Genetic colocalization analyses are frequently conducted to determine if causal signals at a genetic locus are shared between two phenotypes. However, colocalization is rarely undertaken at the HLA locus, due to its complex linkage disequilibrium (LD) and high polymorphism density. This lack of genetic causal inference method limits our ability to translate HLA associations into therapeutic targets. Here we present a method that uses HLA alleles, instead of nucleotide variants, to perform genetic colocalization of two traits at HLA genes. The method, which we call HLA-colocalization, works by controlling for LD using Bayesian variable selection, then performing Bayesian regression on the resulting posterior inclusion probabilities. We first show through simulation that the method correctly identifies truly colocalizing genes. We then test the method in two positive control scenarios, showing colocalization between hepatitis B and liver disease at HLA-DPB1, and between Epstein-Barr virus and multiple sclerosis at HLA-DRB1 and HLA-DQB1. Lastly, we perform a large colocalization scan between multiple viruses and auto-immune diseases, demonstrating that the method is well calibrated, and uncovering multiple biologically plausible novel causal associations, such as cytomegalovirus and ulcerative colitis. To our knowledge, HLA-colocalization is the first accurate genetic colocalization method for the HLA locus (github: https://github.com/DrGBL/hlacoloc).

JBR is the CEO of 5 Prime Sciences Inc

This study did not receive any funding.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

All primary individual level participant data from the UKB was obtained using application 27449. The UKB has ethics approval from the North West Multi-centre Research Ethics Committee. Ethics approval for the CKB study was obtainedEthical Review Committee of the Chinese Centre for Disease Control and Prevention (Beijing, China, 005/2004) and the Oxford Tropical Research Ethics Committee, University of Oxford (UK, 025-04). Data from all other cohorts are publicly available summary statistics from their respective sources.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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All code necessary to perform HLA colocalization and the above simulation is available at https://github.com/DrGBL/hlacoloc. Primary data from the UKB and the CKB are available through their respective owners. All summary statistics needed to replicate our results are available on the git or on their respective publications when applicable.