A proposed multi-domain, digital model for capturing functional status and health-related quality of life in oncology

Whereas traditional oncology clinical trial endpoints remain key for assessing novel treatments, capturing patients' functional status is increasingly recognized as an important aspect for supporting clinical decisions and assessing outcomes in clinical trials. Existing functional status assessments suffer from various limitations, some of which may be addressed by adopting digital health technologies (DHTs) as a means of collecting both objective and self-reported outcomes. In this mini-review, we propose a device-agnostic multi-domain model for oncology capturing functional status, which includes physical activity data, vital signs, sleep variables, and measures related to health-related quality of life enabled by connected digital tools. By using DHTs for all aspects of data collection, our proposed model allows for high-resolution measurement of objective data as patients navigate their daily lives outside of the hospital setting. This is complemented by electronic questionnaires administered at intervals appropriate for each instrument. Preliminary testing and practical considerations to address before adoption are also discussed. Finally, we highlight multi-institutional pre-competitive collaborations as a means of successfully transitioning the proposed digitally enabled data collection model from feasibility studies to interventional trials and care management.

Study protocol: A comparison of mobile and clinic-based spirometry for capturing the treatment effect in moderate asthma

Several inefficiencies in drug development trial implementation may be improved by moving data collection from the clinic to mobile, allowing for more frequent measurements and therefore increased statistical power while aligning to a patient-centric approach to trial design. Sensor-based digital health technologies such as mobile spirometry (mSpirometry) are comparable to clinic spirometry for capturing outcomes, such as forced expiratory volume in 1 s (FEV1); however, the impact of remote spirometry measurements on the detection of treatment effect has not been investigated. A protocol for a multicenter, single-arm, open-label interventional trial of long-acting beta agonist (LABA) therapy among 60 participants with uncontrolled moderate asthma is described. Participants will complete twice-daily mSpirometry at home and clinic spirometry during weekly visits, alongside continuous use of a wrist-worn wearable and regular completion of several diaries capturing asthma symptoms as well as participant- and site-reported satisfaction and ease of use of mSpirometry. The co-primary objectives of this study are (A) to quantify the treatment effect of LABA therapy among participants with moderate asthma, using both clinical spirometry (FEV1c ) and mSpirometry (FEV1m ); and (B) to investigate whether FEV1m is as accurate as FEV1c in detecting the treatment effect using a mixed-effect model for repeated measures. Study results will help inform whether the deployment of mSpirometry and a wrist-worn wearable for remote data collection are feasible in a multicenter setting among participants with moderate asthma, which may then be generalizable to other populations with respiratory disease.

Digital technologies: Innovations that transform the face of drug development

Recently, digital health technologies (DHTs) and digital biomarkers have gained a lot of traction in clinical investigations, motivating sponsors, investigators, and regulators to discuss and implement integrated approaches for deploying DHTs. These new tools present new and unique challenges for optimal technology integration in clinical trial processes, including operational, ethical, and regulatory issues. In this paper, we gathered different perspectives to discuss challenges and perspectives from three different stakeholders: industry, US regulators, and a public-private partnership consortium. The complexities of DHT implementation, which include regulatory definitions, defining the scope of validation experiments, and the need for partnerships between BioPharma and the technology sectors, are highlighted. Most of these challenges are related to translation of DHT-derived measures into endpoints that are meaningful to clinicians and patients, participant safety, training, and retention and privacy of data. The example of the Wearable Assessments in the Clinic and Home in PD (WATCH-PD) study is discussed as an example that demonstrated the advantages of pre-competitive collaborations, which include early regulatory feedback, data sharing, and multistakeholder alignment. Future advances in DHTs are expected to spur device-agnostic measured development and incorporate patient reported outcomes in drug development. More efforts are needed to define validation experiments for a defined context of use, incentivize data sharing and development of data standards. Multistakeholder collaborations via precompetitive consortia will help facilitate broad acceptance of DHT-enabled measures in drug development.

Digital health technology derived measures: Biomarkers or clinical outcome assessments?

Digital health technologies (DHTs) present unique opportunities for clinical evidence generation but pose certain challenges. These challenges stem, in part, from existing definitions of drug development tools, which were not created with DHT-derived measures in mind. DHT-derived measures can be leveraged as either clinical outcome assessments (COAs) or as biomarkers since they share properties with both categories of drug development tools. Examples from the literature indicate a variety of applications for DHT-derived data, including capturing disease physiology, symptom tracking, or response to therapies. The distinction between the categorization of DHT-derived measures as COAs or as biomarkers can be very fine, with terminology variability among regulatory authorities. This has significant implications for integration of DHT-derived measures in clinical trials, leading to confusion regarding the evidence required to support these tools' use in drug development. There is a need to amend definitions and create clear evidentiary requirements to support broad adoption of these new and innovative tools. The biopharma industry, the technology sector, consulting businesses, academic researchers, and regulators need a dialogue via multi-stakeholder collaborations to clarify questions around DHT-derived measures, to unify definitions, and to create the foundations for evidentiary package requirements, providing a path forward to predictable results.

