Sync for Genes Phase 5: Computable artifacts for sharing dynamically annotated FHIR-formatted genomic variants.

Introduction: Variant annotation is a critical component in next-generation sequencing, enabling a sequencing lab to comb through a sea of variants in order to hone in on those likely to be most significant, and providing clinicians with necessary context for decision-making. But with the rapid evolution of genomics knowledge, reported annotations can quickly become out-of-date. Under the ONC Sync for Genes program, our team sought to standardize the sharing of dynamically annotated variants (e.g., variants annotated on demand, based on current knowledge). The computable biomedical knowledge artifacts that were developed enable a clinical decision support (CDS) application to surface up-to-date annotations to clinicians. Methods: The work reported in this article relies on the Health Level 7 Fast Healthcare Interoperability Resources (FHIR) Genomics and Global Alliance for Genomics and Health (GA4GH) Variant Annotation (VA) standards. We developed a CDS pipeline that dynamically annotates patient's variants through an intersection with current knowledge and serves up the FHIR-encoded variants and annotations (diagnostic and therapeutic implications, molecular consequences, population allele frequencies) via FHIR Genomics Operations. ClinVar, CIViC, and PharmGKB were used as knowledge sources, encoded as per the GA4GH VA specification. Results: Primary public artifacts from this project include a GitHub repository with all source code, a Swagger interface that allows anyone to visualize and interact with the code using only a web browser, and a backend database where all (synthetic and anonymized) patient data and knowledge are housed. Conclusions: We found that variant annotation varies in complexity based on the variant type, and that various bioinformatics strategies can greatly improve automated annotation fidelity. More importantly, we demonstrated the feasibility of an ecosystem where genomic knowledge bases have standardized knowledge (e.g., based on the GA4GH VA spec), and CDS applications can dynamically leverage that knowledge to provide real-time decision support, based on current knowledge, to clinicians at the point of care.

Automated HL7v2 LRI informatics framework for streamlining genomics-EHR data integration.

While VCF formatted files are the lingua franca of next-generation sequencing, most EHRs do not provide native VCF support. As a result, labs often must send non-structured PDF reports to the EHR. On the other hand, while FHIR adoption is growing, most EHRs support HL7 interoperability standards, particularly those based on the HL7 Version 2 (HL7v2) standard. The HL7 Version 2 genomics component of the HL7 Laboratory Results Interface (HL7v2 LRI) standard specifies a formalism for the structured communication of genomic data from lab to EHR. We previously described an open-source tool (vcf2fhir) that converts VCF files into HL7 FHIR format. In this report, we describe how the utility has been extended to output HL7v2 LRI data that contains both variants and variant annotations (e.g., predicted phenotypes and therapeutic implications). Using this HL7v2 converter, we implemented an automated pipeline for moving structured genomic data from the clinical laboratory to EHR. We developed an open source hl7v2GenomicsExtractor that converts genomic interpretation report files into a series of HL7v2 observations conformant to HL7v2 LRI. We further enhanced the converter to produce output conformant to Epic's genomic import specification and to support alternative input formats. An automated pipeline for pushing standards-based structured genomic data directly into the EHR was successfully implemented, where genetic variant data and the clinical annotations are now both available to be viewed in the EHR through Epic's genomics module. Issues encountered in the development and deployment of the HL7v2 converter primarily revolved around data variability issues, primarily lack of a standardized representation of data elements within various genomic interpretation report files. The technical implementation of a HL7v2 message transformation to feed genomic variant and clinical annotation data into an EHR has been successful. In addition to genetic variant data, the implementation described here releases the valuable asset of clinically relevant genomic annotations provided by labs from static PDFs to calculable, structured data in EHR systems.

Introducing HL7 FHIR Genomics Operations: a developer-friendly approach to genomics-EHR integration.

