DisCP-Atlas: a comprehensive resource mapping cellular processes to complex diseases
DisCP-Atlas: a comprehensive resource mapping cellular processes to complex diseases

DisCP-Atlas: a comprehensive resource mapping cellular processes to complex diseases

Nucleic Acids Res. 2025 Nov 3:gkaf1129. doi: 10.1093/nar/gkaf1129. Online ahead of print.

ABSTRACT

Genome-wide association studies (GWAS) have identified thousands of disease-associated loci, yet translating these findings into biological mechanisms remains challenging. Single-cell RNA-sequencing provides functional annotation at cellular resolution. Most current resources connect disease associations only to discrete cell-type categories. This cell type centric view overlooks disease-relevant cellular processes, which constitute the primary gene expression programs underlying genetic risk. These cellular processes function along continuous cell-state trajectories and routinely extend beyond conventional cell type boundaries. To address this issue, we present DisCP-Atlas (Disease to Cellular Process Atlas), a comprehensive resource that maps cellular processes to complex diseases. DisCP-Atlas identifies 990 cellular processes derived from 57 single-cell datasets across 35 human tissues, each annotated based on pathway enrichment and cell type-specific activities. Leveraging the sc-linker framework, we systematically linked 1072 GWAS datasets spanning 759 diseases to the cellular processes and identified 37 918 significant cellular process-disease associations. DisCP-Atlas allows bidirectional querying diseases to their underlying cellular processes or identifies diseases associated with specific cellular programs. All the results are presented in interactive visualization and can be conveniently downloaded. Additionally, DisCP-Atlas provides an online enrichment tool, enables users to submit custom genes, and returns detailed tables and interactive visualizations of enriched cellular processes. DisCP-Atlas is freely accessible at https://www.discpatlas.net.

PMID:41182817 | DOI:10.1093/nar/gkaf1129