Empowering drug development: Leveraging insights from imaging technologies to enable the advancement of digital health technologies

The US Food and Drug Administration (FDA) has publicly recognized the importance of improving drug development efficiency, deeming translational biomarkers a top priority. The use of imaging biomarkers has been associated with increased rates of drug approvals. An appropriate level of validation provides a pragmatic way to choose and implement these biomarkers. Standardizing imaging modality selection, data acquisition protocols, and image analysis (in ways that are agnostic to equipment and algorithms) have been key to imaging biomarker deployment. The best known examples come from studies done via precompetitive collaboration efforts, which enable input from multiple stakeholders and data sharing. Digital health technologies (DHTs) provide an opportunity to measure meaningful aspects of patient health, including patient function, for extended periods of time outside of the hospital walls, with objective, sensor-based measures. We identified the areas where learnings from the imaging biomarker field can accelerate the adoption and widespread use of DHTs to develop novel treatments. As with imaging, technical validation parameters and performance acceptance thresholds need to be established. Approaches amenable to multiple hardware options and data processing algorithms can be enabled by sharing DHT data and by cross-validating algorithms. Data standardization and creation of shared databases will be vital. Pre-competitive consortia (public-private partnerships and professional societies that bring together all stakeholders, including patient organizations, industry, academic experts, and regulators) will advance the regulatory maturity of DHTs in clinical trials.

Sensor Verification and Analytical Validation of Algorithms to Measure Gait and Balance and Pronation/Supination in Healthy Volunteers

Numerous studies have sought to demonstrate the utility of digital measures of motor function in Parkinson’s disease. Frameworks, such as V3, document digital measure development: technical verification, analytical and clinical validation. We present the results of a study to (1) technically verify accelerometers in an Apple iPhone 8 Plus and ActiGraph GT9X versus an oscillating table and (2) analytically validate software tasks for walking and pronation/supination on the iPhone plus passively detect walking measures with the ActiGraph in healthy volunteers versus human raters. In technical verification, 99.4% of iPhone and 91% of ActiGraph tests show good or excellent agreement versus the oscillating table as the gold standard. For the iPhone software task and algorithms, intraclass correlation coefficients (ICCs) > 0.75 are achieved versus the human raters for measures when walking distance is >10 s and pronation/supination when the arm is rotated more than two times. Passively detected walking start and end time was accurate to approx. 1 s and walking measures were accurate to one unit, e.g., one step. The results suggest that the Apple iPhone and ActiGraph GT9X accelerometers are fit for purpose and that task and passively collected measures are sufficiently analytically valid to assess usability and clinical validity in Parkinson’s patients.

Recommendations for Defining and Reporting Adherence Measured by Biometric Monitoring Technologies: Systematic Review

Background

Suboptimal adherence to data collection procedures or a study intervention is often the cause of a failed clinical trial. Data from connected sensors, including wearables, referred to here as biometric monitoring technologies (BioMeTs), are capable of capturing adherence to both digital therapeutics and digital data collection procedures, thereby providing the opportunity to identify the determinants of adherence and thereafter, methods to maximize adherence.

Objective

We aim to describe the methods and definitions by which adherence has been captured and reported using BioMeTs in recent years. Identifying key gaps allowed us to make recommendations regarding minimum reporting requirements and consistency of definitions for BioMeT-based adherence data.

Methods

We conducted a systematic review of studies published between 2014 and 2019, which deployed a BioMeT outside the clinical or laboratory setting for which a quantitative, nonsurrogate, sensor-based measurement of adherence was reported. After systematically screening the manuscripts for eligibility, we extracted details regarding study design, participants, the BioMeT or BioMeTs used, and the definition and units of adherence. The primary definitions of adherence were categorized as a continuous variable based on duration (highest resolution), a continuous variable based on the number of measurements completed, or a categorical variable (lowest resolution).

Results

Our PubMed search terms identified 940 manuscripts; 100 (10.6%) met our eligibility criteria and contained descriptions of 110 BioMeTs. During literature screening, we found that 30% (53/177) of the studies that used a BioMeT outside of the clinical or laboratory setting failed to report a sensor-based, nonsurrogate, quantitative measurement of adherence. We identified 37 unique definitions of adherence reported for the 110 BioMeTs and observed that uniformity of adherence definitions was associated with the resolution of the data reported. When adherence was reported as a continuous time-based variable, the same definition of adherence was adopted for 92% (46/50) of the tools. However, when adherence data were simplified to a categorical variable, we observed 25 unique definitions of adherence reported for 37 tools.

Conclusions

We recommend that quantitative, nonsurrogate, sensor-based adherence data be reported for all BioMeTs when feasible; a clear description of the sensor or sensors used to capture adherence data, the algorithm or algorithms that convert sample-level measurements to a metric of adherence, and the analytic validation data demonstrating that BioMeT-generated adherence is an accurate and reliable measurement of actual use be provided when available; and primary adherence data be reported as a continuous variable followed by categorical definitions if needed, and that the categories adopted are supported by clinical validation data and/or consistent with previous reports.

