Implementation of the CDC translational informatics platform--from genetic variants to the national Swedish Rheumatology Quality Register

Exploring the putative role of PRDM1 and PRDM2 transcripts as mediators of T lymphocyte activation

BACKGROUND

T cell activation and programming from their naïve/resting state, characterized by widespread modifications in chromatin accessibility triggering extensive changes in transcriptional programs, is orchestrated by several cytokines and transcription regulators. PRDM1 and PRDM2 encode for proteins with PR/SET and zinc finger domains that control several biological processes, including cell differentiation, through epigenetic regulation of gene expression. Different transcripts leading to main protein isoforms with (PR +) or without (PR-) the PR/SET domain have been described. Although many studies have established the critical PRDM1 role in hematopoietic cell differentiation, maintenance and/or function, the single transcript contribution has not been investigated before. Otherwise, very few evidence is currently available on PRDM2. Here, we aimed to analyze the role of PRDM1 and PRDM2 different transcripts as mediators of T lymphocyte activation.

METHODS

We analyzed the transcription signature of the main variants from PRDM1 (BLIMP1a and BLIMP1b) and PRDM2 (RIZ1 and RIZ2) genes, in human T lymphocytes and Jurkat cells overexpressing PRDM2 cDNAs following activation through different signals.

RESULTS

T lymphocyte activation induced an early increase of RIZ2 and RIZ1 followed by BLIMP1b increase and finally by BLIMP1a increase. The "first" and the "second" signals shifted the balance towards the PR- forms for both genes. Interestingly, the PI3K signaling pathway modulated the RIZ1/RIZ2 ratio in favor of RIZ1 while the balance versus RIZ2 was promoted by MAPK pathway. Cytokines mediating different Jak/Stat signaling pathways (third signal) early modulated the expression of PRDM1 and PRDM2 and the relationship of their different transcripts confirming the early increase of the PR- transcripts. Different responses of T cell subpopulations were also observed. Jurkat cells showed that the acute transient RIZ2 increase promoted the balancing of PRDM1 forms towards BLIMP1b. The stable forced expression of RIZ1 or RIZ2 induced a significant variation in the expression of key transcription factors involved in T lymphocyte differentiation. The BLIMP1a/b balance shifted in favor of BLIMP1a in RIZ1-overexpressing cells and of BLIMP1b in RIZ2-overexpressing cells.

CONCLUSIONS

This study provides the first characterization of PRDM2 in T-lymphocyte activation/differentiation and novel insights on PRDM1 and PRDM2 transcription regulation during initial activation phases.

Incidence and risk factors for adalimumab and infliximab anti-drug antibodies in rheumatoid arthritis: A European retrospective multicohort analysis

OBJECTIVES

To evaluate the incidence of anti-drug antibody (ADA) occurrences and ADA-related risk factors under adalimumab and infliximab treatment in rheumatoid arthritis (RA) patients.

METHODS

The study combined retrospective cohorts from the ABIRISK project totaling 366 RA patients treated with adalimumab (n = 240) or infliximab (n = 126), 92.4% of them anti-TNF naive (n = 328/355) and 96.6% of them co-treated with methotrexate (n = 341/353) with up to 18 months follow-up. ADA positivity was measured by enzyme-linked immunosorbent assay. The cumulative incidence of ADA was estimated, and potential bio-clinical factors were investigated using a Cox regression model on interval-censored data.

RESULTS

ADAs were detected within 18 months in 19.2% (n = 46) of the adalimumab-treated patients and 29.4% (n = 37) of the infliximab-treated patients. The cumulative incidence of ADA increased over time. In the adalimumab and infliximab groups, respectively, the incidence was 15.4% (5.2-20.2) and 0% (0-5.9) at 3 months, 17.6% (11.4-26.4) and 0% (0-25.9) at 6 months, 17.7% (12.6-37.5) and 34.1% (11.4-46.3) at 12 months, 50.0% (25.9-87.5) and 37.5% (25.9-77.4) at 15 months and 50.0% (25.9-87.5) and 66.7% (37.7-100) at 18 months. Factors associated with a higher risk of ADA development were: longer disease duration (1-3 vs. < 1 year; adalimumab: HR 3.0, 95% CI 1.0-8.7; infliximab: HR 2.7, 95% CI 1.1-6.8), moderate disease activity (DAS28 3.2-5.1 vs. < 3.2; adalimumab: HR 6.6, 95% CI 1.3-33.7) and lifetime smoking (infliximab: HR 2.7, 95% CI 1.2-6.3).

