Thymic selection of the T cell receptor repertoire is biased toward autoimmunity in females

Several studies have highlighted a sex imbalance in diseases involving the immune system. This is particularly evident in the case of autoimmune diseases (AIDs), where 80% of affected individuals are women, and the severity of the condition varies between the sexes (Libert et al., 2010; Golden and Voskuhl, 2017; Sokka et al., 2009). In addition, men are more severely affected by infectious diseases such as COVID-19 and tuberculosis (Li et al., 2020; Hertz and Schneider, 2019). The response to preventive immunotherapies such as vaccination, and to curative treatments, like immune checkpoint inhibitors or anti-TNF alpha, is also sex dependent (Klein and Morgan, 2020). These observations indicate the presence of intrinsic biological differences in immune responses between males and females.

A variety of factors have been identified that could help explain the observed sex-based differences. Among these, sex hormones have been shown to influence immune responses by acting on immune cells that express specific receptors to these hormones (Lee and Chang, 2003; Chen et al., 2022; Scarpin et al., 2009). Sex hormones could directly influence the adaptive immune response at the level of thymocyte differentiation and selection by acting on the expression of Autoimmune Regulator (AIRE) in thymic epithelial cells. AIRE is responsible for the thymic expression of otherwise tissue-specific antigens, contributing to both the negative selection of effector cells and the positive selection of Tregs that recognize such antigens (Klein et al., 2014). Research has shown that testosterone increases AIRE expression in medullary thymic epithelial cells, whereas estradiol decreases it (Zhu et al., 2016; Dragin et al., 2016). Furthermore, a recent study has shown that the transcriptomic profiles of these specialized antigen-presenting cells in the thymus differ between males and females (Stankiewicz et al., 2025). This suggests that there may be differences in the selection of the T cell receptor (TCR) repertoire between males and females.

Despite these findings, there is still limited knowledge about potential differences in the TCR repertoire between the sexes. The generation of the TCR is a key process in T-cell development that takes place in the thymus. The TCR consists of two chains, alpha (TRA) and beta (TRB), each of which results from a random genetic rearrangement involving the V (variable), D (diversity) [for the TRB], and J (joining) genes. The combination of these gene segments is accompanied by insertions and deletions, creating a highly diverse region, the Complementarity Determining Region 3 (CDR3; Murugan et al., 2012). It is this region of the TCR that predominantly interacts with the peptide, a critical interaction for antigen recognition and subsequent T cell activation. The ability to specifically recognize diverse antigens via the CDR3 is central to the efficiency and specificity of the adaptive immune response.

TCRs are randomly generated, which means that while some may be useful, others may be harmful by recognizing self-antigens and causing autoimmunity. The current understanding is that during thymocyte development, selection is based on the avidity of their TCRs for antigens presented by cortical and medullary thymic epithelial cells. Thymocytes expressing TCRs with insufficient avidity fail to receive survival signals and undergo death by neglect during positive selection, whereas those with excessive avidity are actively eliminated via negative selection to ensure self-tolerance. In contrast, thymocytes with intermediate avidity are positively selected and mature into single-positive (SP) cells, either CD4 +or CD8+. Thymocytes with the highest of these intermediate affinities develop in Tregs. Given AIRE’s pivotal function in these processes, sex differences in AIRE expression may significantly influence thymic selection.

The TCR repertoire of female and male peripheral T cells has shown that their diversity, particularly that of the TRB repertoire, is influenced not only by the age of the individuals but also by their sex (Yoshida et al., 2017; Trofimov et al., 2022; Mika et al., 2023; Gong et al., 2021). However, another study showed no association between the sex of individuals and the diversity of their TCR repertoire (Qi et al., 2014). Nevertheless, the study of peripheral blood TCRs reflects that of an immune system that has undergone multiple immune responses. For example, observed differences between males and females in their responses to self-antigens associated with autoimmunity could indicate either the cause (the TCRs drive the disease) or the consequence (the TCRs are expanded because of the disease).