OBJECTIVE: Enabling clinicians to formulate individualized clinical management strategies from the sea of molecular data remains a fundamentally important but daunting task. Here, we describe efforts towards a new paradigm in genomics-electronic health record (HER) integration, using a standardized suite of FHIR Genomics Operations that encapsulates the complexity of molecular data so that precision medicine solution developers can focus on building applications. MATERIALS AND METHODS: FHIR Genomics Operations essentially "wrap" a genomics data repository, presenting a uniform interface to applications. More importantly, operations encapsulate the complexity of data within a repository and normalize redundant data representations-particularly relevant in genomics, where a tremendous amount of raw data exists in often-complex non-FHIR formats. RESULTS: Fifteen FHIR Genomics Operations have been developed, designed to support a wide range of clinical scenarios, such as variant discovery; clinical trial matching; hereditary condition and pharmacogenomic screening; and variant reanalysis. Operations are being matured through the HL7 balloting process, connectathons, pilots, and the HL7 FHIR Accelerator program. DISCUSSION: Next-generation sequencing can identify thousands to millions of variants, whose clinical significance can change over time as our knowledge evolves. To manage such a large volume of dynamic and complex data, new models of genomics-EHR integration are needed. Qualitative observations to date suggest that freeing application developers from the need to understand the nuances of genomic data, and instead base applications on standardized APIs can not only accelerate integration but also dramatically expand the applications of Omic data in driving precision care at scale for all.

HerediGene Population Study IT infrastructure: A model to support genomic research recruitment and precision public health.

The HerediGene Population Study is a large research study focused on identifying new genetic biomarkers for disease prevention, diagnosis, prognosis, and development of new therapeutics. A substantial IT infrastructure evolved to reach enrollment targets and return results to participants. More than 170,000 participants have been enrolled in the study to date, with 5.87% of those whole genome sequenced and 0.46% of those genotyped harboring pathogenic variants. Among other purposes, this infrastructure supports: (1) identifying candidates from clinical criteria, (2) monitoring for qualifying clinical events (e.g., blood draw), (3) contacting candidates, (4) obtaining consent electronically, (5) initiating lab orders, (6) integrating consent and lab orders into clinical workflow, (7) de-identifying samples and clinical data, (8) shipping/transmitting samples and clinical data, (9) genotyping/sequencing samples, (10) and re-identifying and returning results for participants where applicable. This study may serve as a model for similar genomic research and precision public health initiatives.

The Development of an Infrastructure to Facilitate the Use of Whole Genome Sequencing for Population Health.

The clinical use of genomic analysis has expanded rapidly resulting in an increased availability and utility of genomic information in clinical care. We have developed an infrastructure utilizing informatics tools and clinical processes to facilitate the use of whole genome sequencing data for population health management across the healthcare system. Our resulting framework scaled well to multiple clinical domains in both pediatric and adult care, although there were domain specific challenges that arose. Our infrastructure was complementary to existing clinical processes and well-received by care providers and patients. Informatics solutions were critical to the successful deployment and scaling of this program. Implementation of genomics at the scale of population health utilizes complicated technologies and processes that for many health systems are not supported by current information systems or in existing clinical workflows. To scale such a system requires a substantial clinical framework backed by informatics tools to facilitate the flow and management of data. Our work represents an early model that has been successful in scaling to 29 different genes with associated genetic conditions in four clinical domains. Work is ongoing to optimize informatics tools; and to identify best practices for translation to smaller healthcare systems.

vcf2fhir: a utility to convert VCF files into HL7 FHIR format for genomics-EHR integration.

BACKGROUND: VCF formatted files are the lingua franca of next-generation sequencing, whereas HL7 FHIR is emerging as a standard language for electronic health record interoperability. A growing number of FHIR-based clinical genomics applications are emerging. Here, we describe an open source utility for converting variants from VCF format into HL7 FHIR format. RESULTS: vcf2fhir converts VCF variants into a FHIR Genomics Diagnostic Report. Conversion translates each VCF row into a corresponding FHIR-formatted variant in the generated report. In scope are simple variants (SNVs, MNVs, Indels), along with zygosity and phase relationships, for autosomes, sex chromosomes, and mitochondrial DNA. Input parameters include VCF file and genome build ('GRCh37' or 'GRCh38'); and optionally a conversion region that indicates the region(s) to convert, a studied region that lists genomic regions studied by the lab, and a non-callable region that lists studied regions deemed uncallable by the lab. Conversion can be limited to a subset of VCF by supplying genomic coordinates of the conversion region(s). If studied and non-callable regions are also supplied, the output FHIR report will include 'region-studied' observations that detail which portions of the conversion region were studied, and of those studied regions, which portions were deemed uncallable. We illustrate the vcf2fhir utility via two case studies. The first, 'SMART Cancer Navigator', is a web application that offers clinical decision support by linking patient EHR information to cancerous gene variants. The second, 'Precision Genomics Integration Platform', intersects a patient's FHIR-formatted clinical and genomic data with knowledge bases in order to provide on-demand delivery of contextually relevant genomic findings and recommendations to the EHR. CONCLUSIONS: Experience to date shows that the vcf2fhir utility can be effectively woven into clinically useful genomic-EHR integration pipelines. Additional testing will be a critical step towards the clinical validation of this utility, enabling it to be integrated in a variety of real world data flow scenarios. For now, we propose the use of this utility primarily to accelerate FHIR Genomics understanding and to facilitate experimentation with further integration of genomics data into the EHR.

