Mon Sep 16 14:00:00 UTC 2024: ## New Imputation Models Improve Understanding of MHC Gene Variation in Disease
**Helsinki, Finland** – Researchers at the Finnish Red Cross Blood Service have developed new imputation models that accurately predict alleles of non-classical HLA and MHC Class I Chain-Related (MIC) genes, furthering our understanding of the complex interplay between these genes and disease risk. The study, published in *PLOS Computational Biology*, provides a powerful tool for exploring genetic associations in large population cohorts and sheds light on the role of MHC variation in disease mechanisms.
The human Major Histocompatibility Complex (MHC) region, located on chromosome 6, is known to significantly influence disease risk, particularly in autoimmune conditions. While existing imputation tools primarily focus on classical HLA genes, the new models extend to non-classical HLA genes (HLA-E, HLA-F, and HLA-G) and MIC genes (MICA and MICB), which play crucial roles in both innate and adaptive immunity.
“These genes have been linked to autoimmune diseases, infections, and even cancer susceptibility, but their specific roles in disease etiology have been difficult to pinpoint,” explained Dr. Silja Tammi, lead author of the study. “Our new imputation models offer a powerful tool to facilitate association studies in large populations and help us understand the complex genetic mechanisms involved.”
The models were trained on a combination of population-specific Finnish and multi-population 1000 Genomes data, achieving an average accuracy of 99.3% in predicting alleles for MICA, MICB, HLA-E, HLA-F, and HLA-G. The researchers also adapted the models for use with two widely used genome SNP arrays, the Infinium Global Screening Array and the Axiom Precision Medicine Research Array, achieving accuracies above 97% in all genes and populations.
“This means that researchers can utilize readily available data to explore genetic MHC associations in more detail,” said Dr. Tammi. “This work provides a significant step forward in our understanding of the complex role of MHC variation in disease and opens doors for further research into personalized medicine and immune-related therapies.”
The imputation models are publicly available on GitHub, allowing researchers to readily apply them to their own genotype data. This accessibility empowers researchers worldwide to delve deeper into MHC associations and contribute to a more comprehensive understanding of immune-related disease mechanisms.
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