other putative biomarkers requires study in longitudinal prospective studies.
Data from the GO-REVEAL trial have shown that a panel of serum-based biomarkers may have clinical application in predicting therapeutic response to golimumab (n = 100). In total, 11 markers (including MMP-3, CRP, VEGF, IL-16 and ICAM-1 from a panel of 92 measured at baseline were shown to be predictive of an ACR20 and/or improvement in DAS28 by week 14, while a smaller group of four proteins was predictive of a PASI75. Models of these predictor biomarkers were constructed to identify the combination that provides the greatest predictive strength, with adiponectin and factor VII appearing in the models for all three clinical end points.
The identification of sensitive and specific biomarkers for PsA in patients with cutaneous manifestations only would allow early identification and treatment of PsA which, as outlined above, could significantly decrease morbidity and disability through preservation of joint function. Villanova et al. present an informative review on the role of biomarkers in assessing prognosis and treatment response in psoriatic disease, and describe genetic, blood, tissue and transcriptional biomarkers that have been explored in psoriatic disease. These authors suggest that a 'molecular signature' that incorporates biomarker data from these four sources is more likely to yield diagnostic and prognostic results, than use of a single biomarker, or that from a single source.
The application of pharmacogenetics, or the use of genetic markers to predict efficacy and toxicity, will increase prescribers' and patients' certainty that a medication will safely ameliorate the disease process. While pharmacogenetic research in PsA is in its infancy, studies in MTX have shown that genetic polymorphisms in the folate pathway enzymes were associated with treatment response. Similarly, genetic variance in the TNF apparatus has been shown to be predictive of response to TNFi.
While these findings are of interest to rheumatologists, their confirmation in large, controlled, prospective studies is required, along with the pursuit of other single nucleotide polymorphisms and genetic variants.
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