Neptune: an environment for the delivery of genomic medicine

eMERGE Consortium

doi:10.1038/s41436-021-01230-w

Neptune: an environment for the delivery of genomic medicine

eMERGE Consortium

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

Purpose: Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. Methods: We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Results: Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Conclusion: Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune.

Original language	English (US)
Pages (from-to)	1838-1846
Number of pages	9
Journal	Genetics in Medicine
Volume	23
Issue number	10
DOIs	https://doi.org/10.1038/s41436-021-01230-w
State	Published - Oct 2021

Funding

This work was funded by internal operating funds of the Baylor College of Medicine Human Genome Sequencing Center (HGSC), and by the National Institutes of Health (NIH) eMERGE program Phase III: U01HG8657 (Kaiser Permanente Washington/ University of Washington); U01HG8685 (Brigham and Women’s Hospital); U01HG8672 (Vanderbilt University Medical Center); U01HG8666 (Cincinnati Children’s Hospital Medical Center); U01HG6379 (Mayo Clinic); U01HG8679 (Geisinger Clinic); U01HG8680 (Columbia University Health Sciences); U01HG8684 (Children’s Hospital of Philadelphia); U01HG8673 (Northwestern University); U01HG8701 (Vanderbilt University Medical Center serving as the Coordinating Center); U01HG8676 (Partners Healthcare/Broad Institute); and U01HG8664 (Baylor College of Medicine).

ASJC Scopus subject areas

Genetics(clinical)

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10.1038/s41436-021-01230-w

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@article{468d862ae5494908924d67642fe93a91,

title = "Neptune: an environment for the delivery of genomic medicine",

abstract = "Purpose: Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. Methods: We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Results: Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Conclusion: Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune.",

author = "{eMERGE Consortium} and Venner Eric and Victoria Yi and David Murdock and Kalla, {Sara E.} and Wu, {Tsung Jung} and Aniko Sabo and Shoudong Li and Qingchang Meng and Xia Tian and Mullai Murugan and Michelle Cohen and Christie Kovar and Wei, {Wei Qi} and Chung, {Wendy K.} and Chunhua Weng and Wiesner, {Georgia L.} and Jarvik, {Gail P.} and Donna Muzny and Gibbs, {Richard A.} and Debra Abrams and Adunyah, {Samuel E.} and Ladia Albertson-Junkans and Berta Almoguera and Ames, {Darren C.} and Paul Appelbaum and Samuel Aronson and Sharon Aufox and Babb, {Lawrence J.} and Adithya Balasubramanian and Hana Bangash and Melissa Basford and Lisa Bastarache and Samantha Baxter and Meckenzie Behr and Barbara Benoit and Elizabeth Bhoj and Bielinski, {Suzette J.} and Bland, {Harris T.} and Carrie Blout and Lisa Castillo and Chisholm, {Rex L.} and Gordon, {Adam S.} and Hayes, {M. Geoffrey} and Christin Hoell and Elizabeth McNally and Puckelwartz, {Megan J.} and Laura Rasmussen-Torvik and Smith, {Maureen E.} and Justin Starren and Theresa Walunas",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive licence to the American College of Medical Genetics and Genomics.",

year = "2021",

month = oct,

doi = "10.1038/s41436-021-01230-w",

language = "English (US)",

volume = "23",

pages = "1838--1846",

journal = "Genetics in Medicine",

issn = "1098-3600",

publisher = "Elsevier B.V.",

number = "10",

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T2 - an environment for the delivery of genomic medicine

AU - eMERGE Consortium

AU - Eric, Venner

AU - Yi, Victoria

AU - Murdock, David

AU - Kalla, Sara E.

AU - Wu, Tsung Jung

AU - Sabo, Aniko

AU - Li, Shoudong

AU - Meng, Qingchang

AU - Tian, Xia

AU - Murugan, Mullai

AU - Cohen, Michelle

AU - Kovar, Christie

AU - Wei, Wei Qi

AU - Chung, Wendy K.

AU - Weng, Chunhua

AU - Wiesner, Georgia L.

AU - Jarvik, Gail P.

AU - Muzny, Donna

AU - Gibbs, Richard A.

AU - Abrams, Debra

AU - Adunyah, Samuel E.

AU - Albertson-Junkans, Ladia

AU - Almoguera, Berta

AU - Ames, Darren C.

AU - Appelbaum, Paul

AU - Aronson, Samuel

AU - Aufox, Sharon

AU - Babb, Lawrence J.

AU - Balasubramanian, Adithya

AU - Bangash, Hana

AU - Basford, Melissa

AU - Bastarache, Lisa

AU - Baxter, Samantha

AU - Behr, Meckenzie

AU - Benoit, Barbara

AU - Bhoj, Elizabeth

AU - Bielinski, Suzette J.

AU - Bland, Harris T.

AU - Blout, Carrie

AU - Castillo, Lisa

AU - Chisholm, Rex L.

AU - Gordon, Adam S.

AU - Hayes, M. Geoffrey

AU - Hoell, Christin

AU - McNally, Elizabeth

AU - Puckelwartz, Megan J.

AU - Rasmussen-Torvik, Laura

AU - Smith, Maureen E.

AU - Starren, Justin

AU - Walunas, Theresa

PY - 2021/10

Y1 - 2021/10

N2 - Purpose: Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. Methods: We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Results: Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Conclusion: Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune.

AB - Purpose: Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. Methods: We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Results: Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Conclusion: Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune.

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JO - Genetics in Medicine

JF - Genetics in Medicine

IS - 10

ER -

Neptune: an environment for the delivery of genomic medicine

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