COL1A1 proximal promoter topology regulates its transcriptional response to transforming growth factor ß.

OBJECTIVE: The COL1A1 proximal promoter contains two GC-rich regions and two inverted CCAAT boxes. The transcription factors Sp1 and CBF bind to the GC sequence at -122 to -115 bp and the inverted CCAAT box at -101 to -96 bp, respectively, and stimulate COL1A1 transcriptional activity. METHODS: To further define the regulatory mechanisms controlling COL1A1 expression by Sp1 and CBF, we introduced 2, 4, 6, or 8 thymidine nucleotides (T-tracts) at position -111 bp of the COL1A1 gene promoter to increase the physical distance between these two binding sites and examined in vitro the transcriptional activities of the resulting constructs and their response to TGF-ß1.`. RESULTS: Insertion of 2 or 4 nucleotides decreased COL1A1 promoter activity by up to 70%. Furthermore, the expected increase in COL1A1 transcription in response to TGF-ß1 was abolished. Computer modeling of the modified DNA structure indicated that increasing the physical distance between the Sp1 and CBF binding sites introduces a rotational change in the DNA topology that disrupts the alignment of Sp1 and CBF binding sites and likely alters protein-protein interactions among these transcription factors or their associated co-activators. CONCLUSION: The topology of the COL1A1 proximal promoter is crucial in determining the transcriptional activity of the gene and its response to the stimulatory effects of TGF-ß1.

Adjustment of the multi-biomarker disease activity score to account for age, sex and adiposity in patients with rheumatoid arthritis.

OBJECTIVE: To develop and evaluate an adjusted score for the multi-biomarker disease activity (MBDA) test to account for the effects of age, sex and adiposity in patients with RA. METHODS: Two models were developed to adjust MBDA score for age, sex and adiposity, using either serum leptin concentration or BMI as proxies for adiposity. Two cohorts were studied. A cohort of 325 781 RA patients who had undergone commercial MBDA testing and had data for age, sex and serum leptin concentration was used for both models. A cohort of 1411 patients from five studies/registries with BMI data was used only for the BMI-adjusted MBDA score. Univariate and multivariate linear regression analyses evaluated the adjusted MBDA scores and conventional clinical measures as predictors of radiographic progression, assessed in terms of modified total Sharp score (ΔmTSS). RESULTS: Two models were developed, based on findings that MBDA score was higher in females than males and increased with age, leptin concentration and BMI. In pairwise regression analyses, the leptin-adjusted (P = 0.00066) and BMI-adjusted (P = 0.0027) MBDA scores were significant independent predictors of ΔmTSS after adjusting for DAS28-CRP, whereas DAS28-CRP was not, after adjusting for leptin-adjusted (P = 0.74) or BMI-adjusted (P = 0.87) MBDA score. Moreover, the leptin-adjusted MBDA score was a significant predictor of ΔmTSS after adjusting for the BMI-adjusted MBDA score (P = 0.025) or the original MBDA score (0.027), whereas the opposite was not true. CONCLUSION: Leptin-adjusted MBDA score significantly adds information to DAS28-CRP and the original MBDA score in predicting radiographic progression. It may offer improved clinical utility for personalized management of RA.

External validation of a multi-biomarker-based score for predicting risk of cardiovascular disease in patients with rheumatoid arthritis.

BACKGROUND: A multi-biomarker disease activity (MBDA)-based cardiovascular disease (CVD) risk score was developed and internally validated in a Medicare cohort to predict 3-year risk for myocardial infarction (MI), stroke or CVD death in patients with rheumatoid arthritis (RA). It combines the MBDA score, leptin, MMP-3, TNF-R1, age and four clinical variables. We are now externally validating it in a younger RA cohort. METHODS: Claims data from a private aggregator were linked to MBDA test data to create a cohort of RA patients ≥18 years old. A univariable Cox proportional hazards regression model was fit using the MBDA-based CVD risk score as sole predictor of time-to-a-CVD event (hospitalized MI or stroke). Hazard ratio (HR) estimate was determined for all patients and for clinically relevant subgroups. A multivariable Cox model evaluated whether the MBDA-based CVD risk score adds predictive information to clinical data. RESULTS: 49,028 RA patients (340 CVD events) were studied. Mean age was 52.3 years; 18.3% were male. HR for predicting 3-year risk of a CVD event by the MBDA-based CVD risk score in the full cohort was 3.99 (95% CI: 3.51-4.49, p = 5.0×10-95). HR were also significant for subgroups based on age, comorbidities, disease activity, and drug use. In a multivariable model, the MBDA-based CVD risk score added significant information to hypertension, diabetes, tobacco use, history of CVD, age, sex and CRP (HR = 2.27, p = 1.7×10-7). CONCLUSION: The MBDA-based CVD risk score has been externally validated in an RA cohort that is younger than and independent of the Medicare cohort that was used for development and internal validation.

Patterns of biologic agent utilization among patients with rheumatoid arthritis: a retrospective cohort study.

