Marc Natter

Somatic KRAS mutations associated with a human nonmalignant syndrome of autoimmunity and abnormal leukocyte homeostasis.

Somatic gain-of-function mutations in members of the RAS subfamily of small guanosine triphosphatases are found in > 30% of all human cancers. We recently described a syndrome of chronic nonmalignant lymphadenopathy, splenomegaly, and autoimmunity associated with a mutation in NRAS affecting hematopoietic cells, and initially we classified the disease as a variant of the autoimmune lymphoproliferative syndrome. Here, we demonstrate that somatic mutations in the related KRAS gene can also be associated with a nonmalignant syndrome of autoimmunity and breakdown of leukocyte homeostasis. The activating KRAS mutation impaired cytokine withdrawal-induced T-cell apoptosis through the suppression of the proapoptotic protein BCL-2 interacting mediator of cell death and facilitated proliferation through p27(kip1) down-regulation. These defects could be corrected in vitro by mitogen-activated protein kinase/extracellular signal-regulated kinase kinase 1 or phosphatidyl inositol-3 kinase inhibition. We suggest the use of the term RAS-associated autoimmune leukoproliferative disease to differentiate this disorder from autoimmune lymphoproliferative syndrome.

An i2b2-based, generalizable, open source, self-scaling chronic disease registry

Objective Registries are a well-established mechanism for obtaining high quality, disease-specific data, but are often highly project-specific in their design, implementation, and policies for data use. In contrast to the conventional model of centralized data contribution, warehousing, and control, we design a self-scaling registry technology for collaborative data sharing, based upon the widely adopted Integrating Biology & the Bedside (i2b2) data warehousing framework and the Shared Health Research Information Network (SHRINE) peer-to-peer networking software. Materials and methods Focusing our design around creation of a scalable solution for collaboration within multi-site disease registries, we leverage the i2b2 and SHRINE open source software to create a modular, ontology-based, federated infrastructure that provides research investigators full ownership and access to their contributed data while supporting permissioned yet robust data sharing. We accomplish these objectives via web services supporting peer-group overlays, group-aware data aggregation, and administrative functions. Results The 56-site Childhood Arthritis & Rheumatology Research Alliance (CARRA) Registry and 3-site Harvard Inflammatory Bowel Diseases Longitudinal Data Repository now utilize i2b2 self-scaling registry technology (i2b2-SSR). This platform, extensible to federation of multiple projects within and between research networks, encompasses >6000 subjects at sites throughout the USA. Discussion We utilize the i2b2-SSR platform to minimize technical barriers to collaboration while enabling fine-grained control over data sharing. Conclusions The implementation of i2b2-SSR for the multi-site, multi-stakeholder CARRA Registry has established a digital infrastructure for community-driven research data sharing in pediatric rheumatology in the USA. We envision i2b2-SSR as a scalable, reusable solution facilitating interdisciplinary research across diseases.

Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS): architecture.

We describe the architecture of the Patient Centered Outcomes Research Institute (PCORI) funded Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS, http://www.SCILHS.org) clinical data research network, which leverages the

Using Registries to Identify Adverse Events in Rheumatic Diseases

48 billion dollar federal investment in health information technology (IT) to enable a queryable semantic data model across 10 health systems covering more than 8 million patients, plugging universally into the point of care, generating evidence and discovery, and thereby enabling clinician and patient participation in research during the patient encounter. Central to the success of SCILHS is development of innovative ‘apps’ to improve PCOR research methods and capacitate point of care functions such as consent, enrollment, randomization, and outreach for patient-reported outcomes. SCILHS adapts and extends an existing national research network formed on an advanced IT infrastructure built with open source, free, modular components.