Functional Transcription Factor Target Networks Illuminate Control of Epithelial Remodelling.

Cell identity is governed by gene expression, regulated by transcription factor (TF) binding at cis-regulatory modules. Decoding the relationship between TF binding patterns and gene regulation is nontrivial, remaining a fundamental limitation in understanding cell decision-making. We developed the NetNC software to predict functionally active regulation of TF targets; demonstrated on nine datasets for the TFs Snail, Twist, and modENCODE Highly Occupied Target (HOT) regions. Snail and Twist are canonical drivers of epithelial to mesenchymal transition (EMT), a cell programme important in development, tumour progression and fibrosis. Predicted "neutral" (non-functional) TF binding always accounted for the majority (50% to 95%) of candidate target genes from statistically significant peaks and HOT regions had higher functional binding than most of the Snail and Twist datasets examined. Our results illuminated conserved gene networks that control epithelial plasticity in development and disease. We identified new gene functions and network modules including crosstalk with notch signalling and regulation of chromatin organisation, evidencing networks that reshape Waddington's epigenetic landscape during epithelial remodelling. Expression of orthologous functional TF targets discriminated breast cancer molecular subtypes and predicted novel tumour biology, with implications for precision medicine. Predicted invasion roles were validated using a tractable cell model, supporting our approach.

FHIR Genomics: enabling standardization for precision medicine use cases.

The development of Fast Healthcare Interoperability Resources (FHIR) Genomics, a feasible and efficient method for exchanging complex clinical genomic data and interpretations, is described. FHIR Genomics is a subset of the emerging Health Level 7 FHIR standard and targets data from increasingly available technologies such as next-generation sequencing. Much care and integration of feedback have been taken to ease implementation, facilitate wide-scale interoperability, and enable modern app development toward a complete precision medicine standard. A new use case, the integration of the Variant Interpretation for Cancer Consortium (VICC) "meta-knowledgebase" into a third-party application, is described.

Lessons Learned in Creating Interoperable Fast Healthcare Interoperability Resources Profiles for Large-Scale Public Health Programs.

OBJECTIVE: This article describes lessons learned from the collaborative creation of logical models and standard Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) profiles for family planning and reproductive health. The National Health Service delivery program will use the FHIR profiles to improve federal reporting, program monitoring, and quality improvement efforts. MATERIALS AND METHODS: Organizational frameworks, work processes, and artifact testing to create FHIR profiles are described. RESULTS: Logical models and FHIR profiles for the Family Planning Annual Report 2.0 dataset have been created and validated. DISCUSSION: Using clinical element models and FHIR to meet the needs of a real-world use case has been accomplished but has also demonstrated the need for additional tooling, terminology services, and application sandbox development. CONCLUSION: FHIR profiles may reduce the administrative burden for the reporting of federally mandated program data.

Physicians' pharmacogenomics information needs and seeking behavior: a study with case vignettes.