CONCLUSIONS

The current study focusing on patients co-treated with methotrexate for more than 95% of them found a late occurrence of ADAs not previously observed, whereby the risk continued to increase over 18 months. Disease duration, DAS28 and lifetime smoking are clinical predictors of ADA development.

EsPRit: ethics committee proposals for Long Term Medical Data Registries in rapidly evolving research fields - a future-proof best practice approach

Background

Long-term data collection is a challenging task in the domain of medical research. Many effects in medicine require long periods of time to become traceable e.g. the development of secondary malignancies based on a given radiotherapeutic treatment of the primary disease. Nevertheless, long-term studies often suffer from an initial lack of available information, thus disallowing a standardized approach for their approval by the ethics committee. This is due to several factors, such as the lack of existing case report forms or an explorative research approach in which data elements may change over time.

In connection with current medical research and the ongoing digitalization in medicine, Long Term Medical Data Registries (MDR-LT) have become an important means of collecting and analyzing study data. As with any clinical study, ethical aspects must be taken into account when setting up such registries.

This work addresses the problem of creating a valid, high-quality ethics committee proposal for medical registries by suggesting groups of tasks (building blocks), information sources and appropriate methods for collecting and analyzing the information, as well as a process model to compile an ethics committee proposal (EsPRit).

Methods

To derive the building blocks and associated methods software and requirements engineering approaches were utilized. Furthermore, a process-oriented approach was chosen, as information required in the creating process of ethics committee proposals remain unknown in the beginning of planning an MDR-LT. Here, we derived the needed steps from medical product certification. This was done as the medical product certification itself also communicates a process-oriented approach rather than merely focusing on content. A proposal was created for validation and inspection of applicability by using the proposed building blocks. The proposed best practice was tested and refined within SEMPER (Secondary Malignoma - Prospective Evaluation of the Radiotherapeutics dose distribution as the cause for induction) as a case study.

Results

The proposed building blocks cover the topics of “Context Analysis”, “Requirements Analysis”, “Requirements Validation”, “Electronic Case Report (eCRF) Design” and “Overall Concept Creation”. Additional methods are attached with regards to each topic. The goals of each block can be met by applying those methods. The proposed methods are proven methods as applied in e.g. existing Medical Data Registry projects, as well as in software or requirements engineering.

Conclusion

Several building blocks and attached methods could be identified in the creation of a generic ethics committee proposal. Hence, an Ethics Committee can make informed decisions on the suggested study via said blocks, using the suggested methods such as “Defining Clinical Questions” within the Context Analysis. The study creators have to confirm that they adhere to the proposed procedure within the ethic proposal statement. Additional existing Medical Data Registry projects can be compared to EsPRit for conformity to the proposed procedure. This allows for the identification of gaps, which can lead to amendments requested by the ethics committee.

Improving the quality of care of patients with rheumatic disease using patient-centric electronic redesign software

OBJECTIVE

Electronic health records (EHRs) are not optimized for chronic disease management. To improve the quality of care for patients with rheumatic disease, we developed electronic data capture, aggregation, display, and documentation software.

METHODS

The software integrated and reassembled information from the patient (via a touchscreen questionnaire), nurse, physician, and EHR into a series of actionable views. Core functions included trends over time, rheumatology-related demographics, and documentation for patient and provider. Quality measures collected included patient-reported outcomes, disease activity, and function. The software was tested and implemented in 3 rheumatology departments, and integrated into routine care delivery. Post-implementation evaluation measured adoption, efficiency, productivity, and patient perception.

