Scaling genomic reanalysis to unlock diagnoses and transform rare disease care

Genomic reanalysis can identify causative variants for rare diseases as patient phenotypes evolve and gene-disease knowledge expands. Despite its diagnostic value, routine reanalysis is limited by clinician capacity, lack of patient follow-up, data silos, cost, and lack of availability of clinical data to testing laboratories that are not obligated to conduct reanalysis. The Children's Rare Disease Collaborative at Boston Children's Hospital (BCH) has integrated genomic and phenotypic data from over 15,500 patients into a clinician-facing platform. Leveraging this infrastructure, we developed a Proactive Genomic Reanalysis (PGR) workflow at BCH for clinical sequencing data that is centralized, semi-automated, and clinically integrated. Here, we report initial results and outline required resources and transferable insights applicable to other healthcare settings. Initial pilot implementation, applied to a subset of clinical sequencing patients' data, revealed practical challenges, notably clinician turnover and patient recontact difficulties. Of 42 patients' candidate variants discovered by the PGR bioinformatics pipeline and returned to treating clinicians, 33 were determined to have a high suspicion of disease causality and an additional 3 were determined to be candidate variant of uncertain significance. A process to generate reports and return results to patients was initiated when applicable. Although the initial pilot implementation was limited, the PGR bioinformatics pipeline is designed to be utilized iteratively, making reanalysis a continuing process. This work highlights the feasibility and impact of centralized PGR processes and the potential for healthcare institutions to scale genomic reanalysis.

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Publication Details

Journal
Human Genetics and Genomics Advances
Published
2026-02-19
DOI
https://doi.org/10.1016/j.xhgg.2026.100582
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
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article

Scaling genomic reanalysis to unlock diagnoses and transform rare disease care

Mira Irons, Janet S. Soul, William Brucker, Jacob Hagen et al.
Human Genetics and Genomics Advances
Genomics and Rare Diseases
article

Scaling genomic reanalysis to unlock diagnoses and transform rare disease care

Mira Irons, Janet S. Soul, William Brucker, Jacob Hagen, Jeanette Petit, Alisa Mo, Gwendolyn Strickland, Tina K. Truong, Rylee McGonigle, Michael Duyzend, Heather E. Olson, JOAN M. STOLER, Amy Kritzer, Beth Rosen Sheidley, Bethany Friedman, Cliff Li, Rittika Mallik, Lacey Smith, Olaf A. Bodamer, Gillian Prinzing, Abbe Lai, Colleen M. Carlston, Jane S. Juusola, Wanqing Shao, Lance Rodan, Janet Chou, Alissa M. D’Gama, Aya Abu-El-Haija, Wendy K. Chung, Jonathan Picker, Erin Ryan, Stephanie Sacharow, Jacklyn Omorodion, Piotr Sliz, Annapurna Poduri, Courtney French, Akiko Shimamura, Anupama Singh, Alexa Geltzeiler, Amy Roberts Kennedy, Siddharth Srivastava, David T. Miller, Sonal Mahida, Shira Rockowitz, Jeff Bolton, Philip M. Boone, Monica H. Wojcik, Anne O’Donnell-Luria
article en

Abstract

Genomic reanalysis can identify causative variants for rare diseases as patient phenotypes evolve and gene-disease knowledge expands. Despite its diagnostic value, routine reanalysis is limited by clinician capacity, lack of patient follow-up, data silos, cost, and lack of availability of clinical data to testing laboratories that are not obligated to conduct reanalysis. The Children's Rare Disease Collaborative at Boston Children's Hospital (BCH) has integrated genomic and phenotypic data from over 15,500 patients into a clinician-facing platform. Leveraging this infrastructure, we developed a Proactive Genomic Reanalysis (PGR) workflow at BCH for clinical sequencing data that is centralized, semi-automated, and clinically integrated. Here, we report initial results and outline required resources and transferable insights applicable to other healthcare settings. Initial pilot implementation, applied to a subset of clinical sequencing patients' data, revealed practical challenges, notably clinician turnover and patient recontact difficulties. Of 42 patients' candidate variants discovered by the PGR bioinformatics pipeline and returned to treating clinicians, 33 were determined to have a high suspicion of disease causality and an additional 3 were determined to be candidate variant of uncertain significance. A process to generate reports and return results to patients was initiated when applicable. Although the initial pilot implementation was limited, the PGR bioinformatics pipeline is designed to be utilized iteratively, making reanalysis a continuing process. This work highlights the feasibility and impact of centralized PGR processes and the potential for healthcare institutions to scale genomic reanalysis.

Human Genetics and Genomics AdvancesVol. 7(2)
Boston Children's Hospital (US), Boston Children's Museum (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 48%
Genomics and Rare Diseases
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