BACKGROUND: Genetic testing, especially in pharmacogenomics, can have a major impact on patient care. However, most physicians do not feel that they have sufficient knowledge to apply pharmacogenomics to patient care. Online information resources can help address this gap. We investigated physicians' pharmacogenomics information needs and information-seeking behavior, in order to guide the design of pharmacogenomics information resources that effectively meet clinical information needs. METHODS: We performed a formative, mixed-method assessment of physicians' information-seeking process in three pharmacogenomics case vignettes. Interactions of 6 physicians' with online pharmacogenomics resources were recorded, transcribed, and analyzed for prominent themes. Quantitative data included information-seeking duration, page navigations, and number of searches entered. RESULTS: We found that participants searched an average of 8 min per case vignette, spent less than 30 s reviewing specific content, and rarely refined search terms. Participants' information needs included a need for clinically meaningful descriptions of test interpretations, a molecular basis for the clinical effect of drug variation, information on the logistics of carrying out a genetic test (including questions related to cost, availability, test turn-around time, insurance coverage, and accessibility of expert support).Also, participants sought alternative therapies that would not require genetic testing. CONCLUSION: This study of pharmacogenomics information-seeking behavior indicates that content to support their information needs is dispersed and hard to find. Our results reveal a set of themes that information resources can use to help physicians find and apply pharmacogenomics information to the care of their patients.

Optimization of infobutton design and Implementation: A systematic review.

OBJECTIVE: Infobuttons are clinical decision tools embedded in the electronic health record that attempt to link clinical data with context sensitive knowledge resources. We systematically reviewed technical approaches that contribute to improved infobutton design, implementation and functionality. METHODS: We searched databases including MEDLINE, EMBASE, and the Cochrane Library database from inception to March 1, 2016 for studies describing the use of infobuttons. We selected full review comparative studies, usability studies, and qualitative studies examining infobutton design and implementation. We abstracted usability measures such as user satisfaction, impact, and efficiency, as well as prediction accuracy of infobutton content retrieval algorithms and infobutton adoption/interoperability. RESULTS: We found 82 original research studies on infobuttons. Twelve studies met criteria for detailed abstraction. These studies investigated infobutton interoperability (1 study); tools to help tailor infobutton functionality (1 study); interventions to improve user experience (7 studies); and interventions to improve content retrieval by improving prediction of relevant knowledge resources and information needs (3 studies). In-depth interviews with implementers showed the Health Level Seven (HL7) Infobutton standard to be simple and easy to implement. A usability study demonstrated the feasibility of a tool to help medical librarians tailor infobutton functionality. User experience studies showed that access to resources with which users are familiar increased user satisfaction ratings; and that links to specific subsections of drug monographs increased information seeking efficiency. However, none of the user experience improvements led to increased usage uptake. Recommender systems based on machine learning algorithms outperformed hand-crafted rules in the prediction of relevant resources and clinicians' information needs in a laboratory setting, but no studies were found using these techniques in clinical settings. Improved content indexing in one study led to improved content retrieval across three health care organizations. CONCLUSION: Best practice technical approaches to ensure optimal infobutton functionality, design and implementation remain understudied. The HL7 Infobutton standard has supported wide adoption of infobutton functionality among clinical information systems and knowledge resources. Limited evidence supports infobutton enhancements such as links to specific subtopics, configuration of optimal resources for specific tasks and users, and improved indexing and content coverage. Further research is needed to investigate user experience improvements to increase infobutton use and effectiveness.

Context-sensitive decision support (infobuttons) in electronic health records: a systematic review.

OBJECTIVE: Infobuttons appear as small icons adjacent to electronic health record (EHR) data (e.g., medications, diagnoses, or test results) that, when clicked, access online knowledge resources tailored to the patient, care setting, or task. Infobuttons are required for "Meaningful Use" certification of US EHRs. We sought to evaluate infobuttons' impact on clinical practice and identify features associated with improved outcomes. METHODS: We conducted a systematic review, searching MEDLINE, EMBASE, and other databases from inception to July 6, 2015. We included and cataloged all original research in any language describing implementation of infobuttons or other context-sensitive links. Studies evaluating clinical implementations with outcomes of usage or impact were reviewed in greater detail. Reviewers worked in duplicate to select articles, evaluate quality, and abstract information. RESULTS: Of 599 potential articles, 77 described infobutton implementation. The 17 studies meriting detailed review, including 3 randomized trials, yielded the following findings. Infobutton usage frequency ranged from 0.3 to 7.4 uses per month per potential user. Usage appeared to be influenced by EHR task. Five studies found that infobuttons are used less often than non-context-sensitive links (proportionate usage 0.20-0.34). In 3 studies, users answered their clinical question in > 69% of infobutton sessions. Seven studies evaluated alternative approaches to infobutton design and implementation. No studies isolated the impact of infobuttons on objectively measured patient outcomes. CONCLUSIONS: Weak evidence suggests that infobuttons can help providers answer clinical questions. Research on optimal infobutton design and implementation, and on the impact on patient outcomes and provider behaviors, is needed.

