Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.

Center of Life Sciences Skoltech Moscow Russia

Laboratoire de physique statistique CNRS Sorbonne Université Université Paris Diderot and École normale supérieure Paris France

Laboratoire de physique théorique CNRS Sorbonne Université Université Paris Diderot and École normale supérieure Paris France

Masaryk University Central European Institute of Technology Brno Czech Republic

Moscow State University Moscow Russia

Pirogov Russian National Research Medical University Moscow Russia

Privolzhsky Research Medical University Nizhny Novgorod Russia

Shemyakin Ovchinnikov Institute of Bioorganic Chemistry Moscow Russia

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Longitudinal high-throughput TCR repertoire profiling reveals the dynamics of T-cell memory formation after mild COVID-19 infection

Identification of Disease-associated Traits and Clonotypes in the T Cell Receptor Repertoire of Monozygotic Twins Affected by Inflammatory Bowel Diseases

Measuring Intratumoral Heterogeneity of Immune Repertoires