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 But with the rapid evolution of genomics knowledge, reported annotations can quickly become out-of-date.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.

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.

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.

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.

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.

Editing independent effects of ADARs on the miRNA/siRNA pathways.

Adenosine deaminases acting on RNA (ADARs) are best known for altering the coding sequences of mRNA through RNA editing, as in the GluR-B Q/R site. ADARs have also been shown to affect RNA interference (RNAi) and microRNA processing by deamination of specific adenosines to inosine. Here, we show that ADAR proteins can affect RNA processing independently of their enzymatic activity. We show that ADAR2 can modulate the processing of mir-376a2 independently of catalytic RNA editing activity. In addition, in a Drosophila assay for RNAi deaminase-inactive ADAR1 inhibits RNAi through the siRNA pathway. These results imply that ADAR1 and ADAR2 have biological functions as RNA-binding proteins that extend beyond editing per se and that even genomically encoded ADARs that are catalytically inactive may have such functions.

Potent siRNA inhibitors of ribonucleotide reductase subunit RRM2 reduce cell proliferation in vitro and in vivo.

PURPOSE: Ribonucleotide reductase (RR) is a therapeutic target for DNA replication-dependent diseases such as cancer. Here, a potent small interfering RNA (siRNA) duplex against the M2 subunit of RR (RRM2) is developed and shown to reduce the growth potential of cancer cells both in vitro and in vivo. EXPERIMENTAL DESIGN: Three anti-RRM2 siRNAs were identified via computational methods, and the potency of these and additional "tiling" duplexes was analyzed in cultured cells via cotransfections using a RRM2-luciferase fusion construct. Knockdown of RRM2 by the best duplex candidates was confirmed directly by Western blotting. The effect of potent duplexes on cell growth was investigated by a real-time cell electronic sensing assay. Finally, duplex performance was tested in vivo in luciferase-expressing cells via whole animal bioluminescence imaging. RESULTS: Moderate anti-RRM2 effects are observed from the three duplexes identified by computational methods. However, the tiling experiments yielded an extremely potent duplex (siR2B+5). This duplex achieves significant knockdown of RRM2 protein in cultured cells and has pronounced antiproliferative activity. S.c. tumors of cells that had been transfected with siR2B+5 preinjection grew slower than those of control cells. CONCLUSIONS: An anti-RRM2 siRNA duplex is identified that exhibits significant antiproliferative activity in cancer cells of varying human type and species (mouse, rat, monkey); these findings suggest that this duplex is a promising candidate for therapeutic development.

Distance constraints between microRNA target sites dictate efficacy and cooperativity.

MicroRNAs (miRNAs) have the potential to regulate the expression of thousands of genes, but the mechanisms that determine whether a gene is targeted or not are poorly understood. We studied the genomic distribution of distances between pairs of identical miRNA seeds and found a propensity for moderate distances greater than about 13 nt between seed starts. Experimental data show that optimal down-regulation is obtained when two seed sites are separated by between 13 and 35 nt. By analyzing the distance between seed sites of endogenous miRNAs and transfected small interfering RNAs (siRNAs), we also find that cooperative targeting of sites with a separation in the optimal range can explain some of the siRNA off-target effects that have been reported in the literature.

siRNA target site secondary structure predictions using local stable substructures.

The crystal structure based model of the catalytic center of Ago2 revealed that the siRNA and the mRNA must be able to form an A-helix for correct positing of the scissile phosphate bond for cleavage in RNAi. This suggests that base pairing of the target mRNA with itself, i.e. secondary structure, must be removed before cleavage. Early on in the siRNA design, GC-rich target sites were avoided because of their potential to be involved in strong secondary structure. It is still unclear how important a factor mRNA secondary structure is in RNAi. However, it has been established that a difference in the thermostability of the ends of an siRNA duplex dictate which strand is loaded into the RNA-induced silencing complex. Here, we use a novel secondary structure prediction method and duplex-end differential calculations to investigate the importance of a secondary structure in the siRNA design. We found that the differential duplex-end stabilities alone account for functional prediction of 60% of the 80 siRNA sites examined, and that secondary structure predictions improve the prediction of site efficacy. A total of 80% of the non-functional sites can be eliminated using secondary structure predictions and duplex-end differential.