Daily step counts to predict hospitalizations during chemoradiotherapy for head and neck cancer

1571

Background: Wearable activity trackers could provide useful data for managing cancer patients with respect to treatment selection, toxicity monitoring, and implementation of supportive care measures. Here, we seek to evaluate the association between daily step counts and hospitalizations in a cohort of patients with head and neck cancer (HNC). Methods: This analysis consists of patients enrolled in one of three prospective trials involving activity monitoring (NCT02649569, NCT03115398, NCT03102229) during chemoradiation. Study subjects were asked to wear a commercial fitness tracker continuously during the therapy. ECOG performance status (PS) was assessed at baseline, and quality of life (QoL) EORTC QLQ-C30 questionnaires were completed weekly. Multivariable Cox regression models with time-dependent covariates (average step count over the past 3 days, most recent QoL score) and time-fixed covariates (age, sex, baseline PS, study number, baseline tumor volume, and treatment setting [definitive versus postoperative]) were used to identify predictors of first hospital admission during the chemoradiotherapy course. In addition to the Cox regression models, linear mixed models were fitted with daily step count as the dependent variable to examine its relationship with certain independent variables including age, sex, weekend status, days after treatment initiation, and study number. Results: Sixty-six HNC patients who received chemoradiotherapy between 2015 and 2019 were included in the analysis. Median age was 60 (range: 27-88). 47% of patients had ECOG PS score 0, 47% ECOG score 1, and 6% ECOG score 2. 29% of patients had HPV-positive oropharyngeal tumors, and the most common other tumor subsites were larynx (27%), and nasopharynx (12%). The Cox regression survival model demonstrated a 26% reduction in the short-term hospitalization risk for every 1000 daily steps (averaged over the past 3 days, hazard ratio 0.74; 95% confidence interval (CI) 0.55-0.98, p = 0.0367). Hospitalizations were not significantly associated with most recent QoL or baseline ECOG PS. Additionally, according to the linear mixed model results, daily step count was not associated with age (p = 0.8048). Study subjects moved less on weekends (on average 245 fewer steps on weekends than weekdays, 95% CI 134-357, p < 0.0001). Also, an increase in most recently measured ECOG PS was associated with a decrease in daily step count (167 fewer steps for every increase in ECOG PS, 95% CI -289 to -45, p < 0.0072). Conclusions: Daily step counts are a dynamic predictor of hospitalizations in patients undergoing chemoradiotherapy for head and neck cancer. Interventional studies are needed to demonstrate feasibility of leveraging physical activity data to optimize supportive care during cancer therapy and enhance cancer care quality. Clinical trial information: NCT02649569, NCT03115398, NCT03102229.

Remote Cardiac Safety Monitoring through the Lens of the FDA Biomarker Qualification Evidentiary Criteria Framework: A Case Study Analysis

Clinical safety findings remain one of the reasons for attrition of drug candidates during clinical development. Cardiovascular liabilities are not consistently detected in early-stage clinical trials and often become apparent when drugs are administered chronically for extended periods of time. Vital sign data collection outside of the clinic offers an opportunity for deeper physiological characterization of drug candidates and earlier safety signal detection. A working group representing expertise from biopharmaceutical and technology sectors, US Food and Drug Administration (FDA) public-private partnerships, academia, and regulators discussed and presented a remote cardiac monitoring case study at the FNIH Biomarkers Consortium Remote Digital Monitoring for Medical Product Development workshop to examine applicability of the biomarker qualification evidentiary framework by the FDA. This use case examined the components of the framework, including the statement of need, the context of use, the state of the evidence, and the benefit/risk profile. Examination of results from 2 clinical trials deploying 510(k)-cleared devices for remote cardiac data collection demonstrated the need for analytical and clinical validity irrespectively of the regulatory status of a device of interest, emphasizing the importance of data collection method assessment in the context of intended use. Additionally, collection of large amounts of ambulatory data also highlighted the need for new statistical methods and contextual information to enable data interpretation. A wider adoption of this approach for drug development purposes will require collaborations across industry, academia, and regulatory agencies to establish methodologies and supportive data sets to enable data interpretation and decision-making.

