LLM-Assisted Reanalysis of Unsolved Rare Disease Genomes Increases Diagnostic Yield

Assessing and mitigating batch effects in large-scale omics studies

Batch effects in omics data are notoriously common technical variations unrelated to study objectives, and may result in misleading outcomes if uncorrected, or hinder biomedical discovery if over-corrected. Assessing and mitigating batch effects is crucial for ensuring the reliability and reproducibility of omics data and minimizing the impact of technical variations on biological interpretation. In this review, we highlight the profound negative impact of batch effects and the urgent need to address this challenging problem in large-scale omics studies. We summarize potential sources of batch effects, current progress in evaluating and correcting them, and consortium efforts aiming to tackle them.

Prime editing-installed suppressor tRNAs for disease-agnostic genome editing

Precise genome-editing technologies such as base editing1,2 and prime editing3 can correct most pathogenic gene variants, but their widespread clinical application is impeded by the need to develop new therapeutic agents for each mutation. For diseases that are caused by premature stop codons, suppressor tRNAs (sup-tRNAs) offer a more general strategy. Existing approaches to use sup-tRNAs therapeutically, however, require lifelong administration4,5 or show modest potency, necessitating potentially toxic overexpression. Here we present prime editing-mediated readthrough of premature termination codons (PERT), a strategy to rescue nonsense mutations in a disease-agnostic manner by using prime editing to permanently convert a dispensable endogenous tRNA into an optimized sup-tRNA. Iterative screening of thousands of variants of all 418 human tRNAs identified tRNAs with the strongest sup-tRNA potential. We optimized prime editing agents to install an engineered sup-tRNA at a single genomic locus without overexpression and observed efficient readthrough of premature termination codons and protein rescue in human cell models of Batten disease, Tay-Sachs disease and cystic fibrosis. In vivo delivery of a single prime editor that converts an endogenous mouse tRNA into a sup-tRNA extensively rescued disease pathology in a model of Hurler syndrome. PERT did not induce detected readthrough of natural stop codons or cause significant transcriptomic or proteomic changes. Our findings suggest the potential of disease-agnostic therapeutic genome-editing approaches that require only a single composition of matter to treat diverse genetic diseases.

Precision Medicine in Neuroscience: Tools, Translation, and Implementation: A Workshop

Precision medicine approaches are rapidly transforming neuroscience, driven by advances in genetics, neuroimaging, biomarkers, and data science. These tools enable more refined disease classification, improved diagnosis, and treatments tailored to individual patients across neurological and psychiatric disorders. However, challenges remain in translating these advances into routine research and clinical practice. On March 4–5, the National Academies’ Forum on Neuroscience and Nervous System Disorders, in collaboration with the Forum on Drug Discovery, Development, and Translation and the Roundtable on Genomics and Precision Health, will host a workshop exploring opportunities, challenges, and strategies for integrating precision medicine into neuroscience research and care.

RCCX Genetic Module Theory

NOTE: This page is modified from a summary of findings available at the RCCX and Illness website.

Navigating the Odyssey of Refractory Hypoglycemia: A Diagnostic and Therapeutic Puzzle in Ehlers-Danlos Syndrome Managed With Octreotide

Author Block: Mehwish Zeb, Michigan State University, Yarub Al-Alousi, St. Joseph University Medical Center, Syed Farasat Ali Shah, Institute of Diabetes and Endocrinology

Hallucination by proxy in LLM-assisted differential diagnosis

Current evidence suggests that LLM assistance could augment the diagnostic accuracy of clinicians. However, these systems are black boxes, susceptible to hallucinations, and project a potentially...

Hallucination by proxy in LLM-assisted differential diagnosis

Current evidence suggests that LLM assistance could augment the diagnostic accuracy of clinicians. However, these systems are black boxes, susceptible to hallucinations, and project a potentially...

Using AI to help physicians diagnose rare genetic diseases affecting children

Researchers used an OpenAI reasoning model to help diagnose rare diseases, identifying 18 new diagnoses in previously unsolved cases.

