113: Joint cohort genomics cracks ultra‑rare disease cases

Nadimpalli Kobren S et al., Nature Communications - The Undiagnosed Diseases Network (UDN) applied joint whole‑genome analysis across 4,236 individuals and introduced RaMeDiES, an analytical framework to prioritize genes by de novo recurrence and compound heterozygosity while integrating intronic splice predictions and experimental validation. The work recapitulated known diagnoses, identified new diagnoses and candidates, and released software and a public browser to enable cross‑cohort, deidentified discovery. Key terms: rare disease, whole genome sequencing, de novo mutations, compound heterozygosity, RaMeDiES. Study Highlights:The authors jointly called SNVs and indels across the UDN whole‑genome cohort and developed RaMeDiES statistical methods to detect genes enriched for deleterious de novo mutations and for recurrent compound heterozygous events. They extended analyses to deep intronic splice‑altering variants using SpliceAI and validated predictions with a massively parallel splicing reporter assay (MPSA). RaMeDiES recovered known diagnoses, produced five new diagnoses and multiple strong candidates, and runs fast on summary-level mutational targets enabling cross-cohort meta-analysis. A public browser and open-source RaMeDiES package were released to support automated, deidentified joint analyses. Conclusion:Well‑calibrated, cohort‑level statistical analyses of whole genomes can complement per‑case evaluation to reveal diagnoses and candidate genes in diverse ultra‑rare disease presentations, and RaMeDiES enables scalable, shareable discovery across sequenced cohorts. Music:Enjoy the music based on this article at the end of the episode. Article title:Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations First author:Nadimpalli Kobren S Journal:Nature Communications DOI:10.1038/s41467-025-61712-2 Reference:Nadimpalli Kobren S, Moldovan MA, Reimers R, et al. Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations. Nat Commun (2025) 16:7267. doi:10.1038/s41467-025-61712-2 License:This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support:Base by Base – Stripe donations: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 Official website https://basebybase.com On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/joint-multifaceted-genomic-analysis-enables-diagnosis-of-ultra-rare-monogenic-presentations QC:This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-08-21. QC Scope:- article metadata and core scientific claims from the narration- excludes analogies, intro/outro, and music- transcript coverage: Audited the transcript sections describing RaMeDiES (joint genomic analysis), RaMeDiES-DN (de novo recurrence), RaMeDiES-CH (compound heterozygosity), intronic/splice-variant incorporation (SpliceAI, MPSA), pathway clustering, privacy-preserving data sharing, and study limitations.- transcript topics: RaMeDiES overview and genotype-first analysis; RaMeDiES-DN de novo recurrence and mutation-rate modeling (Roulette); RaMeDiES-CH compound heterozygosity analysis and trio-based conditioning; Intron-splice variant integration (SpliceAI) and MPSA validation; Pathway analysis and phenotype clustering across cohorts; Privacy-preserving cross-cohort sharing via summary statistics QC Summary:- factual score: 10/10- metadata score: 10/10- supported core claims: 8- claims flagged for review...