Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations. Nat Commun 2025 Aug 07;16(1):7267
Date
08/07/2025Pubmed ID
40770127Pubmed Central ID
PMC12328722DOI
10.1038/s41467-025-61712-2Scopus ID
2-s2.0-105013076026 (requires institutional sign-in at Scopus site) 2 CitationsAbstract
Genomics for rare disease diagnosis has advanced at a rapid pace due to our ability to perform in-depth analyses on individual patients with ultra-rare diseases. The increasing sizes of ultra-rare disease cohorts internationally newly enables cohort-wide analyses for new discoveries, but well-calibrated statistical genetics approaches for jointly analyzing these patients are still under development. The Undiagnosed Diseases Network (UDN) brings multiple clinical, research and experimental centers under the same umbrella across the United States to facilitate and scale case-based diagnostic analyses. Here, we present the first joint analysis of whole genome sequencing data of UDN patients across the network. We introduce new, well-calibrated statistical methods for prioritizing disease genes with de novo recurrence and compound heterozygosity. We also detect pathways enriched with candidate and known diagnostic genes. Our computational analysis, coupled with a systematic clinical review, recapitulated known diagnoses and revealed new disease associations. We further release a software package, RaMeDiES, enabling automated cross-analysis of deidentified sequenced cohorts for new diagnostic and research discoveries. Gene-level findings and variant-level information across the cohort are available in a public-facing browser ( https://dbmi-bgm.github.io/udn-browser/ ). These results show that case-level diagnostic efforts should be supplemented by a joint genomic analysis across cohorts.
Author List
Kobren SN, Moldovan MA, Reimers R, Traviglia D, Li X, Barnum D, Veit A, Corona RI, Carvalho Neto GV, Willett J, Berselli M, Ronchetti W, Nelson SF, Martinez-Agosto JA, Sherwood R, Krier J, Kohane IS, Undiagnosed Diseases Network, Sunyaev SRAuthors
James Verbsky PhD, MD Professor in the Pediatrics department at Medical College of WisconsinMichael T. Zimmermann PhD Director, Associate Professor in the Data Science Institute department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
Cohort StudiesGenomics
Humans
Rare Diseases
Software
Whole Genome Sequencing