Remote FEV1 Monitoring in Asthma Patients: A Pilot Study

Forced expiratory volume in one second (FEV₁ ) is a critical parameter for the assessment of lung function for both clinical care and research in patients with asthma. While asthma is defined by variable airflow obstruction, FEV₁ is typically assessed during clinic visits. Mobile spirometry (mSpirometry) allows more frequent measurements of FEV₁ , resulting in a more continuous assessment of lung function over time and its variability. Twelve patients with moderate asthma were recruited in a single-center study and were instructed to perform pulmonary function tests at home twice daily for 28 days and weekly in the clinic. Daily and mean subject compliances were summarized. The agreement between clinic and mobile FEV₁ was assessed using correlation and Bland-Altman analyses. The test-retest reliability for clinic and mSpirometry was assessed by interclass correlation coefficient (ICC). Simulation was conducted to explore if mSpirometry could improve statistical power over clinic counterparts. The mean subject compliance with mSpirometry was 70% for twice-daily and 85% for at least once-daily. The mSpirometry FEV₁ were highly correlated and agreed with clinic ones from the same morning (r = 0.993) and the same afternoon (r = 0.988) with smaller mean difference for the afternoon (0.0019 L) than morning (0.0126 L) measurements. The test-retest reliability of mobile (ICC = 0.932) and clinic (ICC = 0.942) spirometry were comparable. Our simulation analysis indicated greater power using dense mSpirometry than sparse clinic measurements. Overall, we have demonstrated good compliance for repeated at-home mSpirometry, high agreement and comparable test-retest reliability with clinic counterparts, greater statistical power, suggesting a potential for use in asthma clinical research.

An Evaluation of Biometric Monitoring Technologies for Vital Signs in the Era of COVID-19

The novel coronavirus disease 2019 (COVID-19) global pandemic has shifted how many patients receive outpatient care. Telehealth and remote monitoring have become more prevalent, and measurements taken in a patient's home using biometric monitoring technologies (BioMeTs) offer convenient opportunities to collect vital sign data. Healthcare providers may lack prior experience using BioMeTs in remote patient care, and, therefore, may be unfamiliar with the many versions of BioMeTs, novel data collection protocols, and context of the values collected. To make informed patient care decisions based on the biometric data collected remotely, it is important to understand the engineering solutions embedded in the products, data collection protocols, form factors (physical size and shape), data quality considerations, and availability of validation information. This article provides an overview of BioMeTs available for collecting vital signs (temperature, heart rate, blood pressure, oxygen saturation, and respiratory rate) and discusses the strengths and limitations of continuous monitoring. We provide considerations for remote data collection and sources of validation information to guide BioMeT use in the era of COVID-19 and beyond.

Fit-for-Purpose Biometric Monitoring Technologies: Leveraging the Laboratory Biomarker Experience

Biometric monitoring technologies (BioMeTs) are becoming increasingly common to aid data collection in clinical trials and practice. The state of BioMeTs, and associated digitally measured biomarkers, is highly reminiscent of the field of laboratory biomarkers 2 decades ago. In this review, we have summarized and leveraged historical perspectives, and lessons learned from laboratory biomarkers as they apply to BioMeTs. Both categories share common features, including goals and roles in biomedical research, definitions, and many elements of the biomarker qualification framework. They can also be classified based on the underlying technology, each with distinct features and performance characteristics, which require bench and human experimentation testing phases. In contrast to laboratory biomarkers, digitally measured biomarkers require prospective data collection for purposes of analytical validation in human subjects, lack well‐established and widely accepted performance characteristics, require human factor testing, and, for many applications, access to raw (sample‐level) data. Novel methods to handle large volumes of data, as well as security and data rights requirements add to the complexity of this emerging field. Our review highlights the need for a common framework with appropriate vocabulary and standardized approaches to evaluate digitally measured biomarkers, including defining performance characteristics and acceptance criteria. Additionally, the need for human factor testing drives early patient engagement during technology development. Finally, use of BioMeTs requires a relatively high degree of technology literacy among both study participants and healthcare professionals. Transparency of data generation and the need for novel analytical and statistical tools creates opportunities for precompetitive collaborations.

Remote Digital Monitoring for Medical Product Development

The use of digital health products has gained considerable interest as a new way to improve therapeutic research and development. Although these products are being adopted by various industries and stakeholders, their incorporation in clinical trials has been slow due to a disconnect between the promises of digital products and potential risks in using these new technologies in the absence of regulatory support. The Foundation for the National Institutes of Health (FNIH) Biomarkers Consortium hosted a public workshop to address challenges and opportunities in this field. Important characteristics of tool development were addressed in a series of presentations, case studies, and open panel sessions. The workshop participants endorsed the usefulness of an evidentiary criteria framework, highlighted the importance of early patient engagement, and emphasized the potential impact of digital monitoring tools and precompetitive collaborations. Concerns were expressed about the lack of real‐life validation examples and the limitations of legacy standards used as a benchmark for novel tool development and validation. Participants recognized the need for novel analytical and statistical approaches to accommodate analyses of these novel data types. Future directions are to harmonize definitions to build common methodologies and foster multidisciplinary collaborations; to develop approaches toward integrating digital monitoring data with the totality of the data in clinical trials, and to continue an open dialog in the community. There was a consensus that all these efforts combined may create a paradigm shift of how clinical trials are planned, conducted, and results brought to regulatory reviews.

