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Immune cell repertoire9/12/2023 ![]() The dashed lines represents the theoretical upper bound for heterologous repertoires (see Methods) for both and ( γ = 12). Green dots represent samples extracted from pairs of identical twins. C) Expected value of and for different pairs of samples, sampled from the same individual (in blue) or different ones (yellow). The dashed vertical line represents the threshold value. B) Schematic representation of the distribution of the or scores for multiple pairs of samples extracted from the same individual (in the autologous scenario) or the same pair of individuals (heterologous). In both scenarios, sequences can be shared between the two samples, but their quantity and quality vary. The “Immprint” classifier analyzes this immune fingerprint to decide whether two samples were sampled from the same individual.Ī) The two samples A and B can either originate from the same individual (autologous) or two different individuals (heterologous). In this report, we describe how, from small quantities of blood (blood spot or heel prick), one can extract enough information to uniquely identify an individual, providing an immune fingerprint. The immune T-cell repertoire, defined as the set of TCR expressed in an individual, has been hailed a faithful, personalized medical record, and repertoire sequencing (RepSeq) as a potential tool of choice in personalized medicine. However, as we will show, B- and T-cell receptor (BCR and TCR) genes are an exception to this rule.īCR and TCR are randomly generated through somatic recombination, and the fate of each B- or T-cell clone depends on the environment and immune history. Sequencing experiments that focus on a limited number of expressed genes should be less prone to these concerns. The privacy risks brought by these pseudonymized genomes have been highlighted by multiple studies, and the approach is now routinely used by law enforcement. Genome sequences cannot be anonymized: a genetic fingerprint is in itself enough to fully identify an individual, with the rare exception of monozygotic twins. However, progress comes with privacy concerns. These high-throughput and low-cost sequencing technologies hold the potential of tailored treatment for each individual. Personalized medicine is a frequent promise of next-generation sequencing. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. are supported by RSF-20-15-00351, Russian Science Foundation. dataset can be extracted from the SRA under accession number PRJNA316572.įunding: The study was supported by the European Research Council COG 724208 (AMW). ![]() dataset can also be found on the SRA, under the accession number PRJNA406949 and lastly the Britanova et al. dataset can be found on the Sequence Read Archive (SRA: ), under the accession number PRJNA493983 the Briney et al. dataset is also available from ImmuneAccess, with DOI 10.21417/B7J01X the Pogorely et al. dataset is available from ImmuneAccess ( ) with DOI 10.21417/B7001Z. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the paper and its Supporting information files except for the sequence data: the Emerson et al. Received: JAccepted: DecemPublished: January 4, 2021Ĭopyright: © 2021 Dupic et al. These results emphasize the private and personal nature of repertoire data.Ĭitation: Dupic T, Bensouda Koraichi M, Minervina AA, Pogorelyy MV, Mora T, Walczak AM (2021) Immune fingerprinting through repertoire similarity. We verified through longitudinal datasets that the method is robust to acute infections and that the immune fingerprint is stable for at least three years. Using published T-cell receptor repertoires and statistical modeling, we tested its ability to identify individuals with great accuracy, including identical twins, by computing false positive and false negative rates < 10 −6 from samples composed of 10,000 T-cells. We present “Immprint,” a classifier using an information-theoretic measure of repertoire similarity to distinguish pairs of repertoire samples coming from the same versus different individuals. Here, we show that individuals can be uniquely identified from repertoires of just a few thousands lymphocytes. However, the question of how personal that information is and how it can be used to identify individuals has not been explored. Immune repertoires provide a unique fingerprint reflecting the immune history of individuals, with potential applications in precision medicine.
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