To assess whether there are significant differences in the generation and thymic selection of the TCR repertoire between males and females, we therefore focused on analyzing the TCR repertoires of thymocytes. These cells represent the latest stage in T cell development and have not yet been involved in immune responses. Their repertoires thus represent the mechanisms of TCR generation for the analysis of CD4/CD8 double-positive (DP) cells and of TCR selection for CD4 and CD8 SP T cells. We generated a unique data set comprising the sequences of the TRA and TRB chains of DP cells, CD8 and CD4 SP effector cells, and CD4 SP Tregs from organ donors, both infants and adults. The analysis of TRA and TRB repertoires using state-of-the-art strategies revealed no sex differences in repertoire generation (DP cell repertoire), but an enrichment in females for CD8 SP T cells bearing CDR3 associated with specificities related to autoimmunity.

We analyzed thymic TCRαβ repertoires from 22 human organ donors (11 females, 11 males, aged between 73 days and 64 years; Figure 1, Figure 1—figure supplement 1). For each donor, CD3 +CD4+CD8+ DP, CD3 +CD4 CD8+CD8 SP, and CD3 +CD4+CD8 CD4 SP thymocytes were sorted by flow cytometry. In 16 donors, CD4 SP cells were further subdivided into CD25- conventional CD4 Teff and CD25 +CD4 Treg subsets, whereas in the remaining six donors, total CD4 SP cells were analyzed as Teff-enriched populations. This resulted in 20 DP, 21 CD8 SP, 22 CD4 Teff SP, and 14 CD4 Treg SP samples (Figure 1, Figure 1—figure supplement 1). Bulk TCR sequencing was then performed on each cell subset, with the aim of characterizing the TRA and TRB repertoires. Rank–frequency plots of clonotype abundances displayed comparable heavy-tailed distributions across donors, without any obvious systematic differences between males and females (Figure 1—figure supplement 2).

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Minimal sex-based differences in TCR V and J gene usage across thymic cell subsets

The first level of diversity in generating TCRs is the usage of V and J genes (Davis and Bjorkman, 1988). We analyzed the usage of TRA and TRB V and J genes and their combinations in each thymocyte population (Figure 1).

Males and females had a relatively similar V gene usage, as evidenced by the lack of a clear separation in the Principal Component Analysis (PCA), for both TRA and TRB, and across all cell subtypes studied (Figure 2A). However, we observed some individual differences in V and J gene usage between males and females, with some being specific to certain cell subtypes (Figure 2—figure supplements 1–4), and others observed across multiple cell subtypes (Figure 2—figure supplements 1–4). For example, TRBV6-5 was found to be more highly expressed in females compared to males in DP cells (Figure 2—figure supplement 1C) and CD8 SP cells (Figure 2—figure supplement 2C).

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In the following step, we compared the usage of TRAV-TRAJ and TRBV-TRBJ gene combinations across all individuals using the Jensen-Shannon Divergence (JSD) score (Figure 2B). The hierarchical clustering showed no clear separation between male and female individuals for any of the chain or cell subtype, indicating no significant differences in the gene combination usage between males and females (Figure 2B). A similar observation was made when directly analyzing the frequency of these VJ gene combinations (Figure 2—figure supplements 1E, F–4E, F).

Comparable TCR repertoire diversity between males and females

A high diversity of the TCR repertoire is essential for generating a broad potential reactivity against a variety of antigens. We thus compared the TCR repertoire diversity between males and females. To achieve this objective, we analyzed Rényi diversity curves (from zero to infinite $\alpha$ parameters) that measure various aspects of TCR repertoire diversity. At different $\alpha$ values, the Rényi index places more or less weight on the contribution of the most frequent clonotypes. Higher $\alpha$ values highlight the most prevalent clonotypes, thereby revealing the effect of expanded clones on overall diversity.

Rényi curves showed comparable diversities between sexes in DP and CD4 Teff cells, for both TRA and TRB, and a difference in CD8 and CD4 Treg cells (Figure 3—figure supplement 1). In CD8 cells, the curves begin to diverge at low $\alpha$ values (Figure 3—figure supplement 1), with an earlier inflection in males, indicating a less balanced distribution of TCR clones. This suggests that in males, fewer clones dominate the repertoire at lower diversity thresholds compared to females. In Tregs, while the inflection point is similar, the difference seems to be characterized by higher diversity and richness in females compared to males (Figure 3—figure supplement 1). However, no significant differences were observed for the Shannon diversity index ($\alpha$=1), the Simpson index ($\alpha$=2), and the Berger-Parker index ($\alpha$=infinite), for both chains and all cell subtypes (Figure 3). These results indicate that the diversity of thymic TCR repertoire is similar between males and females.