Remote Monitoring in Clinical Trials During the COVID-19 Pandemic

The coronavirus disease 2019 (COVID‐19) pandemic has rapidly challenged the pharmaceutical industry to implement remote clinical trials. The industry’s lack of extensive experience with remote measurements initiates multiple questions about how to select candidates for remote collection, their validity, and regulatory implications of moving certain assessments to a remote mode. We propose a decision tree for migration of clinic to remote assessments and highlight activities required to ensure that these measurements are valid, safe, and usable.

"In-House" Data on the Outside-A Mobile Health Approach

Mobile health (mHealth) technologies have the potential to capture dense patient data on the background of real-life behavior. Merck & Co., Inc. (Kenilworth, NJ), in collaboration with Koneksa Health, conducted a phase I clinical trial to validate cardiovascular mHealth technologies for concordance with traditional approaches and to establish sensitivity to detect effects of pharmacological intervention. This two-part study enrolled 18 healthy male subjects. Part I, a 5-day study, compared mHealth measures of heart rate (HR) and blood pressure (BP) to those from traditional methods. Hypotheses of similarity, in the clinic and at home, were tested individually for HR, systolic BP, and diastolic BP, at a 2-sided 0.05 alpha level, with a prespecified criterion for similarity being the percentage differences between the 2 measurements within 15%. Part II, a 7-day, 3-period randomized balanced crossover study, evaluated the mHealth technology's ability to detect effects of bisoprolol and salbutamol. Hypotheses that the changes from baseline in HR were greater in the bisoprolol (reduction in HR) and salbutamol (increase in HR) groups compared with no treatment were tested, at a 1-sided 0.05 alpha level. Linear mixed-effects models, Pearson's correlation coefficients, summary statistics, and exploratory plots were applied to analyze the data. The mHealth measures of HR and BP were demonstrated to be similar to those from traditional methods, and sensitive to changes in cardiovascular parameters induced by bisoprolol and salbutamol.

Continuous Monitoring Using a Wearable Device Detects Activity-Induced Heart Rate Changes After Administration of Amphetamine

Wearable digital devices offer potential advantages over traditional methods for the collection of health-related information, including continuous collection of dense data while study subjects are ambulatory or in remote settings. We assessed the utility of collecting continuous actigraphy and cardiac monitoring by deploying two US Food and Drug Administration (FDA) 510(k)-cleared devices in a phase I clinical trial of a novel compound, which included the use of an amphetamine challenge. The Phillips Actiwatch Spectrum Pro (Actiwatch) was used to assess mobility and sleep. The Preventice BodyGuardian (BodyGuardian) was used for monitoring heart rate (HR) and respiratory rate (RR), via single-lead electrocardiogram (ECG) recordings, together with physical activity. We measured data collection rates, compared device readouts with conventional measures, and monitored changes in HR measures during the amphetamine challenge. Completeness of data collection was good for the Actiwatch (96%) and lower for the BodyGuardian (80%). A good correlation was observed between device and in-clinic measures for HR (r = 0.99; P < 0.001), but was poor for RR (r = 0.39; P = 0.004). Manual reviews of selected ECG strips corresponding to HR measures below, within, and above the normal range were consistent with BodyGuardian measurements. The BodyGuardian device detected clear HR responses after amphetamine administration while subjects were physically active, whereas conventional measures collected at predefined timepoints while subjects were resting and supine did not. Wearable digital technology shows promise for monitoring human subjects for physiologic changes and pharmacologic responses, although fit-for-purpose evaluation and validation continues to be important prior to the wider deployment of these devices.

Evaluation of Wearable Digital Devices in a Phase I Clinical Trial

We assessed the performance of two US Food and Drug Administration (FDA) 510(k)‐cleared wearable digital devices and the operational feasibility of deploying them to augment data collection in a 10‐day residential phase I clinical trial. The Phillips Actiwatch Spectrum Pro (Actiwatch) was used to assess mobility and sleep, and the Vitalconnect HealthPatch MD (HealthPatch) was used for monitoring heart rate (HR), respiratory rate (RR), and surface skin temperature (ST). We measured data collection rates, compared device readouts with anticipated readings and conventional in‐clinic measures, investigated data limitations, and assessed user acceptability. Six of nine study participants consented; completeness of data collection was adequate (> 90% for four of six subjects). A good correlation was observed between the HealthPatch device derived and in‐clinic measures for HR (Pearson r = 0.71; P = 2.2e‐16) but this was poor for RR (r = 0.08; P = 0.44) and ST (r = 0.14; P = 0.14). Manual review of electrocardiogram strips recorded during reported episodes of tachycardia > 180 beats/min showed that these were artefacts. The HealthPatch was judged to be not fit‐for‐purpose because of artefacts and the need for time‐consuming manual review. The Actiwatch device was suitable for monitoring mobility, collecting derived sleep data, and facilitating the interpretation of vital sign data. These results suggest the need for fit‐for‐purpose evaluation of wearable devices prior to their deployment in drug development studies.

