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  • A cytoplasmic index for quantifying immune-related A-to-I RNA editing. Genome biology Cohen-Fultheim, R., Twersky, I., Krupkin, H., Roth, S. H., Levanon, E. Y., Eisenberg, E. 2026

    Abstract

    Distinguishing self from non-self is a major challenge for the immune system. Endogenous cytoplasmic double-stranded RNA (dsRNA) can mimic viral RNA and activate immune sensors like MDA5. ADAR1-mediated adenosine-to-inosine editing disrupts base-pairing to suppress immunogenicity of these endogenous structures. Global editing indices are widely used to probe this crucial ADAR1 function. However, they are dominated by nuclear pre‑mRNA edits with limited immune relevance. Here we present the cytoplasmic editing index (CEI) that quantifies editing specifically within inverted Alu repeats in 3' untranslated regions of mature cytoplasmic transcripts, which potentially form cytosolic dsRNA structures carrying higher immunological risk.Analyzing over 25,000 RNA-sequencing samples, we demonstrate CEI captures ADAR1p150 activity and outperforms the global editing index in terms of sensitivity and signal-to-noise, enabling sharper tissue-specific profiling, enhanced detection power of infection‑induced editing changes, and stronger association with cancer prognoses. An open-source, cloud-native pipeline delivers end‑to‑end, reproducible analysis at very low cost, supporting immediate, scalable adoption.CEI provides a refined metric for quantifying immune-relevant RNA editing, revealing previously obscured tissue- and disease-specific editing landscapes. The accompanying open-source, cloud-native pipeline enables broad adoption of high-quality editing analysis across research settings. This approach offers new opportunities for investigating ADAR1's role in immunity, infection, and cancer, with potential applications in biomarker development and therapeutic intervention strategies.

    View details for DOI 10.1186/s13059-026-04154-3

    View details for PubMedID 42310695

  • Genomics-Informed Approach Identifies Which Cell Types Regulate the Metabolome. Bioinformatics (Oxford, England) Krupkin, H., Padhi, E. M., Nachun, D., Kain, J., Long, J. Z., Montgomery, S. B. 2026

    Abstract

    Metabolism occurs in a cell type-specific manner, but which cells regulate metabolite levels remains unclear. Here, we integrate some of the largest metabolite quantitative trait loci datasets, TOPMed and UK Biobank, with one of the most extensive single-cell RNA sequencing resources, Tabula Sapiens. This integration allows us to identify cell types that regulate metabolites body-wide. We find hepatocytes are the primary regulatory cell type for most metabolites, associating with 385/410 (94%) metabolites for whom an association is found. Additionally, our multi-gene approach reveals more metabolite associations with beta cells compared to those identified using a single-gene approach. For example, we identify novel metabolite-cell type associations, such as the association between phenylpropanoic acid and beta cells, this metabolite that was previously thought to be regulated by the microbiome.

    View details for DOI 10.1093/bioinformatics/btag330

    View details for PubMedID 42213079

  • Unsupervised learning reveals landscape of local structural motifs across protein classes. Bioinformatics (Oxford, England) Derry, A., Krupkin, H., Tartici, A., Altman, R. B. 2025

    Abstract

    Proteins are known to share similarities in local regions of 3D structure even across disparate global folds. Such correspondences can help to shed light on functional relationships between proteins and identify conserved local structural features that lead to function. Self-supervised deep learning on large protein structure datasets has produced high-fidelity representations of local structural microenvironments, providing the opportunity to characterize the landscape of local structure and function at scale.In this work, we leverage these representations to cluster over 15 million environments in the Protein Data Bank, resulting in the creation of a "lexicon" of local 3D motifs which form the building blocks of all known protein structures. We characterize these motifs and demonstrate that they provide valuable information for modeling structure and function at all scales of protein analysis, from full protein chains to binding pockets to individual amino acids. We devise a new protein representation based solely on its constituent local motifs and show that this representation enables state-of-the-art performance on protein structure search and model quality assessment. We then show that this approach enables accurate prediction of drug off-target interactions by modeling the similarity between local binding pockets. Finally, we identify structural motifs associated with pathogenic variants in the human proteome by leveraging the predicted structures in the AlphaFold structure database.All code and cluster data are available at https://github.com/awfderry/collapse-motifs  .Supplementary data are available at Bioinformatics online.

    View details for DOI 10.1093/bioinformatics/btaf377

    View details for PubMedID 40569048

  • Sarcopenia and Cognitive Decline in Hospitalized Older Adults from a Prospective Study. Aging and disease Kon-Kfir, S., Cukierman-Yaffe, T., Krupkin, H., Belkin, A., Shlomai, G., Bleier, J., Weinstein, S., Bruckmayer, L., Prinz, E., Kaplan, A., Shraga, M. G., Lev, D., Dekel, S., Shalmon, N., Tsarfaty, N., Reiss, N., Bischof, E., Leibowitz, A. 2025

    Abstract

    As populations age, sarcopenia increasingly impacts healthcare due to its associations with morbidity, mortality, and cognitive decline. This study is a cross-sectional analysis of prospectively collected data from 140 older adults hospitalized in an internal medicine department. Sarcopenia was measured by handgrip strength, and cognitive function by the Digit Symbol Substitution Test (DSST). Sarcopenic patients (n=78) had lower DSST scores (p=0.003) and Norton scores (p&;lt0.001) compared to non-sarcopenic patients. Handgrip strength showed a significant positive correlation with DSST scores (R=0.26, p=0.0019), persisting after adjustments for age and sex (R=0.42, p=1.7e-07). This study underscores a significant association between sarcopenia and cognitive decline in hospitalized older adults, advocating for routine sarcopenia and cognitive assessments upon admission. These findings emphasize the importance of identifying at-risk patients early and developing targeted interventions. Future research should further explore underlying mechanisms and validate findings in broader cohorts.

    View details for DOI 10.14336/AD.2024.1676

    View details for PubMedID 40153579