Integrating Genomic Resources with Electronic Health Records using the HL7 Infobutton Standard.

BACKGROUND: The Clinical Genome Resource (ClinGen) Electronic Health Record (EHR) Workgroup aims to integrate ClinGen resources with EHRs. A promising option to enable this integration is through the Health Level Seven (HL7) Infobutton Standard. EHR systems that are certified according to the US Meaningful Use program provide HL7-compliant infobutton capabilities, which can be leveraged to support clinical decision-making in genomics. OBJECTIVES: To integrate genomic knowledge resources using the HL7 infobutton standard. Two tactics to achieve this objective were: (1) creating an HL7-compliant search interface for ClinGen, and (2) proposing guidance for genomic resources on achieving HL7 Infobutton standard accessibility and compliance. METHODS: We built a search interface utilizing OpenInfobutton, an open source reference implementation of the HL7 Infobutton standard. ClinGen resources were assessed for readiness towards HL7 compliance. Finally, based upon our experiences we provide recommendations for publishers seeking to achieve HL7 compliance. RESULTS: Eight genomic resources and two sub-resources were integrated with the ClinGen search engine via OpenInfobutton and the HL7 infobutton standard. Resources we assessed have varying levels of readiness towards HL7-compliance. Furthermore, we found that adoption of standard terminologies used by EHR systems is the main gap to achieve compliance. CONCLUSION: Genomic resources can be integrated with EHR systems via the HL7 Infobutton standard using OpenInfobutton. Full compliance of genomic resources with the Infobutton standard would further enhance interoperability with EHR systems.

RNA-sequencing analysis of 5' capped RNAs identifies many new differentially expressed genes in acute hepatitis C virus infection.

We describe the first report of RNA sequencing of 5' capped (Pol II) RNAs isolated from acutely hepatitis C virus (HCV) infected Huh 7.5 cells that provides a general approach to identifying differentially expressed annotated and unannotated genes that participate in viral-host interactions. We identified 100, 684, and 1,844 significantly differentially expressed annotated genes in acutely infected proliferative Huh 7.5 cells at 6, 48, and 72 hours, respectively (fold change ≥ 1.5 and Bonferroni adjusted p-values < 0.05). Most of the differentially expressed genes (>80%) and biological pathways (such as adipocytokine, Notch, Hedgehog and NOD-like receptor signaling) were not identified by previous gene array studies. These genes are critical components of host immune, inflammatory and oncogenic pathways and provide new information regarding changes that may benefit the virus or mediate HCV induced pathology. RNAi knockdown studies of newly identified highly upregulated FUT1 and KLHDC7B genes provide evidence that their gene products regulate and facilitate HCV replication in hepatocytes. Our approach also identified novel Pol II unannotated transcripts that were upregulated. Results further identify new pathways that regulate HCV replication in hepatocytes and suggest that our approach will have general applications in studying viral-host interactions in model systems and clinical biospecimens.

Solution structure of the N-terminal dsRBD of Drosophila ADAR and interaction studies with RNA.

Adenosine deaminases that act on RNA (ADAR) catalyze adenosine to inosine (A-to-I) editing in double-stranded RNA (dsRNA) substrates. Inosine is read as guanosine by the translation machinery; therefore A-to-I editing events in coding sequences may result in recoding genetic information. Whereas vertebrates have two catalytically active enzymes, namely ADAR1 and ADAR2, Drosophila has a single ADAR protein (dADAR) related to ADAR2. The structural determinants controlling substrate recognition and editing of a specific adenosine within dsRNA substrates are only partially understood. Here, we report the solution structure of the N-terminal dsRNA binding domain (dsRBD) of dADAR and use NMR chemical shift perturbations to identify the protein surface involved in RNA binding. Additionally, we show that Drosophila ADAR edits the R/G site in the mammalian GluR-2 pre-mRNA which is naturally modified by both ADAR1 and ADAR2. We then constructed a model showing how dADAR dsRBD1 binds to the GluR-2 R/G stem-loop. This model revealed that most side chains interacting with the RNA sugar-phosphate backbone need only small displacement to adapt for dsRNA binding and are thus ready to bind to their dsRNA target. It also predicts that dADAR dsRBD1 would bind to dsRNA with less sequence specificity than dsRBDs of ADAR2. Altogether, this study gives new insights into dsRNA substrate recognition by Drosophila ADAR.