Biologic therapies for refractory juvenile dermatomyositis: five years of experience of the Childhood Arthritis and Rheumatology Research Alliance in North America

The proven effectiveness of biologics and other immunomodulatory products in inflammatory rheumatic diseases has resulted in their widespread use as well as reports of potential short- and long-term complications such as infection and malignancy. These complications are especially worrisome in children who often have serial exposures to multiple immunomodulatory products. Post-marketing surveillance of immunomodulatory products in juvenile idiopathic arthritis (JIA) and pediatric systemic lupus erythematosus is currently based on product-specific registries and passive surveillance, which may not accurately reflect the safety risks for children owing to low numbers, poor long-term retention, and inadequate comparators. In collaboration with the US Food and Drug Administration (FDA), patient and family advocacy groups, biopharmaceutical industry representatives and other stakeholders, the Childhood Arthritis and Rheumatology Research Alliance (CARRA) and the Duke Clinical Research Institute (DCRI) have developed a novel pharmacosurveillance model (CARRA Consolidated Safety Registry [CoRe]) based on a multicenter longitudinal pediatric rheumatic diseases registry with over 8000 participants. The existing CARRA infrastructure provides access to much larger numbers of subjects than is feasible in single-product registries. Enrollment regardless of medication exposure allows more accurate detection and evaluation of safety signals. Flexibility built into the model allows the addition of specific data elements and safety outcomes, and designation of appropriate disease comparator groups relevant to each product, fulfilling post-marketing requirements and commitments. The proposed model can be applied to other pediatric and adult diseases, potentially transforming the paradigm of pharmacosurveillance in response to the growing public mandate for rigorous post-marketing safety monitoring.

C3-PRO: Connecting ResearchKit to the Health System Using i2b2 and FHIR.

BackgroundThe prognosis of children with juvenile dermatomyositis (JDM) has improved remarkably since the 1960’s with the use of corticosteroid and immunosuppressive therapy. Yet there remain a minority of children who have refractory disease. Since 2003 the sporadic use of biologics (genetically-engineered proteins that usually are derived from human genes) for inflammatory myositis has been reported. In 2011–2016 we investigated our collective experience of biologics in JDM through the Childhood Arthritis and Rheumatology Research Alliance (CARRA).MethodsThe JDM biologic study group developed a survey on the CARRA member experience using biologics for Juvenile DM utilizing Delphi consensus methods in 2011–2012. The survey was completed online by the CARRA members interested in JDM in 2012. A second survey was similarly developed that provided more opportunity to describe their experiences with biologics in JDM in detail and was completed by CARRA members in Feb 2013. During three CARRA meetings in 2013–2015, nominal group techniques were used for achieving consensus on the current choices of biologic drugs. A final survey was performed at the 2016 CARRA meeting.ResultsOne hundred and five of a potential 231 pediatric rheumatologists (42%) responded to the first survey in 2012. Thirty-five of 90 had never used a biologic for Juvenile DM at that time. Fifty-five of 91 (denominators vary) had used biologics for JDM in their practice with 32%, 5%, and 4% using rituximab, etanercept, and infliximab, respectively, and 17% having used more than one of the three drugs. Ten percent used a biologic as monotherapy, 19% a biologic in combination with methotrexate (mtx), 52% a biologic in combination with mtx and corticosteroids, 42% a combination of a biologic, mtx, corticosteroids (steroids), and an immunosuppressive drug, and 43% a combination of a biologic, IVIG and mtx. The results of the second survey supported these findings in considerably more detail with multiple combinations of drugs used with biologics and supported the use of rituximab, abatacept, anti-TNFα drugs, and tocilizumab in that order. One hundred percent recommended that CARRA continue studying biologics for JDM. The CARRA meeting survey in 2016 again supported the study and use of these four biologic drug groups.ConclusionsOur CARRA JDM biologic work group developed and performed three surveys demonstrating that pediatric rheumatologists in North America have been using multiple biologics for refractory JDM in numerous scenarios from 2011 to 2016. These survey results and our consensus meetings determined our choice of four biologic therapies (rituximab, abatacept, tocilizumab and anti-TNFα drugs) to consider for refractory JDM treatment when indicated and to evaluate for comparative effectiveness and safety in the future.Significance and InnovationsThis is the first report that provides a substantial clinical experience of a large group of pediatric rheumatologists with biologics for refractory JDM over five years.This experience with biologic therapies for refractory JDM may aid pediatric rheumatologists in the current treatment of these children and form a basis for further clinical research into the comparative effectiveness and safety of biologics for refractory JDM.