Wearable Devices in Clinical Trials: Hype and Hypothesis

The development of innovative wearable technologies has raised great interest in new means of data collection in healthcare and biopharmaceutical research and development. Multiple applications for wearables have been identified in a number of therapeutic areas; however, researchers face many challenges in the clinic, including scientific methodology as well as regulatory, legal, and operational hurdles. To facilitate further evaluation and adoption of these technologies, we highlight methodological and logistical considerations for implementation in clinical trials, including key elements of analytical and clinical validation in the specific context of use (COU). Additionally, we provide an assessment of the maturity of the field and successful examples of recent clinical experiments.

Erroneous augmentation of multiplex assay measurements in patients with rheumatoid arthritis due to heterophilic binding by serum rheumatoid factor

OBJECTIVE

Serum rheumatoid factor (RF) and other heterophilic antibodies potentially interfere with antibody-based immunoassays by nonspecifically binding detection reagents. The purpose of this study was to assess whether these factors confound multiplex-based immunoassays, which are used with increasing frequency to measure cytokine and chemokine analytes in patients with rheumatoid arthritis (RA).

METHODS

We performed multiplex immunoassays using different platforms to measure analyte concentrations in RA patient samples. Samples were depleted of RF by column-based affinity absorption or were exposed to agents that block heterophilic binding activity.

RESULTS

In RA patients with high-titer RF, 69% of analytes demonstrated at least a 2-fold stronger multiplex signal in non-RF-depleted samples as compared to RF-depleted samples. This degree of erroneous signal amplification was less frequent in low-titer RF samples (17% of analytes; P < 0.0000001). Signal amplification by heterophilic antibodies was blocked effectively by HeteroBlock (≥ 150 μg/ml). In 35 RA patients, multiplex signals for 14 of 22 analytes were amplified erroneously in unblocked samples as compared to blocked samples (some >100-fold), but only in patients with high-titer RF (P < 0.002). Two other blocking agents, heterophilic blocking reagent and immunoglobulin-inhibiting reagent, also blocked heterophilic activity.

CONCLUSION

All multiplex protein detection platforms we tested exhibited significant confounding by RF or other heterophilic antibodies. These findings have broad-reaching implications in the acquisition and interpretation of data derived from multiplex immunoassay testing of RA patient serum and possibly also in other conditions in which RF or other heterophilic antibodies may be present. Several available blocking agents effectively suppressed this erroneous signal amplification in the multiplex platforms tested.

Monocyte migration to the synovium in rheumatoid arthritis patients treated with adalimumab

Objectives

The mechanism of action of treatment with tumour necrosis factor (TNF) blockers in rheumatoid arthritis (RA) is still not completely understood. The aim of this study was to test if adalimumab treatment could affect the influx of monocytes into the synovium.

Methods

A novel technique was used to analyse the migration of labelled autologous monocytes before and 14 days after initiation of adalimumab treatment using scintigraphy. CD14 monocytes were isolated from patients with RA, using a positive selection procedure with magnetic-activated cell sorting, and labelled with technetium-99m-hexamethylpropylene-amino-oxime. Scintigraphic scans were made 1, 2 and 3 h after re-infusion.

Results

As early as 14 days after the start of treatment with adalimumab a significant decrease in disease activity score evaluated in 28 joints was shown. There was no significant decrease in the influx of monocytes into the joint at this time.

Conclusions

This study indicates that adalimumab treatment does not reduce the influx of monocytes into the synovium early after initiation of treatment. As previous studies showed a rapid decrease in macrophage infiltration after TNF-antibody therapy, which could not be explained by increased cell death, this points to an important role for enhanced efflux of inflammatory cells from the synovium.

Monocyte scintigraphy in rheumatoid arthritis: the dynamics of monocyte migration in immune-mediated inflammatory disease

BACKGROUND

Macrophages are principal drivers of synovial inflammation in rheumatoid arthritis (RA), a prototype immune-mediated inflammatory disease. Conceivably, synovial macrophages are continuously replaced by circulating monocytes in RA. Animal studies from the 1960s suggested that macrophage replacement by monocytes is a slow process in chronic inflammatory lesions. Translation of these data into the human condition has been hampered by the lack of available techniques to analyze monocyte migration in man.

METHODS/PRINCIPAL FINDINGS

We developed a technique that enabled us to analyze the migration of labelled autologous monocytes in RA patients using single photon emission computer tomography (SPECT). We isolated CD14+ monocytes by CliniMACS in 8 patients and labeled these with technetium-99m (99mTc-HMPAO). Monocytes were re-infused into the same patient. Using SPECT we calculated that a very small but specific fraction of 3.4 x 10(-3) (0.95-5.1 x 10(-3)) % of re-infused monocytes migrated to the inflamed joints, being detectable within one hour after re-infusion.

CONCLUSIONS/SIGNIFICANCE

The results indicate monocytes migrate continuously into the inflamed synovial tissue of RA patients, but at a slow macrophage-replacement rate. This suggests that the rapid decrease in synovial macrophages that occurs after antirheumatic treatment might rather be explained by an alteration in macrophage retention than in monocyte influx and that RA might be particularly sensitive to treatments targeting inflammatory cell retention.