Hierarchical classification of immune cell transcriptomes at population-scale

Accurate immune cell classification is essential for interpreting single-cell RNA sequencing (scRNA-seq) data. However, progress is constrained by the lack of independent, high-resolution benchmarks, as the routine integration of datasets introduces statistical dependencies that artificially inflate model generalizability. Here, we present the single-cell universal classification omnibus (Suco), a resource of independent, uniform expert annotations, and Compocyte, a modular hierarchical classifier. Together, they establish a framework designed for the scale of human population immunology. This approach substantially outperforms existing classifiers while facilitating expert review of ambiguous annotations. Applying Compocyte across 50 studies, including three newly generated datasets, we classified 15.6 million leukocytes from 3,965 patients. Within this expansive cohort, we identified a new tumor-associated resorptive macrophage phenotype, a non-canonical monocyte subtype in subclinical cytokine release syndrome, and the programmatic erosion of T cell memory stemness across metastatic sites. Suco and Compocyte thus provide a generalizable architecture and benchmark capable of sustaining high-resolution annotation across massive clinical cohorts. ### Competing Interest Statement CMR has consulted regarding oncology drug development with Amgen, AstraZeneca, Daiichi Sankyo, Genentech, Merck, and Novartis, and has received licensing and royalty payments for DLL3-directed therapeutics. T.W. reports stock ownership for Roche, Astra Zeneca, Bayer, Innate Pharma, Kyntra, Illumina, 10x Genomics, and Merck KGaA as well as research funding from Atrandi Biosciences, Vilnius, Lithuania; CanVirex AG, Basel Switzerland; and Institut fuer Klinische Krebsforschung GmbH, Frankfurt, Germany, and travel funding from Roche, Basel, Switzerland. S.Z. reports advisory board membership and honoraria from Amgen, Astellas, AstraZeneca, Bayer, Bristol-Myers Squibb, Daiichi Sankyo, Eisai, EUSA, Gilead, Ipsen, Johnson&Johnson, Lilly, MedSir, Medtoday, Merck, MSD, Novartis, Pfizer, Roche, Sanofi Aventis, StreamedUp, Urotrials, Urotube, Zentiva and resarch funding from Eisai. S.Z. reports clinical trial support from Amgen, AstraZeneca, AVEO, Bayer, Biontech, Bristol-Myers Squibb, Calithera, Exelixis, Gilead, Lilly, MSD, Novartis, Pfizer, Roche, Seagen/Astellas, Urotrials and travels & conference support from Amgen, Astellas, AstraZeneca, Bayer, EISAI, Ipsen, Johnson&Johnson, Merck, MSD, Pfizer. All remaining authors declare no relevant competing interests. Spanish Association Against Cancer, PI049999 Federal Ministry of Research, Technology and Space, 001001KT2322 National Cancer Institute, R35 CA263816 National Cancer Institute, U24 CA213274 National Cancer Institute, P30 CA008748 Research Council of Lithuania, P-MIP-24-93

LLMs have Main Character Syndrome

A short note about a consistent pattern

Sid Sijbrandij's Osteosarcoma Data

Explore Sid Sijbrandij's osteosarcoma research data: single-cell transcriptomics, tissue imaging, cell clusters, and gene set enrichment analysis from his own tumor samples.

Ramez Naam on Twitter / X

There was a site years ago called CureTogether where patients could share information in a structured way on their disease, regimen, and progress, working towards a sort of bottoms-up clinical trial. 23andMe acquired them and it seems to be mostly dead.— Ramez Naam (@ramez) September 14, 2025

Sleuths flag ‘complete mismatch’ in data of BMJ stem cell study | Manoj Lalu

This is disappointing, but I’m not surprised. I was one of the reviewers for the initial version. You can see by my review (it’s all open) that I flagged primary outcome switching, a complete lack of any data on the cells themselves, and sample size inconsistencies in the protocol versus the report (and within the report). The data seemed impressive. Too good to be true I guess? I never saw the paper again in peer review after that initial review. The next notification I received was that the paper was accepted. Given BMJ’s commitment to open peer review and post-publication scrutiny (which I admire), I have no doubt we will hear about a formal editorial investigation soon.

Vulnerability Reports Are Not Special Anymore

We needed the insight and confidentiality to protect our users, but now that anyone can get the same results from LLM?

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

SUMMARY The common approach to the multiplicity problem calls for controlling the familywise error rate (FWER). This approach, though, has faults, and we point out a few. A different approach to problems of multiple significance testing is presented. It calls for controlling the expected proportion of falsely rejected hypotheses — the false discovery rate. This error rate is equivalent to the FWER when all hypotheses are true but is smaller otherwise. Therefore, in problems where the control of the false discovery rate rather than that of the FWER is desired, there is potential for a gain in power. A simple sequential Bonferronitype procedure is proved to control the false discovery rate for independent test statistics, and a simulation study shows that the gain in power is substantial. The use of the new procedure and the appropriateness of the criterion are illustrated with examples.