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Comprehensive analysis of treatment response phenotypes in rheumatoid arthritis for pharmacogenetic studies.

ABSTRACT: An individual patient's response to a particular drug is influenced by multiple factors, which may include genetic predisposition. Pharmacogenetic studies attempt to discover and estimate the contributions of genetic variants to the variability in response to a drug treatment. The task of identifying the genetic contribution is often complicated by response phenotypes that are based on imprecise or subjective clinical observations. Because the success of a pharmacogenetic study depends on the analysis of a heritable phenotype, it is important to identify phenotypes with a significant heritable component to ensure reliable and reproducible results in subsequent genetic association studies.We retrospectively analyzed data collected from 436 rheumatoid arthritis patients treated with golimumab during the phase III GO-FURTHER study. We investigated the reliability of several potential response outcomes after golimumab treatment. Using whole-genome sequencing of the clinical trial cohort, we estimated the heritability of each potential outcome measure. We further performed a longitudinal analysis of the clinical data to estimate variability of outcome measures over time and the degree to which each response metric could be confounded by placebo response.We determined that the high degree of within-patient variation over time makes a single follow-up visit insufficient to assess an individual patient's response to golimumab treatment. We found that different potential response outcomes had varying degrees of heritability and that averaging across multiple follow-up visits yielded higher heritability estimates than single follow-up estimates. Importantly, we found that the change in swollen and tender joint counts were the most heritable outcome metrics we tested; however, we showed that they are also more likely to be confounded by a placebo response than objective phenotypes like the change in C-reactive protein levels.Our rigorous approach to finding robust and heritable response phenotypes could be beneficial to all pharmacogenetic studies and may lead to more reliable and reproducible results.Clinicaltrials.gov NCT00973479 . Registered 4 September 2009.

SUBMITTER: Standish KA

PROVIDER: S-EPMC5427602 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Comprehensive analysis of treatment response phenotypes in rheumatoid arthritis for pharmacogenetic studies.

Standish Kristopher A KA Huang C Chris CC Curran Mark E ME Schork Nicholas J NJ

Arthritis research & therapy 20170512 1

<h4>Background</h4>An individual patient's response to a particular drug is influenced by multiple factors, which may include genetic predisposition. Pharmacogenetic studies attempt to discover and estimate the contributions of genetic variants to the variability in response to a drug treatment. The task of identifying the genetic contribution is often complicated by response phenotypes that are based on imprecise or subjective clinical observations. Because the success of a pharmacogenetic stud ...[more]

PMID: 28494788

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Project description:IntroductionRheumatoid arthritis (RA) is a complex and clinically heterogeneous autoimmune disease. Currently, the relationship between pathogenic molecular drivers of disease in RA and therapeutic response is poorly understood.MethodsWe analyzed synovial tissue samples from two RA cohorts of 49 and 20 patients using a combination of global gene expression, histologic and cellular analyses, and analysis of gene expression data from two further publicly available RA cohorts. To identify candidate serum biomarkers that correspond to differential synovial biology and clinical response to targeted therapies, we performed pre-treatment biomarker analysis compared with therapeutic outcome at week 24 in serum samples from 198 patients from the ADACTA (ADalimumab ACTemrA) phase 4 trial of tocilizumab (anti-IL-6R) monotherapy versus adalimumab (anti-TNFα) monotherapy.ResultsWe documented evidence for four major phenotypes of RA synovium - lymphoid, myeloid, low inflammatory, and fibroid - each with distinct underlying gene expression signatures. We observed that baseline synovial myeloid, but not lymphoid, gene signature expression was higher in patients with good compared with poor European league against rheumatism (EULAR) clinical response to anti-TNFα therapy at week 16 (P =0.011). We observed that high baseline serum soluble intercellular adhesion molecule 1 (sICAM1), associated with the myeloid phenotype, and high serum C-X-C motif chemokine 13 (CXCL13), associated with the lymphoid phenotype, had differential relationships with clinical response to anti-TNFα compared with anti-IL6R treatment. sICAM1-high/CXCL13-low patients showed the highest week 24 American College of Rheumatology (ACR) 50 response rate to anti-TNFα treatment as compared with sICAM1-low/CXCL13-high patients (42% versus 13%, respectively, P =0.05) while anti-IL-6R patients showed the opposite relationship with these biomarker subgroups (ACR50 20% versus 69%, P =0.004).ConclusionsThese data demonstrate that underlying molecular and cellular heterogeneity in RA impacts clinical outcome to therapies targeting different biological pathways, with patients with the myeloid phenotype exhibiting the most robust response to anti-TNFα. These data suggest a path to identify and validate serum biomarkers that predict response to targeted therapies in rheumatoid arthritis and possibly other autoimmune diseases.Trial registrationClinicalTrials.gov NCT01119859

Project description:BackgroundA multi-biomarker disease activity (MBDA) score has been validated as an objective measure of disease activity in rheumatoid arthritis (RA) and shown to track response to treatment with several disease-modifying anti-rheumatic drugs (DMARDs). The objective of this study was to evaluate the ability of the MBDA score to track response to treatment with rituximab.MethodsData were used from 57 RA patients from three cohorts treated with rituximab 1000 mg and methylprednisolone 100 mg at days 1 and 15. The MBDA score was assessed in serum samples obtained at baseline and 6 months. Spearman's rank correlation coefficients were calculated for baseline values, 6-month values, and change from baseline to 6 months (∆), between MBDA score and the following measures: disease activity score assessing 28 joints (DAS28) using erythrocyte sedimentation rate (ESR) or high-sensitivity C-reactive protein (hsCRP), ESR, (hs)CRP, swollen and tender joint counts assessing 28 joints (SJC28, TJC28), patient visual analogue scale for general health (VAS-GH), health assessment questionnaire (HAQ), and radiographic progression over 12 months using Sharp/van der Heijde score (SHS), as well as six bone turnover markers. Additionally, multivariable linear regression analyses were performed using these measures as dependent variable and the MBDA score as independent variable, with adjustment for relevant confounders. The association between ∆MBDA score and European League Against Rheumatism (EULAR) response at 6 months was assessed with adjustment for relevant confounders.ResultsAt baseline, the median MBDA score and DAS28-ESR were 54.0 (IQR 44.3-70.0) and 6.3 (IQR 5.4-7.1), respectively. MBDA scores correlated significantly with DAS28-ESR, DAS28-hsCRP, ESR and (hs)CRP at baseline and 6 months. ∆MBDA score correlated significantly with changes in these measures. ∆MBDA score was associated with EULAR good or moderate response (adjusted OR = 0.89, 95% CI = 0.81-0.98, p = 0.02). Neither baseline MBDA score nor ΔMBDA score correlated statistically significantly with ∆SHS (n = 11) or change in bone turnover markers (n = 23), although ∆SHS ≥ 5 was observed in 5 (56%) of nine patients with high MBDA scores.ConclusionsWe have shown, for the first time, that the MBDA score tracked disease activity in RA patients treated with rituximab and that change in MBDA score reflected the degree of treatment response.

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Comprehensive analysis of treatment response phenotypes in rheumatoid arthritis for pharmacogenetic studies.

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Comprehensive analysis of treatment response phenotypes in rheumatoid arthritis for pharmacogenetic studies.

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