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Communications Biology
Article . 2024 . Peer-reviewed
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PubMed Central
Other literature type . 2024
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Communications Biology
Article . 2024
Data sources: DOAJ
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Interpretable GWAS by linking clinical phenotypes to quantifiable immune repertoire components

Authors: Yuhao Tan; Lida Wang; Hongyi Zhang; Mingyao Pan; Dajiang J. Liu; Xiaowei Zhan; Bo Li;

Interpretable GWAS by linking clinical phenotypes to quantifiable immune repertoire components

Abstract

AbstractBridging the gap between genotype and phenotype in GWAS studies is challenging. A multitude of genetic variants have been associated with immune-related diseases, including cancer, yet the interpretability of most variants remains low. Here, we investigate the quantitative components in the T cell receptor (TCR) repertoire, the frequency of clusters of TCR sequences predicted to have common antigen specificity, to interpret the genetic associations of diverse human diseases. We first developed a statistical model to predict the TCR components using variants in the TRB and HLA loci. Applying this model to over 300,000 individuals in the UK Biobank data, we identified 2309 associations between TCR abundances and various immune diseases. TCR clusters predicted to be pathogenic for autoimmune diseases were significantly enriched for predicted autoantigen-specificity. Moreover, four TCR clusters were associated with better outcomes in distinct cancers, where conventional GWAS cannot identify any significant locus. Collectively, our results highlight the integral role of adaptive immune responses in explaining the associations between genotype and phenotype.

Keywords

Phenotype, Genotype, QH301-705.5, Neoplasms, Receptors, Antigen, T-Cell, Humans, Genetic Predisposition to Disease, Biology (General), Article, Genome-Wide Association Study, Autoimmune Diseases

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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