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Comparable CDR3aa length distribution in male and female TCR repertoires

Most of the repertoire diversity is generated by the random addition of nucleotides within the VDJ junctions, resulting in the hypervariable CDR3 region that interacts with the peptide-MHC complex and is mostly responsible for the TCR specificity. The CDR3 length has been shown to directly influence the TCR’s ability to interact with the peptide (Wang et al., 1998). We thus studied the distribution of CDR3 aa (CDR3aa) sequence lengths between males and females to identify potential TCR generation and/or selection biases (Figure 1).

Our results showed that males and females have a comparable distribution of CDR3aa lengths for both TRA (Figure 4—figure supplement 1) and TRB (Figure 4A). CDR3aa sequences in TRA were shorter than those in TRB, as previously described in peripheral blood T cells (Yu et al., 2019; Carter et al., 2019). Although there were subtle differences in certain CDR3aa lengths between males and females, these variations were minimal, involving sequences that represent less than 2% of the total TCR repertoire (Figure 4A, Figure 4—figure supplement 1). Altogether, the overall distribution of CDR3aa length is comparable between males and females.

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Slight sex-based variations in thymic TCR generation probability distribution

Another approach to evaluating biases in the generation and selection of the TCR repertoire is to compare the probability of generation (Pgen) of CDR3 nucleotide sequences (Figure 1). Pgen represents the likelihood of a sequence being produced, according to models of V(D)J recombination (Murugan et al., 2012; Elhanati et al., 2014). For DP and CD8 cells only and for each TCR chain, a sequence generation model was created using 100,000 non-productive nucleotide sequences. Using this model, the Pgen of all productive TCR sequences that make up each repertoire was calculated.

When comparing the distribution of Pgen between males and females, we observe a very slight difference of distribution, characterized by a nearly null Kolmogorov-Smirnov score (D_K-S <0.05; Figure 5). This difference is more pronounced in the TRB compared to the TRA chain (Figure 5). As this minor discrepancy might be indicative of variations among individuals irrespective of their sex, we have generated 20,000 permuted mixed-sex groups utilizing our dataset. Our findings revealed a significant distribution difference of Pgen sequences between these mixed groups population (DP – TRA: D_K-S=0.0183 ± 0.0145 ($\mu \pm sd$), DP – TRB: D_K-S=0.0190 ± 0.0161, CD8 – TRA: D_K-S=0.0227 ± 0.0153, and CD8 – TRB: D_K-S=0.0259 ± 0.0140). However, the observed difference in the Pgen distribution between males and females is higher than that between the mixed groups in the DP TRB.

Figure 5

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Similar network structure of thymic TCR repertoires in males and females

Next, we evaluated whether thymic selection in males and females is directed towards similar or distinct sequences. For each TCR repertoire, CDR3aa sequences are connected if they differ by one aa, that is have a Levenshtein distance of = 1 (Figure 1). Such linked sequences have a high probability of sharing the same specificities (Meysman et al., 2019). For each TCR chain and thymic T cell subset, CDR3aa repertoires were downsampled to the size of the smallest sample to enable comparisons across samples. This process was repeated 100 times. The downsampling sizes used for each chain and subset are provided in Supplementary file 1. The shapes of the network are depicted in Figure 6A.

Figure 6

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To analyze these clusterings with greater precision, we used various metrics. When comparing the number of clustered sequences in each individual network between males and females, no significant differences were observed for any cell type in either chain (Figure 6B). Similarly, the degree of sequence similarity, as indicated by the density of edges between sequences within an individual’s TCR repertoire, was comparable between males and females (Figure 6C). These findings indicate that there are no significant sex-specific differences in the similarity of CDR3aa sequences, suggesting that males and females produce CDR3aa sequences with the same degree of variability within their TCR repertoires.

Absence of sex-specific CDR3aa motifs in thymic TCR repertoires of males and females

We then sought to determine whether we could detect CDR3aa sequence motifs that were more prevalent in one group compared to the other, in order to evaluate whether the selection of CDR3aa was biased towards particular sequences differently between males and females (Figure 1). To identify sequences with shared characteristics that might indicate a probable common specificity among individuals of the same group, the analysis focused exclusively on CDR3aa sequences of the TRB, as this region has been shown to have a greater influence on TCR specificity (Springer et al., 2021; Korpela et al., 2023). Local motifs were defined using Gliph2 (Huang et al., 2020), which are sequences of three to five aa, as well as global motifs, which are sequences of more than three aa where, at one position, an aa can be substituted by another aa if it has a positive BLOSUM62 score (Henikoff and Henikoff, 1992). Importantly, only motifs containing public CDR3aa sequences shared by at least two individuals were retained, thereby excluding private or individual-specific sequences from the analysis.