Genome-wide association study of determinants of anti-cyclic citrullinated peptide antibody titer in adults with rheumatoid arthritis

We carried out a genome-wide association study of genetic predictors of anti-cyclic citrullinated peptide antibody (anti-CCP) level in 531 self-reported non-Hispanic Caucasian Rheumatoid Arthritis (RA) patients enrolled in the Brigham Rheumatoid Arthritis Sequential Study (BRASS). For replication, we then analyzed 289 single nucleotide polymorphisms (SNPs) with P < 0.001 in BRASS in an independent population of 849 RA patients from the North American Rheumatoid Arthritis Consortium (NARAC). BRASS and NARAC samples were genotyped using the Affymetrix 100K and Illumina 550K platforms respectively. Association between SNPs and anti-CCP titer was tested using general linear models. The five most significant SNPs from BRASS all were within the major histocompatibility complex (MHC) region (P < or = 3.5 x 10(-6)). After controlling for the human leukocyte antigen shared epitope (HLA-SE), the top SNPs still yielded P values < 0.0002. In NARAC, a single SNP from the MHC region near BTNL2 and HLA-DRA, rs1980493 (r(2) = 0.85 with the top five SNPs from BRASS), was associated significantly with CCP titer (P = 6.1 x 10(-5)) even after adjustment for the HLA-SE (P = 0.0002). The top SNPs found in BRASS and NARAC had r(2) = 0.46 and 0.64, respectively, to HLA-DRB1 DR3 alleles. These results confirm that the most significant genome region affecting anti-CCP titers in RA is the MHC region. We identified a SNP in moderate linkage disequilibrium (LD) with HLA-DR3, which may influence anti-CCP titer independently of the HLA-SE.

Peripheral blood expression of nuclear factor-kappab-regulated genes is associated with rheumatoid arthritis disease activity and responds differentially to anti-tumor necrosis factor-alpha versus methotrexate

OBJECTIVE

To evaluate peripheral blood expression of genes regulated by nuclear factor-kappaB (NF-kappaB), a key mediator of tumor necrosis factor-alpha (TNF-alpha) signaling, in patients with rheumatoid arthritis (RA) before and during treatment with anti-TNF-alpha or methotrexate (MTX). We analyzed association of gene expression with disease activity, rheumatoid factor (RF), age, sex, disease duration, treatment modality, and clinical response.

METHODS

Sixty patients consented for RNA analysis at baseline and after 2 and 6 weeks of treatment. Disease activity was quantified using Disease Activity Score (DAS28) and C-reactive protein (CRP). Expression of 67 TNF-alpha-responsive, NF-kappaB-regulated genes was measured using Affymetrix arrays and RT-PCR.

RESULTS

Expression of 34 genes was associated with DAS28-CRP, notably S100A12/calgranulin C, IL7R, and aquaporin 3. No association was observed with age, sex, RF, or disease duration. Expression of 16 genes changed in a manner that differed significantly between treatment groups. Eleven were reduced in anti-TNF-alpha-treated patients relative to MTX, while 5 were increased. The majority of these observations were confirmed using RT-PCR. Gene expression was not associated significantly with change in disease activity.

CONCLUSION

NF-kappaB-dependent gene expression in peripheral leukocytes is highly correlated with RA activity as measured by DAS28-CRP. Expression of many genes responds differentially to anti-TNF-alpha versus MTX, suggesting fundamentally different effects on the NF-kappaB pathway. This peripheral blood expression signature provides candidate markers that could lead to development of a simple, minimally invasive pharmacodynamic assay for RA treatments directed at the NF-kappaB pathway. Combination of gene expression data with clinical scores and serum markers may provide more sensitive and predictive measures of RA disease activity.

Use of molecular imaging to quantify response to IKK-2 inhibitor treatment in murine arthritis

OBJECTIVE

The NF-kappaB signaling pathway promotes the immune response in rheumatoid arthritis (RA) and in rodent models of RA. NF-kappaB activity is regulated by the IKK-2 kinase during inflammatory responses. To elucidate how IKK-2 inhibition suppresses disease development, we used a combination of in vivo imaging, transcription profiling, and histopathology technologies to study mice with antibody-induced arthritis.

METHODS

ML120B, a potent, small molecule inhibitor of IKK-2, was administered to arthritic animals, and disease activity was monitored. NF-kappaB activity in diseased joints was quantified by in vivo imaging. Quantitative reverse transcriptase-polymerase chain reaction was used to evaluate gene expression in joints. Protease-activated near-infrared fluorescence (NIRF) in vivo imaging was applied to assess the amounts of active proteases in the joints.

