Scaling genomic reanalysis to unlock diagnoses and transform rare disease care

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Authors: Shira Rockowitz, Wanqing Shao, Courtney French, Tina K. Truong, Jacob Hagen, Rylee McGonigle, Alexa Geltzeiler, Beth Rosen Sheidley, Lacey A. Smith, Alissa M. D’Gama, Mira Irons, Janet S. Chou
+36 more Joan Marilyn Stoler, Amy Kritzer, Lance H. Rodan, Akiko Shimamura, Olaf A. Bodamer, Stephanie J. Sacharow, Janet S. Soul, Siddharth Srivastava, Amy Roberts Kennedy, Aya Abu‐El‐Haija, Abbe Lai, Heather E. Olson, Jane Juusola, Erin Ryan, Bethany Friedman, Anupama Singh, Cliff Li, Rittika Mallik, Gwendolyn Strickland, Gillian Prinzing, Alisa Mo, Anne O’Donnell‐Luria, Jeff Bolton, Philip M. Boone, William J. Brucker, Michael Duyzend, Sonal Mahida, David T. Miller, Jacklyn O. Omorodion, Jeanette Petit, Jonathan D. Picker, Annapurna Poduri, Colleen M. Carlston, Monica H. Wojcik, Piotr Sliz A, Wendy K. Chung
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References: 61

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.

Fields of Study & Subjects

Genomics and Rare Diseases Artificial Intelligence in Healthcare and Education Connective tissue disorders research

Publication details

Journal / source
Human Genetics and Genomics Advances
Volume
7
Issue
2
Pages
100582–100582
Publication date
19 February 2026
Language
EN