Poster Presentation GENEMAPPERS 2026

ImmunoXcan: a novel method to identify T-cell receptor clonotypes mediating HLA associations with complex traits (#91)

Aaron Meyers 1 2 , Khalid Mahmood 2 3 4 , Daniel Buchanan 2 3 5 , Mark Jenkins 1 2 , James Dowty 1 2
  1. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia
  2. Collaborative Centre for Genomic Cancer Medicine, Victorian Comprehensive Cancer Centre, Melbourne, Victoria, Australia
  3. Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, University of Melbourne, Parkville, Victoria, Australia
  4. Melbourne Bioinformatics, University of Melbourne, Melbourne, Victoria, Australia
  5. Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Victoria, Australia

Background: HLA loci contribute the most GWAS signals for complex traits. However, the HLA region is typically excluded from post-GWAS analyses due to complex genetic diversity and distinctive immunobiology. Mechanistically, HLA risk alleles are thought to restrict the hypervariable CDR3 region of T-cell receptors (TCRs) recognising pathogenic antigens. To strengthen functional interpretation of HLA associations, we developed ImmunoXcan, a TCR-based analysis pipeline leveraging HLA variants as instruments.

Method: ImmunoXcan adapts principles from transcriptome-wide association studies and Bayesian fine-mapping to jointly model TCR and non-mediated genetic effects, adjusting for linkage disequilibrium and horizontal pleiotropy despite multicollinearity. Using CDR3β immunosequencing of healthy blood donors (n=628), we trained 21,575 sparse TCR expression models from HLA protein variation (average cross-validated accuracy R2/h2=0.61) and predicted trans-regulatory TCR features into HLA mapping data for 52 immune-mediated phenotypes in UK Biobank Serology Study (n=7,741), 23andMe (n=219,579), and VaccGene clinical trials (n=2,499). We mapped credible causal TCRs to pathogenic antigens using tetramer-sorted T-cell data, k-mer matching, and paratope hotspot clustering.

Results: ImmunoXcan identified multiple 'positive control' TCR-trait associations (posterior probability of association >0.90), supported by functional evidence of target antigen specificity and HLA-colocalisation evidence of shared causal variants. Noteworthy examples include: (i) TCRs specific to uncharacterised Mycobacterium tuberculosis (MTB) Rv1518/MT1568 antigens and memory T-cell response to MTB (HLA-DRβ1 colocalisation PPH4>0.90); (ii) CDR3β-S%GGET_ILV+ clonotypes reactive to myelin basic protein and multiple sclerosis risk (HLA-DQβ1 PPH4>0.70); (iii) Epstein-Barr virus (EBV) EBNA3A-specific TCRs restricted to HLA-B*08 risk alleles and EBV seropositivity (HLA-B PPH4>0.50); (iv) hepatitis B virus (HBV) core protein-specific TCRs and antibody response to HBV vaccination (HLA-DQα1~DQβ1 PPH4>0.99). Probabilistic annotation enrichment using mass spectrometry immunopeptidomics data revealed shared HLA peptide-binding motifs underlying candidate causal axes.

Conclusion: ImmunoXcan provides a framework for resolving constitutional HLA-TCR interactions in immune-mediated trait susceptibility, with implications for designing preventive immunotherapeutics.