RESULTS

Oral administration of ML120B suppressed both clinical and histopathologic manifestations of disease. In vivo imaging demonstrated that NF-kappaB activity in inflamed arthritic paws was inhibited by ML120B, resulting in significant suppression of multiple genes in the NF-kappaB pathway, i.e., KC, epithelial neutrophil-activating peptide 78, JE, intercellular adhesion molecule 1, CD3, CD68, tumor necrosis factor alpha, interleukin-1beta, interleukin-6, inducible nitric oxide synthase, cyclooxygenase 2, matrix metalloproteinase 3, cathepsin B, and cathepsin K. NIRF in vivo imaging demonstrated that ML120B treatment dramatically reduced the amount of active proteases in the joints.

CONCLUSION

Our data demonstrate that IKK-2 inhibition in the murine model of antibody-induced arthritis suppresses both inflammation and joint destruction. In addition, this study highlights how gene expression profiling can facilitate the identification of surrogate biomarkers of disease activity and treatment response in an experimental model of arthritis.

Stat3 enhances vimentin gene expression by binding to the antisilencer element and interacting with the repressor protein, ZBP-89

Vimentin exhibits a complex pattern of developmental- and tissue-specific expression and is aberrantly expressed in most metastatic tumors. The human vimentin promoter contains multiple DNA elements, some of which enhance gene expression and one that inhibits. A silencer element (at -319) binds the repressor ZBP-89. Further upstream (at -757) is an element, which acts positively in the presence of the silencer element and, thus, is referred to as an antisilencer (ASE). Previously, we showed that Stat1alpha binds to this element upon induction by IFN-gamma. However, substantial binding and reporter gene activity was still present in nontreated cells. Here, we have found that Stat3 binds to the ASE element in vitro. Transfection experiments in COS-1 cells with various vimentin promoter--reporter constructs show that gene activity is dependent upon the cotransfection and activation of Stat3. Moreover, activated Stat3 can overcome ZBP-89 repression. Coimmunoprecipitation studies demonstrate that Stat3 and ZBP-89 can interact and confocal microscopy detects these factors to be colocalized in the nucleus. Moreover, a correlation exists between the presence of activated Stat3 and vimentin expression in MDA-MB-231 cells, which is lacking in MCF7 cells where vimentin is not expressed. In the light of these results, we propose that the interaction of Stat3 and ZBP-89 may be crucial for overcoming the effects of the repressor ZBP-89, which suggests a novel mode for Stat3 gene activation.

A Stat1alpha factor regulates the expression of the human vimentin gene by IFN-gamma

Vimentin is an intermediate filament protein normally expressed in cells of mesenchymal origin. Here, we report an increase in vimentin gene transcription induced by the cytokine interferon-y (IFN-gamma). Northern blot analysis and reporter gene assays reveal that IFN-gamma induces vimentin gene transcription in HeLa cells. However, no increase in vimentin mRNA synthesis was observed de novo in MCF-7 cells, which do not already express vimentin. Band shift analysis shows that the Stat1alpha protein mediates vimentin induction by IFN-gamma. A human mutant fibroblast cell line (U3A), which lacks Stat1alpha but expresses vimentin mRNA, yields no increase in vimentin mRNA levels on the addition of IFN-gamma. These results suggest that the induction of vimentin gene expression might be an important part of a complex cellular response to IFN-gamma.

A GC-box is required for expression of the human vimentin gene

Vimentin is an intermediate filament protein normally expressed in cells of mesenchymal origin. The promoter of the human vimentin gene (-1416 to +73) was shown to contain two positive-acting regions, separated by a negative region, and at least eight GC-boxes as determined by sequence homology (Rittling, S.R., Baserga, R., 1987. Mol. Cell. Biol. 7, 3908-3915). We have analyzed the region -900 to +41 for protein binding by in vivo footprinting experiments using ligation-mediated PCR. For the various GC-boxes, we detect protein binding only to that GC-box (at position -64 and -55) closest to the transcriptional start site. Transient transfection assays of various vimentin 5'-end fragments and mutations thereof fused to the reporter gene cat indicate that this sequence is indispensable for promoter function regardless of the inclusion of upstream DNA sequences. In vitro binding studies confirm that this region binds protein specifically. We suggest that this GC-box and its binding factor are required for regulated expression of the human vimentin gene.

An antisilencer element is involved in the transcriptional regulation of the human vimentin gene

Vimentin is an intermediate filament protein normally expressed in cells of mesenchymal origin. The promoter of the human vimentin gene was previously reported to contain two positive-acting regions, separated by a negative region (Rittling, S.R., Baserga, R., 1987. Functional analysis and growth factor regulation of the human vimentin promoter. Mol. Cell. Biol. 7, 3908-3915). Here, detailed studies reveal two additional regulatory elements, a new positive transcriptional element located between -717 and -757, and a new repressor element at -780 to -821. In transient transfections, the positive-acting element is able to completely override the effect of different silencer elements when fused to a heterologous promoter. However, this element does not enhance gene activity when the silencer element is absent and thus cannot be viewed as a true enhancer. Since it appears to overcome the effect of a silencer element, we refer to it as an antisilencer element. Gel mobility shift assays, UV-cross-linking experiments, and Southwestern blots reveal that a 105-kDa protein specifically binds to this region.