We identified several hundred motifs that were differentially expressed between males and females for each cell subpopulation. A greater number of motifs were specific to females, ranging from 426 motifs for DP to 278 motifs for CD4 Tregs, compared to males, ranging from 328 motifs for CD4 Teffs to 34 motifs for CD4 Tregs (Figure 7A). The identified motifs are mainly local motifs and largely confined to their respective sex group, indicating that motifs identified in females are predominantly found in females, and vice versa (Figure 7—figure supplements 1–4).

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As illustrated in Figure 7B, we observed minimal motif overlap between different cell subtypes. Only two female-associated motifs overlapped: one between CD4 Teffs and CD4 Tregs, and another between CD4 Teffs and CD8 cells (Figure 7B). In contrast, no overlap was found between male-associated motifs (Figure 7B). Furthermore, it was observed that there was an overlap between one motif associated with female CD8 cells and a motif associated with male CD4 Teff cells (Figure 7B).

We then proceeded to evaluate the usage of the differentially expressed motifs in external datasets. There is no publicly available thymic TCR dataset that reports repertoires according to cell subsets. We thus tested these motifs on TCRs from pediatric bulk thymocytes, which contain TCR data from children aged between two and eight months, with a male-to-female ratio of 5:3 (Heikkilä et al., 2021; Mattila et al., 2023). We calculated the usage of these differentially expressed motifs in each sample of this dataset. We were unable to separate individuals by sex using these motif usages (Figure 7C).

We then evaluated these motifs using a peripheral blood TCR dataset from healthy individuals, where CD8, CD4 Teff, and CD4 Treg cells had been sorted. The usage of these motifs could not distinguish males from females across all cell subsets (Figure 7D, Figure 7—figure supplement 5).

Sex-biased enrichment of TCRs associated with autoimmune diseases and bacterial antigens

We sought to identify the usage of TCRs with known specificity as represented in the IEDB, Mc-PAS, and VDJdb public databases (Vita et al., 2019; Tickotsky et al., 2017; Shugay et al., 2018). We compiled the TCRs from these three databases, retaining only those with high sequence reliability scores (see Materials and Methods). We focused on TRB sequences exclusively, due to their greater representation in the databases (Springer et al., 2021; Rosati et al., 2017). We identified 55,368 unique TRB CDR3aa sequences with high reliability and specificity assignment scores for at least one specificity.

We classified the TCR specificities based on the antigen they recognize: viral or bacterial peptides, or human peptides overexpressed in cancers, AIDs, or neither of these diseases (Figure 8—figure supplement 1A). We sought to identify the TRB CDR3aa sequences in our thymocyte dataset. Depending on the individuals and cell subtypes, they represented between 0.82% and 3.58% of the TRB repertoires.

We observed that unique TRB CDR3aa sequences specific to self-antigens not associated with pathologies and those associated with cancers are proportionally more represented in our thymic TCR dataset than in the pooled reference database, in both females and males (Figure 8—figure supplement 1B). This pattern was consistent across all cell subtypes (Figure 8—figure supplement 1B). These comparisons to the reference database are presented for descriptive purposes only, as differences between an experimental thymic repertoire and a curated database are expected given the structure of the reference resource. We then compared the distribution of these CDR3aa between males and females for each cell subtype. Strikingly, in the TCR repertoires with one specificity only, we observed a significantly higher proportion of unique TRB CDR3aa sequences associated with AIDs in female CD8 SP cells compared to male CD8 SP cells (Figure 8A). Furthermore, in the specific TCR repertoires only, there was a trend towards a higher proportion of thymic sequences with specificity associated with bacterial compounds in female CD8 SP cells compared to males, and an opposite trend was observed for CD4 Tregs SP (Figure 8A). These differences observed in CD8 SP cells persisted when examining the usage of these sequences (i.e. cumulative usage frequency), with significantly higher usage of sequences with specificity associated with bacterial compounds and those associated with AIDs in females compared to males (Figure 8B). Of particular note are the donor-resolved analyses (Figure 8—figure supplements 1B and 2), in which each individual is represented separately. These confirm that these patterns are not driven by a single donor.

