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

Author:

Dolin Robert1ORCID,Heale Bret S. E.2,Gupta Rohan3ORCID,Alvarez Carla1,Aronson Justin4,Boxwala Aziz1,Gothi Shaileshbhai R.5,Husami Ammar6,Shalaby James1,Babb Lawrence7ORCID,Wagner Alex8,Chamala Srikar9

Affiliation:

1. Elimu Informatics El Cerrito California USA

2. Humanized Health Consulting Salt Lake City Utah USA

3. Shri Mata Vaishno Devi University Katra India

4. Northwestern University Evanston Illinois USA

5. University of Florida Gainesville Florida USA

6. Cincinnati Children's Hospital Medical Center Cincinnati Ohio USA

7. Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge Massachusetts USA

8. Nationwide Children's Hospital/OSU Columbus Ohio USA

9. USC/Children's Hospital Los Angeles Los Angeles California USA

Abstract

AbstractIntroductionVariant 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.MethodsThe 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.ResultsPrimary 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.ConclusionsWe 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.

Funder

Office of the National Coordinator for Health Information Technology

Publisher

Wiley

Subject

Health Information Management,Public Health, Environmental and Occupational Health,Health Informatics

Reference30 articles.

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