Method for identification of condition-associated public antigen receptor sequences

TL;DR

This paper introduces a statistical method for identifying disease-associated immune receptor sequences from small patient cohorts without needing control groups, successfully detecting known disease-responsive receptors.

Contribution

A novel statistical framework that enables disease association analysis of immune receptor sequences from small cohorts without control data.

Findings

Successfully identified Cytomegalovirus-responsive receptors

Detected type 1 diabetes-associated receptors

Operates effectively with small patient cohorts

Abstract

Diverse repertoires of hypervariable immunoglobulin receptors (TCR and BCR) recognize antigens in the adaptive immune system. The development of immunoglobulin receptor repertoire sequencing methods makes it possible to perform repertoire-wide disease association studies of antigen receptor sequences. We developed a statistical framework for associating receptors to disease from only a small cohort of patients, with no need for a control cohort. Our method successfully identifies previously validated Cytomegalovirus and type 1 diabetes responsive receptors.