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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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Personalized Peptide Arrays for Detection of HLA Alloantibodies in Organ Transplantation
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An Accurate Genetic Colocalisation Method for the HLA Locus.

Guillaume Butler-Laporte1,2,3, Tianyuan Lu4,5,6, Sam Morris7

  • 1Centre for Human Genetics, University of Oxford, Oxford, UK.

HLA
|May 22, 2026
PubMed
Summary

This study introduces HLA-colocalisation, a novel method for genetic causal inference at the Human Leukocyte Antigen (HLA) locus. It enables the identification of shared genetic signals between traits, crucial for understanding disease mechanisms and developing therapies.

Keywords:
Epstein Barr virusHLAcolocalisationhepatitis B virusmajor histocompatibility complexmultiple sclerosis

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Area of Science:

  • Immunogenetics
  • Statistical Genetics
  • Computational Biology

Background:

  • Genetic colocalisation analysis is vital for identifying shared causal signals between phenotypes.
  • The Human Leukocyte Antigen (HLA) locus is challenging for colocalisation due to complex linkage disequilibrium (LD) and high polymorphism.
  • Existing methods fail to accurately perform genetic causal inference at the HLA locus, hindering therapeutic target identification.

Purpose of the Study:

  • To develop and validate a novel genetic colocalisation method specifically for the HLA locus.
  • To enable accurate genetic causal inference at the HLA locus by using HLA alleles instead of nucleotide variants.
  • To uncover novel causal associations between viral infections and autoimmune diseases at the HLA locus.

Main Methods:

  • Developed HLA-colocalisation, a Bayesian method using HLA alleles to control for LD.
  • Employed a Bayesian variable selection algorithm (SuSiE) for LD control.
  • Performed Bayesian regression on posterior inclusion probabilities to identify colocalisation.

Main Results:

  • Simulations confirmed the method's accuracy in identifying truly colocalising genes.
  • Validated the method in positive control scenarios, demonstrating colocalisation between hepatitis B and liver disease (HLA-DPB1), and Epstein-Barr virus and multiple sclerosis (HLA-DRB1, HLA-DQB1).
  • A large-scale scan revealed novel, biologically plausible associations, including cytomegalovirus and ulcerative colitis.

Conclusions:

  • HLA-colocalisation is the first accurate genetic colocalisation method for the complex HLA locus.
  • The method facilitates genetic causal inference at the HLA locus, advancing understanding of HLA-associated diseases.
  • This approach has the potential to identify new therapeutic targets for HLA-related conditions.