Oral Presentation GENEMAPPERS 2026

Single-cell genetics identifies cell type-specific causal associations between complex traits and diseases (#4)

Albert Henry 1 2 3 4 , Anne Senabouth 1 2 , Rika Tyebally 1 2 , Blake Bowen 1 2 3 , Peter C. Allen 1 2 , Eleanor Spenceley 1 2 3 , Eszter Sagi-Zsigmond 1 , Anna S.E. Cuomo 1 2 3 5 6 , Jayden Fan 1 2 , Hao L. Huang 1 3 , Hope A. Tanudisastro 5 6 7 , Angli Xue 1 2 3 , Katrina M. de Lange 5 6 , Gemma A. Figtree 8 9 , Alex W. Hewitt 10 11 12 , Daniel G. MacArthur 2 5 6 , Joseph E. Powell 1 2 3
  1. Translational Genomics Program, Garvan Institute of Medical Research, Sydney, NSW, Australia
  2. Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
  3. UNSW Cellular Genomics Futures Institute, University of New South Wales, Sydney, NSW, Australia
  4. Institute of Cardiovascular Sciences, University College London, London, United Kingdom
  5. Centre for Population Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia
  6. Centre for Population Genomics, Murdoch Children’s Research Institute, Melbourne, VIC, Australia
  7. Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
  8. Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia
  9. Kolling Institute of Medical Research, Royal North Shore Hospital, Sydney, NSW, Australia
  10. Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
  11. Department of Ophthalmology, Royal Hobart Hospital, Hobart, TAS, Australia
  12. Centre for Eye Research Australia, University of Melbourne, East Melbourne, VIC, Australia

Genome-wide association studies (GWAS) have identified genomic regions associated with complex traits, but pinpointing the causal genes remains challenging due to context-specific genetic regulation. In this study, we integrate single-cell expression quantitative trait loci (sc-eQTL) data from 1,925 individuals in the TenK10K cohort1 with GWAS to map the putative causal associations between cell type-specific gene expression across 28 peripheral immune cell types and 100 complex traits, including 69 diseases and 31 biomarkers.

Using Mendelian randomization, we identified over 8,000 genes causally associated with at least one disease and over 16,000 with at least one biomarker, totaling 188,634 unique gene–trait associations. Of these, ~35% were undetectable by GWAS-only analysis and ~61% were not captured by bulk-tissue eQTL analysis. Associations that are found only by using sc-eQTL data were often restricted to a few cell types, highlighting the value of cell type-resolved sc-eQTL mapping. Further, we demonstrate associations of ZBTB38 expression in T and B cells with Crohn’s disease that match results from an external differential gene expression study2 using disease-affected intestinal tissue, providing insights into cellular mechanisms of disease.

Through polygenic enrichment analysis, we demonstrate that peripheral immune cell types were enriched for both immune-related and systemic diseases. We observed strong polygenic enrichment for immune-mediated diseases in dendritic cells. Notably, two sub-populations of these cells exhibited distinct enrichment patterns, differentiating between autoimmune disorders and viral infections.

We estimate that past clinical development programs3 with target–indication pairs supported by single-cell MR association identified in our study were 3.3 times more likely to reach regulatory approval, showing the translational potential of these results to accelerate drug development.

Our study demonstrates a framework to characterise cell type-specific effects of genes using single-cell genetics to advance understanding of causal disease biology and identify effective therapeutics targets at cellular level.

  1. Cuomo, A. S. E. et al. Impact of rare and common genetic variation on cell type-specific gene expression. medRxiv (2025) doi:10.1101/2025.03.20.25324352.
  2. Kong, L. et al. The landscape of immune dysregulation in Crohn’s disease revealed through single-cell transcriptomic profiling in the ileum and colon. Immunity 56, 444-458.e5 (2023).
  3. Ochoa, D. et al. The next-generation Open Targets Platform: reimagined, redesigned, rebuilt. Nucleic Acids Res. 51, D1353–D1359 (2023).