122: Patient stratification reveals the molecular basis of disease co-occurrences

Urda-García B et al., PNAS - This episode discusses a PNAS study that builds disease similarity networks from public RNA-seq data and shows that stratifying patients into 'meta-patients' uncovers molecular mechanisms behind many medically observed comorbidities. Key terms: transcriptomics, comorbidity, disease networks, patient stratification, immune system. Study Highlights:The authors used uniformly processed RNA-seq from 45 diseases to build a Disease Similarity Network (DSN) and a Stratified Similarity Network (SSN) that includes patient subgroups (meta-patients). The DSN recapitulates 46.2% of epidemiological comorbidities and the SSN raises recall to 64.13%, while maintaining precision. Most captured comorbidities implicate immune system pathways and shared dysregulated Reactome pathways such as ECM, metabolism, and signal transduction. Meta-patients reveal subgroup-specific comorbidity links and increase detection power, especially for heterogeneous diseases. Conclusion:Gene expression–based disease networks, enhanced by patient stratification, explain a large fraction of known comorbidities and provide molecular hypotheses—predominantly immune-related—that can guide personalized management and further study. Music:Enjoy the music based on this article at the end of the episode. Article title:Patient stratification reveals the molecular basis of disease co- occurrences First author:Urda-García B Journal:PNAS DOI:10.1073/pnas.2421060122 Reference:Urda-García B, Sánchez-Valle J, Lepore R, Valencia A. Patient stratification reveals the molecular basis of disease co-occurrences. PNAS. 2025;122(35):e2421060122. doi:10.1073/pnas.2421060122 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/patient-stratification-reveals-the-molecular-basis-of-disease-co-occurrences QC:This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-08-30. QC Scope:- article metadata and core scientific claims from the narration- excludes analogies, intro/outro, and music- transcript coverage: Audited sections cover: comorbidity concept, differential expression strategy, DSN/SSN methodology, meta-patient stratification, key molecular mechanisms (immune system and ECM), inverse comorbidities (Huntington's with cancers), Down syndrome heterogeneity, and the public web resource.- transcript topics: Comorbidity concepts and data sources; RNA-seq differential expression and disease fingerprinting; Disease Similarity Network (DSN) construction; Stratified Similarity Network (SSN) and meta-patients; Immune system and ECM pathways in comorbidities; Inverse comorbidity and Huntington's disease example QC Summary:- factual score: 10/10- metadata score: 10/10- supported core claims: 6- claims flagged for review: 0- metadata checks passed: 4- metadata issues found: 0 Metadata Audited:- article_doi- article_title- article_journal- license Factual Items Audited:- DSN recalls 46.2% of known epidemiological comorbidities- SSN recalls 64.1% (meta-patients) of epidemiological associations- 95.2% of epidemiological interactions share at least one immune system pathway- ECM pathways and related metabolic/signal pathways are commonly altered in comorbidities Chapters (00:00:00) - Deep Dive: The molecular logic of disease co-occurrences(00:04:43) - RNA Sequencing: the game changer(00:06:55) - The Nature of the Disease similarity network(00:09:52) - Discovery of the disease network(00:12:56) - The Social Science Network (SSN) and the Metapat(00:16:56) - Measuring the molecular basis of diseases