ArticleNature aging2026
Integrating polygenic signals and single-cell multiomics identifies cell-type-specific regulomes critical for immune- and aging-related diseases.
Article in Nature aging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Unraveling the pathogenic mechanisms of osteoarthritis and obesity: An integration of GWAS, cellular specificity, and spatial transcriptomics.Osteoarthritis and cartilage open · 2026Article
- Genetic Evidence for Unified Airway Disease: Shared Epithelial and Immune Architecture Across Major Airway Diseases.International journal of molecular sciences · 2026Article
- Beyond the gene: isoform diversity as a key contributor to human brain disorders.Current opinion in genetics & development · 2026Review
- Stem cells as an essential mediator of the exercise-tumorigenesis link.Nature reviews. Cancer · 2026Review
- Fibrillin-1 Orchestrates a Pro-senescent Niche Driving Peritubular Endothelial Senescence via ZEB1/endothelin-1/β-catenin Signaling.International journal of biological sciences · 2026Article
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Authors and funding
15 authors.
Funding
Abstract
Single-cell multiomics provides critical insights into how disease-associated variants identified through genome-wide association studies (GWASs) influence transcription factor eRegulons within a specific cellular context; however, the regulatory roles of genetic variants in aging and disease remain unclear. Here, we present scMORE, a method that integrates single-cell transcriptomes and chromatin accessibility with GWAS summary statistics to identify cell-type-specific eRegulons associated with diseases. scMORE effectively captures trait-relevant cellular features and demonstrates robust performance across simulated and real single-cell datasets, and GWASs for 31 immune- and aging-related traits, including Parkinson's disease (PD). In the human midbrain, scMORE identifies 77 aging-relevant eRegulons implicated in PD across seven brain cell types and reveals sex-dependent dysregulation of these eRegulons in PD neurons compared to both young and aged groups. By linking genetic variation to cell type-resolved eRegulon activity, scMORE illuminates how variants shape trait-relevant regulatory networks and provides a practical framework for mechanistic interpretation of GWAS signals.
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Registered trials
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