Immune fingerprinting through repertoire similarity.

Immune repertoires provide a unique fingerprint reflecting the immune history of individuals, with potential applications in precision medicine. However, the question of how personal that information is and how it can be used to identify individuals has not been explored. Here, we show that individuals can be uniquely identified from repertoires of just a few thousands lymphocytes. 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. 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 verified through longitudinal datasets that the method is robust to acute infections and that the immune fingerprint is stable for at least three years. These results emphasize the private and personal nature of repertoire data. Author summary: Immune repertoires are a trove of personal information: unique to each individual, they are also windows into their past and future health. Thanks to their potential for personalized medicine and progress of sequencing technologies, these repertoires are now routinely sequenced. As a consequence they raise the question of identifiability of samples. In this paper, we estimate the quantity of immune cells needed to associate two samples from the same individual: as little as a finger prick worth of blood can serve as an immune fingerprint that can distinguish even identical twins, without giving away genetic information about non-consenting relatives. We show that this fingerprint is stable through time, and is not erased during infections or vaccinations. [ABSTRACT FROM AUTHOR]