BACKGROUND: The role of biologic therapies in the treatment of rheumatoid arthritis has expanded, but dosing patterns in the first versus subsequent lines of therapy have not been thoroughly explored. METHODS: In order to describe patterns of biologic agent utilization among patients with rheumatoid arthritis, health care claims data on use of abatacept, rituximab, or the anti-tumor necrosis factor (TNF) agents etanercept, adalimumab, and infliximab in first- or subsequent-line settings were used to form patient cohorts. Variables included: starting dose (first administration or fill), maintenance dose (third administration or fill), average dose, dose escalation, inter-infusion interval, and discontinuation (gap in therapy > 60 days or switch). Time to discontinuation was assessed with Kaplan-Meier curves and Cox proportional hazards models. RESULTS: Over 1 year, average (SD) doses of first-line etanercept (N = 1593; 45.4 [8.8] mg/week), adalimumab (N = 1040; 40.7 [10.4] mg/2 weeks), and abatacept (N = 360; 715.4 [214.5] mg/4 weeks) were similar to the starting and maintenance doses; the average infliximab dose (N = 538; 441.0 [209.2] mg/8 weeks) was greater than the starting and maintenance doses. Trends in the subsequent-line anti-TNF cohorts were similar. The percentages with a dose escalation or discontinuation were greater in the subsequent-line anti-TNF cohorts. The proportion with a dose escalation was greatest for the infliximab cohorts (61.2% first-line and 80.2% subsequent-line). The average period between abatacept infusions was 4.8 [1.4] weeks (4-week approved schedule); and 6.8 [2.6] months between rituximab courses (currently approved schedule is 6 months). Time to discontinuation was significantly shorter for subsequent-line than first-line anti-TNF therapy (median 9.7 vs. 12.5 mo; p < 0.001). The hazard ratio for discontinuing subsequent-line versus first-line anti-TNF therapy was 1.177 (p < 0.001). CONCLUSIONS: Subsequent-line anti-TNF therapy cohorts had higher rates of discontinuation, dose escalation, and shorter time to discontinuation than first-line anti-TNF cohorts.

Derivation and internal validation of a multi-biomarker-based cardiovascular disease risk prediction score for rheumatoid arthritis patients.

BACKGROUND: Rheumatoid arthritis (RA) patients have increased risk for cardiovascular disease (CVD). Accurate CVD risk prediction could improve care for RA patients. Our goal is to develop and validate a biomarker-based model for predicting CVD risk in RA patients. METHODS: Medicare claims data were linked to multi-biomarker disease activity (MBDA) test results to create an RA patient cohort with age ≥ 40 years that was split 2:1 for training and internal validation. Clinical and RA-related variables, MBDA score, and its 12 biomarkers were evaluated as predictors of a composite CVD outcome: myocardial infarction (MI), stroke, or fatal CVD within 3 years. Model building used Cox proportional hazard regression with backward elimination. The final MBDA-based CVD risk score was internally validated and compared to four clinical CVD risk prediction models. RESULTS: 30,751 RA patients (904 CVD events) were analyzed. Covariates in the final MBDA-based CVD risk score were age, diabetes, hypertension, tobacco use, history of CVD (excluding MI/stroke), MBDA score, leptin, MMP-3 and TNF-R1. In internal validation, the MBDA-based CVD risk score was a strong predictor of 3-year risk for a CVD event, with hazard ratio (95% CI) of 2.89 (2.46-3.41). The predicted 3-year CVD risk was low for 9.4% of patients, borderline for 10.2%, intermediate for 52.2%, and high for 28.2%. Model fit was good, with mean predicted versus observed 3-year CVD risks of 4.5% versus 4.4%. The MBDA-based CVD risk score significantly improved risk discrimination by the likelihood ratio test, compared to four clinical models. The risk score also improved prediction, reclassifying 42% of patients versus the simplest clinical model (age + sex), with a net reclassification index (NRI) (95% CI) of 0.19 (0.10-0.27); and 28% of patients versus the most comprehensive clinical model (age + sex + diabetes + hypertension + tobacco use + history of CVD + CRP), with an NRI of 0.07 (0.001-0.13). C-index was 0.715 versus 0.661 to 0.696 for the four clinical models. CONCLUSION: A prognostic score has been developed to predict 3-year CVD risk for RA patients by using clinical data, three serum biomarkers and the MBDA score. In internal validation, it had good accuracy and outperformed clinical models with and without CRP. The MBDA-based CVD risk prediction score may improve RA patient care by offering a risk stratification tool that incorporates the effect of RA inflammation.

Relationship Between Baseline and Early Changes in C-Reactive Protein and Interleukin-6 Levels and Clinical Response to Tocilizumab in Rheumatoid Arthritis.

OBJECTIVE: To clarify the relevance of measuring interleukin-6 (IL-6) and C-reactive protein (CRP) levels in order to predict clinical response to tocilizumab (TCZ) in rheumatoid arthritis patients. METHODS: In a pooled, post hoc analysis of 5 pivotal trials of TCZ, we examined the distributions of baseline serum concentrations of IL-6 and CRP, stratified by randomized treatment group, and week 24 Disease Activity Score in 28 joints (DAS28) status (DAS28 <2.6 versus DAS28 ≥2.6). Relationships between early biomarker changes and later changes in DAS28 scores were evaluated using Spearman's correlations and scatterplots. Finally, percentage changes from baseline in IL-6 and CRP levels were evaluated. RESULTS: Distributions of baseline IL-6 and CRP levels were similar for patients who achieved DAS28 scores <2.6 within 6 months of TCZ initiation and those who did not. Correlations between early changes in these 2 biomarkers and change in DAS28 scores were low (rho < 0.3 for all). Mean percentage increases from baseline in IL-6 concentrations were observed in all treatment groups (highest in the 8 mg/kg dose group); mean percentage decreases in CRP concentrations were greater at week 2 and at all visits for the 8 mg/kg dose group. CONCLUSION: Baseline serum concentrations of IL-6 and CRP may not be predictive of clinical outcomes after TCZ treatment. Data demonstrate the efficacy of TCZ in patients across a broad range of baseline serum IL-6 and CRP concentrations. Similarly, changes in these biomarkers after TCZ dosing are expected and may or may not correspond to changes in other clinical signs and symptoms. These results complement previous reports describing the complex interactions among biomarker changes, other therapeutic mechanisms of action, and clinical outcomes.