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Donor age had no significant effect on the sex-biased enrichment of self- and bacteria-specific TRB CDR3 sequences in CD8 SP and CD4 Treg SP cells (p ≥ 0.52), indicating that the observed differences are age-independent (Figure 8—figure supplement 3). In addition, we investigated for the presence of polyspecific TCRs, which are capable of recognizing multiple antigens from different organisms (Wooldridge et al., 2012; Hadrup et al., 2009; Quiniou et al., 2023). These sequences were found to be enriched across all cell subtypes, in comparison to their representation in the reference database (Figure 8—figure supplement 1C). However, no significant differences were observed in the proportion or usage of these polyspecific sequences between males and females. Interestingly, an inverse usage trend was observed between CD8 and CD4 Treg SP cells: females exhibited higher usage of these sequences in the CD8 SP repertoire but a lower usage in the CD4 Treg SP repertoire compared to males (Figure 8C and D).

In conclusion, our analysis of TCR specificity has identified sex-specific differences in the thymic selection of CD8 effector T cells associated with autoimmune and bacterial antigens that are overrepresented in females versus males.

It is noteworthy that there is a paucity of research on potential differences in the TCR repertoire between the sexes, despite the much higher prevalence of AIDs in females, a topic that remains to be fully elucidated. To explore the hypothesis that the generation and/or the selection of the TCR repertoires may be different between sexes requires, it is necessary to study the TCR repertoire where they are formed and selected, in the thymus. We thus generated a unique and valuable dataset comprising thymic samples collected from deceased organ donors of various ages, and young children who have undergone cardiac surgery. Firstly, we separated the various thymocyte populations in order to study both TCR repertoire generation at the level of DP cells, and repertoire selection at the level of CD8, CD4 Teff, and Treg SP cells. We performed bulk sequencing of the TCRs from these cells, as this is the only method that yet generates enough sequences for sensitive comparison at this time. Single-cell sequencing is an analyzing technique that is limited in its scope. It is only capable of analyzing a few thousand cells and would not have enabled the analyses that can be performed with hundreds of thousands of cells.

All raw sequencing data generated in this study are publicly available on NCBI under the BioProject accession PRJNA1379632 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1379632/).

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Author details

1. Hélène Vantomme

   1. Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France
   2. Biotherapy (CIC-BTi) and Inflammation-Immunolopathology-Biotherapy Department (i2B), Assistance Publique -Hôpitaux de Paris (AP-HP), Paris, France

   Contribution

   Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0009-0008-8759-1208

2. Valentin Quiniou

   Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

   Contribution

   Conceptualization, Data curation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0792-341X

3. Leslie Adda

   Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

   Contribution

   Data curation, Methodology, Writing – review and editing

   Contributed equally with

   Charline Jouannet and Vanessa Mhanna

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1395-6864

4. Charline Jouannet

   Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

   Contribution

   Methodology

   Contributed equally with

   Leslie Adda and Vanessa Mhanna

   Competing interests

   No competing interests declared

5. Vanessa Mhanna

   Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

   Contribution

   Methodology, Writing – review and editing

   Contributed equally with

   Leslie Adda and Charline Jouannet

   Competing interests

   No competing interests declared

6. Celine Albalaa

   Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

   Contribution

   Methodology, Writing – review and editing

   Contributed equally with

   Pierre Barennes, Nicolas Coatnoan, Vimala Diderot, Johanna Dubois, Gwladys Fourcade, Kenz Le Gouge, Otriv Frédéric Nguekap Tchoumba, Martin Pezous and Paul Stys

   Competing interests

   No competing interests declared

7. Pierre Barennes

   Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

   Contribution

   Investigation

   Contributed equally with

   Celine Albalaa, Nicolas Coatnoan, Vimala Diderot, Johanna Dubois, Gwladys Fourcade, Kenz Le Gouge, Otriv Frédéric Nguekap Tchoumba, Martin Pezous and Paul Stys

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3017-0719

8. Nicolas Coatnoan

   1. Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France
   2. Biotherapy (CIC-BTi) and Inflammation-Immunolopathology-Biotherapy Department (i2B), Assistance Publique -Hôpitaux de Paris (AP-HP), Paris, France