Learning a Comorbidity-Driven Taxonomy of Pediatric Pulmonary Hypertension

A renewed interest by consumer information technology giants in the healthcare domain is focused on transforming smartphones into personal health data storage devices. With the introduction of the open source ResearchKit, Apple provides a framework for researchers to inform and consent research subjects, and to readily collect personal health data and patient reported outcomes (PRO) from distributed populations. However, being research backend agnostic, ResearchKit does not provide data transmission facilities, leaving research apps disconnected from the health system. Personal health data and PROs are of the most value when presented in context along with health system data. Our aim was to build a toolchain that allows easy and secure integration of personal health and PRO data into an open source platform widely adopted across 140 academic medical centers. We present C3-PRO: the Consent, Contact, and Community framework for Patient Reported Outcomes. This open source toolchain connects, in a standards-compliant fashion, any ResearchKit app to the widely-used clinical research infrastructure Informatics for Integrating Biology and the Bedside (i2b2). C3-PRO leverages the emerging health data standard Fast Healthcare Interoperability Resources (FHIR).

Scalable collaborative infrastructure for a learning healthcare system (SCILHS)

Rationale: Pediatric pulmonary hypertension (PH) is a heterogeneous condition with varying natural history and therapeutic response. Precise classification of PH subtypes is, therefore, crucial for individualizing care. However, gaps remain in our understanding of the spectrum of PH in children. Objective: We seek to study the manifestations of PH in children and to assess the feasibility of applying a network-based approach to discern disease subtypes from comorbidity data recorded in longitudinal data sets. Methods and Results: A retrospective cohort study comprising 6 943 263 children (<18 years of age) enrolled in a commercial health insurance plan in the United States, between January 2010 and May 2013. A total of 1583 (0.02%) children met the criteria for PH. We identified comorbidities significantly associated with PH compared with the general population of children without PH. A Bayesian comorbidity network was constructed to model the interdependencies of these comorbidities, and network-clustering analysis was applied to derive disease subtypes comprising subgraphs of highly connected comorbid conditions. A total of 186 comorbidities were found to be significantly associated with PH. Network analysis of comorbidity patterns captured most of the major PH subtypes with known pathological basis defined by the World Health Organization and Panama classifications. The analysis further identified many subtypes documented in only a few case studies, including rare subtypes associated with several well-described genetic syndromes. Conclusions: Application of network science to model comorbidity patterns recorded in longitudinal data sets can facilitate the discovery of disease subtypes. Our analysis relearned established subtypes, thus validating the approach, and identified rare subtypes that are difficult to discern through clinical observations, providing impetus for deeper investigation of the disease subtypes that will enrich current disease classifications.

A Computable Phenotype Improves Cohort Ascertainment in a Pediatric Pulmonary Hypertension Registry

We describe the architecture of the Patient Centered Outcomes Research Institute (PCORI) funded Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS, http://www.SCILHS.org) clinical data research network, which leverages the

Brief communication: Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS): Architecture

48 billion dollar federal investment in health information technology (IT) to enable a queryable semantic data model across 10 health systems covering more than 8 million patients, plugging universally into the point of care, generating evidence and discovery, and thereby enabling clinician and patient participation in research during the patient encounter. Central to the success of SCILHS is development of innovative ‘apps’ to improve PCOR research methods and capacitate point of care functions such as consent, enrollment, randomization, and outreach for patient-reported outcomes. SCILHS adapts and extends an existing national research network formed on an advanced IT infrastructure built with open source, free, modular components.