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Most rare disease patients (75-50%) undergoing genomic sequencing remain unsolved, often due to lack of information about variants identified. Data review over time can leverage novel information regarding disease-causing variants and genes, increasing this diagnostic yield. However, time and resource constraints have limited reanalysis of genetic data in clinical laboratories setting. We developed RENEW, (REannotation of NEgative WES/WGS) an automated reannotation procedure that uses relevant new information in on-line genomic databases to enable rapid review of genomic findings. We tested RENEW in an unselected cohort of 1066 undiagnosed cases with a broad spectrum of phenotypes from the Mayo Clinic Center for Individualized Medicine using new information in ClinVar, HGMD and OMIM between the date of previous analysis/testing and April of 2022. 5741 variants prioritized by RENEW were rapidly reviewed by variant interpretation specialists. Mean analysis time was approximately 20 s per variant (32 h total time). Reviewed cases were classified as: 879 (93.0%) undiagnosed, 63 (6.6%) putatively diagnosed, and 4 (0.4%) definitively diagnosed. New strategies are needed to enable efficient review of genomic findings in unsolved cases. We report on a fast and practical approach to address this need and improve overall diagnostic success in patient testing through a recurrent reannotation process.
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http://dx.doi.org/10.1007/s00439-024-02664-3 | DOI Listing |
Sci Data
August 2025
Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518071, China.
Advances in optical microscopy scanning have significantly contributed to computational pathology (CPath) by converting traditional histopathological slides into whole slide images (WSIs). This development enables comprehensive digital reviews by pathologists and accelerates AI-driven diagnostic support for WSI analysis. Recent advances in foundational pathology models have increased the need for benchmarking tasks.
View Article and Find Full Text PDFFront Immunol
May 2025
Emergency Surgery, Affiliated Hospital of Guizhou Medical University, Guiyang, China.
Introduction: Osteoarthritis (OA), a debilitating joint disorder characterized by synovial inflammation and immune myeloid cell infiltration, currently lacks a comprehensive spatial and transcriptional atlas. This study investigates the spatial dynamics, splicing kinetics, and signaling pathways that drive immune infiltration in OA synovium.
Methods: We integrated single-cell RNA sequencing (scRNA-seq) data from 8 OA and 4 healthy synovial samples with spatial transcriptomics using Spatrio.
Int J Gen Med
December 2024
Department of Pathology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yun Nan, People's Republic of China.
Purpose: To identify the epithelial cell centre regulatory transcription factors in the gastric cancer (GC) microenvironment and provide a new strategy for the diagnosis and treatment of GC.
Methods: The GC single-cell dataset was downloaded from the Gene Expression Omnibus (GEO) database. The regulatory mechanisms of transcription factors in both pan-cancer and GC microenvironments were analysed using the Cancer Genome Atlas (TGCA) database.
Microb Pathog
August 2024
School of Artificial Intelligence, Hangzhou Dianzi University, Hangzhou, Zhejiang, China.
Hum Genet
May 2024
Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
Most rare disease patients (75-50%) undergoing genomic sequencing remain unsolved, often due to lack of information about variants identified. Data review over time can leverage novel information regarding disease-causing variants and genes, increasing this diagnostic yield. However, time and resource constraints have limited reanalysis of genetic data in clinical laboratories setting.
View Article and Find Full Text PDF