   Contribution

   Investigation

   Contributed equally with

   Celine Albalaa, Pierre Barennes, Vimala Diderot, Johanna Dubois, Gwladys Fourcade, Kenz Le Gouge, Otriv Frédéric Nguekap Tchoumba, Martin Pezous and Paul Stys

   Competing interests

   No competing interests declared

9. Vimala Diderot

   1. Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France
   2. Biotherapy (CIC-BTi) and Inflammation-Immunolopathology-Biotherapy Department (i2B), Assistance Publique -Hôpitaux de Paris (AP-HP), Paris, France

   Contribution

   Investigation

   Contributed equally with

   Celine Albalaa, Pierre Barennes, Nicolas Coatnoan, Johanna Dubois, Gwladys Fourcade, Kenz Le Gouge, Otriv Frédéric Nguekap Tchoumba, Martin Pezous and Paul Stys

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0009-0003-1494-7502

10. Johanna Dubois

    Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

    Contribution

    Investigation, Writing – review and editing

    Contributed equally with

    Celine Albalaa, Pierre Barennes, Nicolas Coatnoan, Vimala Diderot, Gwladys Fourcade, Kenz Le Gouge, Otriv Frédéric Nguekap Tchoumba, Martin Pezous and Paul Stys

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0009-0009-0440-150X

11. Gwladys Fourcade

    Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

    Contribution

    Investigation

    Contributed equally with

    Celine Albalaa, Pierre Barennes, Nicolas Coatnoan, Vimala Diderot, Johanna Dubois, Kenz Le Gouge, Otriv Frédéric Nguekap Tchoumba, Martin Pezous and Paul Stys

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0009-0009-1167-9243

12. Kenz Le Gouge

    Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

    Contribution

    Data curation, Investigation, Methodology

    Contributed equally with

    Celine Albalaa, Pierre Barennes, Nicolas Coatnoan, Vimala Diderot, Johanna Dubois, Gwladys Fourcade, Otriv Frédéric Nguekap Tchoumba, Martin Pezous and Paul Stys

    Competing interests

    No competing interests declared

13. Otriv Frédéric Nguekap Tchoumba

    Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

    Contribution

    Methodology

    Contributed equally with

    Celine Albalaa, Pierre Barennes, Nicolas Coatnoan, Vimala Diderot, Johanna Dubois, Gwladys Fourcade, Kenz Le Gouge, Martin Pezous and Paul Stys

    Competing interests

    No competing interests declared

14. Martin Pezous

    Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

    Contribution

    Methodology

    Contributed equally with

    Celine Albalaa, Pierre Barennes, Nicolas Coatnoan, Vimala Diderot, Johanna Dubois, Gwladys Fourcade, Kenz Le Gouge, Otriv Frédéric Nguekap Tchoumba and Paul Stys

    Competing interests

    No competing interests declared

15. Paul Stys

    Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

    Contribution

    Data curation, Methodology

    Contributed equally with

    Celine Albalaa, Pierre Barennes, Nicolas Coatnoan, Vimala Diderot, Johanna Dubois, Gwladys Fourcade, Kenz Le Gouge, Otriv Frédéric Nguekap Tchoumba and Martin Pezous

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-4152-2887

16. Adrien Six

    Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France

    Contribution

    Supervision, Methodology

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-5898-555X

17. Encarnita Mariotti-Ferrandiz

    1. Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France
    2. Institut Universitaire de France, Paris, France

    Contribution

    Supervision, Funding acquisition, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

    Additional information

    co-senior authors

    "This ORCID iD identifies the author of this article:" 0000-0002-8770-0186

18. David Klatzmann

    1. Immunology, Immunopathology, Immunotherapy i3 Lab, INSERM UMRS-959, Sorbonne Université, Paris, France
    2. Biotherapy (CIC-BTi) and Inflammation-Immunolopathology-Biotherapy Department (i2B), Assistance Publique -Hôpitaux de Paris (AP-HP), Paris, France

    Contribution

    Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Project administration, Writing – review and editing

    For correspondence

    david.klatzmann@sorbonne-universite.fr

    Competing interests

    No competing interests declared

    Additional information

    co-senior authors

    "This ORCID iD identifies the author of this article:" 0000-0002-0054-3422

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