The Effect of RNA Editing and ADARs on miRNA Biogenesis and Function.

From analysis of deep-sequencing data it is apparent that sequence differences occur between the genome and miRNAs. Changes from genomic A to an apparent G in miRNA can be accounted for by the editing activity of ADARs. Questions that arise from this observation are: How many miRNAs are edited and to what frequency? Is there a specific step in the biogenesis of miRNAs that is preferentially susceptible to editing by ADARs? However the key question is whether editing affects the downstream activity of miRNAs. Despite much evidence that miRNAs are edited, critical examination of the functional data shows a dearth of examples where editing has been demonstrated to actually affect the downstream miRNA activity in vivo. Even where it is demonstrated that RNA editing can affect biogenesis or targeting of a particular miRNA, effects may be limited by redundancy within the miRNA network.

A role for human Dicer in pre-RISC loading of siRNAs.

RNA interference is a powerful mechanism for sequence-specific inhibition of gene expression. It is widely known that small interfering RNAs (siRNAs) targeting the same region of a target-messenger RNA can have widely different efficacies. In efforts to better understand the siRNA features that influence knockdown efficiency, we analyzed siRNA interactions with a high-molecular weight complex in whole cell extracts prepared from two different cell lines. Using biochemical tools to study the nature of the complex, our results demonstrate that the primary siRNA-binding protein in the whole cell extracts is Dicer. We find that Dicer is capable of discriminating highly functional versus poorly functional siRNAs by recognizing the presence of 2-nt 3' overhangs and the thermodynamic properties of 2-4 bp on both ends of effective siRNAs. Our results suggest a role for Dicer in pre-selection of effective siRNAs for handoff to Ago2. This initial selection is reflective of the overall silencing potential of an siRNA.

Analysis of A to I editing of miRNA in macrophages exposed to Salmonella.

The main mediator of the lipopolysaccharide (LPS) response in macrophages is activation of Toll-like receptor 4 (TLR4). This generates interferon-beta (INF-beta) production that stimulates increased expression of the RNA editing enzyme ADAR1. To determine if there is an increase in RNA editing in mature miRNA in response to TLR4 activation upon Salmonella infection of macrophages we analyzed small RNA deep sequencing data. Interestingly, we found that direct infection of macrophage cell lines with Salmonella does not result in an increase of edited mature miRNA. Thus, despite elevated levels of ADAR1 during TLR4 activation of macrophages mediated by Salmonella infection, ADAR1 does not result in redirection of miRNA. The most common consequence of ADAR activity on miRNA is a reduction in the mature miRNA level due to interference with miRNA processing of pri-miRNA. However, we found very few miRNAs with reductions in level, and no significant difference between miRNAs previously reported to be edited and those reported to be not edited. In particular, we did not see significant decrease in mir-22 and mir-142, nor editing of pri-mir-22 or pri-mir-142 in infected RAW macrophages. Thus, ADAR1 has very little, if any, effect on the miRNA machinery following TL4 activation by Salmonella infection.

The effect of RNA editing and ADARs on miRNA biogenesis and function.

From analysis of deep-sequencing data it is apparent that sequence differences occur between the genome and miRNAs. Changes from genomic A to an apparent G in miRNA can be accounted for by the editing activity of ADARs. Questions that arise from this observation are: How many miRNAs are edited and to what frequency? Is there a specific step inthebiogenesis of miRNAs that is preferentially susceptible to editing by ADARs? However the key question is whether editing affects the downstream activity ofmiRNAs. Despite much evidence that miRNAs are edited, critical examination of the functional data shows a dearth of examples where editing has been demonstrated to actually affect the downstream miRNA activity in vivo. Even where it is demonstratedthat RNA editing can affect biogenesis or targeting of a particular miRNA, effects may be limited by redundancy within the miRNA network.