RESULTS

Over 2 years, 6,725 patients completed 19,786 touchscreen questionnaires. The software was adopted for use by 86% of patients and rheumatologists. Chart review and documentation time trended downward, and productivity increased by 26%. Patient satisfaction, activation, and adherence remained unchanged, although pre-implementation values were high. A strong correlation was seen between use of the software and disease control (weighted Pearson's correlation coefficient 0.5927, P = 0.0095), and a relative increase in patients with low disease activity of 3% per quarter was noted.

CONCLUSION

We describe innovative software that aggregates, stores, and displays information vital to improving the quality of care for patients with chronic rheumatic disease. The software was well-adopted by patients and providers. Post-implementation, significant improvements in quality of care, efficiency of care, and productivity were demonstrated.

Biomedical research in a Digital Health Framework

This article describes a Digital Health Framework (DHF), benefitting from the lessons learnt during the three-year life span of the FP7 Synergy-COPD project. The DHF aims to embrace the emerging requirements--data and tools--of applying systems medicine into healthcare with a three-tier strategy articulating formal healthcare, informal care and biomedical research. Accordingly, it has been constructed based on three key building blocks, namely, novel integrated care services with the support of information and communication technologies, a personal health folder (PHF) and a biomedical research environment (DHF-research). Details on the functional requirements and necessary components of the DHF-research are extensively presented. Finally, the specifics of the building blocks strategy for deployment of the DHF, as well as the steps toward adoption are analyzed. The proposed architectural solutions and implementation steps constitute a pivotal strategy to foster and enable 4P medicine (Predictive, Preventive, Personalized and Participatory) in practice and should provide a head start to any community and institution currently considering to implement a biomedical research platform.

Accelerating translational research by clinically driven development of an informatics platform--a case study

Translational medicine is becoming increasingly dependent upon data generated from health care, clinical research, and molecular investigations. This increasing rate of production and diversity in data has brought about several challenges, including the need to integrate fragmented databases, enable secondary use of patient clinical data from health care in clinical research, and to create information systems that clinicians and biomedical researchers can readily use. Our case study effectively integrates requirements from the clinical and biomedical researcher perspectives in a translational medicine setting. Our three principal achievements are (a) a design of a user-friendly web-based system for management and integration of clinical and molecular databases, while adhering to proper de-identification and security measures; (b) providing a real-world test of the system functionalities using clinical cohorts; and (c) system integration with a clinical decision support system to demonstrate system interoperability. We engaged two active clinical cohorts, 747 psoriasis patients and 2001 rheumatoid arthritis patients, to demonstrate efficient query possibilities across the data sources, enable cohort stratification, extract variation in antibody patterns, study biomarker predictors of treatment response in RA patients, and to explore metabolic profiles of psoriasis patients. Finally, we demonstrated system interoperability by enabling integration with an established clinical decision support system in health care. To assure the usefulness and usability of the system, we followed two approaches. First, we created a graphical user interface supporting all user interactions. Secondly we carried out a system performance evaluation study where we measured the average response time in seconds for active users, http errors, and kilobits per second received and sent. The maximum response time was found to be 0.12 seconds; no server or client errors of any kind were detected. In conclusion, the system can readily be used by clinicians and biomedical researchers in a translational medicine setting.

STATegra EMS: an Experiment Management System for complex next-generation omics experiments

High-throughput sequencing assays are now routinely used to study different aspects of genome organization. As decreasing costs and widespread availability of sequencing enable more laboratories to use sequencing assays in their research projects, the number of samples and replicates in these experiments can quickly grow to several dozens of samples and thus require standardized annotation, storage and management of preprocessing steps. As a part of the STATegra project, we have developed an Experiment Management System (EMS) for high throughput omics data that supports different types of sequencing-based assays such as RNA-seq, ChIP-seq, Methyl-seq, etc, as well as proteomics and metabolomics data. The STATegra EMS provides metadata annotation of experimental design, samples and processing pipelines, as well as storage of different types of data files, from raw data to ready-to-use measurements. The system has been developed to provide research laboratories with a freely-available, integrated system that offers a simple and effective way for experiment annotation and tracking of analysis procedures.